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3 |
4 | # statcanR
5 |
6 |
7 |
8 | [](https://app.travis-ci.com/github/warint/statcanR)
10 | [](https://ci.appveyor.com/project/warint/statcanR)
12 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
14 | [](https://CRAN.R-project.org/package=statcanR)
16 | [](https://cran.r-project.org/package=statcanR)
17 |
18 |
19 |
20 | # Overview
21 |
22 | Easily connect to Statistics Canada’s Web Data Service with R. Open
23 | economic data (formerly known as CANSIM tables, now identified by
24 | Product IDs (PID)) are accessible as a data frame, directly in the
25 | user’s R environment.
26 |
27 | ## Shiny App : statcanR ExploR
28 |
29 | 
30 |
31 | For people less comfortable with R and to allow more people to have
32 | access to our package, we have also developed a Shiny
33 | application.Through the same logic present in our package, researchers
34 | can retrieve data from Statistics Canada.
35 |
36 | statcanR EploR is available [\[here\]](https://warin.ca/shiny/statcanr/)
37 |
38 | ## Installation
39 |
40 | The released version of statcanR package is accessible through CRAN and
41 | devtools.
42 |
43 | ``` r
44 | install.packages("statcanR")
45 |
46 | install.packages("devtools")
47 | devtools::install_github('warint/statcanR')
48 | ```
49 |
50 | ## Example
51 |
52 | This section presents an example of how to use the `statcanR` R package
53 | and its function `statcan_data()` and `statcan_download_data()`.
54 |
55 | The following example is provided to illustrate how to use the
56 | functions. It consists in collecting some descriptive statistics about
57 | the Canadian Labour Force at the federal, provincial and industrial
58 | levels, on a monthly basis.
59 |
60 | With a simple web search ‘statistics canada wages by industry
61 | metropolitan area monthly’, the table number can easily be found on
62 | Statisitcs Canada’s webpage. Here is below a figure that illustrates
63 | this example, such as ‘27-10-0014-01’ for the Federal expenditures on
64 | science and technology, by socio-economic objectives.
65 |
66 | Once the table number is identified, the statcan_data() function is easy
67 | to use in order to collect the data, as following:
68 |
69 | ``` r
70 | library(statcanR)
71 | mydata <- statcan_data("27-10-0014-01","eng")
72 | ```
73 |
74 | For the `statcan_download_data()` function there is no difference on how
75 | to use it, the only difference is that this function allow you to
76 | download the data in a csv file on top of having the data in your
77 | environment.
78 |
79 | ``` r
80 | library(statcanR)
81 | mydata <- statcan_download_data("27-10-0014-01","eng")
82 | ```
83 |
84 | ### Video Tutorial
85 |
86 | Tutorial made by Professor Charles Saunders, Director of Master of
87 | Financial Economics Program at Western University
88 | [biography](https://economics.uwo.ca/people/faculty/saunders.html)
89 |
90 | Thanks!
91 |
92 |
93 |
94 | ### Statistics Canada Open Licence
95 |
96 | This licence is issued on behalf of Her Majesty the Queen in Right of
97 | Canada, as represented by the Minister for Statistics Canada
98 | (“Statistics Canada”) to you (an individual or a legal entity that you
99 | are authorized to represent).
100 |
101 | Statistics Canada may modify this licence at any time, and such
102 | modifications shall be effective immediately upon posting of the
103 | modified licence on the Statistics Canada website. Your use of the
104 | Information will be governed by the terms of the licence in force as of
105 | the date and time you accessed the Information.
106 |
107 | Please refer to the [terms of
108 | licence](https://www.statcan.gc.ca/eng/reference/licence) before using
109 | the Information.
110 |
111 | ##### Acknowledgment of Source according to Statistics Canada Open Licence Agreement
112 |
113 | Statistics Canada has a specific procedure regarding the ackowledgment
114 | of source :
115 |
116 | You shall include and maintain the following notice on all licensed
117 | rights of the Information:
118 |
119 | Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
120 |
121 | Where any Information is contained within a Value-added Product, you
122 | shall include on such Value-added Product the following notice:
123 |
124 | Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.
125 |
126 | ### Cite statcanR
127 |
128 | To cite stantcanR package in your work:
129 |
130 | Warin, T., Romain Le Duc (2019). statcanR: Client for Statistics
131 | Canada’s Open Economic Data. v0.1.0.
132 |
133 | ``` r
134 | @Manual{R-statcanR,
135 | title = {statcanR: Client for Statistics Canada's Open Economic Data},
136 | author = {Thierry Warin and Romain {Le Duc}},
137 | note = {R package version 0.1.0},
138 | url = {https://github.com/warint/statcanR},
139 | year = {2019},
140 | doi = "10.6084/m9.figshare.10544735.v1"
141 | }
142 | ```
143 |
144 | ### Acknowledgments
145 |
146 | The authors would like to thank the Center for Interuniversity Research
147 | and Analysis of Organizations (CIRANO, Montreal) for its support, as
148 | well as Thibault Senegas, Marine Leroi and Martin Paquette. However,
149 | errors and omissions are ours.
150 |
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2 | Function reference • statcanR
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59 | Reference
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63 | All functions
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69 | statcanR
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73 | statcanR download data function
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77 | Searching function for statcanR
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1 | # -----------------------------------------------------------
2 | # CITATION file created with {cffr} R package, v0.4.1
3 | # See also: https://docs.ropensci.org/cffr/
4 | # -----------------------------------------------------------
5 |
6 | cff-version: 1.2.0
7 | message: 'To cite package "statcanR" in publications use:'
8 | type: software
9 | license: MIT
10 | title: 'Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses'
11 | version: 0.2.5
12 | abstract: This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy. Warin (2024) .
13 | authors:
14 | - family-names: Warin
15 | given-names: Thierry
16 | email: thierry.warin@hec.ca
17 | orcid: https://orcid.org/0000-0002-5921-3428
18 | repository: https://CRAN.R-project.org/package=statcanR
19 | repository-code: https://github.com/warint/statcanR/issues/
20 | url: https://github.com/warint/statcanR/
21 | contact:
22 | - family-names: Warin
23 | given-names: Thierry
24 | email: thierry.warin@hec.ca
25 | orcid: https://orcid.org/0000-0002-5921-3428
26 | references:
27 | - type: software
28 | title: knitr
29 | abstract: 'knitr: A General-Purpose Package for Dynamic Report Generation in R'
30 | notes: Suggests
31 | url: https://yihui.org/knitr/
32 | repository: https://CRAN.R-project.org/package=knitr
33 | authors:
34 | - family-names: Xie
35 | given-names: Yihui
36 | email: xie@yihui.name
37 | orcid: https://orcid.org/0000-0003-0645-5666
38 | year: '2023'
39 | - type: software
40 | title: rmarkdown
41 | abstract: 'rmarkdown: Dynamic Documents for R'
42 | notes: Suggests
43 | url: https://pkgs.rstudio.com/rmarkdown/
44 | repository: https://CRAN.R-project.org/package=rmarkdown
45 | authors:
46 | - family-names: Allaire
47 | given-names: JJ
48 | email: jj@rstudio.com
49 | - family-names: Xie
50 | given-names: Yihui
51 | email: xie@yihui.name
52 | orcid: https://orcid.org/0000-0003-0645-5666
53 | - family-names: McPherson
54 | given-names: Jonathan
55 | email: jonathan@rstudio.com
56 | - family-names: Luraschi
57 | given-names: Javier
58 | email: javier@rstudio.com
59 | - family-names: Ushey
60 | given-names: Kevin
61 | email: kevin@rstudio.com
62 | - family-names: Atkins
63 | given-names: Aron
64 | email: aron@rstudio.com
65 | - family-names: Wickham
66 | given-names: Hadley
67 | email: hadley@rstudio.com
68 | - family-names: Cheng
69 | given-names: Joe
70 | email: joe@rstudio.com
71 | - family-names: Chang
72 | given-names: Winston
73 | email: winston@rstudio.com
74 | - family-names: Iannone
75 | given-names: Richard
76 | email: rich@rstudio.com
77 | orcid: https://orcid.org/0000-0003-3925-190X
78 | year: '2023'
79 | - type: software
80 | title: data.table
81 | abstract: 'data.table: Extension of `data.frame`'
82 | notes: Imports
83 | url: https://r-datatable.com
84 | repository: https://CRAN.R-project.org/package=data.table
85 | authors:
86 | - family-names: Dowle
87 | given-names: Matt
88 | email: mattjdowle@gmail.com
89 | - family-names: Srinivasan
90 | given-names: Arun
91 | email: asrini@pm.me
92 | year: '2023'
93 | - type: software
94 | title: qpdf
95 | abstract: 'qpdf: Split, Combine and Compress PDF Files'
96 | notes: Imports
97 | url: https://docs.ropensci.org/qpdf/
98 | repository: https://CRAN.R-project.org/package=qpdf
99 | authors:
100 | - family-names: Ooms
101 | given-names: Jeroen
102 | email: jeroen@berkeley.edu
103 | orcid: https://orcid.org/0000-0002-4035-0289
104 | year: '2023'
105 | - type: software
106 | title: DT
107 | abstract: 'DT: A Wrapper of the JavaScript Library ''DataTables'''
108 | notes: Imports
109 | url: https://github.com/rstudio/DT
110 | repository: https://CRAN.R-project.org/package=DT
111 | authors:
112 | - family-names: Xie
113 | given-names: Yihui
114 | email: xie@yihui.name
115 | - family-names: Cheng
116 | given-names: Joe
117 | - family-names: Tan
118 | given-names: Xianying
119 | year: '2023'
120 | - type: software
121 | title: curl
122 | abstract: 'curl: A Modern and Flexible Web Client for R'
123 | notes: Imports
124 | url: https://curl.se/libcurl/
125 | repository: https://CRAN.R-project.org/package=curl
126 | authors:
127 | - family-names: Ooms
128 | given-names: Jeroen
129 | email: jeroen@berkeley.edu
130 | orcid: https://orcid.org/0000-0002-4035-0289
131 | year: '2023'
132 | - type: software
133 | title: httr
134 | abstract: 'httr: Tools for Working with URLs and HTTP'
135 | notes: Imports
136 | url: https://httr.r-lib.org/
137 | repository: https://CRAN.R-project.org/package=httr
138 | authors:
139 | - family-names: Wickham
140 | given-names: Hadley
141 | email: hadley@rstudio.com
142 | year: '2023'
143 | - type: software
144 | title: readr
145 | abstract: 'readr: Read Rectangular Text Data'
146 | notes: Imports
147 | url: https://readr.tidyverse.org
148 | repository: https://CRAN.R-project.org/package=readr
149 | authors:
150 | - family-names: Wickham
151 | given-names: Hadley
152 | email: hadley@rstudio.com
153 | - family-names: Hester
154 | given-names: Jim
155 | - family-names: Bryan
156 | given-names: Jennifer
157 | email: jenny@rstudio.com
158 | orcid: https://orcid.org/0000-0002-6983-2759
159 | year: '2023'
160 | - type: software
161 | title: tibble
162 | abstract: 'tibble: Simple Data Frames'
163 | notes: Imports
164 | url: https://tibble.tidyverse.org/
165 | repository: https://CRAN.R-project.org/package=tibble
166 | authors:
167 | - family-names: Müller
168 | given-names: Kirill
169 | email: krlmlr+r@mailbox.org
170 | - family-names: Wickham
171 | given-names: Hadley
172 | email: hadley@rstudio.com
173 | year: '2023'
174 |
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2 | MIT License • statcanR
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59 | MIT License
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63 |
64 | Copyright (c) 2020 Thierry Warin ; Romain Le Duc
65 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
66 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
67 | THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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1 | ---
2 | output: github_document
3 | ---
4 |
5 |
6 |
7 | ```{r, include = FALSE}
8 | knitr::opts_chunk$set(
9 | collapse = TRUE,
10 | comment = "#>",
11 | fig.path = "man/figures/README-",
12 | out.width = "100%"
13 | )
14 | ```
15 |
16 | # statcanR
17 |
18 |
19 |
20 |
21 | [](https://app.travis-ci.com/github/warint/statcanR)
22 | [](https://ci.appveyor.com/project/warint/statcanR)
23 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
24 | [](https://CRAN.R-project.org/package=statcanR)
25 | [](https://cran.r-project.org/package=statcanR)
26 |
27 |
28 |
29 | # Overview
30 |
31 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
32 |
33 |
34 | ## Shiny App : statcanR ExploR
35 |
36 |
37 |
38 | For people less comfortable with R and to allow more people to have access to our package, we have also developed a Shiny application.Through the same logic present in our package, researchers can retrieve data from Statistics Canada.
39 |
40 | statcanR EploR is available [[here]]( https://warin.ca/shiny/statcanr/)
41 |
42 | ## Installation
43 |
44 | The released version of statcanR package is accessible through CRAN and devtools.
45 |
46 | ``` r
47 | install.packages("statcanR")
48 |
49 | install.packages("devtools")
50 | devtools::install_github('warint/statcanR')
51 | ```
52 |
53 | ## Example
54 |
55 | This section presents an example of how to use the `statcanR` R package and its function `statcan_data()` and `statcan_download_data()`.
56 |
57 | The following example is provided to illustrate how to use the functions. It consists in collecting some descriptive statistics about the Canadian Labour Force at the federal, provincial and industrial levels, on a monthly basis.
58 |
59 | With a simple web search 'statistics canada wages by industry metropolitan area monthly', the table number can easily be found on Statisitcs Canada's webpage. Here is below a figure that illustrates this example, such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives.
60 |
61 | Once the table number is identified, the statcan_data() function is easy to use in order to collect the data, as following:
62 |
63 | ``` r
64 | library(statcanR)
65 | mydata <- statcan_data("27-10-0014-01","eng")
66 | ```
67 |
68 | For the `statcan_download_data()` function there is no difference on how to use it, the only difference is that this function allow you to download the data in a csv file on top of having the data in your environment.
69 |
70 | ``` r
71 | library(statcanR)
72 | mydata <- statcan_download_data("27-10-0014-01","eng")
73 | ```
74 |
75 | ### Video Tutorial
76 |
77 | Tutorial made by Professor Charles Saunders, Director of Master of Financial
78 | Economics Program at Western University [biography](https://economics.uwo.ca/people/faculty/saunders.html)
79 |
80 | Thanks!
81 |
82 |
83 |
84 |
85 | ### Statistics Canada Open Licence
86 |
87 | This licence is issued on behalf of Her Majesty the Queen in Right of Canada, as represented by the Minister for Statistics Canada ("Statistics Canada") to you (an individual or a legal entity that you are authorized to represent).
88 |
89 | Statistics Canada may modify this licence at any time, and such modifications shall be effective immediately upon posting of the modified licence on the Statistics Canada website. Your use of the Information will be governed by the terms of the licence in force as of the date and time you accessed the Information.
90 |
91 | Please refer to the [terms of licence](https://www.statcan.gc.ca/eng/reference/licence) before using the Information.
92 |
93 |
94 | ##### Acknowledgment of Source according to Statistics Canada Open Licence Agreement
95 |
96 | Statistics Canada has a specific procedure regarding the ackowledgment of source :
97 |
98 | You shall include and maintain the following notice on all licensed rights of the Information:
99 |
100 | Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
101 |
102 | Where any Information is contained within a Value-added Product, you shall include on such Value-added Product the following notice:
103 |
104 | Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.
105 |
106 | ### Cite statcanR
107 |
108 | To cite statcanR package in your work:
109 |
110 | Warin, T. (2024). Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses. Technology Innovations in Statistics Education, 15(1). http://dx.doi.org/10.5070/T5.1868 Retrieved from https://escholarship.org/uc/item/9jr7k5hp
111 |
112 | ``` r
113 | @article{warin_access_2024,
114 | title = {Access {Statistics} {Canada}’s {Open} {Economic} {Data} for {Statistics} and {Data} {Science} {Courses}},
115 | volume = {15},
116 | url = {https://escholarship.org/uc/item/9jr7k5hp},
117 | doi = {10.5070/T5.1868},
118 | abstract = {This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy.},
119 | language = {en},
120 | number = {1},
121 | urldate = {2024-01-17},
122 | journal = {Technology Innovations in Statistics Education},
123 | author = {Warin, Thierry},
124 | month = jan,
125 | year = {2024},
126 | file = {Full Text PDF:/Users/thierrywarin/Zotero/storage/7LNXFPKL/Warin - 2024 - Access Statistics Canada’s Open Economic Data for .pdf:application/pdf},
127 | }
128 | ```
129 |
130 | ### Acknowledgments
131 |
132 | The authors would like to thank the Center for Interuniversity Research and Analysis of Organizations (CIRANO, Montreal) for its support, as well as Thibault Senegas, Marine Leroi and Martin Paquette. However, errors and omissions are ours.
133 |
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/docs/news/index.html:
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1 |
2 | Changelog • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
59 | Changelog
60 | Source: NEWS.md
61 |
62 |
63 |
64 | statcanR 0.2.52023-08-10
65 | - We have corrected statcan_search() function by removing top level code. You can now install statcanR package without an internet connection
66 |
67 |
68 | statcanR 0.2.42023-03-03
69 | - we have added the function statcan_search() to identify economic data tables available on Statistics Canada’s website.
70 |
71 |
72 | statcanR 0.2.32021-12-14
73 | - we have modified the function to get an informative message if the table is not available instead of having an error message.
74 |
75 |
79 |
83 |
84 |
85 |
88 |
89 |
90 |
91 |
92 |
101 |
102 |
103 |
104 |
105 |
106 |
107 |
108 |
109 |
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/docs/reference/statcan_data.html:
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1 |
2 | statcanR — statcan_data • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
63 |
64 |
65 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
66 |
67 |
68 |
69 | statcan_data(tableNumber, lang)
70 |
71 |
72 |
73 | Arguments
74 | - tableNumber
75 | The table number of the Statistics Canada data table
- lang
79 | The language wanted
82 |
83 | Value
84 |
85 |
86 | The output will be a data table representing the data associated with the chosen table number.
87 |
88 |
89 | Details
90 | The
91 | statcan_data() function has 2 arguments to fulfill to get data: tableNumber & lang.
92 |
93 | The tableNumber argument simply refers to the table number of the Statistics Canada data table a user wants to collect,
94 | such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
95 |
96 | To get the table number: https://www150.statcan.gc.ca/n1/en/type/data.
97 | The second argument, lang, refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages.
98 | Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c('fra', 'eng').
99 |
100 |
101 |
102 | Examples
103 | #mydata <- statcan_data('27-10-0014-01', 'eng')
104 |
105 |
106 |
107 |
108 |
109 |
112 |
113 |
114 |
115 |
124 |
125 |
126 |
127 |
128 |
129 |
130 |
131 |
132 |
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/README.md:
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1 |
2 |
3 |
4 | # statcanR
5 |
6 |
7 |
8 | [](https://ci.appveyor.com/project/warint/statcanR)
10 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
12 | [](https://CRAN.R-project.org/package=statcanR)
14 | [](https://cran.r-project.org/package=statcanR)
15 |
16 |
17 |
18 | # Overview
19 |
20 | Easily connect to Statistics Canada’s Web Data Service with R. Find and
21 | access open economic data (formerly known as CANSIM tables, now identified by
22 | Product IDs (PID)) which are accessible as a data frame, directly in the
23 | user’s R environment.
24 |
25 |
26 |
27 | ## Shiny App : statcanR ExploR
28 |
29 |
30 |
31 | For people less comfortable with R and to allow more people to have
32 | access to our package, we have also developed a Shiny
33 | application.Through the same logic present in our package, researchers
34 | can retrieve data from Statistics Canada.
35 |
36 | statcanR ExploR is available [\[here\]](https://warin.ca/shiny/statcanr/)
37 |
38 | ## Installation
39 |
40 | The released version of statcanR package is accessible through CRAN and
41 | devtools.
42 |
43 | ``` r
44 | install.packages("statcanR")
45 |
46 | install.packages("devtools")
47 | devtools::install_github('warint/statcanR')
48 | ```
49 |
50 | ## Example
51 |
52 | This section presents an example of how to use the `statcanR` R package
53 | and its functions: `statcan_search()`, `statcan_data()`, and
54 | `statcan_download_data()`.
55 |
56 | The following example is provided to illustrate how to use the
57 | functions. It consists in collecting some descriptive statistics about
58 | the Canadian Labour Force at the federal, provincial and industrial
59 | levels, on a monthly basis.
60 |
61 | To identify a relevant table, the statcan_search() function can be used
62 | by using a keyword or set of keywords and specifying the language in which the
63 | data will be presented (English or French). Below is an example that reveals
64 | the data tables we could be interested in:
65 |
66 | ``` r
67 | library(statcanR)
68 | statcan_search(c("federal","expenditures","objectives"),"eng")
69 | ```
70 |
71 | Notice that for each corresponding table, the unique table number identifier is
72 | also presented. Let's focus the first table out of the two that appear, which
73 | contains data on Federal expenditures on science and technology,
74 | by socio-economic objectives. Once this table number is identified
75 | (‘27-10-0014-01’), the statcan_data() function is easy
76 | to use in order to collect the data, as following:
77 |
78 | ``` r
79 | library(statcanR)
80 | mydata <- statcan_data("27-10-0014-01","eng")
81 | ```
82 |
83 | For the `statcan_download_data()` function there is no difference on how
84 | to use it, the only difference is that this function allow you to
85 | download the data in a csv file on top of having the data in your
86 | environment.
87 |
88 | ``` r
89 | library(statcanR)
90 | mydata <- statcan_download_data("27-10-0014-01","eng")
91 | ```
92 |
93 | ### Video Tutorial
94 |
95 | Tutorial made by Professor Charles Saunders, Director of Master of
96 | Financial Economics Program at Western University
97 | [biography](https://economics.uwo.ca/people/faculty/saunders.html)
98 |
99 | Thanks!
100 |
101 |
102 |
103 | ### Statistics Canada Open Licence
104 |
105 | This licence is issued on behalf of His Majesty the King in Right of
106 | Canada, as represented by the Minister for Statistics Canada
107 | (“Statistics Canada”) to you (an individual or a legal entity that you
108 | are authorized to represent).
109 |
110 | Statistics Canada may modify this licence at any time, and such
111 | modifications shall be effective immediately upon posting of the
112 | modified licence on the Statistics Canada website. Your use of the
113 | Information will be governed by the terms of the licence in force as of
114 | the date and time you accessed the Information.
115 |
116 | Please refer to the [terms of
117 | licence](https://www.statcan.gc.ca/eng/reference/licence) before using
118 | the Information.
119 |
120 | ##### Acknowledgment of Source according to Statistics Canada Open Licence Agreement
121 |
122 | Statistics Canada has a specific procedure regarding the acknowledgment
123 | of source :
124 |
125 | You shall include and maintain the following notice on all licensed
126 | rights of the Information:
127 |
128 | Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
129 |
130 | Where any Information is contained within a Value-added Product, you
131 | shall include on such Value-added Product the following notice:
132 |
133 | Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.
134 |
135 | ### Cite statcanR
136 |
137 | To cite statcanR package in your work:
138 |
139 | Warin, T. (2024). Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses. Technology Innovations in Statistics Education, 15(1). http://dx.doi.org/10.5070/T5.1868 Retrieved from https://escholarship.org/uc/item/9jr7k5hp
140 |
141 | ``` r
142 | @article{warin_access_2024,
143 | title = {Access {Statistics} {Canada}’s {Open} {Economic} {Data} for {Statistics} and {Data} {Science} {Courses}},
144 | volume = {15},
145 | url = {https://escholarship.org/uc/item/9jr7k5hp},
146 | doi = {10.5070/T5.1868},
147 | abstract = {This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy.},
148 | language = {en},
149 | number = {1},
150 | urldate = {2024-01-17},
151 | journal = {Technology Innovations in Statistics Education},
152 | author = {Warin, Thierry},
153 | month = jan,
154 | year = {2024},
155 | file = {Full Text PDF:/Users/thierrywarin/Zotero/storage/7LNXFPKL/Warin - 2024 - Access Statistics Canada’s Open Economic Data for .pdf:application/pdf},
156 | }
157 | ```
158 |
159 | ### Acknowledgments
160 |
161 | A previous version of this package was developed with Romain Le Duc. This version has benefitted from Thibault Senegas's contribution. The author would like to thank the Center for Interuniversity Research and Analysis of Organizations (CIRANO, Montreal) for its support, as well as Thibault Senegas, Jeremy Schneider, Marine Leroi, Martin Paquette and Romain Le Duc. However, errors and omissions are his.
162 |
163 |
164 | ### Contributing to the package
165 | #### Bug reports
166 |
167 | When you file a bug report, please spend some time making it easy for me to follow and reproduce. The more time you spend on making the bug report coherent, the more time I can dedicate to investigate the bug as opposed to the bug report.
168 |
169 | ##### Contributing to the package development
170 |
171 | To get started, consider either adding a new example or enhancing the existing documentation.
172 |
173 | If you're interested in submitting a Pull Request to include your own functions, please include the following:
174 |
175 | - The code for the new function(s), complete with roxygen annotations and sample usage.
176 | - A dedicated section in the relevant vignette that explains how to utilize the new function.
177 |
178 | To ensure your changes are compliant, run rhub::check_for_cran() using rhub. After submission, your Pull Request will undergo automated evaluation via GitHub Actions, allowing you to monitor for any issues.
179 |
180 |
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/vignettes/statCanR.Rmd:
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1 | ---
2 | title: "statCanR"
3 | author: "Thierry Warin"
4 | data: "`r Sys.Date()`"
5 | output: rmarkdown::html_vignette
6 | vignette: >
7 | %\VignetteIndexEntry{statCanR}
8 | %\VignetteEngine{knitr::rmarkdown}
9 | %\VignetteEncoding{UTF-8}
10 | ---
11 |
12 | ```{r, include = FALSE}
13 | knitr::opts_chunk$set(
14 | collapse = TRUE,
15 | comment = "#>"
16 | )
17 | ```
18 |
19 | ```{r setup}
20 | library(statcanR)
21 | ```
22 |
23 |
24 | ## Overview
25 |
26 | statcanR provides the R user with a consistent process to identify and collect data from Statistics Canada's data portal. It allows users to search for and access all of Statistics Canada' open economic data (formerly known as CANSIM tables) now identified by product IDs (PID) by the new Statistics Canada's Web Data Service: .
27 |
28 | ## Quick start
29 |
30 | First, install statcanR:
31 |
32 | ```{r, eval=FALSE}
33 | devtools::install_github("warint/statcanR")
34 | ```
35 |
36 |
37 | Next, call statcanR to make sure everything is installed correctly.
38 |
39 | ```{r}
40 | library(statcanR)
41 | ```
42 |
43 | # Practical usage
44 |
45 | This section presents an example of how to use the statcanR R package and its functions: statcan_search() and statcan_data().
46 |
47 |
48 | The following example is provided to illustrate how to use these functions. It consists of collecting some descriptive statistics about the Canadian labour force at the federal, provincial and industrial levels, on a monthly basis.
49 |
50 | To identify a relevant table, the statcan_search() function can be used
51 | by using a keyword or set of keywords, depending on the language the user wishes to search in (between English and French). Below is an example that reveals
52 | the data tables we could be interested in:
53 |
54 | ```{r, eval=FALSE}
55 | # Identify with statcan_search() function
56 | statcan_search(c("federal","expenditures"),"eng")
57 | ```
58 |
59 |
60 | Notice that for each corresponding table, the unique table number identifier is also presented. Let's focus on the first table out of the two that appear, which contains data on Federal expenditures on science and technology, by socio-economic objectives. Once this table number is identified
61 | (‘27-10-0014-01’), the statcan_data() function is easy to use in order to collect the data, as following:
62 |
63 | ```{r, eval=FALSE}
64 | # Get data with statcan_data function
65 | mydata <- statcan_download_data("27-10-0014-01", "eng")
66 | ```
67 |
68 | Should you want the same data in French, just replace the argument at the end of the function with "fra".
69 |
70 | ## Code architecture
71 |
72 | This section describes the code architecture of the statcanR package.
73 |
74 | The statcan_search() function has 2 arguments:
75 |
76 | 1. keywords
77 | 2. lang
78 |
79 | The 'keywords' argument is useful for identifying what kind of open economic data Statistics Canada has available for users. It can take as inputs either a single word (i.e., statcan_search("expenditures")) or a vector of multiple keywords (such as: statcan_search(c("expenditures","federal","objectives"))).
80 |
81 | The second argument, 'lang', refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages. Therefore, users can see what data tables are available in French or English by setting the lang argument with c("fra", "eng").
82 |
83 |
84 |
85 |
86 | For all data tables that contain these words in either their title or description, the resulting output will include four pieces of information: The name of the data table, its unique table number identifier, the description, and the release date.
87 | In details, the statcan_download_data() function has 2 arguments:
88 |
89 | 1. tableNumber
90 | 2. lang
91 |
92 |
93 | The 'tableNumber' argument simply refers to the table number of the Statistics Canada data table a user wants to collect, such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
94 |
95 |
96 | Just as in the statcan_search() command, 'lang', refers to the language, and can be set to "eng" for English or "fra" for French. Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c("fra", "eng").
97 |
98 | The code architecture of the statcan_download_data() function is as follows. The first step if to clean the table number in order to align it with the official typology of Statistics Canada's Web Data Service. The second step is to create a temporary folder where all the data wrangling operations are performed. The third step is to check and select the correct language. The fourth step is to define the right URL where the actual data table is stored and then to download the .Zip container. The fifth step is to unzip the previously downloaded .Zip file to extract the data and metadata from the .csv files. The final step is to load the statistics data into a data frame called 'data' and to add the official table indicator name in the new 'INDICATOR' column.
99 |
100 |
101 | To be more precise about the functions, below is some further code description:
102 |
103 | ### statcan_search()
104 |
105 | - ` keyword_regex <- paste0("(", paste(keywords, collapse = "|"), ")", collapse = ".*")`:
106 | The first step is to paste (either individually or in vector format) the keywords the user is interested in
107 |
108 | - ` matches <- apply(statcan_data, 1, function(row) {`
109 | ` all(sapply(keywords, function(x) {`
110 | ` grepl(x, paste(as.character(row), collapse = " "))`
111 | ` }))`
112 | ` }) `:
113 | Next, the matching relies on the sapply function, which is applied to any character string in a row of a given observation. Therefore, the "keyword" could be found in the title column or the description column (technically, it could even be in the "release date" or "id" columns).
114 |
115 | - ` filtered_data <- statcan_data[matches, ]`
116 | The third step takes only the data where matches were found.
117 |
118 | - ` datatable(filtered_data, options = list(pageLength = 10))`
119 | Finally, the datatable command presents the filtered data in a clean table.
120 |
121 |
122 |
123 | ### statcan_download_data()
124 |
125 | - `tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber)-2))`:
126 | The first step is to clean the table number provided by the user in order to collect the overall data table related to the specific indicator the user is interested in. In fact, each indicator is an excerpt of the overall table.
127 | In addition, following the new Statistics Canada's Web Data Service, the URL typology defined by REST API is stored in csv files by table numbers without a '-'. Also, the last 2 digits after the last '-' refer to the specific excerpt of the original table.
128 | Therefore, following the Statistics Canada Web Data Service's typology, the function first removes the '-' and the last 2 digits from the user's selection.
129 |
130 | - `if(lang == "eng")` | `if(lang == "fra")`:
131 | The second step is the 'if statement' to get the data in the correct language.
132 |
133 | - `urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/", tableNumber, "-fra.zip")`:
134 | The third step is to create the correct url in order to download the respective .Zip file from the Statistics Canada Web Data Service.
135 |
136 | - `download(urlFra, download_dir, mode = "wb")`:
137 | The fourth step is a simple downloading function that extracts .Zip file and download it into a temporary folder.
138 |
139 | - `unzip(zipfile = download_dir, exdir = unzip_dir)`:
140 | The fifth step consists in unzipping the .Zip file. The unzipping process gives access to two different .csv files, such as the overall data table and the metadata table.
141 |
142 | - `data.table::fread(csv_file)`:
143 | The sixth step consists in loading the data table into a unique data frame. The fread() function from the data.table package is used for its higher performance.
144 |
145 | - `data$INDICATOR <- as.character(0)` and `data$INDICATOR <- as.character(read.csv(paste0(path,"/temp/", tableNumber, "_MetaData.csv"))[1,1])`:
146 | The seventh step of the statcan_data() function consists in adding the name of the table from the metadata table.
147 |
148 | - `unlink(tempdir())`:
149 | The eighth step deletes the temporary folder used to download, unzip, extract and load the data.
150 |
151 | - `return(Data)`:
152 | Finally, the last step of the statcan_data() function allows to return the value into the user's environment.
153 |
154 |
155 |
156 |
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/docs/reference/statcan_download_data.html:
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1 |
2 | statcanR download data function — statcan_download_data • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
63 |
64 |
65 | statcanR download data function
66 |
67 |
68 |
69 | statcan_download_data(tableNumber, lang)
70 |
71 |
72 |
73 | Arguments
74 | - tableNumber
75 | The table number of the Statistics Canada data table
- lang
79 | The language wanted
82 |
83 | Value
84 |
85 |
86 | The output will be a data table and csv file representing the data associated with the chosen table number.
87 |
88 |
89 |
90 | Examples
91 | mydata <- statcan_data('27-10-0014-01', 'eng')
92 | #> statcanR: downloading remote table.
93 | #> Warning: One or more parsing issues, call `problems()` on your data frame for details,
94 | #> e.g.:
95 | #> dat <- vroom(...)
96 | #> problems(dat)
97 | #> Rows: 61 Columns: 10
98 | #> ── Column specification ────────────────────────────────────────────────────────
99 | #> Delimiter: ","
100 | #> chr (8): Cube Title, Product Id, CANSIM Id, URL, Cube Notes, Archive Status...
101 | #> num (1): Total number of dimensions
102 | #> date (1): End Reference Period
103 | #>
104 | #> ℹ Use `spec()` to retrieve the full column specification for this data.
105 | #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
106 |
107 |
108 |
109 |
112 |
113 |
114 |
115 |
124 |
125 |
126 |
127 |
128 |
129 |
130 |
131 |
132 |
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1 | /* Sticky footer */
2 |
3 | /**
4 | * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
5 | * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
6 | *
7 | * .Site -> body > .container
8 | * .Site-content -> body > .container .row
9 | * .footer -> footer
10 | *
11 | * Key idea seems to be to ensure that .container and __all its parents__
12 | * have height set to 100%
13 | *
14 | */
15 |
16 | html, body {
17 | height: 100%;
18 | }
19 |
20 | body {
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22 | }
23 |
24 | body > .container {
25 | display: flex;
26 | height: 100%;
27 | flex-direction: column;
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30 | body > .container .row {
31 | flex: 1 0 auto;
32 | }
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39 | display: flex;
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48 | footer .pkgdown {
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50 | }
51 | footer p {
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54 |
55 | img.icon {
56 | float: right;
57 | }
58 |
59 | /* Ensure in-page images don't run outside their container */
60 | .contents img {
61 | max-width: 100%;
62 | height: auto;
63 | }
64 |
65 | /* Fix bug in bootstrap (only seen in firefox) */
66 | summary {
67 | display: list-item;
68 | }
69 |
70 | /* Typographic tweaking ---------------------------------*/
71 |
72 | .contents .page-header {
73 | margin-top: calc(-60px + 1em);
74 | }
75 |
76 | dd {
77 | margin-left: 3em;
78 | }
79 |
80 | /* Section anchors ---------------------------------*/
81 |
82 | a.anchor {
83 | display: none;
84 | margin-left: 5px;
85 | width: 20px;
86 | height: 20px;
87 |
88 | background-image: url(./link.svg);
89 | background-repeat: no-repeat;
90 | background-size: 20px 20px;
91 | background-position: center center;
92 | }
93 |
94 | h1:hover .anchor,
95 | h2:hover .anchor,
96 | h3:hover .anchor,
97 | h4:hover .anchor,
98 | h5:hover .anchor,
99 | h6:hover .anchor {
100 | display: inline-block;
101 | }
102 |
103 | /* Fixes for fixed navbar --------------------------*/
104 |
105 | .contents h1, .contents h2, .contents h3, .contents h4 {
106 | padding-top: 60px;
107 | margin-top: -40px;
108 | }
109 |
110 | /* Navbar submenu --------------------------*/
111 |
112 | .dropdown-submenu {
113 | position: relative;
114 | }
115 |
116 | .dropdown-submenu>.dropdown-menu {
117 | top: 0;
118 | left: 100%;
119 | margin-top: -6px;
120 | margin-left: -1px;
121 | border-radius: 0 6px 6px 6px;
122 | }
123 |
124 | .dropdown-submenu:hover>.dropdown-menu {
125 | display: block;
126 | }
127 |
128 | .dropdown-submenu>a:after {
129 | display: block;
130 | content: " ";
131 | float: right;
132 | width: 0;
133 | height: 0;
134 | border-color: transparent;
135 | border-style: solid;
136 | border-width: 5px 0 5px 5px;
137 | border-left-color: #cccccc;
138 | margin-top: 5px;
139 | margin-right: -10px;
140 | }
141 |
142 | .dropdown-submenu:hover>a:after {
143 | border-left-color: #ffffff;
144 | }
145 |
146 | .dropdown-submenu.pull-left {
147 | float: none;
148 | }
149 |
150 | .dropdown-submenu.pull-left>.dropdown-menu {
151 | left: -100%;
152 | margin-left: 10px;
153 | border-radius: 6px 0 6px 6px;
154 | }
155 |
156 | /* Sidebar --------------------------*/
157 |
158 | #pkgdown-sidebar {
159 | margin-top: 30px;
160 | position: -webkit-sticky;
161 | position: sticky;
162 | top: 70px;
163 | }
164 |
165 | #pkgdown-sidebar h2 {
166 | font-size: 1.5em;
167 | margin-top: 1em;
168 | }
169 |
170 | #pkgdown-sidebar h2:first-child {
171 | margin-top: 0;
172 | }
173 |
174 | #pkgdown-sidebar .list-unstyled li {
175 | margin-bottom: 0.5em;
176 | }
177 |
178 | /* bootstrap-toc tweaks ------------------------------------------------------*/
179 |
180 | /* All levels of nav */
181 |
182 | nav[data-toggle='toc'] .nav > li > a {
183 | padding: 4px 20px 4px 6px;
184 | font-size: 1.5rem;
185 | font-weight: 400;
186 | color: inherit;
187 | }
188 |
189 | nav[data-toggle='toc'] .nav > li > a:hover,
190 | nav[data-toggle='toc'] .nav > li > a:focus {
191 | padding-left: 5px;
192 | color: inherit;
193 | border-left: 1px solid #878787;
194 | }
195 |
196 | nav[data-toggle='toc'] .nav > .active > a,
197 | nav[data-toggle='toc'] .nav > .active:hover > a,
198 | nav[data-toggle='toc'] .nav > .active:focus > a {
199 | padding-left: 5px;
200 | font-size: 1.5rem;
201 | font-weight: 400;
202 | color: inherit;
203 | border-left: 2px solid #878787;
204 | }
205 |
206 | /* Nav: second level (shown on .active) */
207 |
208 | nav[data-toggle='toc'] .nav .nav {
209 | display: none; /* Hide by default, but at >768px, show it */
210 | padding-bottom: 10px;
211 | }
212 |
213 | nav[data-toggle='toc'] .nav .nav > li > a {
214 | padding-left: 16px;
215 | font-size: 1.35rem;
216 | }
217 |
218 | nav[data-toggle='toc'] .nav .nav > li > a:hover,
219 | nav[data-toggle='toc'] .nav .nav > li > a:focus {
220 | padding-left: 15px;
221 | }
222 |
223 | nav[data-toggle='toc'] .nav .nav > .active > a,
224 | nav[data-toggle='toc'] .nav .nav > .active:hover > a,
225 | nav[data-toggle='toc'] .nav .nav > .active:focus > a {
226 | padding-left: 15px;
227 | font-weight: 500;
228 | font-size: 1.35rem;
229 | }
230 |
231 | /* orcid ------------------------------------------------------------------- */
232 |
233 | .orcid {
234 | font-size: 16px;
235 | color: #A6CE39;
236 | /* margins are required by official ORCID trademark and display guidelines */
237 | margin-left:4px;
238 | margin-right:4px;
239 | vertical-align: middle;
240 | }
241 |
242 | /* Reference index & topics ----------------------------------------------- */
243 |
244 | .ref-index th {font-weight: normal;}
245 |
246 | .ref-index td {vertical-align: top; min-width: 100px}
247 | .ref-index .icon {width: 40px;}
248 | .ref-index .alias {width: 40%;}
249 | .ref-index-icons .alias {width: calc(40% - 40px);}
250 | .ref-index .title {width: 60%;}
251 |
252 | .ref-arguments th {text-align: right; padding-right: 10px;}
253 | .ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
254 | .ref-arguments .name {width: 20%;}
255 | .ref-arguments .desc {width: 80%;}
256 |
257 | /* Nice scrolling for wide elements --------------------------------------- */
258 |
259 | table {
260 | display: block;
261 | overflow: auto;
262 | }
263 |
264 | /* Syntax highlighting ---------------------------------------------------- */
265 |
266 | pre, code, pre code {
267 | background-color: #f8f8f8;
268 | color: #333;
269 | }
270 | pre, pre code {
271 | white-space: pre-wrap;
272 | word-break: break-all;
273 | overflow-wrap: break-word;
274 | }
275 |
276 | pre {
277 | border: 1px solid #eee;
278 | }
279 |
280 | pre .img, pre .r-plt {
281 | margin: 5px 0;
282 | }
283 |
284 | pre .img img, pre .r-plt img {
285 | background-color: #fff;
286 | }
287 |
288 | code a, pre a {
289 | color: #375f84;
290 | }
291 |
292 | a.sourceLine:hover {
293 | text-decoration: none;
294 | }
295 |
296 | .fl {color: #1514b5;}
297 | .fu {color: #000000;} /* function */
298 | .ch,.st {color: #036a07;} /* string */
299 | .kw {color: #264D66;} /* keyword */
300 | .co {color: #888888;} /* comment */
301 |
302 | .error {font-weight: bolder;}
303 | .warning {font-weight: bolder;}
304 |
305 | /* Clipboard --------------------------*/
306 |
307 | .hasCopyButton {
308 | position: relative;
309 | }
310 |
311 | .btn-copy-ex {
312 | position: absolute;
313 | right: 0;
314 | top: 0;
315 | visibility: hidden;
316 | }
317 |
318 | .hasCopyButton:hover button.btn-copy-ex {
319 | visibility: visible;
320 | }
321 |
322 | /* headroom.js ------------------------ */
323 |
324 | .headroom {
325 | will-change: transform;
326 | transition: transform 200ms linear;
327 | }
328 | .headroom--pinned {
329 | transform: translateY(0%);
330 | }
331 | .headroom--unpinned {
332 | transform: translateY(-100%);
333 | }
334 |
335 | /* mark.js ----------------------------*/
336 |
337 | mark {
338 | background-color: rgba(255, 255, 51, 0.5);
339 | border-bottom: 2px solid rgba(255, 153, 51, 0.3);
340 | padding: 1px;
341 | }
342 |
343 | /* vertical spacing after htmlwidgets */
344 | .html-widget {
345 | margin-bottom: 10px;
346 | }
347 |
348 | /* fontawesome ------------------------ */
349 |
350 | .fab {
351 | font-family: "Font Awesome 5 Brands" !important;
352 | }
353 |
354 | /* don't display links in code chunks when printing */
355 | /* source: https://stackoverflow.com/a/10781533 */
356 | @media print {
357 | code a:link:after, code a:visited:after {
358 | content: "";
359 | }
360 | }
361 |
362 | /* Section anchors ---------------------------------
363 | Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
364 | */
365 |
366 | div.csl-bib-body { }
367 | div.csl-entry {
368 | clear: both;
369 | }
370 | .hanging-indent div.csl-entry {
371 | margin-left:2em;
372 | text-indent:-2em;
373 | }
374 | div.csl-left-margin {
375 | min-width:2em;
376 | float:left;
377 | }
378 | div.csl-right-inline {
379 | margin-left:2em;
380 | padding-left:1em;
381 | }
382 | div.csl-indent {
383 | margin-left: 2em;
384 | }
385 |
--------------------------------------------------------------------------------
/docs/reference/statcan_search.html:
--------------------------------------------------------------------------------
1 |
2 | Searching function for statcanR — statcan_search • statcanR
9 |
10 |
11 |
12 |
56 |
57 |
58 |
59 |
60 |
61 |
66 |
67 |
68 | The statcan_search() function has 2 arguments to fulfill to find a database: keywords and lang.
69 | The keywords argument refers to words that can be found in either the title or the description of the database. For example, inserting the keywords
70 | "economy","export",and "link" will bring up the title, table id, description, and release date for databases that include these keywords. In this case, only one data table ("Supply and use tables, link-1997 level")
71 | would be returned as it is the only data table containing all three words.
72 |
73 |
74 |
75 | statcan_search(keywords, lang)
76 |
77 |
78 |
79 | Arguments
80 | - keywords
81 | The words that appear in the title or description of the data table
- lang
85 | The language wanted
88 |
89 | Value
90 |
91 |
92 | The output will be the title, id, description, and release date of a table
93 |
94 |
95 | Details
96 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
97 |
98 |
99 |
100 | Examples
101 | statcan_search(c("economy","export","link"),"eng")
102 |
103 |
104 |
105 |
106 |
109 |
110 |
111 |
112 |
121 |
122 |
123 |
124 |
125 |
126 |
127 |
128 |
129 |
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/docs/docsearch.css:
--------------------------------------------------------------------------------
1 | /* Docsearch -------------------------------------------------------------- */
2 | /*
3 | Source: https://github.com/algolia/docsearch/
4 | License: MIT
5 | */
6 |
7 | .algolia-autocomplete {
8 | display: block;
9 | -webkit-box-flex: 1;
10 | -ms-flex: 1;
11 | flex: 1
12 | }
13 |
14 | .algolia-autocomplete .ds-dropdown-menu {
15 | width: 100%;
16 | min-width: none;
17 | max-width: none;
18 | padding: .75rem 0;
19 | background-color: #fff;
20 | background-clip: padding-box;
21 | border: 1px solid rgba(0, 0, 0, .1);
22 | box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
23 | }
24 |
25 | @media (min-width:768px) {
26 | .algolia-autocomplete .ds-dropdown-menu {
27 | width: 175%
28 | }
29 | }
30 |
31 | .algolia-autocomplete .ds-dropdown-menu::before {
32 | display: none
33 | }
34 |
35 | .algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
36 | padding: 0;
37 | background-color: rgb(255,255,255);
38 | border: 0;
39 | max-height: 80vh;
40 | }
41 |
42 | .algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
43 | margin-top: 0
44 | }
45 |
46 | .algolia-autocomplete .algolia-docsearch-suggestion {
47 | padding: 0;
48 | overflow: visible
49 | }
50 |
51 | .algolia-autocomplete .algolia-docsearch-suggestion--category-header {
52 | padding: .125rem 1rem;
53 | margin-top: 0;
54 | font-size: 1.3em;
55 | font-weight: 500;
56 | color: #00008B;
57 | border-bottom: 0
58 | }
59 |
60 | .algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
61 | float: none;
62 | padding-top: 0
63 | }
64 |
65 | .algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
66 | float: none;
67 | width: auto;
68 | padding: 0;
69 | text-align: left
70 | }
71 |
72 | .algolia-autocomplete .algolia-docsearch-suggestion--content {
73 | float: none;
74 | width: auto;
75 | padding: 0
76 | }
77 |
78 | .algolia-autocomplete .algolia-docsearch-suggestion--content::before {
79 | display: none
80 | }
81 |
82 | .algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
83 | padding-top: .75rem;
84 | margin-top: .75rem;
85 | border-top: 1px solid rgba(0, 0, 0, .1)
86 | }
87 |
88 | .algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
89 | display: block;
90 | padding: .1rem 1rem;
91 | margin-bottom: 0.1;
92 | font-size: 1.0em;
93 | font-weight: 400
94 | /* display: none */
95 | }
96 |
97 | .algolia-autocomplete .algolia-docsearch-suggestion--title {
98 | display: block;
99 | padding: .25rem 1rem;
100 | margin-bottom: 0;
101 | font-size: 0.9em;
102 | font-weight: 400
103 | }
104 |
105 | .algolia-autocomplete .algolia-docsearch-suggestion--text {
106 | padding: 0 1rem .5rem;
107 | margin-top: -.25rem;
108 | font-size: 0.8em;
109 | font-weight: 400;
110 | line-height: 1.25
111 | }
112 |
113 | .algolia-autocomplete .algolia-docsearch-footer {
114 | width: 110px;
115 | height: 20px;
116 | z-index: 3;
117 | margin-top: 10.66667px;
118 | float: right;
119 | font-size: 0;
120 | line-height: 0;
121 | }
122 |
123 | .algolia-autocomplete .algolia-docsearch-footer--logo {
124 | background-image: url("data:image/svg+xml;utf8,");
125 | background-repeat: no-repeat;
126 | background-position: 50%;
127 | background-size: 100%;
128 | overflow: hidden;
129 | text-indent: -9000px;
130 | width: 100%;
131 | height: 100%;
132 | display: block;
133 | transform: translate(-8px);
134 | }
135 |
136 | .algolia-autocomplete .algolia-docsearch-suggestion--highlight {
137 | color: #FF8C00;
138 | background: rgba(232, 189, 54, 0.1)
139 | }
140 |
141 |
142 | .algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
143 | box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
144 | }
145 |
146 | .algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
147 | background-color: rgba(192, 192, 192, .15)
148 | }
149 |
--------------------------------------------------------------------------------
/R/statCanR.R:
--------------------------------------------------------------------------------
1 | #' statcanR
2 | #'
3 | #'
4 | #' Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
5 | #'
6 | #' The
7 | #' \code{statcan_data()} function has 2 arguments to fulfill to get data: {tableNumber} & {lang}.
8 | #'
9 | #'
10 | #' The tableNumber argument simply refers to the table number of the Statistics Canada data table a user wants to collect,
11 | #' such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
12 | #'
13 | #'
14 | #' To get the table number: \url{https://www150.statcan.gc.ca/n1/en/type/data}.
15 | #'
16 | #' The second argument, lang, refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages.
17 | #' Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c('fra', 'eng').
18 | #'
19 | #'
20 | #'
21 | #' @param tableNumber The table number of the Statistics Canada data table
22 | #' @param lang The language wanted
23 | #'
24 | #' @return The output will be a data table representing the data associated with the chosen table number.
25 | #' @export
26 | #'
27 | #' @import curl
28 | #' @import tibble
29 | #' @import qpdf
30 | #' @importFrom httr http_error
31 | #' @importFrom data.table fread
32 | #' @importFrom data.table setDF
33 | #'
34 | #' @examples
35 | #' #mydata <- statcan_data('27-10-0014-01', 'eng')
36 | #'
37 |
38 |
39 | # Scraping function for statcan
40 | statcan_data <- function(tableNumber, lang)
41 | {
42 |
43 | # identifying the table number
44 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber) -
45 | 2))
46 |
47 | # getting data in English version
48 | if (lang == "eng")
49 | {
50 | # downloading the data file in English version
51 | urlEng <- paste0("https://www150.statcan.gc.ca/n1/en/tbl/csv/",
52 | tableNumber, "-eng.zip")
53 |
54 | download_dir <- file.path(tempdir(), "datasetEng.zip")
55 |
56 | #utils::download.file(urlEng, download_dir, method = "curl")
57 | #data.table::fread(input = urlEng, file = download_dir)
58 | #RCurl::getURL(urlEng, ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
59 | #curl::curl_download(urlEng, download_dir)
60 |
61 | if (httr::http_error(urlEng)) { # network is down = message (not an error anymore)
62 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
63 | #return(NULL)
64 | } else { # network is up = proceed to download via curl
65 | message("statcanR: downloading remote table.")
66 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlEng, download_dir))
67 |
68 |
69 | # unziping the downloaded data file in English version
70 | unzip_dir <- file.path(paste0(tempdir(), "/"))
71 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
72 | unlink(download_dir)
73 |
74 | # loading the data file in English version
75 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
76 | can_data <- data.table::fread(csv_file)
77 |
78 | # adding to the data.frame or data.table the Official Data Table
79 | # Indicator defined by Statistics Canada and based on metadata file.
80 | can_data$INDICATOR <- as.character(0)
81 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
82 | can_data$INDICATOR <- as.character(readr::read_csv(paste0(tempdir(),
83 | "/", tableNumber, "_MetaData.csv"))[1, 1])
84 |
85 | if(nchar(can_data[1,1])==9){
86 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
87 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
88 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
89 | }
90 |
91 | else if(nchar(can_data[1,1])==7){
92 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
93 | }
94 |
95 | else if(nchar(can_data[1,1])==4){
96 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
97 | }
98 |
99 | else{
100 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
101 | }
102 |
103 | # creating a data frame
104 | data.table::setDF(return(can_data))
105 |
106 | } # /if - network up or down
107 |
108 | }
109 |
110 | # getting data in French version
111 | if (lang == "fra")
112 | {
113 | # downloading the data file in French version
114 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/",
115 | tableNumber, "-fra.zip")
116 |
117 | download_dir <- file.path(tempdir(), "datasetFra.zip")
118 | #utils::download.file(urlFra, download_dir, method = "curl")
119 | #data.table::fread(urlFra, download_dir)
120 | #curl::curl_download(urlFra, download_dir)
121 |
122 | if (httr::http_error(urlFra)) { # network is down = message (not an error anymore)
123 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
124 | return(NULL)
125 | } else { # network is up = proceed to download via curl
126 | message("statcanR: downloading remote table.")
127 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlFra, download_dir))
128 |
129 |
130 | # unzipping the downloaded data file in French version
131 | unzip_dir <- file.path(paste0(tempdir(), "/"))
132 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
133 | unlink(download_dir)
134 |
135 | # loading the data file in French version
136 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
137 | can_data <- data.table::fread(csv_file)
138 |
139 | # adding to the data.frame or data.table the Official Data Table
140 | # Indicator defined by Statitics Canada and based on metadata file.
141 | can_data$INDICATOR <- as.character(0)
142 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
143 | can_data$INDICATOR <- as.character(readr::read_delim(paste0(tempdir(),
144 | "/", tableNumber, "_MetaData.csv"), delim = ";", escape_double = FALSE, trim_ws = TRUE)[1, 1])
145 |
146 | can_data[,1] <- "REF_DATE"
147 |
148 | if(nchar(can_data[1,1])==9){
149 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
150 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
151 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
152 | }
153 |
154 | else if(nchar(can_data[1,1])==7){
155 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
156 | }
157 |
158 | else if(nchar(can_data[1,1])==4){
159 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
160 | }
161 |
162 | else{
163 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
164 | }
165 |
166 | # creating a data frame
167 | data.table::setDF(return(can_data))
168 | } # /if - network up or down
169 |
170 | }
171 |
172 |
173 | # removing the temp folder and creating a data frame
174 | unlink(tempdir())
175 |
176 | }
177 |
178 | #' statcanR download data function
179 | #'
180 | #' @param tableNumber The table number of the Statistics Canada data table
181 | #' @param lang The language wanted
182 | #'
183 | #' @return The output will be a data table and csv file representing the data associated with the chosen table number.
184 | #' @export
185 | #'
186 | #'
187 | #' @import curl
188 | #' @import tibble
189 | #' @importFrom httr http_error
190 | #' @importFrom data.table fread
191 | #' @importFrom data.table setDF
192 | #'
193 | #' @examples
194 | #' mydata <- statcan_data('27-10-0014-01', 'eng')
195 |
196 | # Download function for statcan
197 | statcan_download_data <- function(tableNumber, lang)
198 | {
199 |
200 | # identifying the table number
201 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber) -
202 | 2))
203 |
204 | # getting data in English version
205 | if (lang == "eng")
206 | {
207 | # downloading the data file in English version
208 | urlEng <- paste0("https://www150.statcan.gc.ca/n1/en/tbl/csv/",
209 | tableNumber, "-eng.zip")
210 |
211 | download_dir <- file.path(tempdir(), "datasetEng.zip")
212 | #utils::download.file(urlEng, download_dir, method = "curl")
213 | #data.table::fread(input = urlEng, file = download_dir)
214 | #RCurl::getURL(urlEng, ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
215 | #curl::curl_download(urlEng, download_dir)
216 |
217 | if (httr::http_error(urlEng)) { # network is down = message (not an error anymore)
218 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
219 | #return(NULL)
220 | } else { # network is up = proceed to download via curl
221 | message("statcanR: downloading remote table.")
222 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlEng, download_dir))
223 |
224 | # unziping the downloaded data file in English version
225 | unzip_dir <- file.path(paste0(tempdir(), "/"))
226 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
227 | unlink(download_dir)
228 |
229 | # loading the data file in English version
230 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
231 | can_data <- data.table::fread(csv_file)
232 |
233 | # adding to the data.frame or data.table the Official Data Table
234 | # Indicator defined by Statistics Canada and based on metadata file.
235 | can_data$INDICATOR <- as.character(0)
236 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
237 | can_data$INDICATOR <- as.character(readr::read_csv(paste0(tempdir(),
238 | "/", tableNumber, "_MetaData.csv"))[1, 1])
239 |
240 | if(nchar(can_data[1,1])==9){
241 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
242 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
243 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
244 | }
245 |
246 | else if(nchar(can_data[1,1])==7){
247 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
248 | }
249 |
250 | else if(nchar(can_data[1,1])==4){
251 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
252 | }
253 |
254 | else{
255 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
256 | }
257 | # creating a data frame
258 | data.table::setDF(return(can_data))
259 | readr::write_csv(can_data, paste0("./statcan_",tableNumber,"_", lang,".csv"))
260 |
261 | } # /if - network up or down
262 |
263 | }
264 |
265 | # getting data in French version
266 | if (lang == "fra")
267 | {
268 | # downloading the data file in French version
269 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/",
270 | tableNumber, "-fra.zip")
271 |
272 | download_dir <- file.path(tempdir(), "datasetFra.zip")
273 | #utils::download.file(urlFra, download_dir, method = "curl")
274 | #data.table::fread(urlFra, download_dir)
275 | #curl::curl_download(urlFra, download_dir)
276 |
277 | if (httr::http_error(urlFra)) { # network is down = message (not an error anymore)
278 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
279 | return(NULL)
280 | } else { # network is up = proceed to download via curl
281 | message("statcanR: downloading remote table.")
282 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlFra, download_dir))
283 |
284 |
285 |
286 | # unzipping the downloaded data file in French version
287 | unzip_dir <- file.path(paste0(tempdir(), "/"))
288 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
289 | unlink(download_dir)
290 |
291 | # loading the data file in French version
292 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
293 | can_data <- data.table::fread(csv_file)
294 |
295 | # adding to the data.frame or data.table the Official Data Table
296 | # Indicator defined by Statistics Canada and based on metadata file.
297 | can_data$INDICATOR <- as.character(0)
298 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
299 | can_data$INDICATOR <- as.character(readr::read_delim(paste0(tempdir(),
300 | "/", tableNumber, "_MetaData.csv"), delim = ";", escape_double = FALSE, trim_ws = TRUE)[1, 1])
301 |
302 | can_data[,1] <- "REF_DATE"
303 |
304 | if(nchar(can_data[1,1])==9){
305 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
306 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
307 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
308 | }
309 |
310 | else if(nchar(can_data[1,1])==7){
311 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
312 | }
313 |
314 | else if(nchar(can_data[1,1])==4){
315 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
316 | }
317 |
318 | else{
319 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
320 | }
321 | # creating a data frame
322 | data.table::setDF(return(can_data))
323 |
324 | readr::write_csv(can_data, paste0("./statcan_",tableNumber,"_", lang,".csv"))
325 | } # /if - network up or down
326 | }
327 |
328 | # removing the temp folder and creating a data frame
329 | unlink(tempdir())
330 | }
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85 | Thierry
86 | Warin
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88 |
89 | Source: vignettes/statCanR.Rmd
90 | statCanR.Rmd
91 |
92 |
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98 |
99 | Overview
100 |
101 | statcanR provides the R user with a consistent process to identify
102 | and collect data from Statistics Canada’s data portal. It allows users
103 | to search for and access all of Statistics Canada’ open economic data
104 | (formerly known as CANSIM tables) now identified by product IDs (PID) by
105 | the new Statistics Canada’s Web Data Service: https://www150.statcan.gc.ca/n1/en/type/data.
106 |
107 |
108 | Quick start
109 |
110 | First, install statcanR:
111 |
112 | devtools::install_github("warint/statcanR")
113 | Next, call statcanR to make sure everything is installed
114 | correctly.
115 |
117 |
118 |
119 | Practical usage
120 |
121 | This section presents an example of how to use the statcanR R package
122 | and its functions: statcan_search() and statcan_data().
123 | The following example is provided to illustrate how to use these
124 | functions. It consists of collecting some descriptive statistics about
125 | the Canadian labour force at the federal, provincial and industrial
126 | levels, on a monthly basis.
127 | To identify a relevant table, the statcan_search() function can be
128 | used by using a keyword or set of keywords, depending on the language
129 | the user wishes to search in (between English and French). Below is an
130 | example that reveals the data tables we could be interested in:
131 |
132 | # Identify with statcan_search() function
133 | statcan_search(c("federal","expenditures"),"eng")
134 | Notice that for each corresponding table, the unique table number
135 | identifier is also presented. Let’s focus on the first table out of the
136 | two that appear, which contains data on Federal expenditures on science
137 | and technology, by socio-economic objectives. Once this table number is
138 | identified (‘27-10-0014-01’), the statcan_data() function is easy to use
139 | in order to collect the data, as following:
140 |
141 | # Get data with statcan_data function
142 | mydata <- statcan_download_data("27-10-0014-01", "eng")
143 | Should you want the same data in French, just replace the argument at
144 | the end of the function with “fra”.
145 |
146 | Code architecture
147 |
148 | This section describes the code architecture of the statcanR
149 | package.
150 | The statcan_search() function has 2 arguments:
151 |
152 | - keywords
153 | - lang
154 |
155 | The ‘keywords’ argument is useful for identifying what kind of open
156 | economic data Statistics Canada has available for users. It can take as
157 | inputs either a single word (i.e., statcan_search(“expenditures”)) or a
158 | vector of multiple keywords (such as:
159 | statcan_search(c(“expenditures”,“federal”,“objectives”))).
160 | The second argument, ‘lang’, refers to the language. As Canada is a
161 | bilingual country, Statistics Canada displays all the economic data in
162 | both languages. Therefore, users can see what data tables are available
163 | in French or English by setting the lang argument with c(“fra”,
164 | “eng”).
165 | For all data tables that contain these words in either their title or
166 | description, the resulting output will include four pieces of
167 | information: The name of the data table, its unique table number
168 | identifier, the description, and the release date. In details, the
169 | statcan_download_data() function has 2 arguments:
170 |
171 | - tableNumber
172 | - lang
173 |
174 | The ‘tableNumber’ argument simply refers to the table number of the
175 | Statistics Canada data table a user wants to collect, such as
176 | ‘27-10-0014-01’ for the Federal expenditures on science and technology,
177 | by socio-economic objectives, as an example.
178 | Just as in the statcan_search() command, ‘lang’, refers to the
179 | language, and can be set to “eng” for English or “fra” for French.
180 | Therefore, users can choose to collect satistics data tables in French
181 | or English by setting the lang argument with c(“fra”, “eng”).
182 | The code architecture of the statcan_download_data() function is as
183 | follows. The first step if to clean the table number in order to align
184 | it with the official typology of Statistics Canada’s Web Data Service.
185 | The second step is to create a temporary folder where all the data
186 | wrangling operations are performed. The third step is to check and
187 | select the correct language. The fourth step is to define the right URL
188 | where the actual data table is stored and then to download the .Zip
189 | container. The fifth step is to unzip the previously downloaded .Zip
190 | file to extract the data and metadata from the .csv files. The final
191 | step is to load the statistics data into a data frame called ‘data’ and
192 | to add the official table indicator name in the new ‘INDICATOR’
193 | column.
194 | To be more precise about the functions, below is some further code
195 | description:
196 |
197 | statcan_search()
198 |
199 |
200 | keyword_regex <- paste0("(", paste(keywords, collapse = "|"), ")", collapse = ".*"):
201 | The first step is to paste (either individually or in vector format) the
202 | keywords the user is interested in
matches <- apply(statcan_data, 1, function(row) {
204 | all(sapply(keywords, function(x) {
205 | grepl(x, paste(as.character(row), collapse = " "))
206 | })) }): Next, the matching relies on the
207 | sapply function, which is applied to any character string in a row of a
208 | given observation. Therefore, the “keyword” could be found in the title
209 | column or the description column (technically, it could even be in the
210 | “release date” or “id” columns).
filtered_data <- statcan_data[matches, ] The
212 | third step takes only the data where matches were found.
datatable(filtered_data, options = list(pageLength = 10))
214 | Finally, the datatable command presents the filtered data in a clean
215 | table.
217 |
218 |
219 | statcan_download_data()
220 |
221 |
222 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber)-2)):
223 | The first step is to clean the table number provided by the user in
224 | order to collect the overall data table related to the specific
225 | indicator the user is interested in. In fact, each indicator is an
226 | excerpt of the overall table. In addition, following the new Statistics
227 | Canada’s Web Data Service, the URL typology defined by REST API is
228 | stored in csv files by table numbers without a ‘-’. Also, the last 2
229 | digits after the last ‘-’ refer to the specific excerpt of the original
230 | table. Therefore, following the Statistics Canada Web Data Service’s
231 | typology, the function first removes the ‘-’ and the last 2 digits from
232 | the user’s selection.
if(lang == "eng") | if(lang == "fra"):
234 | The second step is the ‘if statement’ to get the data in the correct
235 | language.
urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/", tableNumber, "-fra.zip"):
237 | The third step is to create the correct url in order to download the
238 | respective .Zip file from the Statistics Canada Web Data
239 | Service.
download(urlFra, download_dir, mode = "wb"): The
241 | fourth step is a simple downloading function that extracts .Zip file and
242 | download it into a temporary folder.
unzip(zipfile = download_dir, exdir = unzip_dir):
244 | The fifth step consists in unzipping the .Zip file. The unzipping
245 | process gives access to two different .csv files, such as the overall
246 | data table and the metadata table.
data.table::fread(csv_file): The sixth step consists
248 | in loading the data table into a unique data frame. The fread() function
249 | from the data.table package is used for its higher performance.
data$INDICATOR <- as.character(0) and
251 | data$INDICATOR <- as.character(read.csv(paste0(path,"/temp/", tableNumber, "_MetaData.csv"))[1,1]):
252 | The seventh step of the statcan_data() function consists in adding the
253 | name of the table from the metadata table.
unlink(tempdir()): The eighth step deletes the
255 | temporary folder used to download, unzip, extract and load the
256 | data.
return(Data): Finally, the last step of the
258 | statcan_data() function allows to return the value into the user’s
259 | environment.
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76 | getTopLevel: function($scope) {
77 | for (var i = 1; i <= 6; i++) {
78 | var $headings = this.findOrFilter($scope, 'h' + i);
79 | if ($headings.length > 1) {
80 | return i;
81 | }
82 | }
83 |
84 | return 1;
85 | },
86 |
87 | // returns the elements for the top level, and the next below it
88 | getHeadings: function($scope, topLevel) {
89 | var topSelector = 'h' + topLevel;
90 |
91 | var secondaryLevel = topLevel + 1;
92 | var secondarySelector = 'h' + secondaryLevel;
93 |
94 | return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
95 | },
96 |
97 | getNavLevel: function(el) {
98 | return parseInt(el.tagName.charAt(1), 10);
99 | },
100 |
101 | populateNav: function($topContext, topLevel, $headings) {
102 | var $context = $topContext;
103 | var $prevNav;
104 |
105 | var helpers = this;
106 | $headings.each(function(i, el) {
107 | var $newNav = helpers.generateNavItem(el);
108 | var navLevel = helpers.getNavLevel(el);
109 |
110 | // determine the proper $context
111 | if (navLevel === topLevel) {
112 | // use top level
113 | $context = $topContext;
114 | } else if ($prevNav && $context === $topContext) {
115 | // create a new level of the tree and switch to it
116 | $context = helpers.createChildNavList($prevNav);
117 | } // else use the current $context
118 |
119 | $context.append($newNav);
120 |
121 | $prevNav = $newNav;
122 | });
123 | },
124 |
125 | parseOps: function(arg) {
126 | var opts;
127 | if (arg.jquery) {
128 | opts = {
129 | $nav: arg
130 | };
131 | } else {
132 | opts = arg;
133 | }
134 | opts.$scope = opts.$scope || $(document.body);
135 | return opts;
136 | }
137 | },
138 |
139 | // accepts a jQuery object, or an options object
140 | init: function(opts) {
141 | opts = this.helpers.parseOps(opts);
142 |
143 | // ensure that the data attribute is in place for styling
144 | opts.$nav.attr('data-toggle', 'toc');
145 |
146 | var $topContext = this.helpers.createChildNavList(opts.$nav);
147 | var topLevel = this.helpers.getTopLevel(opts.$scope);
148 | var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
149 | this.helpers.populateNav($topContext, topLevel, $headings);
150 | }
151 | };
152 |
153 | $(function() {
154 | $('nav[data-toggle="toc"]').each(function(i, el) {
155 | var $nav = $(el);
156 | Toc.init($nav);
157 | });
158 | });
159 | })();
160 |
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1 |
2 |
3 |
4 | # statcanR
5 |
6 |
7 |
8 | [](https://app.travis-ci.com/github/warint/statcanR)
10 | [](https://ci.appveyor.com/project/warint/statcanR)
12 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
14 | [](https://CRAN.R-project.org/package=statcanR)
16 | [](https://cran.r-project.org/package=statcanR)
17 |
18 |
19 |
20 | # Overview
21 |
22 | Easily connect to Statistics Canada’s Web Data Service with R. Open
23 | economic data (formerly known as CANSIM tables, now identified by
24 | Product IDs (PID)) are accessible as a data frame, directly in the
25 | user’s R environment.
26 |
27 | ## Shiny App : statcanR ExploR
28 |
29 |
30 |
31 | For people less comfortable with R and to allow more people to have
32 | access to our package, we have also developed a Shiny
33 | application.Through the same logic present in our package, researchers
34 | can retrieve data from Statistics Canada.
35 |
36 | statcanR EploR is available [\[here\]](https://warin.ca/shiny/statcanr/)
37 |
38 | ## Installation
39 |
40 | The released version of statcanR package is accessible through CRAN and
41 | devtools.
42 |
43 | ``` r
44 | install.packages("statcanR")
45 |
46 | install.packages("devtools")
47 | devtools::install_github('warint/statcanR')
48 | ```
49 |
50 | ## Example
51 |
52 | This section presents an example of how to use the `statcanR` R package
53 | and its function `statcan_data()` and `statcan_download_data()`.
54 |
55 | The following example is provided to illustrate how to use the
56 | functions. It consists in collecting some descriptive statistics about
57 | the Canadian Labour Force at the federal, provincial and industrial
58 | levels, on a monthly basis.
59 |
60 | With a simple web search ‘statistics canada wages by industry
61 | metropolitan area monthly’, the table number can easily be found on
62 | Statisitcs Canada’s webpage. Here is below a figure that illustrates
63 | this example, such as ‘27-10-0014-01’ for the Federal expenditures on
64 | science and technology, by socio-economic objectives.
65 |
66 | Once the table number is identified, the statcan_data() function is easy
67 | to use in order to collect the data, as following:
68 |
69 | ``` r
70 | library(statcanR)
71 | mydata <- statcan_data("27-10-0014-01","eng")
72 | ```
73 |
74 | For the `statcan_download_data()` function there is no difference on how
75 | to use it, the only difference is that this function allow you to
76 | download the data in a csv file on top of having the data in your
77 | environment.
78 |
79 | ``` r
80 | library(statcanR)
81 | mydata <- statcan_download_data("27-10-0014-01","eng")
82 | ```
83 |
84 | ### Video Tutorial
85 |
86 | Tutorial made by Professor Charles Saunders, Director of Master of
87 | Financial Economics Program at Western University
88 | [biography](https://economics.uwo.ca/people/faculty/saunders.html)
89 |
90 | Thanks!
91 |
92 |
93 |
94 | ### Statistics Canada Open Licence
95 |
96 | This licence is issued on behalf of Her Majesty the Queen in Right of
97 | Canada, as represented by the Minister for Statistics Canada
98 | (“Statistics Canada”) to you (an individual or a legal entity that you
99 | are authorized to represent).
100 |
101 | Statistics Canada may modify this licence at any time, and such
102 | modifications shall be effective immediately upon posting of the
103 | modified licence on the Statistics Canada website. Your use of the
104 | Information will be governed by the terms of the licence in force as of
105 | the date and time you accessed the Information.
106 |
107 | Please refer to the [terms of
108 | licence](https://www.statcan.gc.ca/eng/reference/licence) before using
109 | the Information.
110 |
111 | ##### Acknowledgment of Source according to Statistics Canada Open Licence Agreement
112 |
113 | Statistics Canada has a specific procedure regarding the ackowledgment
114 | of source :
115 |
116 | You shall include and maintain the following notice on all licensed
117 | rights of the Information:
118 |
119 | Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
120 |
121 | Where any Information is contained within a Value-added Product, you
122 | shall include on such Value-added Product the following notice:
123 |
124 | Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.
125 |
126 | ### Cite statcanR
127 |
128 | To cite stantcanR package in your work:
129 |
130 | Warin, T., Romain Le Duc (2019). statcanR: Client for Statistics
131 | Canada’s Open Economic Data. v0.1.0.
132 |
133 | ``` r
134 | @Manual{R-statcanR,
135 | title = {statcanR: Client for Statistics Canada's Open Economic Data},
136 | author = {Thierry Warin and Romain {Le Duc}},
137 | note = {R package version 0.1.0},
138 | url = {https://github.com/warint/statcanR},
139 | year = {2019},
140 | doi = "10.6084/m9.figshare.10544735.v1"
141 | }
142 | ```
143 |
144 | ### Acknowledgments
145 |
146 | The authors would like to thank the Center for Interuniversity Research
147 | and Analysis of Organizations (CIRANO, Montreal) for its support, as
148 | well as Thibault Senegas, Marine Leroi and Martin Paquette. However,
149 | errors and omissions are ours.
150 |
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59 | Reference
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63 | All functions
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69 | statcanR
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73 | statcanR download data function
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1 | # -----------------------------------------------------------
2 | # CITATION file created with {cffr} R package, v0.4.1
3 | # See also: https://docs.ropensci.org/cffr/
4 | # -----------------------------------------------------------
5 |
6 | cff-version: 1.2.0
7 | message: 'To cite package "statcanR" in publications use:'
8 | type: software
9 | license: MIT
10 | title: 'Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses'
11 | version: 0.2.5
12 | abstract: This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy. Warin (2024) .
13 | authors:
14 | - family-names: Warin
15 | given-names: Thierry
16 | email: thierry.warin@hec.ca
17 | orcid: https://orcid.org/0000-0002-5921-3428
18 | repository: https://CRAN.R-project.org/package=statcanR
19 | repository-code: https://github.com/warint/statcanR/issues/
20 | url: https://github.com/warint/statcanR/
21 | contact:
22 | - family-names: Warin
23 | given-names: Thierry
24 | email: thierry.warin@hec.ca
25 | orcid: https://orcid.org/0000-0002-5921-3428
26 | references:
27 | - type: software
28 | title: knitr
29 | abstract: 'knitr: A General-Purpose Package for Dynamic Report Generation in R'
30 | notes: Suggests
31 | url: https://yihui.org/knitr/
32 | repository: https://CRAN.R-project.org/package=knitr
33 | authors:
34 | - family-names: Xie
35 | given-names: Yihui
36 | email: xie@yihui.name
37 | orcid: https://orcid.org/0000-0003-0645-5666
38 | year: '2023'
39 | - type: software
40 | title: rmarkdown
41 | abstract: 'rmarkdown: Dynamic Documents for R'
42 | notes: Suggests
43 | url: https://pkgs.rstudio.com/rmarkdown/
44 | repository: https://CRAN.R-project.org/package=rmarkdown
45 | authors:
46 | - family-names: Allaire
47 | given-names: JJ
48 | email: jj@rstudio.com
49 | - family-names: Xie
50 | given-names: Yihui
51 | email: xie@yihui.name
52 | orcid: https://orcid.org/0000-0003-0645-5666
53 | - family-names: McPherson
54 | given-names: Jonathan
55 | email: jonathan@rstudio.com
56 | - family-names: Luraschi
57 | given-names: Javier
58 | email: javier@rstudio.com
59 | - family-names: Ushey
60 | given-names: Kevin
61 | email: kevin@rstudio.com
62 | - family-names: Atkins
63 | given-names: Aron
64 | email: aron@rstudio.com
65 | - family-names: Wickham
66 | given-names: Hadley
67 | email: hadley@rstudio.com
68 | - family-names: Cheng
69 | given-names: Joe
70 | email: joe@rstudio.com
71 | - family-names: Chang
72 | given-names: Winston
73 | email: winston@rstudio.com
74 | - family-names: Iannone
75 | given-names: Richard
76 | email: rich@rstudio.com
77 | orcid: https://orcid.org/0000-0003-3925-190X
78 | year: '2023'
79 | - type: software
80 | title: data.table
81 | abstract: 'data.table: Extension of `data.frame`'
82 | notes: Imports
83 | url: https://r-datatable.com
84 | repository: https://CRAN.R-project.org/package=data.table
85 | authors:
86 | - family-names: Dowle
87 | given-names: Matt
88 | email: mattjdowle@gmail.com
89 | - family-names: Srinivasan
90 | given-names: Arun
91 | email: asrini@pm.me
92 | year: '2023'
93 | - type: software
94 | title: qpdf
95 | abstract: 'qpdf: Split, Combine and Compress PDF Files'
96 | notes: Imports
97 | url: https://docs.ropensci.org/qpdf/
98 | repository: https://CRAN.R-project.org/package=qpdf
99 | authors:
100 | - family-names: Ooms
101 | given-names: Jeroen
102 | email: jeroen@berkeley.edu
103 | orcid: https://orcid.org/0000-0002-4035-0289
104 | year: '2023'
105 | - type: software
106 | title: DT
107 | abstract: 'DT: A Wrapper of the JavaScript Library ''DataTables'''
108 | notes: Imports
109 | url: https://github.com/rstudio/DT
110 | repository: https://CRAN.R-project.org/package=DT
111 | authors:
112 | - family-names: Xie
113 | given-names: Yihui
114 | email: xie@yihui.name
115 | - family-names: Cheng
116 | given-names: Joe
117 | - family-names: Tan
118 | given-names: Xianying
119 | year: '2023'
120 | - type: software
121 | title: curl
122 | abstract: 'curl: A Modern and Flexible Web Client for R'
123 | notes: Imports
124 | url: https://curl.se/libcurl/
125 | repository: https://CRAN.R-project.org/package=curl
126 | authors:
127 | - family-names: Ooms
128 | given-names: Jeroen
129 | email: jeroen@berkeley.edu
130 | orcid: https://orcid.org/0000-0002-4035-0289
131 | year: '2023'
132 | - type: software
133 | title: httr
134 | abstract: 'httr: Tools for Working with URLs and HTTP'
135 | notes: Imports
136 | url: https://httr.r-lib.org/
137 | repository: https://CRAN.R-project.org/package=httr
138 | authors:
139 | - family-names: Wickham
140 | given-names: Hadley
141 | email: hadley@rstudio.com
142 | year: '2023'
143 | - type: software
144 | title: readr
145 | abstract: 'readr: Read Rectangular Text Data'
146 | notes: Imports
147 | url: https://readr.tidyverse.org
148 | repository: https://CRAN.R-project.org/package=readr
149 | authors:
150 | - family-names: Wickham
151 | given-names: Hadley
152 | email: hadley@rstudio.com
153 | - family-names: Hester
154 | given-names: Jim
155 | - family-names: Bryan
156 | given-names: Jennifer
157 | email: jenny@rstudio.com
158 | orcid: https://orcid.org/0000-0002-6983-2759
159 | year: '2023'
160 | - type: software
161 | title: tibble
162 | abstract: 'tibble: Simple Data Frames'
163 | notes: Imports
164 | url: https://tibble.tidyverse.org/
165 | repository: https://CRAN.R-project.org/package=tibble
166 | authors:
167 | - family-names: Müller
168 | given-names: Kirill
169 | email: krlmlr+r@mailbox.org
170 | - family-names: Wickham
171 | given-names: Hadley
172 | email: hadley@rstudio.com
173 | year: '2023'
174 |
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/docs/LICENSE.html:
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1 |
2 | MIT License • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
59 | MIT License
60 |
61 |
62 |
63 |
64 | Copyright (c) 2020 Thierry Warin ; Romain Le Duc
65 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
66 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
67 | THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
68 |
69 |
70 |
71 |
72 |
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89 |
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93 |
94 |
95 |
96 |
97 |
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/docs/authors.html:
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1 |
2 | Authors and Citation • statcanR
6 |
7 |
8 |
108 |
109 |
110 |
111 |
112 |
113 |
114 |
115 |
116 |
--------------------------------------------------------------------------------
/inst/README.Rmd:
--------------------------------------------------------------------------------
1 | ---
2 | output: github_document
3 | ---
4 |
5 |
6 |
7 | ```{r, include = FALSE}
8 | knitr::opts_chunk$set(
9 | collapse = TRUE,
10 | comment = "#>",
11 | fig.path = "man/figures/README-",
12 | out.width = "100%"
13 | )
14 | ```
15 |
16 | # statcanR
17 |
18 |
19 |
20 |
21 | [](https://app.travis-ci.com/github/warint/statcanR)
22 | [](https://ci.appveyor.com/project/warint/statcanR)
23 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
24 | [](https://CRAN.R-project.org/package=statcanR)
25 | [](https://cran.r-project.org/package=statcanR)
26 |
27 |
28 |
29 | # Overview
30 |
31 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
32 |
33 |
34 | ## Shiny App : statcanR ExploR
35 |
36 |
37 |
38 | For people less comfortable with R and to allow more people to have access to our package, we have also developed a Shiny application.Through the same logic present in our package, researchers can retrieve data from Statistics Canada.
39 |
40 | statcanR EploR is available [[here]]( https://warin.ca/shiny/statcanr/)
41 |
42 | ## Installation
43 |
44 | The released version of statcanR package is accessible through CRAN and devtools.
45 |
46 | ``` r
47 | install.packages("statcanR")
48 |
49 | install.packages("devtools")
50 | devtools::install_github('warint/statcanR')
51 | ```
52 |
53 | ## Example
54 |
55 | This section presents an example of how to use the `statcanR` R package and its function `statcan_data()` and `statcan_download_data()`.
56 |
57 | The following example is provided to illustrate how to use the functions. It consists in collecting some descriptive statistics about the Canadian Labour Force at the federal, provincial and industrial levels, on a monthly basis.
58 |
59 | With a simple web search 'statistics canada wages by industry metropolitan area monthly', the table number can easily be found on Statisitcs Canada's webpage. Here is below a figure that illustrates this example, such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives.
60 |
61 | Once the table number is identified, the statcan_data() function is easy to use in order to collect the data, as following:
62 |
63 | ``` r
64 | library(statcanR)
65 | mydata <- statcan_data("27-10-0014-01","eng")
66 | ```
67 |
68 | For the `statcan_download_data()` function there is no difference on how to use it, the only difference is that this function allow you to download the data in a csv file on top of having the data in your environment.
69 |
70 | ``` r
71 | library(statcanR)
72 | mydata <- statcan_download_data("27-10-0014-01","eng")
73 | ```
74 |
75 | ### Video Tutorial
76 |
77 | Tutorial made by Professor Charles Saunders, Director of Master of Financial
78 | Economics Program at Western University [biography](https://economics.uwo.ca/people/faculty/saunders.html)
79 |
80 | Thanks!
81 |
82 |
83 |
84 |
85 | ### Statistics Canada Open Licence
86 |
87 | This licence is issued on behalf of Her Majesty the Queen in Right of Canada, as represented by the Minister for Statistics Canada ("Statistics Canada") to you (an individual or a legal entity that you are authorized to represent).
88 |
89 | Statistics Canada may modify this licence at any time, and such modifications shall be effective immediately upon posting of the modified licence on the Statistics Canada website. Your use of the Information will be governed by the terms of the licence in force as of the date and time you accessed the Information.
90 |
91 | Please refer to the [terms of licence](https://www.statcan.gc.ca/eng/reference/licence) before using the Information.
92 |
93 |
94 | ##### Acknowledgment of Source according to Statistics Canada Open Licence Agreement
95 |
96 | Statistics Canada has a specific procedure regarding the ackowledgment of source :
97 |
98 | You shall include and maintain the following notice on all licensed rights of the Information:
99 |
100 | Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
101 |
102 | Where any Information is contained within a Value-added Product, you shall include on such Value-added Product the following notice:
103 |
104 | Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.
105 |
106 | ### Cite statcanR
107 |
108 | To cite statcanR package in your work:
109 |
110 | Warin, T. (2024). Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses. Technology Innovations in Statistics Education, 15(1). http://dx.doi.org/10.5070/T5.1868 Retrieved from https://escholarship.org/uc/item/9jr7k5hp
111 |
112 | ``` r
113 | @article{warin_access_2024,
114 | title = {Access {Statistics} {Canada}’s {Open} {Economic} {Data} for {Statistics} and {Data} {Science} {Courses}},
115 | volume = {15},
116 | url = {https://escholarship.org/uc/item/9jr7k5hp},
117 | doi = {10.5070/T5.1868},
118 | abstract = {This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy.},
119 | language = {en},
120 | number = {1},
121 | urldate = {2024-01-17},
122 | journal = {Technology Innovations in Statistics Education},
123 | author = {Warin, Thierry},
124 | month = jan,
125 | year = {2024},
126 | file = {Full Text PDF:/Users/thierrywarin/Zotero/storage/7LNXFPKL/Warin - 2024 - Access Statistics Canada’s Open Economic Data for .pdf:application/pdf},
127 | }
128 | ```
129 |
130 | ### Acknowledgments
131 |
132 | The authors would like to thank the Center for Interuniversity Research and Analysis of Organizations (CIRANO, Montreal) for its support, as well as Thibault Senegas, Marine Leroi and Martin Paquette. However, errors and omissions are ours.
133 |
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/docs/news/index.html:
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1 |
2 | Changelog • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
59 | Changelog
60 | Source: NEWS.md
61 |
62 |
63 |
64 | statcanR 0.2.52023-08-10
65 | - We have corrected statcan_search() function by removing top level code. You can now install statcanR package without an internet connection
66 |
67 |
68 | statcanR 0.2.42023-03-03
69 | - we have added the function statcan_search() to identify economic data tables available on Statistics Canada’s website.
70 |
71 |
72 | statcanR 0.2.32021-12-14
73 | - we have modified the function to get an informative message if the table is not available instead of having an error message.
74 |
75 |
79 |
83 |
84 |
85 |
88 |
89 |
90 |
91 |
92 |
101 |
102 |
103 |
104 |
105 |
106 |
107 |
108 |
109 |
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/docs/reference/statcan_data.html:
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1 |
2 | statcanR — statcan_data • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
63 |
64 |
65 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
66 |
67 |
68 |
69 | statcan_data(tableNumber, lang)
70 |
71 |
72 |
73 | Arguments
74 | - tableNumber
75 | The table number of the Statistics Canada data table
- lang
79 | The language wanted
82 |
83 | Value
84 |
85 |
86 | The output will be a data table representing the data associated with the chosen table number.
87 |
88 |
89 | Details
90 | The
91 | statcan_data() function has 2 arguments to fulfill to get data: tableNumber & lang.
92 |
93 | The tableNumber argument simply refers to the table number of the Statistics Canada data table a user wants to collect,
94 | such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
95 |
96 | To get the table number: https://www150.statcan.gc.ca/n1/en/type/data.
97 | The second argument, lang, refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages.
98 | Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c('fra', 'eng').
99 |
100 |
101 |
102 | Examples
103 | #mydata <- statcan_data('27-10-0014-01', 'eng')
104 |
105 |
106 |
107 |
108 |
109 |
112 |
113 |
114 |
115 |
124 |
125 |
126 |
127 |
128 |
129 |
130 |
131 |
132 |
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/README.md:
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1 |
2 |
3 |
4 | # statcanR
5 |
6 |
7 |
8 | [](https://ci.appveyor.com/project/warint/statcanR)
10 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
12 | [](https://CRAN.R-project.org/package=statcanR)
14 | [](https://cran.r-project.org/package=statcanR)
15 |
16 |
17 |
18 | # Overview
19 |
20 | Easily connect to Statistics Canada’s Web Data Service with R. Find and
21 | access open economic data (formerly known as CANSIM tables, now identified by
22 | Product IDs (PID)) which are accessible as a data frame, directly in the
23 | user’s R environment.
24 |
25 |
26 |
27 | ## Shiny App : statcanR ExploR
28 |
29 |
30 |
31 | For people less comfortable with R and to allow more people to have
32 | access to our package, we have also developed a Shiny
33 | application.Through the same logic present in our package, researchers
34 | can retrieve data from Statistics Canada.
35 |
36 | statcanR ExploR is available [\[here\]](https://warin.ca/shiny/statcanr/)
37 |
38 | ## Installation
39 |
40 | The released version of statcanR package is accessible through CRAN and
41 | devtools.
42 |
43 | ``` r
44 | install.packages("statcanR")
45 |
46 | install.packages("devtools")
47 | devtools::install_github('warint/statcanR')
48 | ```
49 |
50 | ## Example
51 |
52 | This section presents an example of how to use the `statcanR` R package
53 | and its functions: `statcan_search()`, `statcan_data()`, and
54 | `statcan_download_data()`.
55 |
56 | The following example is provided to illustrate how to use the
57 | functions. It consists in collecting some descriptive statistics about
58 | the Canadian Labour Force at the federal, provincial and industrial
59 | levels, on a monthly basis.
60 |
61 | To identify a relevant table, the statcan_search() function can be used
62 | by using a keyword or set of keywords and specifying the language in which the
63 | data will be presented (English or French). Below is an example that reveals
64 | the data tables we could be interested in:
65 |
66 | ``` r
67 | library(statcanR)
68 | statcan_search(c("federal","expenditures","objectives"),"eng")
69 | ```
70 |
71 | Notice that for each corresponding table, the unique table number identifier is
72 | also presented. Let's focus the first table out of the two that appear, which
73 | contains data on Federal expenditures on science and technology,
74 | by socio-economic objectives. Once this table number is identified
75 | (‘27-10-0014-01’), the statcan_data() function is easy
76 | to use in order to collect the data, as following:
77 |
78 | ``` r
79 | library(statcanR)
80 | mydata <- statcan_data("27-10-0014-01","eng")
81 | ```
82 |
83 | For the `statcan_download_data()` function there is no difference on how
84 | to use it, the only difference is that this function allow you to
85 | download the data in a csv file on top of having the data in your
86 | environment.
87 |
88 | ``` r
89 | library(statcanR)
90 | mydata <- statcan_download_data("27-10-0014-01","eng")
91 | ```
92 |
93 | ### Video Tutorial
94 |
95 | Tutorial made by Professor Charles Saunders, Director of Master of
96 | Financial Economics Program at Western University
97 | [biography](https://economics.uwo.ca/people/faculty/saunders.html)
98 |
99 | Thanks!
100 |
101 |
102 |
103 | ### Statistics Canada Open Licence
104 |
105 | This licence is issued on behalf of His Majesty the King in Right of
106 | Canada, as represented by the Minister for Statistics Canada
107 | (“Statistics Canada”) to you (an individual or a legal entity that you
108 | are authorized to represent).
109 |
110 | Statistics Canada may modify this licence at any time, and such
111 | modifications shall be effective immediately upon posting of the
112 | modified licence on the Statistics Canada website. Your use of the
113 | Information will be governed by the terms of the licence in force as of
114 | the date and time you accessed the Information.
115 |
116 | Please refer to the [terms of
117 | licence](https://www.statcan.gc.ca/eng/reference/licence) before using
118 | the Information.
119 |
120 | ##### Acknowledgment of Source according to Statistics Canada Open Licence Agreement
121 |
122 | Statistics Canada has a specific procedure regarding the acknowledgment
123 | of source :
124 |
125 | You shall include and maintain the following notice on all licensed
126 | rights of the Information:
127 |
128 | Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
129 |
130 | Where any Information is contained within a Value-added Product, you
131 | shall include on such Value-added Product the following notice:
132 |
133 | Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.
134 |
135 | ### Cite statcanR
136 |
137 | To cite statcanR package in your work:
138 |
139 | Warin, T. (2024). Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses. Technology Innovations in Statistics Education, 15(1). http://dx.doi.org/10.5070/T5.1868 Retrieved from https://escholarship.org/uc/item/9jr7k5hp
140 |
141 | ``` r
142 | @article{warin_access_2024,
143 | title = {Access {Statistics} {Canada}’s {Open} {Economic} {Data} for {Statistics} and {Data} {Science} {Courses}},
144 | volume = {15},
145 | url = {https://escholarship.org/uc/item/9jr7k5hp},
146 | doi = {10.5070/T5.1868},
147 | abstract = {This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy.},
148 | language = {en},
149 | number = {1},
150 | urldate = {2024-01-17},
151 | journal = {Technology Innovations in Statistics Education},
152 | author = {Warin, Thierry},
153 | month = jan,
154 | year = {2024},
155 | file = {Full Text PDF:/Users/thierrywarin/Zotero/storage/7LNXFPKL/Warin - 2024 - Access Statistics Canada’s Open Economic Data for .pdf:application/pdf},
156 | }
157 | ```
158 |
159 | ### Acknowledgments
160 |
161 | A previous version of this package was developed with Romain Le Duc. This version has benefitted from Thibault Senegas's contribution. The author would like to thank the Center for Interuniversity Research and Analysis of Organizations (CIRANO, Montreal) for its support, as well as Thibault Senegas, Jeremy Schneider, Marine Leroi, Martin Paquette and Romain Le Duc. However, errors and omissions are his.
162 |
163 |
164 | ### Contributing to the package
165 | #### Bug reports
166 |
167 | When you file a bug report, please spend some time making it easy for me to follow and reproduce. The more time you spend on making the bug report coherent, the more time I can dedicate to investigate the bug as opposed to the bug report.
168 |
169 | ##### Contributing to the package development
170 |
171 | To get started, consider either adding a new example or enhancing the existing documentation.
172 |
173 | If you're interested in submitting a Pull Request to include your own functions, please include the following:
174 |
175 | - The code for the new function(s), complete with roxygen annotations and sample usage.
176 | - A dedicated section in the relevant vignette that explains how to utilize the new function.
177 |
178 | To ensure your changes are compliant, run rhub::check_for_cran() using rhub. After submission, your Pull Request will undergo automated evaluation via GitHub Actions, allowing you to monitor for any issues.
179 |
180 |
--------------------------------------------------------------------------------
/vignettes/statCanR.Rmd:
--------------------------------------------------------------------------------
1 | ---
2 | title: "statCanR"
3 | author: "Thierry Warin"
4 | data: "`r Sys.Date()`"
5 | output: rmarkdown::html_vignette
6 | vignette: >
7 | %\VignetteIndexEntry{statCanR}
8 | %\VignetteEngine{knitr::rmarkdown}
9 | %\VignetteEncoding{UTF-8}
10 | ---
11 |
12 | ```{r, include = FALSE}
13 | knitr::opts_chunk$set(
14 | collapse = TRUE,
15 | comment = "#>"
16 | )
17 | ```
18 |
19 | ```{r setup}
20 | library(statcanR)
21 | ```
22 |
23 |
24 | ## Overview
25 |
26 | statcanR provides the R user with a consistent process to identify and collect data from Statistics Canada's data portal. It allows users to search for and access all of Statistics Canada' open economic data (formerly known as CANSIM tables) now identified by product IDs (PID) by the new Statistics Canada's Web Data Service: .
27 |
28 | ## Quick start
29 |
30 | First, install statcanR:
31 |
32 | ```{r, eval=FALSE}
33 | devtools::install_github("warint/statcanR")
34 | ```
35 |
36 |
37 | Next, call statcanR to make sure everything is installed correctly.
38 |
39 | ```{r}
40 | library(statcanR)
41 | ```
42 |
43 | # Practical usage
44 |
45 | This section presents an example of how to use the statcanR R package and its functions: statcan_search() and statcan_data().
46 |
47 |
48 | The following example is provided to illustrate how to use these functions. It consists of collecting some descriptive statistics about the Canadian labour force at the federal, provincial and industrial levels, on a monthly basis.
49 |
50 | To identify a relevant table, the statcan_search() function can be used
51 | by using a keyword or set of keywords, depending on the language the user wishes to search in (between English and French). Below is an example that reveals
52 | the data tables we could be interested in:
53 |
54 | ```{r, eval=FALSE}
55 | # Identify with statcan_search() function
56 | statcan_search(c("federal","expenditures"),"eng")
57 | ```
58 |
59 |
60 | Notice that for each corresponding table, the unique table number identifier is also presented. Let's focus on the first table out of the two that appear, which contains data on Federal expenditures on science and technology, by socio-economic objectives. Once this table number is identified
61 | (‘27-10-0014-01’), the statcan_data() function is easy to use in order to collect the data, as following:
62 |
63 | ```{r, eval=FALSE}
64 | # Get data with statcan_data function
65 | mydata <- statcan_download_data("27-10-0014-01", "eng")
66 | ```
67 |
68 | Should you want the same data in French, just replace the argument at the end of the function with "fra".
69 |
70 | ## Code architecture
71 |
72 | This section describes the code architecture of the statcanR package.
73 |
74 | The statcan_search() function has 2 arguments:
75 |
76 | 1. keywords
77 | 2. lang
78 |
79 | The 'keywords' argument is useful for identifying what kind of open economic data Statistics Canada has available for users. It can take as inputs either a single word (i.e., statcan_search("expenditures")) or a vector of multiple keywords (such as: statcan_search(c("expenditures","federal","objectives"))).
80 |
81 | The second argument, 'lang', refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages. Therefore, users can see what data tables are available in French or English by setting the lang argument with c("fra", "eng").
82 |
83 |
84 |
85 |
86 | For all data tables that contain these words in either their title or description, the resulting output will include four pieces of information: The name of the data table, its unique table number identifier, the description, and the release date.
87 | In details, the statcan_download_data() function has 2 arguments:
88 |
89 | 1. tableNumber
90 | 2. lang
91 |
92 |
93 | The 'tableNumber' argument simply refers to the table number of the Statistics Canada data table a user wants to collect, such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
94 |
95 |
96 | Just as in the statcan_search() command, 'lang', refers to the language, and can be set to "eng" for English or "fra" for French. Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c("fra", "eng").
97 |
98 | The code architecture of the statcan_download_data() function is as follows. The first step if to clean the table number in order to align it with the official typology of Statistics Canada's Web Data Service. The second step is to create a temporary folder where all the data wrangling operations are performed. The third step is to check and select the correct language. The fourth step is to define the right URL where the actual data table is stored and then to download the .Zip container. The fifth step is to unzip the previously downloaded .Zip file to extract the data and metadata from the .csv files. The final step is to load the statistics data into a data frame called 'data' and to add the official table indicator name in the new 'INDICATOR' column.
99 |
100 |
101 | To be more precise about the functions, below is some further code description:
102 |
103 | ### statcan_search()
104 |
105 | - ` keyword_regex <- paste0("(", paste(keywords, collapse = "|"), ")", collapse = ".*")`:
106 | The first step is to paste (either individually or in vector format) the keywords the user is interested in
107 |
108 | - ` matches <- apply(statcan_data, 1, function(row) {`
109 | ` all(sapply(keywords, function(x) {`
110 | ` grepl(x, paste(as.character(row), collapse = " "))`
111 | ` }))`
112 | ` }) `:
113 | Next, the matching relies on the sapply function, which is applied to any character string in a row of a given observation. Therefore, the "keyword" could be found in the title column or the description column (technically, it could even be in the "release date" or "id" columns).
114 |
115 | - ` filtered_data <- statcan_data[matches, ]`
116 | The third step takes only the data where matches were found.
117 |
118 | - ` datatable(filtered_data, options = list(pageLength = 10))`
119 | Finally, the datatable command presents the filtered data in a clean table.
120 |
121 |
122 |
123 | ### statcan_download_data()
124 |
125 | - `tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber)-2))`:
126 | The first step is to clean the table number provided by the user in order to collect the overall data table related to the specific indicator the user is interested in. In fact, each indicator is an excerpt of the overall table.
127 | In addition, following the new Statistics Canada's Web Data Service, the URL typology defined by REST API is stored in csv files by table numbers without a '-'. Also, the last 2 digits after the last '-' refer to the specific excerpt of the original table.
128 | Therefore, following the Statistics Canada Web Data Service's typology, the function first removes the '-' and the last 2 digits from the user's selection.
129 |
130 | - `if(lang == "eng")` | `if(lang == "fra")`:
131 | The second step is the 'if statement' to get the data in the correct language.
132 |
133 | - `urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/", tableNumber, "-fra.zip")`:
134 | The third step is to create the correct url in order to download the respective .Zip file from the Statistics Canada Web Data Service.
135 |
136 | - `download(urlFra, download_dir, mode = "wb")`:
137 | The fourth step is a simple downloading function that extracts .Zip file and download it into a temporary folder.
138 |
139 | - `unzip(zipfile = download_dir, exdir = unzip_dir)`:
140 | The fifth step consists in unzipping the .Zip file. The unzipping process gives access to two different .csv files, such as the overall data table and the metadata table.
141 |
142 | - `data.table::fread(csv_file)`:
143 | The sixth step consists in loading the data table into a unique data frame. The fread() function from the data.table package is used for its higher performance.
144 |
145 | - `data$INDICATOR <- as.character(0)` and `data$INDICATOR <- as.character(read.csv(paste0(path,"/temp/", tableNumber, "_MetaData.csv"))[1,1])`:
146 | The seventh step of the statcan_data() function consists in adding the name of the table from the metadata table.
147 |
148 | - `unlink(tempdir())`:
149 | The eighth step deletes the temporary folder used to download, unzip, extract and load the data.
150 |
151 | - `return(Data)`:
152 | Finally, the last step of the statcan_data() function allows to return the value into the user's environment.
153 |
154 |
155 |
156 |
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/docs/reference/statcan_download_data.html:
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1 |
2 | statcanR download data function — statcan_download_data • statcanR
6 |
7 |
8 |
9 |
53 |
54 |
55 |
56 |
57 |
58 |
63 |
64 |
65 | statcanR download data function
66 |
67 |
68 |
69 | statcan_download_data(tableNumber, lang)
70 |
71 |
72 |
73 | Arguments
74 | - tableNumber
75 | The table number of the Statistics Canada data table
- lang
79 | The language wanted
82 |
83 | Value
84 |
85 |
86 | The output will be a data table and csv file representing the data associated with the chosen table number.
87 |
88 |
89 |
90 | Examples
91 | mydata <- statcan_data('27-10-0014-01', 'eng')
92 | #> statcanR: downloading remote table.
93 | #> Warning: One or more parsing issues, call `problems()` on your data frame for details,
94 | #> e.g.:
95 | #> dat <- vroom(...)
96 | #> problems(dat)
97 | #> Rows: 61 Columns: 10
98 | #> ── Column specification ────────────────────────────────────────────────────────
99 | #> Delimiter: ","
100 | #> chr (8): Cube Title, Product Id, CANSIM Id, URL, Cube Notes, Archive Status...
101 | #> num (1): Total number of dimensions
102 | #> date (1): End Reference Period
103 | #>
104 | #> ℹ Use `spec()` to retrieve the full column specification for this data.
105 | #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
106 |
107 |
108 |
109 |
112 |
113 |
114 |
115 |
124 |
125 |
126 |
127 |
128 |
129 |
130 |
131 |
132 |
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1 | /* Sticky footer */
2 |
3 | /**
4 | * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
5 | * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
6 | *
7 | * .Site -> body > .container
8 | * .Site-content -> body > .container .row
9 | * .footer -> footer
10 | *
11 | * Key idea seems to be to ensure that .container and __all its parents__
12 | * have height set to 100%
13 | *
14 | */
15 |
16 | html, body {
17 | height: 100%;
18 | }
19 |
20 | body {
21 | position: relative;
22 | }
23 |
24 | body > .container {
25 | display: flex;
26 | height: 100%;
27 | flex-direction: column;
28 | }
29 |
30 | body > .container .row {
31 | flex: 1 0 auto;
32 | }
33 |
34 | footer {
35 | margin-top: 45px;
36 | padding: 35px 0 36px;
37 | border-top: 1px solid #e5e5e5;
38 | color: #666;
39 | display: flex;
40 | flex-shrink: 0;
41 | }
42 | footer p {
43 | margin-bottom: 0;
44 | }
45 | footer div {
46 | flex: 1;
47 | }
48 | footer .pkgdown {
49 | text-align: right;
50 | }
51 | footer p {
52 | margin-bottom: 0;
53 | }
54 |
55 | img.icon {
56 | float: right;
57 | }
58 |
59 | /* Ensure in-page images don't run outside their container */
60 | .contents img {
61 | max-width: 100%;
62 | height: auto;
63 | }
64 |
65 | /* Fix bug in bootstrap (only seen in firefox) */
66 | summary {
67 | display: list-item;
68 | }
69 |
70 | /* Typographic tweaking ---------------------------------*/
71 |
72 | .contents .page-header {
73 | margin-top: calc(-60px + 1em);
74 | }
75 |
76 | dd {
77 | margin-left: 3em;
78 | }
79 |
80 | /* Section anchors ---------------------------------*/
81 |
82 | a.anchor {
83 | display: none;
84 | margin-left: 5px;
85 | width: 20px;
86 | height: 20px;
87 |
88 | background-image: url(./link.svg);
89 | background-repeat: no-repeat;
90 | background-size: 20px 20px;
91 | background-position: center center;
92 | }
93 |
94 | h1:hover .anchor,
95 | h2:hover .anchor,
96 | h3:hover .anchor,
97 | h4:hover .anchor,
98 | h5:hover .anchor,
99 | h6:hover .anchor {
100 | display: inline-block;
101 | }
102 |
103 | /* Fixes for fixed navbar --------------------------*/
104 |
105 | .contents h1, .contents h2, .contents h3, .contents h4 {
106 | padding-top: 60px;
107 | margin-top: -40px;
108 | }
109 |
110 | /* Navbar submenu --------------------------*/
111 |
112 | .dropdown-submenu {
113 | position: relative;
114 | }
115 |
116 | .dropdown-submenu>.dropdown-menu {
117 | top: 0;
118 | left: 100%;
119 | margin-top: -6px;
120 | margin-left: -1px;
121 | border-radius: 0 6px 6px 6px;
122 | }
123 |
124 | .dropdown-submenu:hover>.dropdown-menu {
125 | display: block;
126 | }
127 |
128 | .dropdown-submenu>a:after {
129 | display: block;
130 | content: " ";
131 | float: right;
132 | width: 0;
133 | height: 0;
134 | border-color: transparent;
135 | border-style: solid;
136 | border-width: 5px 0 5px 5px;
137 | border-left-color: #cccccc;
138 | margin-top: 5px;
139 | margin-right: -10px;
140 | }
141 |
142 | .dropdown-submenu:hover>a:after {
143 | border-left-color: #ffffff;
144 | }
145 |
146 | .dropdown-submenu.pull-left {
147 | float: none;
148 | }
149 |
150 | .dropdown-submenu.pull-left>.dropdown-menu {
151 | left: -100%;
152 | margin-left: 10px;
153 | border-radius: 6px 0 6px 6px;
154 | }
155 |
156 | /* Sidebar --------------------------*/
157 |
158 | #pkgdown-sidebar {
159 | margin-top: 30px;
160 | position: -webkit-sticky;
161 | position: sticky;
162 | top: 70px;
163 | }
164 |
165 | #pkgdown-sidebar h2 {
166 | font-size: 1.5em;
167 | margin-top: 1em;
168 | }
169 |
170 | #pkgdown-sidebar h2:first-child {
171 | margin-top: 0;
172 | }
173 |
174 | #pkgdown-sidebar .list-unstyled li {
175 | margin-bottom: 0.5em;
176 | }
177 |
178 | /* bootstrap-toc tweaks ------------------------------------------------------*/
179 |
180 | /* All levels of nav */
181 |
182 | nav[data-toggle='toc'] .nav > li > a {
183 | padding: 4px 20px 4px 6px;
184 | font-size: 1.5rem;
185 | font-weight: 400;
186 | color: inherit;
187 | }
188 |
189 | nav[data-toggle='toc'] .nav > li > a:hover,
190 | nav[data-toggle='toc'] .nav > li > a:focus {
191 | padding-left: 5px;
192 | color: inherit;
193 | border-left: 1px solid #878787;
194 | }
195 |
196 | nav[data-toggle='toc'] .nav > .active > a,
197 | nav[data-toggle='toc'] .nav > .active:hover > a,
198 | nav[data-toggle='toc'] .nav > .active:focus > a {
199 | padding-left: 5px;
200 | font-size: 1.5rem;
201 | font-weight: 400;
202 | color: inherit;
203 | border-left: 2px solid #878787;
204 | }
205 |
206 | /* Nav: second level (shown on .active) */
207 |
208 | nav[data-toggle='toc'] .nav .nav {
209 | display: none; /* Hide by default, but at >768px, show it */
210 | padding-bottom: 10px;
211 | }
212 |
213 | nav[data-toggle='toc'] .nav .nav > li > a {
214 | padding-left: 16px;
215 | font-size: 1.35rem;
216 | }
217 |
218 | nav[data-toggle='toc'] .nav .nav > li > a:hover,
219 | nav[data-toggle='toc'] .nav .nav > li > a:focus {
220 | padding-left: 15px;
221 | }
222 |
223 | nav[data-toggle='toc'] .nav .nav > .active > a,
224 | nav[data-toggle='toc'] .nav .nav > .active:hover > a,
225 | nav[data-toggle='toc'] .nav .nav > .active:focus > a {
226 | padding-left: 15px;
227 | font-weight: 500;
228 | font-size: 1.35rem;
229 | }
230 |
231 | /* orcid ------------------------------------------------------------------- */
232 |
233 | .orcid {
234 | font-size: 16px;
235 | color: #A6CE39;
236 | /* margins are required by official ORCID trademark and display guidelines */
237 | margin-left:4px;
238 | margin-right:4px;
239 | vertical-align: middle;
240 | }
241 |
242 | /* Reference index & topics ----------------------------------------------- */
243 |
244 | .ref-index th {font-weight: normal;}
245 |
246 | .ref-index td {vertical-align: top; min-width: 100px}
247 | .ref-index .icon {width: 40px;}
248 | .ref-index .alias {width: 40%;}
249 | .ref-index-icons .alias {width: calc(40% - 40px);}
250 | .ref-index .title {width: 60%;}
251 |
252 | .ref-arguments th {text-align: right; padding-right: 10px;}
253 | .ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
254 | .ref-arguments .name {width: 20%;}
255 | .ref-arguments .desc {width: 80%;}
256 |
257 | /* Nice scrolling for wide elements --------------------------------------- */
258 |
259 | table {
260 | display: block;
261 | overflow: auto;
262 | }
263 |
264 | /* Syntax highlighting ---------------------------------------------------- */
265 |
266 | pre, code, pre code {
267 | background-color: #f8f8f8;
268 | color: #333;
269 | }
270 | pre, pre code {
271 | white-space: pre-wrap;
272 | word-break: break-all;
273 | overflow-wrap: break-word;
274 | }
275 |
276 | pre {
277 | border: 1px solid #eee;
278 | }
279 |
280 | pre .img, pre .r-plt {
281 | margin: 5px 0;
282 | }
283 |
284 | pre .img img, pre .r-plt img {
285 | background-color: #fff;
286 | }
287 |
288 | code a, pre a {
289 | color: #375f84;
290 | }
291 |
292 | a.sourceLine:hover {
293 | text-decoration: none;
294 | }
295 |
296 | .fl {color: #1514b5;}
297 | .fu {color: #000000;} /* function */
298 | .ch,.st {color: #036a07;} /* string */
299 | .kw {color: #264D66;} /* keyword */
300 | .co {color: #888888;} /* comment */
301 |
302 | .error {font-weight: bolder;}
303 | .warning {font-weight: bolder;}
304 |
305 | /* Clipboard --------------------------*/
306 |
307 | .hasCopyButton {
308 | position: relative;
309 | }
310 |
311 | .btn-copy-ex {
312 | position: absolute;
313 | right: 0;
314 | top: 0;
315 | visibility: hidden;
316 | }
317 |
318 | .hasCopyButton:hover button.btn-copy-ex {
319 | visibility: visible;
320 | }
321 |
322 | /* headroom.js ------------------------ */
323 |
324 | .headroom {
325 | will-change: transform;
326 | transition: transform 200ms linear;
327 | }
328 | .headroom--pinned {
329 | transform: translateY(0%);
330 | }
331 | .headroom--unpinned {
332 | transform: translateY(-100%);
333 | }
334 |
335 | /* mark.js ----------------------------*/
336 |
337 | mark {
338 | background-color: rgba(255, 255, 51, 0.5);
339 | border-bottom: 2px solid rgba(255, 153, 51, 0.3);
340 | padding: 1px;
341 | }
342 |
343 | /* vertical spacing after htmlwidgets */
344 | .html-widget {
345 | margin-bottom: 10px;
346 | }
347 |
348 | /* fontawesome ------------------------ */
349 |
350 | .fab {
351 | font-family: "Font Awesome 5 Brands" !important;
352 | }
353 |
354 | /* don't display links in code chunks when printing */
355 | /* source: https://stackoverflow.com/a/10781533 */
356 | @media print {
357 | code a:link:after, code a:visited:after {
358 | content: "";
359 | }
360 | }
361 |
362 | /* Section anchors ---------------------------------
363 | Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
364 | */
365 |
366 | div.csl-bib-body { }
367 | div.csl-entry {
368 | clear: both;
369 | }
370 | .hanging-indent div.csl-entry {
371 | margin-left:2em;
372 | text-indent:-2em;
373 | }
374 | div.csl-left-margin {
375 | min-width:2em;
376 | float:left;
377 | }
378 | div.csl-right-inline {
379 | margin-left:2em;
380 | padding-left:1em;
381 | }
382 | div.csl-indent {
383 | margin-left: 2em;
384 | }
385 |
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/docs/reference/statcan_search.html:
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1 |
2 | Searching function for statcanR — statcan_search • statcanR
9 |
10 |
11 |
12 |
56 |
57 |
58 |
59 |
60 |
61 |
66 |
67 |
68 | The statcan_search() function has 2 arguments to fulfill to find a database: keywords and lang.
69 | The keywords argument refers to words that can be found in either the title or the description of the database. For example, inserting the keywords
70 | "economy","export",and "link" will bring up the title, table id, description, and release date for databases that include these keywords. In this case, only one data table ("Supply and use tables, link-1997 level")
71 | would be returned as it is the only data table containing all three words.
72 |
73 |
74 |
75 | statcan_search(keywords, lang)
76 |
77 |
78 |
79 | Arguments
80 | - keywords
81 | The words that appear in the title or description of the data table
- lang
85 | The language wanted
88 |
89 | Value
90 |
91 |
92 | The output will be the title, id, description, and release date of a table
93 |
94 |
95 | Details
96 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
97 |
98 |
99 |
100 | Examples
101 | statcan_search(c("economy","export","link"),"eng")
102 |
103 |
104 |
105 |
106 |
109 |
110 |
111 |
112 |
121 |
122 |
123 |
124 |
125 |
126 |
127 |
128 |
129 |
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1 | /* Docsearch -------------------------------------------------------------- */
2 | /*
3 | Source: https://github.com/algolia/docsearch/
4 | License: MIT
5 | */
6 |
7 | .algolia-autocomplete {
8 | display: block;
9 | -webkit-box-flex: 1;
10 | -ms-flex: 1;
11 | flex: 1
12 | }
13 |
14 | .algolia-autocomplete .ds-dropdown-menu {
15 | width: 100%;
16 | min-width: none;
17 | max-width: none;
18 | padding: .75rem 0;
19 | background-color: #fff;
20 | background-clip: padding-box;
21 | border: 1px solid rgba(0, 0, 0, .1);
22 | box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
23 | }
24 |
25 | @media (min-width:768px) {
26 | .algolia-autocomplete .ds-dropdown-menu {
27 | width: 175%
28 | }
29 | }
30 |
31 | .algolia-autocomplete .ds-dropdown-menu::before {
32 | display: none
33 | }
34 |
35 | .algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
36 | padding: 0;
37 | background-color: rgb(255,255,255);
38 | border: 0;
39 | max-height: 80vh;
40 | }
41 |
42 | .algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
43 | margin-top: 0
44 | }
45 |
46 | .algolia-autocomplete .algolia-docsearch-suggestion {
47 | padding: 0;
48 | overflow: visible
49 | }
50 |
51 | .algolia-autocomplete .algolia-docsearch-suggestion--category-header {
52 | padding: .125rem 1rem;
53 | margin-top: 0;
54 | font-size: 1.3em;
55 | font-weight: 500;
56 | color: #00008B;
57 | border-bottom: 0
58 | }
59 |
60 | .algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
61 | float: none;
62 | padding-top: 0
63 | }
64 |
65 | .algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
66 | float: none;
67 | width: auto;
68 | padding: 0;
69 | text-align: left
70 | }
71 |
72 | .algolia-autocomplete .algolia-docsearch-suggestion--content {
73 | float: none;
74 | width: auto;
75 | padding: 0
76 | }
77 |
78 | .algolia-autocomplete .algolia-docsearch-suggestion--content::before {
79 | display: none
80 | }
81 |
82 | .algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
83 | padding-top: .75rem;
84 | margin-top: .75rem;
85 | border-top: 1px solid rgba(0, 0, 0, .1)
86 | }
87 |
88 | .algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
89 | display: block;
90 | padding: .1rem 1rem;
91 | margin-bottom: 0.1;
92 | font-size: 1.0em;
93 | font-weight: 400
94 | /* display: none */
95 | }
96 |
97 | .algolia-autocomplete .algolia-docsearch-suggestion--title {
98 | display: block;
99 | padding: .25rem 1rem;
100 | margin-bottom: 0;
101 | font-size: 0.9em;
102 | font-weight: 400
103 | }
104 |
105 | .algolia-autocomplete .algolia-docsearch-suggestion--text {
106 | padding: 0 1rem .5rem;
107 | margin-top: -.25rem;
108 | font-size: 0.8em;
109 | font-weight: 400;
110 | line-height: 1.25
111 | }
112 |
113 | .algolia-autocomplete .algolia-docsearch-footer {
114 | width: 110px;
115 | height: 20px;
116 | z-index: 3;
117 | margin-top: 10.66667px;
118 | float: right;
119 | font-size: 0;
120 | line-height: 0;
121 | }
122 |
123 | .algolia-autocomplete .algolia-docsearch-footer--logo {
124 | background-image: url("data:image/svg+xml;utf8,");
125 | background-repeat: no-repeat;
126 | background-position: 50%;
127 | background-size: 100%;
128 | overflow: hidden;
129 | text-indent: -9000px;
130 | width: 100%;
131 | height: 100%;
132 | display: block;
133 | transform: translate(-8px);
134 | }
135 |
136 | .algolia-autocomplete .algolia-docsearch-suggestion--highlight {
137 | color: #FF8C00;
138 | background: rgba(232, 189, 54, 0.1)
139 | }
140 |
141 |
142 | .algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
143 | box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
144 | }
145 |
146 | .algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
147 | background-color: rgba(192, 192, 192, .15)
148 | }
149 |
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1 | #' statcanR
2 | #'
3 | #'
4 | #' Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
5 | #'
6 | #' The
7 | #' \code{statcan_data()} function has 2 arguments to fulfill to get data: {tableNumber} & {lang}.
8 | #'
9 | #'
10 | #' The tableNumber argument simply refers to the table number of the Statistics Canada data table a user wants to collect,
11 | #' such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
12 | #'
13 | #'
14 | #' To get the table number: \url{https://www150.statcan.gc.ca/n1/en/type/data}.
15 | #'
16 | #' The second argument, lang, refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages.
17 | #' Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c('fra', 'eng').
18 | #'
19 | #'
20 | #'
21 | #' @param tableNumber The table number of the Statistics Canada data table
22 | #' @param lang The language wanted
23 | #'
24 | #' @return The output will be a data table representing the data associated with the chosen table number.
25 | #' @export
26 | #'
27 | #' @import curl
28 | #' @import tibble
29 | #' @import qpdf
30 | #' @importFrom httr http_error
31 | #' @importFrom data.table fread
32 | #' @importFrom data.table setDF
33 | #'
34 | #' @examples
35 | #' #mydata <- statcan_data('27-10-0014-01', 'eng')
36 | #'
37 |
38 |
39 | # Scraping function for statcan
40 | statcan_data <- function(tableNumber, lang)
41 | {
42 |
43 | # identifying the table number
44 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber) -
45 | 2))
46 |
47 | # getting data in English version
48 | if (lang == "eng")
49 | {
50 | # downloading the data file in English version
51 | urlEng <- paste0("https://www150.statcan.gc.ca/n1/en/tbl/csv/",
52 | tableNumber, "-eng.zip")
53 |
54 | download_dir <- file.path(tempdir(), "datasetEng.zip")
55 |
56 | #utils::download.file(urlEng, download_dir, method = "curl")
57 | #data.table::fread(input = urlEng, file = download_dir)
58 | #RCurl::getURL(urlEng, ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
59 | #curl::curl_download(urlEng, download_dir)
60 |
61 | if (httr::http_error(urlEng)) { # network is down = message (not an error anymore)
62 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
63 | #return(NULL)
64 | } else { # network is up = proceed to download via curl
65 | message("statcanR: downloading remote table.")
66 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlEng, download_dir))
67 |
68 |
69 | # unziping the downloaded data file in English version
70 | unzip_dir <- file.path(paste0(tempdir(), "/"))
71 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
72 | unlink(download_dir)
73 |
74 | # loading the data file in English version
75 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
76 | can_data <- data.table::fread(csv_file)
77 |
78 | # adding to the data.frame or data.table the Official Data Table
79 | # Indicator defined by Statistics Canada and based on metadata file.
80 | can_data$INDICATOR <- as.character(0)
81 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
82 | can_data$INDICATOR <- as.character(readr::read_csv(paste0(tempdir(),
83 | "/", tableNumber, "_MetaData.csv"))[1, 1])
84 |
85 | if(nchar(can_data[1,1])==9){
86 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
87 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
88 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
89 | }
90 |
91 | else if(nchar(can_data[1,1])==7){
92 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
93 | }
94 |
95 | else if(nchar(can_data[1,1])==4){
96 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
97 | }
98 |
99 | else{
100 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
101 | }
102 |
103 | # creating a data frame
104 | data.table::setDF(return(can_data))
105 |
106 | } # /if - network up or down
107 |
108 | }
109 |
110 | # getting data in French version
111 | if (lang == "fra")
112 | {
113 | # downloading the data file in French version
114 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/",
115 | tableNumber, "-fra.zip")
116 |
117 | download_dir <- file.path(tempdir(), "datasetFra.zip")
118 | #utils::download.file(urlFra, download_dir, method = "curl")
119 | #data.table::fread(urlFra, download_dir)
120 | #curl::curl_download(urlFra, download_dir)
121 |
122 | if (httr::http_error(urlFra)) { # network is down = message (not an error anymore)
123 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
124 | return(NULL)
125 | } else { # network is up = proceed to download via curl
126 | message("statcanR: downloading remote table.")
127 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlFra, download_dir))
128 |
129 |
130 | # unzipping the downloaded data file in French version
131 | unzip_dir <- file.path(paste0(tempdir(), "/"))
132 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
133 | unlink(download_dir)
134 |
135 | # loading the data file in French version
136 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
137 | can_data <- data.table::fread(csv_file)
138 |
139 | # adding to the data.frame or data.table the Official Data Table
140 | # Indicator defined by Statitics Canada and based on metadata file.
141 | can_data$INDICATOR <- as.character(0)
142 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
143 | can_data$INDICATOR <- as.character(readr::read_delim(paste0(tempdir(),
144 | "/", tableNumber, "_MetaData.csv"), delim = ";", escape_double = FALSE, trim_ws = TRUE)[1, 1])
145 |
146 | can_data[,1] <- "REF_DATE"
147 |
148 | if(nchar(can_data[1,1])==9){
149 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
150 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
151 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
152 | }
153 |
154 | else if(nchar(can_data[1,1])==7){
155 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
156 | }
157 |
158 | else if(nchar(can_data[1,1])==4){
159 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
160 | }
161 |
162 | else{
163 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
164 | }
165 |
166 | # creating a data frame
167 | data.table::setDF(return(can_data))
168 | } # /if - network up or down
169 |
170 | }
171 |
172 |
173 | # removing the temp folder and creating a data frame
174 | unlink(tempdir())
175 |
176 | }
177 |
178 | #' statcanR download data function
179 | #'
180 | #' @param tableNumber The table number of the Statistics Canada data table
181 | #' @param lang The language wanted
182 | #'
183 | #' @return The output will be a data table and csv file representing the data associated with the chosen table number.
184 | #' @export
185 | #'
186 | #'
187 | #' @import curl
188 | #' @import tibble
189 | #' @importFrom httr http_error
190 | #' @importFrom data.table fread
191 | #' @importFrom data.table setDF
192 | #'
193 | #' @examples
194 | #' mydata <- statcan_data('27-10-0014-01', 'eng')
195 |
196 | # Download function for statcan
197 | statcan_download_data <- function(tableNumber, lang)
198 | {
199 |
200 | # identifying the table number
201 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber) -
202 | 2))
203 |
204 | # getting data in English version
205 | if (lang == "eng")
206 | {
207 | # downloading the data file in English version
208 | urlEng <- paste0("https://www150.statcan.gc.ca/n1/en/tbl/csv/",
209 | tableNumber, "-eng.zip")
210 |
211 | download_dir <- file.path(tempdir(), "datasetEng.zip")
212 | #utils::download.file(urlEng, download_dir, method = "curl")
213 | #data.table::fread(input = urlEng, file = download_dir)
214 | #RCurl::getURL(urlEng, ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
215 | #curl::curl_download(urlEng, download_dir)
216 |
217 | if (httr::http_error(urlEng)) { # network is down = message (not an error anymore)
218 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
219 | #return(NULL)
220 | } else { # network is up = proceed to download via curl
221 | message("statcanR: downloading remote table.")
222 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlEng, download_dir))
223 |
224 | # unziping the downloaded data file in English version
225 | unzip_dir <- file.path(paste0(tempdir(), "/"))
226 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
227 | unlink(download_dir)
228 |
229 | # loading the data file in English version
230 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
231 | can_data <- data.table::fread(csv_file)
232 |
233 | # adding to the data.frame or data.table the Official Data Table
234 | # Indicator defined by Statistics Canada and based on metadata file.
235 | can_data$INDICATOR <- as.character(0)
236 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
237 | can_data$INDICATOR <- as.character(readr::read_csv(paste0(tempdir(),
238 | "/", tableNumber, "_MetaData.csv"))[1, 1])
239 |
240 | if(nchar(can_data[1,1])==9){
241 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
242 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
243 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
244 | }
245 |
246 | else if(nchar(can_data[1,1])==7){
247 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
248 | }
249 |
250 | else if(nchar(can_data[1,1])==4){
251 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
252 | }
253 |
254 | else{
255 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
256 | }
257 | # creating a data frame
258 | data.table::setDF(return(can_data))
259 | readr::write_csv(can_data, paste0("./statcan_",tableNumber,"_", lang,".csv"))
260 |
261 | } # /if - network up or down
262 |
263 | }
264 |
265 | # getting data in French version
266 | if (lang == "fra")
267 | {
268 | # downloading the data file in French version
269 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/",
270 | tableNumber, "-fra.zip")
271 |
272 | download_dir <- file.path(tempdir(), "datasetFra.zip")
273 | #utils::download.file(urlFra, download_dir, method = "curl")
274 | #data.table::fread(urlFra, download_dir)
275 | #curl::curl_download(urlFra, download_dir)
276 |
277 | if (httr::http_error(urlFra)) { # network is down = message (not an error anymore)
278 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
279 | return(NULL)
280 | } else { # network is up = proceed to download via curl
281 | message("statcanR: downloading remote table.")
282 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlFra, download_dir))
283 |
284 |
285 |
286 | # unzipping the downloaded data file in French version
287 | unzip_dir <- file.path(paste0(tempdir(), "/"))
288 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
289 | unlink(download_dir)
290 |
291 | # loading the data file in French version
292 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
293 | can_data <- data.table::fread(csv_file)
294 |
295 | # adding to the data.frame or data.table the Official Data Table
296 | # Indicator defined by Statistics Canada and based on metadata file.
297 | can_data$INDICATOR <- as.character(0)
298 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
299 | can_data$INDICATOR <- as.character(readr::read_delim(paste0(tempdir(),
300 | "/", tableNumber, "_MetaData.csv"), delim = ";", escape_double = FALSE, trim_ws = TRUE)[1, 1])
301 |
302 | can_data[,1] <- "REF_DATE"
303 |
304 | if(nchar(can_data[1,1])==9){
305 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
306 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
307 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
308 | }
309 |
310 | else if(nchar(can_data[1,1])==7){
311 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
312 | }
313 |
314 | else if(nchar(can_data[1,1])==4){
315 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
316 | }
317 |
318 | else{
319 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
320 | }
321 | # creating a data frame
322 | data.table::setDF(return(can_data))
323 |
324 | readr::write_csv(can_data, paste0("./statcan_",tableNumber,"_", lang,".csv"))
325 | } # /if - network up or down
326 | }
327 |
328 | # removing the temp folder and creating a data frame
329 | unlink(tempdir())
330 | }
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8 | statCanR • statcanR
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84 | statCanR
85 | Thierry
86 | Warin
87 |
88 |
89 | Source: vignettes/statCanR.Rmd
90 | statCanR.Rmd
91 |
92 |
93 |
94 |
95 |
96 |
98 |
99 | Overview
100 |
101 | statcanR provides the R user with a consistent process to identify
102 | and collect data from Statistics Canada’s data portal. It allows users
103 | to search for and access all of Statistics Canada’ open economic data
104 | (formerly known as CANSIM tables) now identified by product IDs (PID) by
105 | the new Statistics Canada’s Web Data Service: https://www150.statcan.gc.ca/n1/en/type/data.
106 |
107 |
108 | Quick start
109 |
110 | First, install statcanR:
111 |
112 | devtools::install_github("warint/statcanR")
113 | Next, call statcanR to make sure everything is installed
114 | correctly.
115 |
117 |
118 |
119 | Practical usage
120 |
121 | This section presents an example of how to use the statcanR R package
122 | and its functions: statcan_search() and statcan_data().
123 | The following example is provided to illustrate how to use these
124 | functions. It consists of collecting some descriptive statistics about
125 | the Canadian labour force at the federal, provincial and industrial
126 | levels, on a monthly basis.
127 | To identify a relevant table, the statcan_search() function can be
128 | used by using a keyword or set of keywords, depending on the language
129 | the user wishes to search in (between English and French). Below is an
130 | example that reveals the data tables we could be interested in:
131 |
132 | # Identify with statcan_search() function
133 | statcan_search(c("federal","expenditures"),"eng")
134 | Notice that for each corresponding table, the unique table number
135 | identifier is also presented. Let’s focus on the first table out of the
136 | two that appear, which contains data on Federal expenditures on science
137 | and technology, by socio-economic objectives. Once this table number is
138 | identified (‘27-10-0014-01’), the statcan_data() function is easy to use
139 | in order to collect the data, as following:
140 |
141 | # Get data with statcan_data function
142 | mydata <- statcan_download_data("27-10-0014-01", "eng")
143 | Should you want the same data in French, just replace the argument at
144 | the end of the function with “fra”.
145 |
146 | Code architecture
147 |
148 | This section describes the code architecture of the statcanR
149 | package.
150 | The statcan_search() function has 2 arguments:
151 |
152 | - keywords
153 | - lang
154 |
155 | The ‘keywords’ argument is useful for identifying what kind of open
156 | economic data Statistics Canada has available for users. It can take as
157 | inputs either a single word (i.e., statcan_search(“expenditures”)) or a
158 | vector of multiple keywords (such as:
159 | statcan_search(c(“expenditures”,“federal”,“objectives”))).
160 | The second argument, ‘lang’, refers to the language. As Canada is a
161 | bilingual country, Statistics Canada displays all the economic data in
162 | both languages. Therefore, users can see what data tables are available
163 | in French or English by setting the lang argument with c(“fra”,
164 | “eng”).
165 | For all data tables that contain these words in either their title or
166 | description, the resulting output will include four pieces of
167 | information: The name of the data table, its unique table number
168 | identifier, the description, and the release date. In details, the
169 | statcan_download_data() function has 2 arguments:
170 |
171 | - tableNumber
172 | - lang
173 |
174 | The ‘tableNumber’ argument simply refers to the table number of the
175 | Statistics Canada data table a user wants to collect, such as
176 | ‘27-10-0014-01’ for the Federal expenditures on science and technology,
177 | by socio-economic objectives, as an example.
178 | Just as in the statcan_search() command, ‘lang’, refers to the
179 | language, and can be set to “eng” for English or “fra” for French.
180 | Therefore, users can choose to collect satistics data tables in French
181 | or English by setting the lang argument with c(“fra”, “eng”).
182 | The code architecture of the statcan_download_data() function is as
183 | follows. The first step if to clean the table number in order to align
184 | it with the official typology of Statistics Canada’s Web Data Service.
185 | The second step is to create a temporary folder where all the data
186 | wrangling operations are performed. The third step is to check and
187 | select the correct language. The fourth step is to define the right URL
188 | where the actual data table is stored and then to download the .Zip
189 | container. The fifth step is to unzip the previously downloaded .Zip
190 | file to extract the data and metadata from the .csv files. The final
191 | step is to load the statistics data into a data frame called ‘data’ and
192 | to add the official table indicator name in the new ‘INDICATOR’
193 | column.
194 | To be more precise about the functions, below is some further code
195 | description:
196 |
197 | statcan_search()
198 |
199 |
200 | keyword_regex <- paste0("(", paste(keywords, collapse = "|"), ")", collapse = ".*"):
201 | The first step is to paste (either individually or in vector format) the
202 | keywords the user is interested in
matches <- apply(statcan_data, 1, function(row) {
204 | all(sapply(keywords, function(x) {
205 | grepl(x, paste(as.character(row), collapse = " "))
206 | })) }): Next, the matching relies on the
207 | sapply function, which is applied to any character string in a row of a
208 | given observation. Therefore, the “keyword” could be found in the title
209 | column or the description column (technically, it could even be in the
210 | “release date” or “id” columns).
filtered_data <- statcan_data[matches, ] The
212 | third step takes only the data where matches were found.
datatable(filtered_data, options = list(pageLength = 10))
214 | Finally, the datatable command presents the filtered data in a clean
215 | table.
217 |
218 |
219 | statcan_download_data()
220 |
221 |
222 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber)-2)):
223 | The first step is to clean the table number provided by the user in
224 | order to collect the overall data table related to the specific
225 | indicator the user is interested in. In fact, each indicator is an
226 | excerpt of the overall table. In addition, following the new Statistics
227 | Canada’s Web Data Service, the URL typology defined by REST API is
228 | stored in csv files by table numbers without a ‘-’. Also, the last 2
229 | digits after the last ‘-’ refer to the specific excerpt of the original
230 | table. Therefore, following the Statistics Canada Web Data Service’s
231 | typology, the function first removes the ‘-’ and the last 2 digits from
232 | the user’s selection.
if(lang == "eng") | if(lang == "fra"):
234 | The second step is the ‘if statement’ to get the data in the correct
235 | language.
urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/", tableNumber, "-fra.zip"):
237 | The third step is to create the correct url in order to download the
238 | respective .Zip file from the Statistics Canada Web Data
239 | Service.
download(urlFra, download_dir, mode = "wb"): The
241 | fourth step is a simple downloading function that extracts .Zip file and
242 | download it into a temporary folder.
unzip(zipfile = download_dir, exdir = unzip_dir):
244 | The fifth step consists in unzipping the .Zip file. The unzipping
245 | process gives access to two different .csv files, such as the overall
246 | data table and the metadata table.
data.table::fread(csv_file): The sixth step consists
248 | in loading the data table into a unique data frame. The fread() function
249 | from the data.table package is used for its higher performance.
data$INDICATOR <- as.character(0) and
251 | data$INDICATOR <- as.character(read.csv(paste0(path,"/temp/", tableNumber, "_MetaData.csv"))[1,1]):
252 | The seventh step of the statcan_data() function consists in adding the
253 | name of the table from the metadata table.
unlink(tempdir()): The eighth step deletes the
255 | temporary folder used to download, unzip, extract and load the
256 | data.
return(Data): Finally, the last step of the
258 | statcan_data() function allows to return the value into the user’s
259 | environment.
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1 | # -----------------------------------------------------------
2 | # CITATION file created with {cffr} R package, v0.4.1
3 | # See also: https://docs.ropensci.org/cffr/
4 | # -----------------------------------------------------------
5 |
6 | cff-version: 1.2.0
7 | message: 'To cite package "statcanR" in publications use:'
8 | type: software
9 | license: MIT
10 | title: 'Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses'
11 | version: 0.2.5
12 | abstract: This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy. Warin (2024)
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63 | All functions64 | 65 | |
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| 67 | 68 | | 69 |statcanR |
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| 71 | 72 | | 73 |statcanR download data function |
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| 75 | 76 | | 77 |Searching function for statcanR |
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62 | MIT License
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70 | Copyright (c) 2020 Thierry Warin ; Romain Le Duc
65 |Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
66 |The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
67 |THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
68 |
37 |
38 | For people less comfortable with R and to allow more people to have access to our package, we have also developed a Shiny application.Through the same logic present in our package, researchers can retrieve data from Statistics Canada.
39 |
40 | statcanR EploR is available [[here]]( https://warin.ca/shiny/statcanr/)
41 |
42 | ## Installation
43 |
44 | The released version of statcanR package is accessible through CRAN and devtools.
45 |
46 | ``` r
47 | install.packages("statcanR")
48 |
49 | install.packages("devtools")
50 | devtools::install_github('warint/statcanR')
51 | ```
52 |
53 | ## Example
54 |
55 | This section presents an example of how to use the `statcanR` R package and its function `statcan_data()` and `statcan_download_data()`.
56 |
57 | The following example is provided to illustrate how to use the functions. It consists in collecting some descriptive statistics about the Canadian Labour Force at the federal, provincial and industrial levels, on a monthly basis.
58 |
59 | With a simple web search 'statistics canada wages by industry metropolitan area monthly', the table number can easily be found on Statisitcs Canada's webpage. Here is below a figure that illustrates this example, such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives.
60 |
61 | Once the table number is identified, the statcan_data() function is easy to use in order to collect the data, as following:
62 |
63 | ``` r
64 | library(statcanR)
65 | mydata <- statcan_data("27-10-0014-01","eng")
66 | ```
67 |
68 | For the `statcan_download_data()` function there is no difference on how to use it, the only difference is that this function allow you to download the data in a csv file on top of having the data in your environment.
69 |
70 | ``` r
71 | library(statcanR)
72 | mydata <- statcan_download_data("27-10-0014-01","eng")
73 | ```
74 |
75 | ### Video Tutorial
76 |
77 | Tutorial made by Professor Charles Saunders, Director of Master of Financial
78 | Economics Program at Western University [biography](https://economics.uwo.ca/people/faculty/saunders.html)
79 |
80 | Thanks!
81 |
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63 | Changelog
60 | Source:NEWS.md
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64 |
67 | statcanR 0.2.52023-08-10
65 |- We have corrected statcan_search() function by removing top level code. You can now install statcanR package without an internet connection 66 |
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71 | statcanR 0.2.42023-03-03
69 |- we have added the function statcan_search() to identify economic data tables available on Statistics Canada’s website. 70 |
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83 | statcanR 0.2.32021-12-14
73 |- we have modified the function to get an informative message if the table is not available instead of having an error message. 74 |
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/README.md:
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1 |
2 |
3 |
4 | # statcanR
5 |
6 |
7 |
8 | [](https://ci.appveyor.com/project/warint/statcanR)
10 | [](https://github.com/SNStatComp/awesome-official-statistics-software)
12 | [](https://CRAN.R-project.org/package=statcanR)
14 | [](https://cran.r-project.org/package=statcanR)
15 |
16 |
17 |
18 | # Overview
19 |
20 | Easily connect to Statistics Canada’s Web Data Service with R. Find and
21 | access open economic data (formerly known as CANSIM tables, now identified by
22 | Product IDs (PID)) which are accessible as a data frame, directly in the
23 | user’s R environment.
24 |
25 |
26 |
27 | ## Shiny App : statcanR ExploR
28 |
29 |
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65 |
67 |
68 | Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
66 |
69 |
70 |
71 |
72 | statcan_data(tableNumber, lang)
73 |
82 | Arguments
74 |- tableNumber 75 |
The table number of the Statistics Canada data table
76 |
77 |
78 | - lang 79 |
The language wanted
80 |
81 |
83 |
88 | Value
84 | 85 | 86 |The output will be a data table representing the data associated with the chosen table number.
87 |
89 |
100 |
101 | Details
90 |The
91 | statcan_data() function has 2 arguments to fulfill to get data: tableNumber & lang.
The tableNumber argument simply refers to the table number of the Statistics Canada data table a user wants to collect, 94 | such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
95 | 96 |To get the table number: https://www150.statcan.gc.ca/n1/en/type/data.
97 |The second argument, lang, refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages. 98 | Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c('fra', 'eng').
99 |
102 |
107 |
108 | Examples
103 |#mydata <- statcan_data('27-10-0014-01', 'eng')
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2 |
3 | /**
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6 | *
7 | * .Site -> body > .container
8 | * .Site-content -> body > .container .row
9 | * .footer -> footer
10 | *
11 | * Key idea seems to be to ensure that .container and __all its parents__
12 | * have height set to 100%
13 | *
14 | */
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171 | margin-top: 0;
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175 | margin-bottom: 0.5em;
176 | }
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181 |
182 | nav[data-toggle='toc'] .nav > li > a {
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184 | font-size: 1.5rem;
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186 | color: inherit;
187 | }
188 |
189 | nav[data-toggle='toc'] .nav > li > a:hover,
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191 | padding-left: 5px;
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194 | }
195 |
196 | nav[data-toggle='toc'] .nav > .active > a,
197 | nav[data-toggle='toc'] .nav > .active:hover > a,
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200 | font-size: 1.5rem;
201 | font-weight: 400;
202 | color: inherit;
203 | border-left: 2px solid #878787;
204 | }
205 |
206 | /* Nav: second level (shown on .active) */
207 |
208 | nav[data-toggle='toc'] .nav .nav {
209 | display: none; /* Hide by default, but at >768px, show it */
210 | padding-bottom: 10px;
211 | }
212 |
213 | nav[data-toggle='toc'] .nav .nav > li > a {
214 | padding-left: 16px;
215 | font-size: 1.35rem;
216 | }
217 |
218 | nav[data-toggle='toc'] .nav .nav > li > a:hover,
219 | nav[data-toggle='toc'] .nav .nav > li > a:focus {
220 | padding-left: 15px;
221 | }
222 |
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224 | nav[data-toggle='toc'] .nav .nav > .active:hover > a,
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227 | font-weight: 500;
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229 | }
230 |
231 | /* orcid ------------------------------------------------------------------- */
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234 | font-size: 16px;
235 | color: #A6CE39;
236 | /* margins are required by official ORCID trademark and display guidelines */
237 | margin-left:4px;
238 | margin-right:4px;
239 | vertical-align: middle;
240 | }
241 |
242 | /* Reference index & topics ----------------------------------------------- */
243 |
244 | .ref-index th {font-weight: normal;}
245 |
246 | .ref-index td {vertical-align: top; min-width: 100px}
247 | .ref-index .icon {width: 40px;}
248 | .ref-index .alias {width: 40%;}
249 | .ref-index-icons .alias {width: calc(40% - 40px);}
250 | .ref-index .title {width: 60%;}
251 |
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255 | .ref-arguments .desc {width: 80%;}
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304 |
305 | /* Clipboard --------------------------*/
306 |
307 | .hasCopyButton {
308 | position: relative;
309 | }
310 |
311 | .btn-copy-ex {
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313 | right: 0;
314 | top: 0;
315 | visibility: hidden;
316 | }
317 |
318 | .hasCopyButton:hover button.btn-copy-ex {
319 | visibility: visible;
320 | }
321 |
322 | /* headroom.js ------------------------ */
323 |
324 | .headroom {
325 | will-change: transform;
326 | transition: transform 200ms linear;
327 | }
328 | .headroom--pinned {
329 | transform: translateY(0%);
330 | }
331 | .headroom--unpinned {
332 | transform: translateY(-100%);
333 | }
334 |
335 | /* mark.js ----------------------------*/
336 |
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339 | border-bottom: 2px solid rgba(255, 153, 51, 0.3);
340 | padding: 1px;
341 | }
342 |
343 | /* vertical spacing after htmlwidgets */
344 | .html-widget {
345 | margin-bottom: 10px;
346 | }
347 |
348 | /* fontawesome ------------------------ */
349 |
350 | .fab {
351 | font-family: "Font Awesome 5 Brands" !important;
352 | }
353 |
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364 | */
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380 | padding-left:1em;
381 | }
382 | div.csl-indent {
383 | margin-left: 2em;
384 | }
385 |
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68 | statcanR download data function
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71 |
72 | statcan_download_data(tableNumber, lang)
73 |
82 | Arguments
74 |- tableNumber 75 |
The table number of the Statistics Canada data table
76 |
77 |
78 | - lang 79 |
The language wanted
80 |
81 |
83 |
88 |
89 | Value
84 | 85 | 86 |The output will be a data table and csv file representing the data associated with the chosen table number.
87 |
90 |
107 |
108 | Examples
91 |mydata <- statcan_data('27-10-0014-01', 'eng')
92 | #> statcanR: downloading remote table.
93 | #> Warning: One or more parsing issues, call `problems()` on your data frame for details,
94 | #> e.g.:
95 | #> dat <- vroom(...)
96 | #> problems(dat)
97 | #> Rows: 61 Columns: 10
98 | #> ── Column specification ────────────────────────────────────────────────────────
99 | #> Delimiter: ","
100 | #> chr (8): Cube Title, Product Id, CANSIM Id, URL, Cube Notes, Archive Status...
101 | #> num (1): Total number of dimensions
102 | #> date (1): End Reference Period
103 | #>
104 | #> ℹ Use `spec()` to retrieve the full column specification for this data.
105 | #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
106 |
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1 | /* Docsearch -------------------------------------------------------------- */
2 | /*
3 | Source: https://github.com/algolia/docsearch/
4 | License: MIT
5 | */
6 |
7 | .algolia-autocomplete {
8 | display: block;
9 | -webkit-box-flex: 1;
10 | -ms-flex: 1;
11 | flex: 1
12 | }
13 |
14 | .algolia-autocomplete .ds-dropdown-menu {
15 | width: 100%;
16 | min-width: none;
17 | max-width: none;
18 | padding: .75rem 0;
19 | background-color: #fff;
20 | background-clip: padding-box;
21 | border: 1px solid rgba(0, 0, 0, .1);
22 | box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
23 | }
24 |
25 | @media (min-width:768px) {
26 | .algolia-autocomplete .ds-dropdown-menu {
27 | width: 175%
28 | }
29 | }
30 |
31 | .algolia-autocomplete .ds-dropdown-menu::before {
32 | display: none
33 | }
34 |
35 | .algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
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37 | background-color: rgb(255,255,255);
38 | border: 0;
39 | max-height: 80vh;
40 | }
41 |
42 | .algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
43 | margin-top: 0
44 | }
45 |
46 | .algolia-autocomplete .algolia-docsearch-suggestion {
47 | padding: 0;
48 | overflow: visible
49 | }
50 |
51 | .algolia-autocomplete .algolia-docsearch-suggestion--category-header {
52 | padding: .125rem 1rem;
53 | margin-top: 0;
54 | font-size: 1.3em;
55 | font-weight: 500;
56 | color: #00008B;
57 | border-bottom: 0
58 | }
59 |
60 | .algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
61 | float: none;
62 | padding-top: 0
63 | }
64 |
65 | .algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
66 | float: none;
67 | width: auto;
68 | padding: 0;
69 | text-align: left
70 | }
71 |
72 | .algolia-autocomplete .algolia-docsearch-suggestion--content {
73 | float: none;
74 | width: auto;
75 | padding: 0
76 | }
77 |
78 | .algolia-autocomplete .algolia-docsearch-suggestion--content::before {
79 | display: none
80 | }
81 |
82 | .algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
83 | padding-top: .75rem;
84 | margin-top: .75rem;
85 | border-top: 1px solid rgba(0, 0, 0, .1)
86 | }
87 |
88 | .algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
89 | display: block;
90 | padding: .1rem 1rem;
91 | margin-bottom: 0.1;
92 | font-size: 1.0em;
93 | font-weight: 400
94 | /* display: none */
95 | }
96 |
97 | .algolia-autocomplete .algolia-docsearch-suggestion--title {
98 | display: block;
99 | padding: .25rem 1rem;
100 | margin-bottom: 0;
101 | font-size: 0.9em;
102 | font-weight: 400
103 | }
104 |
105 | .algolia-autocomplete .algolia-docsearch-suggestion--text {
106 | padding: 0 1rem .5rem;
107 | margin-top: -.25rem;
108 | font-size: 0.8em;
109 | font-weight: 400;
110 | line-height: 1.25
111 | }
112 |
113 | .algolia-autocomplete .algolia-docsearch-footer {
114 | width: 110px;
115 | height: 20px;
116 | z-index: 3;
117 | margin-top: 10.66667px;
118 | float: right;
119 | font-size: 0;
120 | line-height: 0;
121 | }
122 |
123 | .algolia-autocomplete .algolia-docsearch-footer--logo {
124 | background-image: url("data:image/svg+xml;utf8,");
125 | background-repeat: no-repeat;
126 | background-position: 50%;
127 | background-size: 100%;
128 | overflow: hidden;
129 | text-indent: -9000px;
130 | width: 100%;
131 | height: 100%;
132 | display: block;
133 | transform: translate(-8px);
134 | }
135 |
136 | .algolia-autocomplete .algolia-docsearch-suggestion--highlight {
137 | color: #FF8C00;
138 | background: rgba(232, 189, 54, 0.1)
139 | }
140 |
141 |
142 | .algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
143 | box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
144 | }
145 |
146 | .algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
147 | background-color: rgba(192, 192, 192, .15)
148 | }
149 |
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/R/statCanR.R:
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1 | #' statcanR
2 | #'
3 | #'
4 | #' Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
5 | #'
6 | #' The
7 | #' \code{statcan_data()} function has 2 arguments to fulfill to get data: {tableNumber} & {lang}.
8 | #'
9 | #'
10 | #' The tableNumber argument simply refers to the table number of the Statistics Canada data table a user wants to collect,
11 | #' such as '27-10-0014-01' for the Federal expenditures on science and technology, by socio-economic objectives, as an example.
12 | #'
13 | #'
14 | #' To get the table number: \url{https://www150.statcan.gc.ca/n1/en/type/data}.
15 | #'
16 | #' The second argument, lang, refers to the language. As Canada is a bilingual country, Statistics Canada displays all the economic data in both languages.
17 | #' Therefore, users can choose to collect satistics data tables in French or English by setting the lang argument with c('fra', 'eng').
18 | #'
19 | #'
20 | #'
21 | #' @param tableNumber The table number of the Statistics Canada data table
22 | #' @param lang The language wanted
23 | #'
24 | #' @return The output will be a data table representing the data associated with the chosen table number.
25 | #' @export
26 | #'
27 | #' @import curl
28 | #' @import tibble
29 | #' @import qpdf
30 | #' @importFrom httr http_error
31 | #' @importFrom data.table fread
32 | #' @importFrom data.table setDF
33 | #'
34 | #' @examples
35 | #' #mydata <- statcan_data('27-10-0014-01', 'eng')
36 | #'
37 |
38 |
39 | # Scraping function for statcan
40 | statcan_data <- function(tableNumber, lang)
41 | {
42 |
43 | # identifying the table number
44 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber) -
45 | 2))
46 |
47 | # getting data in English version
48 | if (lang == "eng")
49 | {
50 | # downloading the data file in English version
51 | urlEng <- paste0("https://www150.statcan.gc.ca/n1/en/tbl/csv/",
52 | tableNumber, "-eng.zip")
53 |
54 | download_dir <- file.path(tempdir(), "datasetEng.zip")
55 |
56 | #utils::download.file(urlEng, download_dir, method = "curl")
57 | #data.table::fread(input = urlEng, file = download_dir)
58 | #RCurl::getURL(urlEng, ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
59 | #curl::curl_download(urlEng, download_dir)
60 |
61 | if (httr::http_error(urlEng)) { # network is down = message (not an error anymore)
62 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
63 | #return(NULL)
64 | } else { # network is up = proceed to download via curl
65 | message("statcanR: downloading remote table.")
66 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlEng, download_dir))
67 |
68 |
69 | # unziping the downloaded data file in English version
70 | unzip_dir <- file.path(paste0(tempdir(), "/"))
71 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
72 | unlink(download_dir)
73 |
74 | # loading the data file in English version
75 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
76 | can_data <- data.table::fread(csv_file)
77 |
78 | # adding to the data.frame or data.table the Official Data Table
79 | # Indicator defined by Statistics Canada and based on metadata file.
80 | can_data$INDICATOR <- as.character(0)
81 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
82 | can_data$INDICATOR <- as.character(readr::read_csv(paste0(tempdir(),
83 | "/", tableNumber, "_MetaData.csv"))[1, 1])
84 |
85 | if(nchar(can_data[1,1])==9){
86 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
87 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
88 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
89 | }
90 |
91 | else if(nchar(can_data[1,1])==7){
92 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
93 | }
94 |
95 | else if(nchar(can_data[1,1])==4){
96 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
97 | }
98 |
99 | else{
100 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
101 | }
102 |
103 | # creating a data frame
104 | data.table::setDF(return(can_data))
105 |
106 | } # /if - network up or down
107 |
108 | }
109 |
110 | # getting data in French version
111 | if (lang == "fra")
112 | {
113 | # downloading the data file in French version
114 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/",
115 | tableNumber, "-fra.zip")
116 |
117 | download_dir <- file.path(tempdir(), "datasetFra.zip")
118 | #utils::download.file(urlFra, download_dir, method = "curl")
119 | #data.table::fread(urlFra, download_dir)
120 | #curl::curl_download(urlFra, download_dir)
121 |
122 | if (httr::http_error(urlFra)) { # network is down = message (not an error anymore)
123 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
124 | return(NULL)
125 | } else { # network is up = proceed to download via curl
126 | message("statcanR: downloading remote table.")
127 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlFra, download_dir))
128 |
129 |
130 | # unzipping the downloaded data file in French version
131 | unzip_dir <- file.path(paste0(tempdir(), "/"))
132 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
133 | unlink(download_dir)
134 |
135 | # loading the data file in French version
136 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
137 | can_data <- data.table::fread(csv_file)
138 |
139 | # adding to the data.frame or data.table the Official Data Table
140 | # Indicator defined by Statitics Canada and based on metadata file.
141 | can_data$INDICATOR <- as.character(0)
142 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
143 | can_data$INDICATOR <- as.character(readr::read_delim(paste0(tempdir(),
144 | "/", tableNumber, "_MetaData.csv"), delim = ";", escape_double = FALSE, trim_ws = TRUE)[1, 1])
145 |
146 | can_data[,1] <- "REF_DATE"
147 |
148 | if(nchar(can_data[1,1])==9){
149 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
150 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
151 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
152 | }
153 |
154 | else if(nchar(can_data[1,1])==7){
155 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
156 | }
157 |
158 | else if(nchar(can_data[1,1])==4){
159 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
160 | }
161 |
162 | else{
163 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
164 | }
165 |
166 | # creating a data frame
167 | data.table::setDF(return(can_data))
168 | } # /if - network up or down
169 |
170 | }
171 |
172 |
173 | # removing the temp folder and creating a data frame
174 | unlink(tempdir())
175 |
176 | }
177 |
178 | #' statcanR download data function
179 | #'
180 | #' @param tableNumber The table number of the Statistics Canada data table
181 | #' @param lang The language wanted
182 | #'
183 | #' @return The output will be a data table and csv file representing the data associated with the chosen table number.
184 | #' @export
185 | #'
186 | #'
187 | #' @import curl
188 | #' @import tibble
189 | #' @importFrom httr http_error
190 | #' @importFrom data.table fread
191 | #' @importFrom data.table setDF
192 | #'
193 | #' @examples
194 | #' mydata <- statcan_data('27-10-0014-01', 'eng')
195 |
196 | # Download function for statcan
197 | statcan_download_data <- function(tableNumber, lang)
198 | {
199 |
200 | # identifying the table number
201 | tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber) -
202 | 2))
203 |
204 | # getting data in English version
205 | if (lang == "eng")
206 | {
207 | # downloading the data file in English version
208 | urlEng <- paste0("https://www150.statcan.gc.ca/n1/en/tbl/csv/",
209 | tableNumber, "-eng.zip")
210 |
211 | download_dir <- file.path(tempdir(), "datasetEng.zip")
212 | #utils::download.file(urlEng, download_dir, method = "curl")
213 | #data.table::fread(input = urlEng, file = download_dir)
214 | #RCurl::getURL(urlEng, ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
215 | #curl::curl_download(urlEng, download_dir)
216 |
217 | if (httr::http_error(urlEng)) { # network is down = message (not an error anymore)
218 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
219 | #return(NULL)
220 | } else { # network is up = proceed to download via curl
221 | message("statcanR: downloading remote table.")
222 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlEng, download_dir))
223 |
224 | # unziping the downloaded data file in English version
225 | unzip_dir <- file.path(paste0(tempdir(), "/"))
226 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
227 | unlink(download_dir)
228 |
229 | # loading the data file in English version
230 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
231 | can_data <- data.table::fread(csv_file)
232 |
233 | # adding to the data.frame or data.table the Official Data Table
234 | # Indicator defined by Statistics Canada and based on metadata file.
235 | can_data$INDICATOR <- as.character(0)
236 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
237 | can_data$INDICATOR <- as.character(readr::read_csv(paste0(tempdir(),
238 | "/", tableNumber, "_MetaData.csv"))[1, 1])
239 |
240 | if(nchar(can_data[1,1])==9){
241 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
242 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
243 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
244 | }
245 |
246 | else if(nchar(can_data[1,1])==7){
247 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
248 | }
249 |
250 | else if(nchar(can_data[1,1])==4){
251 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
252 | }
253 |
254 | else{
255 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
256 | }
257 | # creating a data frame
258 | data.table::setDF(return(can_data))
259 | readr::write_csv(can_data, paste0("./statcan_",tableNumber,"_", lang,".csv"))
260 |
261 | } # /if - network up or down
262 |
263 | }
264 |
265 | # getting data in French version
266 | if (lang == "fra")
267 | {
268 | # downloading the data file in French version
269 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/",
270 | tableNumber, "-fra.zip")
271 |
272 | download_dir <- file.path(tempdir(), "datasetFra.zip")
273 | #utils::download.file(urlFra, download_dir, method = "curl")
274 | #data.table::fread(urlFra, download_dir)
275 | #curl::curl_download(urlFra, download_dir)
276 |
277 | if (httr::http_error(urlFra)) { # network is down = message (not an error anymore)
278 | message("No Internet connection or incorrect statcan table number or Statistics Canada website under maintenance.")
279 | return(NULL)
280 | } else { # network is up = proceed to download via curl
281 | message("statcanR: downloading remote table.")
282 | with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(urlFra, download_dir))
283 |
284 |
285 |
286 | # unzipping the downloaded data file in French version
287 | unzip_dir <- file.path(paste0(tempdir(), "/"))
288 | utils::unzip(zipfile = download_dir, exdir = unzip_dir)
289 | unlink(download_dir)
290 |
291 | # loading the data file in French version
292 | csv_file <- file.path(paste0(tempdir(), "/", tableNumber, ".csv"))
293 | can_data <- data.table::fread(csv_file)
294 |
295 | # adding to the data.frame or data.table the Official Data Table
296 | # Indicator defined by Statistics Canada and based on metadata file.
297 | can_data$INDICATOR <- as.character(0)
298 | can_data$COORDINATE <- as.character(can_data$COORDINATE)
299 | can_data$INDICATOR <- as.character(readr::read_delim(paste0(tempdir(),
300 | "/", tableNumber, "_MetaData.csv"), delim = ";", escape_double = FALSE, trim_ws = TRUE)[1, 1])
301 |
302 | can_data[,1] <- "REF_DATE"
303 |
304 | if(nchar(can_data[1,1])==9){
305 | can_data$REF_DATE <- sub(".*/", "", can_data$REF_DATE)
306 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 3, 31, sep = "-"))
307 | can_data <- tibble::add_column(can_data, REF_PERIOD = "Fiscal year", .before = 2)
308 | }
309 |
310 | else if(nchar(can_data[1,1])==7){
311 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, sep = "-"))
312 | }
313 |
314 | else if(nchar(can_data[1,1])==4){
315 | can_data$REF_DATE <- as.Date(paste(can_data$REF_DATE, 1, 1, sep = "-"))
316 | }
317 |
318 | else{
319 | can_data$REF_DATE <- as.Date(can_data$REF_DATE)
320 | }
321 | # creating a data frame
322 | data.table::setDF(return(can_data))
323 |
324 | readr::write_csv(can_data, paste0("./statcan_",tableNumber,"_", lang,".csv"))
325 | } # /if - network up or down
326 | }
327 |
328 | # removing the temp folder and creating a data frame
329 | unlink(tempdir())
330 | }
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74 | The statcan_search() function has 2 arguments to fulfill to find a database: keywords and lang.
69 | The keywords argument refers to words that can be found in either the title or the description of the database. For example, inserting the keywords
70 | "economy","export",and "link" will bring up the title, table id, description, and release date for databases that include these keywords. In this case, only one data table ("Supply and use tables, link-1997 level")
71 | would be returned as it is the only data table containing all three words.
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78 | statcan_search(keywords, lang)
79 |
88 | Arguments
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The words that appear in the title or description of the data table
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84 | - lang 85 |
The language wanted
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94 | Value
90 | 91 | 92 |The output will be the title, id, description, and release date of a table
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95 |
98 |
99 | Details
96 |Easily connect to Statistics Canada's Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user's R environment.
97 |
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105 | Examples
101 |statcan_search(c("economy","export","link"),"eng")
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98 | statCanR
85 |Thierry 86 | Warin
87 | 88 | 89 | Source:vignettes/statCanR.Rmd
90 | statCanR.Rmd
99 |
107 | Overview 100 |
101 |statcanR provides the R user with a consistent process to identify 102 | and collect data from Statistics Canada’s data portal. It allows users 103 | to search for and access all of Statistics Canada’ open economic data 104 | (formerly known as CANSIM tables) now identified by product IDs (PID) by 105 | the new Statistics Canada’s Web Data Service: https://www150.statcan.gc.ca/n1/en/type/data.
106 |
108 |
113 |
118 | Quick start 109 |
110 |First, install statcanR:
111 |
112 | devtools::install_github("warint/statcanR")Next, call statcanR to make sure everything is installed 114 | correctly.
115 | 117 |
119 |
134 |
143 |
264 | Practical usage 120 |
121 |This section presents an example of how to use the statcanR R package 122 | and its functions: statcan_search() and statcan_data().
123 |The following example is provided to illustrate how to use these 124 | functions. It consists of collecting some descriptive statistics about 125 | the Canadian labour force at the federal, provincial and industrial 126 | levels, on a monthly basis.
127 |To identify a relevant table, the statcan_search() function can be 128 | used by using a keyword or set of keywords, depending on the language 129 | the user wishes to search in (between English and French). Below is an 130 | example that reveals the data tables we could be interested in:
131 |
132 | # Identify with statcan_search() function
133 | statcan_search(c("federal","expenditures"),"eng")Notice that for each corresponding table, the unique table number 135 | identifier is also presented. Let’s focus on the first table out of the 136 | two that appear, which contains data on Federal expenditures on science 137 | and technology, by socio-economic objectives. Once this table number is 138 | identified (‘27-10-0014-01’), the statcan_data() function is easy to use 139 | in order to collect the data, as following:
140 |
141 | # Get data with statcan_data function
142 | mydata <- statcan_download_data("27-10-0014-01", "eng")Should you want the same data in French, just replace the argument at 144 | the end of the function with “fra”.
145 |
146 |
263 | Code architecture 147 |
148 |This section describes the code architecture of the statcanR 149 | package.
150 |The statcan_search() function has 2 arguments:
151 |-
152 |
- keywords 153 |
- lang 154 |
The ‘keywords’ argument is useful for identifying what kind of open 156 | economic data Statistics Canada has available for users. It can take as 157 | inputs either a single word (i.e., statcan_search(“expenditures”)) or a 158 | vector of multiple keywords (such as: 159 | statcan_search(c(“expenditures”,“federal”,“objectives”))).
160 |The second argument, ‘lang’, refers to the language. As Canada is a 161 | bilingual country, Statistics Canada displays all the economic data in 162 | both languages. Therefore, users can see what data tables are available 163 | in French or English by setting the lang argument with c(“fra”, 164 | “eng”).
165 |For all data tables that contain these words in either their title or 166 | description, the resulting output will include four pieces of 167 | information: The name of the data table, its unique table number 168 | identifier, the description, and the release date. In details, the 169 | statcan_download_data() function has 2 arguments:
170 |-
171 |
- tableNumber 172 |
- lang 173 |
The ‘tableNumber’ argument simply refers to the table number of the 175 | Statistics Canada data table a user wants to collect, such as 176 | ‘27-10-0014-01’ for the Federal expenditures on science and technology, 177 | by socio-economic objectives, as an example.
178 |Just as in the statcan_search() command, ‘lang’, refers to the 179 | language, and can be set to “eng” for English or “fra” for French. 180 | Therefore, users can choose to collect satistics data tables in French 181 | or English by setting the lang argument with c(“fra”, “eng”).
182 |The code architecture of the statcan_download_data() function is as 183 | follows. The first step if to clean the table number in order to align 184 | it with the official typology of Statistics Canada’s Web Data Service. 185 | The second step is to create a temporary folder where all the data 186 | wrangling operations are performed. The third step is to check and 187 | select the correct language. The fourth step is to define the right URL 188 | where the actual data table is stored and then to download the .Zip 189 | container. The fifth step is to unzip the previously downloaded .Zip 190 | file to extract the data and metadata from the .csv files. The final 191 | step is to load the statistics data into a data frame called ‘data’ and 192 | to add the official table indicator name in the new ‘INDICATOR’ 193 | column.
194 |To be more precise about the functions, below is some further code 195 | description:
196 |
197 |
218 | statcan_search() 198 |
199 |-
200 |
keyword_regex <- paste0("(", paste(keywords, collapse = "|"), ")", collapse = ".*"): 201 | The first step is to paste (either individually or in vector format) the 202 | keywords the user is interested in
203 | matches <- apply(statcan_data, 1, function(row) {204 |all(sapply(keywords, function(x) {205 |grepl(x, paste(as.character(row), collapse = " "))206 |}))}): Next, the matching relies on the 207 | sapply function, which is applied to any character string in a row of a 208 | given observation. Therefore, the “keyword” could be found in the title 209 | column or the description column (technically, it could even be in the 210 | “release date” or “id” columns).
211 | filtered_data <- statcan_data[matches, ]The 212 | third step takes only the data where matches were found.
213 | datatable(filtered_data, options = list(pageLength = 10))214 | Finally, the datatable command presents the filtered data in a clean 215 | table.
216 |
219 |
262 | statcan_download_data() 220 |
221 |-
222 |
tableNumber <- gsub("-", "", substr(tableNumber, 1, nchar(tableNumber)-2)): 223 | The first step is to clean the table number provided by the user in 224 | order to collect the overall data table related to the specific 225 | indicator the user is interested in. In fact, each indicator is an 226 | excerpt of the overall table. In addition, following the new Statistics 227 | Canada’s Web Data Service, the URL typology defined by REST API is 228 | stored in csv files by table numbers without a ‘-’. Also, the last 2 229 | digits after the last ‘-’ refer to the specific excerpt of the original 230 | table. Therefore, following the Statistics Canada Web Data Service’s 231 | typology, the function first removes the ‘-’ and the last 2 digits from 232 | the user’s selection.
233 | if(lang == "eng")|if(lang == "fra"): 234 | The second step is the ‘if statement’ to get the data in the correct 235 | language.
236 | urlFra <- paste0("https://www150.statcan.gc.ca/n1/fr/tbl/csv/", tableNumber, "-fra.zip"): 237 | The third step is to create the correct url in order to download the 238 | respective .Zip file from the Statistics Canada Web Data 239 | Service.
240 | download(urlFra, download_dir, mode = "wb"): The 241 | fourth step is a simple downloading function that extracts .Zip file and 242 | download it into a temporary folder.
243 | unzip(zipfile = download_dir, exdir = unzip_dir): 244 | The fifth step consists in unzipping the .Zip file. The unzipping 245 | process gives access to two different .csv files, such as the overall 246 | data table and the metadata table.
247 | data.table::fread(csv_file): The sixth step consists 248 | in loading the data table into a unique data frame. The fread() function 249 | from the data.table package is used for its higher performance.
250 | data$INDICATOR <- as.character(0)and 251 |data$INDICATOR <- as.character(read.csv(paste0(path,"/temp/", tableNumber, "_MetaData.csv"))[1,1]): 252 | The seventh step of the statcan_data() function consists in adding the 253 | name of the table from the metadata table.
254 | unlink(tempdir()): The eighth step deletes the 255 | temporary folder used to download, unzip, extract and load the 256 | data.
257 | return(Data): Finally, the last step of the 258 | statcan_data() function allows to return the value into the user’s 259 | environment.
260 |