├── README.md ├── screencasts ├── Google_Flu_Trends.png ├── IHME │ ├── todo.md │ ├── tut_imag │ │ ├── 1.png │ │ ├── 2.1.1.png │ │ ├── 2.1.2.png │ │ ├── 2.1.3.png │ │ ├── 2.1.4.png │ │ ├── 2.1.5.png │ │ ├── 2.1.6.png │ │ ├── 2.2.1.png │ │ ├── 2.2.2.png │ │ ├── 2.2.3.png │ │ ├── 2.2.4.png │ │ ├── 2.2.5.png │ │ ├── 2.2.6.png │ │ ├── 2.3.1.png │ │ ├── 2.3.2.png │ │ ├── 2.3.3.png │ │ ├── 2.3.4.png │ │ ├── 2.3.5.png │ │ └── 2.3.6.png │ ├── tut_imag_2 │ │ ├── 2.4.1.png │ │ ├── 2.4.2.png │ │ ├── 2.4.3.png │ │ ├── 2.4.4.png │ │ ├── 2.4.5.png │ │ ├── 2.5.1.png │ │ ├── 2.5.2.png │ │ ├── 2.5.3.png │ │ ├── 2.5.4.png │ │ ├── 2.5.5.png │ │ ├── 2.6.1.png │ │ ├── 2.6.2.png │ │ ├── 2.6.3.png │ │ ├── 2.6.4.png │ │ └── 2.6.5.png │ ├── tut_imag_3 │ │ ├── 2.4.4.1.png │ │ ├── 2.4.6.png │ │ ├── 2.5.4.1.png │ │ ├── 2.5.6.png │ │ ├── 2.6.4.1.png │ │ └── 2.6.6.png │ └── tut_imag_4 │ │ ├── 3.1.png │ │ ├── 3.2.1.png │ │ ├── 3.2.2.png │ │ ├── 3.2.3.png │ │ ├── 3.2.4.png │ │ ├── 3.2.5.png │ │ ├── 3.2.6.png │ │ ├── 3.2.png │ │ ├── 3.3.png │ │ └── 3.png ├── IHME_crossfilter_gif.gif ├── aid-agency │ ├── bar-chart │ │ ├── aggregate.png │ │ ├── axes-titles.png │ │ ├── chart-type.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── dashboard │ │ ├── add-bar-chart.png │ │ ├── add-pie1.png │ │ ├── add-pie2.png │ │ ├── add-plot-title.png │ │ ├── add-plot.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── save.png │ │ ├── settings.png │ │ └── text.png │ ├── pie-chart-activity │ │ ├── chart-type.png │ │ ├── legend.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── pie-chart-countries │ │ ├── chart-type.png │ │ ├── legend.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ └── satellite │ │ ├── add-data.png │ │ ├── chart-type.png │ │ ├── fork-and-edit.png │ │ ├── map-position.png │ │ ├── map-style.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png ├── california_measles_outbreaks.gif ├── ebola-outbreaks │ ├── atlas │ │ ├── add-data.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── color-bar-size.png │ │ ├── color-bar-title.png │ │ ├── fork-and-edit.png │ │ ├── geo-layout.png │ │ ├── geo-style.png │ │ ├── global-font.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── dashboard │ │ ├── add-plot-titles.png │ │ ├── add-plot.png │ │ ├── add-plot2.png │ │ ├── add-plot3.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── save.png │ │ ├── settings.png │ │ └── text.png │ ├── scatter │ │ ├── axes-titles.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png │ └── table │ │ ├── chart-type.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png ├── ebola_humanitarian_aid.gif ├── ebola_outbreak.png ├── ebola_outbreaks.gif ├── google-flu-trends.gif ├── google-flu-trends │ ├── TODO.md │ ├── dashboard │ │ ├── add-plot-all.png │ │ ├── add-plot-title.png │ │ ├── add-plot.png │ │ ├── add-text.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── save.png │ │ ├── settings.png │ │ └── text.png │ ├── ny-bar │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── custom-range.png │ │ ├── global-font.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── oklahoma-bar │ │ ├── add-data.png │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── custom-range.png │ │ ├── fork-and-edit.png │ │ ├── fork-and-save.png │ │ ├── global-font.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── search-box │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── log-scale.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ ├── trace-styles2.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── search-region-box │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels.png │ │ ├── trace-styles-all.png │ │ ├── trace-styles.png │ │ ├── trace-values-all.png │ │ └── trace-values.png │ └── us-bar │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── custom-range.png │ │ ├── global-font.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png ├── infant-mortality-index.gif ├── infant-mortality │ ├── choropleth1990 │ │ ├── add-data.png │ │ ├── chart-type.png │ │ ├── color-bar-border.png │ │ ├── color-bar-label.png │ │ ├── color-bar-size.png │ │ ├── fork-and-edit.png │ │ ├── geo-layout.png │ │ ├── geo-style.png │ │ ├── json.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── choropleth2015 │ │ ├── chart-type.png │ │ ├── color-bar-border.png │ │ ├── color-bar-label.png │ │ ├── color-bar-size.png │ │ ├── geo-layout.png │ │ ├── geo-style.png │ │ ├── json.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── dashboard │ │ ├── add-choropleth1990.png │ │ ├── add-choropleth2015.png │ │ ├── add-plot-titles.png │ │ ├── add-plot.png │ │ ├── add-scatter.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── save.png │ │ ├── settings.png │ │ └── text.png │ └── scatter │ │ ├── annotation-1990.png │ │ ├── annotation-2015.png │ │ ├── axes-titles.png │ │ ├── chart-type.png │ │ ├── legend.png │ │ ├── lines-x.png │ │ ├── lines-y.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels-x.png │ │ ├── tick-labels-y.png │ │ ├── trace-styles1.png │ │ ├── trace-styles2.png │ │ ├── trace-values1.png │ │ ├── trace-values2.png │ │ └── zoom.png ├── infant_mortality_index.png ├── measles │ ├── 3d-scatter │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── color-bar-labels.png │ │ ├── color-bar-size.png │ │ ├── color-bar-title.png │ │ ├── grid-lines.png │ │ ├── hover-projections.png │ │ ├── save.png │ │ ├── scene.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── box │ │ ├── axes-titles.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── grid-lines.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── dashboard │ │ ├── add-plot-title.png │ │ ├── add-plot.png │ │ ├── add-text.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── repeat-process.png │ │ ├── save.png │ │ ├── settings.png │ │ ├── text-editor.png │ │ └── text.png │ └── scatter │ │ ├── add-data.png │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── color-bar-labels.png │ │ ├── color-bar-size.png │ │ ├── color-bar-title.png │ │ ├── fork-and-edit.png │ │ ├── grid-lines.png │ │ ├── log-scale.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png ├── mtcars.gif ├── mtcars │ ├── dashboard │ │ ├── add-plot-titles.png │ │ ├── add-plot.png │ │ ├── add-plot2.png │ │ ├── add-plot3.png │ │ ├── add-plot4.png │ │ ├── add-plot5.png │ │ ├── add-plot6.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── settings.png │ │ └── text.png │ ├── hp-vs-acc │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── lines.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── hp-vs-disp │ │ ├── chart-type.png │ │ └── trace-values.png │ ├── mpg-vs-cyl │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── lines.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── mpg-vs-name │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── global-font.png │ │ ├── lines.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png │ ├── weight-vs-acc │ │ ├── chart-type.png │ │ └── trace-values.png │ └── weight-vs-hp │ │ ├── chart-type.png │ │ └── trace-values.png ├── on_duty_policy_deaths.png ├── pennsylvania_diphtheria.png ├── police-report-deaths.gif ├── police-report │ ├── choropleth │ │ ├── aggregate.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── color-bar-size.png │ │ ├── geo-layout.png │ │ ├── geo-style.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ ├── dashboard │ │ ├── add-choropleth.png │ │ ├── add-pie-chart.png │ │ ├── add-plot-title.png │ │ ├── add-plot.png │ │ ├── add-scatter-plot.png │ │ ├── colors.png │ │ ├── filter.png │ │ ├── header.png │ │ ├── save.png │ │ ├── settings.png │ │ └── text.png │ ├── pie-chart │ │ ├── add-data.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── fork-and-edit.png │ │ ├── legend.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── trace-styles.png │ │ └── trace-values.png │ └── scatter │ │ ├── axes-titles.png │ │ ├── canvas.png │ │ ├── chart-type.png │ │ ├── margins.png │ │ ├── save.png │ │ ├── tick-labels.png │ │ ├── trace-styles.png │ │ ├── trace-values.png │ │ └── zoom.png └── zika-cases │ ├── avg-map │ ├── aggregations.png │ ├── canvas.png │ ├── chart-type.png │ ├── color-bar-size.png │ ├── filter.png │ ├── geo-layout.png │ ├── geo-style.png │ ├── global-font.png │ ├── margins.png │ ├── save.png │ ├── trace-styles.png │ └── trace-values.png │ ├── country-scatter │ ├── axes-titles.png │ ├── canvas.png │ ├── chart-type.png │ ├── color-bar-title.png │ ├── global-font.png │ ├── lines-x.png │ ├── lines-y.png │ ├── log-scale.png │ ├── margins.png │ ├── save.png │ ├── trace-styles.png │ ├── trace-values.png │ └── zoom.png │ ├── dashboard │ ├── add-plot-titles.png │ ├── add-plot.png │ ├── add-plot2.png │ ├── add-plot3.png │ ├── add-plot4.png │ ├── colors.png │ ├── filter.png │ ├── header.png │ ├── save.png │ ├── settings.png │ └── text.png │ ├── max-map │ ├── add-data.png │ ├── aggregations.png │ ├── canvas.png │ ├── chart-type.png │ ├── color-bar-size.png │ ├── filter.png │ ├── fork-and-edit.png │ ├── geo-layout.png │ ├── geo-style.png │ ├── global-font.png │ ├── margins.png │ ├── range.png │ ├── save.png │ ├── trace-styles.png │ └── trace-values.png │ └── week-scatter │ ├── annotation-2015.png │ ├── annotation-2016.png │ ├── axes-titles.png │ ├── canvas.png │ ├── chart-type.png │ ├── global-font.png │ ├── lines-x.png │ ├── lines-y.png │ ├── log-scale.png │ ├── margins.png │ ├── save.png │ ├── shape.png │ ├── trace-styles.png │ ├── trace-values.png │ └── zoom.png └── tutorials ├── aid-agency-dashboard.md ├── ebola-outbreaks.md ├── google-flu-trends.md ├── ihme-dashboard.md ├── infant-mortality-index.md ├── measles-dashboard.md ├── mtcars.md ├── police-report-deaths.md └── zika-cases.md /README.md: -------------------------------------------------------------------------------- 1 | # ⚕ Public health dashboards and tutorials using open data 2 | 3 | > Collection of Tableau-style public health dashboards and tutorials, hosted on plot.ly. Plot.ly is free for public data - [create an account](https://plot.ly/organize/). All dashboards were created without coding using plotly's online chart and dashboard creator. 4 | 5 | *** 6 | 7 | ## Contents 8 | 9 | 0. [Crossfilter Overview](#crossfilter-overview) 10 | 1. [California Measles Outbreak](#california-measles-outbreak) 11 | 2. [Aid Agencies during Ebola Outbreak](#aid-agencies-during-ebola-outbreak) 12 | 3. [U.S. Police officer deaths by cause](#us-police-officer-deaths-by-cause) 13 | 4. [WHO Infant Mortality Index](#comparing-1990-and-2015-infant-mortality-index) 14 | 5. [IHME Global Health Indicators](#ihme-global-health-indicators) 15 | 6. [Google Flu Trends](#google-flu-trends) 16 | 7. [Ebola Outbreaks 1976-2013](#ebola-outbreaks-1976-2013) 17 | 8. [Dashboard Pro Tips](#pro-tips) 18 | 9. [Crossfilter for Data Scientists and Programmers](#crossfilter-for-data-scientists-and-programmers) 19 | 10. [Roadmap](#roadmap) 20 | 21 | ## Crossfilter Overview 22 | 23 | Crossfilter is a visual analysis technique for multidimensional data. It is used to clarify relationships between dimensions. 24 | 25 | To use crossfilter, simply click-and-drag on a chart in one of the linked plot.ly dashboards below. Selected data that shares common rows with other charts will highlight and all other data will fade out. To reset the dashboard, click anywhere on a graph that doesn't have data. 26 | 27 | To make crossfilter dashboards in plot.ly, make sure each dashboard chart is made from the same dataset. Once your dashboard is constructed, enable crossfilter under Settings > Filter. Follow one of the tutorials linked below for a full and illustrated guide to this workflow. 28 | 29 | ## California Measles Outbreak 30 | 31 | | Dashboard Metadata | Link | 32 | | -------------------------------- | ------------------------------------------------------- | 33 | | Link to dashboard | https://plot.ly/dashboard/jackp:18123/present | 34 | | Dataset on plot.ly | https://plot.ly/~jackp/18114/ | 35 | | Original dataset | [Project Tycho at U. Pittsburgh](http://bit.ly/2zrVG6s) | 36 | | Tutorial to make this dashboard | [Tutorial](tutorials/measles-dashboard.md) | 37 | | Plotly.js charts in dashboard | 3d scatter chart, 2d scatter chart, box plot | 38 | 39 | #### Example observations 40 | 41 | - You can see a share fall in measles cases after 1968 when the vaccinne was introduced. 42 | - There were smaller outbreaks in 1988 and 1991. 43 | - Weeks in the springtime had more outbreaks than any other season. 44 | 45 | ![measles-outbreak-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/california_measles_outbreaks.gif) 46 | 47 | ## Aid Agencies during Ebola Outbreak 48 | 49 | | Dashboard Metadata | Link | 50 | | -------------------------------- | --------------------------------------------------------- | 51 | | Link to dashboard | https://plot.ly/dashboard/jackp:18133/present | 52 | | Dataset on plot.ly | https://plot.ly/~jackp/18129/ | 53 | | Original dataset | [Humanitarian Data Exchange (HDE)](http://bit.ly/2zq86Mh) | 54 | | Dashboard inspiration | [Simon B. Johnson](http://bit.ly/2zyztRN) | 55 | | Tutorial to make this dashboard | [Tutorial](tutorials/aid-agency-dashboard.md) | 56 | | Plotly.js charts in dashboard | Mapbox-gl scatter plot, pie charts, bar chart | 57 | 58 | #### Example observations 59 | 60 | - Liberia had the most reported cases and most aid December 10, 2013 61 | - Only 11 aid organizations were reported in Sierra Leone 62 | - WHO provided 6 aid activities - Social mobilization, surveillance, coordination, safe burial, psychological support, and logistics 63 | 64 | ![ebola-aid-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/ebola_humanitarian_aid.gif) 65 | 66 | ## U.S. Police officer deaths by cause 67 | 68 | | Dashboard Metadata | Link | 69 | | -------------------------------- | --------------------------------------------------------- | 70 | | Link to dashboard | https://plot.ly/dashboard/jackp:18052/present | 71 | | Dataset on plot.ly | https://plot.ly/~public.health/17/ | 72 | | Original dataset | [FiveThirtyEight](http://bit.ly/237YWtv) | 73 | | Dashboard inspiration | [FiveThirtyEight](http://53eig.ht/2AsMFqG) | 74 | | Tutorial to make this dashboard | [Tutorial](tutorials/police-report-deaths.md) | 75 | | Plotly.js charts in dashboard | Pie chart, scatter plot, choropleth map | 76 | 77 | #### Example observations 78 | 79 | - After gunfire, the 2nd highest cause of death for on-duty police officers in Alaska is aircraft incidents 80 | - 14 states have reported on-duty police officer cause of death as "struck by train" 81 | - Wyoming has the lowest police officer death rate by gunfire 82 | 83 | ![police-officer-deaths-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/on_duty_policy_deaths.png) 84 | 85 | ## Comparing 1990 and 2015 Infant Mortality Index 86 | 87 | | Dashboard Metadata | Link | 88 | | -------------------------------- | --------------------------------------------------------- | 89 | | Link to dashboard | https://plot.ly/dashboard/jackp:18103/present | 90 | | Dataset on plot.ly | https://plot.ly/~jackp/18100 | 91 | | Original dataset | [World Bank](http://bit.ly/2i2SBjs) | 92 | | Dashboard inspiration | [World Bank](http://bit.ly/2i2SBjs) | 93 | | Tutorial to make this dashboard | [Tutorial](tutorials/infant-mortality-index.md) | 94 | | Plotly.js charts in dashboard | Choropleth maps, scatter plot | 95 | 96 | #### Example observations 97 | 98 | - IMI improved in every country except Dominca between 1990 and 2005 99 | 100 | ![infant-mortality-index-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/infant_mortality_index.png) 101 | 102 | ## IHME Global Health Indicators 103 | 104 | | Dashboard Metadata | Link | 105 | | -------------------------------- | --------------------------------------------------------- | 106 | | Link to dashboard | https://plot.ly/dashboard/Dreamshot:8925/present | 107 | | Dataset on plot.ly | https://plot.ly/~Dreamshot/8914/ | 108 | | Original dataset | [IHME Viz Hub](https://vizhub.healthdata.org/gbd-compare/)| 109 | | Dashboard inspiration | [IHME Viz Hub](https://vizhub.healthdata.org/gbd-compare/)| 110 | | Tutorial to make this dashboard | [Tutorial](tutorials/ihme-dashboard.md) | 111 | | Plotly.js charts in dashboard | Choropleth maps, bubble charts | 112 | 113 | #### Example observations 114 | 115 | - This dashboard is mainly to show crossfilter with a variety of map projections. 116 | 117 | ![IHME-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/IHME_crossfilter_gif.gif) 118 | 119 | ## Google Flu Trends 120 | 121 | | Dashboard Metadata | Link | 122 | | -------------------------------- | --------------------------------------------------------- | 123 | | Link to dashboard | https://plot.ly/dashboard/Dreamshot:9045/present | 124 | | Dataset on plot.ly | https://plot.ly/~Dreamshot/9040/ | 125 | | Original dataset | [US Google Flu Trends CSV](http://bit.ly/2yEtQQU) | 126 | | Dashboard inspiration | [Flu Trends Public Data Explorer](http://bit.ly/2AGrm56) | 127 | | Tutorial to make this dashboard | [Tutorial](tutorials/google-flu-trends.md) | 128 | | Plotly.js charts in dashboard | Time series, histograms, box plots | 129 | 130 | #### Example observations 131 | 132 | - This dashboard is mainly to show crossfilter of distribution plots (box plots and histograms) together with time series. 133 | 134 | ![google-flu-trends-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/Google_Flu_Trends.png) 135 | 136 | ## Ebola Outbreaks 1976-2013 137 | 138 | | Dashboard Metadata | Link | 139 | | -------------------------------- | --------------------------------------------------------- | 140 | | Link to dashboard | https://plot.ly/dashboard/jackp:17876/present | 141 | | Dataset on plot.ly | https://plot.ly/~public.health/8 | 142 | | Original dataset | [Nature: Science Direct](http://go.nature.com/2zKJN9u) | 143 | | Dashboard inspiration | [Nature: Science Direct](http://go.nature.com/2zKJN9u) | 144 | | Tutorial to make this dashboard | [Tutorial](tutorials/ebola-outbreaks.md) | 145 | | Plotly.js charts in dashboard | Time series, D3 map with hover text, SVG table | 146 | 147 | #### Example observations 148 | 149 | - This dashboard is mainly to show using crossfilter with tables. 150 | 151 | ![ebola-outbreak-dashboard](https://github.com/plotly/public-health/raw/master/screencasts/ebola_outbreak.png) 152 | 153 | ## Pro Tips 154 | 155 | Here are a few Pro Tips when creating crossfilter dashboards on Plot.ly: 156 | 157 | 1. To enable crossfilter in Plot.ly dashboards, make sure that all graphs in the dashboard are made from the same dataset and that crossfilter is enabled in the Filter tab of Dashboard Settings. 158 | If dashboard plots are made from multiple datasets and crossfilter is enabled, Plotly will attempt to merge them if all datasets have the same number of rows. If you intend to build a crossfilter dashboard from multiple datasets and cannot merge them in a data preparation tool beforehand, make sure that the datasets are the same length and sorted in the same order. 159 | 2. Right-click (or Ctrl-click) on the Plot.ly spreadsheet for a menu of data preparation tools including: 160 | 1. Convert dates to Plotly date format 161 | - E.g. **December 10, 2016 -> 12-10-2016** 162 | 2. Find... Replace 163 | 3. Merge 2 or more columns with a delimiter 164 | - E.g. **| December | 10 | → December-10** 165 | 4. Merge week of year and year columns into Plotly date format 166 | - E.g. **| 48 | 2016 | → 12-28-2016** 167 | 5. Convert **state name** to **state abbreviation** (for use in choropleth maps) 168 | - E.g. **Vermont → VT** 169 | 6. Cumulative sum 170 | 7. Sometimes you will still have to prep datasets before plotting using a tool like Google Sheets, Python, or R 171 | 3. Raw CSV links on GitHub such as [https://gist.githubusercontent.com/.../mpg.csv](https://gist.githubusercontent.com/omarish/5687264/raw/7e5c814ce6ef33e25d5259c1fe79463c190800d9/mpg.csv) can be imported directly into Plot.ly from the the "URL" tab of the Import tool. 172 | 4. You can access the dataset behind a dashboard plot by: 173 | 1. Selecting "View Plot" under the cog menu in the upper-right corner of the plot 174 | 2. On the plot page, select the "Sources" tab. "Sources" is a tree view of the data sources that make up a plot. The data sources can be created by the author of the plot or a different Plot.ly user. 175 | 3. In the tree view, the root nodes on the left side are the datasets that make up the plot. Click on them to go to the home page for the dataset. 176 | 5. Use the [Plotly modebar](https://help.plot.ly/getting-to-know-the-plotly-modebar/) in the upper-right corner of dashboard plots to change the cursor mode between hover, zoom, and panning states. The modebar can also download a PNG image of plots. 177 | 6. Disable default zoom in dashboard plots to prevent users from accidentally zooming as they scroll through your dashboard. You can disabled zoom for your plot under **Axes → Zoom Interactivity** inside [Chart Studio](https://plot.ly/online-chart-maker/). 178 | 7. Minimize the ink-to-data ratio: Make plots minimalistic or they will be overwhelming when combined in a dashboard. 179 | 180 | ![ink-data-ratio](https://static1.squarespace.com/static/56713bf4dc5cb41142f28d1f/t/5671eae2816924fc2265189a/1454121618204/data-ink.gif?format=750w) 181 | 182 | *(Fantastic GIF via [Dark Horse](http://www.darkhorseanalytics.com/blog/data-looks-better-naked)* 183 | 184 | ## Crossfilter for Data Scientists and Programmers 185 | 186 | If you know how to program in R, Python, or JavaScript, you likely do not need a crossfilter GUI such as [Plotly Dashboards](https://plot.ly/dashboards-and-reports/) or Tableau. Instead, you can use Plotly graphics and a crossfilter engine written in R, Python, or JavaScript crossfilter engine. We recommend using [Dash](https://plot.ly/dash/) for Python, Shiny for R, and [crossfilter.js](https://github.com/square/crossfilter) for JavaScript. Here are 3 simple public health crossfilter examples in each language: 187 | 188 | - **Python/Dash**: Zika Outbreak 189 | - App: https://zika-crossfilter.herokuapp.com/ 190 | - Code: https://github.com/charleyferrari/zika-crossfilter/ 191 | - **R/Shiny**: Zika Outbreak 192 | - Code: https://github.com/cpsievert/zikar 193 | - **JavaScript/crossfilter.js**: World Bank Health Indicators 194 | - App: https://plotly.github.io/plotly.js-crossfilter.js/ 195 | - Code: https://github.com/plotly/plotly.js-crossfilter.js 196 | 197 | ## Roadmap 198 | 199 | 2018 work on Plotly and Plotly.js support for crossfilter will fall under 3 broad categories: 200 | 201 | ### 1. Crossfilter support for all Plotly.js chart types 202 | 203 | Not all of Plotly.js charts currently support interactive data selection via the mouse. Without a drilldown tool for selecting data, a chart cannot initiate crossfilter inside a dashboard. These charts are listed under *"Charts without data selection"* in the table below below. 204 | 205 | Some charts have a data selection tool, but are not yet wired into the crossfilter program in Plot.ly dashboards. These charts, listed under *"Charts not yet connected to crossfilter on Plot.ly"*, will not respond to crossfilter selection inside dashboard. 206 | 207 | In 2018 we'll continue to add data selection and crossfilter responsivity across :100: of Plotly.js charts. 208 | 209 | | Charts with data selection | Charts without data selection | Charts not yet integrated with crossfilter on Plot.ly | 210 | | ------------------------------- | ----------------------------- | ----------------------------------------------------- | 211 | | Mapbox-gl maps | Heatmaps | Heatmaps | 212 | | D3 maps | Lines | Contour plots | 213 | | Scatter plots | Tables | Violin plots | 214 | | Box plots | 3d plots | Sankey diagrams | 215 | | Histograms | Contour plots | Parcoords ("parallel coordinate plots") | 216 | | Choropleth maps | | Multiple y-axis plots | 217 | | Bar charts | | Line plots | 218 | | Bubble charts | | | 219 | | Pie charts (by slice clicking) | | | 220 | | Parcoords (by axis filter) | | | 221 | | Sankey diagrams (by click event)| | | 222 | | Violin plots | | | 223 | 224 | [Related Plotly.js issues](https://github.com/plotly/plotly.js/milestone/25) 225 | 226 | ### 2. Optimizing Plotly.restyle and Plotly.addTraces speed 227 | 228 | Crossfilter on Plot.ly currently works by: 229 | 230 | 1. Listening for a data selection event 231 | 2. Sending the selected data to [crossfilter.js](https://github.com/square/crossfilter) for processing 232 | 3. Updating all graphs on the dashboard with a combination of [Plotly.restyle](https://plot.ly/javascript/plotlyjs-function-reference/#plotlyrestyle) and [Plotly.addTraces](https://plot.ly/javascript/plotlyjs-function-reference/#plotlyaddtraces) 233 | 234 | In order to achieve subsecond dashboard updates with crossfilter, [Plotly.restyle](https://plot.ly/javascript/plotlyjs-function-reference/#plotlyrestyle) and [Plotly.addTraces](https://plot.ly/javascript/plotlyjs-function-reference/#plotlyaddtraces) will need to be optimized. 235 | 236 | [Related Plotly.js issues](https://github.com/plotly/plotly.js/issues/1850) 237 | 238 | ### 3. Open-sourcing crosslink-plotly.js library 239 | 240 | The Plotly.js crossfilter wrapper written for Plot.ly dashboards ([crosslink-plotly.js](https://github.com/plotly/crosslink-plotly.js)) will be documented and published on NPM so that Web developers can build Tableau-style dashboards without getting bogged down in the low level interfaces of [crossfilter.js](https://github.com/square/crossfilter), [Plotly.restyle](https://plot.ly/javascript/plotlyjs-function-reference/#plotlyrestyle), and [Plotly.addTraces](https://plot.ly/javascript/plotlyjs-function-reference/#plotlyaddtraces). 241 | -------------------------------------------------------------------------------- /screencasts/Google_Flu_Trends.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/plotly/public-health/779bd9351b8dd497cd0cb539d1e3b60271159ef3/screencasts/Google_Flu_Trends.png 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these data further. 4 | 5 | ## Contents 6 | 7 | - [Data](#1-data) 8 | - [Create a Chart](#2-create-a-chart) 9 | - [Aid Agency Location Satellite Map](#21-agency-location-satellite-map) 10 | - [Activities Pie Chart](#22-activities-pie-chart) 11 | - [Countries Pie Chart](#23-countries-pie-chart) 12 | - [Total Activity Bar Chart](#24-total-activity-bar-chart) 13 | - [Create a Dashboard](#3-create-a-dashboard) 14 | - [Add Charts](#31-add-charts) 15 | - [Style It](#32-style-it) 16 | - [Crossfilter](#4-crossfilter) 17 | 18 | 19 | ## 1. Data 20 | 21 | To get started, head to Plotly’s [Chart Studio](https://plot.ly/create/) and add your data. You have the option of typing directly in the grid, uploading your file, or entering a URL of an online dataset. For this tutorial, we'll use the 3W Dataset on the Organizations Involved in the Response to the Ebola Crisis dataset from the [Humanitarian Data Exchange (HDE)](http://bit.ly/2zq86Mh). To begin, simply view the [dataset](https://plot.ly/~jackp/18129/) and click **'Fork & Edit'**. The Chart Studio ought to have opened and you're all set to go 22 | 23 | ![Fork and Edit](../screencasts/aid-agency/satellite/fork-and-edit.png) 24 | 25 | Alternatively, navigate to the [Chart Studio](https://plot.ly/create/) and click **Import**, **By URL**, and then paste in the **URL** (https://plot.ly/~jackp/18129.csv). 26 | 27 | ![Add Data](../screencasts/aid-agency/satellite/add-data.png) 28 | 29 | ## 2. Create a Chart 30 | 31 | To visualize aid agencies during the Ebola outbreak, we'll create four individual charts: (1) a satellite map to illustrate aid agency location, (2) a pie chart indicating aid agency activity, (3) another pie chart looking at countries, and (4) a bar chart highlighting the total activity by relief organizations. In the section below, we'll look at how to make each of the charts. 32 | 33 | ### 2.1. Agency Location Satellite Map 34 | 35 | ##### 2.1.1. Create 36 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Satellite Maps** from the *Maps* column. 37 | 38 | ![Chart Type](../screencasts/aid-agency/satellite/chart-type.png) 39 | 40 | Now to populate the graph with data, in the *Latitude* and *Longitude* dropdown select **Lat** and **Lon**, respectively. Additionally, add **Region** in the *hover text* dropdown to display region names on hover. 41 | 42 | ![Trace Values](../screencasts/aid-agency/satellite/trace-values.png) 43 | 44 | ##### 2.1.2. Layout 45 | Now that the map is populated with scatter points, navigate to the *Layout* to fix the map positioning and map style to help focus in on the data points. First, open the *Map Style* box and select **Light** from the dropdown menu to change the map to a lighter style. 46 | 47 | ![Map Style](../screencasts/aid-agency/satellite/map-style.png) 48 | 49 | Next, click *Map Positioning* to adjust the center and zoom of the map. Set *Center Latitude* to **8.5**, *Center Longitude* to **-10**, and *Zoom Level* to **5.4**. The map now ought to display West Africa. 50 | 51 | ![Map Positioning](../screencasts/aid-agency/satellite/map-position.png) 52 | 53 | To make the map the full width and height, open *Margins and Paddings* and set all the values to **0**. 54 | 55 | ![Margins](../screencasts/aid-agency/satellite/margins.png) 56 | 57 | ##### 2.1.3. Traces 58 | With our layout styled, navigate to the *Traces* tab to style the data points. Here, set the color to **#000000**, *Diameter* to **16**, and **Select / Tick All Values** in the *Values Shown on Hover*. 59 | 60 | ![Trace Values](../screencasts/aid-agency/satellite/trace-styles.png) 61 | 62 | ##### 2.1.4. Save 63 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 64 | 65 | ![Save](../screencasts/aid-agency/satellite/save.png) 66 | 67 | ### 2.2. Activities Pie Chart 68 | Using the same grid as the previous plot, open the data in the Chart Studio. 69 | 70 | ##### 2.2.1. Create 71 | Again, now that we have the data in the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Pie Chart** from the *Business* column. 72 | 73 | ![Chart Type](../screencasts/aid-agency/pie-chart-activity/chart-type.png) 74 | 75 | Next, we can populate the graph by selecting **Activity** in the *Labels* dropdown. You ought to see a pie chart with a legend like below. 76 | 77 | ![Trace Values](../screencasts/aid-agency/pie-chart-activity/trace-values.png) 78 | 79 | ##### 2.2.2. Traces 80 | To style the pie chart, we can make changes to the text, colors, borders, and order. To do so, navigate to the *Traces* tab under *Style*. Here, select ** Label** and unselect ** %**, change the *Typeface* to **Raleway**, set the *Slice Order* to **Clockwise**, and the *Rotation* to **130 degrees**. Additionally, to make the slices more defined set the *Border Width* to **1**. 81 | 82 | ![Trace Styles](../screencasts/aid-agency/pie-chart-activity/trace-styles.png) 83 | 84 | ##### 2.2.3. Legend 85 | With the styling done and the option to use labels directly on the slices, the legend on the right-hand side is redundant. Thus, click *Legend* under *Style* and select **Hide**. 86 | 87 | ![Legend](../screencasts/aid-agency/pie-chart-activity/legend.png) 88 | 89 | ##### 2.2.4. Save 90 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 91 | 92 | 93 | ![Save](../screencasts/aid-agency/pie-chart-activity/save.png) 94 | 95 | ### 2.3. Countries Pie Chart 96 | Using the same grid as the previous plot, open the data in the Chart Studio. 97 | 98 | ##### 2.3.1. Create 99 | Like the previous pie chart, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Pie Chart** from the *Business* column. 100 | 101 | ![Chart Type](../screencasts/aid-agency/pie-chart-countries/chart-type.png) 102 | 103 | Populate the graph by selecting **Country** in the *Labels* dropdown. You ought to see a pie chart with a legend like below. 104 | 105 | ![Trace Values](../screencasts/aid-agency/pie-chart-countries/trace-values.png) 106 | 107 | ##### 2.3.2. Traces 108 | To style the pie chart, we can make changes to the text, colors, borders, and order. To do so, navigate to the *Traces* tab under *Style*. Here, **select Label, Value, and %**, change the *Typeface* to **Raleway**, and the *Rotation* to **120 degrees**. Additionally, to make the slices more defined set the *Border Width* to **1**. 109 | 110 | ![Trace Styles](../screencasts/aid-agency/pie-chart-countries/trace-styles.png) 111 | 112 | ##### 2.3.3. Legend 113 | With the styling done and the option to use labels directly on the slices, the legend on the right-hand side is redundant. Thus, click *Legend* under *Style* and select **Hide**. 114 | 115 | ![Legend](../screencasts/aid-agency/pie-chart-countries/legend.png) 116 | 117 | ##### 2.3.4. Save 118 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 119 | 120 | ![Save](../screencasts/aid-agency/pie-chart-countries/save.png) 121 | 122 | 123 | ### 2.4. Total Activity Bar Chart 124 | Using the same grid as the previous plot, open the data in the Chart Studio. 125 | 126 | ##### 2.4.1. Create 127 | After loading the data, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and select **Bar Chart** from the *Business* column. 128 | 129 | ![Chart Type](../screencasts/aid-agency/bar-chart/chart-type.png) 130 | 131 | Now, you ought to see *y*, *x*, and *Hover Text* dropdowns. Select **Lat**, **Organisation**, and **Org type**, respectively. 132 | 133 | ![Trace Values](../screencasts/aid-agency/bar-chart/trace-values.png) 134 | 135 | ##### 2.4.2. Aggregate 136 | As we are wanting to display the total count for each organization, under *Graph* click *Aggregate*. Next, click the blue *+ Agreggate* button. In the box that appears, select **Organisation** as the *Group By Column*. Set *Trace* to **Lat**, *x* to **first**, and aggregate *y* by **count**. 137 | 138 | ![Aggregate](../screencasts/aid-agency/bar-chart/aggregate.png) 139 | 140 | ##### 2.4.3. Layout 141 | Now that our data displays the total count for each organization, we can style the layout. More specifically, the margins. Navigate to *Layout*, open *Margins and Paddings* and set the values to **0, 400, 20, 0, 0**, respectively. 142 | 143 | ![Margins](../screencasts/aid-agency/bar-chart/margins.png) 144 | 145 | ##### 2.4.4. Axes 146 | With the margins adjusted and the x axis tick labels visible, select *Axes* under *Style* to style the tick labels. First, however, open the *Titles*, select *All* and **Remove All Titles**. 147 | 148 | ![Axes Titles](../screencasts/aid-agency/bar-chart/axes-titles.png) 149 | 150 | To style the tick labels, open *Tick Labels* and set the *Typeface* to **Raleway** and *Angle* to **90 degrees**. This is to ensure that the tick labels always stay at 90 degrees. 151 | 152 | ![Tick Labels](../screencasts/aid-agency/bar-chart/tick-labels.png) 153 | 154 | Lastly, at the bottom of *Axes* open the *Zoom Interactivity* box, select *All* and **Disable**. 155 | 156 | ![Zoom](../screencasts/aid-agency/bar-chart/zoom.png) 157 | 158 | ##### 2.4.5. Save 159 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 160 | 161 | ![Save](../screencasts/aid-agency/bar-chart/save.png) 162 | 163 | ## 3. Create a Dashboard 164 | 165 | With the charts completed and saved in your [home folder](https://plot.ly/organize/home), we can now create a dashboard by simply adding these charts, adjusting the layout, and styling the dashboard before sharing and interacting. To get started with creating a dashboard, hover over the *+Create* button and select **Dashboard** from the menu. Alternatively, open this [link](https://plot.ly/dashboard/create). 166 | 167 | ### 3.1. Add Charts 168 | 169 | First, to add the Aid Agency Location Satellite Map, click *+Plot* in the bottom left corner of the screen. A new box ought to appear with the option to 'Add a Plot'. Click, the *'Your Files'* option and then in the pop-up select the ** Aid Agency Location Satellite Map ** we made earlier. 170 | 171 | ![Add Satellite Map](../screencasts/aid-agency/dashboard/add-plot.png) 172 | 173 | Next, add the Activities Pie Chart following the same process. This time drag and drop the plot on the right half of the satellite map. 174 | 175 | ![Add Pie Chart Activity](../screencasts/aid-agency/dashboard/add-pie1.png) 176 | 177 | Again, follow the same process for the Countries Pie Chart. However, drag and drop Countries Pie Chart on the bottom half of the Activities Pie Chart. You ought to see something like below. 178 | 179 | ![Add Pie Chart Country](../screencasts/aid-agency/dashboard/add-pie2.png) 180 | 181 | For the final plot, the Total Activity Bar Chart, simply add this to the bottom of the dashboard. 182 | 183 | ![Add Bar Chart](../screencasts/aid-agency/dashboard/add-bar-chart.png) 184 | 185 | Now that we have added all the plots to the dashboard, for each plot where it says, "Enter a title..." insert plot titles: **"Map (darker locations had more relief attention)"**, **Activities**. **Countries**, and **Relief Organization Total Activity Count**, in the same order as we added the plots. Your result ought to look like below. 186 | 187 | ![Add Plot Titles](../screencasts/aid-agency/dashboard/add-plot-title.png) 188 | 189 | ### 3.2. Style It 190 | 191 | Now that we have the structure of our dashboard, we can style it. To do so, navigate to the *Settings Icon* directly opposite the dashboard title. When hovering you ought to see the option **Settings** from the menu. 192 | 193 | ![Settings](../screencasts/aid-agency/dashboard/settings.png) 194 | 195 | After clicking **Settings**, a panel ought to appear from the right-hand side of the screen. Here, we have the option of *Headers*, *Colors*, *Text*, *Layout*, and *Filter*. First, in *Headers*, we can set the title, add a logo, and multiple links. For this tutorial, add **"UN Office for the Coordination of Humanitarian Affairs"** to the *Title* text box. Next, let's add the OCHA ROWCA logo. We can do this by simply adding the URL for the logo PNG: **http://www.elrha.org/wp-content/uploads/2015/01/ocha.jpg**. As previously mentioned you can add links, in this tutorial we'll use this feature to link the original dataset. Thus, add the text **"December 10, 2013 Data"** with the URL: **https://data.humdata.org/dataset/3w-dataset-on-the-organizations-involved-in-the-response-to-the-ebola-crisis**. 196 | 197 | ![Header](../screencasts/aid-agency/dashboard/header.png) 198 | 199 | In the next tab, *Colors*, we can manipulate the background, borders, and text colors. As you can see, the dashboard has already added these by default. That said, for this dashboard we will set *Header Background*, *Page Background*, *Box Background*, *Box Border*, and *Box Header Background* to **#FFFFFF**. 200 | 201 | ![Colors](../screencasts/aid-agency/dashboard/colors.png) 202 | 203 | *Text*, the third settings option, allows you to control all things text, including font color, family, and size, as well as header styles and text box styles. Again, like the Colors tab, some values are defined. However, here, we'll set the *Font Family* to **Raleway**. Make the header font larger by selecting **2.2em** in the *Header Font Size* and, additionally, change the *Header Font Weight* to **300**. 204 | 205 | ![Text](../screencasts/aid-agency/dashboard/text.png) 206 | 207 | In *Layout*, you have the option of setting the page layout as either a dashboard or a report. Here, we'll leave it as the default dashboard setting. The last settings category, *Filter*, provides you with the option to enable or disable the Search Bar or the Crossfilter feature. For this tutorial, leave the *Search Bar* as is but let’s enable the *Crossfilter* feature by selecting **Enable** (for more information about this feature see the next section). 208 | 209 | ![Filter](../screencasts/aid-agency/dashboard/filter.png) 210 | 211 | Congrats, your dashboard is complete! Click **Save** on in the bottom right-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all), or **Private Link** (visible only to those who you share the link with), or **Private** (visible only to you) and hit **Save**. . 212 | 213 | ![Save](../screencasts/aid-agency/dashboard/save.png) 214 | 215 | ## 4. Crossfilter 216 | Finally, we'll briefly demonstrate crossfilter. 217 | 218 | Crossfilter is a visual analysis technique for multidimensional data. It is used to clarify relationships between dimensions. As discussed in the previous section, crossfilter functionality is invoked by setting **Enable** in *Settings* > *Filter*. 219 | 220 | To use crossfilter, simply click-and-drag on a chart. Selected data that shares common rows with other charts will highlight and all other data will fade out. To reset the dashboard, click anywhere on a graph that doesn't have data. 221 | 222 | ![Crossfilter](../screencasts/ebola_humanitarian_aid.gif) 223 | -------------------------------------------------------------------------------- /tutorials/ebola-outbreaks.md: -------------------------------------------------------------------------------- 1 | # Ebola Outbreaks 1976-2013 2 | In this tutorial, we'll create and style multiple individual plots in the Chart Studio, add them to a dashboard, and utilize the crossfilter feature to interact and explore these data further. 3 | 4 | ## Contents 5 | 6 | - [Data](#1-data) 7 | - [Create a Chart](#2-create-a-chart) 8 | - [Outbreak Location Map](#21-outbreak-location-map) 9 | - [Deaths Per Outbreak Scatter Plot](#22-deaths-per-outbreak-scatter-plot) 10 | - [Ebola Outbreak Table](#23-ebola-outbreak-table) 11 | - [Create a Dashboard](#3-create-a-dashboard) 12 | - [Add Charts](#31-add-charts) 13 | - [Style It](#32-style-it) 14 | - [Crossfilter](#4-crossfilter) 15 | 16 | 17 | ## 1. Data 18 | 19 | To get started, head to Plotly’s [Chart Studio](https://plot.ly/create/) and add your data. You have the option of typing directly in the grid, uploading your file, or entering a URL of an online dataset. For this tutorial, we'll use the Ebola Outbreak dataset from [Nature: Science Direct](http://go.nature.com/2zKJN9u). To begin, simply view the [dataset](https://plot.ly/~public.health/8) and click **'Fork & Edit'** to begin. The Chart Studio ought to open and you're all set to go. 20 | 21 | ![Fork and Edit](../screencasts/ebola-outbreaks/atlas/fork-and-edit.png) 22 | 23 | Alternatively, navigate to the [Chart Studio](https://plot.ly/create/) and click **Import**, **By URL**, and then paste in the **URL** (https://plot.ly/~public.health/8.csv). 24 | 25 | ![Add Data](../screencasts/ebola-outbreaks/atlas/add-data.png) 26 | 27 | ## 2. Create a Chart 28 | 29 | To visualize Ebola outbreaks from 1973 to 2013, we'll create three individual charts: (1) an outbreak location atlas map, (2) a scatter plot looking at deaths per outbreak, and (3) a table to display all outbreak data. In the section below, we'll look at how to make each of the charts. 30 | 31 | ### 2.1. Outbreak Location Map 32 | 33 | ##### 2.1.1. Create 34 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Atlas Maps** from the *Maps* column. 35 | 36 | ![Chart Type](../screencasts/ebola-outbreaks/atlas/chart-type.png) 37 | 38 | Now to populate the graph with data, in the *Latitude* and *Longitude* dropdown select **LAT** and **LONG**, respectively. Additionally, add **NAME** in the *Hover Text* dropdown to display names on hover and **OB_DEATH** to *Color*. As we are looking at the Ebola outbreaks which took place in Africa, set *Map Region* to **Africa**. 39 | 40 | ![Trace Values](../screencasts/ebola-outbreaks/atlas/trace-values.png) 41 | 42 | ##### 2.1.2. Traces 43 | With our trace values entered, next, open *Traces* to begin styling the plot. First, set the *Colorscale* to **Pink/Green** (roughly the 9th from the left), and the select **Reversed** and **Show Color Bar**. Moving on to style the points, alter the *Diameter* to **5**, *Border Width* to **0.5**, and set the *Border-Color* to **#FFFFFF**. Your data points ought to look like the ones below. 44 | 45 | ![Trace Styles](../screencasts/ebola-outbreaks/atlas/trace-styles.png) 46 | 47 | ##### 2.1.3. Layout 48 | Next, navigate to the *Layout* tab to set the background colors and margins. To complete the former, open the *Canvas* box and set *Plot* and *Margin Color* to **#F2F5FA**. 49 | 50 | ![Canvas](../screencasts/ebola-outbreaks/atlas/canvas.png) 51 | 52 | Below *Layout*, open the *Title and Fonts* box and under *Global Font*, set *Typeface* to **Raleway** and *Font Size* to **12**. 53 | 54 | ![Global Font](../screencasts/ebola-outbreaks/atlas/global-font.png) 55 | 56 | To make the atlas map full width and height, open *Margins and Paddings* and set all the values to **0**. 57 | 58 | ![Margins](../screencasts/ebola-outbreaks/atlas/margins.png) 59 | 60 | In atlas maps, we have *Geo Style* and *Geo Layout*. To alter the former, select *Geo Style* and set *Land* to **Show** and *Color* **#222222**; *Coastlines* to **Show**, **1**, and **#444444**; *Oceans* to **Show** and **#FFFFFF**; *Country* to **Show**, **0.2**, **#A2B1C6**. Now, you ought to see substantial changes to the map style. 61 | 62 | ![Geo Style](../screencasts/ebola-outbreaks/atlas/geo-style.png) 63 | 64 | Next, in *Geo Layout* you can define attributes such as *Map Scope*, *Projection*, *Rotation*, *Scale*, and *Map Resolution*. Set the latter two to **2** and **1:50,000,000**, respectively. 65 | 66 | ![Geo Layout](../screencasts/ebola-outbreaks/atlas/geo-layout.png) 67 | 68 | ##### 2.1.4. Color Bars 69 | Finally, you can style the color bar by navigating to *Color Bars*. For this tutorial, in the *Title* box we enter the title **Deaths per Outbreak** and set the *Typeface* to **Raleway**. 70 | 71 | ![Color Bar Title](../screencasts/ebola-outbreaks/atlas/color-bar-title.png) 72 | 73 | Now to minimize the size of the color bar, select the *Size and Positioning* box and set the *Height* to **0.8** and *Width* to **20**. 74 | 75 | ![Color Bar Size](../screencasts/ebola-outbreaks/atlas/color-bar-size.png) 76 | 77 | ##### 2.1.5. Save 78 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 79 | 80 | ![Save](../screencasts/ebola-outbreaks/atlas/save.png) 81 | 82 | ### 2.2. Deaths Per Outbreak Scatter Plot 83 | Using the same grid as the previous plot, open the data in the Chart Studio. 84 | 85 | ##### 2.2.1. Create 86 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Scatter** from the *Business* column. 87 | 88 | ![Chart Type](../screencasts/ebola-outbreaks/scatter/chart-type.png) 89 | 90 | Now to populate the graph with data, in the *x* and *y* dropdown select **PLOTLY_DATE** and **OB_DEATH**, respectively. Additionally, we want to color these data by deaths, thus in the *Color* dropdown select **OB_DEATH**. Lastly, add **NAME** to *hover text*. 91 | 92 | ![Trace Values](../screencasts/ebola-outbreaks/scatter/trace-values.png) 93 | 94 | ##### 2.2.2. Traces 95 | Now that we have a graph with data we can style it. Thus, navigate to *Traces* and set the *Colorscale* to **Greyscale** and **Reversed**. Further below, set the *Diameter* to **10** to make the data points larger and then set Border Width to **2**, which will help define the lighter colored markers. 96 | 97 | ![Trace Styles](../screencasts/ebola-outbreaks/scatter/trace-styles.png) 98 | 99 | ##### 2.2.3. Axes 100 | We won't style this plot that much, so we'll just remove the titles by clicking *Axes*, *Titles*, *All*, and then deleting **MIXED_VALUES**. 101 | 102 | ![Axes Title](../screencasts/ebola-outbreaks/scatter/axes-titles.png) 103 | 104 | Finally, open *Zoom Interactivity* and select **Disable**. 105 | 106 | ![Zoom](../screencasts/ebola-outbreaks/scatter/zoom.png) 107 | 108 | ##### 2.2.4. Save 109 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 110 | 111 | ![Save](../screencasts/ebola-outbreaks/scatter/save.png) 112 | 113 | ### 2.3. Ebola Outbreak Table 114 | Using the same grid as the previous plot, open the data in the Chart Studio. 115 | 116 | ##### 2.3.1. Create 117 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Table** from the *Statistics* column. 118 | 119 | ![Chart Type](../screencasts/ebola-outbreaks/table/chart-type.png) 120 | 121 | Now to populate the table with data, we need to define the *Header Values* and *Columns*. Thus, add **HEADER_VALUES** to the former and **NAME**, **VIRUS**, **LAT**, **LONG**, **OB_DEATH**, **OB_END_YEAR**, **PLOTLY_DATE**, **CS_DEATH** to the latter. Lastly, add **VIRUS** to *Header Fill Color*. 122 | 123 | ![Trace Values](../screencasts/ebola-outbreaks/table/trace-values.png) 124 | 125 | ##### 2.3.2. Traces 126 | To style tables, it is divided into two sections: *Header* and *Cells*. For the *Header*, set the *Typeface* to **Raleway**, *Font Color* to **#FFFFFF**, and the *Border Color* to **#C8D4E3**. For the *Cells*, set the *Fill Color* to **#F2F5FA**, *Cell Height* to **28**, and the *Border Color* the same as the *Header*. 127 | 128 | ![Trace Styles](../screencasts/ebola-outbreaks/table/trace-styles.png) 129 | 130 | ##### 2.3.3. Layout 131 | Finally, navigate to the *Layout* tab, open *Margins and Paddings* and set all the values to **0** to make the table the full width and height. 132 | 133 | ![Margins](../screencasts/ebola-outbreaks/table/margins.png) 134 | 135 | ##### 2.3.4. Save 136 | Congrats, your table is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 137 | 138 | ![Save](../screencasts/ebola-outbreaks/table/save.png) 139 | 140 | ## 3. Create a Dashboard 141 | 142 | With the charts completed and saved in your [home folder](https://plot.ly/organize/home), we can now create a dashboard by simply adding these charts, adjusting the layout, and styling the dashboard before sharing and interacting. To get started with creating a dashboard, hover over the *+Create* button and select **Dashboard** from the menu. Alternatively, open this [link](https://plot.ly/dashboard/create). 143 | 144 | ### 3.1. Add Charts 145 | 146 | First, to add the Outbreak Locations Map, click *+Plot* in the bottom left corner of the screen. A new box ought to appear with the option to 'Add a Plot'. Click, the *'Your Files'* option and then in the pop-up select the **Outbreak Locations Map** we made earlier. 147 | 148 | ![Add Atlas Map](../screencasts/ebola-outbreaks/dashboard/add-plot.png) 149 | 150 | Next, add the **Deaths per Outbreak Scatter Plot** following the same process. This time drag and drop the plot on the right half of the Outbreak Locations Map. You ought to something like below. 151 | 152 | ![Add Scatter Plot](../screencasts/ebola-outbreaks/dashboard/add-plot2.png) 153 | 154 | Add the final plot (or table), **All Outbreak Data**, to the bottom of the dashboard and size accordingly. 155 | 156 | ![Add Table](../screencasts/ebola-outbreaks/dashboard/add-plot3.png) 157 | 158 | Now that we have added all the plots to the dashboard, for each plot where it says, "Enter a title..." insert plot titles: **Outbreak Locations**, **Death per Outbreak**, and **All Outbreak Data** in the same order as we added the plots. Your result ought to look like below. 159 | 160 | ![Add Plot Titles](../screencasts/ebola-outbreaks/dashboard/add-plot-titles.png) 161 | 162 | ### 3.2. Style It 163 | 164 | Now that we have the structure of our dashboard, we can style it. To do so, navigate to the *Settings Icon* directly opposite the dashboard title. When hovering you ought to see the option **Settings** from the menu. 165 | 166 | ![Settings](../screencasts/ebola-outbreaks/dashboard/settings.png) 167 | 168 | After clicking **Settings**, a panel ought to appear from the right-hand side of the screen. Here, we have the option of *Headers*, *Colors*, *Text*, *Layout*, and *Filter*. First, in *Headers*, we can set the title, add a logo, and multiple links. For this tutorial, add **Ebola Outbreaks 1976-2013** to the *Title* text box. Next, we can add a link to the original dataset by adding the text **Data Source: Nature** with the URL: **https://www.nature.com/articles/sdata201442#data-records**. 169 | 170 | ![Header](../screencasts/ebola-outbreaks/dashboard/header.png) 171 | 172 | In the next tab, *Colors*, we can manipulate the background, borders, and text colors. As you can see, the dashboard has already added these by default. Thus, for this tutorial, we'll leave them as is. 173 | 174 | ![Colors](../screencasts/ebola-outbreaks/dashboard/colors.png) 175 | 176 | *Text*, the third settings option, allows you to control all things text, including font color, family, and size, as well as header styles and text box styles. Again, like the Colors tab, some values are defined. However, here, we'll set the *Font Family* to **Raleway**. Make the header font larger by selecting **1.6em** in the *Header Font Size* and, additionally, change the *Header Font Weight* to **300**. Lastly, to separate the text box, set the *Text Box Background Color* to **#FFFFFF**. 177 | 178 | ![Text](../screencasts/ebola-outbreaks/dashboard/text.png) 179 | 180 | In *Layout*, you have the option of setting the page layout as either a dashboard or a report. Here, we'll leave it as the default dashboard setting. The last settings category, *Filter*, provides you with the option to enable or disable the Search Bar or the Crossfilter feature. For this tutorial, enable both the *Search Bar* and the **Crossfilter** feature by selecting **Enable** (for more information about this feature see the next section). 181 | 182 | ![Filter](../screencasts/ebola-outbreaks/dashboard/filter.png) 183 | 184 | Congrats, your dashboard is complete! Click **Save** on in the bottom right-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all), or **Private Link** (visible only to those who you share the link with), or **Private** (visible only to you) and hit **Save**. . 185 | 186 | ![Save](../screencasts/ebola-outbreaks/dashboard/save.png) 187 | 188 | ## 4. Crossfilter 189 | Finally, we'll briefly demonstrate crossfilter. 190 | 191 | Crossfilter is a visual analysis technique for multidimensional data. It is used to clarify relationships between dimensions. As discussed in the previous section, crossfilter functionality is invoked by setting **Enable** in Settings > Filter. 192 | 193 | To use crossfilter, simply click-and-drag on a chart. Selected data that shares common rows with other charts will highlight and all other data will fade out. To reset the dashboard, click anywhere on a graph that doesn't have data. 194 | 195 | ![Crossfilter](../screencasts/ebola_outbreaks.gif) 196 | -------------------------------------------------------------------------------- /tutorials/measles-dashboard.md: -------------------------------------------------------------------------------- 1 | # California Measles Dashboard 2 | 3 | In this tutorial, we'll create and style multiple individual plots in the Chart Studio, add them to a dashboard, and utilize the crossfilter feature to interact and explore these data further. 4 | 5 | ## Contents 6 | 7 | - [Data](#1-data) 8 | - [Create a Chart](#2-create-a-chart) 9 | - [Measles Cases Scatter Plot](#21-measles-cases-scatter-plot) 10 | - [Cases by Week of Year Box Plot](#22-cases-by-week-of-year-box-plot) 11 | - [3D Scatter Plot](#23-3d-scatter-plot) 12 | - [Create a Dashboard](#3-create-a-dashboard) 13 | - [Add Charts](#31-add-charts) 14 | - [Style It](#32-style-it) 15 | - [Crossfilter](#4-crossfilter) 16 | 17 | 18 | ## 1. Data 19 | 20 | To get started, head to Plotly’s [Chart Studio](https://plot.ly/create/) and add your data. You have the option of typing directly in the grid, uploading your file, or entering a URL of an online dataset. For this tutorial, we'll use the Measles Outbreak dataset from [Project Tycho at University of Pittsburgh](http://bit.ly/2zrVG6s). To begin, simply view the [dataset](https://plot.ly/~jackp/18114/) and click **'Fork & Edit'**. The Chart Studio ought to have opened and you're all set to go 21 | 22 | ![Fork and Edit](../screencasts/measles/scatter/fork-and-edit.png) 23 | 24 | Alternatively, navigate to the [Chart Studio](https://plot.ly/create/) and click **Import**, **By URL**, and then paste in the **URL** (https://plot.ly/~jackp/18114.csv). 25 | 26 | ![Add Data](../screencasts/measles/scatter/add-data.png) 27 | 28 | ## 2. Create a Chart 29 | 30 | To visualize measles cases in California between 1928 and 2004, we'll create three individual charts: (1) a scatter plot to illustrate cases per year, (2) a box plot looking at the cases by week of year, and (3) a 3D scatter plot to visualize the week of year versus year versus cases. In the section below, we'll look at how to make each of the charts. 31 | 32 | ### 2.1. Measles Cases Scatter Plot 33 | 34 | ##### 2.1.1. Create 35 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Scatter** from the *Business* column. 36 | 37 | ![Chart Type](../screencasts/measles/scatter/chart-type.png) 38 | 39 | Now to populate the graph with data, in the *x* and *y* dropdown select **YEAR** and **CALIFORNIA**, respectively. Additionally, we want to color these data by week, thus in the *Color* dropdown select **WEEK**. Repeat for *hover text*. 40 | 41 | ![Trace Values](../screencasts/measles/scatter/trace-values.png) 42 | 43 | ##### 2.1.2. Axes 44 | With the graph populated, we can now style it. First, to declutter the scatter points we'll make the y axis log scale instead of linear. To do this, navigate to the *Style* tab and select *Axes* then *Range* and *y*. Next to where it says *Axis Type* click **Log**. 45 | 46 | ![Log Scale](../screencasts/measles/scatter/log-scale.png) 47 | 48 | Staying in the Axes tab, we'll make a few minor adjustments to the lines and texts. Start by selecting *Title*. Remove the title under the x axis, then click *y* and in the text editor type **"Cases per year"**. Select *All* then change the *Typeface* to **Raleway**, size to **17** and the color to **#506784**. 49 | 50 | ![Axes Titles](../screencasts/measles/scatter/axes-titles.png) 51 | 52 | Next, click *Lines*, *All*, and set the color to **#E3E5E9**. 53 | 54 | ![Grid Lines](../screencasts/measles/scatter/grid-lines.png) 55 | 56 | Now navigate to *Tick Labels*. Here, set the *Typeface* to **Raleway**, the *Size* to **14**, and *Color* to **#506784**. 57 | 58 | ![Tick Labels](../screencasts/measles/scatter/tick-labels.png) 59 | 60 | Lastly for the axes, select *Zoom Interactivity* and click **Disable**. 61 | 62 | ![Zoom](../screencasts/measles/scatter/zoom.png) 63 | 64 | ##### 2.1.3. Traces 65 | Now that we have finished with styling the axes, click *Traces* to style the scatter points. We can redefine the *colorscale* by simply choosing from the preselected palettes. For this tutorial, select **Blue/Yellow**. Immediately below, click **Show Color Bar** to enable color bar visibility. Lastly, change the *Border-Width* to **0.5**, which will help define the scatter points. 66 | 67 | ![Trace Styles](../screencasts/measles/scatter/trace-styles.png) 68 | 69 | ##### 2.1.4. Layout 70 | Next, navigate to the *Layout* tab to set the background colors and margins. To complete the former, open the *Canvas* box and set both *Plot* and *Margin Color*, to **#F3F5F9**. 71 | 72 | ![Canvas](../screencasts/measles/scatter/canvas.png) 73 | 74 | To set the margins, select the *Margins and Padding* box 75 | and enter the values **0, 40, 60, 0, 0**, respectively. 76 | 77 | ![Margins](../screencasts/measles/scatter/margins.png) 78 | 79 | ##### 2.1.5. Color Bars 80 | Finally, you can style the color bar by navigating to *Color Bars*. For this tutorial, in the *Title* box we enter the title **Week of year**, set the *Typeface* to **Raleway**, adjust the *Size* to **14**, and set the *Color* to **#506784**. 81 | 82 | ![Color Bar Title](../screencasts/measles/scatter/color-bar-title.png) 83 | 84 | Now to minimize the size of the color bar, select the *Size and Positioning* box and set the *Height* to **0.9**. 85 | 86 | ![Color Bar Size](../screencasts/measles/scatter/color-bar-size.png) 87 | 88 | In the next box, *Labels*, set the *Typeface* to **Raleway** and the font size to **14**. 89 | 90 | ![Color Bar Labels](../screencasts/measles/scatter/color-bar-labels.png) 91 | 92 | ##### 2.1.6. Save 93 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 94 | 95 | ![Save](../screencasts/measles/scatter/save.png) 96 | 97 | ### 2.2. Cases by Week of Year Box Plot 98 | 99 | Using the same grid as the previous plot, open the data in the Chart Studio. 100 | 101 | ##### 2.2.1. Create 102 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Box Plot** from the *Statistics* column. 103 | 104 | ![Chart Type](../screencasts/measles/box/chart-type.png) 105 | 106 | Like the previous plot we want to populate the graph with data, thus in the *Values* and *X Data* dropdown select **CALIFORNIA** and **WEEK**, respectively. 107 | 108 | ![Trace Values](../screencasts/measles/box/trace-values.png) 109 | 110 | ##### 2.2.2. Traces 111 | With the graph populated, we can turn to styling the plot. First, navigate to the *Traces* tab under *Style*. Here, change the *Fill* and *Line Color* to **#222222**, but set the alpha to **50** for the fill and **100** for the line. Immediately below, set the *Display Points* dropdown to **All** and then style the points. To do so, set the *Fill* and *Line Color* to **#222222**, but set the alpha to **50** for the fill and **100** for the line. Next, in *Size and Spacing*, set the *Box Width* to **60** and the *Padding* to **30**. Lastly, with regards to trace styling, in *Show Statistics* select **Mean** from the dropdown. You ought to see the mean line appear on each boxplot. 112 | 113 | ![Trace Styles](../screencasts/measles/box/trace-styles.png) 114 | 115 | ##### 2.2.3. Layout 116 | Now that we've finished styling the trace, click *Layout* to style the background, fonts, and margins. To complete the former, select *Canvas* and set **#F3F5F9** as both plot and margin color. Below that, open the *Title and Fonts* box and under *Global Font*, set *Typeface* to **Raleway** and *Font Size* to **14**. 117 | 118 | ![Global Font](../screencasts/measles/box/global-font.png) 119 | 120 | To set the margins, open *Margins and Padding* and set the values to **0, 80, 60, 0, 0**, respectively. 121 | 122 | ![Margins](../screencasts/measles/box/margins.png) 123 | 124 | ##### 2.2.4. Axes 125 | To edit the axis titles, grid lines, and tick labels, navigate to the *Axes* tab. First, in the *Titles* set the *x* axis title to **Week of year** and then the *y* axis to **Cases**. 126 | 127 | ![Axes Titles](../screencasts/measles/box/axes-titles.png) 128 | 129 | For this plot, we want to remove all grid lines. Thus, open *Lines* box, click *All*, and then select **Hide** for all three options. 130 | 131 | ![Grid Lines](../screencasts/measles/box/grid-lines.png) 132 | 133 | Next, open *Tick Labels* and check that the x axis is selected and scroll to the bottom of the box and, under *Number of Labels*, select **Custom** then enter **30** as the *Max Number of Labels*. 134 | 135 | ![Tick Labels](../screencasts/measles/box/tick-labels.png) 136 | 137 | Now, you ought to see every second week tick label on the x axis. Lastly, open the *Zoom Interactivity* box and select **Disable**. 138 | 139 | ![Zoom](../screencasts/measles/box/zoom.png) 140 | 141 | ##### 2.2.5. Save 142 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 143 | 144 | 145 | ![Save](../screencasts/measles/box/save.png) 146 | 147 | ### 2.3. 3D Scatter Plot 148 | 149 | Using the same grid as the previous plot, open the data in the Chart Studio. 150 | 151 | ##### 2.3.1. Create 152 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **3D Scatter** from the *3D Charts* column. 153 | 154 | ![Chart Type](../screencasts/measles/3d-scatter/chart-type.png) 155 | 156 | Like before, to populate the graph with data, select **YEAR**, **WEEK**, and **CALIFORNIA** in the *x*, *y*, and *z* dropdowns. Additionally, like in the scatter plot we made earlier, we want to color this by week. Thus, in the color dropdown select **WEEK**. 157 | 158 | ![Trace Values](../screencasts/measles/3d-scatter/trace-values.png) 159 | 160 | ##### 2.3.2. Layout 161 | Before styling the traces we'll first adjust the layout of the scene. Hence, navigate to *Layout* under *Style*. Here, open the *Scene* box and select **Manual** in the *Aspect Ratio* dropdown. Furthermore, set *x* to **2**. 162 | 163 | ![Scene](../screencasts/measles/3d-scatter/scene.png) 164 | 165 | Since we have the layout open, select *Canvas* and set the *Margin Color* to **#F3F5F9**. For this plot, we'll leave the rest of the layout as-is. 166 | 167 | ![Canvas](../screencasts/measles/3d-scatter/canvas.png) 168 | 169 | ##### 2.3.3. Traces 170 | Now that we have finished with styling the layout, click *Traces* to style the scatter points. We can redefine the colorscale by simply choosing from the preselected scales. To remain consistent with our scatter plot, select the **Blue/Yellow** palette. Immediately below, click **Show Color Bar** to enable color bar visibility. Lastly, change the *Border-Width* to **0.5** and *Border-Color* to **#506784**, which will help define the scatter points. 171 | 172 | ![Trace Styles](../screencasts/measles/3d-scatter/trace-styles.png) 173 | 174 | ##### 2.3.4. Axes 175 | Navigate to the *Axes* tab to style the axis' title, grid lines, and tick labels. Add **"Year"**, **"Week"**, **"Cases"** as the *x*, *y*, *z* titles, respectively. Additionally, set the *Font Size* to **16** and *Font Color* to **#506784**. 176 | 177 | ![Axes Titles](../screencasts/measles/3d-scatter/axes-titles.png) 178 | 179 | To style the grid lines, open the *Lines* box and select *All*. Here, under *All Axes Grid Lines* set *Thickness* to **3** and *Color* to **#FFFFFF**. Under *Zero Line*, set *Thickness* to **2** and *Color* to **#FFFFFF**. 180 | 181 | ![Grid Lines](../screencasts/measles/3d-scatter/grid-lines.png) 182 | 183 | Next, alter the color of tick labels by opening the *Tick Labels* box, select *All*, and set *Color* to **#506784**. Lastly, for axes styling, open *Hover Projections*, select *All*, set *Color* to **#D62728** and *Width* to **4**. Now, when hovering you ought to see **#D62728** colored axis lines. 184 | 185 | ![Hover Projections](../screencasts/measles/3d-scatter/hover-projections.png) 186 | 187 | ##### 2.3.5. Color Bars 188 | Finally, you can style the color bar by navigating to *Color Bars*. For this tutorial, in the *Title* box we enter the title **Week of year**, set the *Typeface* to **Raleway**, adjust the *Size* to **14**, and set the *Color* to **#506784**. 189 | 190 | ![Color Bar Title](../screencasts/measles/3d-scatter/color-bar-title.png) 191 | 192 | Now to minimize the size of the color bar, select the *Size and Positioning* box and set the *Height* to **0.9**. 193 | 194 | ![Color Bar Size](../screencasts/measles/3d-scatter/color-bar-size.png) 195 | 196 | In the next box, *Labels*, set the *Typeface* to **Raleway** and the *Font Size* to **14**. 197 | 198 | ![Color Bar Labels](../screencasts/measles/3d-scatter/color-bar-labels.png) 199 | 200 | ##### 2.3.6. Save 201 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 202 | 203 | ![Save](../screencasts/measles/3d-scatter/save.png) 204 | 205 | ## 3. Create a Dashboard 206 | 207 | With the charts completed and saved in your [home folder](https://plot.ly/organize/home), we can now create a dashboard by simply adding these charts, adjusting the layout, and styling the dashboard before sharing and interacting. To get started with creating a dashboard, hover over the *+Create* button and select **Dashboard** from the menu. Alternatively, open this [link](https://plot.ly/dashboard/create). 208 | 209 | ### 3.1. Add Charts 210 | 211 | Before adding a chart, we'll add a text box to describe the dashboard and its uses. Simply, click the *Text* button, where a text editor ought to appear. In the text editor, add the text you wish to display in the dashboard. 212 | 213 | ![Add Text](../screencasts/measles/dashboard/text-editor.png) 214 | 215 | Now to add the scatter plot, click *+Plot* in the bottom left corner of the screen. A new box ought to appear with the option to 'Add a Plot'. Click, the *'Your Files'* option and then in the pop-up select the **California Measles Cases Scatter Plot** we made earlier. 216 | 217 | ![Add Plot](../screencasts/measles/dashboard/add-plot.png) 218 | 219 | Now, you ought to see the plot added to your dashboard. Next, in the top left corner of the box where it says, "Enter a title..." insert **California measles cases, colored by week of year**. 220 | 221 | ![Add Plot Title](../screencasts/measles/dashboard/add-plot-title.png) 222 | 223 | Repeat the process for the boxplot and 3D scatter plot we made earlier, but title them **California measles cases by week of year** and **California measles cases: Week of year versus Year versus Cases**, respectively. 224 | 225 | ![Repeat Process](../screencasts/measles/dashboard/repeat-process.png) 226 | 227 | ### 3.2. Style It 228 | 229 | Now that we have the structure of our dashboard, we can style it. To do so, navigate to the *Settings Icon* directly opposite the dashboard title. When hovering you ought to see the option **Settings** from the menu. 230 | 231 | ![Settings](../screencasts/measles/dashboard/settings.png) 232 | 233 | After clicking **Settings**, a panel ought to appear from the right-hand side of the screen. Here, we have the option of *Headers*, *Colors*, *Text*, *Layout*, and *Filter*. First, in *Headers*, we can set the title, add a logo, and multiple links. For this tutorial, add **Measles Cases in California 1928-2004** to the *Title* text box. Next, let's add the Project Tycho logo. We can do this by simply adding the URL for the logo PNG: **https://www.tycho.pitt.edu/images/web3.png**. As previously mentioned you can add links, in this tutorial we'll use this feature to link the original dataset. Thus, add the text **"Data Source: Project Tycho Level 1 data"** with the URL: **https://www.tycho.pitt.edu/data/level1.php**. 234 | 235 | ![Header](../screencasts/measles/dashboard/header.png) 236 | 237 | In the next tab, *Colors*, we can manipulate the background, borders, and text colors. As you can see, the dashboard has already added these by default. Thus, for this tutorial, we'll leave them as-is. 238 | 239 | ![Colors](../screencasts/measles/dashboard/colors.png) 240 | 241 | *Text*, the third option, allows you to control all things text, including font color, family, and size, as well as header styles and text box styles. Again, like the Colors tab, some values are defined. However, here, we'll set the *Font Family* to **Raleway**. Also, we’ll make the header font larger by selecting **2.2em** in the *Header Font Size* and, additionally, change the *Header Font Weight* to **300**. Lastly, to separate the text box, set the *Text Box Background Color* to **#FFFFFF**. 242 | 243 | ![Text](../screencasts/measles/dashboard/text.png) 244 | 245 | In *Layout*, you have the option of setting the page layout as either a dashboard or a report. Here, we'll leave it as the default dashboard setting. The last settings category, *Filter*, provides you with the option to enable or disable the Search Bar or the Crossfilter feature. For this tutorial, leave the *Search Bar* as-is but let’s enable the *Crossfilter* feature by selecting **Enable** (for more information about this feature see the next section). 246 | 247 | ![Filter](../screencasts/measles/dashboard/filter.png) 248 | 249 | Congrats, your dashboard is complete! Click **Save** on in the bottom right-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all), or **Private Link** (visible only to those who you share the link with), or **Private** (visible only to you) and hit **Save**. 250 | 251 | ![Save](../screencasts/measles/dashboard/save.png) 252 | 253 | ## 4. Crossfilter 254 | Finally, we'll briefly demonstrate crossfilter. 255 | 256 | **Crossfilter** is a visual analysis technique for multidimensional data. It is used to clarify relationships between dimensions. As discussed in the previous section, crossfilter functionality is invoked by setting **Enable** in *Settings* > *Filter*. 257 | 258 | To use crossfilter, simply click-and-drag on a chart. Selected data that shares common rows with other charts will highlight and all other data will fade out. To reset the dashboard, click anywhere on a graph that doesn't have data. 259 | 260 | ![Crossfilter](../screencasts/california_measles_outbreaks.gif) 261 | 262 | -------------------------------------------------------------------------------- /tutorials/police-report-deaths.md: -------------------------------------------------------------------------------- 1 | # U.S. Police officer deaths by cause 2 | 3 | In this tutorial, we'll create and style multiple individual plots in the Chart Studio, add them to a dashboard, and utilize the crossfilter feature to interact and explore these data further. 4 | 5 | ## Contents 6 | 7 | - [Data](#1-data) 8 | - [Create a Chart](#2-create-a-chart) 9 | - [Death by Cause Pie Chart](#21-death-by-cause-pie-chart) 10 | - [Death by Cause and Date Scatter Plot](#22-death-by-cause-and-date-scatter-plot) 11 | - [Deaths per State Choropleth Map](#23-deaths-per-state-choropleth-map) 12 | - [Create a Dashboard](#3-create-a-dashboard) 13 | - [Add Charts](#31-add-charts) 14 | - [Style It](#32-style-it) 15 | - [Crossfilter](#4-crossfilter) 16 | 17 | 18 | ## 1. Data 19 | 20 | To get started, head to Plotly’s [Chart Studio](https://plot.ly/create/) and add your data. You have the option of typing directly in the grid, uploading your file, or entering a URL of an online dataset. For this tutorial, we'll use the Police Killings dataset from the [FiveThirtyEight](http://bit.ly/237YWtv). To begin, simply view the [dataset](https://plot.ly/~public.health/17/) and click **'Fork & Edit'**. The Chart Studio ought to have opened and you're all set to go. 21 | 22 | ![Fork and Edit](../screencasts/police-report/pie-chart/fork-and-edit.png) 23 | 24 | Alternatively, navigate to the [Chart Studio](https://plot.ly/create/) and click **'Import'**, **'By URL'**, and then paste in the **URL** (https://plot.ly/~public.health/17.csv). 25 | 26 | ![Add Data](../screencasts/police-report/pie-chart/add-data.png) 27 | 28 | ## 2. Create a Chart 29 | To visualize U.S. police officer deaths between 1985 and 2006, we'll create three individual charts: (1) a pie chart to illustrate deaths by cause , (2) a scatter plot looking at cause and date, and (3) a choropleth map to visualize deaths per state. In the section below, we'll look at how to make each of the charts. 30 | 31 | ### 2.1. Death by Cause Pie Chart 32 | 33 | ##### 2.1.1. Create 34 | Now that we have the data in the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Pie Chart** from the *Business* column. 35 | 36 | ![Chart Type](../screencasts/police-report/pie-chart/chart-type.png) 37 | 38 | Next, we can populate the graph by selecting **cause** in the *Labels* dropdown. You ought to see a pie chart with a legend like below. 39 | 40 | ![Trace Values](../screencasts/police-report/pie-chart/trace-values.png) 41 | 42 | ##### 2.1.2. Traces 43 | To style the pie chart, we can make changes to the text, colors, borders, and order. To do so, navigate to the *Traces* tab under *Style*. Here, select ** Label** and unselect ** %**, change the *Font Size* to **11**, set the *Rotation* to **130 degrees**, and *Hole* to **30%**. 44 | 45 | ![Trace Styles](../screencasts/police-report/pie-chart/trace-styles.png) 46 | 47 | ##### 2.1.4. Layout 48 | To change the background color, click *Layout* under *Style* and set the *Color* to **F0F0F0**. 49 | 50 | ![Canvas](../screencasts/police-report/pie-chart/canvas.png) 51 | 52 | To set the margins, select the *Margins and Padding* box 53 | and enter the values **20, 20, 0, 0, 0**, respectively. 54 | 55 | ![Margins](../screencasts/police-report/pie-chart/margins.png) 56 | 57 | ##### 2.1.4. Legend 58 | With the styling done and the option to use labels directly on the slices, the legend on the right-hand side is redundant. Thus, click *Legend* under *Style* and select **Hide**. 59 | 60 | ![Legend](../screencasts/police-report/pie-chart/legend.png) 61 | 62 | ##### 2.1.5. Save 63 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 64 | 65 | ![Save](../screencasts/police-report/pie-chart/save.png) 66 | 67 | ### 2.2. Death by Cause and Date Scatter Plot 68 | Using the same grid as the previous plot, open the data in the Chart Studio. 69 | 70 | ##### 2.2.1. Create 71 | Now that we have the data added to the grid, we can select our chart type. To do so, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Scatter** from the *Business* column. 72 | 73 | ![Chart Type](../screencasts/police-report/scatter/chart-type.png) 74 | 75 | Now to populate the graph with data, in the *x* and *y* dropdown select **date** and **cause_short**, respectively. 76 | 77 | ![Trace Values](../screencasts/police-report/scatter/trace-values.png) 78 | 79 | ##### 2.2.2. Traces 80 | With the data plotted, let's style the plot by first changing the scatter points color and symbol. Click *Traces*, set the points *Color* to **#222222** and change the *Symbol* to **|** (situated at the bottom of the symbol box). 81 | 82 | ![Trace Styles](../screencasts/police-report/scatter/trace-styles.png) 83 | 84 | ##### 2.2.3. Layout 85 | Next, navigate to the *Layout* tab to set the background colors, and margins. To complete the former, open the *Canvas* box and set the color, for both plot and margin, to **#F0F0F0**. 86 | 87 | ![Canvas](../screencasts/police-report/scatter/canvas.png) 88 | 89 | To set the margins, select the *Margins and Padding* box 90 | and enter the values **0, 40, 150, 0, 0**, respectively. 91 | 92 | ![Margins](../screencasts/police-report/scatter/margins.png) 93 | 94 | ##### 2.2.4. Axes 95 | Moving on to the *Axes* tab, select *Title*. Remove the title under the *x* axis, then click *y* and in the text editor type **Causes of Death**. Leave the *Typeface* as **Open Sans** and *Font Size* as **14**. 96 | 97 | ![Axes Titles](../screencasts/police-report/scatter/axes-titles.png) 98 | 99 | Next, navigate to *Tick Labels*. In the *x* axis, set the *Angle* to **45 degrees** and the *Number of Labels* to **Custom** and **20**. 100 | 101 | ![Tick Labels](../screencasts/police-report/scatter/tick-labels.png) 102 | 103 | Finally, select *Zoom Interactivity* and click **Disable**. 104 | 105 | ![Zoom](../screencasts/police-report/scatter/zoom.png) 106 | 107 | ##### 2.2.5. Save 108 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 109 | 110 | 111 | ![Save](../screencasts/police-report/scatter/save.png) 112 | 113 | ### 2.3. Deaths per State Choropleth Map 114 | Using the same grid as the previous plot, open the data in the Chart Studio. 115 | 116 | 117 | ##### 2.3.1. Create 118 | Like the previous charts, once you've added the data, select *Graph* on the left-hand side, then *Create*. Click *Chart Type*, and **Choropleth** from the *Maps* column. 119 | 120 | ![Chart Type](../screencasts/police-report/choropleth/chart-type.png) 121 | 122 | Now to populate the graph with data, in the *Locations* and *Values* dropdown select **state** and **cause**, respectively. Additionally, set **USA State Abbreviations** in the *Locations Format* dropdown, **USA** in the *Map Regions*, and set the *Projections* to **Albers USA**. Note that states aren't defined yet as we need to aggregate the data. 123 | 124 | ![Trace Values](../screencasts/police-report/choropleth/trace-values.png) 125 | 126 | ##### 2.3.2. Aggregate 127 | Thus, under *Graph* click *Aggregate*. Next, click the blue *+ Aggregate* button. In the box that appears, select **state** as the *Group By Column*. Set *Trace* to **cause**, *z* to **count**, and leave *Locations* as **first**. You ought to not see something like below. 128 | 129 | ![Aggregate](../screencasts/police-report/choropleth/aggregate.png) 130 | 131 | ##### 2.3.3. Traces 132 | The blue is hard to decipher, so navigate to the *Traces* tab and set the *Colorscale* to **Yellow/Purple** (roughly the 8th from the left). 133 | 134 | ![Trace Styles](../screencasts/police-report/choropleth/trace-styles.png) 135 | 136 | ##### 2.3.4. Layout 137 | Now that the choropleth is populated and colored, navigate to the *Layout* tab to style the background, margins, and the geo style and layout. First, open the *Canvas* box and set the *Color* to **#F0F0F0**. 138 | 139 | ![Canvas](../screencasts/police-report/choropleth/canvas.png) 140 | 141 | To make the map the full width and height, open *Margins and Paddings* and set all the values to **0**. 142 | 143 | ![Margins](../screencasts/police-report/choropleth/margins.png) 144 | 145 | Unique to choropleth maps, we have *Geo Layout*. Here, you define attributes such as *Map Scope*, *Projection*, *Rotation*, *Scale*, and *Map Resolution*. Set the latter to **1:50,000,000**. 146 | 147 | ![Geo Layout](../screencasts/police-report/choropleth/geo-layout.png) 148 | 149 | ##### 2.3.5. Color Bars 150 | Finally, you can style the color bar by navigating to *Color Bars*. To minimize the size of the color bar, select the *Size and Positioning* box and set the *Width* to **20**. 151 | 152 | ![Color Bars Size](../screencasts/police-report/choropleth/color-bar-size.png) 153 | 154 | ##### 2.3.6. Save 155 | Congrats, your chart is complete! Click **Save** on the left-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all) or **Private Link** (visible only to those who you share the link with) and hit **Save**. Since these plots are destined for a dashboard, they can't be set to private. 156 | 157 | ![Save](../screencasts/police-report/choropleth/save.png) 158 | 159 | ## 3. Create a Dashboard 160 | 161 | With the charts completed and saved in your [home folder](https://plot.ly/organize/home), we can now create a dashboard by simply adding these charts, adjusting the layout, and styling the dashboard before sharing and interacting. To get started with creating a dashboard, hover over the *+Create* button and select **Dashboard** from the menu. Alternatively, open this [link](https://plot.ly/dashboard/create). 162 | 163 | ### 3.1. Add Charts 164 | First, to add the Death by Cause Pie Chart, click *+Plot* in the bottom left corner of the screen. A new box ought to appear with the option to 'Add a Plot'. Click, the *'Your Files'* option and then in the pop-up select the ** Death by Cause Pie Chart ** we made earlier. 165 | 166 | ![Add Pie Chart](../screencasts/police-report/dashboard/add-pie-chart.png) 167 | 168 | Next, add the Death by Cause and Date Scatter Plot immediately below following the same process. 169 | 170 | ![Add Scatter Plot](../screencasts/police-report/dashboard/add-scatter-plot.png) 171 | 172 | Like previously, add the Deaths per State Choropleth Map following the same process. This time drag and drop the plot on the right half of the Death by Cause and Date Scatter Plot. 173 | 174 | ![Add Choropleth](../screencasts/police-report/dashboard/add-choropleth.png) 175 | 176 | Now that we have added all the plots to the dashboard, for each plot where it says, "Enter a title..." insert plot titles: **Death by Cause 1985-2006 (Click on a pie slice to crossfilter)**, **Death by Cause and Date 1985-2006 (Click drag on the scatter points to crossfilter)**, and **Total Deaths per State 1895-2006 (Click-drag on the map to crossfilter)** in the same order as we added the plots. Your result ought to look like below. 177 | 178 | ![Add Plot Titles](../screencasts/police-report/dashboard/add-plot-title.png) 179 | 180 | ### 3.2. Style It 181 | 182 | Now that we have the structure of our dashboard, we can style it. To do so, navigate to the *settings icon* directly opposite the dashboard title. When hovering you ought to see the option settings from the menu. 183 | 184 | ![Settings](../screencasts/police-report/dashboard/settings.png) 185 | 186 | After clicking *settings*, a panel ought to appear from the right-hand side of the screen. Here, we have the option of *Headers*, *Colors*, *Text*, *Layout*, and *Filter*. First, in *Headers*, we can set the title, add a logo, and multiple links. For this tutorial, add **On-duty U.S. police officer deaths by cause 1985-2006** to the *Title* text box. Next, let's add the FiveThirtyEight logo. We can do this by simply adding the URL for the logo PNG: **https://cdn0.vox-cdn.com/uploads/chorus_asset/file/6954369/538-logo.0.png**. As previously mentioned you can add links, in this tutorial we'll use this feature to link the original dataset. Thus, add the text **"Original Dataset: FiveThirtyEight"** with the URL: **https://github.com/fivethirtyeight/data/tree/master/police-deaths**. 187 | 188 | ![Header](../screencasts/police-report/dashboard/header.png) 189 | 190 | In the next tab, *Colors*, we can manipulate the background, borders, and text colors. As you can see, the dashboard has already added these by default. That said, for this dashboard we will set *Header Background* to **#222222**, *Header Font Color* to **#FFFFFF**, *Page Background*, *Box Background*, *Box Border*, and *Box Header Background* to **#F0F0F0**. Lastly, enter **#222222** as the *Box Header Font Color*. 191 | 192 | ![Colors](../screencasts/police-report/dashboard/colors.png) 193 | 194 | *Text*, allows you to control all things text, including font color, family, and size, as well as header styles and text box styles. Again, like the *Colors* tab, some values are defined. However, here, we'll set the *Font Family* to **Open Sans**. Set the header font to **1.6em** in the *Header Font Size* and, additionally, change the *Header Font Weight* to **300**. We can leave the remainder as-is. 195 | 196 | ![Text](../screencasts/police-report/dashboard/text.png) 197 | 198 | In *Layout*, you have the option of setting the page layout as either a dashboard or a report. Here, we'll leave it as the default dashboard setting. The last settings category, *Filter*, provides you with the option to enable or disable the Search Bar or the Crossfilter feature. For this tutorial, **Enable** both *Search Bar* and the *Crossfilter* feature (for more information about this feature see the next section). Now, like below, you ought to see a search bar and filter dropdown appear under the dashboard header. 199 | 200 | ![Filter](../screencasts/police-report/dashboard/filter.png) 201 | 202 | Congrats, your dashboard is complete! Click **Save** on in the bottom right-hand side of the screen. In the pop-up, enter your filename and select either **Public** (visible to all), or **Private Link** (visible only to those who you share the link with), or **Private** (visible only to you) and hit **Save**. . 203 | 204 | ![Save](../screencasts/police-report/dashboard/save.png) 205 | 206 | ## 4. Crossfilter 207 | Finally, we'll briefly demonstrate crossfilter. 208 | 209 | **Crossfilter** is a visual analysis technique for multidimensional data. It is used to clarify relationships between dimensions. As discussed in the previous section, crossfilter functionality is invoked by setting **enable** in Settings > Filter. 210 | 211 | To use crossfilter, simply click-and-drag on a chart. Selected data that shares common rows with other charts will highlight and all other data will fade out. To reset the dashboard, click anywhere on a graph that doesn't have data. 212 | 213 | ![Crossfilter](../screencasts/police-report-deaths.gif) 214 | --------------------------------------------------------------------------------