├── .Rhistory ├── README.md ├── img ├── banner.png └── prompts.png └── list_prompts.md /.Rhistory: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/30DayChartChallenge/Edition2023/78e04c9091099fb6b322f6fdefa6a60692fbd08f/.Rhistory -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ![](img/banner.png) 2 | 3 |

4 | 5 | Collection of contributions to and resources for the second 6 | #30DayChartChallenge 7 | in April 2022. 8 | 9 |

10 | 11 | ## How to contribute? 12 | 13 | Anyone is welcome to contribute, no matter which data source or tool you 14 | use.\ 15 | If you share your contributions on Twitter, please use the hashtag 16 | [#30DayChartChallenge](https://twitter.com/search?q=%2330DayChartChallenge) 17 | and/or tag the [\@30DayChartCall](https://twitter.com/30DayChartChall) 18 | account. 19 | 20 | ## Topics 21 | 22 | ![](img/prompts.png) 23 | 24 | → [List of 25 | Topics](list_prompts.md) 26 | 27 | *Data days:* 28 | 29 | * Day 6. [OWID](https://ourworldindata.org/) 30 | * Day 18. [EuroStat](https://t.co/Ql8DIMRnAH) 31 | * Day 30. [Worldbank](https://t.co/ml9rIhQk3I) 32 | 33 | ## Contributions 34 | 35 | Collection of all contributions per day (shared on Twitter with the 36 | hashtag and/or mentioning @30DayChartChall account). For now just named 37 | images in a folder---hopefully going to clean it up once the challenge 38 | is over. 39 | 40 | 41 | *Further links:* 42 | 43 | - [Dedicated list of #Rstats 44 | contributions to the 2021 edition](https://github.com/dominicroye/rstats-chart-challenge-2021) 45 | - [#30DayChartChallenge](https://twitter.com/search?q=%2330DayChartChallenge) 46 | on Twitter 47 | 48 | ## Resources 49 | 50 | ### Tools 51 | 52 | We do not care what tool you use. Whatever works for you is fine! 53 | Programing, designing, crafting --- pick what you prefer or try 54 | different things. An extensive list of tools can be found at 55 | [Visualising Data](https://www.visualisingdata.com/resources/). 56 | 57 | ### Data 58 | 59 | You are free to pick whatever data you want---we do not provide any 60 | particular dataset for each challenge. Either use the same dataset for 61 | all or different datasets each day, as you like! Search the internet, 62 | collect your own, visualize daily experiences or funny stats. 63 | Nevertheless, we would like to provide a starter kit of possible data 64 | sources: 65 | 66 | - [Google dataset search](https://datasetsearch.research.google.com/) 67 | - [data.world](https://data.world/) 68 | - [kaggle](https://www.kaggle.com/datasets) 69 | - [Data Is 70 | Plural](https://docs.google.com/spreadsheets/d/1wZhPLMCHKJvwOkP4juclhjFgqIY8fQFMemwKL2c64vk/edit#gid=0) 71 | - [OurWorldInData](https://ourworldindata.org/) 72 | - [Eurostats](https://ec.europa.eu/eurostat) 73 | - [UN Stats](https://unstats.un.org/home/) 74 | - [WHO](https://www.who.int/data/collections) 75 | - [OECD Stats](https://stats.oecd.org/) 76 | - [Socioeconomic Data and Applications Center 77 | (NASA)](https://sedac.ciesin.columbia.edu/) 78 | - [MakeoverMonday](https://www.makeovermonday.co.uk/data/) 79 | - [TidyTuesday](https://github.com/rfordatascience/tidytuesday/tree/master/data/2021) 80 | (search through old datasets 81 | [here](https://github.com/rfordatascience/tidytuesday/tree/master/data/2018), 82 | [here](https://github.com/rfordatascience/tidytuesday/tree/master/data/2019) 83 | and 84 | [here](https://github.com/rfordatascience/tidytuesday/tree/master/data/2020)) 85 | - [IMDB datasets](https://www.imdb.com/interfaces/) 86 | - [Free GIS data](http://freegisdata.rtwilson.com/) 87 | - [WorldClim](https://worldclim.org/) --- maps, graphs, tables, and 88 | data of the global climate 89 | - [Rdatasets](https://vincentarelbundock.github.io/Rdatasets/datasets.html) 90 | --- over 1300 datasets originally distributed in R packages 91 | - [List of R packages to import 92 | data](https://www.computerworld.com/article/3109890/these-r-packages-import-sports-weather-stock-data-and-more.html) 93 | 94 | ### Chart Type Selection 95 | 96 | There are many great selection helpers out there, guiding you through 97 | the many different boxes you can fit the endless number of (sub)chart 98 | types in. Here is a non-exhaustive list: 99 | 100 | - [Chart Suggestions---A 101 | Thought-Starter](http://extremepresentation.com/wp-content/uploads/choosing-a-good-chart-09-1.pdf) 102 | by Andrew Abela --- an all-time classic ([latest 103 | version](https://extremepresentation.typepad.com/files/chart-chooser-2020.pdf)) 104 | - [Graphic 105 | Continuum](https://policyviz.com/2014/09/09/graphic-continuum/) by 106 | Jon Schwabish and Severino Ribecca --- the main source for the five 107 | categories 108 | - [Visual 109 | Vocabulary](https://github.com/ft-interactive/chart-doctor/tree/master/visual-vocabulary) 110 | by the Financial Times Visual Journalism --- chart choice helpers 111 | with lots of further links 112 | - [interactive version](https://www.ft.com/chart-doctor) 113 | - [static 114 | version](https://raw.githubusercontent.com/ft-interactive/chart-doctor/master/visual-vocabulary/poster.png) 115 | - [From Data to Viz](https://www.data-to-viz.com/) by Yan Holtz --- 116 | interactive, with information and codes for each chart type 117 | - [R code collection](https://www.r-graph-gallery.com/) 118 | - [Python code collection](https://www.python-graph-gallery.com/) 119 | - [D3js code collection](https://www.d3-graph-gallery.com/) 120 | - [DataVizProject](https://datavizproject.com/) by ferdio --- 121 | interactive with lots of examples 122 | - [Visualization Universe](http://visualizationuniverse.com/) by 123 | Adioma and Google News Lab 124 | - [How to Choose the Right Chart 125 | Type](https://activewizards.com/blog/how-to-choose-the-right-chart-type-infographic/) 126 | --- another, very compact, decision tree to help you 127 | -------------------------------------------------------------------------------- /img/banner.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/30DayChartChallenge/Edition2023/78e04c9091099fb6b322f6fdefa6a60692fbd08f/img/banner.png -------------------------------------------------------------------------------- /img/prompts.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/30DayChartChallenge/Edition2023/78e04c9091099fb6b322f6fdefa6a60692fbd08f/img/prompts.png -------------------------------------------------------------------------------- /list_prompts.md: -------------------------------------------------------------------------------- 1 | # #30DayChartChallenge Topics by Day 2 | 3 | * **Comparisons**\ 4 | 1\. part-to-whole\ 5 | 2. waffle\ 6 | 3. fauna/flora\ 7 | 4. historical\ 8 | 5. slope\ 9 | 6. data day: [OWID](https://ourworldindata.org/) 10 | * **Distributions**\ 11 | 7. hazards\ 12 | 8. humans\ 13 | 9. high/low\ 14 | 10. hybrid\ 15 | 11. circular\ 16 | 12. theme day: BBC News 17 | * **Relationships**\ 18 | 13. pop culture\ 19 | 14. new tool\ 20 | 15. positive/negative\ 21 | 16. family\ 22 | 17. networks\ 23 | 18. data day: [EuroStat](https://t.co/Ql8DIMRnAH) 24 | * **Timeseries**\ 25 | 19. anthropocene\ 26 | 20. correlation\ 27 | 21. down/upwards\ 28 | 22. green energy\ 29 | 23. tiles\ 30 | 24. theme day: UN Woman 31 | * **Uncertainties**\ 32 | 25. global change\ 33 | 26. local change\ 34 | 27. good/bad\ 35 | 28. trend\ 36 | 29. monochrome\ 37 | 30. data day: [Worldbank](https://t.co/ml9rIhQk3I) 38 | --------------------------------------------------------------------------------