From a2d735ac0fa64bf2d40cc3a5cfde786f574ae96c Mon Sep 17 00:00:00 2001 From: Jon Harmon Date: Sun, 20 Oct 2024 10:46:23 -0500 Subject: [PATCH 1/5] CIA World Factbook from {usadatasets}. --- data/curated/usdata/cia_factbook.csv | 260 +++++++++++++++++++++++++ data/curated/usdata/cia_factbook.md | 13 ++ data/curated/usdata/cleaning.R | 12 ++ data/curated/usdata/instructions.md | 24 +++ data/curated/usdata/intro.md | 29 +++ data/curated/usdata/meta.yaml | 20 ++ data/curated/usdata/saving.R | 9 + data/curated/usdata/world_factbook.png | Bin 0 -> 207343 bytes 8 files changed, 367 insertions(+) create mode 100644 data/curated/usdata/cia_factbook.csv create mode 100644 data/curated/usdata/cia_factbook.md create mode 100644 data/curated/usdata/cleaning.R create mode 100644 data/curated/usdata/instructions.md create mode 100644 data/curated/usdata/intro.md create mode 100644 data/curated/usdata/meta.yaml create mode 100644 data/curated/usdata/saving.R create mode 100644 data/curated/usdata/world_factbook.png diff --git a/data/curated/usdata/cia_factbook.csv b/data/curated/usdata/cia_factbook.csv new file mode 100644 index 000000000..07268130e --- /dev/null +++ b/data/curated/usdata/cia_factbook.csv @@ -0,0 +1,260 @@ +country,area,birth_rate,death_rate,infant_mortality_rate,internet_users,life_exp_at_birth,maternal_mortality_rate,net_migration_rate,population,population_growth_rate +Russia,17098242,11.87,13.83,7.08,40853000,70.16,34,1.69,142470272,-0.03 +Canada,9984670,10.29,8.31,4.71,26960000,81.67,12,5.66,34834841,0.76 +United States,9826675,13.42,8.15,6.17,245000000,79.56,21,2.45,318892103,0.77 +China,9596960,12.17,7.44,14.79,389000000,75.15,37,-0.32,1355692576,0.44 +Brazil,8514877,14.72,6.54,19.21,75982000,73.28,56,-0.15,202656788,0.8 +Australia,7741220,12.19,7.07,4.43,15810000,82.07,7,5.74,22507617,1.09 +India,3287263,19.89,7.35,43.19,61338000,67.8,200,-0.05,1236344631,1.25 +Argentina,2780400,16.88,7.34,9.96,13694000,77.51,77,0,43024374,0.95 +Kazakhstan,2724900,19.61,8.31,21.61,5299000,70.24,51,0.42,17948816,1.17 +Algeria,2381741,23.99,4.31,21.76,NA,76.39,97,-0.93,38813722,1.88 +"Congo, Democratic Republic of the",2344858,35.62,10.3,73.15,290000,56.54,540,-0.33,77433744,2.5 +Greenland,2166086,14.53,8.38,9.42,36000,71.82,NA,-5.98,57728,0.02 +Saudi Arabia,2149690,18.78,3.32,14.58,9774000,74.82,24,-0.59,27345986,1.49 +Mexico,1964375,19.02,5.24,12.58,31020000,75.43,50,-1.64,120286655,1.21 +Indonesia,1904569,17.04,6.34,25.16,20000000,72.17,220,-1.18,253609643,0.95 +Sudan,1861484,30.01,7.87,52.86,4200000,63.32,730,-4.36,35482233,1.78 +Libya,1759540,18.4,3.57,11.87,353900,76.04,58,16.01,6244174,3.08 +Iran,1648195,18.23,5.94,39,8214000,70.89,21,-0.08,80840713,1.22 +Mongolia,1564116,20.88,6.38,23.15,330000,68.98,63,-0.85,2953190,1.37 +Peru,1285216,18.57,5.99,20.21,9158000,73.23,67,-2.69,30147935,0.99 +Chad,1284000,37.29,14.56,90.3,168100,49.44,1100,-3.54,11412107,1.92 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+Comoros,2235,29.05,7.76,65.31,24300,63.48,280,-2.58,766865,1.87 +Mauritius,2040,13.46,6.85,10.59,290000,75.17,60,0,1331155,0.66 +Virgin Islands,1910,10.49,8.24,6.79,30000,79.75,NA,-7.84,104170,-0.56 +Faroe Islands,1393,13.57,8.71,5.71,37500,80.11,NA,0,49947,0.49 +Hong Kong,1108,9.38,6.93,2.73,4873000,82.78,NA,1.69,7112688,0.41 +Sao Tome and Principe,964,35.12,7.45,49.16,26700,64.22,70,-8.79,190428,1.89 +Turks and Caicos Islands,948,16.61,3.08,10.97,NA,79.55,NA,12.23,49070,2.58 +Kiribati,811,21.85,7.18,35.37,7800,65.47,9,-2.86,104488,1.18 +Bahrain,760,13.92,2.67,9.68,419500,78.58,20,13.6,1314089,2.49 +Dominica,751,15.53,7.94,11.61,28000,76.59,NA,-5.39,73449,0.22 +Tonga,747,23.55,4.86,12.36,8400,75.82,110,-17.85,106440,0.09 +"Micronesia, Federated States of",702,20.97,4.25,21.93,17000,72.35,100,-20.93,105681,-0.42 +Singapore,697,8.1,3.42,2.53,3235000,84.38,3,14.55,5567301,1.92 +Saint Lucia,616,13.94,7.32,11.75,142900,77.41,35,-3.13,163362,0.35 +Isle of Man,572,11.17,10.03,4.17,NA,80.98,NA,6.84,86866,0.8 +Guam,544,17.01,5.04,5.51,90000,78.82,NA,-7.61,161001,0.44 +Andorra,468,8.48,6.82,3.69,67100,82.65,NA,0,85458,0.17 +Northern Mariana Islands,464,18.94,3.61,5.5,NA,77.64,NA,-4.02,51483,1.13 +Palau,459,10.95,7.93,11.46,NA,72.6,NA,0.66,21186,0.37 +Seychelles,455,14.54,6.9,10.77,32000,74.25,NA,1,91650,0.87 +Curacao,444,NA,8,NA,NA,77.98,NA,1.27,146836,NA +Antigua and Barbuda,443,15.94,5.7,13.29,65000,76.12,NA,2.23,91295,1.25 +Barbados,430,11.97,8.41,10.93,188000,74.99,51,-0.3,289680,0.33 +Saint Vincent and the Grenadines,389,13.85,7.12,13.07,76000,74.86,48,-9.6,102918,-0.29 +Gaza Strip,360,32.2,3.09,15.46,1379000,74.64,64,0,1816379,2.91 +Grenada,344,16.3,8.04,10.5,25000,73.8,24,-3.24,110152,0.5 +Malta,316,10.24,8.96,3.59,240600,80.11,8,1.99,412655,0.33 +"Saint Helena, Ascension, and Tristan da Cunha",308,10.03,7.33,14.71,900,79.21,NA,0,7776,0.27 +Maldives,298,15.59,3.84,24.59,86400,75.15,60,-12.67,393595,-0.09 +Cayman Islands,264,12.13,5.41,6.21,23000,81.02,NA,14.71,54914,2.14 +Saint Kitts and Nevis,261,13.64,7.08,8.98,17000,75.29,NA,1.22,51538,0.78 +Niue,260,NA,NA,NA,1100,NA,NA,NA,1190,-0.03 +Saint Pierre and Miquelon,242,7.7,9.27,6.95,NA,80.26,NA,-8.57,5716,-1.02 +Cook Islands,236,14.7,7.8,14.33,6000,75.38,NA,NA,10134,-3 +American Samoa,199,22.87,4.68,8.92,NA,74.91,NA,-21.64,54517,-0.35 +Marshall Islands,181,26.36,4.24,21.39,2200,72.58,NA,-4.92,70983,1.72 +Aruba,180,12.65,8.09,11.74,24000,76.35,NA,9.04,110663,1.36 +Liechtenstein,160,10.53,7.02,4.33,23000,81.68,NA,4.72,37313,0.82 +British Virgin Islands,151,10.83,4.93,13.45,4000,78.29,NA,17.69,32680,2.36 +Wallis and Futuna,142,13.56,4.95,4.49,1300,79.42,NA,-5.27,15561,0.33 +Christmas Island,135,NA,NA,NA,464,NA,NA,NA,1530,1.11 +Jersey,116,11.65,7.63,3.86,29500,81.66,NA,4.08,96513,0.81 +Montserrat,102,11.31,6.52,13.66,1200,73.9,NA,0,5215,0.48 +Anguilla,91,12.68,4.54,3.4,3700,81.2,NA,12.43,16086,2.06 +Guernsey,78,9.89,8.69,3.47,48300,82.39,NA,2.4,65849,0.36 +San Marino,61,8.7,8.31,4.52,17000,83.18,NA,8.31,32742,0.87 +Saint Martin,54,NA,NA,NA,NA,NA,NA,NA,31530,NA +Bermuda,54,11.35,8.06,2.48,54000,81.04,NA,1.92,69839,0.52 +Pitcairn Islands,47,NA,NA,NA,NA,NA,NA,NA,48,0 +Norfolk Island,36,NA,NA,NA,NA,NA,NA,NA,2210,0.01 +Sint Maarten,34,13,4.51,9.05,NA,77.61,NA,6.63,39689,1.51 +Macau,28,8.98,4.1,3.13,270200,84.48,NA,3.4,587914,0.83 +Tuvalu,26,23.74,8.9,31.69,4200,65.81,NA,-6.86,10782,0.8 +Nauru,21,25.61,5.9,8.21,NA,66.4,NA,-14.12,9488,0.56 +Cocos (Keeling) Islands,14,NA,NA,NA,NA,NA,NA,NA,596,0 +Tokelau,12,NA,NA,NA,800,NA,NA,NA,1337,-0.01 +Gibraltar,7,14.15,8.33,6.29,20200,79.13,NA,-3.29,29185,0.25 +Monaco,2,6.72,9.01,1.81,23000,89.57,NA,2.85,30508,0.06 +Holy See (Vatican City),0,NA,NA,NA,NA,NA,NA,NA,842,0 +Jan Mayen,377,NA,NA,NA,NA,NA,NA,NA,NA,NA +Howland Island,2,NA,NA,NA,NA,NA,NA,NA,NA,NA +Heard Island and McDonald Islands,412,NA,NA,NA,NA,NA,NA,NA,NA,NA +South Georgia and South Sandwich Islands,3903,NA,NA,NA,NA,NA,NA,NA,NA,NA +Spratly Islands,5,NA,NA,NA,NA,NA,NA,NA,NA,NA +Midway Islands,6,NA,NA,NA,NA,NA,NA,NA,NA,NA +Clipperton Island,6,NA,NA,NA,NA,NA,NA,NA,NA,NA +British Indian Ocean Territory,54400,NA,NA,NA,NA,NA,NA,NA,NA,NA +Johnston Atoll,3,NA,NA,NA,NA,NA,NA,NA,NA,NA +Ashmore and Cartier Islands,5,NA,NA,NA,NA,NA,NA,NA,NA,NA +Jarvis Island,5,NA,NA,NA,NA,NA,NA,NA,NA,NA +Coral Sea Islands,3,NA,NA,NA,NA,NA,NA,NA,NA,NA +French Southern and Antarctic Lands,55,NA,NA,NA,NA,NA,NA,NA,NA,NA +Navassa Island,5,NA,NA,NA,NA,NA,NA,NA,NA,NA +Wake Island,7,NA,NA,NA,NA,NA,NA,NA,NA,NA +Kingman Reef,1,NA,NA,NA,NA,NA,NA,NA,NA,NA +United States Pacific Island Wildlife Refuges,22,NA,NA,NA,NA,NA,NA,NA,NA,NA +Dhekelia,131,NA,NA,NA,NA,NA,NA,NA,NA,NA +Bouvet Island,49,NA,NA,NA,NA,NA,NA,NA,NA,NA +Palmyra Atoll,12,NA,NA,NA,NA,NA,NA,NA,NA,NA +Akrotiri,123,NA,NA,NA,NA,NA,NA,NA,NA,NA +European Union,NA,NA,NA,4.33,NA,80.02,NA,NA,511434812,NA +Saint Barthelemy,NA,NA,NA,NA,NA,NA,NA,NA,7267,NA diff --git a/data/curated/usdata/cia_factbook.md b/data/curated/usdata/cia_factbook.md new file mode 100644 index 000000000..b93e0756c --- /dev/null +++ b/data/curated/usdata/cia_factbook.md @@ -0,0 +1,13 @@ +|variable |class |description | +|:-----------------------|:-------|:-------------------------------------| +|country |integer |Name of the country (factor with 259 levels). | +|area |integer |Total area of the country (in square kilometers). | +|birth_rate |double |Birth rate (number of live births per 1,000 people). | +|death_rate |double |Death rate (number of deaths per 1,000 people). | +|infant_mortality_rate |double |Infant mortality rate (number of deaths of infants under one year old per 1,000 live births). | +|internet_users |integer |Number of internet users. | +|life_exp_at_birth |double |Life expectancy at birth (in years). | +|maternal_mortality_rate |integer |Maternal mortality rate (number of maternal deaths per 100,000 live births). | +|net_migration_rate |double |Net migration rate (number of migrants per 1,000 people). | +|population |integer |Total population of the country. | +|population_growth_rate |double |Population growth rate (multiplier). | diff --git a/data/curated/usdata/cleaning.R b/data/curated/usdata/cleaning.R new file mode 100644 index 000000000..5cfd8fa9d --- /dev/null +++ b/data/curated/usdata/cleaning.R @@ -0,0 +1,12 @@ +# Mostly clean data provided by the {usdatasets} R package +# (https://cran.r-project.org/package=usdatasets). No cleaning was necessary. + +# pak::pak("usdatasets") +library(usdatasets) +cia_factbook <- usdatasets::cia_factbook_tbl_df |> + dplyr::mutate( + dplyr::across( + c("area", "internet_users"), + as.integer + ) + ) diff --git a/data/curated/usdata/instructions.md b/data/curated/usdata/instructions.md new file mode 100644 index 000000000..9fb091d89 --- /dev/null +++ b/data/curated/usdata/instructions.md @@ -0,0 +1,24 @@ +## Prepare the dataset + +These instructions are for preparing a dataset using the R programming language. +We hope to provide instructions for other programming languages eventually. + +If you have not yet set up your computer for submitting a dataset, please see the full instructions at . + +1. `cleaning.R`: Modify the `cleaning.R` file to get and clean the data. + - Write the code to download and clean the data in `cleaning.R`. + - If you're getting the data from a github repo, remember to use the 'raw' version of the URL. + - This script should result in one or more data.frames, with descriptive variable names (eg `players` and `teams`, not `df1` and `df2`). +2. `saving.R`: Use`saving.R` to save your datasets. This process creates both the `.csv` file(s) and the data dictionary template file(s) for your datasets. **It is not enough to simply save the CSV files using a separate process. We also need the data dictionaries.** + - Run the first line of `saving.R` to create the functions we'll use to save your dataset. + - Provide the name of your directory as `dir_name`. + - Use `ttsave()` for each dataset you created in `cleaning.R`, substituting the name fo the dataset for `YOUR_DATASET_DF`. +3. `{dataset}.md`: Edit the `{dataset}.md` files to describe your datasets. There should be one file for each of your datasets. You most likely only need to edit the "description" column to provide a description of each variable. +4. `intro.md`: Edit the `intro.md` file to describe your dataset. You don't need to add a `# Title` at the top; this is just a paragraph or two to introduce the week. +5. Find at least one image for your dataset, and ideally two. These often come from the article about your dataset. If you can't find an image, create an example data visualization, and save that. Save the images in your folder as `png` files. +6. `meta.yaml`: Edit `meta.yaml` to provide information about your dataset. Also provide information about how we can credit you in the `credit` block, and delete lines from this block that do not apply to you. + +### Submit your pull request with the data + +1. Commit the changes in this folder to your branch. In RStudio, you can do this on the "Git" tab (the "Commit" button). +2. Submit a pull request to https://github.com/rfordatascience/tidytuesday. In R, you can do this with `usethis::pr_push()`, and then follow the instructions in your browser. diff --git a/data/curated/usdata/intro.md b/data/curated/usdata/intro.md new file mode 100644 index 000000000..9774fd9da --- /dev/null +++ b/data/curated/usdata/intro.md @@ -0,0 +1,29 @@ +This week we're exploring the [CIA World Factbook](https://www.cia.gov/the-world-factbook/)! +The dataset comes from the [{usdatasets}](https://cran.r-project.org/package=usdatasets) R package via [this post on LinkedIn](https://www.linkedin.com/posts/andrescaceresrossi_rstats-rstudio-opensource-activity-7249513444830318592-r395). + +> The *World Factbook* provides basic intelligence on the history, people, government, +> economy, energy, geography, environment, communications, transportation, military, +> terrorism, and transnational issues for 265 world entities. + +Which countries have the highest number of internet users per square kilometer? +Which countries have the highest percentage of internet users? + +You might want to join this dataset with past TidyTueday datasets that featured country information! + +```r +# pak::pak("r4ds/ttmeta") +library(tidyverse) +library(ttmeta) + +country_datasets <- ttmeta::tt_datasets_metadata |> + dplyr::mutate( + has_country = purrr::map_lgl( + .data$variable_details, + \(var_dets) { + !is.null(var_dets) && + any(stringr::str_detect(tolower(var_dets$variable), "country")) + } + ) + ) |> + dplyr::filter(has_country) +``` diff --git a/data/curated/usdata/meta.yaml b/data/curated/usdata/meta.yaml new file mode 100644 index 000000000..9021618cb --- /dev/null +++ b/data/curated/usdata/meta.yaml @@ -0,0 +1,20 @@ +title: "The CIA World Factbook" +article: + title: "The World Factbook" + url: "https://www.cia.gov/the-world-factbook/" +data_source: + title: "usdatasets R package" + url: "https://cran.r-project.org/package=usdatasets" +images: +# Please include at least one image, and up to three images +- file: world_factbook.png + alt: > + The logo of the World Factbook, a blue globe with an eagle's head in white. + The eagle is wearing a monocle. +credit: +# We want to thank you for curating this dataset! If you do not want a +# particular type of credit, please delete the related line. + post: Jon Harmon + linkedin: https://www.linkedin.com/in/jonthegeek + mastodon: @jonthegeek@fosstodon.org + github: https://github.com/jonthegeek diff --git a/data/curated/usdata/saving.R b/data/curated/usdata/saving.R new file mode 100644 index 000000000..04260ac0d --- /dev/null +++ b/data/curated/usdata/saving.R @@ -0,0 +1,9 @@ +# Run this +source("data/curated/curation_scripts.R") + +# Fill in the name of your directory, then run this. +dir_name <- "usdata" + +# Run this for each of your datasets, replacing YOUR_DATASET_DF with the name of +# a data.frame from cleaning.R. +ttsave(cia_factbook, dir_name = dir_name) diff --git a/data/curated/usdata/world_factbook.png b/data/curated/usdata/world_factbook.png new file mode 100644 index 0000000000000000000000000000000000000000..6db90954c02a21ccb4face017cb545b59e85716b GIT binary patch literal 207343 zcmYIvby(Bw_rD;Wqq|3kw19#zYLqZKq*FqqTZsXqMk*F3-!%Gm9;7A 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zcfXTg(f?k)t^Wh1W8kdPK5$;?9K4Y48oY?`F`Dlj98G$!rpx*&))uiPDRT*Ips}nW|cI&mQ~vD%GQ#G(_4!6Kewgm_NOx~ z`ySt7+55=aEoBegm{D@yx{Q*$ZpbV?IxjK5KXOHS3ro0h4+~pNnIi{+nH68&G7fD# zyM(VzP^6YI1UkkP{I!dT$qY`IpMlr$HKo^<_VgfNFe-5?Zv>Y!8Ph@ry@yxJXpn`3 ggoK2ySuyti0|1)zAuho1$p8QV07*qoM6N<$g8s%!z5oCK literal 0 HcmV?d00001 From e1c60ce02886b2f3b39d00aac1d48fa4b2cbdde3 Mon Sep 17 00:00:00 2001 From: Jon Harmon Date: Sun, 20 Oct 2024 10:50:22 -0500 Subject: [PATCH 2/5] Update data/curated/usdata/cleaning.R --- data/curated/usdata/cleaning.R | 1 + 1 file changed, 1 insertion(+) diff --git a/data/curated/usdata/cleaning.R b/data/curated/usdata/cleaning.R index 5cfd8fa9d..94a5add0d 100644 --- a/data/curated/usdata/cleaning.R +++ b/data/curated/usdata/cleaning.R @@ -2,6 +2,7 @@ # (https://cran.r-project.org/package=usdatasets). No cleaning was necessary. # pak::pak("usdatasets") +library(dplyr) library(usdatasets) cia_factbook <- usdatasets::cia_factbook_tbl_df |> dplyr::mutate( From e16beb33cb493cf0c515e603687dd84de486936d Mon Sep 17 00:00:00 2001 From: Jon Harmon Date: Sun, 20 Oct 2024 10:50:27 -0500 Subject: [PATCH 3/5] Update data/curated/usdata/meta.yaml --- data/curated/usdata/meta.yaml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/data/curated/usdata/meta.yaml b/data/curated/usdata/meta.yaml index 9021618cb..4aaeea2cc 100644 --- a/data/curated/usdata/meta.yaml +++ b/data/curated/usdata/meta.yaml @@ -14,7 +14,3 @@ images: credit: # We want to thank you for curating this dataset! If you do not want a # particular type of credit, please delete the related line. - post: Jon Harmon - linkedin: https://www.linkedin.com/in/jonthegeek - mastodon: @jonthegeek@fosstodon.org - github: https://github.com/jonthegeek From 1558a532b3802e6be6ebada28e190cc2692b3e04 Mon Sep 17 00:00:00 2001 From: jonthegeek Date: Sun, 20 Oct 2024 15:54:50 +0000 Subject: [PATCH 4/5] Accept submission --- README.md | 1 + .../2024-10-22}/cia_factbook.csv | 0 .../usdata => 2024/2024-10-22}/meta.yaml | 2 +- data/2024/2024-10-22/readme.md | 91 ++++++++++++++++++ .../2024-10-22}/world_factbook.png | Bin data/2024/readme.md | 1 + data/curated/usdata/cia_factbook.md | 13 --- data/curated/usdata/cleaning.R | 13 --- data/curated/usdata/instructions.md | 24 ----- data/curated/usdata/intro.md | 29 ------ data/curated/usdata/saving.R | 9 -- static/tt_data_type.csv | 1 + 12 files changed, 95 insertions(+), 89 deletions(-) rename data/{curated/usdata => 2024/2024-10-22}/cia_factbook.csv (100%) rename data/{curated/usdata => 2024/2024-10-22}/meta.yaml (95%) create mode 100644 data/2024/2024-10-22/readme.md rename data/{curated/usdata => 2024/2024-10-22}/world_factbook.png (100%) delete mode 100644 data/curated/usdata/cia_factbook.md delete mode 100644 data/curated/usdata/cleaning.R delete mode 100644 data/curated/usdata/instructions.md delete mode 100644 data/curated/usdata/intro.md delete mode 100644 data/curated/usdata/saving.R diff --git a/README.md b/README.md index c3ce6c44c..81aa95d0c 100644 --- a/README.md +++ b/README.md @@ -74,6 +74,7 @@ If you are using TidyTuesday to teach data-related skills, [please let us know]( | 40 | `2024-10-01` | [Chess Game Dataset (Lichess)](data/2024/2024-10-01/readme.md) | [Chess Game Dataset (Lichess)](https://www.kaggle.com/datasets/datasnaek/chess/data) | [Beginner's Guide: Data Visualization with Python](https://www.kaggle.com/code/batibayburak/beginner-s-guide-data-visualization-with-python) | | 41 | `2024-10-08` | [National Park Species](data/2024/2024-10-08/readme.md) | [NPSpecies - The National Park Service biodiversity database](https://irma.nps.gov/npspecies/) | [NPSpecies with Julia & Tidier](https://github.com/frankiethull/NPSpecies/inst/examples/julia/NPSpecies_TidierOrg.md) | | 42 | `2024-10-15` | [Southern Resident Killer Whale Encounters](data/2024/2024-10-15/readme.md) | [Center for Whale Research](https://www.whaleresearch.com/) | [Web Scraping & Mapping {orcas} Encounters](https://jadeynryan.github.io/orcas/) | +| 43 | `2024-10-22` | [The CIA World Factbook](data/2024/2024-10-22/readme.md) | [usdatasets R package](https://cran.r-project.org/package=usdatasets) | [The World Factbook](https://www.cia.gov/the-world-factbook/) | *** diff --git a/data/curated/usdata/cia_factbook.csv b/data/2024/2024-10-22/cia_factbook.csv similarity index 100% rename from data/curated/usdata/cia_factbook.csv rename to data/2024/2024-10-22/cia_factbook.csv diff --git a/data/curated/usdata/meta.yaml b/data/2024/2024-10-22/meta.yaml similarity index 95% rename from data/curated/usdata/meta.yaml rename to data/2024/2024-10-22/meta.yaml index 4aaeea2cc..e8cd193fd 100644 --- a/data/curated/usdata/meta.yaml +++ b/data/2024/2024-10-22/meta.yaml @@ -7,7 +7,7 @@ data_source: url: "https://cran.r-project.org/package=usdatasets" images: # Please include at least one image, and up to three images -- file: world_factbook.png +- file: "world_factbook.png" alt: > The logo of the World Factbook, a blue globe with an eagle's head in white. The eagle is wearing a monocle. diff --git a/data/2024/2024-10-22/readme.md b/data/2024/2024-10-22/readme.md new file mode 100644 index 000000000..eb75c8d47 --- /dev/null +++ b/data/2024/2024-10-22/readme.md @@ -0,0 +1,91 @@ +# The CIA World Factbook + +This week we're exploring the [CIA World Factbook](https://www.cia.gov/the-world-factbook/)! +The dataset comes from the [{usdatasets}](https://cran.r-project.org/package=usdatasets) R package via [this post on LinkedIn](https://www.linkedin.com/posts/andrescaceresrossi_rstats-rstudio-opensource-activity-7249513444830318592-r395). + +> The *World Factbook* provides basic intelligence on the history, people, government, +> economy, energy, geography, environment, communications, transportation, military, +> terrorism, and transnational issues for 265 world entities. + +Which countries have the highest number of internet users per square kilometer? +Which countries have the highest percentage of internet users? + +You might want to join this dataset with past TidyTueday datasets that featured country information! + +```r +# pak::pak("r4ds/ttmeta") +library(tidyverse) +library(ttmeta) + +country_datasets <- ttmeta::tt_datasets_metadata |> + dplyr::mutate( + has_country = purrr::map_lgl( + .data$variable_details, + \(var_dets) { + !is.null(var_dets) && + any(stringr::str_detect(tolower(var_dets$variable), "country")) + } + ) + ) |> + dplyr::filter(has_country) +``` + +## The Data + +```r +# Option 1: tidytuesdayR package +## install.packages("tidytuesdayR") + +tuesdata <- tidytuesdayR::tt_load('2024-10-22') +## OR +tuesdata <- tidytuesdayR::tt_load(2024, week = 43) + +cia_factbook <- tuesdata$cia_factbook + +# Option 2: Read directly from GitHub + +cia_factbook <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-10-22/cia_factbook.csv') +``` + +## How to Participate + +- [Explore the data](https://r4ds.hadley.nz/), watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about **causation** in the data. There are various moderating variables that affect all data, many of which might not have been captured in these datasets. As such, our suggestion is to use the data provided to practice your data tidying and plotting techniques, and to consider for yourself what nuances might underlie these relationships. +- Create a visualization, a model, a [shiny app](https://shiny.posit.co/), or some other piece of data-science-related output, using R or another programming language. +- [Share your output and the code used to generate it](../../../sharing.md) on social media with the #TidyTuesday hashtag. +- [Submit your own dataset!](../../../.github/pr_instructions.md) + +### Data Dictionary + +# `cia_factbook.csv` + +|variable |class |description | +|:-----------------------|:-------|:-------------------------------------| +|country |integer |Name of the country (factor with 259 levels). | +|area |integer |Total area of the country (in square kilometers). | +|birth_rate |double |Birth rate (number of live births per 1,000 people). | +|death_rate |double |Death rate (number of deaths per 1,000 people). | +|infant_mortality_rate |double |Infant mortality rate (number of deaths of infants under one year old per 1,000 live births). | +|internet_users |integer |Number of internet users. | +|life_exp_at_birth |double |Life expectancy at birth (in years). | +|maternal_mortality_rate |integer |Maternal mortality rate (number of maternal deaths per 100,000 live births). | +|net_migration_rate |double |Net migration rate (number of migrants per 1,000 people). | +|population |integer |Total population of the country. | +|population_growth_rate |double |Population growth rate (multiplier). | + +### Cleaning Script + +```r +# Mostly clean data provided by the {usdatasets} R package +# (https://cran.r-project.org/package=usdatasets). No cleaning was necessary. + +# pak::pak("usdatasets") +library(dplyr) +library(usdatasets) +cia_factbook <- usdatasets::cia_factbook_tbl_df |> + dplyr::mutate( + dplyr::across( + c("area", "internet_users"), + as.integer + ) + ) +``` diff --git a/data/curated/usdata/world_factbook.png b/data/2024/2024-10-22/world_factbook.png similarity index 100% rename from data/curated/usdata/world_factbook.png rename to data/2024/2024-10-22/world_factbook.png diff --git a/data/2024/readme.md b/data/2024/readme.md index 2b5b02641..cc67d632d 100644 --- a/data/2024/readme.md +++ b/data/2024/readme.md @@ -46,3 +46,4 @@ Archive of datasets and articles from the 2024 series of `#TidyTuesday` events. | 40 | `2024-10-01` | [Chess Game Dataset (Lichess)](2024-10-01/readme.md) | [Chess Game Dataset (Lichess)](https://www.kaggle.com/datasets/datasnaek/chess/data) | [Beginner's Guide: Data Visualization with Python](https://www.kaggle.com/code/batibayburak/beginner-s-guide-data-visualization-with-python) | | 41 | `2024-10-08` | [National Park Species](2024-10-08/readme.md) | [NPSpecies - The National Park Service biodiversity database](https://irma.nps.gov/npspecies/) | [NPSpecies with Julia & Tidier](https://github.com/frankiethull/NPSpecies/inst/examples/julia/NPSpecies_TidierOrg.md) | | 42 | `2024-10-15` | [Southern Resident Killer Whale Encounters](2024-10-15/readme.md) | [Center for Whale Research](https://www.whaleresearch.com/) | [Web Scraping & Mapping {orcas} Encounters](https://jadeynryan.github.io/orcas/) | +| 43 | `2024-10-22` | [The CIA World Factbook](2024-10-22/readme.md) | [usdatasets R package](https://cran.r-project.org/package=usdatasets) | [The World Factbook](https://www.cia.gov/the-world-factbook/) | diff --git a/data/curated/usdata/cia_factbook.md b/data/curated/usdata/cia_factbook.md deleted file mode 100644 index b93e0756c..000000000 --- a/data/curated/usdata/cia_factbook.md +++ /dev/null @@ -1,13 +0,0 @@ -|variable |class |description | -|:-----------------------|:-------|:-------------------------------------| -|country |integer |Name of the country (factor with 259 levels). | -|area |integer |Total area of the country (in square kilometers). | -|birth_rate |double |Birth rate (number of live births per 1,000 people). | -|death_rate |double |Death rate (number of deaths per 1,000 people). | -|infant_mortality_rate |double |Infant mortality rate (number of deaths of infants under one year old per 1,000 live births). | -|internet_users |integer |Number of internet users. | -|life_exp_at_birth |double |Life expectancy at birth (in years). | -|maternal_mortality_rate |integer |Maternal mortality rate (number of maternal deaths per 100,000 live births). | -|net_migration_rate |double |Net migration rate (number of migrants per 1,000 people). | -|population |integer |Total population of the country. | -|population_growth_rate |double |Population growth rate (multiplier). | diff --git a/data/curated/usdata/cleaning.R b/data/curated/usdata/cleaning.R deleted file mode 100644 index 94a5add0d..000000000 --- a/data/curated/usdata/cleaning.R +++ /dev/null @@ -1,13 +0,0 @@ -# Mostly clean data provided by the {usdatasets} R package -# (https://cran.r-project.org/package=usdatasets). No cleaning was necessary. - -# pak::pak("usdatasets") -library(dplyr) -library(usdatasets) -cia_factbook <- usdatasets::cia_factbook_tbl_df |> - dplyr::mutate( - dplyr::across( - c("area", "internet_users"), - as.integer - ) - ) diff --git a/data/curated/usdata/instructions.md b/data/curated/usdata/instructions.md deleted file mode 100644 index 9fb091d89..000000000 --- a/data/curated/usdata/instructions.md +++ /dev/null @@ -1,24 +0,0 @@ -## Prepare the dataset - -These instructions are for preparing a dataset using the R programming language. -We hope to provide instructions for other programming languages eventually. - -If you have not yet set up your computer for submitting a dataset, please see the full instructions at . - -1. `cleaning.R`: Modify the `cleaning.R` file to get and clean the data. - - Write the code to download and clean the data in `cleaning.R`. - - If you're getting the data from a github repo, remember to use the 'raw' version of the URL. - - This script should result in one or more data.frames, with descriptive variable names (eg `players` and `teams`, not `df1` and `df2`). -2. `saving.R`: Use`saving.R` to save your datasets. This process creates both the `.csv` file(s) and the data dictionary template file(s) for your datasets. **It is not enough to simply save the CSV files using a separate process. We also need the data dictionaries.** - - Run the first line of `saving.R` to create the functions we'll use to save your dataset. - - Provide the name of your directory as `dir_name`. - - Use `ttsave()` for each dataset you created in `cleaning.R`, substituting the name fo the dataset for `YOUR_DATASET_DF`. -3. `{dataset}.md`: Edit the `{dataset}.md` files to describe your datasets. There should be one file for each of your datasets. You most likely only need to edit the "description" column to provide a description of each variable. -4. `intro.md`: Edit the `intro.md` file to describe your dataset. You don't need to add a `# Title` at the top; this is just a paragraph or two to introduce the week. -5. Find at least one image for your dataset, and ideally two. These often come from the article about your dataset. If you can't find an image, create an example data visualization, and save that. Save the images in your folder as `png` files. -6. `meta.yaml`: Edit `meta.yaml` to provide information about your dataset. Also provide information about how we can credit you in the `credit` block, and delete lines from this block that do not apply to you. - -### Submit your pull request with the data - -1. Commit the changes in this folder to your branch. In RStudio, you can do this on the "Git" tab (the "Commit" button). -2. Submit a pull request to https://github.com/rfordatascience/tidytuesday. In R, you can do this with `usethis::pr_push()`, and then follow the instructions in your browser. diff --git a/data/curated/usdata/intro.md b/data/curated/usdata/intro.md deleted file mode 100644 index 9774fd9da..000000000 --- a/data/curated/usdata/intro.md +++ /dev/null @@ -1,29 +0,0 @@ -This week we're exploring the [CIA World Factbook](https://www.cia.gov/the-world-factbook/)! -The dataset comes from the [{usdatasets}](https://cran.r-project.org/package=usdatasets) R package via [this post on LinkedIn](https://www.linkedin.com/posts/andrescaceresrossi_rstats-rstudio-opensource-activity-7249513444830318592-r395). - -> The *World Factbook* provides basic intelligence on the history, people, government, -> economy, energy, geography, environment, communications, transportation, military, -> terrorism, and transnational issues for 265 world entities. - -Which countries have the highest number of internet users per square kilometer? -Which countries have the highest percentage of internet users? - -You might want to join this dataset with past TidyTueday datasets that featured country information! - -```r -# pak::pak("r4ds/ttmeta") -library(tidyverse) -library(ttmeta) - -country_datasets <- ttmeta::tt_datasets_metadata |> - dplyr::mutate( - has_country = purrr::map_lgl( - .data$variable_details, - \(var_dets) { - !is.null(var_dets) && - any(stringr::str_detect(tolower(var_dets$variable), "country")) - } - ) - ) |> - dplyr::filter(has_country) -``` diff --git a/data/curated/usdata/saving.R b/data/curated/usdata/saving.R deleted file mode 100644 index 04260ac0d..000000000 --- a/data/curated/usdata/saving.R +++ /dev/null @@ -1,9 +0,0 @@ -# Run this -source("data/curated/curation_scripts.R") - -# Fill in the name of your directory, then run this. -dir_name <- "usdata" - -# Run this for each of your datasets, replacing YOUR_DATASET_DF with the name of -# a data.frame from cleaning.R. -ttsave(cia_factbook, dir_name = dir_name) diff --git a/static/tt_data_type.csv b/static/tt_data_type.csv index b506d7dd6..32e200912 100644 --- a/static/tt_data_type.csv +++ b/static/tt_data_type.csv @@ -1,4 +1,5 @@ Week,Date,year,data_files,data_type,delim +43,2024-10-22,2024,cia_factbook.csv,csv,"," 42,2024-10-15,2024,orcas.csv,csv,"," 41,2024-10-08,2024,most_visited_nps_species_data.csv,csv,"," 40,2024-10-01,2024,chess.csv,csv,"," From a79fd3379e6bbe50e8ff7b455106568e0dfcc89c Mon Sep 17 00:00:00 2001 From: Jon Harmon Date: Sun, 20 Oct 2024 11:02:42 -0500 Subject: [PATCH 5/5] Update data/2024/2024-10-22/readme.md --- data/2024/2024-10-22/readme.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/data/2024/2024-10-22/readme.md b/data/2024/2024-10-22/readme.md index eb75c8d47..29cdb32f5 100644 --- a/data/2024/2024-10-22/readme.md +++ b/data/2024/2024-10-22/readme.md @@ -1,7 +1,10 @@ # The CIA World Factbook This week we're exploring the [CIA World Factbook](https://www.cia.gov/the-world-factbook/)! -The dataset comes from the [{usdatasets}](https://cran.r-project.org/package=usdatasets) R package via [this post on LinkedIn](https://www.linkedin.com/posts/andrescaceresrossi_rstats-rstudio-opensource-activity-7249513444830318592-r395). +The dataset this week comes from the [CIA Factbook, Country Comparisons, 2014](https://www.cia.gov/the-world-factbook/references/guide-to-country-comparisons), +via the [{openintro}](https://openintrostat.github.io/openintro/) R package, +via the [{usdatasets}](https://cran.r-project.org/package=usdatasets) R package, +via [this post on LinkedIn](https://www.linkedin.com/posts/andrescaceresrossi_rstats-rstudio-opensource-activity-7249513444830318592-r395). > The *World Factbook* provides basic intelligence on the history, people, government, > economy, energy, geography, environment, communications, transportation, military,