[ { "date_posted": "2023-10-03", "project_name": "US Government Grant Opportunities", "project_source": [ "https://opencollective.foundation", "https://r4ds.io/donate", "https://r4ds.io/join", "https://www.grants.gov/web/grants/search-grants.html", "https://r4ds.io/youtube" ], "description": "The R4DS Online Learning Community is a community of learners at all skill levels working together to improve our data-science-related skills. We offer free data-related education throughbook clubsand free live question-answering on ourSlack, and by curating a dataset every week here at TidyTuesday. We are now a fiscally sponsored project of Open Collective Foundation (https://opencollective.foundation), a 501(c)(3) public charity. That meansdonations to the R4DS Online Learning Communityare now tax-deductible in the US! It also means that we are now eligible for a number of grants, including some of the grants listed onGrants.gov. We have exported all grants past and present from that site, and we are making them available here for you to explore and visualize. We also scraped details for all posted grants. Please let us know if you find anything interesting!", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-03", "data_dictionary": [ { "variable": [ "opportunity_id", "opportunity_number", "opportunity_title", "agency_code", "agency_name", "estimated_funding", "expected_number_of_awards", "grantor_contact", "agency_contact_phone", "agency_contact_email", "estimated_post_date", "estimated_application_due_date", "posted_date", "close_date", "last_updated_date_time", "version", "opportunity_status" ], "class": [ "integer", "character", "character", "character", "character", "double", "integer", "character", "character", "character", "date", "date", "date", "date", "datetime", "character", "character" ], "description": [ "Integer ID for this opportunity, which can be used to find details at https://www.grants.gov/web/grants/view-opportunity.html?oppId={opportunity_id}", "Funding opportunity ID number", "Title of the opportunity", "Abbreviated name for the funding agency", "Full name of the funding agency", "Estimated funding amount in dollars", "Expected count of awards", "Information about how to contact the grantor. Often includes email address", "Phone number for the agency when available", "Contact email address for the agency (almost always available)", "When the opportunity is/was expected to be posted", "Date by which applications are/were expected to be received", "When the opportunity was posted", "When the opportunity was closed or will close", "Date and time when the opportunity was updated", "Integer version number of the opportunity", "Whether the opportunity is Archived, Closed, Forecasted, or Posted" ] }, { "variable": [ "opportunity_id", "funding_opportunity_number", "funding_opportunity_title", "opportunity_category", "opportunity_category_explanation", "expected_number_of_awards", "cost_sharing_or_matching_requirement", "version", "posted_date", "last_updated_date", "original_closing_date_for_applications", "current_closing_date_for_applications", "archive_date", "estimated_total_program_funding", "award_ceiling", "award_floor", "agency_name", "description", "link_to_additional_information", "grantor_contact_information", "eligibility_individuals", "eligibility_state_governments", "eligibility_county_governments", "eligibility_independent_school_districts", "eligibility_city_or_township_governments", "eligibility_special_district_governments", "eligibility_native_american_tribal_governments_federally_recognized", "eligibility_native_american_tribal_organizations_other", "eligibility_nonprofits_501c3", "eligibility_nonprofits_non_501c3", "eligibility_for_profit", "eligibility_small_businesses", "eligibility_private_institutions_of_higher_education", "eligibility_public_institutions_of_higher_education", "eligibility_public_indian_housing_authorities", "eligibility_others", "eligibility_unrestricted", "additional_information_on_eligibility", "funding_cooperative_agreement", "funding_grant", "funding_procurement_contract", "funding_other", "cfda_numbers", "category_agriculture", "category_arts", "category_business", "category_community_development", "category_consumer_protection", "category_disaster", "category_education", "category_employment", "category_energy", "category_environment", "category_food", "category_health", "category_housing", "category_humanities", "category_iija", "category_income_security", "category_info", "category_law", "category_natural_resources", "category_opportunity_zone", "category_regional_development", "category_science", "category_transportation", "category_other", "category_explanation" ], "class": [ "integer", "character", "character", "character", "character", "integer", "logical", "integer", "date", "date", "date", "date", "date", "double", "double", "double", "character", "character", "character", "character", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "character", "logical", "logical", "logical", "logical", "character", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "character" ], "description": [ "Integer ID for this opportunity, which can be used to find these details at https://www.grants.gov/web/grants/view-opportunity.html?oppId={opportunity_id}", "Funding opportunity ID number", "Title of the opportunity", "\\\"Continuation\\\", \\\"Discretionary\\\", \\\"Earmark\\\", \\\"Mandatory\\\", or \\\"Other\\\"", "More details about why the opportunity is in that category (mostly details about Other)", "Expected count of awards", "Whether the opportunity requires a cost-sharing or cost-matching agreement", "Integer version number of the opportunity", "When the opportunity was posted", "When the opportunity was updated", "When the opportunity was originally scheduled to close", "When the opportunity is currently scheduled to close", "When the opportunity will be archived", "Estimated funding amount in dollars", "Maximum individual award amount in dollars", "Minimum individual award amount in dollars", "Full name of the granting agency", "Free text description of the opportunity. Sometimes includes tables or potentially other figures, which did not necessarily scrape accurately", "The text of any links to additional information (unlikely to be useful in this format)", "Information about who to contact about the grant; may have contained links, which are not included in the scraped data", "Are individuals eligible?", "Are state governments eligible?", "Are county governments eligible?", "Are independent school districts eligible?", "Are city or township governments eligible?", "Are special district governments eligible?", "Are Native American tribal governments (Federally recognized) eligible?", "Are Native American tribal organizations (other than Federally recognized tribal governments) eligible?", "Are nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education eligible?", "Are nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education eligible?", "Are for profit organizations other than small businesses eligible?", "Are small businesses eligible?", "Are private institutions of higher education eligible?", "Are public and State controlled institutions of higher education eligible?", "Are public housing authorities and Indian housing authorities eligible?", "Are other groups eligible?", "Is eligibility unrestricted?", "Additional details about eligibility", "Is the opportunity funded via a cooperative agreement?", "Is the opportunity funded via a grant?", "Is the opportunity funded via a procurement contract?", "Is the opportunity funded via some other instrument?", "Catalog of Federal Domestic Assistance number(s) (see https://sam.gov/content/assistance-listings)", "Category: Agriculture", "Category: Arts (see \\\"Cultural Affairs\\\" in CFDA)", "Category: Business and Commerce", "Category: Community Development", "Category: Consumer Protection", "Category: Disaster Prevention and Relief", "Category: Education", "Category: Employment, Labor and Training", "Category: Energy", "Category: Environment", "Category: Food and Nutrition", "Category: Health", "Category: Housing", "Category: Humanities (see \\\"Cultural Affairs\\\" in CFDA)", "Category: Infrastructure Investment and Jobs Act (IIJA)", "Category: Income Security and Social Services", "Category: Information and Statistics", "Category: Law, Justice and Legal Services", "Category: Natural Resources", "Category: Opportunity Zone Benefits", "Category: Regional Development", "Category: Science and Technology and other Research and Development", "Category: Transportation", "Category: Other (see category_explanation for clarification)", "More details about the funding category or categories" ] } ], "data": { "file_name": [ "grant_opportunity_details.csv", "grants.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-03/grant_opportunity_details.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-03/grants.csv" ] } }, { "date_posted": "2023-12-05", "project_name": "Life Expectancy", "project_source": [ "https://ourworldindata.org/life-expectancy?insight=life-expectancy-has-surpassed-predictions-again-and-again#key-insights", "https://ourworldindata.org/life-expectancy#key-insights", "https://github.com/rfordatascience/tidytuesday/tree/master/data/2018#readme", "https://doi.org/10.1111/j.1728-4457.2005.00083.x", "https://ourworldindata.org/life-expectancy", "http://hdl.handle.net/10622/LKYT5" ], "description": "Our World in Data released anew report on life expectancy, and analysis and interpretations are making the rounds this week, and you can join in too! We had a dataset on Global Life Expectancy on2018-07-03, so if you're a long time tidytuesday-er, this is a chance for some new analyses. The data this week comes theOur World in Data Life Expectancy report, specifically the figures in thekey insightssection. The source for this data is from United Nations World Population Prospects (2022); Human Mortality Database (2023); Zijdeman, Richard and Filipa Ribeira da Silva (2015),Life Expectancy at Birth (Total); Riley, J.C. (2005),Estimates of Regional and Global Life Expectancy 1800-2001, Population and Development Review, 31: 537-543. Minor processing by Our World in Data. Across the world, people are living longer. In 1900, the average life expectancy of a newborn was 32 years. By 2021 this had more than doubled to 71 years. But where, when, how, and why has this dramatic change occurred? To understand it, we can look at data on life expectancy worldwide. The large reduction in child mortality has played an important role in increasing life expectancy. But life expectancy has increased at all ages. Infants, children, adults, and the elderly are all less likely to die than in the past, and death is being delayed. This remarkable shift results from advances in medicine, public health, and living standards. Along with it, many predictions of the ‘limit’ of life expectancy have been broken. On the Our World in Data Life Expectancy page, you will find global data and research on life expectancy and related measures of longevity: the probability of death at a given age, the sex gap in life expectancy, lifespan inequality within countries, and more. Data was downloaded from the tables for the figures in theKey Insights sectionof the Life Expectancy article. Column names were changed to make the data easier to work with.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-05", "data_dictionary": [ { "variable": [ "Entity", "Code", "Year", "LifeExpectancy" ], "class": [ "character", "character", "double", "double" ], "description": [ "Country or region entity", "Entity code", "Year", "Period life expectancy at birth - Sex: all - Age: 0" ] }, { "variable": [ "Entity", "Code", "Year", "LifeExpectancy0", "LifeExpectancy10", "LifeExpectancy25", "LifeExpectancy45", "LifeExpectancy65", "LifeExpectancy80" ], "class": [ "character", "character", "double", "double", "double", "double", "double", "double", "double" ], "description": [ "Country or region entity", "Entity code", "Year", "Period life expectancy at birth - Sex: all - Age: 0", "Period life expectancy - Sex: all - Age: 10", "Period life expectancy - Sex: all - Age: 25", "Period life expectancy - Sex: all - Age: 45", "Period life expectancy - Sex: all - Age: 65", "Period life expectancy - Sex: all - Age: 80" ] }, { "variable": [ "Entity", "Code", "Year", "LifeExpectancyDiffFM" ], "class": [ "character", "character", "double", "double" ], "description": [ "Country or region entity", "Entity code", "Year", "Life expectancy difference (f-m) - Type: period - Sex: both - Age: 0" ] } ], "data": { "file_name": [ "life_expectancy.csv", "life_expectancy_different_ages.csv", "life_expectancy_female_male.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-05/life_expectancy.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-05/life_expectancy_different_ages.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-05/life_expectancy_female_male.csv" ] } }, { "date_posted": "2023-12-12", "project_name": "Holiday Movies", "project_source": [ "https://networkdatascience.ceu.edu/article/2019-12-16/christmas-movies", "https://developer.imdb.com/non-commercial-datasets/" ], "description": "Happy holidays! This week we're exploring \"holiday\" movies: movies with \"holiday\", \"Christmas\", \"Hanukkah\", or \"Kwanzaa\" (or variants thereof) in their title! The data this week comes from theInternet Movie Database. We don't have an article using exactly this dataset, but you might get inspiration from thisChristmas Moviesblog post by Milán Janosov at Central European University.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-12", "data_dictionary": [ { "variable": [ "tconst", "title_type", "primary_title", "original_title", "year", "runtime_minutes", "genres", "simple_title", "average_rating", "num_votes", "christmas", "hanukkah", "kwanzaa", "holiday" ], "class": [ "character", "character", "character", "character", "double", "double", "character", "character", "double", "double", "logical", "logical", "logical", "logical" ], "description": [ "alphanumeric unique identifier of the title", "the type/format of the title (movie, video, or tvMovie)", "the more popular title / the title used by the filmmakers on promotional materials at the point of release", "original title, in the original language", "the release year of a title", "primary runtime of the title, in minutes", "includes up to three genres associated with the title (comma-delimited)", "the title in lowercase, with punctuation removed, for easier filtering and grouping", "weighted average of all the individual user ratings on IMDb", "number of votes the title has received on IMDb (titles with fewer than 10 votes were not included in this dataset)", "whether the title includes \\\"christmas\\\", \\\"xmas\\\", \\\"x mas\\\", etc", "whether the title includes \\\"hanukkah\\\", \\\"chanukah\\\", etc", "whether the title includes \\\"kwanzaa\\\"", "whether the title includes the word \\\"holiday\\\"" ] }, { "variable": [ "tconst", "genres" ], "class": [ "character", "character" ], "description": [ "alphanumeric unique identifier of the title", "genres associated with the title, one row per genre" ] } ], "data": { "file_name": [ "holiday_movie_genres.csv", "holiday_movies.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-12/holiday_movie_genres.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-12-12/holiday_movies.csv" ] } }, { "date_posted": "2023-03-14", "project_name": "European Drug Development", "project_source": [ "https://www.ema.europa.eu/en/medicines/download-medicine-data", "https://github.com/MiqG/EMA-Data-Scratching-with-RSelenium", "https://towardsdatascience.com/dissecting-28-years-of-european-pharmaceutical-development-3affd8f87dc0", "https://www.ema.europa.eu/sites/default/files/Medicines_output_european_public_assessment_reports.xlsx" ], "description": "The data this week comes from theEuropean Medicines AgencyviaMiquel Anglada Girotto on GitHub. We used thesource table of all EPARs for human and veterinary medicines, rather than Miquel's scraped data. Miquelwrote abouthis exploration of the data.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-03-14", "data_dictionary": [ { "variable": [ "category", "medicine_name", "therapeutic_area", "common_name", "active_substance", "product_number", "patient_safety", "authorisation_status", "atc_code", "additional_monitoring", "generic", "biosimilar", "conditional_approval", "exceptional_circumstances", "accelerated_assessment", "orphan_medicine", "marketing_authorisation_date", "date_of_refusal_of_marketing_authorisation", "marketing_authorisation_holder_company_name", "pharmacotherapeutic_group", "date_of_opinion", "decision_date", "revision_number", "condition_indication", "species", "first_published", "revision_date", "url" ], "class": [ "character", "character", "character", "character", "character", "character", "logical", "character", "character", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "date", "date", "character", "character", "date", "date", "integer", "character", "character", "datetime", "datetime", "character" ], "description": [ "human or veterinary", "brand name of the medicine", "semicolon-separated list of therapeutic areas; might benefit from further cleaning", "international non-proprietary name (INN) or common name", "common name of the active chemical in the drug", "EMEA/H/C/ (human) or EMEA/V/C/ (veterinary) number for the drug", "has patient safety notices", "whether the drug was authorised, withdrawn, or refused (or does not have a reported status)", "anatomical therapeutic chemical code", "when true, the medicine is under additional monitoring, meaning that it is monitored even more intensively than other medicines", "whether the drug is a generic medicine, which is developed to be the same as a medicine that has already been authorised, called the reference medicine. A generic medicine contains the same active substance(s) as the reference medicine, and is used at the same dose(s) to treat the same disease(s)", "whether the drug is a biosimilar medicine, which is a biological medicine highly similar to another already approved biological medicine called the reference medicine.", "whether the medicine received a conditional marketing authorisation. This was granted in the interest of public health because the medicine addresses an unmet medical need and the benefit of immediate availability outweighs the risk from less comprehensive data than normally required.", "whether the medicine was authorised under exceptional circumstances, because the applicant was unable to provide comprehensive data on the efficacy and safety of the medicine under normal conditions of use. This can happen because the condition to be treated is rare or because collection of full information is not possible or is unethical.", "whether the medicine had an accelerated assessment. This means that it is a medicine of major interest for public health, so its timeframe for review was 150 evaluation days rather than 210.", "whether the medicine was designated an orphan medicine. This means that it was developed for use against a rare, life-threatening or chronically debilitating condition or, for economic reasons, it would be unlikely to have been developed without incentives.", "date on which the drug was authorised", "date on which the drug was refused", "name of the company that is authorised to market the drug", "the target of the drug; might benefit from further cleaning", "date on which the opinion was made", "date on which the latest decision was made", "integer revision number", "language describing the specific uses of the drug", "for veterinary medicines, the target species; might benefit from further cleaning", "datetime when the information was first published", "datetime of the most recent revision", "url for details about the drug and submission" ] } ], "data": { "file_name": [ "drugs.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-03-14/drugs.csv" ] } }, { "date_posted": "2023-09-05", "project_name": "Union Membership in the United States", "project_source": [ "https://www.unionstats.com/", "https://onlinelibrary.wiley.com/doi/10.1111/irel.12330" ], "description": "Happy Labor Day*! The data this week comes from theUnion Membership, Coverage, and Earnings from the CPSby Barry Hirsch (Georgia State University), David Macpherson (Trinity University), and William Even (Miami University). They claim a copyright on the data, and state that \"Use of data requires citation.\" Unionstats.com provides annual measures of union, nonunion, and overall wages, beginning in 1973, compiled from the U.S. Current Population Surveys. Regression-based union wage gap estimates are presented economy-wide, for demographic groups, and sectors (private/public, industries). Union wage gaps are higher in the private than in the public sector, higher for men than women, roughly similar for black and white men, and much higher for Hispanic men than for Hispanic women. The database is updated annually. See their open-access article\"Five decades of CPS wages, methods, and union-nonunion wage gaps at Unionstats.com\"for details about their methods and additional visualizations. Data sources: The definition of union membership was expanded in 1977 to include \"employee associations similar to a union\". Data sources: The definition of union membership was expanded in 1977 to include \"employee associations similar to a union\". Data source: Current Population Survey (CPS) Outgoing Rotation Group (ORG) Earnings Files", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-05", "data_dictionary": [ { "variable": [ "year", "sample_size", "employment", "members", "covered", "p_members", "p_covered", "facet" ], "class": [ "double", "double", "double", "double", "double", "double", "double", "character" ], "description": [ "When the data was collected.", "The number of wage and salary workers ages 16 and over who were surveyed.", "Wage and salary employment in thousands.", "Employed workers who are union members in thousands.", "Workers covered by a collective bargaining agreement in thousands.", "Percent of employed workers who are union members.", "Percent of employed workers who are covered by a collective bargaining agreement.", "The sector or demographic group contained in this row of data." ] }, { "variable": [ "year", "sample_size", "wage", "at_cap", "union_wage", "nonunion_wage", "union_wage_premium_raw", "union_wage_premium_adjusted", "facet" ], "class": [ "double", "double", "double", "double", "double", "double", "double", "double", "character" ], "description": [ "When the data was collected.", "The number of wage and salary workers ages 16 and over who were surveyed and provided earnings and hours worked information.", "Mean hourly earnings in nominal dollars.", "Percent of workers with weekly earnings at the top code of $999 through 1988, $1923 in 1989-97, and $2885 beginning in 1998, with individuals assigned mean earnings above the cap based on annual estimates of the gender-specific Pareto distribution.", "Mean wage among union members.", "Mean wage among nonunion workers.", "The percentage difference between the union and nonunion wage.", "Estimated as exp(b)-1 where b is the regression coefficient on a union membership variable (equal to 1 if union and 0 otherwise) from a semi-logarithmic wage equation, with controls included for worker/job characteristics. Included in the all-worker wage equation are the control variables: years of schooling, potential years of experience [proxied by age minus years of schooling minus 6] and its square [both interacted with gender], and categorical variables for marital status, race and ethnicity, gender, part-time, large metropolitan area, state, public sector, broad industry, and broad occupation. Controls are omitted, as appropriate, for estimates within sectors or by demographic group [i.e., by class, gender, race, or industry sector]. Workers who do not report earnings but instead have them imputed [i.e., assigned] by the Census are removed from the estimation samples in all years, except 1994 and 1995 when imputed earners cannot be identified. Inclusion of imputed earners causes union wages to be understated, nonunion wages overstated, and union-nonunion wage differences understated. For 1994-95, the sample includes imputed earners and estimates in those years have been adjusted to remove the bias from imputation.", "The sector or demographic group contained in this row of data." ] }, { "variable": [ "state_census_code", "state", "sector", "observations", "employment", "members", "covered", "p_members", "p_covered", "state_abbreviation", "year" ], "class": [ "double", "character", "character", "double", "double", "double", "double", "double", "double", "character", "double" ], "description": [ "Census state code used in CPS", "State name.", "Employment sector.", "CPS sample size.", "Wage and salary employment in thousands.", "Employed workers who are union members in thousands.", "Workers covered by a collective bargaining agreement in thousands.", "Percent of employed workers who are union members.", "Percent of employed workers who are covered by a collective bargaining agreement.", "State abbreviation.", "Year of the survey." ] } ], "data": { "file_name": [ "demographics.csv", "states.csv", "wages.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-05/demographics.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-05/states.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-05/wages.csv" ] } }, { "date_posted": "2023-08-29", "project_name": "Fair Use", "project_source": [ "https://www.copyright.gov/fair-use/fair-index.html" ], "description": "The data this week comes from theU.S. Copyright Office Fair Use Index. Fair use is a longstanding and vital aspect of American copyright law. The goal of the Index is to make the principles and application of fair use more accessible and understandable to the public by presenting a searchable database of court opinions, including by category and type of use (e.g., music, internet/digitization, parody). There are two datasets this week for which the rows align, but the values might not precisely line up for a clean join -- a case you often have to deal with in real-world data.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-29", "data_dictionary": [ { "variable": [ "case", "year", "court", "jurisdiction", "categories", "outcome", "fair_use_found" ], "class": [ "character", "integer", "character", "character", "character", "character", "logical" ], "description": [ "The name and number of the case.", "The year in which the case was decided.", "The court in which the ruling was made.", "The jurisdiction of that court.", "A comma- or semicolon-separated list of categories to which the case belongs. These have not been normalized.", "A string describing the outcome of the case.", "Whether fair use was found by the court. FALSE might sometimes indicate a more complicated finding." ] }, { "variable": [ "title", "case_number", "year", "court", "key_facts", "issue", "holding", "tags", "outcome" ], "class": [ "character", "character", "character", "character", "character", "character", "character", "character", "character" ], "description": [ "The title of the case.", "The case number or numbers of the case.", "The year in which the finding was made (or findings were made).", "The court or courts involved.", "The key facts of the case.", "A brief description of the fair use issue.", "The decision of the court in paragraph form.", "Comma- or semicolon-separated tags for this case.", "A brief description of the outcome of the case. These fields have not been normalized." ] } ], "data": { "file_name": [ "fair_use_cases.csv", "fair_use_findings.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-29/fair_use_cases.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-29/fair_use_findings.csv" ] } }, { "date_posted": "2023-08-01", "project_name": "US State Names", "project_source": [ "https://en.wikipedia.org/wiki/List_of_demonyms_for_US_states_and_territories", "https://tidytues.day/2018/2018-04-03", "https://tidytues.day/2022/2022-11-08", "https://tidytues.day/2019/2019-01-29", "https://en.wikipedia.org/wiki/List_of_state_and_territory_name_etymologies_of_the_United_States", "https://tidytues.day/2020/2020-03-10", "https://en.wikipedia.org/wiki/List_of_states_and_territories_of_the_United_States", "https://www.timeanddate.com/holidays/us/colorado-day" ], "description": "HappyColorado Day! The data this week comes from three Wikipedia articles:List of states and territories of the United States,List of demonyms for US states and territories, andList of state and territory name etymologies of the United States. A number of past TidyTuesdays (such as 2018/2018-04-03,2019/2019-01-29,2020/2020-03-10, and2022/2022-11-08have state columns. Might joining in this state date offer any insights to those datasets?", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-01", "data_dictionary": [ { "variable": [ "state", "postal_abbreviation", "capital_city", "largest_city", "admission", "population_2020", "total_area_mi2", "total_area_km2", "land_area_mi2", "land_area_km2", "water_area_mi2", "water_area_km2", "n_representatives", "demonym" ], "class": [ "character", "character", "character", "character", "date", "integer", "integer", "integer", "integer", "integer", "integer", "integer", "integer", "character" ], "description": [ "The name of the state. The Wikipedia article has footnotes pointing out that Kentucky, Massachusetts, Pennsylvania, and Virginia are officially \\\"commonwealths\\\" in their full official names, not states.", "The 2-letter postal abbreviation.", "The capital of the state.", "The largest city in the state as of 2020.", "The date when the state was admitted to the union, or when it ratified the US Constitution.", "The population as of the 2020 census.", "The total area of the state in square miles.", "The total area of the state in square kilometers.", "The area of the state that is on land in square miles.", "The area of the state that is on land in square kilometers.", "The area of the state occupied by water in square miles.", "The area of the state occupied by water in square kilometers.", "The number of representatives the state has in the US House of Representatives.", "The official name of a resident of the state." ] }, { "variable": [ "state", "date_named", "language", "words_in_original", "meaning" ], "class": [ "character", "date", "character", "character", "character" ], "description": [ "The name of the state.", "The date on which the name (or a version of the name that led to the modern version) was first attested. Note: Colorado is shown as occurring on January 1, but only the year is known.", "The language from which the state name is believed to have been derived. Note that some states have more than one entry, in more than one row!", "The word or words in the original language that became the state name. This field has footnotes in the original Wikipedia article.", "The meaning of the original words. This field has footnotes in the original Wikipedia article." ] } ], "data": { "file_name": [ "state_name_etymology.csv", "states.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-01/state_name_etymology.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-01/states.csv" ] } }, { "date_posted": "2023-01-31", "project_name": "Pet Cats UK", "project_source": [ "http://dx.doi.org/10.1111/acv.12563", "https://www.datarepository.movebank.org/handle/10255/move.876", "https://www.datarepository.movebank.org/handle/10255/move.882", "https://themarkup.org/data-is-plural/2023/01/25/from-jazz-solos-to-cats-on-the-move#:~:text=Giuseppe%20Sollazzo%5D-,Cats%20on%20the%20move,-.%20Between%202013", "https://www.datarepository.movebank.org/handle/10255/move.879", "https://www.datarepository.movebank.org/handle/10255/move.885", "http://dx.doi.org/10.5441/001/1.pf315732" ], "description": "The data this week comes from theMovebank for Animal Tracking DataviaData is Plural. Thanks @jthomasmock for the suggestion! Between 2013 and 2017, Roland Kays et al. convinced hundreds of volunteers in the U.S., U.K., Australia, and New Zealand to strap GPS sensors on their pet cats. The aforelinked datasets include each cat's characteristics (such as age, sex, neuter status, hunting habits) and time-stamped GPS pings. When using this dataset, please cite the original article. Kays R, Dunn RR, Parsons AW, Mcdonald B, Perkins T, Powers S, Shell L, McDonald JL, Cole H, Kikillus H, Woods L, Tindle H, Roetman P (2020) The small home ranges and large local ecological impacts of pet cats. Animal Conservation.doi:10.1111/acv.12563 Additionally, please cite the Movebank data package: McDonald JL, Cole H (2020) Data from: The small home ranges and large local ecological impacts of pet cats [United Kingdom]. Movebank Data Repository.doi:10.5441/001/1.pf315732 Additional datasets for theUS,Australia, andNew Zealandare also available for download, but they were too large for us to include them directly. Full dictionaries are available onMovebank", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-01-31", "data_dictionary": [ { "variable": [ "tag_id", "event_id", "visible", "timestamp", "location_long", "location_lat", "ground_speed", "height_above_ellipsoid", "algorithm_marked_outlier", "manually_marked_outlier", "study_name" ], "class": [ "character", "double", "logical", "double", "double", "double", "double", "double", "logical", "logical", "character" ], "description": [ "A unique identifier for the tag, provided by the data owner. If the data owner does not provide a tag ID, an internal Movebank tag identifier may sometimes be shown.", "An identifier for the set of values associated with each event, i.e. sensor measurement. A unique event ID is assigned to every time-location or other time-measurement record in Movebank. If multiple measurements are included within a single row of a data file, they will share an event ID. If users import the same sensor measurement to Movebank multiple times, a separate event ID will be assigned to each.", "Determines whether an event is visible on the Movebank map. Values are calculated automatically, with TRUE indicating the event has not been flagged as an outlier by algorithm_marked_outlier, import_marked_outlier or manually_marked_outlier, or that the user has overridden the results of these outlier attributes using manually_marked_valid = TRUE. Allowed values are TRUE or FALSE.", "The date and time corresponding to a sensor measurement or an estimate derived from sensor measurements.", "The geographic longitude of the location as estimated by the sensor. Positive values are east of the Greenwich Meridian, negative values are west of it.", "The geographic longitude of the location as estimated by the sensor. Positive values are east of the Greenwich Meridian, negative values are west of it.", "The estimated ground speed provided by the sensor or calculated between consecutive locations. Units are reportedly m/s, which indicates that there is likely a problem with this data (either the units were reported erroneously or their is an issue with the sensor data).", "The estimated height above the ellipsoid, typically estimated by the tag. Units: meters", "Identifies events marked as outliers using a user-selected filter algorithm in Movebank. Outliers have the value TRUE.", "Identifies events flagged manually as outliers, typically using the Event Editor in Movebank, and may also include outliers identified using other methods. Outliers have the value TRUE.", "The name of the study in Movebank." ] }, { "variable": [ "tag_id", "animal_id", "animal_taxon", "deploy_on_date", "deploy_off_date", "hunt", "prey_p_month", "animal_reproductive_condition", "animal_sex", "hrs_indoors", "n_cats", "food_dry", "food_wet", "food_other", "study_site", "age_years" ], "class": [ "character", "character", "character", "double", "double", "logical", "double", "character", "character", "double", "double", "logical", "logical", "logical", "character", "double" ], "description": [ "A unique identifier for the tag, provided by the data owner. If the data owner does not provide a tag ID, an internal Movebank tag identifier may sometimes be shown.", "An individual identifier for the animal, provided by the data owner. If the data owner does not provide an Animal ID, an internal Movebank animal identifier is sometimes shown.", "The scientific name of the species on which the tag was deployed, as defined by the Integrated Taxonomic Information System (ITIS, www.itis.gov). If the species name can not be provided, this should be the lowest level taxonomic rank that can be determined and that is used in the ITIS taxonomy.", "The timestamp when the tag deployment started.", "The timestamp when the tag deployment ended.", "Whether the animal was allowed to hunt.", "Approximate number of prey caught by the animal per month.", "The reproductive condition of the animal at the beginning of the deployment.", "The sex of the animal, as \\\"m\\\" or \\\"f\\\".", "The average number of hours which the animal was indoors per day.", "The number of cats in the house.", "Whether the cat was fed dry food.", "Whether the cat was fed wet food.", "Whether the cat was fed other food.", "A location such as the deployment site or colony, or a location-related group such as the herd or pack name.", "The age of the animal at the beginning of the deployment, in years. \\\"0\\\" indicates that the animal was < 1 year old." ] } ], "data": { "file_name": [ "cats_uk.csv", "cats_uk_reference.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-01-31/cats_uk.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-01-31/cats_uk_reference.csv" ] } }, { "date_posted": "2023-08-08", "project_name": "Hot Ones Episodes", "project_source": [ "https://en.wikipedia.org/wiki/List_of_Hot_Ones_episodes", "https://github.com/borstell", "https://github.com/rfordatascience/tidytuesday/issues/591", "https://en.wikipedia.org/wiki/Hot_Ones" ], "description": "The data this week comes from Wikipedia articles:Hot OnesandList of Hot Ones episodes. Thank you toCarl Börstellfor thesuggestion and cleaning script! Hot Ones is an American YouTube talk show, created by Chris Schonberger, hosted by Sean Evans and produced by First We Feast and Complex Media. Its basic premise involves celebrities being interviewed by Evans over a platter of increasingly spicy chicken wings.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-08", "data_dictionary": [ { "variable": [ "season", "episode_overall", "episode_season", "title", "original_release", "guest", "guest_appearance_number", "finished" ], "class": [ "integer", "integer", "integer", "character", "date", "character", "integer", "logical" ], "description": [ "The season number.", "The overall count of this episode, from 1-300.", "The count of this episode within this season.", "The title of the episode.", "The date on which the episode was originally available on YouTube.", "The name of the guest.", "The number of appearances by this guest so far as of this date.", "Whether the guest finished trying all of the sauces." ] }, { "variable": [ "season", "sauce_number", "sauce_name", "scoville" ], "class": [ "integer", "integer", "character", "integer" ], "description": [ "The season number.", "The number of this sauce, from 1 (least hot) to 10 (hottest).", "The name of the sauce.", "The rating of the sauce in Scoville heat units." ] }, { "variable": [ "season", "episodes", "note", "original_release", "last_release" ], "class": [ "integer", "integer", "character", "date", "date" ], "description": [ "The season number.", "The count of episodes in this season.", "Notes about this season.", "The date of the first episode in this season.", "The date of the last episode of this season (if that episode has aired at the time of scraping)." ] } ], "data": { "file_name": [ "episodes.csv", "sauces.csv", "seasons.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-08/episodes.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-08/sauces.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-08/seasons.csv" ] } }, { "date_posted": "2023-08-22", "project_name": "Refugees", "project_source": [], "description": "The data this week comes from PopulationStatistics {refugees} R package. {refugees} is an R package designed to facilitate access to the United Nations High Commissioner for Refugees (UNHCR) Refugee Data Finder. It provides an easy-to-use interface to the database, which covers forcibly displaced populations, including refugees, asylum-seekers, internally displaced people, stateless people, and others over a span of more than 70 years. This package provides data from three major sources: The {refugees} package includes eight datasets. We're working withpopulationwith data from 2010 to 2022.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-22", "data_dictionary": [ { "variable": [ "year", "coo_name", "coo", "coo_iso", "coa_name", "coa", "coa_iso", "refugees", "asylum_seekers", "returned_refugees", "idps", "returned_idps", "stateless", "ooc", "oip", "hst" ], "class": [ "double", "character", "character", "character", "character", "character", "character", "double", "double", "double", "double", "double", "double", "double", "double", "double" ], "description": [ "The year.", "Country of origin name.", "Country of origin UNHCR code.", "Country of origin ISO code.", "Country of asylum name.", "Country of asylum UNHCR code.", "Country of asylum ISO code.", "The number of refugees.", "The number of asylum-seekers.", "The number of returned refugees.", "The number of internally displaced persons.", "The number of returned internally displaced persons.", "The number of stateless persons.", "The number of others of concern to UNHCR.", "The number of other people in need of international protection.", "The number of host community members." ] } ], "data": { "file_name": [ "population.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-08-22/population.csv" ] } }, { "date_posted": "2023-03-21", "project_name": "Programming Languages", "project_source": [ "https://github.com/rfordatascience/tidytuesday/issues/530", "https://pldb.com/posts/does-every-programming-language-support-line-comments.html", "https://pldb.com/csv.html", "https://pldb.com/index.html", "https://pldb.com/posts/index.html" ], "description": "The data this week comes from theProgramming Language DataBase. Thanks toJesus M. Castagnettofor the suggestion! The PLDB has ablogwith numerous articles exploring the data, such asDoes every programming language have line comments?. The data is user-submitted, so you might want to confirm the accuracy of anything particularly surprising that you find before stating it with certainty! Thefull data dictionaryis available from PLDB.com.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-03-21", "data_dictionary": [ { "variable": [ "pldb_id", "title", "description", "type", "appeared", "creators", "website", "domain_name", "domain_name_registered", "reference", "isbndb", "book_count", "semantic_scholar", "language_rank", "github_repo", "github_repo_stars", "github_repo_forks", "github_repo_updated", "github_repo_subscribers", "github_repo_created", "github_repo_description", "github_repo_issues", "github_repo_first_commit", "github_language", "github_language_tm_scope", "github_language_type", "github_language_ace_mode", "github_language_file_extensions", "github_language_repos", "wikipedia", "wikipedia_daily_page_views", "wikipedia_backlinks_count", "wikipedia_summary", "wikipedia_page_id", "wikipedia_appeared", "wikipedia_created", "wikipedia_revision_count", "wikipedia_related", "features_has_comments", "features_has_semantic_indentation", "features_has_line_comments", "line_comment_token", "last_activity", "number_of_users", "number_of_jobs", "origin_community", "central_package_repository_count", "file_type", "is_open_source" ], "class": [ "character", "character", "character", "character", "double", "character", "character", "character", "double", "character", "double", "double", "integer", "double", "character", "double", "double", "double", "double", "double", "character", "double", "double", "character", "character", "character", "character", "character", "double", "character", "double", "double", "character", "double", "double", "double", "double", "character", "logical", "logical", "logical", "character", "double", "double", "double", "character", "double", "character", "logical" ], "description": [ "A standardized, uniquified version of the language name, used as an ID on the PLDB site.", "The official title of the language.", "Description of the repo on GitHub.", "Which category in PLDB's subjective ontology does this entity fit into.", "What year was the language publicly released and/or announced?", "Name(s) of the original creators of the language delimited by \\\" and \\\"", "URL of the official homepage for the language project.", "If the project website is on its own domain.", "When was this domain first registered?", "A link to more info about this entity.", "Books about this language from ISBNdb.", "Computed; the number of books found for this language at isbndb.com", "Papers about this language from Semantic Scholar.", "Computed; A rank for the language, taking into account various online rankings. The computation for this column is not currently clear.", "URL of the official GitHub repo for the project if it hosted there.", "How many stars of the repo?", "How many forks of the repo?", "What year was the last commit made?", "How many subscribers to the repo?", "When was the Github repo for this entity created?", "Description of the repo on GitHub.", "How many isses on the repo?", "What year the first commit made in this git repo?", "GitHub has a set of supported languages as defined here", "The TextMate scope that represents this programming language.", "Either data, programming, markup, prose, or nil.", "A String name of the Ace Mode used for highlighting whenever a file is edited. This must match one of the filenames in http://git.io/3XO_Cg. Use \\\"text\\\" if a mode does not exist.", "An Array of associated extensions (the first one is considered the primary extension, the others should be listed alphabetically).", "How many repos for this language does GitHub report?", "URL of the entity on Wikipedia, if and only if it has a page dedicated to it.", "How many page views per day does this Wikipedia page get? Useful as a signal for rankings. Available via WP api.", "How many pages on WP link to this page?", "What is the text summary of the language from the Wikipedia page?", "Waht is the internal ID for this entity on WP?", "When does Wikipedia claim this entity first appeared?", "When was the Wikipedia page for this entity created?", "How many revisions does this page have?", "What languages does Wikipedia have as related?", "Does this language have a comment character?", "Does indentation have semantic meaning in this language?", "Does this language support inline comments (as opposed to comments that must span an entire line)?", "Defined as a token that can be placed anywhere on a line and starts a comment that cannot be stopped except by a line break character or end of file.", "Computed; The most recent of any year field in the PLDB for this language.", "Computed; \\\"Crude user estimate from a linear model.", "Computed; The estimated number of job openings for programmers in this language.", "In what community(ies) did the language first originate?", "Number of packages in a central repository. If this value is not known, it is set to 0 (so \\\"0\\\" can mean \\\"no repository exists\\\", \\\"the repository exists but is empty\\\" (unlikely), or \\\"we do not know if a repository exists\\\". This value is definitely incorrect for R.", "What is the file encoding for programs in this language?", "Is it an open source project?" ] } ], "data": { "file_name": [ "languages.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-03-21/languages.csv" ] } }, { "date_posted": "2023-10-17", "project_name": "Taylor Swift", "project_source": [ "https://taylor.wjakethompson.com/", "https://developer.spotify.com/documentation/web-api/reference/get-audio-features", "https://www.tstheerastourfilm.com/", "https://asteves.github.io/tayloRswift/", "https://github.com/JosiahParry/cpcinema" ], "description": "SinceThe Eras Tour Filmwas just released, this week we're exploring Taylor Swift song data! Are you Ready for It? ThetaylorR package from W. Jake Thompson is a curated data set of Taylor Swift songs, including lyrics and audio characteristics. The data comes from Genius and the Spotify API. There are three main datasets. The first is taylor_album_songs, which includes lyrics and audio features from the Spotify API for all songs on Taylor’s official studio albums. Notably this excludes singles released separately from an album (e.g., Only the Young, Christmas Tree Farm, etc.), and non-Taylor-owned albums that have a Taylor-owned alternative (e.g., Fearless is excluded in favor of Fearless (Taylor’s Version)). We stan artists owning their own songs. You can access Taylor’s entire discography with taylor_all_songs. This includes all of the songs in taylor_album_songs plus EPs, individual singles, and the original versions of albums that have been re-released as Taylor’s Version. Finally, there is a small data set, taylor_albums, summarizing Taylor’s album release history. Information on the audio features in the dataset from Spotify are included in theirAPI documentation. For your visualizations, the {taylor} package comes with it’s own class of color palettes, inspired by the work of Josiah Parry in the{cpcinema}package. You might also be interested in thetayoRswift packageby Alex Stephenson, a ggplot2 color palette based on Taylor Swift album covers. \"For when your colors absolutely should not be excluded from the narrative.\"", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-17", "data_dictionary": [ { "variable": [ "album_name", "ep", "album_release", "track_number", "track_name", "artist", "featuring", "bonus_track", "promotional_release", "single_release", "track_release", "danceability", "energy", "key", "loudness", "mode", "speechiness", "acousticness", "instrumentalness", "liveness", "valence", "tempo", "time_signature", "duration_ms", "explicit", "key_name", "mode_name", "key_mode", "lyrics" ], "class": [ "character", "logical", "double", "integer", "character", "character", "character", "logical", "double", "double", "double", "double", "double", "integer", "double", "integer", "double", "double", "double", "double", "double", "double", "integer", "integer", "logical", "character", "character", "character", "list" ], "description": [ "Album name", "Is it an EP", "Album release date", "Track number", "Track name", "Artists", "Artists featured", "Is it a bonus track", "Date of promotional release", "Date of single release", "Date of track release", "Spotify danceability score. A value of 0.0 is least danceable and 1.0 is most danceable.", "Spotify energy score. Energy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity.", "The key the track is in.", "Spotify loudness score. The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track.", "Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1 and minor is 0.", "Spotify speechiness score. Speechiness detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value.", "Spotify acousticness score. A confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic.", "Spotify instrumentalness score. Predicts whether a track contains no vocals. The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0.", "Spotify liveness score. Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live.", "Spotify valence score. A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).", "The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration.", "An estimated time signature. The time signature (meter) is a notational convention to specify how many beats are in each bar (or measure). The time signature ranges from 3 to 7 indicating time signatures of \\\"3/4\\\", to \\\"7/4\\\".", "The duration of the track in milliseconds.", "Does the track have explicit lyrics.", "The key the track is in. Integers map to pitches using standard Pitch Class notation. E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1.", "Modality of the track.", "The key of the track.", "Track lyrics. These values are all NA. To get the lyrics in nested tibbles, install.packages(\\\"taylor\\\") and use the source data." ] }, { "variable": [ "album_name", "ep", "album_release", "track_number", "track_name", "artist", "featuring", "bonus_track", "promotional_release", "single_release", "track_release", "danceability", "energy", "key", "loudness", "mode", "speechiness", "acousticness", "instrumentalness", "liveness", "valence", "tempo", "time_signature", "duration_ms", "explicit", "key_name", "mode_name", "key_mode", "lyrics" ], "class": [ "character", "logical", "double", "integer", "character", "character", "character", "logical", "double", "double", "double", "double", "double", "integer", "double", "integer", "double", "double", "double", "double", "double", "double", "integer", "integer", "logical", "character", "character", "character", "list" ], "description": [ "Album name", "Is it an EP", "Album release date", "Track number", "Track name", "Artists", "Artists featured", "Is it a bonus track", "Date of promotional release", "Date of single release", "Date of track release", "Spotify danceability score. A value of 0.0 is least danceable and 1.0 is most danceable.", "Spotify energy score. Energy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity.", "The key the track is in.", "Spotify loudness score. The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track.", "Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1 and minor is 0.", "Spotify speechiness score. Speechiness detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value.", "Spotify acousticness score. A confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic.", "Spotify instrumentalness score. Predicts whether a track contains no vocals. The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0.", "Spotify liveness score. Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live.", "Spotify valence score. A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).", "The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration.", "An estimated time signature. The time signature (meter) is a notational convention to specify how many beats are in each bar (or measure). The time signature ranges from 3 to 7 indicating time signatures of \\\"3/4\\\", to \\\"7/4\\\".", "The duration of the track in milliseconds.", "Does the track have explicit lyrics.", "The key the track is in. Integers map to pitches using standard Pitch Class notation. E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1.", "Modality of the track.", "The key of the track.", "Track lyrics. These values are all NA. To get the lyrics in nested tibbles, install.packages(\\\"taylor\\\") and use the source data." ] }, { "variable": [ "album_name", "ep", "album_release", "metacritic_score", "user_score" ], "class": [ "character", "logical", "double", "integer", "double" ], "description": [ "Album name", "Is it an EP", "Album release date", "Metacritic score", "User score" ] } ], "data": { "file_name": [ "taylor_album_songs.csv", "taylor_albums.csv", "taylor_all_songs.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-17/taylor_album_songs.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-17/taylor_albums.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-10-17/taylor_all_songs.csv" ] } }, { "date_posted": "2023-11-14", "project_name": "Diwali Sales Data", "project_source": [ "https://www.kaggle.com/code/bhushanshelke69/diwali-data-exploration", "https://github.com/vikasvachheta08/Diwali_Sales_Analysis_Using_Python", "https://www.kaggle.com/datasets/saadharoon27/diwali-sales-dataset" ], "description": "This week is Diwali, the festival of lights! The data this week comes fromsales datafor a retail store during the Diwali festival period in India. The data is shared on Kaggle by Saad Haroon. This week we're sharing Python data analysis examples! There's a few out there, but these ones fromBrushan ShelkeorVikas Vachheta(see the Diwali_Sales_Analysis.ipynb file for the code) are some data exploration analyses. Data was downloaded fromKaggle, and theStatusandunnamed1columns removed.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-11-14", "data_dictionary": [ { "variable": [ "User_ID", "Cust_name", "Product_ID", "Gender", "Age Group", "Age", "Marital_Status", "State", "Zone", "Occupation", "Product_Category", "Orders", "Amount" ], "class": [ "double", "character", "character", "character", "character", "double", "double", "character", "character", "character", "character", "double", "double" ], "description": [ "User identification number", "Customer name", "Product identification number", "Gender of the customer (e.g. Male, Female)", "Age group of the customer", "Age of the customer", "Marital status of the customer (e.g. Married, Single)", "State of the customer", "Geographic zone of the customer", "Occupation of the customer", "Category of the product", "Number of orders made by the customer", "Amount in Indian rupees spent by the customer" ] } ], "data": { "file_name": [ "diwali_sales_data.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-11-14/diwali_sales_data.csv" ] } }, { "date_posted": "2023-01-03", "project_name": "Week 1", "project_source": [], "description": "This was really just a bring your own dataset week.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-01-03", "data_dictionary": [ { "variable": [ "1" ], "class": [ "2023-01-03" ], "description": [ "Bring your own data from 2022!" ] } ], "data": { "file_name": [], "file_url": [] } }, { "date_posted": "2023-05-23", "project_name": "Central Park Squirrel Census", "project_source": [ "https://data.cityofnewyork.us/Environment/2018-Central-Park-Squirrel-Census-Squirrel-Data/vfnx-vebw", "https://www.thesquirrelcensus.com/" ], "description": "Squirrel data! The data this week comes from the2018 Central Park Squirrel Census. The Squirrel Censusis a multimedia science, design, and storytelling project focusing on the Eastern gray (Sciurus carolinensis). They count squirrels and present their findings to the public. The dataset contains squirrel data for each of the 3,023 sightings, including location coordinates, age, primary and secondary fur color, elevation, activities, communications, and interactions between squirrels and with humans. No data cleaning", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-05-23", "data_dictionary": [ { "variable": [ "X", "Y", "Unique Squirrel ID", "Hectare", "Shift", "Date", "Hectare Squirrel Number", "Age", "Primary Fur Color", "Highlight Fur Color", "Combination of Primary and Highlight Color", "Color notes", "Location", "Above Ground Sighter Measurement", "Specific Location", "Running", "Chasing", "Climbing", "Eating", "Foraging", "Other Activities", "Kuks", "Quaas", "Moans", "Tail flags", "Tail twitches", "Approaches", "Indifferent", "Runs from", "Other Interactions", "Lat/Long" ], "class": [ "double", "double", "character", "character", "character", "double", "double", "character", "character", "character", "character", "character", "character", "character", "character", "logical", "logical", "logical", "logical", "logical", "character", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "logical", "character", "character" ], "description": [ "Longitude coordinate for squirrel sighting point", "Latitude coordinate for squirrel sighting point", "Identification tag for each squirrel sightings. The tag is comprised of \\\"Hectare ID\\\" + \\\"Shift\\\" + \\\"Date\\\" + \\\"Hectare Squirrel Number.\\\"", "ID tag, which is derived from the hectare grid used to divide and count the park area. One axis that runs predominantly north-to-south is numerical (1-42), and the axis that runs predominantly east-to-west is roman characters (A-I).", "Value is either \\\"AM\\\" or \\\"PM,\\\" to communicate whether or not the sighting session occurred in the morning or late afternoon.", "Concatenation of the sighting session day and month.", "Number within the chronological sequence of squirrel sightings for a discrete sighting session.", "Value is either \\\"Adult\\\" or \\\"Juvenile.\\\"", "Primary Fur Color - value is either \\\"Gray,\\\" \\\"Cinnamon\\\" or \\\"Black.\\\"", "Discrete value or string values comprised of \\\"Gray,\\\" \\\"Cinnamon\\\" or \\\"Black.\\\"", "A combination of the previous two columns; this column gives the total permutations of primary and highlight colors observed.", "Sighters occasionally added commentary on the squirrel fur conditions. These notes are provided here.", "Value is either \\\"Ground Plane\\\" or \\\"Above Ground.\\\" Sighters were instructed to indicate the location of where the squirrel was when first sighted.", "For squirrel sightings on the ground plane, fields were populated with a value of \\\"FALSE.\\\"", "Sighters occasionally added commentary on the squirrel location. These notes are provided here.", "Squirrel was seen running.", "Squirrel was seen chasing another squirrel.", "Squirrel was seen climbing a tree or other environmental landmark.", "Squirrel was seen eating.", "Squirrel was seen foraging for food.", "Other activities squirrels were observed doing.", "Squirrel was heard kukking, a chirpy vocal communication used for a variety of reasons.", "Squirrel was heard quaaing, an elongated vocal communication which can indicate the presence of a ground predator such as a dog.", "Squirrel was heard moaning, a high-pitched vocal communication which can indicate the presence of an air predator such as a hawk.", "Squirrel was seen flagging its tail. Flagging is a whipping motion used to exaggerate squirrel's size and confuse rivals or predators. Looks as if the squirrel is scribbling with tail into the air.", "Squirrel was seen twitching its tail. Looks like a wave running through the tail, like a breakdancer doing the arm wave. Often used to communicate interest, curiosity.", "Squirrel was seen approaching human, seeking food.", "Squirrel was indifferent to human presence.", "Squirrel was seen running from humans, seeing them as a threat.", "Sighter notes on other types of interactions between squirrels and humans.", "Latitude and longitude" ] } ], "data": { "file_name": [ "squirrel_data.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-05-23/squirrel_data.csv" ] } }, { "date_posted": "2023-05-09", "project_name": "Childcare Costs", "project_source": [ "https://twitter.com/jschwabish/status/1626597782491639810?s=46&t=avwSC7an3lwX3FH35u0gMA", "https://www.dol.gov/agencies/wb/topics/featured-childcare" ], "description": "Happy Mothers Day! The data this week comes from theNational Database of Childcare Prices. The National Database of Childcare Prices (NDCP) is the most comprehensive federal source of childcare prices at the county level. The database offers childcare price data by childcare provider type, age of children, and county characteristics. Data are available from 2008 to 2018. Thanks this week to Thomas Mock for the submission, with a hat tip toJon Schwabish on Twitterfor pointing out the lack of labels on the original government-posted map. Note: This dataset implies that \"both parents\" means one man and one woman. We recognize that this does not reflect the reality of every loving family.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-05-09", "data_dictionary": [ { "variable": [ "county_fips_code", "study_year", "unr_16", "funr_16", "munr_16", "unr_20to64", "funr_20to64", "munr_20to64", "flfpr_20to64", "flfpr_20to64_under6", "flfpr_20to64_6to17", "flfpr_20to64_under6_6to17", "mlfpr_20to64", "pr_f", "pr_p", "mhi_2018", "me_2018", "fme_2018", "mme_2018", "total_pop", "one_race", "one_race_w", "one_race_b", "one_race_i", "one_race_a", "one_race_h", "one_race_other", "two_races", "hispanic", "households", "h_under6_both_work", "h_under6_f_work", "h_under6_m_work", "h_under6_single_m", "h_6to17_both_work", "h_6to17_fwork", "h_6to17_mwork", "h_6to17_single_m", "emp_m", "memp_m", "femp_m", "emp_service", "memp_service", "femp_service", "emp_sales", "memp_sales", "femp_sales", "emp_n", "memp_n", "femp_n", "emp_p", "memp_p", "femp_p", "mcsa", "mfccsa", "mc_infant", "mc_toddler", "mc_preschool", "mfcc_infant", "mfcc_toddler", "mfcc_preschool" ], "class": [ "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double" ], "description": [ "Four- or five-digit number that uniquely identifies the county in a state. The first two digits (for five-digit numbers) or 1 digit (for four-digit numbers) refer to the FIPS code of the state to which the county belongs.", "Year the data collection began for the market rate survey and in which ACS data is representative of, or the study publication date.", "Unemployment rate of the population aged 16 years old or older.", "Unemployment rate of the female population aged 16 years old or older.", "Unemployment rate of the male population aged 16 years old or older.", "Unemployment rate of the population aged 20 to 64 years old.", "Unemployment rate of the female population aged 20 to 64 years old.", "Unemployment rate of the male population aged 20 to 64 years old.", "Labor force participation rate of the female population aged 20 to 64 years old.", "Labor force participation rate of the female population aged 20 to 64 years old who have children under 6 years old.", "Labor force participation rate of the female population aged 20 to 64 years old who have children between 6 and 17 years old.", "Labor force participation rate of the female population aged 20 to 64 years old who have children under 6 years old and between 6 and 17 years old.", "Labor force participation rate of the male population aged 20 to 64 years old.", "Poverty rate for families.", "Poverty rate for individuals.", "Median household income expressed in 2018 dollars.", "Median earnings expressed in 2018 dollars for the population aged 16 years old or older.", "Median earnings for females expressed in 2018 dollars for the population aged 16 years old or older.", "Median earnings for males expressed in 2018 dollars for the population aged 16 years old or older.", "Count of the total population.", "Percent of population that identifies as being one race.", "Percent of population that identifies as being one race and being only White or Caucasian.", "Percent of population that identifies as being one race and being only Black or African American.", "Percent of population that identifies as being one race and being only American Indian or Alaska Native.", "Percent of population that identifies as being one race and being only Asian.", "Percent of population that identifies as being one race and being only Native Hawaiian or Pacific Islander.", "Percent of population that identifies as being one race and being a different race not previously mentioned.", "Percent of population that identifies as being two or more races.", "Percent of population that identifies as being Hispanic or Latino regardless of race.", "Number of households.", "Number of households with children under 6 years old with two parents that are both working.", "Number of households with children under 6 years old with two parents with only the father working.", "Number of households with children under 6 years old with two parents with only the mother working.", "Number of households with children under 6 years old with a single mother.", "Number of households with children between 6 and 17 years old with two parents that are both working.", "Number of households with children between 6 and 17 years old with two parents with only the father working.", "Number of households with children between 6 and 17 years old with two parents with only the mother working.", "Number of households with children between 6 and 17 years old with a single mother.", "Percent of civilians employed in management, business, science, and arts occupations aged 16 years old or older in the county.", "Percent of male civilians employed in management, business, science, and arts occupations aged 16 years old or older in the county.", "Percent of female civilians employed in management, business, science, and arts occupations aged 16 years old or older in the county.", "Percent of civilians employed in service occupations aged 16 years old and older in the county.", "Percent of male civilians employed in service occupations aged 16 years old and older in the county.", "Percent of female civilians employed in service occupations aged 16 years old and older in the county.", "Percent of civilians employed in sales and office occupations aged 16 years old and older in the county.", "Percent of male civilians employed in sales and office occupations aged 16 years old and older in the county.", "Percent of female civilians employed in sales and office occupations aged 16 years old and older in the county.", "Percent of civilians employed in natural resources, construction, and maintenance occupations aged 16 years old and older in the county.", "Percent of male civilians employed in natural resources, construction, and maintenance occupations aged 16 years old and older in the county.", "Percent of female civilians employed in natural resources, construction, and maintenance occupations aged 16 years old and older in the county.", "Percent of civilians employed in production, transportation, and material moving occupations aged 16 years old and older in the county.", "Percent of male civilians employed in production, transportation, and material moving occupations aged 16 years old and older in the county.", "Percent of female civilians employed in production, transportation, and material moving occupations aged 16 years old and older in the county.", "Weekly, full-time median price charged for Center-Based Care for those who are school age based on the results reported in the market rate survey report for the county or the rate zone/cluster to which the county is assigned.", "Weekly, full-time median price charged for Family Childcare for those who are school age based on the results reported in the market rate survey report for the county or the rate zone/cluster to which the county is assigned.", "Aggregated weekly, full-time median price charged for Center-based Care for infants (i.e. aged 0 through 23 months).", "Aggregated weekly, full-time median price charged for Center-based Care for toddlers (i.e. aged 24 through 35 months).", "Aggregated weekly, full-time median price charged for Center-based Care for preschoolers (i.e. aged 36 through 54 months).", "Aggregated weekly, full-time median price charged for Family Childcare for infants (i.e. aged 0 through 23 months).", "Aggregated weekly, full-time median price charged for Family Childcare for toddlers (i.e. aged 24 through 35 months).", "Aggregated weekly, full-time median price charged for Family Childcare for preschoolers (i.e. aged 36 through 54 months)." ] }, { "variable": [ "county_fips_code", "county_name", "state_name", "state_abbreviation" ], "class": [ "double", "character", "character", "character" ], "description": [ "Four- or five-digit number that uniquely identifies the county in a state. The first two digits (for five-digit numbers) or 1 digit (for four-digit numbers) refer to the FIPS code of the state to which the county belongs.", "The full name of the county.", "The full name of the state in which the county is found.", "The two-letter state abbreviation." ] } ], "data": { "file_name": [ "childcare_costs.csv", "counties.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-05-09/childcare_costs.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-05-09/counties.csv" ] } }, { "date_posted": "2023-09-19", "project_name": "CRAN Package Authors", "project_source": [ "https://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-DESCRIPTION-file", "https://github.com/schochastics/CRAN_collaboration#readme", "https://github.com/schochastics/CRAN_collaboration", "https://posit.co/conference/", "https://github.com/schochastics" ], "description": "It's time forposit::conf(2023L)! To celebrate, the data this week comes from theCRAN collaboration graph, a project by David Schoch. The CRAN collaboration graph consists of R package developers who are connected if they appear together as authors of an R package in the DESCRIPTION file. The “Hadley number” is defined as the distance of R developers to Hadley Wickham in the collaboration graph. See theREADME of the GitHub projectfor a fun exploration of the data, and to see how it was gathered. SeeWriting R Extensionsfor more information about the fields in this dataset. The data was mostly cleaned byDavid Schoch. Additional cleaning was performed to save simple representations of the graph, and then to check that it worked.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-19", "data_dictionary": [ { "variable": [ "Package", "Version", "Priority", "Depends", "Imports", "LinkingTo", "Suggests", "Enhances", "License", "License_is_FOSS", "License_restricts_use", "OS_type", "Archs", "MD5sum", "NeedsCompilation", "Additional_repositories", "Author", "Authors@R", "Biarch", "BugReports", "BuildKeepEmpty", "BuildManual", "BuildResaveData", "BuildVignettes", "Built", "ByteCompile", "Classification/ACM", "Classification/ACM-2012", "Classification/JEL", "Classification/MSC", "Classification/MSC-2010", "Collate", "Collate.unix", "Collate.windows", "Contact", "Copyright", "Date", "Date/Publication", "Description", "Encoding", "KeepSource", "Language", "LazyData", "LazyDataCompression", "LazyLoad", "MailingList", "Maintainer", "Note", "Packaged", "RdMacros", "StagedInstall", "SysDataCompression", "SystemRequirements", "Title", "Type", "URL", "UseLTO", "VignetteBuilder", "ZipData", "Path", "X-CRAN-Comment", "Published", "Reverse depends", "Reverse imports", "Reverse linking to", "Reverse suggests", "Reverse enhances" ], "class": [ "character", "character", "character", "character", "character", "character", "character", "character", "character", "logical", "logical", "character", "character", "character", "character", "character", "character", "character", "character", "character", "logical", "logical", "character", "character", "logical", "character", "logical", "logical", "logical", "character", "logical", "character", "logical", "logical", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "character", "logical", "logical", "character", "character", "character", "character", "logical", "character", "character", "character", "logical", "double", "character", "character", "character", "character", "character" ], "description": [ "the name of the package", "the version of the package", "'recommended' indicates packages that are recommended to be incuded in every binary distribution of R. A handful of other packages use \\\"optional\\\" here.", "a comma-separated list of package names which this package depends on", "packages whose namespaces are imported from (as specified in the NAMESPACE file) but which do not need to be attached", "packages whose header files are used to compile this package's C/C++ code", "packages that are not necessarily needed", "packages “enhanced” by the package at hand, e.g., by providing methods for classes from these packages, or ways to handle objects from these packages", "license information", "whether the license is considered free, open-source software", "whether the license restricts use", "specifies the OS(es) for which the package is intended", "Archs", "MD5sum", "should be set to \\\"yes\\\" if the package contains native code which needs to be compiled, otherwise \\\"no\\\"", "Additional_repositories", "who wrote the package", "a refined and machine-readable description of the package “authors” (in particular specifying their precise roles)", "used on Windows to select the INSTALL option --force-biarch for this package", "a single URL to which bug reports about the package should be submitted", "BuildKeepEmpty", "BuildManual", "BuildResaveData", "can be set to a false value to stop R CMD build from attempting to build the vignettes, as well as preventing R CMD check from testing this", "added by the package management tools", "controls if the package R code is to be byte-compiled on installation", "subject classifications for the content of the package Computing Classification System of the Association for Computing Machinery", "subject classifications for the content of the package Computing Classification System of the Association for Computing Machinery", "subject classifications for the content of the package Journal of Economic Literature Classification System", "subject classifications for the content of the package Mathematics Subject Classification of the American Mathematical Society", "subject classifications for the content of the package Mathematics Subject Classification of the American Mathematical Society", "used for controlling the collation order for the R code files in a package when these are processed for package installation", "a UNIX-specific version of Collate", "a Windows-specific version of Collate", "Contact", "an optional field to be used when the copyright holder(s) are not the authors", "the release date of the current version of the package", "Date/Publication", "a comprehensive description of what the package does", "used as the encoding of the DESCRIPTION file itself and of the R and NAMESPACE files, and as the default encoding of .Rd files", "controls if the package code is sourced using keep.source = TRUE or FALSE", "used to indicate if the package documentation is not in English", "controls whether the R datasets use lazy-loading", "LazyDataCompression", "was used in versions prior to 2.14.0, but now is ignored", "MailingList", "a single name followed by a valid (RFC 2822) email address in angle brackets", "Note", "added by the package management tools", "used to hold a comma-separated list of packages from which the current package will import Rd macro definitions", "controls if package installation is ‘staged’, that is done to a temporary location and moved to the final location when successfully completed", "SysDataCompression", "dependencies external to the R system", "a short description of the package", "specifies the type of the package", "a list of URLs separated by commas or whitespace, for example the homepage of the author or a page where additional material describing the software can be found", "used to indicate if source code in the package is to be compiled with Link-Time Optimization", "names (in a comma-separated list) packages that provide an engine for building vignettes", "has been ignored since R 2.13.0", "Path", "X-CRAN-Comment", "Published", "Reverse depends", "Reverse imports", "Reverse linking to", "Reverse suggests", "Reverse enhances" ] }, { "variable": [ "Package", "authorsR" ], "class": [ "character", "character" ], "description": [ "the name of the package", "the author name from Authors@R, one author per row" ] }, { "variable": [ "name", "x", "y", "dist2HW", "cc" ], "class": [ "character", "double", "double", "double", "double" ], "description": [ "the name of this author", "x location for graph layout", "y location for graph layout", "distance from this author to Hadley Wickham", "1/igraph::closeness() for this node; the sum of the distances to all the other vertices in the graph" ] }, { "variable": [ "from", "to", "weight" ], "class": [ "double", "double", "double" ], "description": [ "the id (row) of the author to link from", "the id (row) of the author to link to", "a measure of the number of connections between these two authors" ] } ], "data": { "file_name": [ "cran_20230905.csv", "cran_graph_edges.csv", "cran_graph_nodes.csv", "package_authors.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-19/cran_20230905.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-19/cran_graph_edges.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-19/cran_graph_nodes.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-09-19/package_authors.csv" ] } }, { "date_posted": "2024-02-13", "project_name": "Valentine's Day Consumer Data", "project_source": [ "https://github.com/rfordatascience/tidytuesday/tree/master/data/2022/2022-01-25", "https://nrf.com/research-insights/holiday-data-and-trends/valentines-day/valentines-day-data-center", "https://www.kaggle.com/datasets/infinator/happy-valentines-day-2022", "https://github.com/rfordatascience/tidytuesday/tree/master/data/2022/2022-01-18" ], "description": "Happy Valentine's Day! This week we're exploringValentine's Day survey data. The National Retail Federation in the United States conducts surveys and has created aValentine's Day Data Centerso you can explore the data on how consumers celebrate. The NRF has surveyed consumers about how they plan to celebrate Valentine’s Day annually for over a decade. Take a deeper dive into the data from the last 10 years, and use the interactive charts to explore a demographic breakdown of total spending, average spending, types of gifts planned and spending per type of gift. The NRF has continued to collect data. The data for this week is from 2010 to 2022, as organized by Suraj Das for a Kaggle dataset. In the historical surveys gender was collected as only 'Men' and 'Women', which does not accurately include all genders. If you're looking for other Valentine's Day type datasets, check out previous datasets onchocolateorboard games(a good Valentine's Day activity!). Data was downloaded fromSunja aa Kaggle dataset. Data from historical_gift_trends_per_person_spending.csv, historical_spending_average_expected_spending.csv and historical_spending_percent_celebrating.csv were combined into historical_spending.csv. Data from planned_gifts_age.csv and spending_or_celebrating_age_1.csv were combined into gifts_age.csv. Data from planned_gifts_gender.csv and spending_or_celebrating_gender_1.csv were combined into gifts_gender.csv. Percentage signs and dollar signs were removed from all numerical values.", "data_source_url": "https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-02-13", "data_dictionary": [ { "variable": [ "Year", "PercentCelebrating", "PerPerson", "Candy", "Flowers", "Jewelry", "GreetingCards", "EveningOut", "Clothing", "GiftCards" ], "class": [ "double", "double", "double", "double", "double", "double", "double", "double", "double", "double" ], "description": [ "Year", "Percent of people celebrating Valentines Day", "Average amount each person is spending", "Average amount spending on candy", "Average amount spending on flowers", "Average amount spending on jewelry", "Average amount spending on greeting cards", "Average amount spending on an evening out", "Average amount spending on clothing", "Average amount spending on gift cards" ] }, { "variable": [ "Age", "SpendingCelebrating", "Candy", "Flowers", "Jewelry", "GreetingCards", "EveningOut", "Clothing", "GiftCards" ], "class": [ "character", "double", "double", "double", "double", "double", "double", "double", "double" ], "description": [ "Age", "Percent spending money on or celebrating Valentines Day", "Average percent spending on candy", "Average percent spending on flowers", "Average percent spending on jewelry", "Average percent spending on greeting cards", "Average percent spending on an evening out", "Average percent spending on clothing", "Average percent spending on gift cards" ] }, { "variable": [ "Gender", "SpendingCelebrating", "Candy", "Flowers", "Jewelry", "GreetingCards", "EveningOut", "Clothing", "GiftCards" ], "class": [ "character", "double", "double", "double", "double", "double", "double", "double", "double" ], "description": [ "Gender only including Men or Women", "Percent spending money on or celebrating Valentines Day", "Average percent spending on candy", "Average percent spending on flowers", "Average percent spending on jewelry", "Average percent spending on greeting cards", "Average percent spending on an evening out", "Average percent spending on clothing", "Average percent spending on gift cards" ] } ], "data": { "file_name": [ "gifts_age.csv", "gifts_gender.csv", "historical_spending.csv" ], "file_url": [ "https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-02-13/gifts_age.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-02-13/gifts_gender.csv", "https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-02-13/historical_spending.csv" ] } } ]