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Population and GDP/GNI/CO2 emissions (2019, raw data)
- figshare.com
txtUpdated Feb 23, 2023
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EmailClick to copy linkLink copiedCiteLiang Zhao (2023). Population and GDP/GNI/CO2 emissions (2019, raw data) [Dataset]. http://doi.org/10.6084/m9.figshare.22085060.v6txtAvailable download formatsUnique identifierhttps://doi.org/10.6084/m9.figshare.22085060.v6Dataset updatedFeb 23, 2023Dataset provided byfigshareAuthorsLiang ZhaoLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionOriginal dataset The original year-2019 dataset was downloaded from the World Bank Databank by the following approach on July 23, 2022.
Database: "World Development Indicators" Country: 266 (all available) Series: "CO2 emissions (kt)", "GDP (current US$)", "GNI, Atlas method (current US$)", and "Population, total" Time: 1960, 1970, 1980, 1990, 2000, 2010, 2017, 2018, 2019, 2020, 2021 Layout: Custom -> Time: Column, Country: Row, Series: Column Download options: Excel
Preprocessing
With libreoffice,
remove non-country entries (lines after Zimbabwe), shorten column names for easy processing: Country Name -> Country, Country Code -> Code, "XXXX ... GNI ..." -> GNI_1990, etc (notice '_', not '-', for R), remove unnesssary rows after line Zimbabwe.
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FacebookTwitterEmailAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Original dataset The original year-2019 dataset was downloaded from the World Bank Databank by the following approach on July 23, 2022.
Database: "World Development Indicators" Country: 266 (all available) Series: "CO2 emissions (kt)", "GDP (current US$)", "GNI, Atlas method (current US$)", and "Population, total" Time: 1960, 1970, 1980, 1990, 2000, 2010, 2017, 2018, 2019, 2020, 2021 Layout: Custom -> Time: Column, Country: Row, Series: Column Download options: Excel
Preprocessing
With libreoffice,
remove non-country entries (lines after Zimbabwe), shorten column names for easy processing: Country Name -> Country, Country Code -> Code, "XXXX ... GNI ..." -> GNI_1990, etc (notice '_', not '-', for R), remove unnesssary rows after line Zimbabwe.