Global GDP & Population Dataset(2023)- Ready To Go
A well-structured dataset combining GDP and population data for insights.
@kaggle.rizwanbinakbar_global_gdp_and_population_dataset2023_r_2b095660
A well-structured dataset combining GDP and population data for insights.
@kaggle.rizwanbinakbar_global_gdp_and_population_dataset2023_r_2b095660
This dataset merges global GDP and population data for 2023 into a structured and analysis-ready format. The raw data originally contained inconsistencies like currency symbols, commas, and percentage signs, which have been carefully cleaned and formatted.
🛠Data Cleaning Steps:
Merged GDP and Population data using the country name as the key.
Removed unnecessary characters (e.g., $, %, , from numeric columns).
Converted GDP figures from text (trillion/billion format) into absolute values.
Handled missing values to maintain data consistency.
Rearranged column order for better readability.
📂 Columns in the Dataset:
Country – Name of the country.
Population – Total population in 2023.
Area – Total land area (sq km).
Languages – Official languages spoken.
Currencies – National currencies used.
Region & Sub-region – Geographical classification.
Capital – Country's capital city.
GDP (2023) – Total nominal GDP in USD.
GDP per Capita – GDP divided by population.
GDP Growth – Percentage increase/decrease in GDP.
Share of World GDP – Country's contribution to global GDP.
💡 Why Use This Dataset?
This dataset is perfect for data visualization, economic analysis, and machine learning models. You can:
✅ Compare GDP & population across different regions.
✅ Analyze economic growth trends.
✅ Create stunning visualizations (bar charts, pie charts, choropleth maps).
✅ Build predictive models on economic indicators.
🔗 Credits & Source:
The original GDP and population data were collected from [reliable global sources] (add the actual sources here).
Cleaning and transformation were done using Python (Pandas, NumPy, Matplotlib/Seaborn for visual checks).
CREATE TABLE gdp_population_cleaned (
"country" VARCHAR,
"population" BIGINT,
"capital" VARCHAR,
"gdp_per_capita" DOUBLE,
"share_of_world_gdp" DOUBLE,
"gdp_growth" DOUBLE,
"gdp_2023" DOUBLE,
"area" DOUBLE,
"languages" VARCHAR,
"currencies" VARCHAR,
"region" VARCHAR,
"sub_region" VARCHAR
);
CREATE TABLE gdp_population_cleaned_noissue (
"country" VARCHAR,
"population" BIGINT,
"capital" VARCHAR,
"gdp_per_capita" BIGINT,
"share_of_world_gdp" DOUBLE,
"gdp_growth" DOUBLE,
"gdp_2023" DOUBLE,
"area" BIGINT,
"languages" VARCHAR,
"currencies" VARCHAR,
"region" VARCHAR,
"sub_region" VARCHAR
);
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