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Botswana/datacard.md

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+# Datacard for Botswana Economic Indicators (1960-2024)
+
+This dataset contains a time-series of key economic indicators for Botswana, spanning from 1960 to 2024. The data has been aggregated from multiple sources, cleaned, and processed into a single, analysis-ready CSV file.
+
+The raw data was sourced from **The World Bank** data portal. The original files were provided in Excel (.xls) format.
+
+- **Temporal Coverage**: 1960-2024
+- **Geographic Coverage**: Botswana
+- **Format**: Comma-Separated Values (CSV)
+
+---
+
+## Data Points (Features)
+
+The dataset includes the following economic indicators, with 'Year' serving as the primary date column:
+
+1. `inflation_consumer_prices_annual_`: Inflation, consumer prices (annual %)
+2. `gdp_per_capita_current_us_`: GDP per capita (current US$)
+3. `personal_remittances_received_of_gdp_`: Personal remittances, received (% of GDP)
+4. `gdp_current_us_`: GDP (current US$)
+5. `gdp_growth_annual_`: GDP growth (annual %)
+6. `unemployment_total_of_total_labor_force_modeled_ilo_estimate_`: Unemployment, total (% of total labor force) (modeled ILO estimate)
+
+---
+
+## Data Preparation & Missing Data Handling
+
+The raw data was processed using a Python script to transform it into a clean, structured format. The key steps were:
+
+1.  **Filtering**: The data was filtered to include only records for 'Botswana'.
+2.  **Reshaping**: The original wide-format data (years as columns) was melted into a long format.
+3.  **Merging**: Data from all indicator files was merged into a single DataFrame on 'Year'.
+4.  **Handling Missing Data**: Missing values (`NaN`) were filled using a two-step strategy: linear interpolation followed by a back-fill to handle any remaining gaps at the start of the series.