Upload Benin/datacard_Poverty_and_Inequality.md with huggingface_hub

Benin/datacard_Poverty_and_Inequality.md

@@ -0,0 +1,31 @@
+# Datacard for Benin Poverty_And_Inequality Indicators (1960-2024)
+
+This dataset contains a time-series of key poverty_and_inequality indicators for Benin, 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**: Benin
+- **Format**: Comma-Separated Values (CSV)
+
+---
+
+## Data Points (Features)
+
+The dataset includes the following poverty_and_inequality indicators, with 'Year' serving as the primary date column:
+
+1. `gini_index`: Gini index
+2. `income_share_held_by_lowest_20_`: Income share held by lowest 20%
+3. `population_living_in_slums_of_urban_population_`: Population living in slums (% of urban population)
+4. `poverty_headcount_ratio_at_3_00_a_day_2021_ppp_of_population_`: Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)
+
+---
+
+## 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 'Benin'.
+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.