Upload Angola/datacard_Jobs-and-Development.md with huggingface_hub

Angola/datacard_Jobs-and-Development.md

@@ -0,0 +1,30 @@
+# Datacard for Angola Jobs And Development Indicators (1960-2024)
+
+This dataset contains a time-series of key jobs and development indicators for Angola, 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**: Angola
+- **Format**: Comma-Separated Values (CSV)
+
+---
+
+## Data Points (Features)
+
+The dataset includes the following jobs and development indicators, with 'Year' serving as the primary date column:
+
+1. `employment_to_population_ratio_15_total_modeled_ilo_estimate_`: Employment to population ratio, 15+, total (%) (modeled ILO estimate)
+2. `gdp_per_person_employed_constant_2021_ppp_`: GDP per person employed (constant 2021 PPP $)
+3. `labor_force_participation_rate_total_of_total_population_ages_15_modeled_ilo_estimate_`: Labor force participation rate, total (% of total population ages 15+) (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 'Angola'.
+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.