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English
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Tags:
africa
humanitarian
hdx
electric-sheep-africa
anti-corruption
economic-and-corporate-governance
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| # Datacard for Morocco Governance Indicators (1960-2024) | |
| This dataset contains a time-series of key governance indicators for Morocco, 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**: Morocco | |
| - **Format**: Comma-Separated Values (CSV) | |
| --- | |
| ## Data Points (Features) | |
| The dataset includes the following governance indicators, with 'Year' serving as the primary date column: | |
| 1. `central_government_debt_total_of_gdp_`: Central government debt, total (% of GDP) | |
| 2. `military_expenditure_of_gdp_`: Military expenditure (% of GDP) | |
| 3. `statistical_performance_indicators_spi_overall_score_scale_0_100_`: Statistical performance indicators (SPI): Overall score (scale 0-100) | |
| --- | |
| ## 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 'Morocco'. | |
| 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. | |