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+ # Datacard for Namibia Finance_Competitiveness_And_Innovation Indicators (1960-2024)
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+ This dataset contains a time-series of key finance_competitiveness_and_innovation indicators for Namibia, spanning from 1960 to 2024. The data has been aggregated from multiple sources, cleaned, and processed into a single, analysis-ready CSV file.
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+ The raw data was sourced from **The World Bank** data portal. The original files were provided in Excel (.xls) format.
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+ - **Temporal Coverage**: 1960-2024
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+ - **Geographic Coverage**: Namibia
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+ - **Format**: Comma-Separated Values (CSV)
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+ ---
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+ ## Data Points (Features)
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+ The dataset includes the following finance_competitiveness_and_innovation indicators, with 'Year' serving as the primary date column:
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+ 1. `firms_using_banks_to_finance_investment_of_firms_`: Firms using banks to finance investment (% of firms)
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+ 2. `high_technology_exports_of_manufactured_exports_`: High-technology exports (% of manufactured exports)
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+ 3. `logistics_performance_index_ease_of_arranging_competitively_priced_shipments_1_low_to_5_high_`: Logistics performance index: Ease of arranging competitively priced shipments (1=low to 5=high)
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+ 4. `stocks_traded_total_value_of_gdp_`: Stocks traded, total value (% of GDP)
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+ ---
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+ ## Data Preparation & Missing Data Handling
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+ The raw data was processed using a Python script to transform it into a clean, structured format. The key steps were:
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+ 1. **Filtering**: The data was filtered to include only records for 'Namibia'.
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+ 2. **Reshaping**: The original wide-format data (years as columns) was melted into a long format.
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+ 3. **Merging**: Data from all indicator files was merged into a single DataFrame on 'Year'.
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+ 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.