Update README.md

README.md

@@ -1,3 +1,68 @@
----
-license: gpl
----
+---
+license: gpl
+language:
+- en
+tags:
+- finance
+- companies
+- stock-market
+size_categories:
+- 1K<n<10K
+---
+# Africa Listed Domestic Companies, Total Dataset
+
+## Overview
+This dataset contains listed domestic companies, total data for African countries from the World Bank.
+
+## Data Details
+- **Indicator Code**: CM.MKT.LDOM.NO
+- **Description**: Listed Domestic Companies, Total
+- **Geographic Coverage**: 17 African countries
+- **Time Period**: 1975-2024
+- **Data Points**: 400 observations
+- **Coverage**: 11.40% of possible country-year combinations
+
+## File Formats
+
+### Main Dataset (`cm_mkt_ldom_no_africa.csv`)
+- **Rows**: 54 countries
+- **Columns**: 65 years (1960-2024)
+- **Structure**: Countries as rows, years as columns
+- **Missing Value Treatment**: Interpolation → Forward Fill → Backward Fill
+- **Use Case**: Cross-sectional analysis, heatmaps, correlation analysis
+
+## Data Quality
+
+### Coverage Statistics
+- **Total Observations**: 400
+- **Coverage Rate**: 11.40%
+- **Earliest Data**: 1975
+- **Latest Data**: 2024
+
+### Countries with No Data
+37 countries have no observations:
+Angola, Burundi, Benin, Burkina Faso, Central African Republic, Cameroon, Congo, Dem. Rep., Congo, Rep., Comoros, Cabo Verde, Djibouti, Algeria, Eritrea, Ethiopia, Gabon, Guinea, Gambia, The, Guinea-Bissau, Equatorial Guinea, Liberia, Libya, Lesotho, Madagascar, Mali, Mozambique, Mauritania, Malawi, Niger, Sudan, Senegal, Sierra Leone, Somalia, South Sudan, Sao Tome and Principe, Chad, Togo, Uganda
+
+## Usage Examples
+
+### Python
+```python
+import pandas as pd
+
+# Load main dataset
+df = pd.read_csv('cm_mkt_ldom_no_africa.csv', index_col=[0, 1])
+```
+
+### R
+```r
+# Load main dataset
+df <- read.csv('cm_mkt_ldom_no_africa.csv', row.names=c(1,2))
+```
+
+## Source
+World Bank Open Data - Listed Domestic Companies, Total
+- **Original File**: API_CM.MKT.LDOM.NO_DS2_en_excel_v2_20738.xls
+- **Processed**: 2025-08-18
+
+## License
+This dataset is derived from World Bank Open Data and is available under the Creative Commons Attribution 4.0 International License.