๐ 2023-09-29 โ Session: Standardized and Merged Financial Datasets by Country
๐ 11:40โ13:25
๐ท๏ธ Labels: Data Merging, Python, Pandas, Data Aggregation, Financial Analysis
๐ Project: Dev
โญ Priority: MEDIUM
Session Goal: The primary goal of this session was to standardize country names across multiple datasets and perform data aggregation and merging by country and year. This was aimed at creating a unified dataset for financial analysis.
Key Activities:
- Implemented Python code snippets to merge datasets using pandas, focusing on unifying the โcountryโ column.
- Developed a function to aggregate data by counting records for each group and summing financial columns.
- Standardized country names before merging to ensure consistency across datasets.
- Merged datasets by country and year, handling column name conflicts and summing total monetary values.
- Saved the processed and aggregated data into CSV files for further analysis.
Achievements:
- Successfully standardized country names and merged multiple datasets, resulting in a comprehensive dataset ready for financial analysis.
- Aggregated data by specified categories and years, ensuring data integrity and consistency.
Pending Tasks:
- Further debugging and validation of the merged dataset to ensure accuracy.
- Explore additional data sources for potential inclusion in the dataset.