๐Ÿ“… 2023-09-29 โ€” Session: Standardized and Merged Financial Datasets by Country

๐Ÿ•’ 11:40โ€“13:25
๐Ÿท๏ธ Labels: Data Merging, Python, Pandas, Data Aggregation, Financial Analysis
๐Ÿ“‚ 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 โ€˜countryโ€™ 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.