Developed methods for handling and merging datasets

• Day: 2023-09-28
• Time: 18:10 to 19:10
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Processing, Merging Datasets, Pandas, CSV

Description

Session Goal:

The session aimed to explore and implement methods for handling Stata data files (.dta) and merging datasets using Python and R.

Key Activities:

• Discussed various methods to open and process .dta files using Stata, Python (pandas), and R (haven package).
• Provided code snippets and instructions for merging datasets in Python, focusing on analyzing discrepancies in country names.
• Developed a Python script to fix duplicated country names in DataFrames by splitting and retaining only the first part of the names.
• Outlined a Python script for merging multiple DataFrames, summing money columns, and displaying results with merge indicators.
• Created a CSV file with unique country names from datasets for manual matching, facilitating future data processing tasks.

Achievements:

• Successfully outlined methods to handle .dta files and merge datasets using Python and R.
• Developed scripts for data cleaning and merging, enhancing data processing capabilities.

Pending Tasks:

• Further manual matching of country names using the generated CSV file to ensure data consistency in future analyses.

Evidence

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• event_ids: []