📅 2025-07-06 — Session: Financial Data Analysis and Visualization
🕒 00:55–01:15
🏷️ Labels: Data_Analysis, Financial_Data, Python, Pandas, Visualization
📂 Project: Accounting
⭐ Priority: MEDIUM
Session Goal
The primary aim of this session was to perform a comprehensive analysis of financial data files, focusing on data cleaning, aggregation, and visualization.
Key Activities
- Conducted a diagnostic overview of financial data files to assess their status and determine next steps for analysis.
- Developed a Python script to analyze monthly inflow and outflow per currency from ledger files.
- Addressed issues with non-datetime columns in Pandas, ensuring proper data types for further processing.
- Managed timezone-aware datetimes in CSV files, converting them to naive datetimes for compatibility.
- Implemented robust date handling in Pandas DataFrames to prevent errors during date parsing.
- Solved mixed timezone offsets in Pandas
posted_date
columns by converting timestamps to UTC. - Visualized financial flows using bar charts in Python, leveraging Matplotlib for data pivoting and plotting.
Achievements
- Successfully cleaned and processed financial data for accurate analysis.
- Developed visualizations to represent financial inflows and outflows effectively.
Pending Tasks
- Further refinement of visualization techniques to enhance clarity and insights.
- Exploration of additional data sources for more comprehensive analysis.