Processed Financial Data with Pandas for Monthly Analysis

• Day: 2025-07-06
• Time: 00:55 to 01:10
• Project: Accounting
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Data_Processing, Financial_Analysis, Pandas, CSV, Datetime

Description

Session Goal

The goal of this session was to process and analyze multiple financial data files to generate a unified DataFrame for aggregation and analysis.

Key Activities

• Conducted a diagnostic overview of financial data files, assessing their status and contents.
• Implemented scripts using Pandas to process CSV files, compute monthly inflows and outflows, and group results by month, currency, and flow direction.
• Addressed data cleaning and transformation steps, including handling non-datetime columns and timezone-aware datetimes in DataFrames.
• Developed a robust solution for mixed-type date columns to ensure accurate data parsing and prevent errors.

Achievements

• Successfully processed financial data files into a unified DataFrame, ready for further analysis.
• Enhanced data integrity by resolving datetime handling issues and ensuring accurate reporting.

Pending Tasks

• Further analysis and visualization of the processed financial data to derive insights.
• Integration of the processed data into a larger financial reporting system.

Evidence

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• event_ids: []