Executed Data Manipulation and Visualization Tasks

• Day: 2023-05-18
• Time: 02:20 to 03:00
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Pandas, Seaborn, Git, Data Visualization

Description

Session Goal: The session aimed to perform various data manipulation and visualization tasks using Python, focusing on Git repository management, pandas DataFrame operations, and [[data visualization]] techniques.

Key Activities:

1. Configured a .gitignore file to exclude the datos folder from a Git repository, including staging and committing changes.
2. Utilized pandas to group and aggregate a DataFrame by monthly frequency using groupby and resample functions.
3. Created a date table by aggregating earliest and latest dates for each serie_id using pandas.
4. Formatted dates in a pandas DataFrame to ‘yyyy-mm’ format.
5. Developed a correlation matrix heatmap using Seaborn, with customization options for color maps and annotations.
6. Updated the heatmap code for larger cells and custom row labels.
7. Applied hierarchical clustering to time series data and visualized it with a dendrogram using scipy and seaborn.
8. Aligned time series data for hierarchical clustering to ensure accuracy.
9. Implemented Dynamic Time Warping (DTW) for comparing time series of different lengths.

Achievements: Successfully executed and documented multiple data manipulation and visualization tasks, enhancing the understanding of pandas and Seaborn for data analysis.

Pending Tasks: None identified.

Evidence

• source_file=2023-05-18.sessions.jsonl, line_number=1, event_count=0, session_id=1039499de53767b2185e270108e12cdf3073b86e65f66799d1c5b68ac081edbd
• event_ids: []