📅 2023-05-18 — Session: Implemented Gitignore and Data Analysis Techniques
🕒 02:20–03:00
🏷️ Labels: Git, Pandas, Data Visualization, Clustering, Python
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance repository management by excluding unnecessary folders using .gitignore
and to perform advanced data analysis and visualization using Python libraries.
Key Activities
- Configured a
.gitignore
file to exclude thedatos
folder from the Git repository, including staging and committing the changes. - Demonstrated data manipulation using pandas, including grouping and aggregating data by monthly frequency and creating a date table from grouped data.
- Formatted dates in a DataFrame to ‘yyyy-mm’ format for better readability.
- Created and customized a correlation matrix heatmap using Seaborn and Matplotlib, with a focus on visual clarity and customization.
- Applied hierarchical clustering to time series data, visualizing it with a dendrogram using Seaborn.
- Utilized Dynamic Time Warping (DTW) for comparing time series of different lengths, enhancing clustering analysis.
Achievements
- Successfully excluded a folder from the Git repository using
.gitignore
. - Completed data aggregation and visualization tasks, including the creation of a correlation matrix heatmap and hierarchical clustering dendrogram.
Pending Tasks
- Further exploration of advanced clustering techniques and optimization of data visualization parameters may be required for future sessions.