Enhanced DataFrame manipulation and visualization techniques

📅 2023-03-22 — Session: Enhanced DataFrame manipulation and visualization techniques

🕒 20:30–21:10
🏷️ Labels: Python, Pandas, Data Visualization, Dataframe, Data Analysis
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The objective of this session was to enhance skills in DataFrame manipulation and visualization using Python’s pandas and matplotlib libraries.

Key Activities

• Created a DataFrame to track the presence of columns across multiple DataFrames using boolean values.
• Styled DataFrame cells based on boolean values, replacing them with ‘Y’ and ‘N’.
• Concatenated multiple DataFrames and visualized unique value counts using grouped bar charts.
• Modified code to add an identifier for the originating dataset during concatenation and visualized data using grouped bar charts.
• Generated grouped bar charts with thin bars for better visual clarity.
• Used the transform() method for normalized counts in data visualization.
• Preprocessed DataFrames by replacing ‘#NULL!’ with NaN and converting columns to numerical data.

Achievements

• Successfully implemented various techniques for DataFrame manipulation and visualization.
• Improved understanding of pandas for data manipulation and matplotlib for visualization.

Pending Tasks

• Further exploration of advanced visualization techniques for large datasets.
• Optimization of DataFrame processing for performance improvements.