Enhanced Data Processing and Visualization with Python

2 min read

📅 2023-07-30 — Session: Enhanced Data Processing and Visualization with Python

🕒 17:55–18:35
🏷️ Labels: Python, Pandas, Seaborn, Data Processing, Data Visualization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance data processing and visualization capabilities using Python libraries, specifically Seaborn and Pandas.

Key Activities

  • Color Palette Generation: Utilized Seaborn’s color_palette() function to interpolate and generate a color palette based on three given colors. This involved executing practical code examples to demonstrate the functionality.
  • CSV to Dictionary Conversion: Demonstrated how to read a CSV file using Pandas and convert a specific column from hexadecimal format to an RGB tuple in a dictionary format.
  • Quantile Calculation: Provided code snippets for calculating the 0.1 and 0.9 quantiles of a DataFrame using Pandas’ quantile method and .agg() method.
  • Conditional Value Modification: Showcased Python code for modifying a dictionary value conditionally, based on data read from a CSV file.

Achievements

  • Successfully generated color palettes using Seaborn, enhancing visualization techniques.
  • Converted CSV data to dictionary format, facilitating easier data manipulation.
  • Calculated multiple quantiles in a DataFrame, providing insights into data distribution.
  • Implemented conditional logic to modify dictionary values based on CSV data.

Pending Tasks

  • Further exploration of advanced data visualization techniques using Seaborn.
  • Optimization of data processing workflows in Pandas for larger datasets.

Graph View

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