Debugged and Enhanced Data Visualization Pipeline

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📅 2023-11-02 — Session: Debugged and Enhanced Data Visualization Pipeline

🕒 22:45–23:00
🏷️ Labels: Python, Matplotlib, Data Visualization, Debugging, Dataframe, Resampling
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to debug and enhance a data visualization pipeline using Matplotlib in Python, focusing on custom y-axis formatting and resolving errors in data handling and plotting functions.

Key Activities

  • Implemented a custom y-axis formatter for Matplotlib to improve tick label readability by using abbreviations for thousands and millions.
  • Addressed an error in the plot_data function related to an unsupported parameter ylims, and revised the function call to correct the argument mismatch.
  • Fixed sample data generation by ensuring the inclusion of a ‘grouper’ column to match expected keys in the plot_data function.
  • Troubleshot a KeyError in data grouping by verifying the presence of required columns in the DataFrame and adjusting the data preparation process.
  • Resolved a resampling error by correctly applying the resample method to a DataFrame, ensuring the ‘Q’ column’s presence and adjusting the plotting code accordingly.

Achievements

  • Successfully implemented a custom y-axis formatter for better data visualization.
  • Corrected errors in the plotting functions, including argument mismatches and data preparation issues.
  • Applied the correct resampling method to the DataFrame, enabling accurate plotting of yearly average values.

Pending Tasks

  • Further testing of the updated plotting functions with diverse datasets to ensure robustness.
  • Optimization of the data visualization pipeline for performance improvements.

Graph View

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