Enhanced Jupyter Notebook Function Import and DataFrame Handling

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📅 2023-03-27 — Session: Enhanced Jupyter Notebook Function Import and DataFrame Handling

🕒 06:45–07:10
🏷️ Labels: Jupyter, Python, Pandas, Dataframe, Function Import
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance the process of importing functions across Jupyter notebooks and improve DataFrame handling in Python using Pandas.

Key Activities

  • Explored methods for importing functions defined in one Jupyter notebook into another, including setting the PYTHONPATH environment variable.
  • Provided a step-by-step guide for using the aggregate_csv function from the data_process.py module.
  • Addressed a DataFrame column not found error by suggesting checks for typos and proper loading.
  • Demonstrated efficient data manipulation techniques in Pandas, such as converting ‘date’ and ‘datetime’ columns to datetime objects and creating a new ‘year’ column.

Achievements

  • Successfully set up the environment for function imports in Jupyter notebooks.
  • Clarified the process of handling datetime columns in Pandas, optimizing DataFrame manipulation.

Pending Tasks

  • Further exploration of error handling techniques for DataFrame operations to prevent common issues like missing columns.

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