Скачать или смотреть How to Effectively Use a Library Inside a Python Function in Jupyter Notebook

Discover how to solve the common issue of undefined libraries when importing Python files into Jupyter Notebooks. Learn how to properly use `pandas` within functions!
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This video is based on the question https://stackoverflow.com/q/64322762/ asked by the user 'Adnan Hadi' ( https://stackoverflow.com/u/14034459/ ) and on the answer https://stackoverflow.com/a/64322825/ provided by the user 'Jesper' ( https://stackoverflow.com/u/1629102/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Effectively Use a Library Inside a Python Function in Jupyter Notebook

When working with Jupyter Notebooks, many users encounter frustrating errors due to undefined libraries. One common scenario involves importing a Python file that utilizes libraries like pandas. This guide aims to help you overcome the issue of seeing the "pd is not defined" error when using imported functions that rely on such libraries.

The Problem

You may find yourself using a Python script (such as EDA.py) that leverages the powerful pandas library to perform exploratory data analysis (EDA) on your data frames. However, when you attempt to run the function from your Jupyter Notebook, you receive an error indicating that pd (the common alias for pandas) is not defined. Here’s a recap of the scenario:

Example Python File: EDA.py

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Example Jupyter Notebook Code

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Error Output

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The Solution

The error you're experiencing occurs because the import statement for pandas inside the function eda_df does not make pd accessible in your Jupyter Notebook scope. To resolve this, there are a few simple steps you can take.

Step 1: Import pandas Globally

The most straightforward solution is to import pandas at the beginning of your Jupyter Notebook, so it's available for the entire session. Here's how you can do that:

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Step 2: Modify Your Function

Another approach is to modify the EDA.py file directly to make pandas globally available within the function by changing how it's imported. Here is the revised function:

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Use the Function Correctly

After modifying your function (or importing pandas at the start of your notebook), you can effectively call eda_df without running into the NameError. This ensures that any time your function calls for pd, it will correctly recognize the import.

Best Practices for Using Libraries in Functions

Global Imports: Consider importing libraries you frequently use at the beginning of your scripts or notebooks to avoid scope issues.

Function Documentation: Comment your functions to inform users of internal dependencies, such as required libraries.

Testing: Always test functions independently to ensure they work correctly, especially in isolated environments like Jupyter.

Conclusion

By understanding the scope of library imports in Python functions, particularly when using Jupyter Notebooks, you can troubleshoot issues more effectively. Whether you choose to import libraries globally or structure your function to handle imports neatly, the goal is to prevent the dreaded "pd is not defined" error. Now you can focus more on your data analysis without the hassle of import-related errors!

Feel free to reach out if you have additional questions or need further clarification. Happy coding!