Python Pandas DataFrame If Index Contains Any String Values Apply Label Else Apply Different Label

Опубликовано: 29 Декабрь 2024
на канале: CodeFlare

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Pandas is a powerful data manipulation library for Python, and one of its key data structures is the DataFrame. DataFrames are two-dimensional, tabular data structures with labeled axes (rows and columns). In some cases, you might have string values in the index of your DataFrame and want to apply different labels based on whether the index contains strings or not. This tutorial will guide you through the process of handling such scenarios using Python and Pandas.
Make sure you have Python and Pandas installed. You can install Pandas using the following command:
Let's assume you have a DataFrame with a mixed-type index (containing both string and non-string values), and you want to apply different labels based on the type of values in the index.
We create a sample DataFrame (df) with a mixed-type index ([1, 'two', 3, 'four']).
The label_index function is defined to apply labels based on the type of index value. If the index value is a string, it returns 'String Label'; otherwise, it returns 'Non-String Label'.
The map function is used to apply the label_index function to each index value in the DataFrame, and the result is stored in a new column called 'label'.
The final DataFrame is displayed, showing the original data along with the newly added 'label' column.
Handling mixed-type indexes in Pandas DataFrames can be achieved by creating a custom function to apply labels based on the type of index values. This tutorial provides a simple example to get you started, and you can adapt the approach based on your specific use case.
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