python pandas stack unstack
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Pandas is a powerful data manipulation library in Python, and it provides various tools to reshape and transform datasets. Two essential functions for reshaping dataframes are stack and unstack. These functions help you pivot or unpivot your data, making it more convenient for analysis. In this tutorial, we will explore the stack and unstack functions with code examples.
Let's start by creating a sample dataframe:
In this example, we set the 'Date' and 'City' columns as the index, and then use the stack function to pivot the columns 'Temperature' and 'Humidity' into a new level of the index.
In this example, we use the unstack function to revert the changes made by stack. The columns 'Temperature' and 'Humidity' are moved back as regular columns.
In this example, we use the stack function with the parameter level='City' to stack only the 'City' column, resulting in a more specific level of the index.
Here, we use the unstack function with level='City' to unstack the specified level back to columns.
These examples showcase the basic usage of stack and unstack functions in Pandas. These functions are valuable tools for reshaping dataframes, especially when dealing with multi-level indexes.
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