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Pandas is a powerful data manipulation library for Python, and it provides various functions to manipulate and analyze tabular data structures, such as DataFrames. Sorting a DataFrame based on specific columns is a common operation, but sometimes you may want to sort it based on a custom order defined by a list. In this tutorial, we'll explore how to sort a Pandas DataFrame by values in a specific column using a custom order defined by a list.
Make sure you have Python and Pandas installed on your system. You can install Pandas using the following command if you haven't already:
Let's consider a scenario where you have a DataFrame containing information about fruits, and you want to sort the DataFrame based on the "fruit" column using a custom order specified by a list.
Now, let's say we want to sort the DataFrame by the "fruit" column based on a custom order defined by a list. Here's how you can achieve this:
In this example, we use the set_index method to set the "fruit" column as the index. Then, we use the loc accessor with the custom order list to rearrange the DataFrame based on the specified order. Finally, we use reset_index to bring the original index back.
Sorting a Pandas DataFrame by values in a specific column using a custom order defined by a list is a straightforward process. By leveraging the set_index, loc, and reset_index methods, you can easily achieve the desired sorting based on your custom order. This can be particularly useful in scenarios where the default sorting order is not sufficient, and you need a specific arrangement of rows in your DataFrame.
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