Advanced pandas—Going Beyond the Basics/

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Advanced Indexing 2

Advanced Indexing 2

Learn how to use advanced indexing techniques to work effectively with MultiIndex DataFrames.

We'll cover the following...

Overview

Having seen how to sort and select data from MultiIndex DataFrames, we now explore how the indexes can be modified.

The swaplevel() and reorder_levels

There may be occasions when we want to modify the order of the indexes. We can utilize the swaplevel() method to flip the order of two levels. We can pass either the level number or label name into the swaplevel() method, because both are accepted and will give the same output.

Let's see how we can perform the level swapping either by level number (i.e., index position) with the following example:

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# Original DataFrame

print('===== Original DataFrame =====')

print(df)



# Swap level with level numbers (index positions)

df_swapped = df.swaplevel(0, 1)



print('===== Swapped DataFrame by Level Numbers =====')

print(df_swapped)

With the code above, we've flipped the position of fruit_name and store_name in the row index— fruit_name index has been changed to become the leftmost index. Besides level number, we can also swap indexes by name, as shown below:

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# Original DataFrame

print('===== Original DataFrame =====')

print(df)



# Swap level with level name

df_swapped = df.swaplevel('fruit_name', 'store_name')



print('===== Swapped DataFrame by Level Name =====')

print(df_swapped)

If we want to specify the order for the indexes explicitly, the reorder_levels() is the method we should use. This method is particularly useful when dealing with more than ...