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Effective Data Manipulation with pandas

Filtering and Indexing Operations

Explore techniques for filtering and indexing in pandas DataFrames. Understand how to rename and reset indexes, apply boolean arrays for conditional filtering, and use the query method for flexible data selection.

We'll cover the following...

Renaming an index

In this example, we’ll use the rename method to update the index values. This method accepts a function that takes the current value and returns a new value. Here we’ll use the initial of the president’s first name:

Python 3.8
def name_to_initial(val):
    names = val.split()
    return ' '.join([f'{names[0][0]}.', *names[1:]])
print(pres
 .set_index('President')
 .rename(name_to_initial)
)

Resetting the index

If we want a monotonically increasing integer index for a DataFrame, we’ll use the reset_index method:

Python 3.8
print(pres
 .set_index('President')
 .reset_index()
)

DataFrame indexing, filtering, and

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