Effective Data Manipulation with pandas/

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Similarities in pandas and NumPy

Similarities in pandas and NumPy

Learn about the similarities between pandas and NumPy.

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Similar to NumPy

The Series object behaves similarly to a NumPy array. As shown below, both types respond to index operations:

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import numpy as np
import pandas as pd
songs3 = pd.Series([145, 142, 38, 13], name='counts', index=['Paul', 'John', 'George', 'Ringo'])
numpy_ser = np.array([145, 142, 38, 13])
print(songs3[1])
print(numpy_ser[1])

They both have these methods in common:

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print(songs3.mean())
print(numpy_ser.mean())

They also both have a notion of a boolean array. A boolean array is a Series with the same index as the Series we’re working with and has boolean values. It can be used as a mask to filter out items. Normal Python lists ...