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Boolean Indexing

The boolean array must be of the same length as the array axis it’s indexing. 

Selecting data from an array by boolean indexing always creates a copy of the data, even if the returned array is unchanged.

NumPy array boolean indexing

 

select from the rows where names == 'Bob' and index the columns

NumPy array boolean indexing

 

select everything but 'Bob', you can either use != or negate the condition using ~

NumPy array boolean indexing

 

select two of the three names to combine multiple boolean conditions, use boolean arithmetic operators like & (and) and | (or)

NumPy array boolean indexing

Note: The Python keywords and and or do not work with boolean arrays. Use & (and) and | (or) instead.

 

Setting values with boolean arrays works in a common-sense way. To set all of the negative values in data to 0 we need only do

NumPy array boolean indexing

 

Setting whole rows or columns using a one-dimensional boolean array is also easy

NumPy array boolean indexing

 

Reference

Python for Data Analysis Second Edition

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