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boolean indexing

What is boolean indexing?

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Boolean indexing

Boolean indexing is used to filter data through the use of boolean vectors. Boolean vectors are created at the backend with respect to the given condition and all the values against the "true" value are then returned.

Define an Array
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Note: It is necessary to use symbols instead of words while working with boolean indexing. We can use &, |, and ~ in place of AND, OR, and NOT.


# import pandas
import pandas as pd
# initialize panda series
ser1 = pd.Series([1,2,3,4,5,6])
#boolean indexing 
print("Orignal Series")
print("Example 1: Greater than 2")
print(ser1[ser1 > 2])
print("Example 2: Greater then 5 and less than 2")
print(ser1[(ser1 < 5) & (ser1 > 2)])
print("Example 3: Not less than 4")
print(ser1[~(ser1 < 4)])
Example of boolean indexing

The code given above is an example of boolean indexing in Python, where an array is divided into a sub-array depending on a certain condition.

In the first example, numbers that are greater than 2 are extracted from the series. In the second example, the AND operator is used to extract values that are greater than 2 and less than 5. Similarly, in the third example, the NOT operator is used to get the values that are equal to or greater than 4.


boolean indexing
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