What is Python pandas any() and how does it work?

The DataFrame.any() function from the Python library pandas is used to check if at least one value along a specified axis in a DataFrame evaluates to True.

What is the syntax for pandas any()?

The basic syntax of the pandas any() function is straightforward. Here’s what it looks like:

DataFrame.any(axis=0, bool_only=None, skipna=True)

Important parameters for any()

The function accepts several parameters:

How to use pandas DataFrame.any()

Example 1: Checking for True values in rows

The any() function is most commonly used to check if any of the rows in a DataFrame contain at least one value that evaluates to True. This can come in handy when validating conditions.

import pandas as pd
# Defining a DataFrame with three columns and three rows
data = {
    'A': [0, 0, 0],
    'B': [True, False, False],
    'C': [False, False, False]
}
df = pd.DataFrame(data)
# Using the any() function to check if any values in the rows evaluate to True
result = df.any(axis=0)
print(result)

In the code above, pandas DataFrame.any() returns a series showing that only column B contains a value that evaluates to True. The output looks like this:

A    False
B    True
C    False
dtype: bool

Example 2: Checking for True values in columns

Similar to the first example, you can check if any column contains at least one True value by passing axis=1 as a parameter:

result = df.any(axis=1)
print(result)

The output shows that only the first row has a value that evaluates to True:

0     True
1    False
2    False
dtype: bool