# Pandas Series any() Method

In this tutorial, we will learn the Python pandas `Series.any()` method. This method can be used to check whether the elements in the Series are `True` or `False`. This method returns the True at least one element in the Series is True otherwise it returns False.

Below is the syntax of the `Series.any()` method.

### Syntax

``Series.any(axis=0, bool_only=None, skipna=True, level=None, **kwargs)``

## Example: Pandas `Series.any()` Method

Let's create a Series and check the elements using the `Series.any()` method. In this example, we created three series with different elements, for the Series `s_1` and `s_2 `the `Series.any()` method returns `True` because both the Series contains at least one element as `'True'` and for the Series `s_3`, it returns `False` as it contains `'False'` as all elements. See the below example.

``````#importing pandas as pd
import pandas as pd
#creating Series
s_1=pd.Series([True,True])
s_2=pd.Series([False,False])
s_3=pd.Series([True,False])
print(s_1.any())
print(s_2.any())
print(s_3.any())``````

True
False
True

## Example 2: Pandas `Series.any()` Method

Here, in this example, we are checking the Series that consists of `null values`, `'0'` and `'1'` as elements and also with the `empty Series`. For the Series s_1 and s_3, the `Series.any()` method returns True fas these Series consist one element as True and '1' respectively and for `empty Series `and for number `'0'` it returns False. See the below example.

``````#importing pandas as pd
import pandas as pd
import numpy as np
#creating Series
s_1=pd.Series([True,np.NaN,np.NaN])
s_2=pd.Series([])
s_3=pd.Series()
s_4=pd.Series()
print(s_1.any(skipna=False))
print(s_2.any())
print(s_3.any())
print(s_4.any())``````

True
False
True
False

## Example 3: Pandas `Series.any()` Method

Here, in this example, we will check the two Series. The `Series.any()` method returns `True` only if the given condition matches otherwise it returns `False`. See the below example.

``````#importing pandas as pd
import pandas as pd
#creating Series
s_1=pd.Series([1,2,7])
s_2=pd.Series([4,5,6])
s_3=pd.Series([7,8,9])
print(any(s_1>s_2))
print(any(s_2>s_3))``````

True
False

### Conclusion

In this tutorial, we learned how to use the `Series.any()` method of the python pandas.