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# Pandas Series all() Method

In this tutorial, we will learn the Python pandas `Series.all()` method. This method can be used to check whether the elements in the Series are `True` or `False`. This method returns the True only if all the elements are True otherwise it returns False.

The below shows the syntax of the `Series.all()` method.

### Syntax

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

## Example: Pandas `Series.all()` method

Let's create a Series and check the elements using the `Series.all()` method. In this example, we created three series with different elements, as you can see for the first series only we got True and for the remaining series, we got False. Because `Series.all()` method returns False if the Series contains at least one element as False. 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.all())
print(s_2.all())
print(s_3.all())``````

True
False
False

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

In this example, we are checking the Series that consists of `null values`, `'0'` and `'1'` as elements and also with the `empty Series`. The `Series.all()` method returns `False` for the `null values `and for number `'0'`. 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.all(skipna=False))
print(s_2.all())
print(s_3.all())
print(s_4.all())``````

nan
True
True
False

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

Here, in this example, we will check the two Series. The `Series.all()` 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([1,2,3])
s_2=pd.Series([4,5,6])
print(all(s_1>s_2))
print(all(s_1<s_2))``````

False
True

### Conclusion

In this tutorial, we learned how to the `Series.all()` method of the python pandas. We solved examples by applying this method on DataFrame.

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