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# Pandas Series apply() Method

We can apply the numpy method or the python method to the entire Series and to the elements of Series respectively using the Python pandas `Series.apply() `method. This method applies the passed method to the values of the Series.

The below is the syntax of the `Series.apply() `method.

### Syntax

``Series.apply(func, convert_dtype=True, args=(), **kwds)``

### Parameters

func: It is the method that is the Python method or NumPy ufunc to apply.

convert_dtype: It represents the bool(True or False), and the default value is True.

args: It represents the tuple. It is the positional arguments passed to func after the series value.

**kwds: It is the additional keyword arguments passed to func.

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

Let's apply the `np.pi `method to the values of the Series. Here, in this example, we have passed the lambda method along with the numpy `np.pi `method, which multiplies the Series values with the pi value. See the below example.

``````#importing pandas as pd
import pandas as pd
#importing numpy as np
import numpy as np
#creating Series
s = pd.Series([1,2,3])
print(s.apply(lambda x: x*np.pi))``````

0 3.141593
1 6.283185
2 9.424778
dtype: float64

## Example : Applying lower() function to the `Series.apply() `Method

Here, in this example, we apply the python lower() method to the Series. The Series`.apply()` method returns a Series by converting the elements of the Series to a lower case. See the below example.

``````#importing pandas as pd
import pandas as pd
#creating Series
s = pd.Series(['PYTHON','JAVA'])
print(s.apply(lambda x: x.lower()))``````

0 python
1 java
dtype: object

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

Here, in this example, we apply a lambda method along with the condition. If the condition satisfies, it returns True otherwise it returns False. See the below example.

``````#importing pandas as pd
import pandas as pd
#importing numpy as np
import numpy as np
#creating Series
s = pd.Series([2,1,8,4])
print(s.apply(lambda x: x >= 2 and x <=5))``````

0 True
1 False
2 False
3 True
dtype: bool

### Conclusion

In this tutorial, we understand the `Series.apply()` method of the data frame. We learned the syntax and parameters of `Series.apply()` method and created different examples to better understand this topic.

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