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Pandas Series argmax() Method

In this tutorial, we will learn the python pandas `Series.argmax() `method. This function returns the integer value which indicates the position where the largest value exists.

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

Syntax

``Series.argmax(axis=None, skipna=True, *args, **kwargs)``

Parameters

axis: It is None. It is the dummy argument for consistency with Series.

skipna: It is the bool(True or False), and the default value is True. It excludes all null values when showing the result.

*args, **kwargs: It is the additional arguments and keywords for compatibility with NumPy.

Example: Get the Position of max Value using the `Series.argmax() `Method

Let's apply the `Series.argmax() `method to the two Series and get the position of the larger value. See the below example.

Here, in Series `s_1`, there are different values and in `s_2`, it consists of repeated values. The `Series.argmax() `method returns a position and if the larger value present in a different location, it returns the position of the first row.

``````#importing pandas as pd
import pandas as pd
#creating Series
s_1= pd.Series([12,45,78,22])
s_2= pd.Series([11,45,14,45])
print("In Series s_1 the maximum value is in position:",s_1.argmax())
print("In Series s_2 the maximum value is in position:",s_2.argmax())``````

In Series s_1 the maximum value is in position: 2
In Series s_2 the maximum value is in position: 1

Example: Get thePosition of a mx value consists of null values

Here, in this example, the Series elements consist of null values, and by default the `Series.argmax() `method `ignores` the null values and returns the position of the larger value just by considering the integer elements. 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([np.nan,12,100,np.nan])
print("The maximum value is in position:",s.argmax())``````

The maximum value is in position: 2

Conclusion

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

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