Pandas Series: idxmin() function

Row label of the minimum value in Pandas series

The idxmin() function is used to get the row label of the minimum value.

If multiple values equal the minimum, the first row label with that value is returned.

Syntax:

Series.idxmin(self, axis=0, skipna=True, *args, **kwargs)

Parameters:

Returns: Index
Label of the minimum value.

Raises: ValueError
If the Series is empty.

Notes: This method is the Series version of ndarray.argmin. This method returns the label of the minimum, while ndarray.argmin returns the position. To get the position, use series.values.argmin().

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(data=[2, None, 5, 2],
              index=['P', 'Q', 'R', 'S'])
s

Output:

P    2.0
Q    NaN
R    5.0
S    2.0
dtype: float64

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(data=[2, None, 5, 2],
              index=['P', 'Q', 'R', 'S'])
s.idxmin()

Output:

'P'

Example - If skipna is False and there is an NA value in the data, the function returns nan:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(data=[2, None, 5, 2],
              index=['P', 'Q', 'R', 'S'])
s.idxmin(skipna=False)

Output:

nan

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