Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas
Series.argmin() function returns the row label of the minimum value in the given series object.
Syntax: Series.argmin(axis=0, skipna=True, *args, **kwargs)
Parameter :
skipna : Exclude NA/null values. If the entire Series is NA, the result will be NA.
axis : For compatibility with DataFrame.idxmin. Redundant for application on Series.
*args, **kwargs : Additional keywords have no effect but might be accepted for compatibility with NumPy.
Returns : idxmin : Index of minimum of values.
Example #1: Use
Series.argmin() function to return the row label of the minimum value in the given series object
Output :
Coca Cola 34
Sprite 5
Coke 13
Fanta 32
Dew 4
ThumbsUp 15
dtype: int64
Now we will use
Series.argmin() function to return the row label of the minimum value in the given series object.
Output :
Dew
As we can see in the output, the
Series.argmin() function has successfully returned the row label of the minimum value in the given series object.
Example #2 : Use
Series.argmin() function to return the row label of the minimum value in the given series object.
Output :
2010-12-31 08:45:00 11.0
2011-12-31 08:45:00 21.0
2012-12-31 08:45:00 8.0
2013-12-31 08:45:00 18.0
2014-12-31 08:45:00 65.0
2015-12-31 08:45:00 18.0
2016-12-31 08:45:00 32.0
2017-12-31 08:45:00 10.0
2018-12-31 08:45:00 5.0
2019-12-31 08:45:00 32.0
2020-12-31 08:45:00 NaN
Freq: A-DEC, dtype: float64
Now we will use
Series.argmin() function to return the row label of the minimum value in the given series object.
Output :
2018-12-31 08:45:00
As we can see in the output, the
Series.argmin() function has successfully returned the row label of the minimum value in the given series object.
