Python Pandas Series cummin() Function

Pandas Series cummin() Function:

Cumulative minimum is computed over a DataFrame or Series axis by the Pandas Series cummin() function, which returns a DataFrame or Series of the same size including the cumulative minimum.

Syntax:

Series.cummin(axis=None, skipna=True)

Parameters

axis: This is optional. It indicates 0 or “index”, 1 or “columns.” Cumulative minimums are generated for each column if the value is 0 or ‘index’. Cumulative minimums are generated for each row if 1 or ‘columns’ is selected. 0 is the default.

skipna: This is optional. When determining the result, specify True to exclude NA/null values. True is the default value.

Return Value:

The cumulative minimum of scalar or a Series is returned by the cummin() function.

Pandas Series cummin() Function in Python

Example1

Here, the cummin() function returns the cumulative minimum of values in a given series.

Approach:

Import pandas module using the import keyword.
Pass some random list as an argument to the Series() function of the pandas module to create a series.
Store it in a variable.
Print the above-given series.
Apply cummax() function on the given series to get the cumulative minimum values of all the elements of the given series and print the result.
The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Pass some random list as an argument to the Series() function
# of the pandas module to create a series.
# Store it in a variable.
gvn_series = pd.Series([12, 40, 10, 5, 15, 40, 12, 12])
# Print the above given series
print("The given series is:")
print(gvn_series)
print()
# Apply cummin() function on the given series to get the 
# cumulative minimum of values of all the elements of the given series
# and print the result.
print("The cumulative minimum of values of all the elements of the given series:")
print(gvn_series.cummin())

Output:

The given series is:
0    12
1    40
2    10
3     5
4    15
5    40
6    12
7    12
dtype: int64

The cumulative minimum of values of all the elements of the given series:
0    12
1    12
2    10
3     5
4     5
5     5
6     5
7     5
dtype: int64

Example2

Here, the cummin() function is used on a specified series/columns of a DataFrame.

Approach:

Import pandas module using the import keyword.
Pass some random key-value pair(dictionary), index list as arguments to the DataFrame() function of the pandas module to create a dataframe.
Store it in a variable.
Print the given dataframe
Get the cumulative minimum of values of the student_marks column of the dataframe using the cummin() function and print the result.
The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Pass some random key-value pair(dictionary), index list as arguments to the 
# DataFrame() function of the pandas module to create a dataframe
# Store it in a variable.
data_frme = pd.DataFrame({
  "student_rollno": [1, 2, 3, 4],
  "student_marks": [80, 35, 25, 90]},
  index= ["virat", "nick" , "jessy", "sindhu"]
)
# Print the given dataframe
print("The given Dataframe:")
print(data_frme)
print()

# Get the cumulative minimum of values of the student_marks column of the 
# dataframe using the cummin() function and print the result
print("The cumulative minimum of values of the student_marks column of the dataframe:")
print(data_frme['student_marks'].cummin())

Output:

The given Dataframe:
        student_rollno  student_marks
virat                1             80
nick                 2             35
jessy                3             25
sindhu               4             90

The cumulative minimum of values of the student_marks column of the dataframe:
virat     80
nick      35
jessy     25
sindhu    25
Name: student_marks, dtype: int64

Pandas Series cummin() Function in Python

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