How to obtain the cumulative minimum over a pandas dataframe axis

Overview

The cummin() function of a DataFrame object is used to obtain the cumulative minimum over its axis.

Note: Axis here represents the rows and columns of the DataFrame. An axis with a value of '0' indicates the axes running vertically downwards across a row, while a value of '1' indicates the axes running horizontally across a column.

Syntax

DataFrame.cummin(axis=None, skipna=True, *args, **kwargs)
Syntax for the cummin() function in Pandas

Parameters

  • axis: This represents the name for the row ( designated as 0 or 'index') or the column (designated as 1 or columns) axis.
  • skipna: This takes a boolean value indicating if null values are to be excluded. This is an optional parameter.
  • args and **kwargs: These are keywords that have no effect but may be accepted for compatibility with NumPy. These are optional.

Return value

This function returns a series or DataFrame object showing the cumulative minimum in the axis.

Example

# A code to illustrate the cummin() function in Pandas



# importing the pandas library

import pandas as pd



# creating a dataframe

df = pd.DataFrame([[5,10,4,15,3],

                   [1,7,5,9,0.5],

                   [3,11,13,14,12]],

                   columns=list('ABCDE'))

# printing the dataframe

print(df)



# obtaining the cummulative minimum vertically across rows

print(df.cummin(axis="index"))



# obtaining the cummulative minimum horizontally over columns

print(df.cummin(axis="columns"))

Explanation

  • Line 4: We import the pandas library.
  • Lines 7–10: We create a DataFrame, df.
  • Line 12: We print the DataFrame, df.
  • Line 15: We obtain the cumulative minimum values running downwards across the rows (axis 0). We print the result to the console.
  • Line 18: We obtain the cumulative minimum values running horizontally across columns (axis 1). We print the result to the console.

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