How to obtain the maximum value of an axis of a pandas DataFrame
Overview
The max() function is used to return the maximum values of a specified axis.
Note: Axis here represents the rows and columns of the DataFrame. An axis with a value of
'0'indicate the axes running vertically downwards across a row, while a value of'1'indicates the axes running running horizontally across a column.
Syntax
DataFrame.max(axis=None, skipna=True, *args, **kwargs)
Syntax for the cummax() function in Pandas
Parameters
axis: This represents the name for the row (designated as0or'index') or the column (designated as1orcolumns) axis.skipna: This takes a Boolean value indicating if null values are to be excluded. This is an optional parameter.level: This takes an integer or a level name specifying the count along a particular level.numeric_only: This takes a boolean value indicating whether to include only float, integer, or boolean columns.**kwargs: This is a keyword that has no effect but may be accepted for compatibility with NumPy. This is an optional parameter.
Return value
This function returns a Series or DataFrame object showing the maximum values in the specified axis.
Example
# A code to illustrate the max() function in Pandas# importing the pandas libraryimport pandas as pd# creating a dataframedf = pd.DataFrame([[5,10,4,15,3],[1,7,5,9,0.5],[3,11,13,14,12]],columns=list('ABCDE'))# printing the dataframeprint(df)# obtaining the maximum values vertically across rowsprint(df.max(axis="index"))# obtaining the maximum values horizontally over columnsprint(df.max(axis="columns"))
Explanation
- Line 4 : We import the
pandaslibrary. - Lines 7–10: We create a DataFrame,
df. - Line 12: We print the DataFrame,
df. - Line 15: We use the
max()function to obtain the maximum values running downwards across the rows (axis0). We print the result to the console. - Line 18: We use the
max()function to obtain the maximum values running horizontally across columns (axis1). We print the result to the console.