Get the maximum value from the DataFrame

Pandas DataFrame max() method is used to find the maximum values in the object and returns it.In DatFrame it returns a series with maximum values over specified axis in a dataframe. 

Syntax

DataFrame.max(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)

Parameters

  • axis:{index (0), columns (1)} 
  • skipna: Exclude null values when computing the result 
  • level: It is by default None. If the axis is multiindex
  • numeric_only: Include float, int, boolean columns. If None is given then use numerical data
  • **kwargs: Any additional keyword argument to be passed.

Return

According to the level specified(either series or dataframe)

1. Find the max value of DataFrame column

Example

import pandas as pd

names = ["John","Jill","Monica","Joey","Alice"]
ages = [22,24,20,24,26]
fees = [True,False,True,True,False]

students = pd.DataFrame({'name':names ,'age':ages,'Fees Submitted':fees})
print(students)

max_value=students.max()
print("max_value along column is:\n",max_value)

Output

     Name  Age  Fees Submitted
0    John   22            True
1    Jill   24           False
2  Monica   20            True
3    Joey   24            True
4   Alice   26           False
max_value along column is:
names    Monica
ages         26
fees       True
dtype: object

2. Find the max value of DataFrame along rows

Example

max_value=students.max(axis=1)
print("max_value along row is:\n",max_value)

Output

max_value along row is:
 0    22.0
1    24.0
2    20.0
3    24.0
4    26.0
dtype: float64

3. Find the max value of complete DataFrame

Example

import pandas as pd

physics=[88,98,67]
chemistry=[56,78,90]
biology=[85,69,93]

students=pd.DataFrame({'Physics':physics,'Chemistry':chemistry,'Biology':biology})
print(students)

max_value=students.max().max()
print("max_value in complete DataFrame is: ",max_value)

Output:

   Physics  Chemistry  Biology
0       88         56       85
1       98         78       69
2       67         90       93

max_value in complete DataFrame is: 98
Thu, 02/11/2021 - 23:07

Authored by

Devanshi, is working as a Data Scientist with iVagus. She has expertise in Python, NumPy, Pandas and other data science technologies.