Pandas: Find the row for where the value of a given column is maximum

Last update on May 01 2025 12:53:06 (UTC/GMT +8 hours)

45. Row with Maximum Value

Write a Pandas program to find the row for where the value of a given column is maximum.

Sample Solution:

Python Code :

import pandas as pd
d = {'col1': [1, 2, 3, 4, 7], 'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}
df = pd.DataFrame(data=d)
print("Original DataFrame")
print(df)
print("Row where col1 has maximum value:")
print(df['col1'].argmax())
print("Row where col2 has maximum value:")
print(df['col2'].argmax())
print("Row where col3 has maximum value:")
print(df['col3'].argmax())

Sample Output:

    Original DataFrame
   col1  col2  col3
0     1     4     7
1     2     5     8
2     3     6    12
3     4     9     1
4     7     5    11
Row where col1 has maximum value:
4
Row where col2 has maximum value:
3
Row where col3 has maximum value:
2

Explanation:

The above code creates a pandas DataFrame 'df' with three columns - 'col1', 'col2', and 'col3'. The code then uses the 'argmax()' function to find the index of the maximum value in each column.

Therefore -

The first 'print' statement returns the index of the row that has the maximum value in 'col1'.
The second 'print' statement returns the index of the row that has the maximum value in 'col2'.
The third 'print' statement returns the index of the row that has the maximum value in 'col3'.

For more Practice: Solve these Related Problems:

Write a Pandas program to find the row where a given column has the maximum value and then output that row as a Series.
Write a Pandas program to determine the index of the row with the maximum value in a column and then extract the corresponding row.
Write a Pandas program to locate the row with the highest value in each column and then compile these rows into a new DataFrame.
Write a Pandas program to find the row with the maximum value in a specified column and then compare it to the row with the minimum value.

Go to:

Previous: Write a Pandas program to create a DataFrame from a Numpy array and specify the index column and column headers.
Next: Write a Pandas program to check whether a given column is present in a DataFrame or not.

Python-Pandas Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.