Python Pandas – Find the maximum value of a column and return its corresponding row values

To find the maximum value of a column and to return its corresponding row values in Pandas, we can use df.loc[df[col].idxmax()]. Let's take an example to understand it better.

Steps

• Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.
• Print the input DataFrame, df.
• Initialize a variable, col, to find the maximum value of that column.
• Find the maximum value and its corresponding row, using df.loc[df[col].idxmax()]
• Print the Step 4 output.

Example

import pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 7, 0],       "y": [4, 7, 5, 1],       "z": [9, 3, 5, 1]    } ) print "Input DataFrame is:\n", df col = "x" max_x = df.loc[df[col].idxmax()] print "Maximum value of column ", col, " and its corresponding row values:\n", max_x col = "y" max_x = df.loc[df[col].idxmax()] print "Maximum value of column ", col, " and its corresponding row values:\n", max_x col = "z" max_x = df.loc[df[col].idxmax()] print "Maximum value of column ", col, " and its corresponding row values:\n", max_x

Output

Input DataFrame is: x y z 0 5 4 9 1 2 7 3 2 7 5 5 3 0 1 1 Maximum value of column x and its corresponding row values: x 7 y 5 z 5 Name: 2, dtype: int64 Maximum value of column y and its corresponding row values: x 2 y 7 z 3 Name: 1, dtype: int64 Maximum value of column z and its corresponding row values: x 5 y 4 z 9 Name: 0, dtype: int64