Sometimes, we want to find row where values for column is maximal in a Python Pandas DataFrame.
In this article, we’ll look at how to find row where values for column is maximal in a Python Pandas DataFrame.
How to find row where values for column is maximal in a Python Pandas DataFrame?
To find row where values for column is maximal in a Python Pandas DataFrame, we can use the idxmax method.
For instance, we write
import pandas
import numpy as np
df = pandas.DataFrame(np.random.randn(5,3),columns=['A','B','C'])
index_max = df['A'].idxmax()
to create a data frame with some random numbers in columns A, B and C with
df = pandas.DataFrame(np.random.randn(5,3),columns=['A','B','C'])
Then we get the index with the max value of column A with
index_max = df['A'].idxmax()
Conclusion
To find row where values for column is maximal in a Python Pandas DataFrame, we can use the idxmax method.
