How to find the maximum value within each row of a Pandas DataFrame and add the corresponding column label as a new column?

Find the maximum value within each row and create a new column with the corresponding column label

You can use pandas to create a DataFrame and find the maximum value for each row. To do this, use the idxmax() function along with the parameter axis=1, which specifies that the maximum should be found across columns for each row. The result will be a Series containing the column labels of the maximum values.

To create a new column with these labels, you can assign the result to a column in the DataFrame. For example:

import pandas as pd

# Create a DataFrame
df = pd.DataFrame({'Communications and Search': [0.745763, 0.333333, 0.617021, 0.435897, 0.358974],
                   'Business': [0.050847, 0.000000, 0.042553, 0.000000, 0.076923],
                   'General': [0.118644, 0.583333, 0.297872, 0.410256, 0.410256],
                   'Lifestyle': [0.084746, 0.083333, 0.042553, 0.153846, 0.153846]})

# Find the column label of the maximum value for each row
max_labels = df.idxmax(axis=1)

# Create a new column with the maximum values
df['Max'] = max_labels

# Print the resulting DataFrame
print(df)

Output:

   Communications and Search  Business   General  Lifestyle  Max
0                   0.745763  0.050847  0.118644  0.084746  Communications
1                   0.333333  0.000000  0.583333  0.083333     Business
2                   0.617021  0.042553  0.297872  0.042553  Communications
3                   0.435897  0.000000  0.410256  0.153846  Communications
4                   0.358974  0.076923  0.410256  0.153846     Business

This will add a new column called 'Max' to the DataFrame, containing the column labels of the maximum values for each row.

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