How to Combine Maximum Values from Multiple Columns in a DataFrame?

Getting the Maximum Value from Multiple DataFrame Columns

When working with dataframes, having a consolidated column containing the maximum values from multiple other columns can be useful. One such instance is obtaining the maximum value between columns A and B, as illustrated in this example:

import pandas as pd

df = pd.DataFrame({"A": [1, 2, 3], "B": [-2, 8, 1]})

print("Original DataFrame:")
print(df)

Our goal is to create a new column C containing the maximum value for each row between columns A and B. To achieve this, we can use the following steps:

print("\nMaximum values between A and B:")
df["C"] = df[["A", "B"]].max(axis=1)
print(df)

Explanation:

1. We fetch the maximum value between columns A and B for each row using .max(axis=1) and store it in a new column titled "C".
2. Optionally, we could also utilize .max(axis=1) directly on the dataframe.
3. Using .apply(max, axis=1) is another viable approach.

As a result, we obtain a modified dataframe with the "C" column containing the desired maximum values:

Original DataFrame:
   A  B
0  1 -2
1  2  8
2  3  1

Maximum values between A and B:
   A  B  C
0  1 -2  1
1  2  8  8
2  3  1  3

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