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DataFrame.transform() - ( Pandas DataFrame Basics )

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Syntax

DataFrame.transform(func, axis=0, *args, **kwargs)

Example

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

def my_func(x):
    return x.mean()

df2 = df.transform(my_func)

print(df2)

Output

     A    B    C
0  2.0  5.0  8.0
1  2.0  5.0  8.0
2  2.0  5.0  8.0

Explanation

DataFrame.transform() is a Pandas function that applies a function to each element across one or more columns in a DataFrame and returns a transformed DataFrame with the same shape. The function can be a built-in function, a lambda function, or a user-defined function.

In the above example, we create a simple DataFrame df with three columns and three rows. We define a function my_func that returns the mean of a DataFrame. We then apply this function to the columns of df using the transform() function, which returns a new DataFrame df2 with the same shape as the original df, but with the mean value of each column.

Use

DataFrame.transform() is useful in Pandas for performing element-wise operations on one or more columns of a DataFrame. It is also used in data wrangling and feature engineering during data preprocessing.

Important Points

  • DataFrame.transform() applies a function to each element across one or more columns in a DataFrame and returns a transformed DataFrame with the same shape
  • The function can be a built-in function, a lambda function, or a user-defined function
  • DataFrame.transform() is useful for performing element-wise operations on one or more columns of a DataFrame, especially during data preprocessing and feature engineering

Summary

In conclusion, DataFrame.transform() is an important function in Pandas for performing element-wise operations on one or more columns of a DataFrame. It returns a transformed DataFrame with the same shape as the original DataFrame. It is useful for performing data preprocessing and feature engineering operations such as scaling, normalization, and imputation.

DataFrame.to_excel()DataFrame.transpose()
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