The transform() method in pandas allows you to execute a function for each value of the DataFrame.
Syntax –
DataFrame.transform(func, axis=0, *args, **kwargs)func – Function to use for transforming the data.
axis – If 0 or ‘index’: apply function to each column. If 1 or ‘columns’: apply function to each row.
*args – Positional arguments to pass to func.
**kwargs – Keyword arguments to pass to func.
Examples –
1 . Create a DataFrame –
Let’s create a dataframe to work with.
import pandas as pd
import numpy as np
df = pd.DataFrame({'A':[1, 2, 3],
'B':[4, 5, 6],
'C':[7, 8, 9]})
df
2 . Apply a function to a dataframe –
Let’s say we want to add 10 to each values in the dataframe. For this we can use the transform() method in pandas.
df.transform(lambda x: x + 10)
3 . Apply a function to a series –
We can also apply a function to each values in a series.
# create a series
s = df['A']
# apply functions to the series
s.transform(['sqrt','exp'])