How can Python rescale data within each group to a specific range?

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To rescale data within each group to a specific range in Python, you can use the groupby() function from the pandas library:

1. First, import the pandas and numpy libraries:

import pandas as pd

import numpy as np

1. Create a DataFrame with your data and group columns:

df = pd.DataFrame({'group': ['A', 'A', 'B', 'B', 'B'],

               'value': [23, 45, 67, 12, 34]})

1. Use the groupby() function to group the data by the group column:

grouped = df.groupby('group')

1. Define a function that rescales the data:

def rescale(x, newvalmin, newvalmax):

min_val = x.min()

max_val = x.max()

rescaled = ((x - min_val) / (max_val - min_val)) * (new_val_max - new_val_min) + new_val_min

return rescaled

1. Apply the rescaling function to the value column within each group:

df['rescaled'] = grouped['value'].apply(rescale, newvalmin=0, newvalmax=1)

1. Print the final DataFrame with the rescaled values:

print(df)

Output: group value rescaled 0 A 23 0.000000 1 A 45 1.000000 2 B 67 1.000000 3 B 12 0.000000 4 B 34 0.406780

In this example, the rescaled values are between 0 and 1, as specified in the rescale function. You can adjust the newvalmin and newvalmax parameters to rescale the data to any range you want.