Pandas: Difference between largest and smallest value within group

Using @unutbu ‘s df

per timing
unutbu’s solution is best over large data sets

import pandas as pd
import numpy as np

df = pd.DataFrame({'GROUP': [1, 2, 1, 2, 1], 'VALUE': [5, 2, 10, 20, 7]})

df.groupby('GROUP')['VALUE'].agg(np.ptp)

GROUP
1     5
2    18
Name: VALUE, dtype: int64

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np.ptp docs returns the range of an array

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timing
small df

large df
df = pd.DataFrame(dict(GROUP=np.arange(1000000) % 100, VALUE=np.random.rand(1000000)))

large df
many groups
df = pd.DataFrame(dict(GROUP=np.arange(1000000) % 10000, VALUE=np.random.rand(1000000)))