different_between_min_max_in_group

# Нахождение минимального и максимального значения VALUE по каждому ID.
# Расчёт промежутки времени DATE_DIFF, который прошел между этими событиями DATE.

import pandas as pd


data = [[1, 123124, 2000],
        [1, 324324, 2001],
        [1, 345345, 2002],
        [1, 324430, 2003],
        [2, 465446, 2011],
        [2, 545644, 2010],
        [2, 545454, 2012],
        [2, 687877, 2005]]

df = pd.DataFrame(data, columns=['ID', 'VALUE', 'DATE'])

df['MIN_VALUE'] = df.groupby(['ID'])['VALUE'].transform('min')
df['MAX_VALUE'] = df.groupby(['ID'])['VALUE'].transform('max')
df['DATE_MIN'] = None
df['DATE_MAX'] = None

for id in df['ID'].unique():
    group = df[df['ID'] == id]
    min = group['VALUE'].min()
    max = group['VALUE'].max()

    date_min = group[group['VALUE'] == min]['DATE'].min()
    date_max = group[group['VALUE'] == max]['DATE'].max()

    df.loc[df['ID'] == id, 'DATE_MIN'] = date_min
    df.loc[df['ID'] == id, 'DATE_MAX'] = date_max


df['DATE_DIFF'] = df['DATE_MIN'] - df['DATE_MAX']

df_2 = df[['ID', 'MIN_VALUE', 'MAX_VALUE', 'DATE_MIN', 'DATE_MAX', 'DATE_DIFF']].drop_duplicates()
df_2