2. Applying a function Three types of operation can be performed with groupby function: a. Aggregation b. Transformation c. Filteration a. Aggregation An aggregated function returns a single aggregated value for each group. Example:- import pandas as pd import numpy as np weather_data = {'Weather': ['Rainy', 'Stormy', 'Sunny', 'Cloudy', 'Rainy', 'Sunny', 'Cloudy', 'Rainy', 'Stormy', 'Cloudy', 'Sunny', 'Sunny'], 'State': ['CG', 'AP', 'HP', 'MP', 'HY','DH' ,'CG' ,'HP','AP' , 'MP','CG','AP'], 'Year': [2014,2015,2014,2015,2014,2015,2016,2017,2016,2014,2015,2017], 'Humidity':[3.4,2.3,3.2,4.7,5.8,8.1,3.2,3.5,7.3,1.1,1.2,2.3]} df = pd.DataFrame(weather_data) grouped = df.groupby('Year') print(grouped['Humidity'].agg(np.sum)) Output:- ...
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