import pandas as pd
import numpy as np
d = {
'Name':['Alisa','Bobby','Cathrine','Alisa','Bobby','Cathrine',
'Alisa','Bobby','Cathrine','Alisa','Bobby','Cathrine'],
'Semester':['Semester 1','Semester 1','Semester 1','Semester 1','Semester 1','Semester 1',
'Semester 2','Semester 2','Semester 2','Semester 2','Semester 2','Semester 2'],
'Subject':['Mathematics','Mathematics','Mathematics','Science','Science','Science',
'Mathematics','Mathematics','Mathematics','Science','Science','Science'],
'Score':[62,47,55,74,31,77,85,63,42,67,89,81]}
df = pd.DataFrame(d)
df
df.pivot_table(values='Score', index='Semester', columns='Subject', aggfunc=np.sum)
df.pivot_table(values='Score', index='Semester', columns='Subject', margins=True, aggfunc=np.sum)
df.pivot_table(values='Score', index='Semester', columns='Subject', aggfunc={
'mean', 'max', 'min'})
cars_df = pd.read_csv('../data/cars.csv')
cars_df.head()
cars_df.pivot_table(values='(kW)', index='YEAR', columns='Make')