Creating a multi-index dataframe

Question

Please consider these two dataframes that contain demographical info about a single zip code (10001):

df1 = pd.DataFrame([['Enrolled In Public School',2000 ], ['Enrolled In Private School', 100], ['Not Enrolled In School', 1]], columns = ['enrollment type', 'count'], index = ['10001', '10001','10001'])

df2 =  pd.DataFrame([12000], columns = ['population'], index = ['10001'])

df1 looks like:

        enrollment type             count
10001   Enrolled In Public School   2000
10001   Enrolled In Private School  100
10001   Not Enrolled In School      1

df2 looks like:

        population
10001   12000

How can I create a multi-index dataframe that looks like below? My goal is then to expand this dataframe for more zipcodes.

Answer 1

You can first reset_index() on df1 and df2 , merge them together, and then use pandas.pivot_table() .

df1 = df1.reset_index()
df2 = df2.reset_index()

df = pd.merge(df1, df2, how='left', on='index')

df.columns = ['zipcode', 'enrollment type', 'count', 'population']

df.pivot_table(columns=['enrollment type'], index=['zipcode', 'population'])

Result:

Result Table