Multiindex Data Frame is a data frame with more than one index. Let’s say the following is our csv stored on the Desktop −
At first, import the pandas library and read the above CSV file −
import pandas as pd
df = pd.read_csv("C:/Users/amit_/Desktop/sales.csv") print(df)We will form the ‘Car‘ and ‘Place‘ columns of the Dataframe as the index −
df = df.set_index(['Car', 'Place'])
The DataFrame is now a multi-indexed DataFrame having the ‘Car‘ and ‘Place‘ columns as an index.
Now, let us use groupby on the multiindex dataframe:
res = df.groupby(level=['Car'])['UnitsSold'].mean() print(res)
Example
Following is the code −
import pandas as pd
df = pd.read_csv("C:/Users/amit_/Desktop/sales.csv")
print(df)
# set Car and Place columns of the DataFrame as index
df = df.set_index(['Car', 'Place'])
# sorting
df.sort_index()
# groupby on multiindex datafram
res = df.groupby(level=['Car'])['UnitsSold'].mean()
print(res)Output
This will produce the following output −
Car Place Sold 0 BMW Delhi 95 1 Mercedes Hyderabad 80 2 Lamborgini Chandigarh 80 3 Audi Bangalore 75 4 Mercedes Hyderabad 90 5 Porsche Mumbai 90 6 RollsRoyce Mumbai 95 7 BMW Delhi 50 Car Audi 75.8 BMW 72.5 Lamborgini 80.0 Mercedes 85.0 Porsche 90.0 RollsRoyce 95.0 Name: UnitsSold, dtype: float64