Q. Consider the crop statistics DataFrame prodf. Write a program to print the average crop production for each crop.
Dataframe prodf :-
Rice Wheat Pulses Fruits
Andhra P. 7452.4 NaN 931.0 7830.0
Gujarat 1930.0 2737.0 818.0 11950.0
Kerala 2604.8 NaN 1.7 113.1
Punjab 11586.2 16440.5 33.0 7152.0
Tripura 814.6 0.5 23.2 44.1
Uttar P. 13754.0 30056.0 2184.4 140169.2
Answer :-
import pandas as pd import numpy as np iprod = { 'Rice': {'Andhra P.':7452.4, 'Gujarat' :1930.0, 'Kerala': 2604.8,\ 'Punjab':11586.2, 'Tripura':814.6, 'Uttar P.':13754.0},\ 'Wheat' : { 'Andhra P.': np.NaN, 'Gujarat':2737.0, 'Kerala':np.NaN,\ 'Punjab' :16440.5, 'Tripura':0.5, 'Uttar P.':30056.0},\ 'Pulses': {'Andhra P.':931.0, 'Gujarat':818.0, 'Kerala':1.7,\ 'Punjab' :33.0, 'Tripura':23.2, 'Uttar P.':2184.4},\ 'Fruits': {'Andhra P.':7830.0, 'Gujarat':11950.0, 'Kerala':113.1,\ 'Punjab' :7152.0, 'Tripura':44.1, 'Uttar P.':140169.2}} prodf = pd.DataFrame(iprod) print ("Dataframe prodf :-\n") print (prodf) print("\nAverage crop production:-\n") print (prodf.mean())
Output :-
Dataframe prodf :-
Rice Wheat Pulses Fruits
Andhra P. 7452.4 NaN 931.0 7830.0
Gujarat 1930.0 2737.0 818.0 11950.0
Kerala 2604.8 NaN 1.7 113.1
Punjab 11586.2 16440.5 33.0 7152.0
Tripura 814.6 0.5 23.2 44.1
Uttar P. 13754.0 30056.0 2184.4 140169.2
Average crop production:-
Rice 6357.000000
Wheat 12308.500000
Pulses 665.216667
Fruits 27876.400000
dtype: float64
>>>
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