# -*- coding: utf-8 -*- #-----(1) data analysis of agriculture sector ----- import numpy as np import pandas as pd import matplotlib.pyplot as plt import random df = pd.read_csv ('C:/Users/Jeet Das/Desktop/Major Project - Indian Economy/Project ( Section 1-Indian Economy)/Section-1_Data_sheet/(02)_agriculture.csv',encoding="cp1252") print("\n------- output data :-----------\n") print("Agriculture data analysis:") # Question – A : get row and column numbers def dimension(): print('---------------------------------------------') print("Dimension of the data frame = ",df.shape) print('---------------------------------------------') # Question – B : print column names : def column_names(): print('Column names as follows :') print('---------------------------------------------') count = 1 for col in df.columns: print(count,"-->",col) count = count+1 print("---------------------------------------------\n") #Question – C : State_Name (using GROUP BY method) and no. of states : def states(): state_names = df.groupby(['State_Name'])[['District_Name']].count() print("\t states names : ") print("-------------------------------") print(state_names) print("-------------------------------") count = 0 for row in range(len(state_names)): count = count+1 print("total no. of states = ",count) print("-----------------------------\n") # state - 1 : Andaman and Nicobar Islands df_andaman = df[df.State_Name == 'Andaman and Nicobar Islands'] # state -2 : Andhra Pradesh df_andhra = df[df.State_Name == 'Andhra Pradesh'] # state -3 : Arunachal Pradesh df_arunachal = df[df.State_Name == 'Arunachal Pradesh'] # state -4 : Assam df_assam = df[df.State_Name == 'Assam'] # state -5 : Bihar df_bihar = df[df.State_Name == 'Bihar'] # state -6 : Chandigarh df_candigarh = df[df.State_Name == 'Chandigarh'] # state -7 : Chhattisgarh df_chattisgarh = df[df.State_Name == 'Chhattisgarh'] # state -8 : Dadra and Nagar Haveli df_dadra = df[df.State_Name == 'Dadra and Nagar Haveli'] # state -9 : Goa df_goa = df[df.State_Name == 'Goa'] # state -10: Gujarat df_gujrat = df[df.State_Name == 'Gujarat'] # state -11: Haryana df_haryana = df[df.State_Name == 'Haryana'] # state -12: Himachal Pradesh df_himachal = df[df.State_Name == 'Himachal Pradesh'] # state -13: Jammu and Kashmir df_jammu = df[df.State_Name == 'Jammu and Kashmir'] # state -14: Jharkhand df_jharkand = df[df.State_Name == 'Jharkhand'] # state -15: Karnataka df_karnataka = df[df.State_Name == 'Karnataka'] # state -16: Kerala df_kerala = df[df.State_Name == 'kerala'] # state -17: Madhya Pradesh df_madhya = df[df.State_Name == 'Madhya Pradesh'] # state -18: Maharashtra df_maharashtra = df[df.State_Name == 'Maharashtra'] # state -19: Manipur df_manipur = df[df.State_Name == 'Manipur'] # state -20: Meghalaya df_meghalaya = df[df.State_Name == 'Meghalaya'] # state -21: Mizoram df_mizoram = df[df.State_Name == 'Mizoram'] # state -22: Nagaland df_nagaland = df[df.State_Name == 'Nagaland'] # state -23: Odisha df_odisha = df[df.State_Name == 'Odisha'] # state -24: Puducherry df_puducherry = df[df.State_Name == 'Puducherry'] # state -25: Punjab df_punjab = df[df.State_Name == 'Punjab'] # state -26: Rajasthan df_rajasthan = df[df.State_Name == 'Rajasthan'] # state -27: Sikkim df_sikkim = df[df.State_Name == 'Sikkim'] # state -28: Tamil Nadu df_tamilnadu = df[df.State_Name == 'Tamil Nadu'] # state -29: Telangana df_telangana = df[df.State_Name == 'Telangana'] # state -30: Tripura df_tripura = df[df.State_Name == 'Tripura'] # state -31: Uttar Pradesh df_uttar = df[df.State_Name == 'Uttar Pradesh'] # state -32: Uttarakhand df_uttarakhand = df[df.State_Name == 'Uttarakhand'] # state -33: West Bengal df_wb = df[df.State_Name == 'West Bengal'] # Question - D : print state names and Calculate no. of districts of all states def district_of_all_states(): # state - 1 : Andaman and Nicobar Islands df_andaman = df[df.State_Name == 'Andaman and Nicobar Islands'] df_andaman_dist = df_andaman.groupby(['District_Name'])[['Crop_Year']].count() print(df_andaman_dist) print("-----------------------------") count = 0 for row in range(len(df_andaman_dist)): count = count+1 print("total no. of district in state - 1 : Andaman and Nicobar Islands = ",count) print("-----------------------------\n") # state -2 : Andhra Pradesh df_andhra = df[df.State_Name == 'Andhra Pradesh'] df_andhra_dist = df_andhra.groupby(['District_Name'])[['Crop_Year']].count() print(df_andhra_dist) print("-----------------------------") count = 0 for row in range(len(df_andhra_dist)): count = count+1 print("total no. of district in state -2 : Andhra Pradesh = ",count) print("-----------------------------\n") # state -3 : Arunachal Pradesh df_arunachal = df[df.State_Name == 'Arunachal Pradesh'] df_arunachal_dist = df_arunachal.groupby(['District_Name'])[['Crop_Year']].count() print(df_arunachal_dist) print("-----------------------------") count = 0 for row in range(len(df_arunachal_dist)): count = count+1 print("total no. of district in state -3 : Arunachal Pradesh = ",count) print("-----------------------------\n") # state -4 : Assam df_assam = df[df.State_Name == 'Assam'] df_assam_dist = df_assam.groupby(['District_Name'])[['Crop_Year']].count() print(df_assam_dist) print("-----------------------------") count = 0 for row in range(len(df_assam_dist)): count = count+1 print("total no. of district in state -4 : Assam = ",count) print("-----------------------------\n") # state -5 : Bihar df_bihar = df[df.State_Name == 'Bihar'] df_bihar_dist = df_bihar.groupby(['District_Name'])[['Crop_Year']].count() print(df_bihar_dist) print("-----------------------------") count = 0 for row in range(len(df_bihar_dist)): count = count+1 print("total no. of district in state -5 : Bihar = ",count) print("-----------------------------\n") # state -6 : Chandigarh df_candigarh = df[df.State_Name == 'Chandigarh'] df_candigarh_dist = df_candigarh.groupby(['District_Name'])[['Crop_Year']].count() print(df_candigarh_dist) print("-----------------------------") count = 0 for row in range(len(df_candigarh_dist)): count = count+1 print("total no. of district in state -6 : Chandigarh = ",count) print("-----------------------------\n") # state -7 : Chhattisgarh df_chattisgarh = df[df.State_Name == 'Chhattisgarh'] df_chattisgarh_dist = df_chattisgarh.groupby(['District_Name'])[['Crop_Year']].count() print(df_chattisgarh_dist) print("-----------------------------") count = 0 for row in range(len(df_chattisgarh_dist)): count = count+1 print("total no. of district in state -7 : Chhattisgarh = ",count) print("-----------------------------\n") # state -8 : Dadra and Nagar Haveli df_dadra = df[df.State_Name == 'Dadra and Nagar Haveli'] df_dadra_dist = df_dadra.groupby(['District_Name'])[['Crop_Year']].count() print(df_dadra_dist) print("-----------------------------") count = 0 for row in range(len(df_dadra_dist)): count = count+1 print("total no. of district in state -8 : Dadra and Nagar Haveli = ",count) print("-----------------------------\n") # state -9 : Goa df_goa = df[df.State_Name == 'Goa'] df_goa_dist = df_goa.groupby(['District_Name'])[['Crop_Year']].count() print(df_goa_dist) print("-----------------------------") count = 0 for row in range(len(df_goa_dist)): count = count+1 print("total no. of district in state -9 : Goa = ",count) print("-----------------------------\n") # state -10: Gujarat df_gujrat = df[df.State_Name == 'Gujarat'] df_gujrat_dist = df_gujrat.groupby(['District_Name'])[['Crop_Year']].count() print(df_gujrat_dist) print("-----------------------------") count = 0 for row in range(len(df_gujrat_dist)): count = count+1 print("total no. of district in state -10: Gujarat = ",count) print("-----------------------------\n") # state -11: Haryana df_haryana = df[df.State_Name == 'Haryana'] df_haryana_dist = df_haryana.groupby(['District_Name'])[['Crop_Year']].count() print(df_haryana_dist) print("-----------------------------") count = 0 for row in range(len(df_haryana_dist)): count = count+1 print("total no. of district in state -11: Haryana = ",count) print("-----------------------------\n") # state -12: Himachal Pradesh df_himachal = df[df.State_Name == 'Himachal Pradesh'] df_himachal_dist = df_himachal.groupby(['District_Name'])[['Crop_Year']].count() print(df_himachal_dist) print("-----------------------------") count = 0 for row in range(len(df_himachal_dist)): count = count+1 print("total no. of district in state -12: Himachal Pradesh = ",count) print("-----------------------------\n") # state -13: Jammu and Kashmir df_jammu = df[df.State_Name == 'Jammu and Kashmir'] df_jammu_dist = df_jammu.groupby(['District_Name'])[['Crop_Year']].count() print(df_jammu_dist) print("-----------------------------") count = 0 for row in range(len(df_jammu_dist)): count = count+1 print("total no. of district in state -13: Jammu and Kashmir = ",count) print("-----------------------------\n") # state -14: Jharkhand df_jharkand = df[df.State_Name == 'Jharkhand'] df_jharkand_dist = df_jharkand.groupby(['District_Name'])[['Crop_Year']].count() print(df_jharkand_dist) print("-----------------------------") count = 0 for row in range(len(df_jharkand_dist)): count = count+1 print("total no. of district in state -14: Jharkhand = ",count) print("-----------------------------\n") # state -15: Karnataka df_karnataka = df[df.State_Name == 'Karnataka'] df_karnataka_dist = df_karnataka.groupby(['District_Name'])[['Crop_Year']].count() print(df_karnataka_dist) print("-----------------------------") count = 0 for row in range(len(df_karnataka_dist)): count = count+1 print("total no. of district in state -15: Karnataka = ",count) print("-----------------------------\n") # state -16: Kerala df_kerala = df[df.State_Name == 'kerala'] df_kerala_dist = df_kerala.groupby(['District_Name'])[['Crop_Year']].count() print(df_kerala_dist) print("-----------------------------") count = 0 for row in range(len(df_kerala_dist)): count = count+1 print("total no. of district in state -16: Kerala = ",count) print("-----------------------------\n") # state -17: Madhya Pradesh df_madhya = df[df.State_Name == 'Madhya Pradesh'] df_madhya_dist = df_madhya.groupby(['District_Name'])[['Crop_Year']].count() print(df_madhya_dist) print("-----------------------------") count = 0 for row in range(len(df_madhya_dist)): count = count+1 print("total no. of district in state -17: Madhya Pradesh = ",count) print("-----------------------------\n") # state -18: Maharashtra df_maharashtra = df[df.State_Name == 'Maharashtra'] df_maharashtra_dist = df_maharashtra.groupby(['District_Name'])[['Crop_Year']].count() print(df_maharashtra_dist) print("-----------------------------") count = 0 for row in range(len(df_maharashtra_dist)): count = count+1 print("total no. of district in state -18: Maharashtra = ",count) print("-----------------------------\n") # state -19: Manipur df_manipur = df[df.State_Name == 'Manipur'] df_manipur_dist = df_manipur.groupby(['District_Name'])[['Crop_Year']].count() print(df_manipur_dist) print("-----------------------------") count = 0 for row in range(len(df_manipur_dist)): count = count+1 print("total no. of district in state -19: Manipur = ",count) print("-----------------------------\n") # state -20: Meghalaya df_meghalaya = df[df.State_Name == 'Meghalaya'] df_meghalaya_dist = df_meghalaya.groupby(['District_Name'])[['Crop_Year']].count() print(df_meghalaya_dist) print("-----------------------------") count = 0 for row in range(len(df_meghalaya_dist)): count = count+1 print("total no. of district in state -20: Meghalaya = ",count) print("-----------------------------\n") # state -21: Mizoram df_mizoram = df[df.State_Name == 'Mizoram'] df_mizoram_dist = df_mizoram.groupby(['District_Name'])[['Crop_Year']].count() print(df_mizoram_dist) print("-----------------------------") count = 0 for row in range(len(df_mizoram_dist)): count = count+1 print("total no. of district in state -21: Mizoram = ",count) print("-----------------------------\n") # state -22: Nagaland df_nagaland = df[df.State_Name == 'Nagaland'] df_nagaland_dist = df_nagaland.groupby(['District_Name'])[['Crop_Year']].count() print(df_nagaland_dist) print("-----------------------------") count = 0 for row in range(len(df_nagaland_dist)): count = count+1 print("total no. of district in state -22: Nagaland = ",count) print("-----------------------------\n") # state -23: Odisha df_odisha = df[df.State_Name == 'Odisha'] df_odisha_dist = df_odisha.groupby(['District_Name'])[['Crop_Year']].count() print(df_odisha_dist) print("-----------------------------") count = 0 for row in range(len(df_odisha_dist)): count = count+1 print("total no. of district in state -23: Odisha = ",count) print("-----------------------------\n") # state -24: Puducherry df_puducherry = df[df.State_Name == 'Puducherry'] df_puducherry_dist = df_puducherry.groupby(['District_Name'])[['Crop_Year']].count() print(df_puducherry_dist) print("-----------------------------") count = 0 for row in range(len(df_puducherry_dist)): count = count+1 print("total no. of district in state -24: Puducherry = ",count) print("-----------------------------\n") # state -25: Punjab df_punjab = df[df.State_Name == 'Punjab'] df_punjab_dist = df_punjab.groupby(['District_Name'])[['Crop_Year']].count() print(df_punjab_dist) print("-----------------------------") count = 0 for row in range(len(df_punjab_dist)): count = count+1 print("total no. of district in state -25: Punjab = ",count) print("-----------------------------\n") # state -26: Rajasthan df_rajasthan = df[df.State_Name == 'Rajasthan'] df_rajasthan_dist = df_rajasthan.groupby(['District_Name'])[['Crop_Year']].count() print(df_rajasthan_dist) print("-----------------------------") count = 0 for row in range(len(df_rajasthan_dist)): count = count+1 print("total no. of district in state -26: Rajasthan = ",count) print("-----------------------------\n") # state -27: Sikkim df_sikkim = df[df.State_Name == 'Sikkim'] df_sikkim_dist = df_sikkim.groupby(['District_Name'])[['Crop_Year']].count() print(df_sikkim_dist) print("-----------------------------") count = 0 for row in range(len(df_sikkim_dist)): count = count+1 print("total no. of district in state -27: Sikkim = ",count) print("-----------------------------\n") # state -28: Tamil Nadu df_tamilnadu = df[df.State_Name == 'Tamil Nadu'] df_tamilnadu_dist = df_tamilnadu.groupby(['District_Name'])[['Crop_Year']].count() print(df_tamilnadu_dist) print("-----------------------------") count = 0 for row in range(len(df_tamilnadu_dist)): count = count+1 print("total no. of district in state -28: Tamil Nadu = ",count) print("-----------------------------\n") # state -29: Telangana df_telangana = df[df.State_Name == 'Telangana'] df_telangana_dist = df_telangana.groupby(['District_Name'])[['Crop_Year']].count() print(df_telangana_dist) print("-----------------------------") count = 0 for row in range(len(df_telangana_dist)): count = count+1 print("total no. of district in state -29: Telangana = ",count) print("-----------------------------\n") # state -30: Tripura df_tripura = df[df.State_Name == 'Tripura'] df_tripura_dist = df_tripura.groupby(['District_Name'])[['Crop_Year']].count() print(df_tripura_dist) print("-----------------------------") count = 0 for row in range(len(df_tripura_dist)): count = count+1 print("total no. of district in state -30: Tripura = ",count) print("-----------------------------\n") # state -31: Uttar Pradesh df_uttar = df[df.State_Name == 'Uttar Pradesh'] df_uttar_dist = df_uttar.groupby(['District_Name'])[['Crop_Year']].count() print(df_uttar_dist) print("-----------------------------") count = 0 for row in range(len(df_uttar_dist)): count = count+1 print("total no. of district in state -31: Uttar Pradesh = ",count) print("-----------------------------\n") # state -32: Uttarakhand df_uttarakhand = df[df.State_Name == 'Uttarakhand'] df_uttarakhand_dist = df_uttarakhand.groupby(['District_Name'])[['Crop_Year']].count() print(df_uttarakhand_dist) print("-----------------------------") count = 0 for row in range(len(df_uttarakhand_dist)): count = count+1 print("total no. of district in state -32: Uttarakhand = ",count) print("-----------------------------\n") # state -33: West Bengal df_wb = df[df.State_Name == 'West Bengal'] df_wb_dist = df_wb.groupby(['District_Name'])[['Crop_Year']].count() print(df_wb_dist) print("-----------------------------") count = 0 for row in range(len(df_wb_dist)): count = count+1 print("total no. of district in state -33: West Bengal = ",count) print("-----------------------------\n") # ----- indian area of production in year 2000 ------ df_area_2000 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2000]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2000]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2000]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2000]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2000]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2000]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2000]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2000]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2000]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2000]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2000]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2000]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2000]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2000]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2000]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2000]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2000]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2000]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2000]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2000]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2000]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2000]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2000]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2000]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2000]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2000]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2000]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2000]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2000]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2000]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2000]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2000]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2000]) ) # ----- indian area of production in year 2001 ------ df_area_2001 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2001]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2001]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2001]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2001]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2001]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2001]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2001]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2001]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2001]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2001]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2001]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2001]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2001]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2001]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2001]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2001]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2001]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2001]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2001]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2001]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2001]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2001]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2001]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2001]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2001]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2001]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2001]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2001]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2001]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2001]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2001]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2001]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2001]) ) # ----- indian area of production in year 2002 ------ df_area_2002 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2002]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2002]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2002]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2002]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2002]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2002]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2002]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2002]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2002]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2002]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2002]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2002]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2002]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2002]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2002]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2002]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2002]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2002]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2002]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2002]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2002]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2002]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2002]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2002]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2002]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2002]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2002]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2002]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2002]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2002]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2002]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2002]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2002]) ) # ----- indian area of production in year 2003 ------ df_area_2003 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2003]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2003]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2003]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2003]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2003]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2003]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2003]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2003]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2003]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2003]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2003]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2003]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2003]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2003]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2003]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2003]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2003]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2003]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2003]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2003]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2003]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2003]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2003]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2003]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2003]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2003]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2003]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2003]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2003]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2003]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2003]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2003]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2003]) ) # ----- indian area of production in year 2004 ------ df_area_2004 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2004]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2004]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2004]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2004]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2004]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2004]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2004]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2004]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2004]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2004]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2004]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2004]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2004]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2004]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2004]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2004]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2004]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2004]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2004]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2004]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2004]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2004]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2004]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2004]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2004]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2004]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2004]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2004]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2004]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2004]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2004]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2004]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2004]) ) # ----- indian area of production in year 2005 ------ df_area_2005 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2005]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2005]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2005]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2005]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2005]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2005]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2005]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2005]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2005]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2005]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2005]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2005]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2005]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2005]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2005]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2005]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2005]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2005]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2005]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2005]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2005]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2005]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2005]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2005]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2005]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2005]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2005]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2005]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2005]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2005]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2005]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2005]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2005]) ) # ----- indian area of production in year 2006 ------ df_area_2006 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2006]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2006]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2006]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2006]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2006]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2006]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2006]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2006]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2006]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2006]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2006]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2006]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2006]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2006]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2006]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2006]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2006]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2006]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2006]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2006]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2006]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2006]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2006]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2006]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2006]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2006]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2006]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2006]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2006]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2006]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2006]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2006]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2006]) ) # ----- indian area of production in year 2007 ------ df_area_2007 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2007]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2007]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2007]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2007]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2007]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2007]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2007]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2007]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2007]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2007]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2007]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2007]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2007]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2007]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2007]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2007]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2007]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2007]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2007]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2007]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2007]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2007]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2007]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2007]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2007]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2007]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2007]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2007]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2007]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2007]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2007]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2007]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2007]) ) # ----- indian area of production in year 2008 ------ df_area_2008 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2008]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2008]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2008]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2008]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2008]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2008]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2008]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2008]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2008]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2008]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2008]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2008]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2008]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2008]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2008]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2008]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2008]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2008]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2008]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2008]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2008]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2008]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2008]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2008]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2008]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2008]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2008]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2008]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2008]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2008]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2008]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2008]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2008]) ) # ----- indian area of production in year 2009 ------ df_area_2009 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2009]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2009]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2009]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2009]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2009]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2009]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2009]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2009]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2009]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2009]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2009]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2009]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2009]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2009]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2009]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2009]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2009]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2009]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2009]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2009]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2009]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2009]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2009]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2009]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2009]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2009]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2009]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2009]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2009]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2009]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2009]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2009]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2009]) ) # ----- indian area of production in year 2010 ------ df_area_2010 = ( sum(df_andaman['Area'][df_andaman['Crop_Year'] == 2010]) + sum(df_andhra['Area'][df_andhra['Crop_Year'] == 2010]) + sum(df_arunachal['Area'][df_arunachal['Crop_Year'] == 2010]) + sum(df_assam['Area'][df_assam['Crop_Year'] == 2010]) + sum(df_bihar['Area'][df_bihar['Crop_Year'] == 2010]) + sum(df_candigarh['Area'][df_candigarh['Crop_Year'] == 2010]) + sum(df_chattisgarh['Area'][df_chattisgarh['Crop_Year'] == 2010]) + sum(df_dadra['Area'][df_dadra['Crop_Year'] == 2010]) + sum(df_goa['Area'][df_goa['Crop_Year'] == 2010]) + sum(df_gujrat['Area'][df_gujrat['Crop_Year'] == 2010]) + sum(df_haryana['Area'][df_haryana['Crop_Year'] == 2010]) + sum(df_himachal['Area'][df_himachal['Crop_Year'] == 2010]) + sum(df_jammu['Area'][df_jammu['Crop_Year'] == 2010]) + sum(df_jharkand['Area'][df_jharkand['Crop_Year'] == 2010]) + sum(df_karnataka['Area'][df_karnataka['Crop_Year'] == 2010]) + sum(df_kerala['Area'][df_kerala['Crop_Year'] == 2010]) + sum(df_madhya['Area'][df_madhya['Crop_Year'] == 2010]) + sum(df_maharashtra['Area'][df_maharashtra['Crop_Year'] == 2010]) + sum(df_manipur['Area'][df_manipur['Crop_Year'] == 2010]) + sum(df_meghalaya['Area'][df_meghalaya['Crop_Year'] == 2010]) + sum(df_mizoram['Area'][df_mizoram['Crop_Year'] == 2010]) + sum(df_nagaland['Area'][df_nagaland['Crop_Year'] == 2010]) + sum(df_odisha['Area'][df_odisha['Crop_Year'] == 2010]) + sum(df_puducherry['Area'][df_puducherry['Crop_Year'] == 2010]) + sum(df_punjab['Area'][df_punjab['Crop_Year'] == 2010]) + sum(df_rajasthan['Area'][df_rajasthan['Crop_Year'] == 2010]) + sum(df_sikkim['Area'][df_sikkim['Crop_Year'] == 2010]) + sum(df_tamilnadu['Area'][df_tamilnadu['Crop_Year'] == 2010]) + sum(df_telangana['Area'][df_telangana['Crop_Year'] == 2010]) + sum(df_tripura['Area'][df_tripura['Crop_Year'] == 2010]) + sum(df_uttar['Area'][df_uttar['Crop_Year'] == 2010]) + sum(df_uttarakhand['Area'][df_uttarakhand['Crop_Year'] == 2010]) + sum(df_wb['Area'][df_wb['Crop_Year'] == 2010]) ) # ----- indian Production in year 2000 ------ df_Production_2000 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2000]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2000]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2000]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2000]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2000]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2000]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2000]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2000]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2000]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2000]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2000]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2000]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2000]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2000]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2000]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2000]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2000]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2000]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2000]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2000]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2000]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2000]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2000]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2000]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2000]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2000]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2000]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2000]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2000]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2000]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2000]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2000]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2000]) ) # ----- indian Production in year 2001 ------ df_Production_2001 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2001]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2001]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2001]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2001]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2001]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2001]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2001]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2001]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2001]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2001]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2001]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2001]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2001]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2001]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2001]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2001]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2001]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2001]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2001]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2001]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2001]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2001]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2001]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2001]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2001]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2001]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2001]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2001]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2001]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2001]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2001]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2001]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2001]) ) # ----- indian Production in year 2002 ------ df_Production_2002 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2002]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2002]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2002]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2002]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2002]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2002]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2002]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2002]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2002]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2002]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2002]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2002]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2002]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2002]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2002]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2002]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2002]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2002]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2002]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2002]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2002]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2002]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2002]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2002]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2002]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2002]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2002]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2002]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2002]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2002]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2002]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2002]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2002]) ) # ----- indian Production in year 2003 ------ df_Production_2003 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2003]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2003]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2003]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2003]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2003]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2003]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2003]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2003]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2003]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2003]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2003]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2003]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2003]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2003]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2003]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2003]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2003]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2003]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2003]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2003]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2003]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2003]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2003]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2003]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2003]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2003]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2003]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2003]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2003]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2003]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2003]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2003]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2003]) ) # ----- indian Production in year 2004 ------ df_Production_2004 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2004]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2004]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2004]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2004]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2004]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2004]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2004]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2004]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2004]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2004]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2004]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2004]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2004]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2004]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2004]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2004]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2004]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2004]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2004]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2004]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2004]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2004]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2004]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2004]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2004]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2004]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2004]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2004]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2004]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2004]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2004]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2004]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2004]) ) # ----- indian Production in year 2005 ------ df_Production_2005 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2005]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2005]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2005]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2005]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2005]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2005]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2005]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2005]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2005]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2005]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2005]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2005]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2005]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2005]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2005]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2005]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2005]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2005]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2005]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2005]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2005]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2005]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2005]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2005]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2005]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2005]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2005]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2005]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2005]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2005]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2005]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2005]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2005]) ) # ----- indian Production in year 2006 ------ df_Production_2006 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2006]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2006]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2006]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2006]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2006]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2006]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2006]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2006]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2006]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2006]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2006]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2006]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2006]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2006]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2006]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2006]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2006]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2006]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2006]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2006]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2006]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2006]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2006]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2006]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2006]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2006]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2006]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2006]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2006]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2006]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2006]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2006]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2006]) ) # ----- indian Production in year 2007 ------ df_Production_2007 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2007]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2007]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2007]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2007]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2007]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2007]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2007]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2007]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2007]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2007]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2007]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2007]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2007]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2007]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2007]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2007]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2007]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2007]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2007]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2007]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2007]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2007]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2007]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2007]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2007]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2007]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2007]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2007]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2007]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2007]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2007]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2007]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2007]) ) # ----- indian Production in year 2008 ------ df_Production_2008 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2008]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2008]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2008]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2008]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2008]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2008]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2008]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2008]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2008]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2008]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2008]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2008]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2008]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2008]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2008]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2008]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2008]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2008]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2008]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2008]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2008]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2008]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2008]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2008]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2008]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2008]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2008]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2008]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2008]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2008]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2008]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2008]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2008]) ) # ----- indian Production in year 2009 ------ df_Production_2009 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2009]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2009]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2009]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2009]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2009]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2009]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2009]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2009]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2009]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2009]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2009]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2009]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2009]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2009]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2009]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2009]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2009]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2009]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2009]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2009]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2009]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2009]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2009]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2009]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2009]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2009]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2009]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2009]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2009]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2009]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2009]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2009]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2009]) ) # ----- indian Production in year 2010 ------ df_Production_2010 = ( sum(df_andaman['Production'][df_andaman['Crop_Year'] == 2010]) + sum(df_andhra['Production'][df_andhra['Crop_Year'] == 2010]) + sum(df_arunachal['Production'][df_arunachal['Crop_Year'] == 2010]) + sum(df_assam['Production'][df_assam['Crop_Year'] == 2010]) + sum(df_bihar['Production'][df_bihar['Crop_Year'] == 2010]) + sum(df_candigarh['Production'][df_candigarh['Crop_Year'] == 2010]) + sum(df_chattisgarh['Production'][df_chattisgarh['Crop_Year'] == 2010]) + sum(df_dadra['Production'][df_dadra['Crop_Year'] == 2010]) + sum(df_goa['Production'][df_goa['Crop_Year'] == 2010]) + sum(df_gujrat['Production'][df_gujrat['Crop_Year'] == 2010]) + sum(df_haryana['Production'][df_haryana['Crop_Year'] == 2010]) + sum(df_himachal['Production'][df_himachal['Crop_Year'] == 2010]) + sum(df_jammu['Production'][df_jammu['Crop_Year'] == 2010]) + sum(df_jharkand['Production'][df_jharkand['Crop_Year'] == 2010]) + sum(df_karnataka['Production'][df_karnataka['Crop_Year'] == 2010]) + sum(df_kerala['Production'][df_kerala['Crop_Year'] == 2010]) + sum(df_madhya['Production'][df_madhya['Crop_Year'] == 2010]) + sum(df_maharashtra['Production'][df_maharashtra['Crop_Year'] == 2010]) + sum(df_manipur['Production'][df_manipur['Crop_Year'] == 2010]) + sum(df_meghalaya['Production'][df_meghalaya['Crop_Year'] == 2010]) + sum(df_mizoram['Production'][df_mizoram['Crop_Year'] == 2010]) + sum(df_nagaland['Production'][df_nagaland['Crop_Year'] == 2010]) + sum(df_odisha['Production'][df_odisha['Crop_Year'] == 2010]) + sum(df_puducherry['Production'][df_puducherry['Crop_Year'] == 2010]) + sum(df_punjab['Production'][df_punjab['Crop_Year'] == 2010]) + sum(df_rajasthan['Production'][df_rajasthan['Crop_Year'] == 2010]) + sum(df_sikkim['Production'][df_sikkim['Crop_Year'] == 2010]) + sum(df_tamilnadu['Production'][df_tamilnadu['Crop_Year'] == 2010]) + sum(df_telangana['Production'][df_telangana['Crop_Year'] == 2010]) + sum(df_tripura['Production'][df_tripura['Crop_Year'] == 2010]) + sum(df_uttar['Production'][df_uttar['Crop_Year'] == 2010]) + sum(df_uttarakhand['Production'][df_uttarakhand['Crop_Year'] == 2010]) + sum(df_wb['Production'][df_wb['Crop_Year'] == 2010]) ) def production_area_data(): print("\n----------------------------------------------------") print("\tArea of production in India (2000 to 2010)") print("-------------------------------------------------------\n") print("[01] Area of production in year 2000 =",df_area_2000) print("[02] Area of production in year 2001 =",df_area_2001) print("[03] Area of production in year 2002 =",df_area_2002) print("[04] Area of production in year 2003 =",df_area_2003) print("[05] Area of production in year 2004 =",df_area_2004) print("[06] Area of production in year 2005 =",df_area_2005) print("[07] Area of production in year 2006 =",df_area_2006) print("[08] Area of production in year 2007 =",df_area_2007) print("[09] Area of production in year 2008 =",df_area_2008) print("[10] Area of production in year 2009 =",df_area_2009) print("[11] Area of production in year 2010 =",df_area_2010) print("-------------------------------------------------------\n") def production_data(): print("\n----------------------------------------------------") print("\tProduction in India (2000 to 2010)") print("-------------------------------------------------------\n") print("[01] Production in year 2000 =",df_Production_2000) print("[02] Production in year 2001 =",df_Production_2001) print("[03] Production in year 2002 =",df_Production_2002) print("[04] Production in year 2003 =",df_Production_2003) print("[05] Production in year 2004 =",df_Production_2004) print("[06] Production in year 2005 =",df_Production_2005) print("[07] Production in year 2006 =",df_Production_2006) print("[08] Production in year 2007 =",df_Production_2007) print("[09] Production in year 2008 =",df_Production_2008) print("[10] Production in year 2009 =",df_Production_2009) print("[11] Production in year 2010 =",df_Production_2010) print("-------------------------------------------------------\n") df_year = (2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010) df_area_2000_10 = (df_area_2000//pow(10,5), df_area_2001//pow(10,5), df_area_2002//pow(10,5), df_area_2003//pow(10,5), df_area_2004//pow(10,5), df_area_2005//pow(10,5), df_area_2005//pow(10,5), df_area_2005//pow(10,5), df_area_2005//pow(10,5), df_area_2009//pow(10,5), df_area_2010//pow(10,5)) df_Production_2000_10 = ( df_Production_2000//pow(10,6), df_Production_2001//pow(10,6), df_Production_2002//pow(10,6), df_Production_2003//pow(10,6), df_Production_2004//pow(10,6), df_Production_2006//pow(10,6), df_Production_2006//pow(10,6), df_Production_2006//pow(10,6), df_Production_2006//pow(10,6), df_Production_2009//pow(10,6), df_Production_2010//pow(10,6)) def area_and_production_plot(): plt.title("Crop_year vs. (production_area & production)[2000 to 2010]") plt.plot(df_year,df_area_2000_10,linestyle="dashed",label="Area * 10^5") plt.plot(df_year,df_Production_2000_10,label="Production * 10^6") plt.legend() plt.show() # [area of production] predection model design using linear regression def estimate_coef(x, y): n = np.size(x) # size of data set mean_x = np.mean(x) mean_y = np.mean(y) xy = np.sum(y*x) - n*(mean_y)*(mean_x) xx = np.sum(x*x) - n*(mean_x)*(mean_x) b_1 = xy / xx b_0 = (mean_y) - b_1*(mean_x) return(b_0,b_1) def production_area_prediction_2025(x,y,b,bm,a): # Create perdiction upto 2023 # Using Equation : y = b_0 + (b_1 * x) df_area_2010_1 = df_area_2010//pow(10,5) df_area_2011 = bm + (a * 2011) df_area_2012 = bm + (a * 2012) df_area_2013 = bm + (a * 2013) df_area_2014 = bm + (a * 2014) df_area_2015 = bm + (a * 2015) df_area_2016 = bm + (a * 2016) df_area_2017 = bm + (a * 2017) df_area_2018 = bm + (a * 2018) df_area_2019 = bm + (a * 2019) df_area_2020 = bm + (a * 2020) df_area_2021 = bm + (a * 2021) df_area_2022 = bm + (a * 2022) df_area_2023 = bm + (a * 2023) df_area_2024 = bm + (a * 2024) df_area_2025 = bm + (a * 2025) df_2000_2023 =(df_area_2010_1, df_area_2011,df_area_2012,df_area_2013, df_area_2014,df_area_2015,df_area_2016, df_area_2017,df_area_2018,df_area_2019, df_area_2020,df_area_2021,df_area_2022, df_area_2023,df_area_2024,df_area_2025 ) df_year1 = (2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021, 2022,2023,2024,2025) # plot regression line plt.plot(x, y, color = "m",marker = "o",label="Actual production area * 10^5") y_pred = b[0] + b[1]*x plt.plot(x, y_pred, color = "g",label="Regression line") plt.xlabel('year -- >') plt.ylabel('Area of production --->') # plot prediction line plt.title("Prediction for production area from 2011 to 2025 ") plt.plot(df_year1,df_2000_2023,linestyle="dashed",label="Predicted production area * 10^5") plt.legend() plt.show() mean_y = np.mean(y) area_growth_2011 = (((df_area_2011)-(mean_y))/(mean_y))*100 area_growth_2012 = (((df_area_2012)-(mean_y))/(mean_y))*100 area_growth_2013 = (((df_area_2013)-(mean_y))/(mean_y))*100 area_growth_2014 = (((df_area_2014)-(mean_y))/(mean_y))*100 area_growth_2015 = (((df_area_2015)-(mean_y))/(mean_y))*100 area_growth_2016 = (((df_area_2016)-(mean_y))/(mean_y))*100 area_growth_2017 = (((df_area_2017)-(mean_y))/(mean_y))*100 area_growth_2018 = (((df_area_2018)-(mean_y))/(mean_y))*100 area_growth_2019 = (((df_area_2019)-(mean_y))/(mean_y))*100 area_growth_2020 = (((df_area_2020)-(mean_y))/(mean_y))*100 area_growth_2021 = (((df_area_2021)-(mean_y))/(mean_y))*100 area_growth_2022 = (((df_area_2022)-(mean_y))/(mean_y))*100 area_growth_2023 = (((df_area_2023)-(mean_y))/(mean_y))*100 area_growth_2024 = (((df_area_2024)-(mean_y))/(mean_y))*100 area_growth_2025 = (((df_area_2025)-(mean_y))/(mean_y))*100 print("\n----------------------------------------------------------") print("production area growth according to prediction model") print("--------------------------------------------------------\n") print("Production area gowth in 2011 = ",area_growth_2011,"%") print("Production area gowth in 2012 = ",area_growth_2012,"%") print("Production area gowth in 2013 = ",area_growth_2013,"%") print("Production area gowth in 2014 = ",area_growth_2014,"%") print("Production area gowth in 2015 = ",area_growth_2015,"%") print("Production area gowth in 2016 = ",area_growth_2016,"%") print("Production area gowth in 2017 = ",area_growth_2017,"%") print("Production area gowth in 2018 = ",area_growth_2018,"%") print("Production area gowth in 2019 = ",area_growth_2019,"%") print("Production area gowth in 2020 = ",area_growth_2020,"%") print("Production area gowth in 2021 = ",area_growth_2021,"%") print("Production area gowth in 2022 = ",area_growth_2022,"%") print("Production area gowth in 2023 = ",area_growth_2023,"%") print("Production area gowth in 2024 = ",area_growth_2024,"%") print("Production area gowth in 2025 = ",area_growth_2025,"%") print("--------------------------------------------------------\n") #---- Production prediction model ----- def estimate_coef1(x, y): n = np.size(x) # size of data set mean_x = np.mean(x) mean_y = np.mean(y) xy = np.sum(y*x) - n*(mean_y)*(mean_x) xx = np.sum(x*x) - n*(mean_x)*(mean_x) b_1 = xy / xx b_0 = (mean_y) - b_1*(mean_x) return(b_0,b_1) def Production_prediction_2025(x,y,b,bm,a): # Create perdiction upto 2023 # Using Equation : y = b_0 + (b_1 * x) df_Production_2010_1 = df_Production_2010//pow(10,6) df_Production_2011 = bm + (a * 2011) df_Production_2012 = bm + (a * 2012) df_Production_2013 = bm + (a * 2013) df_Production_2014 = bm + (a * 2014) df_Production_2015 = bm + (a * 2015) df_Production_2016 = bm + (a * 2016) df_Production_2017 = bm + (a * 2017) df_Production_2018 = bm + (a * 2018) df_Production_2019 = bm + (a * 2019) df_Production_2020 = bm + (a * 2020) df_Production_2021 = bm + (a * 2021) df_Production_2022 = bm + (a * 2022) df_Production_2023 = bm + (a * 2023) df_Production_2024 = bm + (a * 2024) df_Production_2025 = bm + (a * 2025) df_production_2000_2023 =(df_Production_2010_1, df_Production_2011,df_Production_2012,df_Production_2013, df_Production_2014,df_Production_2015,df_Production_2016, df_Production_2017,df_Production_2018,df_Production_2019, df_Production_2020,df_Production_2021,df_Production_2022, df_Production_2023,df_Production_2024,df_Production_2025 ) df_year1 = (2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021, 2022,2023,2024,2025) # plot regression line plt.plot(x, y, color = "m",marker = "o",label="Actual production * 10^6") y_pred = b[0] + b[1]*x plt.plot(x, y_pred, color = "g",label="Regression line") plt.xlabel('year -- >') plt.ylabel('production --->') # plot prediction line plt.title("Prediction for Crop Production from 2011 to 2025 ") plt.plot(df_year1,df_production_2000_2023,linestyle="dashed",label="Predicted Production * 10^6") plt.legend() plt.show() mean_y = np.mean(y) Production_growth_2011 = (((df_Production_2011)-(mean_y))/(mean_y))*100 Production_growth_2012 = (((df_Production_2012)-(mean_y))/(mean_y))*100 Production_growth_2013 = (((df_Production_2013)-(mean_y))/(mean_y))*100 Production_growth_2014 = (((df_Production_2014)-(mean_y))/(mean_y))*100 Production_growth_2015 = (((df_Production_2015)-(mean_y))/(mean_y))*100 Production_growth_2016 = (((df_Production_2016)-(mean_y))/(mean_y))*100 Production_growth_2017 = (((df_Production_2017)-(mean_y))/(mean_y))*100 Production_growth_2018 = (((df_Production_2018)-(mean_y))/(mean_y))*100 Production_growth_2019 = (((df_Production_2019)-(mean_y))/(mean_y))*100 Production_growth_2020 = (((df_Production_2020)-(mean_y))/(mean_y))*100 Production_growth_2021 = (((df_Production_2021)-(mean_y))/(mean_y))*100 Production_growth_2022 = (((df_Production_2022)-(mean_y))/(mean_y))*100 Production_growth_2023 = (((df_Production_2023)-(mean_y))/(mean_y))*100 Production_growth_2024 = (((df_Production_2024)-(mean_y))/(mean_y))*100 Production_growth_2025 = (((df_Production_2025)-(mean_y))/(mean_y))*100 print("\n----------------------------------------------------------") print("Production growth according to prediction model") print("--------------------------------------------------------\n") print("Production gowth in 2011 = ",Production_growth_2011,"%") print("Production gowth in 2012 = ",Production_growth_2012,"%") print("Production gowth in 2013 = ",Production_growth_2013,"%") print("Production gowth in 2014 = ",Production_growth_2014,"%") print("Production gowth in 2015 = ",Production_growth_2015,"%") print("Production gowth in 2016 = ",Production_growth_2016,"%") print("Production gowth in 2017 = ",Production_growth_2017,"%") print("Production gowth in 2018 = ",Production_growth_2018,"%") print("Production gowth in 2019 = ",Production_growth_2019,"%") print("Production gowth in 2020 = ",Production_growth_2020,"%") print("Production gowth in 2021 = ",Production_growth_2021,"%") print("Production gowth in 2022 = ",Production_growth_2022,"%") print("Production gowth in 2023 = ",Production_growth_2023,"%") print("Production gowth in 2024 = ",Production_growth_2024,"%") print("Production gowth in 2025 = ",Production_growth_2025,"%") print("--------------------------------------------------------\n") def agriculture_main(): ch = 1 while (ch == 1): print("-----------------------------------------") print("\tMain menu (Agriculture Data Aanlysis) :") print("-----------------------------------------\n") print("[1] Print dimension of the data file") print("[2] Print column names of the data file") print("[3] Print available states in the data") print("[4] Print districts of all states") print("[5] Print production data") print("[6] Print production area data") print("[7] Plot area and production (without prediction)") print("[8] Area prediction model and print growth rate") print("[9] Production prediction model and print growth rate") print("---------------------------------------") op = input("enter your option : ") op1 = int(op,10) if op1 == 1: dimension() elif op1 == 2: column_names() elif op1 == 3: states() elif op1 == 4 : district_of_all_states() elif op1 == 5: production_data() elif op1 == 6: production_area_data() elif op1 == 7: area_and_production_plot() break elif op1 == 8: x = np.array(df_year) y = np.array(df_area_2000_10) b = estimate_coef(x, y) print("\n----------------------") print("Estimated coefficients for area:\n----------------------\n") print("b_0 = {}\nb_1 = {}".format(b[0], b[1])) print("----------------------\n") production_area_prediction_2025(x,y,b,b[0],b[1]) break elif op1 == 9 : x = np.array(df_year) y = np.array(df_Production_2000_10) b = estimate_coef1(x, y) print("\n----------------------") print("Estimated coefficients for production:\n----------------------\n") print("b_0 = {}\nb_1 = {}".format(b[0], b[1])) print("----------------------\n") Production_prediction_2025(x,y,b,b[0],b[1]) break else: print("wrong input !!") #------- exit process design -------- ch1 = input("enter:\n[0] for exit\n[1] for continue : ") ch =int(ch1,10) if __name__ == "__main__": agriculture_main()