# -*- 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:") print("\n-----------------------------------\n") # Question – A : get row and column numbers print('---------------------------------------------') print("Dimension of the data frame = ",df.shape) print('---------------------------------------------') # Question – B : print column names : print('------------------------\n Column names as follows :') print('------------------------\n') count = 0 for col in df.columns: print(count,"-->",col) count = count+1 print("\n-----------------------------\n") #Question – C : State_Name (using GROUP BY method) and no. of states : state_names = df.groupby(['State_Name'])[['District_Name']].count() print("---------------------------------") 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") #Question-(5) West Bengal print("--- State-5 : 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) # crop year in West Bengal print("--- Crop year in West Bengal -----") df_wb_year = df_wb.groupby(['Crop_Year'])[['Crop_Year']].count() print(df_wb_year) # crop types in West Bengal print("---- Crop Types in West Bengal -----") df_wb_crop = df_wb.groupby(['Crop'])[['Crop']].count() print(df_wb_crop) # details of wb : [1] 24 PARAGANAS NORTH print("---- Details of wb : [1] 24 PARAGANAS NORTH ----") df_wb_1 = df_wb[df_wb.District_Name == '24 PARAGANAS NORTH'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_1_1997 = df_wb_1.loc[df_wb_1['Crop_Year'] == 1997,'Area':'Production'] df_wb_1_1997_sum = df_wb_1_1997.sum(axis = 0, skipna = True) print(df_wb_1_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_1_1998 = df_wb_1.loc[df_wb_1['Crop_Year'] == 1998,'Area':'Production'] df_wb_1_1998_sum = df_wb_1_1998.sum(axis = 0, skipna = True) print(df_wb_1_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_1_1999 = df_wb_1.loc[df_wb_1['Crop_Year'] == 1999,'Area':'Production'] df_wb_1_1999_sum = df_wb_1_1999.sum(axis = 0, skipna = True) print(df_wb_1_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_1_2000 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2000,'Area':'Production'] df_wb_1_2000_sum = df_wb_1_2000.sum(axis = 0, skipna = True) print(df_wb_1_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_1_2001 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2001,'Area':'Production'] df_wb_1_2001_sum = df_wb_1_2001.sum(axis = 0, skipna = True) print(df_wb_1_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_1_2002 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2002,'Area':'Production'] df_wb_1_2002_sum = df_wb_1_2002.sum(axis = 0, skipna = True) print(df_wb_1_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_1_2003 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2003,'Area':'Production'] df_wb_1_2003_sum = df_wb_1_2003.sum(axis = 0, skipna = True) print(df_wb_1_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_1_2004 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2004,'Area':'Production'] df_wb_1_2004_sum = df_wb_1_2004.sum(axis = 0, skipna = True) print(df_wb_1_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_1_2005 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2005,'Area':'Production'] df_wb_1_2005_sum = df_wb_1_2005.sum(axis = 0, skipna = True) print(df_wb_1_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_1_2006 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2006,'Area':'Production'] df_wb_1_2006_sum = df_wb_1_2006.sum(axis = 0, skipna = True) print(df_wb_1_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_1_2007 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2007,'Area':'Production'] df_wb_1_2007_sum = df_wb_1_2007.sum(axis = 0, skipna = True) print(df_wb_1_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_1_2008 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2008,'Area':'Production'] df_wb_1_2008_sum = df_wb_1_2008.sum(axis = 0, skipna = True) print(df_wb_1_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_1_2009 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2009,'Area':'Production'] df_wb_1_2009_sum = df_wb_1_2009.sum(axis = 0, skipna = True) print(df_wb_1_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_1_2010 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2010,'Area':'Production'] df_wb_1_2010_sum = df_wb_1_2010.sum(axis = 0, skipna = True) print(df_wb_1_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_1_2011 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2011,'Area':'Production'] df_wb_1_2011_sum = df_wb_1_2011.sum(axis = 0, skipna = True) print(df_wb_1_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_1_2012 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2012,'Area':'Production'] df_wb_1_2012_sum = df_wb_1_2012.sum(axis = 0, skipna = True) print(df_wb_1_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_1_2013 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2013,'Area':'Production'] df_wb_1_2013_sum = df_wb_1_2013.sum(axis = 0, skipna = True) print(df_wb_1_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_1_2014 = df_wb_1.loc[df_wb_1['Crop_Year'] == 2014,'Area':'Production'] df_wb_1_2014_sum = df_wb_1_2014.sum(axis = 0, skipna = True) print(df_wb_1_2014_sum) print("---------------------------------") # details of wb : [2] 24 PARAGANAS SOUTH print("--- Details of wb : [2] 24 PARAGANAS SOUTH ----") df_wb_2 = df_wb[df_wb.District_Name == '24 PARAGANAS SOUTH'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_2_1997 = df_wb_2.loc[df_wb_2['Crop_Year'] == 1997,'Area':'Production'] df_wb_2_1997_sum = df_wb_2_1997.sum(axis = 0, skipna = True) print(df_wb_2_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_2_1998 = df_wb_2.loc[df_wb_2['Crop_Year'] == 1998,'Area':'Production'] df_wb_2_1998_sum = df_wb_2_1998.sum(axis = 0, skipna = True) print(df_wb_2_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_2_1999 = df_wb_2.loc[df_wb_2['Crop_Year'] == 1999,'Area':'Production'] df_wb_2_1999_sum = df_wb_2_1999.sum(axis = 0, skipna = True) print(df_wb_2_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_2_2000 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2000,'Area':'Production'] df_wb_2_2000_sum = df_wb_2_2000.sum(axis = 0, skipna = True) print(df_wb_2_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_2_2001 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2001,'Area':'Production'] df_wb_2_2001_sum = df_wb_2_2001.sum(axis = 0, skipna = True) print(df_wb_2_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_2_2002 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2002,'Area':'Production'] df_wb_2_2002_sum = df_wb_2_2002.sum(axis = 0, skipna = True) print(df_wb_2_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_2_2003 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2003,'Area':'Production'] df_wb_2_2003_sum = df_wb_2_2003.sum(axis = 0, skipna = True) print(df_wb_2_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_2_2004 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2004,'Area':'Production'] df_wb_2_2004_sum = df_wb_2_2004.sum(axis = 0, skipna = True) print(df_wb_2_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_2_2005 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2005,'Area':'Production'] df_wb_2_2005_sum = df_wb_2_2005.sum(axis = 0, skipna = True) print(df_wb_2_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_2_2006 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2006,'Area':'Production'] df_wb_2_2006_sum = df_wb_2_2006.sum(axis = 0, skipna = True) print(df_wb_2_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_2_2007 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2007,'Area':'Production'] df_wb_2_2007_sum = df_wb_2_2007.sum(axis = 0, skipna = True) print(df_wb_2_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_2_2008 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2008,'Area':'Production'] df_wb_2_2008_sum = df_wb_2_2008.sum(axis = 0, skipna = True) print(df_wb_2_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_2_2009 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2009,'Area':'Production'] df_wb_2_2009_sum = df_wb_2_2009.sum(axis = 0, skipna = True) print(df_wb_2_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_2_2010 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2010,'Area':'Production'] df_wb_2_2010_sum = df_wb_2_2010.sum(axis = 0, skipna = True) print(df_wb_2_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_2_2011 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2011,'Area':'Production'] df_wb_2_2011_sum = df_wb_2_2011.sum(axis = 0, skipna = True) print(df_wb_2_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_2_2012 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2012,'Area':'Production'] df_wb_2_2012_sum = df_wb_2_2012.sum(axis = 0, skipna = True) print(df_wb_2_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_2_2013 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2013,'Area':'Production'] df_wb_2_2013_sum = df_wb_2_2013.sum(axis = 0, skipna = True) print(df_wb_2_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_2_2014 = df_wb_2.loc[df_wb_2['Crop_Year'] == 2014,'Area':'Production'] df_wb_2_2014_sum = df_wb_2_2014.sum(axis = 0, skipna = True) print(df_wb_2_2014_sum) print("---------------------------------") # details of wb : [3] BANKURA print("---- Details of wb : [3] BANKURA -----") df_wb_3 = df_wb[df_wb.District_Name == 'BANKURA'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_3_1997 = df_wb_3.loc[df_wb_3['Crop_Year'] == 1997,'Area':'Production'] df_wb_3_1997_sum = df_wb_3_1997.sum(axis = 0, skipna = True) print(df_wb_3_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_3_1998 = df_wb_3.loc[df_wb_3['Crop_Year'] == 1998,'Area':'Production'] df_wb_3_1998_sum = df_wb_3_1998.sum(axis = 0, skipna = True) print(df_wb_3_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_3_1999 = df_wb_3.loc[df_wb_3['Crop_Year'] == 1999,'Area':'Production'] df_wb_3_1999_sum = df_wb_3_1999.sum(axis = 0, skipna = True) print(df_wb_3_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_3_2000 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2000,'Area':'Production'] df_wb_3_2000_sum = df_wb_3_2000.sum(axis = 0, skipna = True) print(df_wb_3_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_3_2001 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2001,'Area':'Production'] df_wb_3_2001_sum = df_wb_3_2001.sum(axis = 0, skipna = True) print(df_wb_3_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_3_2002 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2002,'Area':'Production'] df_wb_3_2002_sum = df_wb_3_2002.sum(axis = 0, skipna = True) print(df_wb_3_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_3_2003 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2003,'Area':'Production'] df_wb_3_2003_sum = df_wb_3_2003.sum(axis = 0, skipna = True) print(df_wb_3_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_3_2004 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2004,'Area':'Production'] df_wb_3_2004_sum = df_wb_3_2004.sum(axis = 0, skipna = True) print(df_wb_3_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_3_2005 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2005,'Area':'Production'] df_wb_3_2005_sum = df_wb_3_2005.sum(axis = 0, skipna = True) print(df_wb_3_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_3_2006 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2006,'Area':'Production'] df_wb_3_2006_sum = df_wb_3_2006.sum(axis = 0, skipna = True) print(df_wb_3_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_3_2007 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2007,'Area':'Production'] df_wb_3_2007_sum = df_wb_3_2007.sum(axis = 0, skipna = True) print(df_wb_3_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_3_2008 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2008,'Area':'Production'] df_wb_3_2008_sum = df_wb_3_2008.sum(axis = 0, skipna = True) print(df_wb_3_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_3_2009 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2009,'Area':'Production'] df_wb_3_2009_sum = df_wb_3_2009.sum(axis = 0, skipna = True) print(df_wb_3_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_3_2010 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2010,'Area':'Production'] df_wb_3_2010_sum = df_wb_3_2010.sum(axis = 0, skipna = True) print(df_wb_3_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_3_2011 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2011,'Area':'Production'] df_wb_3_2011_sum = df_wb_3_2011.sum(axis = 0, skipna = True) print(df_wb_3_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_3_2012 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2012,'Area':'Production'] df_wb_3_2012_sum = df_wb_3_2012.sum(axis = 0, skipna = True) print(df_wb_3_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_3_2013 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2013,'Area':'Production'] df_wb_3_2013_sum = df_wb_3_2013.sum(axis = 0, skipna = True) print(df_wb_3_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_3_2014 = df_wb_3.loc[df_wb_3['Crop_Year'] == 2014,'Area':'Production'] df_wb_3_2014_sum = df_wb_3_2014.sum(axis = 0, skipna = True) print(df_wb_3_2014_sum) print("---------------------------------") # details of wb : [4] BARDHAMAN print("---- Details of wb : [4] BARDHAMAN -----") df_wb_4 = df_wb[df_wb.District_Name == 'BARDHAMAN'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_4_1997 = df_wb_4.loc[df_wb_4['Crop_Year'] == 1997,'Area':'Production'] df_wb_4_1997_sum = df_wb_4_1997.sum(axis = 0, skipna = True) print(df_wb_4_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_4_1998 = df_wb_4.loc[df_wb_4['Crop_Year'] == 1998,'Area':'Production'] df_wb_4_1998_sum = df_wb_4_1998.sum(axis = 0, skipna = True) print(df_wb_4_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_4_1999 = df_wb_4.loc[df_wb_4['Crop_Year'] == 1999,'Area':'Production'] df_wb_4_1999_sum = df_wb_4_1999.sum(axis = 0, skipna = True) print(df_wb_4_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_4_2000 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2000,'Area':'Production'] df_wb_4_2000_sum = df_wb_4_2000.sum(axis = 0, skipna = True) print(df_wb_4_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_4_2001 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2001,'Area':'Production'] df_wb_4_2001_sum = df_wb_4_2001.sum(axis = 0, skipna = True) print(df_wb_4_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_4_2002 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2002,'Area':'Production'] df_wb_4_2002_sum = df_wb_4_2002.sum(axis = 0, skipna = True) print(df_wb_4_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_4_2003 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2003,'Area':'Production'] df_wb_4_2003_sum = df_wb_4_2003.sum(axis = 0, skipna = True) print(df_wb_4_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_4_2004 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2004,'Area':'Production'] df_wb_4_2004_sum = df_wb_4_2004.sum(axis = 0, skipna = True) print(df_wb_4_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_4_2005 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2005,'Area':'Production'] df_wb_4_2005_sum = df_wb_4_2005.sum(axis = 0, skipna = True) print(df_wb_4_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_4_2006 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2006,'Area':'Production'] df_wb_4_2006_sum = df_wb_4_2006.sum(axis = 0, skipna = True) print(df_wb_4_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_4_2007 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2007,'Area':'Production'] df_wb_4_2007_sum = df_wb_4_2007.sum(axis = 0, skipna = True) print(df_wb_4_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_4_2008 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2008,'Area':'Production'] df_wb_4_2008_sum = df_wb_4_2008.sum(axis = 0, skipna = True) print(df_wb_4_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_4_2009 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2009,'Area':'Production'] df_wb_4_2009_sum = df_wb_4_2009.sum(axis = 0, skipna = True) print(df_wb_4_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_4_2010 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2010,'Area':'Production'] df_wb_4_2010_sum = df_wb_4_2010.sum(axis = 0, skipna = True) print(df_wb_4_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_4_2011 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2011,'Area':'Production'] df_wb_4_2011_sum = df_wb_4_2011.sum(axis = 0, skipna = True) print(df_wb_4_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_4_2012 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2012,'Area':'Production'] df_wb_4_2012_sum = df_wb_4_2012.sum(axis = 0, skipna = True) print(df_wb_4_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_4_2013 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2013,'Area':'Production'] df_wb_4_2013_sum = df_wb_4_2013.sum(axis = 0, skipna = True) print(df_wb_4_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_4_2014 = df_wb_4.loc[df_wb_4['Crop_Year'] == 2014,'Area':'Production'] df_wb_4_2014_sum = df_wb_4_2014.sum(axis = 0, skipna = True) print(df_wb_4_2014_sum) print("---------------------------------") # details of wb : [5] BIRBHUM print("--- Details of wb : [5] BIRBHUM -----") df_wb_5 = df_wb[df_wb.District_Name == 'BIRBHUM'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_5_1997 = df_wb_5.loc[df_wb_5['Crop_Year'] == 1997,'Area':'Production'] df_wb_5_1997_sum = df_wb_5_1997.sum(axis = 0, skipna = True) print(df_wb_5_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_5_1998 = df_wb_5.loc[df_wb_5['Crop_Year'] == 1998,'Area':'Production'] df_wb_5_1998_sum = df_wb_5_1998.sum(axis = 0, skipna = True) print(df_wb_5_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_5_1999 = df_wb_5.loc[df_wb_5['Crop_Year'] == 1999,'Area':'Production'] df_wb_5_1999_sum = df_wb_5_1999.sum(axis = 0, skipna = True) print(df_wb_5_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_5_2000 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2000,'Area':'Production'] df_wb_5_2000_sum = df_wb_5_2000.sum(axis = 0, skipna = True) print(df_wb_5_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_5_2001 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2001,'Area':'Production'] df_wb_5_2001_sum = df_wb_5_2001.sum(axis = 0, skipna = True) print(df_wb_5_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_5_2002 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2002,'Area':'Production'] df_wb_5_2002_sum = df_wb_5_2002.sum(axis = 0, skipna = True) print(df_wb_5_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_5_2003 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2003,'Area':'Production'] df_wb_5_2003_sum = df_wb_5_2003.sum(axis = 0, skipna = True) print(df_wb_5_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_5_2004 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2004,'Area':'Production'] df_wb_5_2004_sum = df_wb_5_2004.sum(axis = 0, skipna = True) print(df_wb_5_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_5_2005 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2005,'Area':'Production'] df_wb_5_2005_sum = df_wb_5_2005.sum(axis = 0, skipna = True) print(df_wb_5_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_5_2006 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2006,'Area':'Production'] df_wb_5_2006_sum = df_wb_5_2006.sum(axis = 0, skipna = True) print(df_wb_5_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_5_2007 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2007,'Area':'Production'] df_wb_5_2007_sum = df_wb_5_2007.sum(axis = 0, skipna = True) print(df_wb_5_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_5_2008 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2008,'Area':'Production'] df_wb_5_2008_sum = df_wb_5_2008.sum(axis = 0, skipna = True) print(df_wb_5_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_5_2009 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2009,'Area':'Production'] df_wb_5_2009_sum = df_wb_5_2009.sum(axis = 0, skipna = True) print(df_wb_5_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_5_2010 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2010,'Area':'Production'] df_wb_5_2010_sum = df_wb_5_2010.sum(axis = 0, skipna = True) print(df_wb_5_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_5_2011 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2011,'Area':'Production'] df_wb_5_2011_sum = df_wb_5_2011.sum(axis = 0, skipna = True) print(df_wb_5_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_5_2012 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2012,'Area':'Production'] df_wb_5_2012_sum = df_wb_5_2012.sum(axis = 0, skipna = True) print(df_wb_5_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_5_2013 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2013,'Area':'Production'] df_wb_5_2013_sum = df_wb_5_2013.sum(axis = 0, skipna = True) print(df_wb_5_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_5_2014 = df_wb_5.loc[df_wb_5['Crop_Year'] == 2014,'Area':'Production'] df_wb_5_2014_sum = df_wb_5_2014.sum(axis = 0, skipna = True) print(df_wb_5_2014_sum) print("---------------------------------") # details of wb : [6] COOCHBEHAR print("---- Details of wb : [6] COOCHBEHAR ----- ") df_wb_6 = df_wb[df_wb.District_Name == 'COOCHBEHAR'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_6_1997 = df_wb_6.loc[df_wb_6['Crop_Year'] == 1997,'Area':'Production'] df_wb_6_1997_sum = df_wb_6_1997.sum(axis = 0, skipna = True) print(df_wb_6_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_6_1998 = df_wb_6.loc[df_wb_6['Crop_Year'] == 1998,'Area':'Production'] df_wb_6_1998_sum = df_wb_6_1998.sum(axis = 0, skipna = True) print(df_wb_6_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_6_1999 = df_wb_6.loc[df_wb_6['Crop_Year'] == 1999,'Area':'Production'] df_wb_6_1999_sum = df_wb_6_1999.sum(axis = 0, skipna = True) print(df_wb_6_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_6_2000 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2000,'Area':'Production'] df_wb_6_2000_sum = df_wb_6_2000.sum(axis = 0, skipna = True) print(df_wb_6_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_6_2001 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2001,'Area':'Production'] df_wb_6_2001_sum = df_wb_6_2001.sum(axis = 0, skipna = True) print(df_wb_6_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_6_2002 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2002,'Area':'Production'] df_wb_6_2002_sum = df_wb_6_2002.sum(axis = 0, skipna = True) print(df_wb_6_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_6_2003 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2003,'Area':'Production'] df_wb_6_2003_sum = df_wb_6_2003.sum(axis = 0, skipna = True) print(df_wb_6_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_6_2004 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2004,'Area':'Production'] df_wb_6_2004_sum = df_wb_6_2004.sum(axis = 0, skipna = True) print(df_wb_6_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_6_2005 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2005,'Area':'Production'] df_wb_6_2005_sum = df_wb_6_2005.sum(axis = 0, skipna = True) print(df_wb_6_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_6_2006 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2006,'Area':'Production'] df_wb_6_2006_sum = df_wb_6_2006.sum(axis = 0, skipna = True) print(df_wb_6_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_6_2007 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2007,'Area':'Production'] df_wb_6_2007_sum = df_wb_6_2007.sum(axis = 0, skipna = True) print(df_wb_6_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_6_2008 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2008,'Area':'Production'] df_wb_6_2008_sum = df_wb_6_2008.sum(axis = 0, skipna = True) print(df_wb_6_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_6_2009 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2009,'Area':'Production'] df_wb_6_2009_sum = df_wb_6_2009.sum(axis = 0, skipna = True) print(df_wb_6_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_6_2010 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2010,'Area':'Production'] df_wb_6_2010_sum = df_wb_6_2010.sum(axis = 0, skipna = True) print(df_wb_6_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_6_2011 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2011,'Area':'Production'] df_wb_6_2011_sum = df_wb_6_2011.sum(axis = 0, skipna = True) print(df_wb_6_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_6_2012 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2012,'Area':'Production'] df_wb_6_2012_sum = df_wb_6_2012.sum(axis = 0, skipna = True) print(df_wb_6_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_6_2013 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2013,'Area':'Production'] df_wb_6_2013_sum = df_wb_6_2013.sum(axis = 0, skipna = True) print(df_wb_6_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_6_2014 = df_wb_6.loc[df_wb_6['Crop_Year'] == 2014,'Area':'Production'] df_wb_6_2014_sum = df_wb_6_2014.sum(axis = 0, skipna = True) print(df_wb_6_2014_sum) print("---------------------------------") # details of wb : [7] DARJEELING print("--- details of wb : [7] DARJEELING -----") df_wb_7 = df_wb[df_wb.District_Name == 'DARJEELING'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_7_1997 = df_wb_7.loc[df_wb_7['Crop_Year'] == 1997,'Area':'Production'] df_wb_7_1997_sum = df_wb_7_1997.sum(axis = 0, skipna = True) print(df_wb_7_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_7_1998 = df_wb_7.loc[df_wb_7['Crop_Year'] == 1998,'Area':'Production'] df_wb_7_1998_sum = df_wb_7_1998.sum(axis = 0, skipna = True) print(df_wb_7_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_7_1999 = df_wb_7.loc[df_wb_7['Crop_Year'] == 1999,'Area':'Production'] df_wb_7_1999_sum = df_wb_7_1999.sum(axis = 0, skipna = True) print(df_wb_7_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_7_2000 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2000,'Area':'Production'] df_wb_7_2000_sum = df_wb_7_2000.sum(axis = 0, skipna = True) print(df_wb_7_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_7_2001 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2001,'Area':'Production'] df_wb_7_2001_sum = df_wb_7_2001.sum(axis = 0, skipna = True) print(df_wb_7_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_7_2002 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2002,'Area':'Production'] df_wb_7_2002_sum = df_wb_7_2002.sum(axis = 0, skipna = True) print(df_wb_7_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_7_2003 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2003,'Area':'Production'] df_wb_7_2003_sum = df_wb_7_2003.sum(axis = 0, skipna = True) print(df_wb_7_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_7_2004 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2004,'Area':'Production'] df_wb_7_2004_sum = df_wb_7_2004.sum(axis = 0, skipna = True) print(df_wb_7_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_7_2005 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2005,'Area':'Production'] df_wb_7_2005_sum = df_wb_7_2005.sum(axis = 0, skipna = True) print(df_wb_7_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_7_2006 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2006,'Area':'Production'] df_wb_7_2006_sum = df_wb_7_2006.sum(axis = 0, skipna = True) print(df_wb_7_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_7_2007 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2007,'Area':'Production'] df_wb_7_2007_sum = df_wb_7_2007.sum(axis = 0, skipna = True) print(df_wb_7_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_7_2008 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2008,'Area':'Production'] df_wb_7_2008_sum = df_wb_7_2008.sum(axis = 0, skipna = True) print(df_wb_7_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_7_2009 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2009,'Area':'Production'] df_wb_7_2009_sum = df_wb_7_2009.sum(axis = 0, skipna = True) print(df_wb_7_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_7_2010 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2010,'Area':'Production'] df_wb_7_2010_sum = df_wb_7_2010.sum(axis = 0, skipna = True) print(df_wb_7_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_7_2011 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2011,'Area':'Production'] df_wb_7_2011_sum = df_wb_7_2011.sum(axis = 0, skipna = True) print(df_wb_7_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_7_2012 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2012,'Area':'Production'] df_wb_7_2012_sum = df_wb_7_2012.sum(axis = 0, skipna = True) print(df_wb_7_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_7_2013 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2013,'Area':'Production'] df_wb_7_2013_sum = df_wb_7_2013.sum(axis = 0, skipna = True) print(df_wb_7_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_7_2014 = df_wb_7.loc[df_wb_7['Crop_Year'] == 2014,'Area':'Production'] df_wb_7_2014_sum = df_wb_7_2014.sum(axis = 0, skipna = True) print(df_wb_7_2014_sum) print("---------------------------------") # details of wb : [8] DINAJPUR DAKSHIN print("--- Details of wb : [8] DINAJPUR DAKSHIN ----") df_wb_8 = df_wb[df_wb.District_Name == 'DINAJPUR DAKSHIN'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_8_1997 = df_wb_8.loc[df_wb_8['Crop_Year'] == 1997,'Area':'Production'] df_wb_8_1997_sum = df_wb_8_1997.sum(axis = 0, skipna = True) print(df_wb_8_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_8_1998 = df_wb_8.loc[df_wb_8['Crop_Year'] == 1998,'Area':'Production'] df_wb_8_1998_sum = df_wb_8_1998.sum(axis = 0, skipna = True) print(df_wb_8_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_8_1999 = df_wb_8.loc[df_wb_8['Crop_Year'] == 1999,'Area':'Production'] df_wb_8_1999_sum = df_wb_8_1999.sum(axis = 0, skipna = True) print(df_wb_8_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_8_2000 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2000,'Area':'Production'] df_wb_8_2000_sum = df_wb_8_2000.sum(axis = 0, skipna = True) print(df_wb_8_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_8_2001 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2001,'Area':'Production'] df_wb_8_2001_sum = df_wb_8_2001.sum(axis = 0, skipna = True) print(df_wb_8_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_8_2002 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2002,'Area':'Production'] df_wb_8_2002_sum = df_wb_8_2002.sum(axis = 0, skipna = True) print(df_wb_8_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_8_2003 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2003,'Area':'Production'] df_wb_8_2003_sum = df_wb_8_2003.sum(axis = 0, skipna = True) print(df_wb_8_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_8_2004 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2004,'Area':'Production'] df_wb_8_2004_sum = df_wb_8_2004.sum(axis = 0, skipna = True) print(df_wb_8_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_8_2005 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2005,'Area':'Production'] df_wb_8_2005_sum = df_wb_8_2005.sum(axis = 0, skipna = True) print(df_wb_8_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_8_2006 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2006,'Area':'Production'] df_wb_8_2006_sum = df_wb_8_2006.sum(axis = 0, skipna = True) print(df_wb_8_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_8_2007 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2007,'Area':'Production'] df_wb_8_2007_sum = df_wb_8_2007.sum(axis = 0, skipna = True) print(df_wb_8_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_8_2008 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2008,'Area':'Production'] df_wb_8_2008_sum = df_wb_8_2008.sum(axis = 0, skipna = True) print(df_wb_8_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_8_2009 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2009,'Area':'Production'] df_wb_8_2009_sum = df_wb_8_2009.sum(axis = 0, skipna = True) print(df_wb_8_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_8_2010 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2010,'Area':'Production'] df_wb_8_2010_sum = df_wb_8_2010.sum(axis = 0, skipna = True) print(df_wb_8_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_8_2011 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2011,'Area':'Production'] df_wb_8_2011_sum = df_wb_8_2011.sum(axis = 0, skipna = True) print(df_wb_8_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_8_2012 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2012,'Area':'Production'] df_wb_8_2012_sum = df_wb_8_2012.sum(axis = 0, skipna = True) print(df_wb_8_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_8_2013 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2013,'Area':'Production'] df_wb_8_2013_sum = df_wb_8_2013.sum(axis = 0, skipna = True) print(df_wb_8_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_8_2014 = df_wb_8.loc[df_wb_8['Crop_Year'] == 2014,'Area':'Production'] df_wb_8_2014_sum = df_wb_8_2014.sum(axis = 0, skipna = True) print(df_wb_8_2014_sum) print("---------------------------------") # details of wb : [9] DINAJPUR UTTAR df_wb_9 = df_wb[df_wb.District_Name == 'DINAJPUR UTTAR'] print("---- Details of wb : [9] DINAJPUR UTTAR ---") # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_9_1997 = df_wb_9.loc[df_wb_9['Crop_Year'] == 1997,'Area':'Production'] df_wb_9_1997_sum = df_wb_9_1997.sum(axis = 0, skipna = True) print(df_wb_9_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_9_1998 = df_wb_9.loc[df_wb_9['Crop_Year'] == 1998,'Area':'Production'] df_wb_9_1998_sum = df_wb_9_1998.sum(axis = 0, skipna = True) print(df_wb_9_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_9_1999 = df_wb_9.loc[df_wb_9['Crop_Year'] == 1999,'Area':'Production'] df_wb_9_1999_sum = df_wb_9_1999.sum(axis = 0, skipna = True) print(df_wb_9_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_9_2000 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2000,'Area':'Production'] df_wb_9_2000_sum = df_wb_9_2000.sum(axis = 0, skipna = True) print(df_wb_9_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_9_2001 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2001,'Area':'Production'] df_wb_9_2001_sum = df_wb_9_2001.sum(axis = 0, skipna = True) print(df_wb_9_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_9_2002 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2002,'Area':'Production'] df_wb_9_2002_sum = df_wb_9_2002.sum(axis = 0, skipna = True) print(df_wb_9_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_9_2003 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2003,'Area':'Production'] df_wb_9_2003_sum = df_wb_9_2003.sum(axis = 0, skipna = True) print(df_wb_9_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_9_2004 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2004,'Area':'Production'] df_wb_9_2004_sum = df_wb_9_2004.sum(axis = 0, skipna = True) print(df_wb_9_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_9_2005 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2005,'Area':'Production'] df_wb_9_2005_sum = df_wb_9_2005.sum(axis = 0, skipna = True) print(df_wb_9_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_9_2006 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2006,'Area':'Production'] df_wb_9_2006_sum = df_wb_9_2006.sum(axis = 0, skipna = True) print(df_wb_9_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_9_2007 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2007,'Area':'Production'] df_wb_9_2007_sum = df_wb_9_2007.sum(axis = 0, skipna = True) print(df_wb_9_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_9_2008 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2008,'Area':'Production'] df_wb_9_2008_sum = df_wb_9_2008.sum(axis = 0, skipna = True) print(df_wb_9_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_9_2009 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2009,'Area':'Production'] df_wb_9_2009_sum = df_wb_9_2009.sum(axis = 0, skipna = True) print(df_wb_9_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_9_2010 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2010,'Area':'Production'] df_wb_9_2010_sum = df_wb_9_2010.sum(axis = 0, skipna = True) print(df_wb_9_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_9_2011 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2011,'Area':'Production'] df_wb_9_2011_sum = df_wb_9_2011.sum(axis = 0, skipna = True) print(df_wb_9_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_9_2012 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2012,'Area':'Production'] df_wb_9_2012_sum = df_wb_9_2012.sum(axis = 0, skipna = True) print(df_wb_9_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_9_2013 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2013,'Area':'Production'] df_wb_9_2013_sum = df_wb_9_2013.sum(axis = 0, skipna = True) print(df_wb_9_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_9_2014 = df_wb_9.loc[df_wb_9['Crop_Year'] == 2014,'Area':'Production'] df_wb_9_2014_sum = df_wb_9_2014.sum(axis = 0, skipna = True) print(df_wb_9_2014_sum) print("---------------------------------") # details of wb : [10] HOOGHLY print("---- Details of wb : [10] HOOGHLY ----") df_wb_10 = df_wb[df_wb.District_Name == 'HOOGHLY'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_10_1997 = df_wb_10.loc[df_wb_10['Crop_Year'] == 1997,'Area':'Production'] df_wb_10_1997_sum = df_wb_10_1997.sum(axis = 0, skipna = True) print(df_wb_10_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_10_1998 = df_wb_10.loc[df_wb_10['Crop_Year'] == 1998,'Area':'Production'] df_wb_10_1998_sum = df_wb_10_1998.sum(axis = 0, skipna = True) print(df_wb_10_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_10_1999 = df_wb_10.loc[df_wb_10['Crop_Year'] == 1999,'Area':'Production'] df_wb_10_1999_sum = df_wb_10_1999.sum(axis = 0, skipna = True) print(df_wb_10_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_10_2000 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2000,'Area':'Production'] df_wb_10_2000_sum = df_wb_10_2000.sum(axis = 0, skipna = True) print(df_wb_10_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_10_2001 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2001,'Area':'Production'] df_wb_10_2001_sum = df_wb_10_2001.sum(axis = 0, skipna = True) print(df_wb_10_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_10_2002 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2002,'Area':'Production'] df_wb_10_2002_sum = df_wb_10_2002.sum(axis = 0, skipna = True) print(df_wb_10_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_10_2003 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2003,'Area':'Production'] df_wb_10_2003_sum = df_wb_10_2003.sum(axis = 0, skipna = True) print(df_wb_10_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_10_2004 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2004,'Area':'Production'] df_wb_10_2004_sum = df_wb_10_2004.sum(axis = 0, skipna = True) print(df_wb_10_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_10_2005 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2005,'Area':'Production'] df_wb_10_2005_sum = df_wb_10_2005.sum(axis = 0, skipna = True) print(df_wb_10_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_10_2006 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2006,'Area':'Production'] df_wb_10_2006_sum = df_wb_10_2006.sum(axis = 0, skipna = True) print(df_wb_10_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_10_2007 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2007,'Area':'Production'] df_wb_10_2007_sum = df_wb_10_2007.sum(axis = 0, skipna = True) print(df_wb_10_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_10_2008 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2008,'Area':'Production'] df_wb_10_2008_sum = df_wb_10_2008.sum(axis = 0, skipna = True) print(df_wb_10_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_10_2009 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2009,'Area':'Production'] df_wb_10_2009_sum = df_wb_10_2009.sum(axis = 0, skipna = True) print(df_wb_10_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_10_2010 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2010,'Area':'Production'] df_wb_10_2010_sum = df_wb_10_2010.sum(axis = 0, skipna = True) print(df_wb_10_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_10_2011 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2011,'Area':'Production'] df_wb_10_2011_sum = df_wb_10_2011.sum(axis = 0, skipna = True) print(df_wb_10_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_10_2012 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2012,'Area':'Production'] df_wb_10_2012_sum = df_wb_10_2012.sum(axis = 0, skipna = True) print(df_wb_10_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_10_2013 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2013,'Area':'Production'] df_wb_10_2013_sum = df_wb_10_2013.sum(axis = 0, skipna = True) print(df_wb_10_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_10_2014 = df_wb_10.loc[df_wb_10['Crop_Year'] == 2014,'Area':'Production'] df_wb_10_2014_sum = df_wb_10_2014.sum(axis = 0, skipna = True) print(df_wb_10_2014_sum) print("---------------------------------") # details of wb : [11] HOWRAH print("---- Details of wb : [11] HOWRAH --------") df_wb_11 = df_wb[df_wb.District_Name == 'HOWRAH'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_11_1997 = df_wb_11.loc[df_wb_11['Crop_Year'] == 1997,'Area':'Production'] df_wb_11_1997_sum = df_wb_11_1997.sum(axis = 0, skipna = True) print(df_wb_11_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_11_1998 = df_wb_11.loc[df_wb_11['Crop_Year'] == 1998,'Area':'Production'] df_wb_11_1998_sum = df_wb_11_1998.sum(axis = 0, skipna = True) print(df_wb_11_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_11_1999 = df_wb_11.loc[df_wb_11['Crop_Year'] == 1999,'Area':'Production'] df_wb_11_1999_sum = df_wb_11_1999.sum(axis = 0, skipna = True) print(df_wb_11_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_11_2000 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2000,'Area':'Production'] df_wb_11_2000_sum = df_wb_11_2000.sum(axis = 0, skipna = True) print(df_wb_11_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_11_2001 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2001,'Area':'Production'] df_wb_11_2001_sum = df_wb_11_2001.sum(axis = 0, skipna = True) print(df_wb_11_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_11_2002 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2002,'Area':'Production'] df_wb_11_2002_sum = df_wb_11_2002.sum(axis = 0, skipna = True) print(df_wb_11_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_11_2003 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2003,'Area':'Production'] df_wb_11_2003_sum = df_wb_11_2003.sum(axis = 0, skipna = True) print(df_wb_11_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_11_2004 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2004,'Area':'Production'] df_wb_11_2004_sum = df_wb_11_2004.sum(axis = 0, skipna = True) print(df_wb_11_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_11_2005 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2005,'Area':'Production'] df_wb_11_2005_sum = df_wb_11_2005.sum(axis = 0, skipna = True) print(df_wb_11_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_11_2006 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2006,'Area':'Production'] df_wb_11_2006_sum = df_wb_11_2006.sum(axis = 0, skipna = True) print(df_wb_11_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_11_2007 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2007,'Area':'Production'] df_wb_11_2007_sum = df_wb_11_2007.sum(axis = 0, skipna = True) print(df_wb_11_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_11_2008 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2008,'Area':'Production'] df_wb_11_2008_sum = df_wb_11_2008.sum(axis = 0, skipna = True) print(df_wb_11_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_11_2009 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2009,'Area':'Production'] df_wb_11_2009_sum = df_wb_11_2009.sum(axis = 0, skipna = True) print(df_wb_11_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_11_2010 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2010,'Area':'Production'] df_wb_11_2010_sum = df_wb_11_2010.sum(axis = 0, skipna = True) print(df_wb_11_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_11_2011 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2011,'Area':'Production'] df_wb_11_2011_sum = df_wb_11_2011.sum(axis = 0, skipna = True) print(df_wb_11_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_11_2012 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2012,'Area':'Production'] df_wb_11_2012_sum = df_wb_11_2012.sum(axis = 0, skipna = True) print(df_wb_11_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_11_2013 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2013,'Area':'Production'] df_wb_11_2013_sum = df_wb_11_2013.sum(axis = 0, skipna = True) print(df_wb_11_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_11_2014 = df_wb_11.loc[df_wb_11['Crop_Year'] == 2014,'Area':'Production'] df_wb_11_2014_sum = df_wb_11_2014.sum(axis = 0, skipna = True) print(df_wb_11_2014_sum) print("---------------------------------") # details of wb : [12] JALPAIGURI print("---- Details of wb : [11] JALPAIGURI -----") df_wb_12 = df_wb[df_wb.District_Name == 'JALPAIGURI'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_12_1997 = df_wb_12.loc[df_wb_12['Crop_Year'] == 1997,'Area':'Production'] df_wb_12_1997_sum = df_wb_12_1997.sum(axis = 0, skipna = True) print(df_wb_12_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_12_1998 = df_wb_12.loc[df_wb_12['Crop_Year'] == 1998,'Area':'Production'] df_wb_12_1998_sum = df_wb_12_1998.sum(axis = 0, skipna = True) print(df_wb_12_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_12_1999 = df_wb_12.loc[df_wb_12['Crop_Year'] == 1999,'Area':'Production'] df_wb_12_1999_sum = df_wb_12_1999.sum(axis = 0, skipna = True) print(df_wb_12_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_12_2000 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2000,'Area':'Production'] df_wb_12_2000_sum = df_wb_12_2000.sum(axis = 0, skipna = True) print(df_wb_12_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_12_2001 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2001,'Area':'Production'] df_wb_12_2001_sum = df_wb_12_2001.sum(axis = 0, skipna = True) print(df_wb_12_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_12_2002 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2002,'Area':'Production'] df_wb_12_2002_sum = df_wb_12_2002.sum(axis = 0, skipna = True) print(df_wb_12_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_12_2003 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2003,'Area':'Production'] df_wb_12_2003_sum = df_wb_12_2003.sum(axis = 0, skipna = True) print(df_wb_12_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_12_2004 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2004,'Area':'Production'] df_wb_12_2004_sum = df_wb_12_2004.sum(axis = 0, skipna = True) print(df_wb_12_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_12_2005 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2005,'Area':'Production'] df_wb_12_2005_sum = df_wb_12_2005.sum(axis = 0, skipna = True) print(df_wb_12_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_12_2006 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2006,'Area':'Production'] df_wb_12_2006_sum = df_wb_12_2006.sum(axis = 0, skipna = True) print(df_wb_12_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_12_2007 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2007,'Area':'Production'] df_wb_12_2007_sum = df_wb_12_2007.sum(axis = 0, skipna = True) print(df_wb_12_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_12_2008 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2008,'Area':'Production'] df_wb_12_2008_sum = df_wb_12_2008.sum(axis = 0, skipna = True) print(df_wb_12_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_12_2009 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2009,'Area':'Production'] df_wb_12_2009_sum = df_wb_12_2009.sum(axis = 0, skipna = True) print(df_wb_12_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_12_2010 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2010,'Area':'Production'] df_wb_12_2010_sum = df_wb_12_2010.sum(axis = 0, skipna = True) print(df_wb_12_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_12_2011 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2011,'Area':'Production'] df_wb_12_2011_sum = df_wb_12_2011.sum(axis = 0, skipna = True) print(df_wb_12_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_12_2012 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2012,'Area':'Production'] df_wb_12_2012_sum = df_wb_12_2012.sum(axis = 0, skipna = True) print(df_wb_12_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_12_2013 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2013,'Area':'Production'] df_wb_12_2013_sum = df_wb_12_2013.sum(axis = 0, skipna = True) print(df_wb_12_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_12_2014 = df_wb_12.loc[df_wb_12['Crop_Year'] == 2014,'Area':'Production'] df_wb_12_2014_sum = df_wb_12_2014.sum(axis = 0, skipna = True) print(df_wb_12_2014_sum) print("---------------------------------") # details of wb : [13] MALDAH print("----- Details of wb : [13] MALDAH -------") df_wb_13 = df_wb[df_wb.District_Name == 'MALDAH'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_13_1997 = df_wb_13.loc[df_wb_13['Crop_Year'] == 1997,'Area':'Production'] df_wb_13_1997_sum = df_wb_13_1997.sum(axis = 0, skipna = True) print(df_wb_13_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_13_1998 = df_wb_13.loc[df_wb_13['Crop_Year'] == 1998,'Area':'Production'] df_wb_13_1998_sum = df_wb_13_1998.sum(axis = 0, skipna = True) print(df_wb_13_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_13_1999 = df_wb_13.loc[df_wb_13['Crop_Year'] == 1999,'Area':'Production'] df_wb_13_1999_sum = df_wb_13_1999.sum(axis = 0, skipna = True) print(df_wb_13_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_13_2000 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2000,'Area':'Production'] df_wb_13_2000_sum = df_wb_13_2000.sum(axis = 0, skipna = True) print(df_wb_13_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_13_2001 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2001,'Area':'Production'] df_wb_13_2001_sum = df_wb_13_2001.sum(axis = 0, skipna = True) print(df_wb_13_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_13_2002 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2002,'Area':'Production'] df_wb_13_2002_sum = df_wb_13_2002.sum(axis = 0, skipna = True) print(df_wb_13_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_13_2003 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2003,'Area':'Production'] df_wb_13_2003_sum = df_wb_13_2003.sum(axis = 0, skipna = True) print(df_wb_13_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_13_2004 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2004,'Area':'Production'] df_wb_13_2004_sum = df_wb_13_2004.sum(axis = 0, skipna = True) print(df_wb_13_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_13_2005 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2005,'Area':'Production'] df_wb_13_2005_sum = df_wb_13_2005.sum(axis = 0, skipna = True) print(df_wb_13_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_13_2006 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2006,'Area':'Production'] df_wb_13_2006_sum = df_wb_13_2006.sum(axis = 0, skipna = True) print(df_wb_13_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_13_2007 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2007,'Area':'Production'] df_wb_13_2007_sum = df_wb_13_2007.sum(axis = 0, skipna = True) print(df_wb_13_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_13_2008 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2008,'Area':'Production'] df_wb_13_2008_sum = df_wb_13_2008.sum(axis = 0, skipna = True) print(df_wb_13_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_13_2009 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2009,'Area':'Production'] df_wb_13_2009_sum = df_wb_13_2009.sum(axis = 0, skipna = True) print(df_wb_13_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_13_2010 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2010,'Area':'Production'] df_wb_13_2010_sum = df_wb_13_2010.sum(axis = 0, skipna = True) print(df_wb_13_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_13_2011 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2011,'Area':'Production'] df_wb_13_2011_sum = df_wb_13_2011.sum(axis = 0, skipna = True) print(df_wb_13_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_13_2012 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2012,'Area':'Production'] df_wb_13_2012_sum = df_wb_13_2012.sum(axis = 0, skipna = True) print(df_wb_13_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_13_2013 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2013,'Area':'Production'] df_wb_13_2013_sum = df_wb_13_2013.sum(axis = 0, skipna = True) print(df_wb_13_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_13_2014 = df_wb_13.loc[df_wb_13['Crop_Year'] == 2014,'Area':'Production'] df_wb_13_2014_sum = df_wb_13_2014.sum(axis = 0, skipna = True) print(df_wb_13_2014_sum) print("---------------------------------") # details of wb : [14] MEDINIPUR EAST print("----- Details of wb : [14] MEDINIPUR EAST ------") df_wb_14 = df_wb[df_wb.District_Name == 'MEDINIPUR EAST'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_14_1997 = df_wb_14.loc[df_wb_14['Crop_Year'] == 1997,'Area':'Production'] df_wb_14_1997_sum = df_wb_14_1997.sum(axis = 0, skipna = True) print(df_wb_14_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_14_1998 = df_wb_14.loc[df_wb_14['Crop_Year'] == 1998,'Area':'Production'] df_wb_14_1998_sum = df_wb_14_1998.sum(axis = 0, skipna = True) print(df_wb_14_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_14_1999 = df_wb_14.loc[df_wb_14['Crop_Year'] == 1999,'Area':'Production'] df_wb_14_1999_sum = df_wb_14_1999.sum(axis = 0, skipna = True) print(df_wb_14_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_14_2000 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2000,'Area':'Production'] df_wb_14_2000_sum = df_wb_14_2000.sum(axis = 0, skipna = True) print(df_wb_14_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_14_2001 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2001,'Area':'Production'] df_wb_14_2001_sum = df_wb_14_2001.sum(axis = 0, skipna = True) print(df_wb_14_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_14_2002 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2002,'Area':'Production'] df_wb_14_2002_sum = df_wb_14_2002.sum(axis = 0, skipna = True) print(df_wb_14_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_14_2003 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2003,'Area':'Production'] df_wb_14_2003_sum = df_wb_14_2003.sum(axis = 0, skipna = True) print(df_wb_14_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_14_2004 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2004,'Area':'Production'] df_wb_14_2004_sum = df_wb_14_2004.sum(axis = 0, skipna = True) print(df_wb_14_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_14_2005 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2005,'Area':'Production'] df_wb_14_2005_sum = df_wb_14_2005.sum(axis = 0, skipna = True) print(df_wb_14_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_14_2006 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2006,'Area':'Production'] df_wb_14_2006_sum = df_wb_14_2006.sum(axis = 0, skipna = True) print(df_wb_14_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_14_2007 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2007,'Area':'Production'] df_wb_14_2007_sum = df_wb_14_2007.sum(axis = 0, skipna = True) print(df_wb_14_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_14_2008 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2008,'Area':'Production'] df_wb_14_2008_sum = df_wb_14_2008.sum(axis = 0, skipna = True) print(df_wb_14_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_14_2009 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2009,'Area':'Production'] df_wb_14_2009_sum = df_wb_14_2009.sum(axis = 0, skipna = True) print(df_wb_14_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_14_2010 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2010,'Area':'Production'] df_wb_14_2010_sum = df_wb_14_2010.sum(axis = 0, skipna = True) print(df_wb_14_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_14_2011 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2011,'Area':'Production'] df_wb_14_2011_sum = df_wb_14_2011.sum(axis = 0, skipna = True) print(df_wb_14_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_14_2012 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2012,'Area':'Production'] df_wb_14_2012_sum = df_wb_14_2012.sum(axis = 0, skipna = True) print(df_wb_14_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_14_2013 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2013,'Area':'Production'] df_wb_14_2013_sum = df_wb_14_2013.sum(axis = 0, skipna = True) print(df_wb_14_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_14_2014 = df_wb_14.loc[df_wb_14['Crop_Year'] == 2014,'Area':'Production'] df_wb_14_2014_sum = df_wb_14_2014.sum(axis = 0, skipna = True) print(df_wb_14_2014_sum) print("---------------------------------") # details of wb : [15] MEDINIPUR WEST print("---- Details of wb : [15] MEDINIPUR WEST -------") df_wb_15 = df_wb[df_wb.District_Name == 'MEDINIPUR WEST'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_15_1997 = df_wb_15.loc[df_wb_15['Crop_Year'] == 1997,'Area':'Production'] df_wb_15_1997_sum = df_wb_15_1997.sum(axis = 0, skipna = True) print(df_wb_15_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_15_1998 = df_wb_15.loc[df_wb_15['Crop_Year'] == 1998,'Area':'Production'] df_wb_15_1998_sum = df_wb_15_1998.sum(axis = 0, skipna = True) print(df_wb_15_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_15_1999 = df_wb_15.loc[df_wb_15['Crop_Year'] == 1999,'Area':'Production'] df_wb_15_1999_sum = df_wb_15_1999.sum(axis = 0, skipna = True) print(df_wb_15_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_15_2000 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2000,'Area':'Production'] df_wb_15_2000_sum = df_wb_15_2000.sum(axis = 0, skipna = True) print(df_wb_15_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_15_2001 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2001,'Area':'Production'] df_wb_15_2001_sum = df_wb_15_2001.sum(axis = 0, skipna = True) print(df_wb_15_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_15_2002 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2002,'Area':'Production'] df_wb_15_2002_sum = df_wb_15_2002.sum(axis = 0, skipna = True) print(df_wb_15_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_15_2003 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2003,'Area':'Production'] df_wb_15_2003_sum = df_wb_15_2003.sum(axis = 0, skipna = True) print(df_wb_15_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_15_2004 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2004,'Area':'Production'] df_wb_15_2004_sum = df_wb_15_2004.sum(axis = 0, skipna = True) print(df_wb_15_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_15_2005 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2005,'Area':'Production'] df_wb_15_2005_sum = df_wb_15_2005.sum(axis = 0, skipna = True) print(df_wb_15_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_15_2006 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2006,'Area':'Production'] df_wb_15_2006_sum = df_wb_15_2006.sum(axis = 0, skipna = True) print(df_wb_15_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_15_2007 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2007,'Area':'Production'] df_wb_15_2007_sum = df_wb_15_2007.sum(axis = 0, skipna = True) print(df_wb_15_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_15_2008 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2008,'Area':'Production'] df_wb_15_2008_sum = df_wb_15_2008.sum(axis = 0, skipna = True) print(df_wb_15_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_15_2009 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2009,'Area':'Production'] df_wb_15_2009_sum = df_wb_15_2009.sum(axis = 0, skipna = True) print(df_wb_15_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_15_2010 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2010,'Area':'Production'] df_wb_15_2010_sum = df_wb_15_2010.sum(axis = 0, skipna = True) print(df_wb_15_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_15_2011 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2011,'Area':'Production'] df_wb_15_2011_sum = df_wb_15_2011.sum(axis = 0, skipna = True) print(df_wb_15_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_15_2012 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2012,'Area':'Production'] df_wb_15_2012_sum = df_wb_15_2012.sum(axis = 0, skipna = True) print(df_wb_15_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_15_2013 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2013,'Area':'Production'] df_wb_15_2013_sum = df_wb_15_2013.sum(axis = 0, skipna = True) print(df_wb_15_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_15_2014 = df_wb_15.loc[df_wb_15['Crop_Year'] == 2014,'Area':'Production'] df_wb_15_2014_sum = df_wb_15_2014.sum(axis = 0, skipna = True) print(df_wb_15_2014_sum) print("---------------------------------") # details of wb : [16] MURSHIDABAD print("---- Details of wb : [16] MURSHIDABAD ----") df_wb_16 = df_wb[df_wb.District_Name == 'MURSHIDABAD'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_16_1997 = df_wb_16.loc[df_wb_16['Crop_Year'] == 1997,'Area':'Production'] df_wb_16_1997_sum = df_wb_16_1997.sum(axis = 0, skipna = True) print(df_wb_16_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_16_1998 = df_wb_16.loc[df_wb_16['Crop_Year'] == 1998,'Area':'Production'] df_wb_16_1998_sum = df_wb_16_1998.sum(axis = 0, skipna = True) print(df_wb_16_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_16_1999 = df_wb_16.loc[df_wb_16['Crop_Year'] == 1999,'Area':'Production'] df_wb_16_1999_sum = df_wb_16_1999.sum(axis = 0, skipna = True) print(df_wb_16_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_16_2000 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2000,'Area':'Production'] df_wb_16_2000_sum = df_wb_16_2000.sum(axis = 0, skipna = True) print(df_wb_16_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_16_2001 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2001,'Area':'Production'] df_wb_16_2001_sum = df_wb_16_2001.sum(axis = 0, skipna = True) print(df_wb_16_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_16_2002 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2002,'Area':'Production'] df_wb_16_2002_sum = df_wb_16_2002.sum(axis = 0, skipna = True) print(df_wb_16_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_16_2003 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2003,'Area':'Production'] df_wb_16_2003_sum = df_wb_16_2003.sum(axis = 0, skipna = True) print(df_wb_16_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_16_2004 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2004,'Area':'Production'] df_wb_16_2004_sum = df_wb_16_2004.sum(axis = 0, skipna = True) print(df_wb_16_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_16_2005 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2005,'Area':'Production'] df_wb_16_2005_sum = df_wb_16_2005.sum(axis = 0, skipna = True) print(df_wb_16_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_16_2006 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2006,'Area':'Production'] df_wb_16_2006_sum = df_wb_16_2006.sum(axis = 0, skipna = True) print(df_wb_16_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_16_2007 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2007,'Area':'Production'] df_wb_16_2007_sum = df_wb_16_2007.sum(axis = 0, skipna = True) print(df_wb_16_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_16_2008 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2008,'Area':'Production'] df_wb_16_2008_sum = df_wb_16_2008.sum(axis = 0, skipna = True) print(df_wb_16_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_16_2009 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2009,'Area':'Production'] df_wb_16_2009_sum = df_wb_16_2009.sum(axis = 0, skipna = True) print(df_wb_16_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_16_2010 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2010,'Area':'Production'] df_wb_16_2010_sum = df_wb_16_2010.sum(axis = 0, skipna = True) print(df_wb_16_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_16_2011 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2011,'Area':'Production'] df_wb_16_2011_sum = df_wb_16_2011.sum(axis = 0, skipna = True) print(df_wb_16_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_16_2012 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2012,'Area':'Production'] df_wb_16_2012_sum = df_wb_16_2012.sum(axis = 0, skipna = True) print(df_wb_16_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_16_2013 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2013,'Area':'Production'] df_wb_16_2013_sum = df_wb_16_2013.sum(axis = 0, skipna = True) print(df_wb_16_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_16_2014 = df_wb_16.loc[df_wb_16['Crop_Year'] == 2014,'Area':'Production'] df_wb_16_2014_sum = df_wb_16_2014.sum(axis = 0, skipna = True) print(df_wb_16_2014_sum) print("---------------------------------") # details of wb : [17] NADIA print("---- Details of wb : [17] NADIA -----") df_wb_17 = df_wb[df_wb.District_Name == 'NADIA'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_17_1997 = df_wb_17.loc[df_wb_17['Crop_Year'] == 1997,'Area':'Production'] df_wb_17_1997_sum = df_wb_17_1997.sum(axis = 0, skipna = True) print(df_wb_17_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_17_1998 = df_wb_17.loc[df_wb_17['Crop_Year'] == 1998,'Area':'Production'] df_wb_17_1998_sum = df_wb_17_1998.sum(axis = 0, skipna = True) print(df_wb_17_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_17_1999 = df_wb_17.loc[df_wb_17['Crop_Year'] == 1999,'Area':'Production'] df_wb_17_1999_sum = df_wb_17_1999.sum(axis = 0, skipna = True) print(df_wb_17_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_17_2000 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2000,'Area':'Production'] df_wb_17_2000_sum = df_wb_17_2000.sum(axis = 0, skipna = True) print(df_wb_17_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_17_2001 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2001,'Area':'Production'] df_wb_17_2001_sum = df_wb_17_2001.sum(axis = 0, skipna = True) print(df_wb_17_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_17_2002 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2002,'Area':'Production'] df_wb_17_2002_sum = df_wb_17_2002.sum(axis = 0, skipna = True) print(df_wb_17_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_17_2003 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2003,'Area':'Production'] df_wb_17_2003_sum = df_wb_17_2003.sum(axis = 0, skipna = True) print(df_wb_17_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_17_2004 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2004,'Area':'Production'] df_wb_17_2004_sum = df_wb_17_2004.sum(axis = 0, skipna = True) print(df_wb_17_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_17_2005 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2005,'Area':'Production'] df_wb_17_2005_sum = df_wb_17_2005.sum(axis = 0, skipna = True) print(df_wb_17_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_17_2006 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2006,'Area':'Production'] df_wb_17_2006_sum = df_wb_17_2006.sum(axis = 0, skipna = True) print(df_wb_17_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_17_2007 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2007,'Area':'Production'] df_wb_17_2007_sum = df_wb_17_2007.sum(axis = 0, skipna = True) print(df_wb_17_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_17_2008 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2008,'Area':'Production'] df_wb_17_2008_sum = df_wb_17_2008.sum(axis = 0, skipna = True) print(df_wb_17_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_17_2009 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2009,'Area':'Production'] df_wb_17_2009_sum = df_wb_17_2009.sum(axis = 0, skipna = True) print(df_wb_17_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_17_2010 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2010,'Area':'Production'] df_wb_17_2010_sum = df_wb_17_2010.sum(axis = 0, skipna = True) print(df_wb_17_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_17_2011 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2011,'Area':'Production'] df_wb_17_2011_sum = df_wb_17_2011.sum(axis = 0, skipna = True) print(df_wb_17_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_17_2012 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2012,'Area':'Production'] df_wb_17_2012_sum = df_wb_17_2012.sum(axis = 0, skipna = True) print(df_wb_17_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_17_2013 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2013,'Area':'Production'] df_wb_17_2013_sum = df_wb_17_2013.sum(axis = 0, skipna = True) print(df_wb_17_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_17_2014 = df_wb_17.loc[df_wb_17['Crop_Year'] == 2014,'Area':'Production'] df_wb_17_2014_sum = df_wb_17_2014.sum(axis = 0, skipna = True) print(df_wb_17_2014_sum) print("---------------------------------") # details of wb : [18] PURULIA print("---- Details of wb : [18] PURULIA -----") df_wb_18 = df_wb[df_wb.District_Name == 'PURULIA'] # Select rows from year =( 1997 to 2014 ) and all columns between 'Area' and 'Production' print("---------------------------------") print("Data for Crop_Year = 1997") print("---------------------------------") df_wb_18_1997 = df_wb_18.loc[df_wb_18['Crop_Year'] == 1997,'Area':'Production'] df_wb_18_1997_sum = df_wb_18_1997.sum(axis = 0, skipna = True) print(df_wb_18_1997_sum) print("---------------------------------") print("Data for Crop_Year = 1998") print("---------------------------------") df_wb_18_1998 = df_wb_18.loc[df_wb_18['Crop_Year'] == 1998,'Area':'Production'] df_wb_18_1998_sum = df_wb_18_1998.sum(axis = 0, skipna = True) print(df_wb_18_1998_sum) print("---------------------------------") print("Data for Crop_Year = 1999") print("---------------------------------") df_wb_18_1999 = df_wb_18.loc[df_wb_18['Crop_Year'] == 1999,'Area':'Production'] df_wb_18_1999_sum = df_wb_18_1999.sum(axis = 0, skipna = True) print(df_wb_18_1999_sum) print("---------------------------------") print("Data for Crop_Year = 2000") print("---------------------------------") df_wb_18_2000 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2000,'Area':'Production'] df_wb_18_2000_sum = df_wb_18_2000.sum(axis = 0, skipna = True) print(df_wb_18_2000_sum) print("---------------------------------") print("Data for Crop_Year = 2001") print("---------------------------------") df_wb_18_2001 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2001,'Area':'Production'] df_wb_18_2001_sum = df_wb_18_2001.sum(axis = 0, skipna = True) print(df_wb_18_2001_sum) print("---------------------------------") print("Data for Crop_Year = 2002") print("---------------------------------") df_wb_18_2002 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2002,'Area':'Production'] df_wb_18_2002_sum = df_wb_18_2002.sum(axis = 0, skipna = True) print(df_wb_18_2002_sum) print("---------------------------------") print("Data for Crop_Year = 2003") print("---------------------------------") df_wb_18_2003 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2003,'Area':'Production'] df_wb_18_2003_sum = df_wb_18_2003.sum(axis = 0, skipna = True) print(df_wb_18_2003_sum) print("---------------------------------") print("Data for Crop_Year = 2004") print("---------------------------------") df_wb_18_2004 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2004,'Area':'Production'] df_wb_18_2004_sum = df_wb_18_2004.sum(axis = 0, skipna = True) print(df_wb_18_2004_sum) print("---------------------------------") print("Data for Crop_Year = 2005") print("---------------------------------") df_wb_18_2005 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2005,'Area':'Production'] df_wb_18_2005_sum = df_wb_18_2005.sum(axis = 0, skipna = True) print(df_wb_18_2005_sum) print("---------------------------------") print("Data for Crop_Year = 2006") print("---------------------------------") df_wb_18_2006 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2006,'Area':'Production'] df_wb_18_2006_sum = df_wb_18_2006.sum(axis = 0, skipna = True) print(df_wb_18_2006_sum) print("---------------------------------") print("Data for Crop_Year = 2007") print("---------------------------------") df_wb_18_2007 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2007,'Area':'Production'] df_wb_18_2007_sum = df_wb_18_2007.sum(axis = 0, skipna = True) print(df_wb_18_2007_sum) print("---------------------------------") print("Data for Crop_Year = 2008") print("---------------------------------") df_wb_18_2008 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2008,'Area':'Production'] df_wb_18_2008_sum = df_wb_18_2008.sum(axis = 0, skipna = True) print(df_wb_18_2008_sum) print("---------------------------------") print("Data for Crop_Year = 2009") print("---------------------------------") df_wb_18_2009 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2009,'Area':'Production'] df_wb_18_2009_sum = df_wb_18_2009.sum(axis = 0, skipna = True) print(df_wb_18_2009_sum) print("---------------------------------") print("Data for Crop_Year = 2010") print("---------------------------------") df_wb_18_2010 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2010,'Area':'Production'] df_wb_18_2010_sum = df_wb_18_2010.sum(axis = 0, skipna = True) print(df_wb_18_2010_sum) print("---------------------------------") print("Data for Crop_Year = 2011") print("---------------------------------") df_wb_18_2011 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2011,'Area':'Production'] df_wb_18_2011_sum = df_wb_18_2011.sum(axis = 0, skipna = True) print(df_wb_18_2011_sum) print("---------------------------------") print("Data for Crop_Year = 2012") print("---------------------------------") df_wb_18_2012 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2012,'Area':'Production'] df_wb_18_2012_sum = df_wb_18_2012.sum(axis = 0, skipna = True) print(df_wb_18_2012_sum) print("---------------------------------") print("Data for Crop_Year = 2013") print("---------------------------------") df_wb_18_2013 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2013,'Area':'Production'] df_wb_18_2013_sum = df_wb_18_2013.sum(axis = 0, skipna = True) print(df_wb_18_2013_sum) print("---------------------------------") print("Data for Crop_Year = 2014") print("---------------------------------") df_wb_18_2014 = df_wb_18.loc[df_wb_18['Crop_Year'] == 2014,'Area':'Production'] df_wb_18_2014_sum = df_wb_18_2014.sum(axis = 0, skipna = True) print(df_wb_18_2014_sum) print("---------------------------------") # plotting of West Bengal 'Area' and 'Production' # plotting wb : [1] 24 PARAGANAS NORTH x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_1_1997_sum['Area'], df_wb_1_1998_sum['Area'], df_wb_1_1999_sum['Area'], df_wb_1_2000_sum['Area'], df_wb_1_2001_sum['Area'], df_wb_1_2002_sum['Area'], df_wb_1_2003_sum['Area'], df_wb_1_2004_sum['Area'], df_wb_1_2005_sum['Area'], df_wb_1_2006_sum['Area'], df_wb_1_2007_sum['Area'], df_wb_1_2008_sum['Area'], df_wb_1_2009_sum['Area'], df_wb_1_2010_sum['Area'], df_wb_1_2011_sum['Area'], df_wb_1_2012_sum['Area'], df_wb_1_2013_sum['Area'], df_wb_1_2014_sum['Area']) y22 =(df_wb_1_1997_sum['Production'], df_wb_1_1998_sum['Production'], df_wb_1_1999_sum['Production'], df_wb_1_2000_sum['Production'], df_wb_1_2001_sum['Production'], df_wb_1_2002_sum['Production'], df_wb_1_2003_sum['Production'], df_wb_1_2004_sum['Production'], df_wb_1_2005_sum['Production'], df_wb_1_2006_sum['Production'], df_wb_1_2007_sum['Production'], df_wb_1_2008_sum['Production'], df_wb_1_2009_sum['Production'], df_wb_1_2010_sum['Production'], df_wb_1_2011_sum['Production'], df_wb_1_2012_sum['Production'], df_wb_1_2013_sum['Production'], df_wb_1_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [1] 24 PARAGANAS NORTH(Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [1] 24 PARAGANAS NORTH(Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [2] 24 PARAGANAS SOUTH x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_2_1997_sum['Area'], df_wb_2_1998_sum['Area'], df_wb_2_1999_sum['Area'], df_wb_2_2000_sum['Area'], df_wb_2_2001_sum['Area'], df_wb_2_2002_sum['Area'], df_wb_2_2003_sum['Area'], df_wb_2_2004_sum['Area'], df_wb_2_2005_sum['Area'], df_wb_2_2006_sum['Area'], df_wb_2_2007_sum['Area'], df_wb_2_2008_sum['Area'], df_wb_2_2009_sum['Area'], df_wb_2_2010_sum['Area'], df_wb_2_2011_sum['Area'], df_wb_2_2012_sum['Area'], df_wb_2_2013_sum['Area'], df_wb_2_2014_sum['Area']) y22 =(df_wb_2_1997_sum['Production'], df_wb_2_1998_sum['Production'], df_wb_2_1999_sum['Production'], df_wb_2_2000_sum['Production'], df_wb_2_2001_sum['Production'], df_wb_2_2002_sum['Production'], df_wb_2_2003_sum['Production'], df_wb_2_2004_sum['Production'], df_wb_2_2005_sum['Production'], df_wb_2_2006_sum['Production'], df_wb_2_2007_sum['Production'], df_wb_2_2008_sum['Production'], df_wb_2_2009_sum['Production'], df_wb_2_2010_sum['Production'], df_wb_2_2011_sum['Production'], df_wb_2_2012_sum['Production'], df_wb_2_2013_sum['Production'], df_wb_2_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [2] 24 PARAGANAS SOUTH(Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [2] 24 PARAGANAS SOUTH(Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [3] BANKURA x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_3_1997_sum['Area'], df_wb_3_1998_sum['Area'], df_wb_3_1999_sum['Area'], df_wb_3_2000_sum['Area'], df_wb_3_2001_sum['Area'], df_wb_3_2002_sum['Area'], df_wb_3_2003_sum['Area'], df_wb_3_2004_sum['Area'], df_wb_3_2005_sum['Area'], df_wb_3_2006_sum['Area'], df_wb_3_2007_sum['Area'], df_wb_3_2008_sum['Area'], df_wb_3_2009_sum['Area'], df_wb_3_2010_sum['Area'], df_wb_3_2011_sum['Area'], df_wb_3_2012_sum['Area'], df_wb_3_2013_sum['Area'], df_wb_3_2014_sum['Area']) y22 =(df_wb_3_1997_sum['Production'], df_wb_3_1998_sum['Production'], df_wb_3_1999_sum['Production'], df_wb_3_2000_sum['Production'], df_wb_3_2001_sum['Production'], df_wb_3_2002_sum['Production'], df_wb_3_2003_sum['Production'], df_wb_3_2004_sum['Production'], df_wb_3_2005_sum['Production'], df_wb_3_2006_sum['Production'], df_wb_3_2007_sum['Production'], df_wb_3_2008_sum['Production'], df_wb_3_2009_sum['Production'], df_wb_3_2010_sum['Production'], df_wb_3_2011_sum['Production'], df_wb_3_2012_sum['Production'], df_wb_3_2013_sum['Production'], df_wb_3_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [3] BANKURA (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [3] BANKURA (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [4] BARDHAMAN x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_4_1997_sum['Area'], df_wb_4_1998_sum['Area'], df_wb_4_1999_sum['Area'], df_wb_4_2000_sum['Area'], df_wb_4_2001_sum['Area'], df_wb_4_2002_sum['Area'], df_wb_4_2003_sum['Area'], df_wb_4_2004_sum['Area'], df_wb_4_2005_sum['Area'], df_wb_4_2006_sum['Area'], df_wb_4_2007_sum['Area'], df_wb_4_2008_sum['Area'], df_wb_4_2009_sum['Area'], df_wb_4_2010_sum['Area'], df_wb_4_2011_sum['Area'], df_wb_4_2012_sum['Area'], df_wb_4_2013_sum['Area'], df_wb_4_2014_sum['Area']) y22 =(df_wb_4_1997_sum['Production'], df_wb_4_1998_sum['Production'], df_wb_4_1999_sum['Production'], df_wb_4_2000_sum['Production'], df_wb_4_2001_sum['Production'], df_wb_4_2002_sum['Production'], df_wb_4_2003_sum['Production'], df_wb_4_2004_sum['Production'], df_wb_4_2005_sum['Production'], df_wb_4_2006_sum['Production'], df_wb_4_2007_sum['Production'], df_wb_4_2008_sum['Production'], df_wb_4_2009_sum['Production'], df_wb_4_2010_sum['Production'], df_wb_4_2011_sum['Production'], df_wb_4_2012_sum['Production'], df_wb_4_2013_sum['Production'], df_wb_4_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [4] BARDHAMAN (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [4] BARDHAMAN (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [5] BIRBHUM x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_5_1997_sum['Area'], df_wb_5_1998_sum['Area'], df_wb_5_1999_sum['Area'], df_wb_5_2000_sum['Area'], df_wb_5_2001_sum['Area'], df_wb_5_2002_sum['Area'], df_wb_5_2003_sum['Area'], df_wb_5_2004_sum['Area'], df_wb_5_2005_sum['Area'], df_wb_5_2006_sum['Area'], df_wb_5_2007_sum['Area'], df_wb_5_2008_sum['Area'], df_wb_5_2009_sum['Area'], df_wb_5_2010_sum['Area'], df_wb_5_2011_sum['Area'], df_wb_5_2012_sum['Area'], df_wb_5_2013_sum['Area'], df_wb_5_2014_sum['Area']) y22 =(df_wb_5_1997_sum['Production'], df_wb_5_1998_sum['Production'], df_wb_5_1999_sum['Production'], df_wb_5_2000_sum['Production'], df_wb_5_2001_sum['Production'], df_wb_5_2002_sum['Production'], df_wb_5_2003_sum['Production'], df_wb_5_2004_sum['Production'], df_wb_5_2005_sum['Production'], df_wb_5_2006_sum['Production'], df_wb_5_2007_sum['Production'], df_wb_5_2008_sum['Production'], df_wb_5_2009_sum['Production'], df_wb_5_2010_sum['Production'], df_wb_5_2011_sum['Production'], df_wb_5_2012_sum['Production'], df_wb_5_2013_sum['Production'], df_wb_5_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [5] BIRBHUM (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [5] BIRBHUM (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [6] COOCHBEHAR x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_6_1997_sum['Area'], df_wb_6_1998_sum['Area'], df_wb_6_1999_sum['Area'], df_wb_6_2000_sum['Area'], df_wb_6_2001_sum['Area'], df_wb_6_2002_sum['Area'], df_wb_6_2003_sum['Area'], df_wb_6_2004_sum['Area'], df_wb_6_2005_sum['Area'], df_wb_6_2006_sum['Area'], df_wb_6_2007_sum['Area'], df_wb_6_2008_sum['Area'], df_wb_6_2009_sum['Area'], df_wb_6_2010_sum['Area'], df_wb_6_2011_sum['Area'], df_wb_6_2012_sum['Area'], df_wb_6_2013_sum['Area'], df_wb_6_2014_sum['Area']) y22 =(df_wb_6_1997_sum['Production'], df_wb_6_1998_sum['Production'], df_wb_6_1999_sum['Production'], df_wb_6_2000_sum['Production'], df_wb_6_2001_sum['Production'], df_wb_6_2002_sum['Production'], df_wb_6_2003_sum['Production'], df_wb_6_2004_sum['Production'], df_wb_6_2005_sum['Production'], df_wb_6_2006_sum['Production'], df_wb_6_2007_sum['Production'], df_wb_6_2008_sum['Production'], df_wb_6_2009_sum['Production'], df_wb_6_2010_sum['Production'], df_wb_6_2011_sum['Production'], df_wb_6_2012_sum['Production'], df_wb_6_2013_sum['Production'], df_wb_6_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [6] COOCHBEHAR (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [6] COOCHBEHAR (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [7] DARJEELING x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_7_1997_sum['Area'], df_wb_7_1998_sum['Area'], df_wb_7_1999_sum['Area'], df_wb_7_2000_sum['Area'], df_wb_7_2001_sum['Area'], df_wb_7_2002_sum['Area'], df_wb_7_2003_sum['Area'], df_wb_7_2004_sum['Area'], df_wb_7_2005_sum['Area'], df_wb_7_2006_sum['Area'], df_wb_7_2007_sum['Area'], df_wb_7_2008_sum['Area'], df_wb_7_2009_sum['Area'], df_wb_7_2010_sum['Area'], df_wb_7_2011_sum['Area'], df_wb_7_2012_sum['Area'], df_wb_7_2013_sum['Area'], df_wb_7_2014_sum['Area']) y22 =(df_wb_7_1997_sum['Production'], df_wb_7_1998_sum['Production'], df_wb_7_1999_sum['Production'], df_wb_7_2000_sum['Production'], df_wb_7_2001_sum['Production'], df_wb_7_2002_sum['Production'], df_wb_7_2003_sum['Production'], df_wb_7_2004_sum['Production'], df_wb_7_2005_sum['Production'], df_wb_7_2006_sum['Production'], df_wb_7_2007_sum['Production'], df_wb_7_2008_sum['Production'], df_wb_7_2009_sum['Production'], df_wb_7_2010_sum['Production'], df_wb_7_2011_sum['Production'], df_wb_7_2012_sum['Production'], df_wb_7_2013_sum['Production'], df_wb_7_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [7] DARJEELING (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [7] DARJEELING (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [8] DINAJPUR DAKSHIN x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_8_1997_sum['Area'], df_wb_8_1998_sum['Area'], df_wb_8_1999_sum['Area'], df_wb_8_2000_sum['Area'], df_wb_8_2001_sum['Area'], df_wb_8_2002_sum['Area'], df_wb_8_2003_sum['Area'], df_wb_8_2004_sum['Area'], df_wb_8_2005_sum['Area'], df_wb_8_2006_sum['Area'], df_wb_8_2007_sum['Area'], df_wb_8_2008_sum['Area'], df_wb_8_2009_sum['Area'], df_wb_8_2010_sum['Area'], df_wb_8_2011_sum['Area'], df_wb_8_2012_sum['Area'], df_wb_8_2013_sum['Area'], df_wb_8_2014_sum['Area']) y22 =(df_wb_8_1997_sum['Production'], df_wb_8_1998_sum['Production'], df_wb_8_1999_sum['Production'], df_wb_8_2000_sum['Production'], df_wb_8_2001_sum['Production'], df_wb_8_2002_sum['Production'], df_wb_8_2003_sum['Production'], df_wb_8_2004_sum['Production'], df_wb_8_2005_sum['Production'], df_wb_8_2006_sum['Production'], df_wb_8_2007_sum['Production'], df_wb_8_2008_sum['Production'], df_wb_8_2009_sum['Production'], df_wb_8_2010_sum['Production'], df_wb_8_2011_sum['Production'], df_wb_8_2012_sum['Production'], df_wb_8_2013_sum['Production'], df_wb_8_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [8] DINAJPUR DAKSHIN (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [8] DINAJPUR DAKSHIN (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [9] DINAJPUR UTTAR x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_9_1997_sum['Area'], df_wb_9_1998_sum['Area'], df_wb_9_1999_sum['Area'], df_wb_9_2000_sum['Area'], df_wb_9_2001_sum['Area'], df_wb_9_2002_sum['Area'], df_wb_9_2003_sum['Area'], df_wb_9_2004_sum['Area'], df_wb_9_2005_sum['Area'], df_wb_9_2006_sum['Area'], df_wb_9_2007_sum['Area'], df_wb_9_2008_sum['Area'], df_wb_9_2009_sum['Area'], df_wb_9_2010_sum['Area'], df_wb_9_2011_sum['Area'], df_wb_9_2012_sum['Area'], df_wb_9_2013_sum['Area'], df_wb_9_2014_sum['Area']) y22 =(df_wb_9_1997_sum['Production'], df_wb_9_1998_sum['Production'], df_wb_9_1999_sum['Production'], df_wb_9_2000_sum['Production'], df_wb_9_2001_sum['Production'], df_wb_9_2002_sum['Production'], df_wb_9_2003_sum['Production'], df_wb_9_2004_sum['Production'], df_wb_9_2005_sum['Production'], df_wb_9_2006_sum['Production'], df_wb_9_2007_sum['Production'], df_wb_9_2008_sum['Production'], df_wb_9_2009_sum['Production'], df_wb_9_2010_sum['Production'], df_wb_9_2011_sum['Production'], df_wb_9_2012_sum['Production'], df_wb_9_2013_sum['Production'], df_wb_9_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [9] DINAJPUR UTTAR (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [9] DINAJPUR UTTAR (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [10] HOOGHLY x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_10_1997_sum['Area'], df_wb_10_1998_sum['Area'], df_wb_10_1999_sum['Area'], df_wb_10_2000_sum['Area'], df_wb_10_2001_sum['Area'], df_wb_10_2002_sum['Area'], df_wb_10_2003_sum['Area'], df_wb_10_2004_sum['Area'], df_wb_10_2005_sum['Area'], df_wb_10_2006_sum['Area'], df_wb_10_2007_sum['Area'], df_wb_10_2008_sum['Area'], df_wb_10_2009_sum['Area'], df_wb_10_2010_sum['Area'], df_wb_10_2011_sum['Area'], df_wb_10_2012_sum['Area'], df_wb_10_2013_sum['Area'], df_wb_10_2014_sum['Area']) y22 =(df_wb_10_1997_sum['Production'], df_wb_10_1998_sum['Production'], df_wb_10_1999_sum['Production'], df_wb_10_2000_sum['Production'], df_wb_10_2001_sum['Production'], df_wb_10_2002_sum['Production'], df_wb_10_2003_sum['Production'], df_wb_10_2004_sum['Production'], df_wb_10_2005_sum['Production'], df_wb_10_2006_sum['Production'], df_wb_10_2007_sum['Production'], df_wb_10_2008_sum['Production'], df_wb_10_2009_sum['Production'], df_wb_10_2010_sum['Production'], df_wb_10_2011_sum['Production'], df_wb_10_2012_sum['Production'], df_wb_10_2013_sum['Production'], df_wb_10_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [10] HOOGHLY (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [10] HOOGHLY (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [11] HOWRAH x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_11_1997_sum['Area'], df_wb_11_1998_sum['Area'], df_wb_11_1999_sum['Area'], df_wb_11_2000_sum['Area'], df_wb_11_2001_sum['Area'], df_wb_11_2002_sum['Area'], df_wb_11_2003_sum['Area'], df_wb_11_2004_sum['Area'], df_wb_11_2005_sum['Area'], df_wb_11_2006_sum['Area'], df_wb_11_2007_sum['Area'], df_wb_11_2008_sum['Area'], df_wb_11_2009_sum['Area'], df_wb_11_2010_sum['Area'], df_wb_11_2011_sum['Area'], df_wb_11_2012_sum['Area'], df_wb_11_2013_sum['Area'], df_wb_11_2014_sum['Area']) y22 =(df_wb_11_1997_sum['Production'], df_wb_11_1998_sum['Production'], df_wb_11_1999_sum['Production'], df_wb_11_2000_sum['Production'], df_wb_11_2001_sum['Production'], df_wb_11_2002_sum['Production'], df_wb_11_2003_sum['Production'], df_wb_11_2004_sum['Production'], df_wb_11_2005_sum['Production'], df_wb_11_2006_sum['Production'], df_wb_11_2007_sum['Production'], df_wb_11_2008_sum['Production'], df_wb_11_2009_sum['Production'], df_wb_11_2010_sum['Production'], df_wb_11_2011_sum['Production'], df_wb_11_2012_sum['Production'], df_wb_11_2013_sum['Production'], df_wb_11_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [11] HOWRAH (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [11] HOWRAH (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [12] JALPAIGURI x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_12_1997_sum['Area'], df_wb_12_1998_sum['Area'], df_wb_12_1999_sum['Area'], df_wb_12_2000_sum['Area'], df_wb_12_2001_sum['Area'], df_wb_12_2002_sum['Area'], df_wb_12_2003_sum['Area'], df_wb_12_2004_sum['Area'], df_wb_12_2005_sum['Area'], df_wb_12_2006_sum['Area'], df_wb_12_2007_sum['Area'], df_wb_12_2008_sum['Area'], df_wb_12_2009_sum['Area'], df_wb_12_2010_sum['Area'], df_wb_12_2011_sum['Area'], df_wb_12_2012_sum['Area'], df_wb_12_2013_sum['Area'], df_wb_12_2014_sum['Area']) y22 =(df_wb_12_1997_sum['Production'], df_wb_12_1998_sum['Production'], df_wb_12_1999_sum['Production'], df_wb_12_2000_sum['Production'], df_wb_12_2001_sum['Production'], df_wb_12_2002_sum['Production'], df_wb_12_2003_sum['Production'], df_wb_12_2004_sum['Production'], df_wb_12_2005_sum['Production'], df_wb_12_2006_sum['Production'], df_wb_12_2007_sum['Production'], df_wb_12_2008_sum['Production'], df_wb_12_2009_sum['Production'], df_wb_12_2010_sum['Production'], df_wb_12_2011_sum['Production'], df_wb_12_2012_sum['Production'], df_wb_12_2013_sum['Production'], df_wb_12_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [12] JALPAIGURI (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [12] JALPAIGURI (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [13] MALDAH x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_13_1997_sum['Area'], df_wb_13_1998_sum['Area'], df_wb_13_1999_sum['Area'], df_wb_13_2000_sum['Area'], df_wb_13_2001_sum['Area'], df_wb_13_2002_sum['Area'], df_wb_13_2003_sum['Area'], df_wb_13_2004_sum['Area'], df_wb_13_2005_sum['Area'], df_wb_13_2006_sum['Area'], df_wb_13_2007_sum['Area'], df_wb_13_2008_sum['Area'], df_wb_13_2009_sum['Area'], df_wb_13_2010_sum['Area'], df_wb_13_2011_sum['Area'], df_wb_13_2012_sum['Area'], df_wb_13_2013_sum['Area'], df_wb_13_2014_sum['Area']) y22 =(df_wb_13_1997_sum['Production'], df_wb_13_1998_sum['Production'], df_wb_13_1999_sum['Production'], df_wb_13_2000_sum['Production'], df_wb_13_2001_sum['Production'], df_wb_13_2002_sum['Production'], df_wb_13_2003_sum['Production'], df_wb_13_2004_sum['Production'], df_wb_13_2005_sum['Production'], df_wb_13_2006_sum['Production'], df_wb_13_2007_sum['Production'], df_wb_13_2008_sum['Production'], df_wb_13_2009_sum['Production'], df_wb_13_2010_sum['Production'], df_wb_13_2011_sum['Production'], df_wb_13_2012_sum['Production'], df_wb_13_2013_sum['Production'], df_wb_13_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [13] MALDAH (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [13] MALDAH (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [14] MEDINIPUR EAST x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_14_1997_sum['Area'], df_wb_14_1998_sum['Area'], df_wb_14_1999_sum['Area'], df_wb_14_2000_sum['Area'], df_wb_14_2001_sum['Area'], df_wb_14_2002_sum['Area'], df_wb_14_2003_sum['Area'], df_wb_14_2004_sum['Area'], df_wb_14_2005_sum['Area'], df_wb_14_2006_sum['Area'], df_wb_14_2007_sum['Area'], df_wb_14_2008_sum['Area'], df_wb_14_2009_sum['Area'], df_wb_14_2010_sum['Area'], df_wb_14_2011_sum['Area'], df_wb_14_2012_sum['Area'], df_wb_14_2013_sum['Area'], df_wb_14_2014_sum['Area']) y22 =(df_wb_14_1997_sum['Production'], df_wb_14_1998_sum['Production'], df_wb_14_1999_sum['Production'], df_wb_14_2000_sum['Production'], df_wb_14_2001_sum['Production'], df_wb_14_2002_sum['Production'], df_wb_14_2003_sum['Production'], df_wb_14_2004_sum['Production'], df_wb_14_2005_sum['Production'], df_wb_14_2006_sum['Production'], df_wb_14_2007_sum['Production'], df_wb_14_2008_sum['Production'], df_wb_14_2009_sum['Production'], df_wb_14_2010_sum['Production'], df_wb_14_2011_sum['Production'], df_wb_14_2012_sum['Production'], df_wb_14_2013_sum['Production'], df_wb_14_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [14] MEDINIPUR EAST (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [14] MEDINIPUR EAST (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [15] MEDINIPUR WEST x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_15_1997_sum['Area'], df_wb_15_1998_sum['Area'], df_wb_15_1999_sum['Area'], df_wb_15_2000_sum['Area'], df_wb_15_2001_sum['Area'], df_wb_15_2002_sum['Area'], df_wb_15_2003_sum['Area'], df_wb_15_2004_sum['Area'], df_wb_15_2005_sum['Area'], df_wb_15_2006_sum['Area'], df_wb_15_2007_sum['Area'], df_wb_15_2008_sum['Area'], df_wb_15_2009_sum['Area'], df_wb_15_2010_sum['Area'], df_wb_15_2011_sum['Area'], df_wb_15_2012_sum['Area'], df_wb_15_2013_sum['Area'], df_wb_15_2014_sum['Area']) y22 =(df_wb_15_1997_sum['Production'], df_wb_15_1998_sum['Production'], df_wb_15_1999_sum['Production'], df_wb_15_2000_sum['Production'], df_wb_15_2001_sum['Production'], df_wb_15_2002_sum['Production'], df_wb_15_2003_sum['Production'], df_wb_15_2004_sum['Production'], df_wb_15_2005_sum['Production'], df_wb_15_2006_sum['Production'], df_wb_15_2007_sum['Production'], df_wb_15_2008_sum['Production'], df_wb_15_2009_sum['Production'], df_wb_15_2010_sum['Production'], df_wb_15_2011_sum['Production'], df_wb_15_2012_sum['Production'], df_wb_15_2013_sum['Production'], df_wb_15_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [15] MEDINIPUR WEST (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [15] MEDINIPUR WEST (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [16] MURSHIDABAD x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_16_1997_sum['Area'], df_wb_16_1998_sum['Area'], df_wb_16_1999_sum['Area'], df_wb_16_2000_sum['Area'], df_wb_16_2001_sum['Area'], df_wb_16_2002_sum['Area'], df_wb_16_2003_sum['Area'], df_wb_16_2004_sum['Area'], df_wb_16_2005_sum['Area'], df_wb_16_2006_sum['Area'], df_wb_16_2007_sum['Area'], df_wb_16_2008_sum['Area'], df_wb_16_2009_sum['Area'], df_wb_16_2010_sum['Area'], df_wb_16_2011_sum['Area'], df_wb_16_2012_sum['Area'], df_wb_16_2013_sum['Area'], df_wb_16_2014_sum['Area']) y22 =(df_wb_16_1997_sum['Production'], df_wb_16_1998_sum['Production'], df_wb_16_1999_sum['Production'], df_wb_16_2000_sum['Production'], df_wb_16_2001_sum['Production'], df_wb_16_2002_sum['Production'], df_wb_16_2003_sum['Production'], df_wb_16_2004_sum['Production'], df_wb_16_2005_sum['Production'], df_wb_16_2006_sum['Production'], df_wb_16_2007_sum['Production'], df_wb_16_2008_sum['Production'], df_wb_16_2009_sum['Production'], df_wb_16_2010_sum['Production'], df_wb_16_2011_sum['Production'], df_wb_16_2012_sum['Production'], df_wb_16_2013_sum['Production'], df_wb_16_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [16] MURSHIDABAD (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [16] MURSHIDABAD (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [17] NADIA x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_17_1997_sum['Area'], df_wb_17_1998_sum['Area'], df_wb_17_1999_sum['Area'], df_wb_17_2000_sum['Area'], df_wb_17_2001_sum['Area'], df_wb_17_2002_sum['Area'], df_wb_17_2003_sum['Area'], df_wb_17_2004_sum['Area'], df_wb_17_2005_sum['Area'], df_wb_17_2006_sum['Area'], df_wb_17_2007_sum['Area'], df_wb_17_2008_sum['Area'], df_wb_17_2009_sum['Area'], df_wb_17_2010_sum['Area'], df_wb_17_2011_sum['Area'], df_wb_17_2012_sum['Area'], df_wb_17_2013_sum['Area'], df_wb_17_2014_sum['Area']) y22 =(df_wb_17_1997_sum['Production'], df_wb_17_1998_sum['Production'], df_wb_17_1999_sum['Production'], df_wb_17_2000_sum['Production'], df_wb_17_2001_sum['Production'], df_wb_17_2002_sum['Production'], df_wb_17_2003_sum['Production'], df_wb_17_2004_sum['Production'], df_wb_17_2005_sum['Production'], df_wb_17_2006_sum['Production'], df_wb_17_2007_sum['Production'], df_wb_17_2008_sum['Production'], df_wb_17_2009_sum['Production'], df_wb_17_2010_sum['Production'], df_wb_17_2011_sum['Production'], df_wb_17_2012_sum['Production'], df_wb_17_2013_sum['Production'], df_wb_17_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [17] NADIA (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [17] NADIA (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show() # plotting wb : [18] PURULIA x1 = ('1997','1998','1999','2000','2001','2002','2003','2004','2005', '2006','2007','2008','2009','2010','2011','2012','2013','2014') y11 =(df_wb_18_1997_sum['Area'], df_wb_18_1998_sum['Area'], df_wb_18_1999_sum['Area'], df_wb_18_2000_sum['Area'], df_wb_18_2001_sum['Area'], df_wb_18_2002_sum['Area'], df_wb_18_2003_sum['Area'], df_wb_18_2004_sum['Area'], df_wb_18_2005_sum['Area'], df_wb_18_2006_sum['Area'], df_wb_18_2007_sum['Area'], df_wb_18_2008_sum['Area'], df_wb_18_2009_sum['Area'], df_wb_18_2010_sum['Area'], df_wb_18_2011_sum['Area'], df_wb_18_2012_sum['Area'], df_wb_18_2013_sum['Area'], df_wb_18_2014_sum['Area']) y22 =(df_wb_18_1997_sum['Production'], df_wb_18_1998_sum['Production'], df_wb_18_1999_sum['Production'], df_wb_18_2000_sum['Production'], df_wb_18_2001_sum['Production'], df_wb_18_2002_sum['Production'], df_wb_18_2003_sum['Production'], df_wb_18_2004_sum['Production'], df_wb_18_2005_sum['Production'], df_wb_18_2006_sum['Production'], df_wb_18_2007_sum['Production'], df_wb_18_2008_sum['Production'], df_wb_18_2009_sum['Production'], df_wb_18_2010_sum['Production'], df_wb_18_2011_sum['Production'], df_wb_18_2012_sum['Production'], df_wb_18_2013_sum['Production'], df_wb_18_2014_sum['Production']) plt.subplot(121) plt.title('State-5 : wb : [18] PURULIA (Area) :') plt.xlabel('year -->') plt.ylabel('area -->') plt.plot(x1,y11) plt.show plt.subplot(122) plt.title('State-5 : wb : [18] PURULIA (Production) :') plt.xlabel('year -->') plt.ylabel('production -->') plt.plot(x1,y22) plt.show()