def create_soc_piechart(uid,fieldid,img_type, image_date):
	import matplotlib.pyplot as plt
	import numpy as np
	import os,sys
	import cv2
	import csv
	import matplotlib.patches as mpatches
	import matplotlib.pyplot as plt
	import numpy as np
	import os,sys
	import cv2
	import csv
	import firebase_admin
	from firebase_admin import credentials
	from firebase_admin import db
	import seaborn as sns
	sns.set()
	import csv
	import time
	import traceback
	import xlsxwriter
	cred = credentials.Certificate('servicekey.json')
	try:
		firebase_admin.initialize_app(cred, {'databaseURL': 'https://farmbase-b2f7e-31c0c.firebaseio.com/'})
	except:
		wes1 = 1#print('fire running')
	import matplotlib.patches as mpatches
	plt.rcParams.update({'font.size':12})
	lb='SOC: '
	lb2 = 'SOC'	
	labels = (lb+'less than 0.05%'),(lb+'0.05% to 0.075%'),(lb+'0.075% to 0.1%'),(lb+'0.1% to 0.112%'),(lb+'0.112% to 0.125%'),(lb+'0.125% to 0.137%'),(lb+'0.137% to 0.15%'),(lb+'0.15% to 0.2%'),(lb+'0.2% to 0.25%'),(lb+' more than 0.25%')

	cmap = ["#ab0535","#ea4f3b","#f7885a","#fbc07e","#fff0b5","#e6f3a4","#bae383","#81bf6c","#11a75f","#06653d"]
	file_name = uid + '/' + fieldid + '/IndexValues_'+img_type+'.csv'
	abc = 0
	sqm = []
	#ind_values = []
	explode = (0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2)
	with open(file_name,'rt') as f:
		data = csv.reader(f)
		for row in data:
			print('myrow',row)
			db.reference('PaidMonitoredFields').child('PMF').child(uid).child(fieldid).child('IndexBreakdown').child(image_date).child(img_type).set(row[1:11])
			for values in row:
				if (abc>0) and (abc<11):
					sq1 = (float(values)/10000)
					sq1 = round(sq1,1)
					#ind_values.append(sq1)
					ss = str(values) + ' sq. m.'
					sqm.append(ss)
				if abc==0:
					avg_ind_value = values
				if abc==11:
					field_area = values
				abc = abc+1
	fig1,ax1 = plt.subplots()
	print(labels)
	# print(ind_values)
	# sizes = ind_values
	#ax1.set_prop_cycle("color",cmap)
	#ax1.pie(ind_values,labeldistance = 2, explode=explode, labels=labels, autopct='%1.1f%%',shadow=True, startangle=90)
	ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.
	ax1.set_title(("Field Area (in square meters) with Different SOC%"))
	patch1 = mpatches.Patch(color="#ab0535",label=(labels[0]+' -> '+sqm[0]))
	patch2 = mpatches.Patch(color="#ea4f3b",label=(labels[1]+' -> '+sqm[1]))
	patch3 = mpatches.Patch(color="#f7885a",label=(labels[2]+' -> '+sqm[2]))
	patch4 = mpatches.Patch(color="#fbc07e",label=(labels[3]+' -> '+sqm[3]))
	patch5 = mpatches.Patch(color="#fff0b5",label=(labels[4]+' -> '+sqm[4]))
	patch6 = mpatches.Patch(color="#e6f3a4",label=(labels[5]+' -> '+sqm[5]))
	patch7 = mpatches.Patch(color="#bae383",label=(labels[6]+' -> '+sqm[6]))
	patch8 = mpatches.Patch(color="#81bf6c",label=(labels[7]+' -> '+sqm[7]))
	patch9 = mpatches.Patch(color="#11a75f",label=(labels[8]+' -> '+sqm[8]))
	patch10 = mpatches.Patch(color="#06653d",label=(labels[9]+' -> '+sqm[9]))
	ax1.legend(loc = 'center',handles=[patch10,patch9,patch8,patch7,patch6,patch5,patch4,patch3,patch2,patch1],title='Field Area with Different SOC%')
	plt.show()
	file_name = uid+ '/' + fieldid +'/'+img_type+'_piechart.png'
	plt.savefig(file_name)
	plt.close()
	pie_c =	cv2.imread(file_name)
	pie_c = pie_c[100:400,120:500]
	cv2.imwrite(file_name,pie_c)

	return avg_ind_value