import json
import numpy as np
import matplotlib.pylab as plt
import math
from datetime import datetime
import pandas as pd
data = []
with open("bitcoin.json") as f:
    for i,j in json.load(f)["bpi"].items():
        data.append([datetime.strptime(i,"%Y-%m-%d"), j])
    for date, value in data:
        pass

all_dates=[]
price=[]
dates_2018=[]
price_2018=[]

for date,value in data:
    all_dates.append(date)
    price.append(value)
    a=str(date)
    if "2018" in a:
        dates_2018.append(date)
        price_2018.append(value)
    if "2019" in a:
        break
# print(dates_2018)
# print(price_2018)
plt.plot(dates_2018,price_2018,"b-")
# plt.show()
# plt.savefig("2018.png")
weekly_price=[]
x=0
y=7
# for i in price_2018[x:y]:
#     b.append(i)
#     weekly_price.append(sum(b[x:y])/7)
#     x+=7
#     y+=7
#     if x==364:
#         break
# print(sum(b(0,7)))
# print(weekly_price)
# print(len(weekly_price))
# counter=0
# week=0
# week1=0
# while counter!=364:
#     counter+=1
#     weekly_price+=price_2018[counter]
#     week1=week/7
#     if counter%7 == 0:
#         weekly_price.append(week)
# print(weekly_price)
# print(len(weekly_price))

# store sum every 7 values
weeks=[i for i in range(0,53)]
    # weeks=datetime.strptime("%Y"-"%m"-"%d")
while x<364:
    weekly_price.append(sum(price_2018[x:y])/7)
    x+=7
    y+=7

# print(price_2018)
weekly_average=[]
for pr in weekly_price:
    for i in range(0,7):
        weekly_average.append(pr)
weekly_average.append(price_2018[364])
print(weekly_average)


print(weekly_price)
print(len(weekly_price))
plt.xlabel("Dates2018")
plt.ylabel("Price")
plt.title("WeeklyAverage Red, YearlyPrice Blue")
plt.plot(dates_2018,weekly_average,"r-")
# plt.show()
plt.savefig("weeklyaverageanddailyprice.png")
# print(weeks)