import pandas as pd
import matplotlib.pyplot as plt
import pandas_datareader as web
from datetime import date
import dateutil.relativedelta

interval = 30
level = 3

# read csv
tickers = pd.read_csv('stock.csv').to_records(index=False)
tickers = [i[0] for i in tickers]

# get figure
today = date.today()
start_date = today + dateutil.relativedelta.relativedelta(days=-1 * interval * (level + 1))
stocks = web.DataReader(tickers, 'yahoo', start=start_date, end=today)['Adj Close']

print('info')
print(stocks.info())

# calc returns
stocks_returns = stocks.resample(str(interval) + 'D').ffill().pct_change()

# calc risks
days = stocks_returns.index
rows = []
for i in range(len(days) - 1):
    price_in_period = stocks.loc[days[i]:days[i + 1]]
    risks = price_in_period.pct_change().std()
    for symbol in risks.index:
        r = stocks_returns.loc[days[i + 1]]
        row = {'Date': days[i + 1], 'Symbols': symbol,
               'Return': r.loc[symbol],
               'Risk': risks.loc[symbol]}
        rows.append(row)

df = pd.DataFrame(rows)
print('df')
print(df)

symbols = df.Symbols.unique()
colors = ['b', 'r', 'k', 'y', 'g']
date = df.Date.unique()

# plot line chart
for s in range(len(symbols)):
    color = colors[s]
    symbol_data = df.loc[df['Symbols'] == symbols[s]]

    for i in range(len(date) - 1):
        plt.plot([symbol_data['Risk'].iloc[i], symbol_data['Risk'].iloc[i + 1]],
                 [symbol_data['Return'].iloc[i], symbol_data['Return'].iloc[i + 1]], color + '-')

    last_data = symbol_data.iloc[len(date) - 1]
    plt.text(last_data['Risk'], last_data['Return'], symbols[s], fontsize=9)

# add 0 return line
plt.axhline(y=0, color='k', linestyle='-')
plt.show()