# -*- coding: utf-8 -*-

"""

Created on Fri Nov 27 08:09:11 2020

@author: Tin

"""

# Plot Candlestick in Matplotlib

import pandas as pd # Dataframe Library

import matplotlib.pyplot as plt # Plot Chart Library

pd.set_option('max_columns', None) # To show all columns

import yfinance as yf

yf.pdr_override()

# input

symbol = 'AAPL'

start = '2019-01-01'

end = '2020-01-01'

# dataframe

data = yf.download(symbol,start,end)

data['VolumePositive'] = data['Open'] < data['Adj Close']

print('Line Chart')

fig = plt.figure(figsize=(14,10))

ax1 = plt.subplot(3, 1, 1)

ax1.plot(data['Adj Close'])

ax1.set_title('Stock '+ symbol +' Closing Price')

ax1.set_ylabel('Price')

ax1.legend(loc='best')

ax2 = plt.subplot(3, 1, 2)

ax2.plot(data['Volume'], label='Volume')

ax2.grid()

ax2.legend(loc='best')

ax2.set_ylabel('Volume')

ax3 = plt.subplot(3, 1, 3)

ax3v = ax3.twinx()

colors = data.VolumePositive.map({True: 'g', False: 'r'})

ax3v.bar(data.index, data['Volume'], color=colors, alpha=0.4)

ax3.set_ylabel('Volume')

ax3.grid()

ax3.set_xlabel('Date')

# Candlestick

print('Candlestick')

from matplotlib import dates as mdates

dfc = data.copy()

dfc['VolumePositive'] = dfc['Open'] < dfc['Adj Close']

#dfc = dfc.dropna()

dfc = dfc.reset_index()

dfc['Date'] = pd.to_datetime(dfc['Date'])

dfc['Date'] = dfc['Date'].apply(mdates.date2num)

dfc.head()

from mpl_finance import candlestick_ohlc

fig = plt.figure(figsize=(14,10))

ax1 = plt.subplot(3, 1, 1)

candlestick_ohlc(ax1,dfc.values, width=0.5, colorup='g', colordown='r', alpha=1.0)

ax1.xaxis_date()

ax1.xaxis.set_major_formatter(mdates.DateFormatter('%d-%m-%Y'))

ax1.grid(True, which='both')

ax1.minorticks_on()

ax1v = ax1.twinx()

colors = dfc.VolumePositive.map({True: 'g', False: 'r'})

ax1v.bar(dfc.Date, dfc['Volume'], color=colors, alpha=0.4)

ax1v.axes.yaxis.set_ticklabels([])

ax1v.set_ylim(0, 3*data.Volume.max())

ax1.set_title('Stock '+ symbol +' Closing Price')

ax1.set_ylabel('Price')

ax2 = plt.subplot(3, 1, 2)

ax2.plot(data['Volume'], label='Volume')

ax2.grid()

ax2.legend(loc='best')

ax2.set_ylabel('Volume')

ax3 = plt.subplot(3, 1, 3)

ax3v = ax3.twinx()

colors = data.VolumePositive.map({True: 'g', False: 'r'})

ax3v.bar(data.index, data['Volume'], color=colors, alpha=0.4)

ax3.set_ylabel('Volume')

ax3.grid()

ax3.set_xlabel('Date')