datavisualp3.py

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
from mpl_finance import candlestick_ohlc
from matplotlib import style

import numpy as np
import urllib
import datetime as dt

style.use('fivethirtyeight')
print(plt.style.available)

print(plt.__file__)


def bytespdate2num(fmt, encoding='utf-8'):
    strconverter = mdates.strpdate2num(fmt)
    def bytesconverter(b):
        s = b.decode(encoding)
        return strconverter(s)
    return bytesconverter
    

def graph_data(stock):

    fig = plt.figure()
    ax1 = plt.subplot2grid((1,1), (0,0))
    
    stock_price_url = 'https://pythonprogramming.net/yahoo_finance_replacement'
    source_code = urllib.request.urlopen(stock_price_url).read().decode()
    stock_data = []
    split_source = source_code.split('\n')
    for line in split_source:
        split_line = line.split(',')
        if len(split_line) == 6:
            if 'values' not in line and 'labels' not in line:
                stock_data.append(line)

    
    date, closep, highp, lowp, openp, volume = np.loadtxt(stock_data,
                                                        delimiter=',',
                                                        unpack=True,
                                                        converters={0: bytespdate2num('%Y%m%d')})

    x = 0
    y = len(date)
    ohlc = []

    while x < y:
        append_me = date[x], openp[x], highp[x], lowp[x], closep[x], volume[x]
        ohlc.append(append_me)
        x+=1


    candlestick_ohlc(ax1, ohlc, width=0.4, colorup='#77d879', colordown='#db3f3f')
    for label in ax1.xaxis.get_ticklabels():
        label.set_rotation(45)

    ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
    ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
    ax1.grid(True)
    ax1.annotate('Bad News!',(date[9],highp[9]),
                xytext=(0.8, 0.9), textcoords='axes fraction',
                arrowprops = dict(facecolor='grey',color='grey'))
    
##    # Text placement example:
##    font_dict = {'family':'serif',
##                 'color':'darkred',
##                 'size':15}
##    ax1.text(date[10], closep[1],'Text Example', fontdict=font_dict)

    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.title(stock)
    #plt.legend()
    plt.subplots_adjust(left=0.09, bottom=0.20, right=0.94, top=0.90, wspace=0.2, hspace=0)
    plt.show()


graph_data('ebay')