replace former example with csvread of google data; remove binance API call

Author: andrewrgarcia

tests/test_ema.py

@@ -1,67 +1,15 @@
-
 import mplfinance as mpf
-import requests        # for making http requests to binance
-import json            # for parsing what binance sends back to us
-import pandas as pd    # for storing and manipulating the data we get back
-import numpy as np     # numerical python, i usually need this somewhere
-# and so i import by habit nowadays
-
-import matplotlib.pyplot as plt  # for charts and such
-import datetime as dt  # for dealing with times
-
-INTERVAL = '1d'
-
-
-def get_bars(quote, interval=INTERVAL):
-
-    root_url = 'https://api.binance.com/api/v1/klines'
-    url = root_url + '?symbol=' + quote + '&interval=' + interval
-    data = json.loads(requests.get(url).text)
-    df = pd.DataFrame(data)
-    df.columns = ['open_time',
-                  'o', 'h', 'l', 'c', 'v',
-                  'close_time', 'qav', 'num_trades',
-                  'taker_base_vol', 'taker_quote_vol', 'ignore'
-    ]
-
-    df.index = [dt.datetime.fromtimestamp(x/1000.0) for x in df.close_time]
-
-    return df
-
-
-def coinpair(quote, interval='1d', base='USDT'):
-    '''returns ohlc data of the quote cryptocurrency with
-        the base currency (i.e. 'market'); base for alts must be either USDT or BTC'''
-
-    btcusd = 1 if quote == 'BTC' else \
-                            get_bars('BTCUSDT', interval=interval)['c'].astype('float') \
-                            if base == 'USDT' else 1
-
-    base0 = 'USDT' if quote == 'BTC' else 'BTC'
-
-    df = get_bars(quote + base0, interval=interval)
-
-    df['close'] = df['c'].astype('float')*btcusd
-    df['open' ] = df['o'].astype('float')*btcusd
-    df['high' ] = df['h'].astype('float')*btcusd
-    df['low'  ] = df['l'].astype('float')*btcusd
-
-    df.drop(['o', 'h', 'l', 'c'], axis=1, inplace=True)
-    print(quote, base, 'on {} candles'.format(interval))
-
-    return df
-
+import pandas as pd   
 
 def test_ema():
 
-    coin = 'BTC'
-    market = 'USDT'
-    candles = '1M'
+    df = pd.read_csv('./examples/data/yahoofinance-GOOG-20040819-20180120.csv', parse_dates=True)
+    df.index = pd.DatetimeIndex(df['Date'])
 
-    df = coinpair(coin, interval=candles, base=market)
+    df = df[-50:]               # show last 50 data points only                     
 
-    ema25 = df['close'].ewm(span=25.0, adjust=False).mean()
-    mav25 = df['close'].rolling(window=25).mean()
+    ema25 = df['Close'].ewm(span=25.0, adjust=False).mean()       
+    mav25 = df['Close'].rolling(window=25).mean()
 
     ap = [
         mpf.make_addplot(df, panel=1, type='ohlc', color='c',
@@ -73,7 +21,7 @@ def test_ema():
     ]
 
     mpf.plot(df, ylabel="mpf ema", type='ohlc',
-             ema=25, addplot=ap, panel_ratios=(1, 1))
-
+             ema=25, addplot=ap, panel_ratios=(1, 1)
+    )
 
 test_ema()