Example of how to use ta-lib to plot some financial graphs.

talib-example.py

#%%
# Made the following example work in python 3
# https://github.com/mellertson/talib-macd-example/blob/master/talib-macd-matplotlib-example.py
#
# To get it working do the following:
# use anaconda 3 https://www.anaconda.com/download/#linux
# if using manjaro linux install TA-lib from the package manager otherwise lookup instructions on how to install TA-lib on your system 
# cd ~/anaconda3/bin; ./pip install pandas_datareader
# cd ~/anaconda3/bin; ./pip install TA-Lib
# cd ~/anaconda3/bin; ./pip install https://github.com/matplotlib/mpl_finance/archive/master.zip
from pandas_datareader import data
import pandas as pd
import numpy as np
import talib as ta
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.gridspec as gridspec
from matplotlib.dates import date2num
# from matplotlib.finance import candlestick_ohlc as candlestick
from mpl_finance import candlestick_ohlc as candlestick
import datetime

ticker = 'OPK'

# Download sample data
sec_id = data.get_data_yahoo(ticker, '2014-06-01')

# Data for matplotlib finance plot
sec_id_ochl = np.array(pd.DataFrame({'0':date2num(sec_id.index.to_pydatetime()),
                                  '1':sec_id.Open,
                                  '2':sec_id.Close,
                                  '3':sec_id.High,
                                  '4':sec_id.Low}))

# Technical Analysis
SMA_FAST = 50
SMA_SLOW = 200
RSI_PERIOD = 14
RSI_AVG_PERIOD = 15
MACD_FAST = 12
MACD_SLOW = 26
MACD_SIGNAL = 9
STOCH_K = 14
STOCH_D = 3
SIGNAL_TOL = 3
Y_AXIS_SIZE = 12

analysis = pd.DataFrame(index = sec_id.index)

analysis['sma_f'] = sec_id.Close.rolling(SMA_FAST).mean()
analysis['sma_s'] = sec_id.Close.rolling(SMA_SLOW).mean()
analysis['rsi'] = ta.RSI(sec_id.Close.as_matrix(), RSI_PERIOD)
analysis['sma_r'] = analysis.rsi.rolling(RSI_AVG_PERIOD).mean() # check shift
analysis['macd'], analysis['macdSignal'], analysis['macdHist'] = ta.MACD(sec_id.Close.as_matrix(), fastperiod=MACD_FAST, slowperiod=MACD_SLOW, signalperiod=MACD_SIGNAL)
analysis['stoch_k'], analysis['stoch_d'] = ta.STOCH(sec_id.High.as_matrix(), sec_id.Low.as_matrix(), sec_id.Close.as_matrix(), slowk_period=STOCH_K, slowd_period=STOCH_D)

analysis['sma'] = np.where(analysis.sma_f > analysis.sma_s, 1, 0)
analysis['macd_test'] = np.where((analysis.macd > analysis.macdSignal), 1, 0)
analysis['stoch_k_test'] = np.where((analysis.stoch_k < 50) & (analysis.stoch_k > analysis.stoch_k.shift(1)), 1, 0)
analysis['rsi_test'] = np.where((analysis.rsi < 50) & (analysis.rsi > analysis.rsi.shift(1)), 1, 0)

# Prepare plot
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, sharex=True)
ax1.set_ylabel(ticker, size=20)
ax1.yaxis.tick_right()
ax1.yaxis.set_label_position("right")

#size plot
fig.set_size_inches(15,30)

# Plot candles
candlestick(ax1, sec_id_ochl, width=0.5, colorup='g', colordown='r', alpha=1)

# Draw Moving Averages
analysis.sma_f.plot(ax=ax1, c='r')
analysis.sma_s.plot(ax=ax1, c='g')

#RSI
ax2.set_ylabel('RSI', size=Y_AXIS_SIZE)
analysis.rsi.plot(ax = ax2, c='g', label = 'Period: ' + str(RSI_PERIOD))
analysis.sma_r.plot(ax = ax2, c='r', label = 'MA: ' + str(RSI_AVG_PERIOD))
ax2.axhline(y=30, c='b')
ax2.axhline(y=50, c='black')
ax2.axhline(y=70, c='b')
ax2.set_ylim([0,100])
handles, labels = ax2.get_legend_handles_labels()
ax2.legend(handles, labels)

# Draw MACD computed with Talib
ax3.set_ylabel('MACD: '+ str(MACD_FAST) + ', ' + str(MACD_SLOW) + ', ' + str(MACD_SIGNAL), size=Y_AXIS_SIZE)
analysis.macd.plot(ax=ax3, color='b', label='Macd')
analysis.macdSignal.plot(ax=ax3, color='g', label='Signal')
analysis.macdHist.plot(ax=ax3, color='r', label='Hist')
ax3.axhline(0, lw=2, color='0')
handles, labels = ax3.get_legend_handles_labels()
ax3.legend(handles, labels)

# Stochastic plot
ax4.set_ylabel('Stoch (k,d)', size=Y_AXIS_SIZE)
analysis.stoch_k.plot(ax=ax4, label='stoch_k:'+ str(STOCH_K), color='r')
analysis.stoch_d.plot(ax=ax4, label='stoch_d:'+ str(STOCH_D), color='g')
handles, labels = ax4.get_legend_handles_labels()
ax4.legend(handles, labels)
ax4.axhline(y=20, c='b')
ax4.axhline(y=50, c='black')
ax4.axhline(y=80, c='b')

plt.show()