带有 pandas.io.data 的 Python ta-lib : candlestick not plotting but other charts are ok

Question

iPython 2.3.1，OS-X 优胜美地 10.10.2
Python 打印 (sys.version):
2.7.6(默认，2014 年 9 月 9 日，15:04:36)
[GCC 4.2.1 兼容 Apple LLVM 6.0 (clang-600.0.39)]

以下代码适用于为美国股票数据提取的数据，例如为 Intel 设置安全 ID“INTC”。但是，当我访问欧洲股票的数据时，即使所有 OHLC 数据都在数据框中，烛台功能也会失败。已将完整代码放于此处，以表明其他技术分析图表绘制的欧洲股票数据效果很好。

import pandas.io.data as web
import pandas as pd
import numpy as np
import talib as ta
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib.dates import date2num
from matplotlib.finance import candlestick
import datetime

ticker = 'DNO.L'

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

# Data for matplotlib finance plot
sec_id_ochl = np.array(pd.DataFrame({'0':date2num(sec_id.index),
                                  '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'] = pd.rolling_mean(sec_id.Close, SMA_FAST)
analysis['sma_s'] = pd.rolling_mean(sec_id.Close, SMA_SLOW)
analysis['rsi'] = ta.RSI(sec_id.Close.as_matrix(), RSI_PERIOD)
analysis['sma_r'] = pd.rolling_mean(analysis.rsi, RSI_AVG_PERIOD) # 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)

#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()

Answer 1

我复制了您的代码并遇到了与您相同的错误。我修复了它，但它需要几个步骤。我已经在此处复制了固定代码，以及我为使代码无误运行而执行的其他步骤。

1. 修复 pandas_datareader 由于 Yahoo API 发生变化而导致的问题。我从 another StackOverflow post 得到了这个解决方案.

   git clone https://github.com/pydata/pandas-datareader
   cd pandas-datareader/
   git remote add rgkimball http://github.com/rgkimball/pandas-datareader
   git fetch rgkimball fix-yahoo
   git checkout fix-yahoo
   pip2 uninstall pandas_datareader
   python setup.py install
   

2. 我还使用@ndrw 上面提交的答案修复了代码中的第 18 行。

3. 我做了一些其他更改，我已将其包含在此 Github repo 中.为了您的方便，我复制了下面的代码。希望对您有所帮助!

   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
   import datetime
   
   ticker = 'OPK'
   
   # Download sample data
   sec_id = data.get_data_google(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'] = pd.rolling_mean(sec_id.Close, SMA_FAST)
   analysis['sma_s'] = pd.rolling_mean(sec_id.Close, SMA_SLOW)
   analysis['rsi'] = ta.RSI(sec_id.Close.as_matrix(), RSI_PERIOD)
   analysis['sma_r'] = pd.rolling_mean(analysis.rsi, RSI_AVG_PERIOD) # 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)
   
   #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()
   

这是我得到的输出: