3

iPython 2.3.1, OS-X Yosemite 10.10.2
Python print (sys.version):
2.7.6 (default, Sep 9 2014, 15:04:36)
[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.39)]

The following code works for data pulled for US stock data e.g. make the security id "INTC" for Intel. However when I access data for European stocks, the candlestick function fails even though all the OHLC data is there in the dataframe. Have put the full code in here to show that the other tech analysis charts plot just fine for the European stock data.

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()

plot

4

2 回答 2

2

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。我在这里复制了固定代码，以及我为使代码无错误运行所做的其他步骤。

  1. pandas_datareader由于 Yahoo API 的更改，修复了 的问题。我从另一个 StackOverflow 帖子中得到了一些解决方案。

    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. 我进行了一些其他更改，这些更改已包含在此Github 存储库中。为了您的方便，我复制了下面的代码。我希望它有帮助！

    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：在此处输入图像描述

于 2017-06-08T02:36:33.613 回答
1

pandas data.index 需要转换 datetype。

import matplotlib.dates as mdates

...

在您的代码中，在 sec_id_ochl 之前：

# Data for matplotlib finance plot
sec_id.index  = mdates.date2num(sec_id.index.to_pydatetime())
于 2016-10-17T01:03:15.657 回答