对于以下格式数据，我应该如何绘制matplotlib.finance的“K”图？

Question

我是matplotlib的新手，现在我很困惑。 的代码如下：

import matplotlib.finance as mpf 
import matplotlib.pyplot as plt 
import tushare as ts 
start = '2016-09-01' 
end = '2016-09-30' 
quotes = ts.get_hist_data('sh', start=start, end=end) 
quote = quotes[['open', 'close', 'high', 'low']] 
fig, ax = plt.subplots(figsize=(8, 5)) 
fig.subplots_adjust(bottom=0.2) 
mpf.candlestick2_ochl(ax, opens, closes, highs, lows, width=0.6, colorup='k', colordown='r', alpha=0.75) 
plt.grid(True) 
ax.xaxis_date() 
ax.autoscale_view() 
plt.setp(plt.gca().get_xticklabels(), rotation=30) 
plt.show() 

的 “引用” 的的数据都是：

   open close  high  low 
date           
2016-09-30 2994.25 3004.70 3009.20 2993.06 
2016-09-29 2992.17 2998.48 3009.20 2991.91 
2016-09-28 3000.70 2987.86 3000.70 2984.32 
2016-09-27 2974.59 2998.17 2998.23 2969.13 
2016-09-26 3028.24 2980.43 3028.24 2980.12 
2016-09-23 3044.79 3033.90 3046.80 3032.80 
2016-09-22 3038.42 3042.31 3054.44 3035.07 
2016-09-21 3021.58 3025.87 3032.45 3017.54 
2016-09-20 3027.17 3023.00 3027.82 3015.88 
2016-09-19 3005.32 3026.05 3026.65 3005.32 
2016-09-14 3008.90 3002.85 3017.94 2995.42 
2016-09-13 3025.03 3023.51 3029.72 3008.74 
2016-09-12 3037.51 3021.98 3040.95 2999.93 
2016-09-09 3095.43 3078.85 3101.79 3078.22 
2016-09-08 3089.95 3095.95 3096.78 3083.90 
2016-09-07 3091.33 3091.93 3105.68 3087.88 
2016-09-06 3071.06 3090.71 3095.51 3053.19 
2016-09-05 3070.71 3072.10 3085.49 3065.33 
2016-09-02 3057.49 3067.35 3072.53 3050.49 
2016-09-01 3083.96 3063.31 3088.70 3062.88 

而且我得到这个错误：

ValueError: ordinal must be >= 1 

如何将我解决呢？

Answer 1

请参阅使用Python3.5的工作代码：

import matplotlib.pyplot as plt 
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY,YEARLY 
import matplotlib.finance as mpf 

def main(): 
    # plt.rcParams['font.sans-serif'] = ['SimHei'] 
    plt.rcParams['axes.unicode_minus'] = False 

    ticker = '600028' 
    ticker += '.ss'  

    date1 = (2015, 8, 1) 
    date2 = (2016, 1, 1) 


    mondays = WeekdayLocator(MONDAY)   
    alldays = DayLocator()      
    #weekFormatter = DateFormatter('%b %d')  
    mondayFormatter = DateFormatter('%Y-%m-%d') 
    dayFormatter = DateFormatter('%d')   

    quotes = mpf.quotes_historical_yahoo_ochl('^GDAXI', date1, date2) 

    if len(quotes) == 0: 
     raise SystemExit 

    fig, ax = plt.subplots() 
    fig.subplots_adjust(bottom=0.2) 

    ax.xaxis.set_major_locator(mondays) 
    ax.xaxis.set_minor_locator(alldays) 
    ax.xaxis.set_major_formatter(mondayFormatter) 

    mpf.candlestick_ohlc(ax, quotes, width=0.6, colorup='r', colordown='g') 

    ax.xaxis_date() 
    ax.autoscale_view() 
    plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right') 

    ax.grid(True) 
    plt.title('600028') 
    plt.show() 
    return 

if __name__ == '__main__': 
    main() 

#Slight modified base on http://blog.csdn.net/matrix_laboratory/article/details/50688275 

或者这方面的工作代码Python3.5：

import matplotlib.pyplot as plt 
import matplotlib.finance as mpf 
from dateutil import parser 
import matplotlib.dates as mpl_dt 
import tushare as ts 

start = '2016-09-01' 
end = '2016-09-30' 
df = ts.get_hist_data('sh', start=start, end=end) 
DATA = df[['open', 'high', 'close', 'low', 'volume']] 
DATA = DATA.reset_index() 
DATA["date"] = DATA["date"].apply(lambda x : mpl_dt.date2num(parser.parse(x))) 
fig, ax = plt.subplots() 
mpf.candlestick_ohlc(ax, DATA.values, width=0.6, colorup='r', colordown='g') 
plt.grid(True) 
ax.xaxis_date() 
ax.autoscale_view() 
plt.setp(plt.gca().get_xticklabels(), rotation=30) 
plt.show() 


#cf: http://stackoverflow.com/questions/35677173/charting-with-candlestick-ohlc