股市数据获取
import tushare as ts
ts.get_hist_data('600848')#一次性获取全部日k线数据结果显示：
open high close low volume p_change ma5 \date2012-01-11 6.880 7.380 7.060 6.880 14129.96 2.62 7.0602012-01-12 7.050 7.100 6.980 6.900 7895.19 -1.13 7.0202012-01-13 6.950 7.000 6.700 6.690 6611.87 -4.01 6.9132012-01-16 6.680 6.750 6.510 6.480 2941.63 -2.84 6.8132012-01-17 6.660 6.880 6.860 6.460 8642.57 5.38 6.8222012-01-18 7.000 7.300 6.890 6.880 13075.40 0.44 6.7882012-01-19 6.690 6.950 6.890 6.680 6117.32 0.00 6.7702012-01-20 6.870 7.080 7.010 6.870 6813.09 1.74 6.832 ma10 ma20 v_ma5 v_ma10 v_ma20 turnoverdate2012-01-11 7.060 7.060 14129.96 14129.96 14129.96 0.482012-01-12 7.020 7.020 11012.58 11012.58 11012.58 0.272012-01-13 6.913 6.913 9545.67 9545.67 9545.67 0.232012-01-16 6.813 6.813 7894.66 7894.66 7894.66 0.102012-01-17 6.822 6.822 8044.24 8044.24 8044.24 0.302012-01-18 6.833 6.833 7833.33 8882.77 8882.77 0.452012-01-19 6.841 6.841 7477.76 8487.71 8487.71 0.212012-01-20 6.863 6.863 7518.00 8278.38 8278.38 0.23
绘制K线图
matplotlib.finance 工具包的绘制K线图
def _candlestick(ax, quotes, width=0.2, colorup='k', colordown='r', alpha=1.0, ochl=True): """ Plot the time, open, high, low, close as a vertical line ranging from low to high. Use a rectangular bar to represent the open-close span. If close >= open, use colorup to color the bar, otherwise use colordown Parameters ---------- ax : `Axes` an Axes instance to plot to quotes : sequence of quote sequences data to plot. time must be in float date format - see date2num (time, open, high, low, close, ...) vs (time, open, close, high, low, ...) set by `ochl` width : float fraction of a day for the rectangle width colorup : color the color of the rectangle where close >= open colordown : color the color of the rectangle where close < open alpha : float the rectangle alpha level ochl: bool argument to select between ochl and ohlc ordering of quotes Returns ------- ret : tuple returns (lines, patches) where lines is a list of lines added and patches is a list of the rectangle patches added """ OFFSET = width / 2.0 lines = [] patches = [] for q in quotes: if ochl: t, open, close, high, low = q[:5] else: t, open, high, low, close = q[:5] if close >= open: color = colorup lower = open height = close - open else: color = colordown lower = close height = open - close vline = Line2D( xdata=(t, t), ydata=(low, high), color=color, linewidth=0.5, antialiased=True, ) rect = Rectangle( xy=(t - OFFSET, lower), width=width, height=height, facecolor=color, edgecolor=color, ) rect.set_alpha(alpha) lines.append(vline) patches.append(rect) ax.add_line(vline) ax.add_patch(rect) ax.autoscale_view() return lines, patches
tushare 的 pandas dataframe 生成K线图
def _candlestick(ax, df, width=0.2, colorup='k', colordown='r', alpha=1.0): """ Plot the time, open, high, low, close as a vertical line ranging from low to high. Use a rectangular bar to represent the open-close span. If close >= open, use colorup to color the bar, otherwise use colordown Parameters ---------- ax : `Axes` an Axes instance to plot to df : pandas data from tushare width : float fraction of a day for the rectangle width colorup : color the color of the rectangle where close >= open colordown : color the color of the rectangle where close < open alpha : float the rectangle alpha level ochl: bool argument to select between ochl and ohlc ordering of quotes Returns ------- ret : tuple returns (lines, patches) where lines is a list of lines added and patches is a list of the rectangle patches added """ OFFSET = width / 2.0 lines = [] patches = [] for date_string,row in df.iterrows(): date_time = datetime.datetime.strptime(date_string,'%Y-%m-%d') t = date2num(date_time) open, high, close, low = row[:4] if close >= open: color = colorup lower = open height = close - open else: color = colordown lower = close height = open - close vline = Line2D( xdata=(t, t), ydata=(low, high), color=color, linewidth=0.5, antialiased=True, ) rect = Rectangle( xy=(t - OFFSET, lower), width=width, height=height, facecolor=color, edgecolor=color, ) rect.set_alpha(alpha) lines.append(vline) patches.append(rect) ax.add_line(vline) ax.add_patch(rect) ax.autoscale_view() return lines, patchesdef drawPic(df, code, name): mondays = WeekdayLocator(MONDAY) # 主要刻度 alldays = DayLocator() # 次要刻度 #weekFormatter = DateFormatter('%b %d') # 如：Jan 12 mondayFormatter = DateFormatter('%m-%d-%Y') # 如：2-29-2015 dayFormatter = DateFormatter('%d') # 如：12 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) _candlestick(ax, df, 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(name + ' ' + code, fontproperties=zhfont) plt.show()def makePicture(code, name): df = ts.get_hist_data(code, start=begin_time, end=end_time) df = df.sort_index(0)# df.plot() drawPic(df, code, name)