How to draw a classic stock chart with matplotlib?

Question

The classic stock price chart consists of a vertical line connecting the highest and lowest prices for each time period with a mark to the left of the opening price (first) and a checkmark to the right of the closing price (last).

Matplotlib can draw the Japanese version, which is called a candle, but I could not find a solution for the western version, which is simply called a "histogram". Can Matplotlib draw such a chart?

Answer 1

Adaptation of the candlestick function from matplotlib financing package ( documentation , code ):

def westerncandlestick(ax, quotes, width=0.2, colorup='k', colordown='r', ochl=True, linewidth=0.5): """ 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 open and close lines colorup : color the color of the lines close >= open colordown : color the color of the lines where close < open ochl: bool argument to select between ochl and ohlc ordering of quotes linewidth: float linewidth of lines Returns ------- ret : tuple returns (lines, openlines, closelines) where lines is a list of lines added """ OFFSET = width / 2.0 lines = [] openlines = [] closelines = [] 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 else: color = colordown vline = Line2D( xdata=(t, t), ydata=(low, high), color=color, linewidth=linewidth, antialiased=True) lines.append(vline) openline = Line2D(xdata=(t - OFFSET, t), ydata=(open,open), color=color, linewidth=linewidth, antialiased=True) openlines.append(openline) closeline = Line2D(xdata=(t , t+OFFSET), ydata=(close,close), color=color, linewidth=linewidth, antialiased=True) closelines.append(closeline) ax.add_line(vline) ax.add_line(openline) ax.add_line(closeline) ax.autoscale_view() return lines, openlines, closelines 

call him, for example. eg:

 westerncandlestick(ax, quotes, width=0.6, linewidth=1.44, ochl=False) 

Of course, you can adapt colors with the colorup and colordown .

Full code to reproduce the above graph:

 import matplotlib.pyplot as plt from matplotlib.finance import quotes_historical_yahoo_ohlc from matplotlib.lines import Line2D def westerncandlestick(ax, quotes, width=0.2, colorup='k', colordown='r', ochl=True, linewidth=0.5): """ 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 open and close lines colorup : color the color of the lines close >= open colordown : color the color of the lines where close < open ochl: bool argument to select between ochl and ohlc ordering of quotes linewidth: float linewidth of lines Returns ------- ret : tuple returns (lines, openlines, closelines) where lines is a list of lines added """ OFFSET = width / 2.0 lines = [] openlines = [] closelines = [] 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 else: color = colordown vline = Line2D( xdata=(t, t), ydata=(low, high), color=color, linewidth=linewidth, antialiased=True) lines.append(vline) openline = Line2D(xdata=(t - OFFSET, t), ydata=(open,open), color=color, linewidth=linewidth, antialiased=True) openlines.append(openline) closeline = Line2D(xdata=(t , t+OFFSET), ydata=(close,close), color=color, linewidth=linewidth, antialiased=True) closelines.append(closeline) ax.add_line(vline) ax.add_line(openline) ax.add_line(closeline) ax.autoscale_view() return lines, openlines, closelines from matplotlib.dates import DateFormatter, WeekdayLocator,\ DayLocator, MONDAY # (Year, month, day) tuples suffice as args for quotes_historical_yahoo date1 = (2004, 2, 1) date2 = (2004, 4, 12) mondays = WeekdayLocator(MONDAY) # major ticks on the mondays alldays = DayLocator() # minor ticks on the days weekFormatter = DateFormatter('%b %d') # eg, Jan 12 dayFormatter = DateFormatter('%d') # eg, 12 quotes = quotes_historical_yahoo_ohlc('INTC', 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(weekFormatter) westerncandlestick(ax, quotes, width=0.6, linewidth=1.44, ochl=False) ax.xaxis_date() ax.autoscale_view() plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right') plt.show() 

Answer 2

In the western canonical bars, closing relationships were colored; black for higher closures, red for lower ones. I changed the @ImportanceOfBeingErnes code to allow the selection of Japanese or Western color schemes.

 import matplotlib.pyplot as plt from matplotlib.finance import quotes_historical_yahoo_ohlc from matplotlib.lines import Line2D def westerncandlestick(ax, quotes, width=0.2, colorup='k', colordown='r', ochl=True, linewidth=0.5, westerncolor=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 open and close lines colorup : color the color of the lines close >= open colordown : color the color of the lines where close < open ochl: bool argument to select between ochl and ohlc ordering of quotes linewidth: float linewidth of lines westerncolor: bool use western cannon colors? Returns ------- ret : tuple returns (lines, openlines, closelines) where lines is a list of lines added """ OFFSET = width / 2.0 lines = [] openlines = [] closelines = [] for q in quotes: if ochl: t, open, close, high, low = q[:5] else: t, open, high, low, close = q[:5] if westerncolor: try: close_ except NameError: close_ = close if close >= close_: color = colorup else: color = colordown close_ = close else: if close >= open: color = colorup else: color = colordown vline = Line2D( xdata=(t, t), ydata=(low, high), color=color, linewidth=linewidth, antialiased=True) lines.append(vline) openline = Line2D(xdata=(t - OFFSET, t), ydata=(open,open), color=color, linewidth=linewidth, antialiased=True) openlines.append(openline) closeline = Line2D(xdata=(t , t+OFFSET), ydata=(close,close), color=color, linewidth=linewidth, antialiased=True) closelines.append(closeline) ax.add_line(vline) ax.add_line(openline) ax.add_line(closeline) ax.autoscale_view() return lines, openlines, closelines from matplotlib.dates import DateFormatter, WeekdayLocator,\ DayLocator, MONDAY # (Year, month, day) tuples suffice as args for quotes_historical_yahoo date1 = (2004, 2, 1) date2 = (2004, 4, 12) mondays = WeekdayLocator(MONDAY) # major ticks on the mondays alldays = DayLocator() # minor ticks on the days weekFormatter = DateFormatter('%b %d') # eg, Jan 12 dayFormatter = DateFormatter('%d') # eg, 12 quotes = quotes_historical_yahoo_ohlc('INTC', 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(weekFormatter) westerncandlestick(ax, quotes, width=0.6, linewidth=1.44, ochl=False, westerncolor=True) ax.xaxis_date() ax.autoscale_view() plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right') plt.show()