Financial Charts / Graphs in Ruby or Python

Question

What are my best options for creating a financial open-high-low-close (OHLC) chart in a high level language like Ruby or Python? While there seem to be a lot of options for graphing, I haven't seen any gems or eggs with this kind of chart.

http://en.wikipedia.org/wiki/Open-high-low-close_chart (but I don't need the moving average or Bollinger bands)

JFreeChart can do this in Java, but I'd like to make my codebase as small and simple as possible.

Thanks!

Answer 1

Some examples about financial plots (OHLC) using matplotlib can be found here:

• finance demo

  #!/usr/bin/env python
  from pylab import *
  from matplotlib.dates import  DateFormatter, WeekdayLocator, HourLocator, \
       DayLocator, MONDAY
  from matplotlib.finance import quotes_historical_yahoo, candlestick,\
       plot_day_summary, candlestick2
  
  # (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('INTC', date1, date2)
  if len(quotes) == 0:
      raise SystemExit
  
  fig = figure()
  fig.subplots_adjust(bottom=0.2)
  ax = fig.add_subplot(111)
  ax.xaxis.set_major_locator(mondays)
  ax.xaxis.set_minor_locator(alldays)
  ax.xaxis.set_major_formatter(weekFormatter)
  #ax.xaxis.set_minor_formatter(dayFormatter)
  
  #plot_day_summary(ax, quotes, ticksize=3)
  candlestick(ax, quotes, width=0.6)
  
  ax.xaxis_date()
  ax.autoscale_view()
  setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
  
  show()
  

• finance work 2

Answer 2

Are you free to use JRuby instead of Ruby? That'd let you use JFreeChart, plus your code would still be in Ruby

Answer 3

This is the stock chart I draw just days ago using Matplotlib, I've posted the source too, for your reference: StockChart_Matplotlib

Answer 4

Open Flash Chart is nice choice if you like the look of examples. I've moved to JavaScript/Canvas library like Flot for HTML embedded charts, as it is more customizable and I get desired effect without much hacking (http://itprolife.worona.eu/2009/08/scatter-chart-library-moving-to-flot.html).

Answer 5

You can use matplotlib and the the optional bottom parameter of matplotlib.pyplot.bar. You can then use line plot to indicate the opening and closing prices:

For example:

#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import lines

import random


deltas = [4, 6, 13, 18, 15, 14, 10, 13, 9, 6, 15, 9, 6, 1, 1, 2, 4, 4, 4, 4, 10, 11, 16, 17, 12, 10, 12, 15, 17, 16, 11, 10, 9, 9, 7, 10, 7, 16, 8, 12, 10, 14, 10, 15, 15, 16, 12, 8, 15, 16]
bases = [46, 49, 45, 45, 44, 49, 51, 52, 56, 58, 53, 57, 62, 63, 68, 66, 65, 66, 63, 63, 62, 61, 61, 57, 61, 64, 63, 58, 56, 56, 56, 60, 59, 54, 57, 54, 54, 50, 53, 51, 48, 43, 42, 38, 37, 39, 44, 49, 47, 43]


def rand_pt(bases, deltas):
    return [random.randint(base, base + delta) for base, delta in zip(bases, deltas)]

# randomly assign opening and closing prices 
openings = rand_pt(bases, deltas)
closings = rand_pt(bases, deltas)

# First we draw the bars which show the high and low prices
# bottom holds the low price while deltas holds the difference 
# between high and low.
width = 0
ax = plt.axes()
rects1 = ax.bar(np.arange(50), deltas, width, color='r', bottom=bases)

# Now draw the ticks indicating the opening and closing price
for opening, closing, bar in zip(openings, closings, rects1):
    x, w = bar.get_x(), 0.2

    args = {
    }

    ax.plot((x - w, x), (opening, opening), **args)
    ax.plot((x, x + w), (closing, closing), **args)


plt.show()

creates a plot like this:

Obviously, you'd want to package this up in a function that drew the plot using (open, close, min, max) tuples (and you probably wouldn't want to randomly assign your opening and closing prices).

Answer 6

You can use Pylab (matplotlib.finance) with Python. Here are some examples: http://matplotlib.sourceforge.net/examples/pylab_examples/plotfile_demo.html . There is some good material specifically on this problem in Beginning Python Visualization.

Update: I think you can use matplotlib.finance.candlestick for the Japanese candlestick effect.