matplotlib: Creating two (stacked) subplots with SHARED X axis but SEPARATE Y axis values

Question

I am using matplotlib 1.2.x and Python 2.6.5 on Ubuntu 10.0.4. I am trying to create a SINGLE plot that consists of a top plot and a bottom plot.

The X axis is the date of the time series. The top plot contains a candlestick plot of the data, and the bottom plot should consist of a bar type plot - with its own Y axis (also on the left - same as the top plot). These two plots should NOT OVERLAP.

Here is a snippet of what I have done so far.

datafile = r'/var/tmp/trz12.csv'
r = mlab.csv2rec(datafile, delimiter=',', names=('dt', 'op', 'hi', 'lo', 'cl', 'vol', 'oi'))

mask = (r["dt"] >= datetime.date(startdate)) & (r["dt"] <= datetime.date(enddate))
selected = r[mask]
plotdata = zip(date2num(selected['dt']), selected['op'], selected['cl'], selected['hi'], selected['lo'], selected['vol'], selected['oi'])

# Setup charting 
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
monthFormatter = DateFormatter('%b %y')

# every Nth month
months = MonthLocator(range(1,13), bymonthday=1, interval=1)

fig = pylab.figure()
fig.subplots_adjust(bottom=0.1)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(months)#mondays
ax.xaxis.set_major_formatter(monthFormatter) #weekFormatter
ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
ax.format_ydata = price
ax.grid(True)

candlestick(ax, plotdata, width=0.5, colorup='g', colordown='r', alpha=0.85)

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

# Add volume data 
# Note: the code below OVERWRITES the bottom part of the first plot
# it should be plotted UNDERNEATH the first plot - but somehow, that's not happening
fig.subplots_adjust(hspace=0.15)
ay = fig.add_subplot(212)
volumes = [ x[-2] for x in plotdata]
ay.bar(range(len(plotdata)), volumes, 0.05)

pylab.show()

I have managed to display the two plots using the code above, however, there are two problems with the bottom plot:

It COMPLETELY OVERWRITES the bottom part of the first (top) plot - almost as though the second plot was drawing on the same 'canvas' as the first plot - I can't see where/why that is happening.
It OVERWRITES the existing X axis with its own indice, the X axis values (dates) should be SHARED between the two plots.

What am I doing wrong in my code?. Can someone spot what is causing the 2nd (bottom) plot to overwrite the first (top) plot - and how can I fix this?

Here is a screenshot of the plot created by the code above:

faulty plot

[[Edit]]

After modifying the code as suggested by hwlau, this is the new plot. It is better than the first in that the two plots are separate, however the following issues remain:

The X axis should be SHARED by the two plots (i.e. the X axis should be shown only for the 2nd [bottom] plot)
The Y values for the 2nd plot seem to be formmated incorrectly

partly correct plot

I think these issues should be quite easy to resolve however, my matplotlib fu is not great at the moment, as I have only recently started programming with matplotlib. any help will be much appreciated.

pelson · Accepted Answer · 2012-04-04 12:27:12Z

12

There seem to be a couple of problems with your code:

If you were using figure.add_subplots with the full signature of subplot(nrows, ncols, plotNum) it may have been more apparent that your first plot asking for 1 row and 1 column and the second plot was asking for 2 rows and 1 column. Hence your first plot is filling the whole figure. Rather than fig.add_subplot(111) followed by fig.add_subplot(212) use fig.add_subplot(211) followed by fig.add_subplot(212).
Sharing an axis should be done in the add_subplot command using sharex=first_axis_instance

I have put together an example which you should be able to run:

import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import matplotlib.dates as mdates


import datetime as dt


n_pts = 10
dates = [dt.datetime.now() + dt.timedelta(days=i) for i in range(n_pts)]

ax1 = plt.subplot(2, 1, 1)
ax1.plot(dates, range(10))

ax2 = plt.subplot(2, 1, 2, sharex=ax1)
ax2.bar(dates, range(10, 20))

# Now format the x axis. This *MUST* be done after all sharex commands are run.

# put no more than 10 ticks on the date axis.  
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
# format the date in our own way.
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

# rotate the labels on both date axes
for label in ax1.xaxis.get_ticklabels():
    label.set_rotation(30)
for label in ax2.xaxis.get_ticklabels():
    label.set_rotation(30)

# tweak the subplot spacing to fit the rotated labels correctly
plt.subplots_adjust(hspace=0.35, bottom=0.125)

plt.show()

Hope that helps.

answered Apr 4, 2012 at 12:27

pelson

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2 Comments

Bonlenfum Over a year ago

The sharex and sharey properties in subplots are really handy, thanks for posting. (It can be much better than setting common limits by reading from one and setting in the other: when inspecting results by interactively zooming in, both / all subplots will zoom together if shared.)

Adam Wheeler Over a year ago

sharex=first_axis_instance this is an axes instance, correct?

unsym · Accepted Answer · 2012-04-04 10:18:56Z

6

You should change this line:

ax = fig.add_subplot(111)

to

ax = fig.add_subplot(211)

The original command means that there is one row and one column so it occupies the whole graph. So your second graph fig.add_subplot(212) cover the lower part of the first graph.

Edit

If you dont want the gap between two plots, use subplots_adjust() to change the size of the subplots margin.

answered Apr 4, 2012 at 10:18

unsym

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1 Comment

Homunculus Reticulli Over a year ago

Thanks for spotting that. I am almost embarrased to have missed something that obvious. Perhaps I have been staring at the code for too long ;). The plot is now much closer to what I want. However, there are a couple of outstanding issues. Please take a look at my edited question when you have a chance.

Mel · Accepted Answer · 2017-08-05 10:35:52Z

2

The example from @Pelson, simplified.

import matplotlib.pyplot as plt
import datetime as dt

#Two subplots that share one x axis
fig,ax=plt.subplots(2,sharex=True)

#plot data
n_pts = 10
dates = [dt.datetime.now() + dt.timedelta(days=i) for i in range(n_pts)]
ax[0].bar(dates, range(10, 20))
ax[1].plot(dates, range(10))

#rotate and format the dates on the x axis
fig.autofmt_xdate()

The subplots sharing an x-axis are created in one line, which is convenient when you want more than two subplots:

fig, ax = plt.subplots(number_of_subplots, sharex=True)

To format the date correctly on the x axis, we can simply use fig.autofmt_xdate()

For additional informations, see shared axis demo and date demo from the pylab examples. This example ran on Python3, matplotlib 1.5.1

edited Aug 5, 2017 at 10:35

answered Jan 28, 2016 at 12:59

Mel

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