Matplotlib - label each bin

Question

I'm currently using Matplotlib to create a histogram:

import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as pyplot ... fig = pyplot.figure() ax = fig.add_subplot(1,1,1,) n, bins, patches = ax.hist(measurements, bins=50, range=(graph_minimum, graph_maximum), histtype='bar')  #ax.set_xticklabels([n], rotation='vertical')  for patch in patches:     patch.set_facecolor('r')  pyplot.title('Spam and Ham') pyplot.xlabel('Time (in seconds)') pyplot.ylabel('Bits of Ham') pyplot.savefig(output_filename) 

I'd like to make the x-axis labels a bit more meaningful.

Firstly, the x-axis ticks here seem to be limited to five ticks. No matter what I do, I can't seem to change this - even if I add more xticklabels, it only uses the first five. I'm not sure how Matplotlib calculates this, but I assume it's auto-calculated from the range/data?

Is there some way I can increase the resolution of x-tick labels - even to the point of one for each bar/bin?

(Ideally, I'd also like the seconds to be reformatted in micro-seconds/milli-seconds, but that's a question for another day).

Secondly, I'd like each individual bar labeled - with the actual number in that bin, as well as the percentage of the total of all bins.

The final output might look something like this:

Is something like that possible with Matplotlib?

Cheers, Victor

Answer 1

Sure! To set the ticks, just, well... Set the ticks (see matplotlib.pyplot.xticks or ax.set_xticks). (Also, you don't need to manually set the facecolor of the patches. You can just pass in a keyword argument.)

For the rest, you'll need to do some slightly more fancy things with the labeling, but matplotlib makes it fairly easy.

As an example:

import matplotlib.pyplot as plt import numpy as np from matplotlib.ticker import FormatStrFormatter  data = np.random.randn(82) fig, ax = plt.subplots() counts, bins, patches = ax.hist(data, facecolor='yellow', edgecolor='gray')  # Set the ticks to be at the edges of the bins. ax.set_xticks(bins) # Set the xaxis's tick labels to be formatted with 1 decimal place... ax.xaxis.set_major_formatter(FormatStrFormatter('%0.1f'))  # Change the colors of bars at the edges... twentyfifth, seventyfifth = np.percentile(data, [25, 75]) for patch, rightside, leftside in zip(patches, bins[1:], bins[:-1]):     if rightside < twentyfifth:         patch.set_facecolor('green')     elif leftside > seventyfifth:         patch.set_facecolor('red')  # Label the raw counts and the percentages below the x-axis... bin_centers = 0.5 * np.diff(bins) + bins[:-1] for count, x in zip(counts, bin_centers):     # Label the raw counts     ax.annotate(str(count), xy=(x, 0), xycoords=('data', 'axes fraction'),         xytext=(0, -18), textcoords='offset points', va='top', ha='center')      # Label the percentages     percent = '%0.0f%%' % (100 * float(count) / counts.sum())     ax.annotate(percent, xy=(x, 0), xycoords=('data', 'axes fraction'),         xytext=(0, -32), textcoords='offset points', va='top', ha='center')   # Give ourselves some more room at the bottom of the plot plt.subplots_adjust(bottom=0.15) plt.show()