I did it once and posted it to the list but never found the time to add it to the official gallery (my bad):
http://www.loria.fr/~rougier/coding/gallery/showcase/showcase-3-large.png http://www.loria.fr/~rougier/coding/gallery/ Nicolas On Jun 23, 2012, at 5:36 , Benjamin Root wrote: > > > On Friday, June 22, 2012, John Hunter wrote: > On Fri, Jun 22, 2012 at 2:48 PM, Alan G Isaac <alan.is...@gmail.com> wrote: > > On 6/21/2012 10:24 PM, Tony Yu wrote: > >> Here's an example based off the horizontal bar charts in the gallery. > > > > Pretty good, really! > > More than just a starting point. > > And here is a modified example a little closer visually > > > # tornado chart example; inspired by > # http://www.nytimes.com/imagepages/2007/07/29/health/29cancer.graph.web.html > # and sample code from Tony Yu > import numpy as np > import matplotlib.pyplot as plt > > cancers = [ > 'Kidney cancer', > 'Bladder cancer', > 'Esophageal cancer', > 'Ovarian cancer', > 'Liver cancer', > "Non-Hodgkin's\nlymphoma", > 'Leukemia', > 'Prostate cancer', > 'Pancreatic cancer', > 'Breast cancer', > 'Colorectal cancer', > 'Lung cancer', > ] > > num_cancers = len(cancers) > > # generate some random data for the graphs (TODO; put real data here) > new_cases_men = np.random.uniform(low=20e3, high=200e3, size=num_cancers) > new_cases_women = np.random.uniform(low=20e3, high=200e3, size=num_cancers) > deaths_women = np.random.rand(num_cancers)*new_cases_women > deaths_men = np.random.rand(num_cancers)*new_cases_men > > # force these values where the labels happen to make sure they are > # positioned nicely > new_cases_men[-1] = 120e3 > new_cases_men[-2] = 55e3 > deaths_men[-1] = 80e3 > > # bars centered on the y axis > pos = np.arange(num_cancers) + .5 > > # make the left and right axes for women and men > fig = plt.figure(facecolor='white', edgecolor='none') > ax_women = fig.add_axes([0.05, 0.1, 0.35, 0.8]) > ax_men = fig.add_axes([0.6, 0.1, 0.35, 0.8]) > > ax_men.set_xticks(np.arange(50e3, 201e3, 50e3)) > ax_women.set_xticks(np.arange(50e3, 201e3, 50e3)) > > # turn off the axes spines except on the inside y-axis > for loc, spine in ax_women.spines.iteritems(): > if loc!='right': > spine.set_color('none') # don't draw spine > > for loc, spine in ax_men.spines.iteritems(): > if loc!='left': > spine.set_color('none') # don't draw spine > > # just tick on the top > ax_women.xaxis.set_ticks_position('top') > ax_men.xaxis.set_ticks_position('top') > > # make the women's graphs > ax_women.barh(pos, new_cases_women, align='center', > facecolor='#DBE3C2', edgecolor='None') > ax_women.barh(pos, deaths_women, align='center', facecolor='#7E895F', > height=0.5, edgecolor='None') > ax_women.set_yticks([]) > ax_women.invert_xaxis() > > # make the men's graphs > ax_men.barh(pos, new_cases_men, align='center', facecolor='#D8E2E1', > edgecolor='None') > ax_men.barh(pos, deaths_men, align='center', facecolor='#6D7D72', > height=0.5, edgecolor='None') > ax_men.set_yticks([]) > > # we want the cancer labels to be centered in the fig coord system and > # centered w/ respect to the bars so we use a custom transform > import matplotlib.transforms as transforms > transform = transforms.blended_transform_factory( > fig.transFigure, ax_men.transData) > for i, label in enumerate(cancers): > ax_men.text(0.5, i+0.5, label, ha='center', va='center', > transform=transform) > > # the axes titles are in axes coords, so x=0, y=1.025 is on the left > # side of the axes, just above, x=1.0, y=1.025 is the right side of the > # axes, just above > ax_men.set_title('MEN', x=0.0, y=1.025, fontsize=12) > ax_women.set_title('WOMEN', x=1.0, y=1.025, fontsize=12) > > # the fig suptile is in fig coords, so 0.98 is the far right; we right > align the text > fig.suptitle('July 29, 2007', x=0.98, ha='right') > > # now add the annotations > ax_men.annotate('New Cases', xy=(0.95*new_cases_men[-1], num_cancers-0.5), > xycoords='data', > xytext=(20, 0), textcoords='offset points', > size=12, > va='center', > arrowprops=dict(arrowstyle="->"), > ) > > # a curved arrow for the deaths annotation > ax_men.annotate('Deaths', xy=(0.95*deaths_men[-1], num_cancers-0.5), > xycoords='data', > xytext=(40, -20), textcoords='offset points', > size=12, > va='center', > arrowprops=dict(arrowstyle="->", > > connectionstyle="angle,angleA=0,angleB=90,rad=3"), > > ) > > plt.show() > > > With some real data and a bit of polish to the source, I would love to add > this to the gallery. Real data is a must, of course-- men with ovarian > cancer just look silly. > > Ben Root > ------------------------------------------------------------------------------ > Live Security Virtual Conference > Exclusive live event will cover all the ways today's security and > threat landscape has changed and how IT managers can respond. Discussions > will include endpoint security, mobile security and the latest in malware > threats. > http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/_______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
