Yes, that works nice. So my final code, as minimalist as possible (while
still maintaining readability):
import matplotlib.pyplot as plt
import numpy as np
# the data to plot
defects = [32, 22, 15, 5, 2]
labels = ['vertical', 'horizontal', 'behind', 'left area', 'other']
the_sum = sum(defects) # ie, 32 + 22 + 15 + 5 + 2
the_cumsum = np.cumsum(defects) # 32, 32 + 22, 32 + 22 + 15, 32 + 22 + 15
+ 5, 32 + 22, + 15 + 5 + 2
percent = (np.divide(the_cumsum, the_sum)) * 100
ind = np.arange(len(defects)) # the x locations for the groups
width = .98 # with do of the bars, where a width of 1 indidcates no space
between bars
x = ind + .5 * width # find the middle of the bar
fig = plt.figure() # create a figure
ax1 = fig.add_subplot(111) # and a subplot
ax2 = ax1.twinx() # create a duplicate y axis
rects1 = ax1.bar(ind, defects, width=width) # draw the chart
line, = ax2.plot(x, percent) # draw the line
ax1.set_ylim(ymax=the_sum) # without these limits, graphs will not work
ax2.set_ylim(0, 100)
ax1.set_xticks(x) # set ticks for middle of bars
ax1.set_xticklabels(labels) # create the labels for the bars
ax1.set_ylabel('Defects') # create the left y axis label
ax2.set_ylabel('Percentage') # create the right y axis label
plt.show()
On Tue, Sep 25, 2012 at 2:31 PM, Jeffrey Melloy <jmel...@gmail.com> wrote:
> ax1.set_ylim(0, sum(data))
> ax2.set_ylim(0, 100)
> seems to solve both of these issues.
>
> On Tue, Sep 25, 2012 at 11:16 AM, Paul Tremblay <paulhtremb...@gmail.com>
> wrote:
> > There are two problems with this chart:
> >
> > 1. The scale is wrong. Imagine that you can stack all the bars on top of
> > each other. When stacked, all the bars should fill in the graph exactly.
> In
> > other words: ax1.set_ylim = sum(defects). See my original, or the wiki
> page.
> >
> > 2. The line starts in the middle of the bar. It needs to start on top, in
> > the middle.
> >
> > Maybe there is a way to correct 1 & 2 with your method, but I can't
> seem to
> > find it.
> >
> > Thanks!
> >
> > Paul
> >
> >
> > On Tue, Sep 25, 2012 at 12:58 PM, Jeffrey Melloy <jmel...@gmail.com>
> wrote:
> >>
> >> I think pareto charts are supposed to be percentages, not totals.
> >>
> >> data = [83, 38, 7, 5, 5, 4, 4, 2, 1]
> >> labels = ["Vertical", "Horizontal", "Upper", "Lower", "Left", "Right",
> >> "Behind", "Front", "Down"]
> >> colors = ["#001499", "#ff7f00", "#9440ed", "#edc240", "#238c3f",
> >> "#a60085", "#00cca3", "#464f8c", "#005947", "#00004d",
> >> "#cc0052", "#591616", "#7d8060", "#299da6", "#9c8fbf",
> >> "#4c132a", "#8c3f23", "#85cc33", "#607980", "#7c30bf", "#bf9360",
> >> "#324d13", "#13394d", "#4c1659", "#b25f00", "#99cca7",
> >> "#669ccc", "#594358"]
> >>
> >> fig, ax1 = plt.subplots()
> >> ax2 = ax1.twinx()
> >>
> >> for i, d in enumerate(data):
> >> ax1.bar(i + .25, d, .5, zorder=0, alpha=0.5, label = labels[i],
> >> color=colors[i % len(colors)])
> >>
> >> percent = [d*1.0/sum(data) * 100 for d in np.cumsum(data)]
> >> ax2.plot(np.arange(len(data)) + 0.5, percent, linestyle='-',
> >> color='k', linewidth=2, zorder=5)
> >>
> >> ax1.set_xticks(np.arange(len(data)) + 0.5)
> >> ax1.set_xticklabels(labels, rotation=30, ha='right')
> >> #ax1.legend()
> >>
> >> ax1.set_ylabel('Defects')
> >> ax2.set_ylabel('Percentage')
> >> ax2.set_ylim(0,110)
> >>
> >> plt.show()
> >>
> >>
> >> On Mon, Sep 24, 2012 at 11:43 PM, Paul Hobson <pmhob...@gmail.com>
> wrote:
> >> >> On Mon, Sep 24, 2012 at 12:21 AM, Paul Tremblay
> >> >> <paulhtremb...@gmail.com>
> >> >> wrote:
> >> >>>
> >> >>> Here is my example of a Pareto chart.
> >> >>>
> >> >>> For an explanation of a Pareto chart:
> >> >>>
> >> >>> http://en.wikipedia.org/wiki/Pareto_chart
> >> >>>
> >> >>> Could I get this chart added to the matplolib gallery?
> >> >>>
> >> >>>
> >> >>> Thanks
> >> >>>
> >> >>> Paul
> >> >>>
> >> >
> >> >> On 9/24/12 4:40 PM, Benjamin Root wrote:
> >> >> Your code looks overly complicated. You shouldn't have to be doing
> the
> >> >> connection to the ylim_changed event, I don't think. I think your
> main
> >> >> problem is that you are calling ax1.plot instead of ax2.plot.
> >> >>
> >> >> I am not against adding more examples to the gallery, but this would
> >> >> have to
> >> >> be cleaned up before it gets included.
> >> >>
> >> >> Ben Root
> >> >
> >> > On Mon, Sep 24, 2012 at 5:50 PM, Paul Tremblay <
> paulhtremb...@gmail.com>
> >> > wrote:
> >> >> I took my example from the matplotlib pages itself:
> >> >>
> >> >> http://matplotlib.org/examples/api/fahrenheit_celcius_scales.html
> >> >>
> >> >> If you know a better way, please show me.
> >> >>
> >> >> P.
> >> >
> >> > Paul,
> >> >
> >> > That example is an overly complicated template for making a pareto
> >> > chart.
> >> >
> >> > Here's how I'd do it:
> >> >
> >> > # data
> >> > defects = [0, 32, 22, 15, 5, 2]
> >> > labels = ['', 'vertical', 'horizontal', 'behind', 'left area',
> 'other']
> >> >
> >> > # axes
> >> > fig, ax1 = plt.subplots()
> >> > ax2 = ax1.twinx()
> >> >
> >> > # plotting
> >> > ax1.bar(np.arange(len(defects))-0.4, defects, zorder=0, alpha=0.5)
> >> > ax2.plot(np.cumsum(defects), linestyle='-', color='k', linewidth=2,
> >> > zorder=5)
> >> >
> >> > # formatting
> >> > ax1.set_xticks(np.arange(len(defects)))
> >> > ax1.set_xticklabels(labels)
> >> > ax1.set_ylabel('Defects')
> >> > ax2.set_ylabel('Percentage')
> >> > plt.show()
> >> >
> >> >
> >> >
> ------------------------------------------------------------------------------
> >> > 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
