On 9/26/12 12:31 PM, Benjamin Root wrote:
On Wed, Sep 26, 2012 at 12:10 PM, Paul Tremblay
mailto:paulhtremb...@gmail.com>> wrote:
Thanks. I know when doing 8/9 in python 2.x you get 0. With python
3 you get a decimal (Hooray, Python 3!).
I ran the script I submitted with python
On Wed, Sep 26, 2012 at 12:10 PM, Paul Tremblay wrote:
> Thanks. I know when doing 8/9 in python 2.x you get 0. With python 3 you
> get a decimal (Hooray, Python 3!).
>
> I ran the script I submitted with python 3. Do I need to change the
> defects and totals from integers to floats to make my cha
Thanks. I know when doing 8/9 in python 2.x you get 0. With python 3 you
get a decimal (Hooray, Python 3!).
I ran the script I submitted with python 3. Do I need to change the defects
and totals from integers to floats to make my chart work universally?
P.
On Wed, Sep 26, 2012 at 4:31 AM, Pierre
Le 26/09/2012 15:25, Benjamin Root a écrit :
>
> Actually, if you are using the latest numpy (the 1.7 beta), that will
> also not work unless you are using py3k or did "from __future__ import
> division". Well, actually, using np.divide will always result in
> integer division (this may or may not
On Wed, Sep 26, 2012 at 4:31 AM, Pierre Haessig wrote:
> Hi,
>
> Just a detail :
>
> Le 26/09/2012 04:29, Paul Tremblay a écrit :
>
> percent = (np.divide(the_cumsum, the_sum)) * 100
>
> This lines doesn't work on my computer (numpy 1.6.2)
>
> Indeed, there is a casting issue :
> In [2]: percent
Hi,
Just a detail :
Le 26/09/2012 04:29, Paul Tremblay a écrit :
> percent = (np.divide(the_cumsum, the_sum)) * 100
This lines doesn't work on my computer (numpy 1.6.2)
Indeed, there is a casting issue :
In [2]: percent
Out[2]: array([ 0, 0, 0, 0, 100])
However, using the regular "/" ope
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) #
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 middl
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",
> On Mon, Sep 24, 2012 at 12:21 AM, Paul Tremblay
> 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 9/24/1
By the way, I had done the chart differently to begin with. But this code
requires more lines, more imports, and is more complex. (Without
plt.gca().yaxis or the formatter, the graph will not come out.)
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FuncFormatter
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.
On 9/24/12 4:40 PM, Benjamin Root wrote:
On Mon, Sep 24, 2012 at 12:21 AM, Paul Tremblay
mailto:paulhtremb...@gmail.com>> wrote
On Mon, Sep 24, 2012 at 12:21 AM, Paul Tremblay 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
>
>
Your code looks overly complic
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
import matplotlib.pyplot as plt
import numpy as np
def update_ax2(axx):
ax2.set_ylim(0, 100)
ax2.f
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