Hi there,
I’m having trouble understanding what it is you exactly want.
You said you want to indicate that 'the monthly usage between September 1st and January 1st
was, on average, the same as that between January 1st and February 1st.’
So looking at the data you provided I’ll assume the following:
The measurement your taking is not in fact the utility usage for one month, but rather the sum of all usage over all prior months. And unfortunately it seems measurements aren’t very regular (you working for the gov?). 
no problem.
Seeing that we’re missing some data for the months in between measurements we’ll have to interpolate.
The simplest will be linear line segments between the known data points. (There are also some nice interpolation modules in scipy if you’re looking for something “smoother”, ie. polynomials or cubic splines or something)
Linear interpolation should look something like this.
2007/09/01 - 5000
2007/10/01 - 5750
2007/11/01 - 6500
2007/12/01 - 7250
2008/01/01 - 8000
2008/02/01 - 9000
Of course we’re looking for the usage per month so we’ll just calculate the difference in the aggregates.
2007/09/01 - 0
2007/10/01 - 750
2007/11/01 - 750
2007/12/01 - 750
2008/01/01 - 750
2008/02/01 - 1000
Obviously we don’t have data prior to October so Augusts’ usage ends up as zero. Now you can simply through that at matplotlib’s plot() command and Bob’s you’re uncle. Using bar graphs for the usage per month is recommended, seeing that the measurements are so inconsistent to begin with plotting with continuous lines will only add to a false sense of accuracy.
I’ll recommend not using linear interpolation on this because the data will clearly be skewed. In our case there would have been a gradual increase in usage from September to January, and not the constant usage that linear interpolation gave us.
Hope this helps. With matplotlib and scipy you’re basically covered for all your scientific plotting needs.
Have a nice day now.
cputter
···
---------- Forwarded message ----------
From: Christiaan Putter <ceputter@…982…>
Date: 14 Mar 2008 03:22
Subject: Re: [Matplotlib-users] visualisation for utility usage sought
To: Chris Withers <chris@…1920…>
On 12/03/2008, Chris Withers <chris@…1920…> wrote:
Hi All,
I hope this isn’t considered off topic here, but this has been bugging
me for a while and I reckon you guys may be able to help. To boot, I’d
like to use matplotlib to make it happen, so I figure this list is fairgame
So, I have a series of measurements at points in time, eg:
2007/09/01 - 5000
2008/01/01 - 8000
2008/02/01 - 9000…and I’m looking to create some type of visualisation that indicates
usage over time.
The import point is that the gaps between point measurements are not
constant, so a straight bar chart won’t be right.The points also won’t necessarilly be as convenient as those above, but
hopefully they’ll work as an example: What I’d expect to see would
indicate that the monthly usage between September 1st and January 1st
was, on average, the same as that between January 1st and February 1st.I’m having trouble expressing myself clearly, but hopefully I’m making
some kind of sense.Any ideas very greatfully recieved!
cheers,
Chris
–
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