# Graph Dates and Values

brianrpsgt1 brianlong at cox.net
Tue Mar 10 16:32:10 CET 2009

```On Mar 10, 7:40 am, "Gabriel Genellina" <gagsl-... at yahoo.com.ar>
wrote:
> En Tue, 10 Mar 2009 05:08:41 -0200, brianrpsgt1 <brianl... at cox.net>
> escribió:
>
> > I am trying to plot dates and values on a graph using matplotlib.
> > Below is the code.  I can run this and it works great, until I get to
> > about 2000 rows from the DB.  Things really start to slow down.  I
> > have successfully plotted up to 5000 rows from the DB, but it is very
> > slow.  I am attempting to plot values for a day, which would be equal
> > to 84600 records.  Is there a more efficient may to accomplish this?
>
> (isn't it 86400?)
>
> > for s in value_data:
> >     dates = mdates.date2num([s[0]])
> >     plt.plot([dates],[s[1]], 'bo', ms=6)
>
> Without looking at the matplotlib docs, the above [] suggests that both
> date2num and plt.plot take a list of values to act upon, and you're
> feeding one point at a time. Probably you end up creating one series per
> point (instead of a single series with many points). I guess something
> like this should work:
>
> x, y = zip(*value_data) # "transpose"
> dates = mdates.date2num(x)
> plt.plot(dates, y, 'bo', ms=6)
>
> (totally untested)
>
> --
> Gabriel Genellina

Gabriel ::

Thanks for the notes.  That is exactly what I thought the problem
was.  Here is an update.  I put a limit to 100 on the SQL Query to
test.  When I run your code, I get the data returned, however, I get
the same return equal to the limit I set.  In other words, when I run
with a limit of 100, I get the same result 100 times.  Which would
mean that when I try to run a whole day (86400 :) - it was late!), I
am getting the same result 86400 times and then it is tyring to plot
that.

Output below:

[ 733414.06489583  733414.06490741  733414.06491898  733414.06493056
733414.06494213  733414.0649537   733414.06496528  733414.06497685
733414.06498843  733414.065       733414.06501157  733414.06502315
733414.06503472  733414.0650463   733414.06505787  733414.06506944
733414.06508102  733414.06509259  733414.06510417  733414.06511574
733414.06512731  733414.06513889  733414.06515046  733414.06516204
733414.06517361  733414.06518519  733414.06519676  733414.06520833
733414.06521991  733414.06523148  733414.06524306  733414.06525463
733414.0652662   733414.06527778  733414.06528935  733414.06530093
733414.0653125   733414.06532407  733414.06533565  733414.06534722
733414.0653588   733414.06537037  733414.06538194  733414.06539352
733414.06540509  733414.06541667  733414.06542824  733414.06543981
733414.06545139  733414.06546296  733414.06547454  733414.06548611
733414.06549769  733414.06550926  733414.06552083  733414.06553241
733414.06554398  733414.06555556  733414.06556713  733414.0655787
733414.06559028  733414.06560185  733414.06561343  733414.065625
733414.06563657  733414.06564815  733414.06565972  733414.0656713
733414.06568287  733414.06569444  733414.06570602  733414.06571759
733414.06572917  733414.06574074  733414.06575231  733414.06576389
733414.06577546  733414.06578704  733414.06579861  733414.06581019
733414.06582176  733414.06583333  733414.06584491  733414.06585648
733414.06586806  733414.06587963  733414.0658912   733414.06590278
733414.06591435  733414.06592593  733414.0659375   733414.06594907
733414.06596065  733414.06597222  733414.0659838   733414.06599537
733414.06600694  733414.06601852  733414.06603009  733414.06604167]
(95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95,
95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95,
95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95,
95, 95, 95, 95, 95, 95, 94, 94, 94, 94, 94, 94, 94, 95, 95, 95, 95,
95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95,
95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 94)

If I run this code:

for s in value_data:
x = mdates.date2num([s[0]])
y = [s[1]]

print [x, y]

The results returned are the following:

There are 100 rows in the database
[ 733414.06489583] [95]
[ 733414.06490741] [95]
[ 733414.06491898] [95]
[ 733414.06493056] [95]
[ 733414.06494213] [95]
[ 733414.0649537] [95]
[ 733414.06496528] [95]
[ 733414.06497685] [95]
[ 733414.06498843] [95]
[ 733414.065] [95]
[ 733414.06501157] [95]
[ 733414.06502315] [95]
[ 733414.06503472] [95]
[ 733414.0650463] [95]
[ 733414.06505787] [95]
[ 733414.06506944] [95]
[ 733414.06508102] [95]
[ 733414.06509259] [95]
[ 733414.06510417] [95]
[ 733414.06511574] [95]
[ 733414.06512731] [95]
[ 733414.06513889] [95]
[ 733414.06515046] [95]
[ 733414.06516204] [95]
[ 733414.06517361] [95]
[ 733414.06518519] [95]
[ 733414.06519676] [95]
[ 733414.06520833] [95]
[ 733414.06521991] [95]
[ 733414.06523148] [95]
[ 733414.06524306] [95]
[ 733414.06525463] [95]
[ 733414.0652662] [95]
[ 733414.06527778] [95]
[ 733414.06528935] [95]
[ 733414.06530093] [95]
[ 733414.0653125] [95]
[ 733414.06532407] [95]
[ 733414.06533565] [95]
[ 733414.06534722] [95]
[ 733414.0653588] [95]
[ 733414.06537037] [95]
[ 733414.06538194] [95]
[ 733414.06539352] [95]
[ 733414.06540509] [95]
[ 733414.06541667] [95]
[ 733414.06542824] [95]
[ 733414.06543981] [95]
[ 733414.06545139] [95]
[ 733414.06546296] [95]
[ 733414.06547454] [95]
[ 733414.06548611] [95]
[ 733414.06549769] [95]
[ 733414.06550926] [95]
[ 733414.06552083] [95]
[ 733414.06553241] [95]
[ 733414.06554398] [95]
[ 733414.06555556] [94]
[ 733414.06556713] [94]
[ 733414.0655787] [94]
[ 733414.06559028] [94]
[ 733414.06560185] [94]
[ 733414.06561343] [94]
[ 733414.065625] [94]
[ 733414.06563657] [95]
[ 733414.06564815] [95]
[ 733414.06565972] [95]
[ 733414.0656713] [95]
[ 733414.06568287] [95]
[ 733414.06569444] [95]
[ 733414.06570602] [95]
[ 733414.06571759] [95]
[ 733414.06572917] [95]
[ 733414.06574074] [95]
[ 733414.06575231] [95]
[ 733414.06576389] [95]
[ 733414.06577546] [95]
[ 733414.06578704] [95]
[ 733414.06579861] [95]
[ 733414.06581019] [95]
[ 733414.06582176] [95]
[ 733414.06583333] [95]
[ 733414.06584491] [95]
[ 733414.06585648] [95]
[ 733414.06586806] [95]
[ 733414.06587963] [95]
[ 733414.0658912] [95]
[ 733414.06590278] [95]
[ 733414.06591435] [95]
[ 733414.06592593] [95]
[ 733414.0659375] [95]
[ 733414.06594907] [95]
[ 733414.06596065] [95]
[ 733414.06597222] [95]
[ 733414.0659838] [95]
[ 733414.06599537] [95]
[ 733414.06600694] [95]
[ 733414.06601852] [95]
[ 733414.06603009] [95]
[ 733414.06604167] [94]

Like you stated above, I am sending one point each time, instead of a
list with many values.  I think I am on the right track, but still
looking to get that last step worked out.

B

```