I am attempting to perform some non-GIS specific work within a larger Geoprocessing tool and hoped someone has worked with the Pandas and matplotlib libraries :)
A .csv table containing the fields "PKID" (integer), "STATION" (text), "DAILY_DATE" (datetime), "READVALUE" (double). I need to group by STATION and plot a figure with DAILY_DATE and READVALUE but I am running into errors: "x and y must have same first dimension".
Of course the issue is that for unique_key ("station"), it can have a different numer of dates. That is, for some STATION values it could be 10/1/2011, 10/5/2011, 10/31/2011 and for other STATION values it could include each date in the entire month 10/1/2011 thru 10/31/2011.
Figured I'd ask here before moving to another forum.
Thanks!
j
A .csv table containing the fields "PKID" (integer), "STATION" (text), "DAILY_DATE" (datetime), "READVALUE" (double). I need to group by STATION and plot a figure with DAILY_DATE and READVALUE but I am running into errors: "x and y must have same first dimension".
Of course the issue is that for unique_key ("station"), it can have a different numer of dates. That is, for some STATION values it could be 10/1/2011, 10/5/2011, 10/31/2011 and for other STATION values it could include each date in the entire month 10/1/2011 thru 10/31/2011.
Code:
dtable = pd.io.parsers.read_table(str(datasource), sep=',')
unique_keys = np.unique(dtable['STATION'])
for key in unique_keys:
index = date_range(np.unique(dtable['STATION']))
values = dtable[dtable['STATION'] == key]
plt.figure()
plt.plot(index, values['READVAL']) <-- fails with x/y dimension error if index has less than full list of datesThanks!
j