[SciPy-user] creating timeseries for non convertional custom frequencies
Thu Apr 3 18:24:49 CDT 2008
thanks to the help of the time series developers I am stepping gradually into
time series processing with Python.
I have another issue creating timeseries objects:
How do I create a timeseries object with custom or irregular frequencies?
Here a more verbose explanation of what I want:
I have data that has been recorded from a data logger. Due to memory
constraints, the logger has been set to only save the observations
on a 5-minute basis (1 data point every 5 minutes).
How do I create a hourly data set / timeseries from such a data?
To give two more examples:
* Another data set I have has only data point at every 6 hours (NCAR reanalysis
How do I convert such data into a normal frequencies such as daily or monthly?
* A restaurant records statistics about its guests. The place is closed every
Monday. So there will not be any attendance numbers for Monday. If I use the
daily frequency the timeseries will mess up.
They'd not count the Monday as "empty."
Basicly, I am looking for a way to create my time series object with data that
is not complete by purpose, irregular or of a non convertional frequency.
Something like the business day frequency with the difference that the gaps are
Thanks in advance for your help!
More information about the SciPy-user