[SciPy-User] scikits.timeseries: frequency conversion with non-numeric series?

Abiel X Reinhart abiel.x.reinhart@jpmchase....
Mon Apr 26 08:14:17 CDT 2010


I would like to use scikits.timeseries to do a high-to-low frequency conversion on a time series composed of strings. A conversion function like mean or sum obviously does not make sense here, but it should be possible to use functions like end-of-period or start-of-period. Unfortunately, I end up with a ValueError. In general, is it possible to do frequency conversion with non-numeric series?

Example:

import scikits.timeseries as ts

data = ['Q1', 'Q2', 'Q3', 'Q4', 'Q5', 'Q6', 'Q7', 'Q8']
t = ts.time_series(data, freq='Q', start_date=ts.Date('Q', year=2010, quarter=1))
t.convert('A', ts.last_unmasked_val)

Traceback (most recent call last):
  File "cratings.py", line 39, in <module>
    t.convert('A', ts.last_unmasked_val)
  File "C:\Python26\lib\site-packages\scikits.timeseries-0.91.3-py2.6-win32.egg\
scikits\timeseries\tseries.py", line 2002, in convert
    obj = _convert1d(series, freq, func, position, *args, **kwargs)
  File "C:\Python26\lib\site-packages\scikits.timeseries-0.91.3-py2.6-win32.egg\
scikits\timeseries\tseries.py", line 1912, in _convert1d
    int(start_date), mask_)
ValueError: data type must provide an itemsize

This communication is for informational purposes only. It is not
intended as an offer or solicitation for the purchase or sale of
any financial instrument or as an official confirmation of any
transaction. All market prices, data and other information are not
warranted as to completeness or accuracy and are subject to change
without notice. Any comments or statements made herein do not
necessarily reflect those of JPMorgan Chase & Co., its subsidiaries
and affiliates.

This transmission may contain information that is privileged,
confidential, legally privileged, and/or exempt from disclosure
under applicable law. If you are not the intended recipient, you
are hereby notified that any disclosure, copying, distribution, or
use of the information contained herein (including any reliance
thereon) is STRICTLY PROHIBITED. Although this transmission and any
attachments are believed to be free of any virus or other defect
that might affect any computer system into which it is received and
opened, it is the responsibility of the recipient to ensure that it
is virus free and no responsibility is accepted by JPMorgan Chase &
Co., its subsidiaries and affiliates, as applicable, for any loss
or damage arising in any way from its use. If you received this
transmission in error, please immediately contact the sender and
destroy the material in its entirety, whether in electronic or hard
copy format. Thank you.

Please refer to http://www.jpmorgan.com/pages/disclosures for
disclosures relating to European legal entities.


More information about the SciPy-User mailing list