Good morning,
I store time series data in a SQL database. The results of a typical
query using pyodbc look like this.
Date Close
"2007-01-17" 22.57
Where Date is a datetime.date object and Close is a float.
I'd like to put this data in a NumPy array for processing, but am
unsure as to how to handle the date. In the past I've used lists, but I
am looking to boost speed a bit as I wish to do a large number of
transformations and comparisons.
Can one index an array using datetime objects?
For example it would be nice to do a union of two arrays so that any
dates missing in either one were eliminated.
Thoughts on doing rolling operations, such as an n-period average or
variance?
Thoughts on working with time series data in arrays in general?
Thanks in advance,
jab--who is very happily returning to Python after a sojourn in
R-land
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