On 07/09/2017 06:53 PM, siko1056
Fritz Sonnichsen wrote
I did this all the time with Matlab--loaded files with the very common
form of records like this:
2017/07/07, 13:59:59, 022.2, 12.69
Personally, I found that it's a little awkward to process dates
in Octave, so I like to keep my time series data in sqlite
because it has a builtin CSV import, and does dates very well.
The purist may object to such mixing, but the practical person
would point out that the Domain Specific Languages (DSL) concept
is a cool idea.
For Octave use, it's convenient to convert dates to numbers,
e.g. Julian day numbers used by astronomers. I'd do something
sqlite3 mydata.db -csv '.import mydata.csv m' # import the CSV
file to table 'm'
sqlite3 mydata.db 'select julianday(date),col3,col4 from m' #
spit out the data
or actually use the sqlite extension in Octave to read the
database directly instead of using =system()
- it's easier if the first line of the CSV file has column
headers---they become the SQL column names
- actually, since your dates use / instead of - for separator,
and separates date and time, and doesn't specify timezone, it'd
sqlite3 mydata.db 'select julianday(replace(date,"/","-")||"
"||time,"localtime"),col3,col4 from m'
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