tstoolbox.tstoolbox.createts

tstoolbox.tstoolbox.createts(input_ts=None, freq=None, fillvalue=None, index_type='datetime', start_date=None, end_date=None)

Create empty time series, optionally fill with a value.

Parameters:

freq (Optional[str]) –

[optional, default is None]

To use this form start_date and end_date must be supplied also. The freq option is the pandas date offset code used to create the index.

Python example:

freq='A'

Command line example:

--freq='A'

fillvalue

[optional, default is None]

The fill value for the time-series. The default is None, which generates the date/time stamps only.

input_tsstr

[optional though required if using within Python, default is ‘-’ (stdin)]

Whether from a file or standard input, data requires a single line header of column names. The default header is the first line of the input, but this can be changed for CSV files using the ‘skiprows’ option.

Most common date formats can be used, but the closer to ISO 8601 date/time standard the better.

Comma-separated values (CSV) files or tab-separated values (TSV):

File separators will be automatically detected.

Columns can be selected by name or index, where the index for
data columns starts at 1.

Command line examples:

Keyword Example	Description
–input_ts=fn.csv	read all columns from ‘fn.csv’
–input_ts=fn.csv,2,1	read data columns 2 and 1 from ‘fn.csv’
–input_ts=fn.csv,2,skiprows=2	read data column 2 from ‘fn.csv’, skipping first 2 rows so header is read from third row
–input_ts=fn.xlsx,2,Sheet21	read all data from 2nd sheet all data from “Sheet21” of ‘fn.xlsx’
–input_ts=fn.hdf5,Table12,T2	read all data from table “Table12” then all data from table “T2” of ‘fn.hdf5’
–input_ts=fn.wdm,210,110	read DSNs 210, then 110 from ‘fn.wdm’
–input_ts=’-’	read all columns from standard input (stdin)
–input_ts=’-’ –columns=4,1	read column 4 and 1 from standard input (stdin)

If working with CSV or TSV files you can use redirection rather than use –input_ts=fname.csv. The following are identical:

From a file:

command subcmd –input_ts=fname.csv

From standard input (since ‘–input_ts=-’ is the default:

command subcmd < fname.csv

Can also combine commands by piping:

command subcmd < filein.csv | command subcmd1 > fileout.csv

Python library examples:

You must use the `input_ts=...` option where `input_ts` can be
one of a [pandas DataFrame, pandas Series, dict, tuple, list,
StringIO, or file name].

start_datestr

[optional, defaults to first date in time-series, input filter]

The start_date of the series in ISOdatetime format, or ‘None’ for beginning.

end_datestr

[optional, defaults to last date in time-series, input filter]

The end_date of the series in ISOdatetime format, or ‘None’ for end.

index_typestr

[optional, default is ‘datetime’, output format]

Can be either ‘number’ or ‘datetime’. Use ‘number’ with index values that are Julian dates, or other epoch reference.

tablefmtstr

[optional, default is ‘csv’, output format]

The table format. Can be one of ‘csv’, ‘tsv’, ‘plain’, ‘simple’, ‘grid’, ‘pipe’, ‘orgtbl’, ‘rst’, ‘mediawiki’, ‘latex’, ‘latex_raw’ and ‘latex_booktabs’.