io

timeseries.io.read_csv(filepath, date_column='times', value_column='values', to_datetime=None, **kwargs)

Read CSV file and return time series.

Parameters

• filepath – path of CSV file

• date_column – date column string, defaults to ‘times’

• value_column – value column string, defaults to ‘values’

• to_datetime – date format string or explicit function for datetime conversion, defaults to days since UNIX epoch

• **kwargs – optional keyword arguments passed to DictReader

Example

>>> import timeseries as ts

>>> ts.read_csv(ts.samples_path + 'epoch.csv')
date                            value
1970-01-01 00:00:00              1.00
1970-01-02 00:00:00              2.00
1970-01-03 00:00:00              3.00

>>> ts.read_csv(ts.samples_path + 'iso.csv', to_datetime='%Y-%m-%d')
date                            value
1970-01-01 00:00:00              1.00
1970-01-02 00:00:00              2.00
1970-01-03 00:00:00              3.00

>>> ts.read_csv(ts.samples_path + 'epoch_semicolon.csv', delimiter=';')
date                            value
1970-01-01 00:00:00              1.00
1970-01-02 00:00:00              2.00
1970-01-03 00:00:00              3.00

timeseries.io.to_csv(tseries, filepath, date_column='times', value_column='values', to_string=None, **kwargs)

Write time series to CSV file.

Parameters

• tseries – time series object

• filepath – path of output file

• date_column – date column string, defaults to ‘times’

• value_column – value column string, defaults to ‘values’

• to_string – date format string or explicit function for string conversion, defaults to days since UNIX epoch

• **kwargs – optional keyword arguments passed to DictWriter