autots.datasets package

Submodules

autots.datasets.fred module

FRED (Federal Reserve Economic Data) Data Import

requires API key from FRED and pip install fredapi

autots.datasets.fred.get_fred_data(fredkey: str, SeriesNameDict: dict = None, long=True, **kwargs)

Imports Data from Federal Reserve. For simplest results, make sure requested series are all of the same frequency.

Parameters
  • fredkey (str) – an API key from FRED

  • SeriesNameDict (dict) – pairs of FRED Series IDs and Series Names like: {‘SeriesID’: ‘SeriesName’} or a list of FRED IDs. Series id must match Fred IDs, but name can be anything if None, several default series are returned

  • long (bool) – if True, return long style data, else return wide style data with dt index

Module contents

Tools for Importing Sample Data

autots.datasets.load_daily(long: bool = True)

2020 Covid, Air Pollution, and Economic Data.

Sources: Covid Tracking Project, EPA, and FRED

Parameters

long (bool) – if True, return data in long format. Otherwise return wide

autots.datasets.load_monthly(long: bool = True)

Federal Reserve of St. Louis monthly economic indicators.

autots.datasets.load_yearly(long: bool = True)

Federal Reserve of St. Louis annual economic indicators.

autots.datasets.load_hourly(long: bool = True)

Traffic data from the MN DOT via the UCI data repository.

autots.datasets.load_weekly(long: bool = True)

Weekly petroleum industry data from the EIA.

autots.datasets.load_weekdays(long: bool = False, categorical: bool = True, periods: int = 180)

Test edge cases by creating a Series with values as day of week.

Parameters
  • long (bool) – if True, return a df with columns “value” and “datetime” if False, return a Series with dt index

  • categorical (bool) – if True, return str/object, else return int

  • periods (int) – number of periods, ie length of data to generate