From 64f71a9afcf3ea519758686e46231e69f768e35b Mon Sep 17 00:00:00 2001 From: Ben Letham Date: Wed, 19 Aug 2020 14:08:16 -0700 Subject: [PATCH] Add documentation about holidays with aggregated data --- notebooks/non-daily_data.ipynb | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/notebooks/non-daily_data.ipynb b/notebooks/non-daily_data.ipynb index a36eb84..035f935 100644 --- a/notebooks/non-daily_data.ipynb +++ b/notebooks/non-daily_data.ipynb @@ -552,25 +552,34 @@ "fcst = m.predict(future)\n", "fig = m.plot(fcst)" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Holidays with aggregated data\n", + "\n", + "Holiday effects are applied to the particular date on which the holiday was specified. With data that has been aggregated to weekly or monthly frequency, holidays that don't fall on the particular date used in the data will be ignored: for example, a Monday holiday in a weekly time series where each data point is on a Sunday. To include holiday effects in the model, the holiday will need to be moved to the date in the history dataframe for which the effect is desired. Note that with weekly or monthly aggregated data, many holiday effects will be well-captured by the yearly seasonality, so added holidays may only be necessary for holidays that occur in different weeks throughout the time series." + ] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.13" + "pygments_lexer": "ipython3", + "version": "3.7.8" } }, "nbformat": 4,