statsmodels.tsa.statespace.news.NewsResults.summary¶

NewsResults.summary(impact_date=None, impacted_variable=None, update_date=None, updated_variable=None, impacts_groupby='impact date', details_groupby='update date', show_revisions_columns=None, sparsify=True, include_details_tables=None, include_revisions_tables=False, float_format='%.2f')[source]¶

Create summary tables describing news and impacts

Parameters

impact_dateint, str, datetime, list, array, or slice, optional: Observation index label or slice of labels specifying particular impact periods to display. The impact date(s) describe the periods in which impacted variables were affected by the news. If this argument is given, the impact and details tables will only show this impact date or dates. Note that this argument is passed to the Pandas loc accessor, and so it should correspond to the labels of the model’s index. If the model was created with data in a list or numpy array, then these labels will be zero-indexes observation integers.
impacted_variablestr, list, array, or slice, optional: Observation variable label or slice of labels specifying particular impacted variables to display. The impacted variable(s) describe the variables that were affected by the news. If you do not know the labels for the variables, check the endog_names attribute of the model instance.
update_dateint, str, datetime, list, array, or slice, optional: Observation index label or slice of labels specifying particular updated periods to display. The updated date(s) describe the periods in which the new data points were available that generated the news). See the note on impact_date for details about what these labels are.
updated_variablestr, list, array, or slice, optional: Observation variable label or slice of labels specifying particular updated variables to display. The updated variable(s) describe the variables that were affected by the news. If you do not know the labels for the variables, check the endog_names attribute of the model instance.
impacts_groupby{impact date, impacted date}: The primary variable for grouping results in the impacts table. The default is to group by update date.
details_groupbystr: One of “update date”, “updated date”, “impact date”, or “impacted date”. The primary variable for grouping results in the details table. Only used if the details tables are included. The default is to group by update date.
show_revisions_columnsbool, optional: If set to False, the impacts table will not show the impacts from data revisions or the total impacts. Default is to show the revisions and totals columns if any revisions were made and otherwise to hide them.
sparsifybool, optional, default True: Set to False for the table to include every one of the multiindex keys at each row.
include_details_tablesbool, optional: If set to True, the summary will show tables describing the details of how news from specific updates translate into specific impacts. These tables can be very long, particularly in cases where there were many updates and in multivariate models. The default is to show detailed tables only for univariate models.
include_revisions_tablesbool, optional: If set to True, the summary will show tables describing the revisions and updates that lead to impacts on variables of interest.
float_formatstr, optional: Formatter format string syntax for converting numbers to strings. Default is ‘%.2f’.

Returns

summary_tablesSummary

Summary tables describing news and impacts. Basic tables include:

A table with general information about the sample.
A table describing the impacts of revisions and news.
Tables describing revisions in the dataset since the previous results set (unless include_revisions_tables=False).

In univariate models or if include_details_tables=True, one or more tables will additionally be included describing the details of how news from specific updates translate into specific impacts.