analysis.attendance¶
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bigbang.analysis.attendance.
name_email_affil_relations_from_IETF_attendance
(meeting_range=[106, 107, 108], threshold=None)¶ Extract and infer from IETF attendance records relations between full names, email address, and affiliations.
In the returned dataframes, each row represents a relation between two of these forms of entity, along with the maximum and minimum date associated with it in the data.
Two forms of inference are used when generating these relational tables:
Missing values in time are filled forward, then filled backward
TODO: Affiliations are ran through the entity resolution script to reduce them to a ‘cannonical form’
- Parameters
meeting_range (list of ints) – The numbers of the IETF meetings to use for source data
threshold (float) – Defaults to None. If not None, activate entity resolution on the affiliations. Threshold value is used for the entity resolution.
- Returns
rel_name_affil (pandas.DataFrame)
rel_email_affil (pandas.DataFrame)
rel_name_email (pandas.DataFrame)