flowmachine.features.utilities.event_table_subset¶
Class EventTableSubset¶
EventTableSubset(*, start=None, stop=None, hours: Union[Tuple[int, int], NoneType] = None, hour_slices=None, table='events.calls', subscriber_subset=None, columns=['*'], subscriber_identifier='msisdn')
Represent the whole of a dataset subset over certain date ranges.
Attributes¶
Parameters¶
-
start:str, defaultNoneiso format date range for the beginning of the time frame, e.g. 2016-01-01 or 2016-01-01 14:03:01. If None, it will use the earliest date seen in the
events.callstable. -
stop:str, defaultNoneAs above. If None, it will use the latest date seen in the
events.callstable. -
hours:typing.Union[typing.Tuple[int, int], NoneType], defaultNoneSubset the result within certain hours, e.g. (4,17) This will subset the query only with these hours, but across all specified days. Or set to 'all' to include all hours.
-
table:str, default'events.calls'schema qualified name of the table which the analysis is based upon
-
subscriber_identifier:{'msisdn', 'imei'}, default'msisdn'Either msisdn, or imei, the column that identifies the subscriber.
-
subscriber_subset:flowmachine.core.Table,flowmachine.core.Query,list,str, defaultNoneIf provided, string or list of string which are msisdn or imeis to limit results to; or, a query or table which has a column with a name matching subscriber_identifier (typically, msisdn), to limit results to.
Examples¶
sd = EventTableSubset(start='2016-01-01 13:30:30', stop='2016-01-02 16:25:00')
sd.head()
Note
- A date without a hours and mins will be interpreted as midnight of that day, so to get data within a single day pass (e.g.) '2016-01-01', '2016-01-02'. * Use 24 hr format!
Methods¶
cache¶
cache
Returns¶
-
boolTrue is caching is switched on.
column_names¶
column_names
Returns the column names.
Returns¶
-
typing.List[str]List of the column names of this query.
column_names_as_string_list¶
column_names_as_string_list
Get the column names as a comma separated list
Returns¶
-
strComma separated list of column names
dependencies¶
dependencies
Returns¶
-
setThe set of queries which this one is directly dependent on.
fully_qualified_table_name¶
fully_qualified_table_name
Returns a unique fully qualified name for the query to be stored as under the cache schema, based on a hash of the parameters, class, and subqueries.
Returns¶
-
strString form of the table's fqn
index_cols¶
index_cols
A list of columns to use as indexes when storing this query.
Returns¶
-
ixen:listBy default, returns the location columns if they are present and self.spatial_unit is defined, and the subscriber column.
Examples¶
daily_location("2016-01-01").index_cols
[['name'], '"subscriber"']
is_stored¶
is_stored
Returns¶
-
boolTrue if the table is stored, and False otherwise.
query_id¶
query_id
Generate a uniquely identifying hash of this query, based on the parameters of it and the subqueries it is composed of.
Returns¶
-
strquery_id hash string
query_state¶
query_state
Return the current query state.
Returns¶
-
QueryStateThe current query state
query_state_str¶
query_state_str
Return the current query state as a string
Returns¶
-
strThe current query state. The possible values are the ones defined in
flowmachine.core.query_state.QueryState.
table_name¶
table_name
Returns a uniquename for the query to be stored as, based on a hash of the parameters, class, and subqueries.
Returns¶
-
strString form of the table's fqn