Eventstream Core

Eventstream

class retentioneering.eventstream.eventstream.Eventstream(raw_data, raw_data_schema=None, schema=None, prepare=True, index_order=None, relations=None, user_sample_size=None, user_sample_seed=None)

Collection of tools for storing and processing clickstream data.

Parameters:

raw_datapd.DataFrame or pd.Series

Raw clickstream data.

raw_data_schemaRawDataSchema, optional

Should be specified as an instance of class RawDataSchema:

• If raw_data column names are different from the default RawDataSchema.

• If there is at least one custom_col in raw_data.

schemaEventstreamSchema, optional

Schema of the created eventstream. See default schema EventstreamSchema.

preparebool, default True

• If True, input data will be transformed in the following way:

  • event_timestamp column is converted to pandas datetime format.

  • event_type column is added and filled with raw value.

    If the column exists, it remains unchanged.

• If False - raw_data will be remained as is.

index_orderlist of str, default DEFAULT_INDEX_ORDER

Sorting order for event_type column.

relationslist, optional

user_sample_sizeint of float, optional

Number (int) or share (float) of all users’ trajectories that will be randomly chosen and left in final sample (all other trajectories will be removed) . See numpy documentation.

user_sample_seedint, optional

A seed value that is used to generate user samples. See numpy documentation.

Notes

See Eventstream user guide for the details.

add_custom_col(name, data)

Add custom column to an existing eventstream.

Parameters:

namestr

New column name.

datapd.Series

• If pd.Series - new column with given values will be added.

• If None - new column will be filled with np.nan.

Returns:

Eventstream

append_eventstream(eventstream)

Append eventstream with the same schema.

Parameters:

eventstreamEventstream

Returns:

eventstream

Raises:

ValueError

If EventstreamSchemas of two eventstreams are not equal.

copy()

Make a copy of current eventstream.

Returns:

Eventstream

index_events()

Sort and index eventstream using DEFAULT_INDEX_ORDER.

Returns:

None

to_dataframe(raw_cols=False, show_deleted=False, copy=False)

Convert eventstream to pd.Dataframe

Parameters:

raw_colsbool, default False

If True - original columns of the input raw_data will be shown.

show_deletedbool, default False

If True - show all rows in eventstream.

copybool, default False

If True - copy data from current eventstream. See details in the pandas documentation.

Returns:

pd.DataFrame

Schema

class retentioneering.eventstream.schema.EventstreamSchema(event_id='event_id', event_type='event_type', event_index='event_index', event_name='event', event_timestamp='timestamp', user_id='user_id', custom_cols=<factory>)

Define a schema for eventstream columns names. If names of the columns are different from default names, they need to be specified.

Parameters:

event_idstr, default “event_id”

event_typestr, default “event_type”

event_indexstr, default “event_index”

event_namestr, default “event”

event_timestampstr, default “timestamp”

user_idstr, default “user_id”

custom_colslist of str, optional

Notes

See Eventstream user guide for the details.

class retentioneering.eventstream.schema.RawDataSchema(event_name='event', event_timestamp='timestamp', user_id='user_id', event_type=None, custom_cols=<factory>)

Define schema for raw_data columns names. If names of the columns are different from default names, they need to be specified.

Parameters:

event_namestr, default “event”

event_timestampstr, default “timestamp”

user_idstr, default “user_id”

event_typestr, optional

custom_colslist, optional

Notes

See Eventstream user guide for the details.