==================================
Tutorial of *EventStream* Class
==================================

| When you use the method function *CourseInformation*.load_eventstream(), the function returns the instance of *EventStream* class.
| The class has the e-Book event log as the member variable and has the method functions to get the information.

.. image:: event_stream.png
 :scale: 70%
 :align: center

.. code-block:: python

    import openLA as la

    course_info = la.CourseInformation(files_dir="dataset_sample", course_id="A")
    event_stream = course_info.load_eventstream()

    # or

    course_info, event_stream = la.start_analysis(files_dir="dataset_sample", course_id="A")

| The method functions in below table are available now.
| You can get the information of the log like ``event_stream.num_users()``.
| The documentation is in :doc:`../scripts/event_stream`

+-----------------------------+------------------------------------------------------------+
| function                    | description                                                |
+=============================+============================================================+
| num_users                   | Get the number of users in the log                         |
+-----------------------------+------------------------------------------------------------+
| user_id                     | Get the unique user ids in the log                         |
+-----------------------------+------------------------------------------------------------+
| contents_id                 | Get the unique contents ids in the log                     |
+-----------------------------+------------------------------------------------------------+
| operation_name              | Get the unique operation name in the log                   |
+-----------------------------+------------------------------------------------------------+
| operation_count             | Get the count of each (or specified) operation in the log  |
+-----------------------------+------------------------------------------------------------+
| marker_type                 | Get the unique marker type in the log                      |
+-----------------------------+------------------------------------------------------------+
| device_code                 | Get the unique device code in the log                      |
+-----------------------------+------------------------------------------------------------+

If you want to process other than the above functions, you can get DataFrame type event stream by ``event_stream.df`` and process with Pandas library.

.. code-block:: python

    import openLA as la
    import pandas as pd

    USER_ID = "userid"

    course_info = la.CourseInformation(files_dir="dataset_sample", course_id="A")
    event_stream = course_info.load_eventstream()

    event_stream_df = event_stream.df
    print(event_stream_df)
    """
              userid contentsid operationname  pageno   marker  memo_length  devicecode      eventtime
    0           U1         C1          OPEN       1      NaN          0        tablet    2018-04-08 17:53:47
    1           U1         C1     PAGE_JUMP       1      NaN          0        tablet    2018-04-08 17:53:50
    2           U1         C1          NEXT       1      NaN          0        tablet    2018-04-08 17:54:01
    3           U1         C1          NEXT       2      NaN          0        tablet    2018-04-08 17:54:21
    ...         ...        ...          ...      ...     ...         ...         ...            ...
    """

    # Add "User_" to the beginning of user id
    event_stream_df[USER_ID] = event_stream_df[USERID].apply(lambda x: f"User_{x}")
    print(event_stream_df)
    """
              userid contentsid operationname  pageno   marker  memo_length  devicecode      eventtime
    0        User_U1       C1          OPEN       1      NaN          0        tablet    2018-04-08 17:53:47
    1        User_U1       C1     PAGE_JUMP       1      NaN          0        tablet    2018-04-08 17:53:50
    2        User_U1       C1          NEXT       1      NaN          0        tablet    2018-04-08 17:54:01
    3        User_U1       C1          NEXT       2      NaN          0        tablet    2018-04-08 17:54:21
    ...         ...        ...          ...      ...     ...         ...         ...            ...
    """

Example
============

.. toctree::
   :maxdepth: 1

   ../jupyter_examples/example_event_stream