=========================================================
Tutorial of *TimeRangeAggregation*
=========================================================

| *TimeRangeAggregation* class has the aggregated log as the member variable and has the method functions to get the information.

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

.. code-block:: python

    import OpenLA as la
    import pandas as pd

    operations = ["NEXT", "PREV", "ADD MARKER"]

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

    user = event_stream.user_id()[5]
    lecture = 1
    content = "C1"

    timerange_aggregation = la.convert_into_time_range(course_info, event_stream,
                                                       user_id=user,
                                                       contents_id=content,
                                                       lecture_week=lecture,
                                                       interval_seconds=60,
                                                       start_time='start_of_lecture',
                                                       end_time='end_of_lecture',
                                                       time_range_basis='minutes',
                                                       count_operation=True,
                                                       operation_name=operations,
                                                       )

    timerange_df = timerange_aggregation.df
    print(timerange_df)
    """
        elapsed_minutes        start_of_range          end_of_range   userid contentsid  pageno  NEXT  PREV
    0               1.0   2018-04-10 14:50:00   2018-04-10 14:51:00       U1         C1       1   0.0   0.0
    1               2.0   2018-04-10 14:51:00   2018-04-10 14:52:00       U1         C1       1   0.0   0.0
    2               3.0   2018-04-10 14:52:00   2018-04-10 14:53:00       U1         C1       1   0.0   0.0
    3               4.0   2018-04-10 14:53:00   2018-04-10 14:54:00       U1         C1       1   0.0   0.0
    4               5.0   2018-04-10 14:54:00   2018-04-10 14:55:00       U1         C1       1   0.0   0.0
    ..              ...                   ...                   ...      ...        ...     ...   ...   ...
    85             86.0   2018-04-10 16:15:00   2018-04-10 16:16:00       U1         C1      27  18.0   2.0
    86             87.0   2018-04-10 16:16:00   2018-04-10 16:17:00       U1         C1      40   0.0   0.0
    87             88.0   2018-04-10 16:17:00   2018-04-10 16:18:00       U1         C1      38   0.0  22.0
    88             89.0   2018-04-10 16:18:00   2018-04-10 16:19:00       U1         C1       9   5.0  13.0
    89             90.0   2018-04-10 16:19:00   2018-04-10 16:20:00       U1         C1      14  19.0   0.0
    """

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

+-----------------------------+------------------------------------------------------------+
| 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  |
+-----------------------------+------------------------------------------------------------+
| reading_seconds             | Get the reading seconds in the log                         |
+-----------------------------+------------------------------------------------------------+
| num_unique_pages            | Get the number of unique pages in the log                  |
+-----------------------------+------------------------------------------------------------+
| unique_pages                | Get the unique page numbers in the log                     |
+-----------------------------+------------------------------------------------------------+

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


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

.. toctree::
   :maxdepth: 1

   ../jupyter_examples/example_timerange