Tutorial of OperationCount

OperationCount class has the aggregated log as the member variable and has the method functions to get the information.

import openLA as la

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

operation_count = la.convert_into_operation_count(event_stream,
                                                  user_id=None,        # all user
                                                  contents_id=None,    # all contents
                                                  operation_name=None  # all operation
                                                  )

The method functions in below table are available now.

You can get the information of the log like operation_count.num_users().

The documentation is in Operation Count Document

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

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

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")
operation_count = la.convert_into_operation_count(event_stream,
                                                  operation_name=operations)

operation_count_df = operation_count.df
print(operation_count_df)
"""
    userid contentsid   NEXT   PREV  ADD MARKER
0       U1         C1  299.0  136.0         2.0
1       U1         C2  182.0  143.0         0.0
2       U1         C3  133.0   39.0         0.0
...     ...       ...   ...     ...         ...
"""

# normalize the count of operations
def normalize(col):
    return (col - min(col)) / (max(col) - min(col))

operation_count_df.loc[:, operations] = operation_count_df.loc[:, operations].apply(normalize, axis=0)
print(operation_count_df)
"""
    userid contentsid      NEXT      PREV  ADD MARKER
0       U1         C1  0.404054  0.303571    0.007435
1       U1         C2  0.245946  0.319196    0.000000
2       U1         C3  0.179730  0.087054    0.000000
...     ...       ...       ...     ...         ...
"""

Example

• Example of Operation Count