Example of Page Transition

# import openLA as la
import OpenLA as la

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

Before conversion

event_stream.df

	userid	contentsid	operationname	pageno	marker	memo_length	devicecode	eventtime
0	A_U1	C1	PREV	10	NaN	0	tablet	2018-04-09 10:57:15
1	A_U1	C1	PREV	9	NaN	0	tablet	2018-04-09 11:00:59
2	A_U1	C1	PREV	8	NaN	0	tablet	2018-04-09 11:03:31
3	A_U1	C1	PREV	30	NaN	0	tablet	2018-04-10 10:14:12
4	A_U1	C1	PREV	29	NaN	0	tablet	2018-04-10 10:27:24
...	...	...	...	...	...	...	...	...
263279	A_U99	C8	NEXT	3	NaN	0	pc	2018-06-05 16:16:18
263280	A_U99	C8	ADD MARKER	4	difficult	0	pc	2018-06-05 16:18:34
263281	A_U99	C8	NEXT	4	NaN	0	pc	2018-06-05 16:19:24
263282	A_U99	C8	NEXT	5	NaN	0	pc	2018-06-05 16:20:45
263283	A_U99	C8	PREV	6	NaN	0	pc	2018-06-05 16:21:03

263284 rows × 8 columns

Behavior in each page with consideration page transition, e.g. going back and jumping page

page_transition = la.convert_into_page_transition(event_stream=event_stream,
                                                  user_id=course_info.user_id()[:5],
                                                  contents_id="C1",
                                                  invalid_seconds=5,
                                                  timeout_seconds=20*60,
                                                  count_operation=True,
                                                  operation_name=["ADD MARKER", "ADD MEMO", "ADD BOOKMARK"],
                                                  separate_marker_type=False)

page_transition.df

	userid	contentsid	pageno	reading_seconds	time_of_entry	time_of_exit	ADD MARKER	ADD MEMO	ADD BOOKMARK
0	A_U1	C1	9	224	2018-04-09 10:57:15	2018-04-09 11:00:59	0	0	0
1	A_U1	C1	8	152	2018-04-09 11:00:59	2018-04-09 11:03:31	0	0	0
2	A_U1	C1	29	792	2018-04-10 10:14:12	2018-04-10 10:27:24	0	0	0
3	A_U1	C1	27	595	2018-04-10 10:27:24	2018-04-10 10:37:19	0	0	0
4	A_U1	C1	28	99	2018-04-10 15:13:55	2018-04-10 15:15:34	0	0	0
...	...	...	...	...	...	...	...	...	...
1333	A_U102	C1	9	23	2018-06-05 16:12:20	2018-06-05 16:12:43	1	0	0
1334	A_U102	C1	51	63	2018-06-05 16:12:43	2018-06-05 16:13:46	0	0	0
1335	A_U102	C1	47	330	2018-06-05 16:13:46	2018-06-05 16:19:16	0	0	0
1336	A_U102	C1	48	330	2018-06-05 16:19:16	2018-06-05 16:24:46	1	0	0
1337	A_U102	C1	23	473	2018-06-05 16:24:46	2018-06-05 16:32:39	0	0	0

1338 rows × 9 columns

Save the data to CSV file

page_transition.to_csv(save_file="data.csv")

Aggregate Information

# Number of users in the data
page_transition.num_users()

5

# User ids in the data
page_transition.user_id()

['A_U1', 'A_U10', 'A_U100', 'A_U101', 'A_U102']

# Contents ids in the data
page_transition.contents_id()

['C1']

# Operation names in the data
page_transition.operation_name()

['ADD MARKER', 'ADD MEMO', 'ADD BOOKMARK']

# Number of selected operation logs
page_transition.operation_count(operation_name="ADD MARKER",
                                user_id="A_U1",
                                contents_id="C1")

2

page_transition.operation_count(operation_name=["ADD MARKER", "ADD BOOKMARK"],
                                user_id="A_U1",
                                contents_id="C1")

{'ADD MARKER': 2, 'ADD BOOKMARK': 3}

# Number of unique pages in the data
page_transition.num_unique_pages(user_id="A_U1", contents_id="C1")

67

# Total reading seconds in the data
page_transition.reading_seconds(user_id="A_U1", contents_id="C1")

42748

# Total reading time in the data (seconds)
page_transition.reading_time(time_unit="seconds", user_id="A_U1", contents_id="C1")

42748

# Total reading time in the data (minutes)
page_transition.reading_time(time_unit="minutes", user_id="A_U1", contents_id="C1")

712.4666666666667

# Total reading time in the data (hours)
page_transition.reading_time(time_unit="hours", user_id="A_U1", contents_id="C1")

11.874444444444444

# Number of page transition (number of reading pages including duplication)
page_transition.num_transition(user_id="A_U1", contents_id="C1")

363