Overview

Dataset statistics

Number of variables4
Number of observations281198
Missing cells0
Missing cells (%)0.0%
Total size in memory9.4 MiB
Average record size in memory35.0 B

Variable types

Text1
Numeric1
DateTime1
Boolean1

Dataset

Description[unitless] Sensor that detects when the user is present. An example is when the user unlocks the screen. This sensor can be used in comparison to Screen status to check if the screen turn on event occurred due to the user or, for example, due to a received notification. The event user present OFF is simply when the screen turns off. To compare each sensor observation, the frequency was reduced to one minute. The first non-missing name is reported for each of the categorical variables.
CreatorAndrea Bontempelli, Matteo Busso, Roy Alia Asiku
AuthorAndrea Bontempelli, Matteo Busso, Fausto Giunchiglia
URL
Copyright(c) University of Trento - Knowledge Diversity 2023

Variable descriptions

experimentidExperiment Id
useridUser id
timestampshow month(2), day(2), hour(2), minute(2), second(2), decimals(3)
statusReturn if the user is present or not

Alerts

experimentid has constant value "wenetIndia"Constant
userid has 100759 (35.8%) zerosZeros

Reproduction

Analysis started2024-11-22 12:32:04.489083
Analysis finished2024-11-22 12:32:05.623809
Duration1.13 second
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

experimentid
Text

CONSTANT 

Experiment Id

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.8 MiB
2024-11-22T13:32:05.717965image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2811980
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowwenetIndia
2nd rowwenetIndia
3rd rowwenetIndia
4th rowwenetIndia
5th rowwenetIndia
ValueCountFrequency (%)
wenetindia 281198
100.0%
2024-11-22T13:32:05.941369image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 562396
20.0%
n 562396
20.0%
w 281198
10.0%
t 281198
10.0%
I 281198
10.0%
d 281198
10.0%
i 281198
10.0%
a 281198
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2811980
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 562396
20.0%
n 562396
20.0%
w 281198
10.0%
t 281198
10.0%
I 281198
10.0%
d 281198
10.0%
i 281198
10.0%
a 281198
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2811980
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 562396
20.0%
n 562396
20.0%
w 281198
10.0%
t 281198
10.0%
I 281198
10.0%
d 281198
10.0%
i 281198
10.0%
a 281198
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2811980
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 562396
20.0%
n 562396
20.0%
w 281198
10.0%
t 281198
10.0%
I 281198
10.0%
d 281198
10.0%
i 281198
10.0%
a 281198
10.0%

userid
Real number (ℝ)

ZEROS 

User id

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.59305187
Minimum0
Maximum62
Zeros100759
Zeros (%)35.8%
Negative0
Negative (%)0.0%
Memory size2.1 MiB
2024-11-22T13:32:06.046187image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q326
95-th percentile35
Maximum62
Range62
Interquartile range (IQR)26

Descriptive statistics

Standard deviation12.51441168
Coefficient of variation (CV)0.9937552717
Kurtosis0.7930764788
Mean12.59305187
Median Absolute Deviation (MAD)12
Skewness0.9245361871
Sum3541141
Variance156.6104998
MonotonicityIncreasing
2024-11-22T13:32:06.144033image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 100759
35.8%
26 66860
23.8%
12 65076
23.1%
9 21719
 
7.7%
35 5150
 
1.8%
17 4835
 
1.7%
24 3356
 
1.2%
43 3079
 
1.1%
4 2315
 
0.8%
44 2196
 
0.8%
Other values (10) 5853
 
2.1%
ValueCountFrequency (%)
0 100759
35.8%
4 2315
 
0.8%
8 633
 
0.2%
9 21719
 
7.7%
12 65076
23.1%
ValueCountFrequency (%)
62 1356
0.5%
57 1539
0.5%
49 591
 
0.2%
46 156
 
0.1%
44 2196
0.8%

timestamp
Date

show month(2), day(2), hour(2), minute(2), second(2), decimals(3)

Distinct281181
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
Minimum2021-07-12 08:05:14.999000
Maximum2021-08-12 14:40:29.583000
2024-11-22T13:32:06.273596image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-22T13:32:06.409914image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

status
Boolean

Return if the user is present or not

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size274.7 KiB
False
243804 
True
37394 
ValueCountFrequency (%)
False 243804
86.7%
True 37394
 
13.3%
2024-11-22T13:32:06.507287image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-11-22T13:32:06.560478image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
statususerid
status1.0000.014
userid0.0141.000