Overview

Dataset statistics

Number of variables4
Number of observations3211889
Missing cells1317771
Missing cells (%)10.3%
Total size in memory202.3 MiB
Average record size in memory66.1 B

Variable types

Text2
Numeric1
DateTime1

Dataset

Description[unitless] Returns the name of the application (or application package) that is currently running in the foreground of the phone. 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)
applicationnameName of the application

Alerts

experimentid has constant value "wenetDenmark"Constant
applicationname has 1317771 (41.0%) missing valuesMissing
userid has 404033 (12.6%) zerosZeros

Reproduction

Analysis started2024-11-24 09:19:12.253587
Analysis finished2024-11-24 09:19:22.933805
Duration10.68 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

experimentid
Text

CONSTANT 

Experiment Id

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size85.8 MiB
2024-11-24T10:19:23.002356image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters38542668
Distinct characters9
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 rowwenetDenmark
2nd rowwenetDenmark
3rd rowwenetDenmark
4th rowwenetDenmark
5th rowwenetDenmark
ValueCountFrequency (%)
wenetdenmark 3211889
100.0%
2024-11-24T10:19:23.258053image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 9635667
25.0%
n 6423778
16.7%
w 3211889
 
8.3%
t 3211889
 
8.3%
D 3211889
 
8.3%
m 3211889
 
8.3%
a 3211889
 
8.3%
r 3211889
 
8.3%
k 3211889
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38542668
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 9635667
25.0%
n 6423778
16.7%
w 3211889
 
8.3%
t 3211889
 
8.3%
D 3211889
 
8.3%
m 3211889
 
8.3%
a 3211889
 
8.3%
r 3211889
 
8.3%
k 3211889
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38542668
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 9635667
25.0%
n 6423778
16.7%
w 3211889
 
8.3%
t 3211889
 
8.3%
D 3211889
 
8.3%
m 3211889
 
8.3%
a 3211889
 
8.3%
r 3211889
 
8.3%
k 3211889
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38542668
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 9635667
25.0%
n 6423778
16.7%
w 3211889
 
8.3%
t 3211889
 
8.3%
D 3211889
 
8.3%
m 3211889
 
8.3%
a 3211889
 
8.3%
r 3211889
 
8.3%
k 3211889
 
8.3%

userid
Real number (ℝ)

ZEROS 

User id

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.15101051
Minimum0
Maximum27
Zeros404033
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size49.0 MiB
2024-11-24T10:19:23.364984image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median17
Q323
95-th percentile27
Maximum27
Range27
Interquartile range (IQR)20

Descriptive statistics

Standard deviation10.29584401
Coefficient of variation (CV)0.7828937554
Kurtosis-1.741320652
Mean13.15101051
Median Absolute Deviation (MAD)10
Skewness-0.00224297697
Sum42239586
Variance106.0044038
MonotonicityIncreasing
2024-11-24T10:19:23.461270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 404033
12.6%
23 393270
12.2%
6 391784
12.2%
3 383912
12.0%
2 338114
10.5%
26 331880
10.3%
17 269035
8.4%
21 246470
7.7%
27 213373
6.6%
22 100782
 
3.1%
Other values (7) 139236
 
4.3%
ValueCountFrequency (%)
0 404033
12.6%
2 338114
10.5%
3 383912
12.0%
6 391784
12.2%
8 11377
 
0.4%
ValueCountFrequency (%)
27 213373
6.6%
26 331880
10.3%
25 34852
 
1.1%
23 393270
12.2%
22 100782
 
3.1%

timestamp
Date

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

Distinct3209666
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size49.0 MiB
Minimum2020-11-16 07:00:00.157000
Maximum2020-12-11 21:59:59.138000
2024-11-24T10:19:23.572177image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-24T10:19:23.687416image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

applicationname
Text

MISSING 

Name of the application

Distinct333
Distinct (%)< 0.1%
Missing1317771
Missing (%)41.0%
Memory size92.0 MiB
2024-11-24T10:19:23.842550image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length47
Median length41
Mean length23.61359852
Min length7

Characters and Unicode

Total characters44726942
Distinct characters45
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

Unique19 ?
Unique (%)< 0.1%

Sample

1st rowcom.facebook.katana
2nd rowcom.facebook.katana
3rd rowcom.facebook.katana
4th rowcom.facebook.katana
5th rowcom.facebook.katana
ValueCountFrequency (%)
com.sec.android.app.launcher 411454
21.7%
com.huawei.android.launcher 140901
 
7.4%
com.instagram.android 114344
 
6.0%
net.oneplus.launcher 96557
 
5.1%
com.whatsapp 84791
 
4.5%
com.android.chrome 78022
 
4.1%
com.android.launcher3 72246
 
3.8%
com.facebook.katana 63749
 
3.4%
com.oneplus.deskclock 61768
 
3.3%
it.unitn.disi.witmee.sensorlog 52400
 
2.8%
Other values (323) 717886
37.9%
2024-11-24T10:19:24.156482image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5138642
11.5%
o 4524972
 
10.1%
a 3888177
 
8.7%
c 3642388
 
8.1%
e 3050400
 
6.8%
n 2892730
 
6.5%
d 2625031
 
5.9%
r 2494560
 
5.6%
i 2443892
 
5.5%
m 2381018
 
5.3%
Other values (35) 11645132
26.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 44726942
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 5138642
11.5%
o 4524972
 
10.1%
a 3888177
 
8.7%
c 3642388
 
8.1%
e 3050400
 
6.8%
n 2892730
 
6.5%
d 2625031
 
5.9%
r 2494560
 
5.6%
i 2443892
 
5.5%
m 2381018
 
5.3%
Other values (35) 11645132
26.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 44726942
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 5138642
11.5%
o 4524972
 
10.1%
a 3888177
 
8.7%
c 3642388
 
8.1%
e 3050400
 
6.8%
n 2892730
 
6.5%
d 2625031
 
5.9%
r 2494560
 
5.6%
i 2443892
 
5.5%
m 2381018
 
5.3%
Other values (35) 11645132
26.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 44726942
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 5138642
11.5%
o 4524972
 
10.1%
a 3888177
 
8.7%
c 3642388
 
8.1%
e 3050400
 
6.8%
n 2892730
 
6.5%
d 2625031
 
5.9%
r 2494560
 
5.6%
i 2443892
 
5.5%
m 2381018
 
5.3%
Other values (35) 11645132
26.0%