Overview

Dataset statistics

Number of variables4
Number of observations85820
Missing cells0
Missing cells (%)0.0%
Total size in memory4.4 MiB
Average record size in memory53.3 B

Variable types

Text2
Numeric1
DateTime1

Dataset

Description[0/1] Returns the current ring status of the phone (normal/silent/vibrate). 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)
statusThe ring mode status (silent, vibrante, normal)

Alerts

experimentid has constant value "wenetItaly"Constant

Reproduction

Analysis started2024-11-23 06:06:38.350450
Analysis finished2024-11-23 06:06:38.842832
Duration0.49 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 size1.5 MiB
2024-11-23T07:06:38.912760image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters858200
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 rowwenetItaly
2nd rowwenetItaly
3rd rowwenetItaly
4th rowwenetItaly
5th rowwenetItaly
ValueCountFrequency (%)
wenetitaly 85820
100.0%
2024-11-23T07:06:39.162805image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 171640
20.0%
t 171640
20.0%
w 85820
10.0%
n 85820
10.0%
I 85820
10.0%
a 85820
10.0%
l 85820
10.0%
y 85820
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 858200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 171640
20.0%
t 171640
20.0%
w 85820
10.0%
n 85820
10.0%
I 85820
10.0%
a 85820
10.0%
l 85820
10.0%
y 85820
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 858200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 171640
20.0%
t 171640
20.0%
w 85820
10.0%
n 85820
10.0%
I 85820
10.0%
a 85820
10.0%
l 85820
10.0%
y 85820
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 858200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 171640
20.0%
t 171640
20.0%
w 85820
10.0%
n 85820
10.0%
I 85820
10.0%
a 85820
10.0%
l 85820
10.0%
y 85820
10.0%

userid
Real number (ℝ)

User id

Distinct194
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.1769984
Minimum0
Maximum265
Zeros206
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size670.6 KiB
2024-11-23T07:06:39.286911image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19
Q182
median136
Q3202
95-th percentile253
Maximum265
Range265
Interquartile range (IQR)120

Descriptive statistics

Standard deviation71.49331467
Coefficient of variation (CV)0.5211756746
Kurtosis-1.018280303
Mean137.1769984
Median Absolute Deviation (MAD)60
Skewness-0.1761909513
Sum11772530
Variance5111.294042
MonotonicityIncreasing
2024-11-23T07:06:39.409121image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202 8443
 
9.8%
118 8211
 
9.6%
163 5032
 
5.9%
196 3375
 
3.9%
146 2313
 
2.7%
175 2137
 
2.5%
112 2078
 
2.4%
136 1941
 
2.3%
97 1649
 
1.9%
76 1597
 
1.9%
Other values (184) 49044
57.1%
ValueCountFrequency (%)
0 206
 
0.2%
1 88
 
0.1%
2 135
 
0.2%
3 572
0.7%
4 78
 
0.1%
ValueCountFrequency (%)
265 151
 
0.2%
263 72
 
0.1%
262 43
 
0.1%
259 170
 
0.2%
258 1579
1.8%

timestamp
Date

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

Distinct85612
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size670.6 KiB
Minimum2020-11-16 07:00:00.048000
Maximum2020-12-11 21:59:15.736000
2024-11-23T07:06:39.527227image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-23T07:06:39.647177image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

status
Text

The ring mode status (silent, vibrante, normal)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
2024-11-23T07:06:39.731153image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.32366581
Min length11

Characters and Unicode

Total characters971797
Distinct characters14
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 rowmode_normal
2nd rowmode_normal
3rd rowmode_normal
4th rowmode_normal
5th rowmode_silent
ValueCountFrequency (%)
mode_silent 29818
34.7%
mode_normal 28225
32.9%
mode_vibrate 27777
32.4%
2024-11-23T07:06:39.919347image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 143415
14.8%
m 114045
11.7%
o 114045
11.7%
d 85820
8.8%
_ 85820
8.8%
l 58043
6.0%
n 58043
6.0%
i 57595
5.9%
t 57595
5.9%
r 56002
 
5.8%
Other values (4) 141374
14.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 971797
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 143415
14.8%
m 114045
11.7%
o 114045
11.7%
d 85820
8.8%
_ 85820
8.8%
l 58043
6.0%
n 58043
6.0%
i 57595
5.9%
t 57595
5.9%
r 56002
 
5.8%
Other values (4) 141374
14.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 971797
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 143415
14.8%
m 114045
11.7%
o 114045
11.7%
d 85820
8.8%
_ 85820
8.8%
l 58043
6.0%
n 58043
6.0%
i 57595
5.9%
t 57595
5.9%
r 56002
 
5.8%
Other values (4) 141374
14.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 971797
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 143415
14.8%
m 114045
11.7%
o 114045
11.7%
d 85820
8.8%
_ 85820
8.8%
l 58043
6.0%
n 58043
6.0%
i 57595
5.9%
t 57595
5.9%
r 56002
 
5.8%
Other values (4) 141374
14.5%