Overview

Dataset statistics

Number of variables4
Number of observations311079
Missing cells0
Missing cells (%)0.0%
Total size in memory13.1 MiB
Average record size in memory44.0 B

Variable types

Text1
Numeric2
DateTime1

Dataset

Description[cm] Measures the distance between the user's head and the phone, depending on the phone it may be measured in centimeters (i.e., the absolute distance) or as labels (e.g., 'near', 'far'). 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)
valueThe distance value (cm, centimeter)

Alerts

experimentid has constant value "wenetDenmark"Constant
userid has 6863 (2.2%) zerosZeros
value has 130796 (42.0%) zerosZeros

Reproduction

Analysis started2024-11-23 02:40:08.996965
Analysis finished2024-11-23 02:40:10.137228
Duration1.14 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 size5.9 MiB
2024-11-23T03:40:10.236297image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3732948
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 311079
100.0%
2024-11-23T03:40:10.458172image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 933237
25.0%
n 622158
16.7%
w 311079
 
8.3%
t 311079
 
8.3%
D 311079
 
8.3%
m 311079
 
8.3%
a 311079
 
8.3%
r 311079
 
8.3%
k 311079
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3732948
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 933237
25.0%
n 622158
16.7%
w 311079
 
8.3%
t 311079
 
8.3%
D 311079
 
8.3%
m 311079
 
8.3%
a 311079
 
8.3%
r 311079
 
8.3%
k 311079
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3732948
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 933237
25.0%
n 622158
16.7%
w 311079
 
8.3%
t 311079
 
8.3%
D 311079
 
8.3%
m 311079
 
8.3%
a 311079
 
8.3%
r 311079
 
8.3%
k 311079
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3732948
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 933237
25.0%
n 622158
16.7%
w 311079
 
8.3%
t 311079
 
8.3%
D 311079
 
8.3%
m 311079
 
8.3%
a 311079
 
8.3%
r 311079
 
8.3%
k 311079
 
8.3%

userid
Real number (ℝ)

ZEROS 

User id

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.2072046
Minimum0
Maximum27
Zeros6863
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-11-23T03:40:10.562665image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q117
median20
Q326
95-th percentile26
Maximum27
Range27
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.30357827
Coefficient of variation (CV)0.4560600296
Kurtosis-0.3057496149
Mean18.2072046
Median Absolute Deviation (MAD)5
Skewness-1.031546868
Sum5663879
Variance68.94941209
MonotonicityIncreasing
2024-11-23T03:40:10.678932image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20 85432
27.5%
26 76074
24.5%
2 25477
 
8.2%
17 22440
 
7.2%
6 16572
 
5.3%
21 16349
 
5.3%
25 16223
 
5.2%
23 14165
 
4.6%
3 13313
 
4.3%
0 6863
 
2.2%
Other values (7) 18171
 
5.8%
ValueCountFrequency (%)
0 6863
 
2.2%
2 25477
8.2%
3 13313
4.3%
6 16572
5.3%
8 3456
 
1.1%
ValueCountFrequency (%)
27 4964
 
1.6%
26 76074
24.5%
25 16223
 
5.2%
23 14165
 
4.6%
22 1548
 
0.5%

timestamp
Date

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

Distinct311047
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
Minimum2020-11-16 07:05:55.291000
Maximum2020-12-11 21:59:25.255000
2024-11-23T03:40:10.794746image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-23T03:40:10.913677image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

value
Real number (ℝ)

ZEROS 

The distance value (cm, centimeter)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.650648228
Minimum0
Maximum100
Zeros130796
Zeros (%)42.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-11-23T03:40:11.007778image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q35
95-th percentile8
Maximum100
Range100
Interquartile range (IQR)5

Descriptive statistics

Standard deviation19.01143098
Coefficient of variation (CV)2.858583153
Kurtosis19.74210884
Mean6.650648228
Median Absolute Deviation (MAD)3
Skewness4.611562562
Sum2068877
Variance361.4345079
MonotonicityNot monotonic
2024-11-23T03:40:11.094521image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 140699
45.2%
0 130796
42.0%
8 14107
 
4.5%
100 12167
 
3.9%
3 11258
 
3.6%
1 2052
 
0.7%
ValueCountFrequency (%)
0 130796
42.0%
1 2052
 
0.7%
3 11258
 
3.6%
5 140699
45.2%
8 14107
 
4.5%
ValueCountFrequency (%)
100 12167
 
3.9%
8 14107
 
4.5%
5 140699
45.2%
3 11258
 
3.6%
1 2052
 
0.7%

Correlations

2024-11-23T03:40:11.155987image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
useridvalue
userid1.000-0.110
value-0.1101.000