Overview

Dataset statistics

Number of variables4
Number of observations635166
Missing cells0
Missing cells (%)0.0%
Total size in memory25.4 MiB
Average record size in memory42.0 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 "wenetIndia"Constant
userid has 25323 (4.0%) zerosZeros
value has 150178 (23.6%) zerosZeros

Reproduction

Analysis started2024-11-22 13:04:45.865708
Analysis finished2024-11-22 13:04:47.939121
Duration2.07 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 size10.9 MiB
2024-11-22T14:04:48.034623image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6351660
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 635166
100.0%
2024-11-22T14:04:48.256968image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1270332
20.0%
n 1270332
20.0%
w 635166
10.0%
t 635166
10.0%
I 635166
10.0%
d 635166
10.0%
i 635166
10.0%
a 635166
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6351660
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1270332
20.0%
n 1270332
20.0%
w 635166
10.0%
t 635166
10.0%
I 635166
10.0%
d 635166
10.0%
i 635166
10.0%
a 635166
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6351660
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1270332
20.0%
n 1270332
20.0%
w 635166
10.0%
t 635166
10.0%
I 635166
10.0%
d 635166
10.0%
i 635166
10.0%
a 635166
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6351660
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1270332
20.0%
n 1270332
20.0%
w 635166
10.0%
t 635166
10.0%
I 635166
10.0%
d 635166
10.0%
i 635166
10.0%
a 635166
10.0%

userid
Real number (ℝ)

ZEROS 

User id

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.70121354
Minimum0
Maximum62
Zeros25323
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size4.8 MiB
2024-11-22T14:04:48.364986image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q140
median40
Q340
95-th percentile46
Maximum62
Range62
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.32361136
Coefficient of variation (CV)0.3085350664
Kurtosis4.10905626
Mean36.70121354
Median Absolute Deviation (MAD)0
Skewness-2.275047896
Sum23311363
Variance128.2241742
MonotonicityIncreasing
2024-11-22T14:04:48.466799image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
40 472227
74.3%
46 65669
 
10.3%
0 25323
 
4.0%
8 23623
 
3.7%
35 10858
 
1.7%
17 7356
 
1.2%
9 6297
 
1.0%
4 4502
 
0.7%
26 4427
 
0.7%
24 2702
 
0.4%
Other values (10) 12182
 
1.9%
ValueCountFrequency (%)
0 25323
4.0%
4 4502
 
0.7%
8 23623
3.7%
9 6297
 
1.0%
12 1324
 
0.2%
ValueCountFrequency (%)
62 1156
 
0.2%
57 1957
 
0.3%
49 1031
 
0.2%
46 65669
10.3%
44 93
 
< 0.1%

timestamp
Date

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

Distinct635154
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size4.8 MiB
Minimum2021-07-12 08:02:18.159000
Maximum2021-08-12 14:41:25.366000
2024-11-22T14:04:48.596314image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-22T14:04:48.721389image/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)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.824908764
Minimum0
Maximum8
Zeros150178
Zeros (%)23.6%
Negative0
Negative (%)0.0%
Memory size4.8 MiB
2024-11-22T14:04:48.816666image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median5
Q35
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.133413502
Coefficient of variation (CV)0.5577684682
Kurtosis-0.4523065597
Mean3.824908764
Median Absolute Deviation (MAD)0
Skewness-1.217624067
Sum2429452
Variance4.551453171
MonotonicityNot monotonic
2024-11-22T14:04:48.904010image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
5 483484
76.1%
0 150178
 
23.6%
8 1504
 
0.2%
ValueCountFrequency (%)
0 150178
 
23.6%
5 483484
76.1%
8 1504
 
0.2%
ValueCountFrequency (%)
8 1504
 
0.2%
5 483484
76.1%
0 150178
 
23.6%

Correlations

2024-11-22T14:04:48.970162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
useridvalue
userid1.0000.119
value0.1191.000