Overview

Dataset statistics

Number of variables5
Number of observations140298
Missing cells0
Missing cells (%)0.0%
Total size in memory6.7 MiB
Average record size in memory50.0 B

Variable types

Text1
Numeric3
DateTime1

Dataset

Description[%] Returns whether the phone is on charge and the type of charger. 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)
levelNumeric value of the charge level of the battery
scaleScale of the battery

Alerts

experimentid has constant value "wenetIndia"Constant
scale has constant value "100.0"Constant
userid has 34949 (24.9%) zerosZeros

Reproduction

Analysis started2024-11-24 09:04:13.139053
Analysis finished2024-11-24 09:04:13.684442
Duration0.55 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 size2.4 MiB
2024-11-24T10:04:13.781394image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1402980
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 140298
100.0%
2024-11-24T10:04:14.109463image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 280596
20.0%
n 280596
20.0%
w 140298
10.0%
t 140298
10.0%
I 140298
10.0%
d 140298
10.0%
i 140298
10.0%
a 140298
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1402980
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 280596
20.0%
n 280596
20.0%
w 140298
10.0%
t 140298
10.0%
I 140298
10.0%
d 140298
10.0%
i 140298
10.0%
a 140298
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1402980
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 280596
20.0%
n 280596
20.0%
w 140298
10.0%
t 140298
10.0%
I 140298
10.0%
d 140298
10.0%
i 140298
10.0%
a 140298
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1402980
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 280596
20.0%
n 280596
20.0%
w 140298
10.0%
t 140298
10.0%
I 140298
10.0%
d 140298
10.0%
i 140298
10.0%
a 140298
10.0%

userid
Real number (ℝ)

ZEROS 

User id

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.8801052
Minimum0
Maximum62
Zeros34949
Zeros (%)24.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-11-24T10:04:14.221039image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median12
Q317
95-th percentile49
Maximum62
Range62
Interquartile range (IQR)13

Descriptive statistics

Standard deviation15.30414832
Coefficient of variation (CV)1.02849732
Kurtosis1.199431112
Mean14.8801052
Median Absolute Deviation (MAD)5
Skewness1.407012537
Sum2087649
Variance234.2169558
MonotonicityIncreasing
2024-11-24T10:04:14.342713image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
12 38071
27.1%
0 34949
24.9%
9 19922
14.2%
17 15366
11.0%
43 8269
 
5.9%
18 4354
 
3.1%
44 4311
 
3.1%
57 3410
 
2.4%
49 2307
 
1.6%
8 1747
 
1.2%
Other values (10) 7592
 
5.4%
ValueCountFrequency (%)
0 34949
24.9%
4 1359
 
1.0%
8 1747
 
1.2%
9 19922
14.2%
12 38071
27.1%
ValueCountFrequency (%)
62 1578
 
1.1%
57 3410
2.4%
49 2307
1.6%
46 233
 
0.2%
44 4311
3.1%

timestamp
Date

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

Distinct140297
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Minimum2021-07-12 08:00:08.023000
Maximum2021-08-12 14:40:03.490000
2024-11-24T10:04:14.461276image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-24T10:04:14.585779image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

level
Real number (ℝ)

Numeric value of the charge level of the battery

Distinct99
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.69198421
Minimum2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-11-24T10:04:14.707413image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile25
Q147
median66
Q384
95-th percentile100
Maximum100
Range98
Interquartile range (IQR)37

Descriptive statistics

Standard deviation23.30888611
Coefficient of variation (CV)0.3603056298
Kurtosis-0.9717596279
Mean64.69198421
Median Absolute Deviation (MAD)18
Skewness-0.2003254086
Sum9076156
Variance543.3041719
MonotonicityNot monotonic
2024-11-24T10:04:14.830701image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11423
 
8.1%
77 2327
 
1.7%
78 2200
 
1.6%
75 2188
 
1.6%
73 2182
 
1.6%
71 2174
 
1.5%
57 2110
 
1.5%
54 2086
 
1.5%
56 2065
 
1.5%
70 2058
 
1.5%
Other values (89) 109485
78.0%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 8
 
< 0.1%
4 15
< 0.1%
5 18
< 0.1%
6 26
< 0.1%
ValueCountFrequency (%)
100 11423
8.1%
99 1082
 
0.8%
98 1193
 
0.9%
97 1281
 
0.9%
96 1391
 
1.0%

scale
Real number (ℝ)

CONSTANT 

Scale of the battery

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100
Minimum100
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-11-24T10:04:14.924010image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean100
Median Absolute Deviation (MAD)0
Skewness0
Sum14029800
Variance0
MonotonicityIncreasing
2024-11-24T10:04:15.004750image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
100 140298
100.0%
ValueCountFrequency (%)
100 140298
100.0%
ValueCountFrequency (%)
100 140298
100.0%

Correlations

2024-11-24T10:04:15.062017image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
leveluserid
level1.0000.040
userid0.0401.000