Overview

Dataset statistics

Number of variables8
Number of observations224590
Missing cells0
Missing cells (%)0.0%
Total size in memory45.6 MiB
Average record size in memory213.0 B

Variable types

Text5
Numeric2
DateTime1

Dataset

Description[unitless] Returns wheter the device to wirelessly exchange data with other Bluetooth devices. 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)
addressMAC address.
bondstatebond state of the remote device.
namename of the remote device.
rssi(Received Signal Strength Indicator) is an estimated measure of power level received from an access point or router. (dBm)
typethe type of bluetooth device {normal, low-energy}

Alerts

experimentid has constant value "wenetIndia"Constant
userid has 10361 (4.6%) zerosZeros

Reproduction

Analysis started2024-11-22 13:01:42.434688
Analysis finished2024-11-22 13:01:44.603836
Duration2.17 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 size3.9 MiB
2024-11-22T14:01:44.699346image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2245900
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 224590
100.0%
2024-11-22T14:01:44.929382image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 449180
20.0%
n 449180
20.0%
w 224590
10.0%
t 224590
10.0%
I 224590
10.0%
d 224590
10.0%
i 224590
10.0%
a 224590
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2245900
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 449180
20.0%
n 449180
20.0%
w 224590
10.0%
t 224590
10.0%
I 224590
10.0%
d 224590
10.0%
i 224590
10.0%
a 224590
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2245900
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 449180
20.0%
n 449180
20.0%
w 224590
10.0%
t 224590
10.0%
I 224590
10.0%
d 224590
10.0%
i 224590
10.0%
a 224590
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2245900
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 449180
20.0%
n 449180
20.0%
w 224590
10.0%
t 224590
10.0%
I 224590
10.0%
d 224590
10.0%
i 224590
10.0%
a 224590
10.0%

userid
Real number (ℝ)

ZEROS 

User id

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.95031391
Minimum0
Maximum57
Zeros10361
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size1.7 MiB
2024-11-22T14:01:45.043642image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q19
median9
Q312
95-th percentile57
Maximum57
Range57
Interquartile range (IQR)3

Descriptive statistics

Standard deviation19.04986525
Coefficient of variation (CV)1.005253282
Kurtosis0.01188910227
Mean18.95031391
Median Absolute Deviation (MAD)0
Skewness1.345093292
Sum4256051
Variance362.8973661
MonotonicityIncreasing
2024-11-22T14:01:45.129303image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
9 147674
65.8%
57 39701
 
17.7%
12 11727
 
5.2%
0 10361
 
4.6%
26 5759
 
2.6%
44 5227
 
2.3%
35 1903
 
0.8%
49 956
 
0.4%
17 564
 
0.3%
40 377
 
0.2%
Other values (2) 341
 
0.2%
ValueCountFrequency (%)
0 10361
 
4.6%
8 180
 
0.1%
9 147674
65.8%
12 11727
 
5.2%
17 564
 
0.3%
ValueCountFrequency (%)
57 39701
17.7%
49 956
 
0.4%
44 5227
 
2.3%
40 377
 
0.2%
35 1903
 
0.8%

timestamp
Date

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

Distinct223790
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
Minimum2021-07-12 08:06:08.177000
Maximum2021-08-07 21:08:07.539000
2024-11-22T14:01:45.238661image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-22T14:01:45.353987image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

address
Text

MAC address.

Distinct1899
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size15.4 MiB
2024-11-22T14:01:45.468654image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters14373760
Distinct characters16
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

Unique67 ?
Unique (%)< 0.1%

Sample

1st row0657ed65f031755eed076b781610bd032a21626d9c0e7ddd4bfd5bc7afbe053a
2nd row0657ed65f031755eed076b781610bd032a21626d9c0e7ddd4bfd5bc7afbe053a
3rd row0657ed65f031755eed076b781610bd032a21626d9c0e7ddd4bfd5bc7afbe053a
4th row0657ed65f031755eed076b781610bd032a21626d9c0e7ddd4bfd5bc7afbe053a
5th row0657ed65f031755eed076b781610bd032a21626d9c0e7ddd4bfd5bc7afbe053a
ValueCountFrequency (%)
7a9cd4646e8b6eda985e728b61e2fe1e7f45d2052f24d098f02f31cd0fb9ab8c 64454
28.7%
242a7574854dea819bbf7e109d8e7824011cc47a9205c20ff3255932a62e7dac 32544
 
14.5%
0657ed65f031755eed076b781610bd032a21626d9c0e7ddd4bfd5bc7afbe053a 7300
 
3.3%
1718e81f078940226a435c0dad692e3674807d4e447564d965073c1b453d80cf 5855
 
2.6%
3b82510dd8749d02d49cf903e44a45f35f587947d16bd7b1dc8dab93db12a771 2865
 
1.3%
8fc8f2f06697d65550fd84b10d74b34e30abc0b78aae8e1ccc6e1e84552655c7 2752
 
1.2%
4d17991530071442a6318fd24782dfec8608cb74149bfd9a9a24482514aa5a0a 2459
 
1.1%
f9346891c8abd1b3285a1f97b47c77cc4be96800d5b702da7e2cc5bc6ee16c6e 2054
 
0.9%
27621fbf7ac200136d99bf9a4a0138015a0c405d3212624f97034b5382832725 1967
 
0.9%
a8a7e7b9babffd814b80b13ba144ece0edd6129194153317fd274e317cec0c90 1547
 
0.7%
Other values (1889) 100793
44.9%
2024-11-22T14:01:45.672781image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1129187
 
7.9%
e 1022846
 
7.1%
8 967349
 
6.7%
f 966678
 
6.7%
d 954953
 
6.6%
4 947365
 
6.6%
7 939662
 
6.5%
0 935446
 
6.5%
5 886842
 
6.2%
9 883417
 
6.1%
Other values (6) 4740015
33.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14373760
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 1129187
 
7.9%
e 1022846
 
7.1%
8 967349
 
6.7%
f 966678
 
6.7%
d 954953
 
6.6%
4 947365
 
6.6%
7 939662
 
6.5%
0 935446
 
6.5%
5 886842
 
6.2%
9 883417
 
6.1%
Other values (6) 4740015
33.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14373760
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 1129187
 
7.9%
e 1022846
 
7.1%
8 967349
 
6.7%
f 966678
 
6.7%
d 954953
 
6.6%
4 947365
 
6.6%
7 939662
 
6.5%
0 935446
 
6.5%
5 886842
 
6.2%
9 883417
 
6.1%
Other values (6) 4740015
33.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14373760
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 1129187
 
7.9%
e 1022846
 
7.1%
8 967349
 
6.7%
f 966678
 
6.7%
d 954953
 
6.6%
4 947365
 
6.6%
7 939662
 
6.5%
0 935446
 
6.5%
5 886842
 
6.2%
9 883417
 
6.1%
Other values (6) 4740015
33.0%

bondstate
Text

bond state of the remote device.

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.8 MiB
2024-11-22T14:01:45.752141image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.609501759
Min length9

Characters and Unicode

Total characters2158198
Distinct characters6
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 rowBOND_NONE
2nd rowBOND_NONE
3rd rowBOND_NONE
4th rowBOND_NONE
5th rowBOND_NONE
ValueCountFrequency (%)
bond_none 156146
69.5%
bond_bonded 68444
30.5%
2024-11-22T14:01:45.950810image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 605326
28.0%
O 449180
20.8%
D 361478
16.7%
B 293034
13.6%
_ 224590
 
10.4%
E 224590
 
10.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2158198
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 605326
28.0%
O 449180
20.8%
D 361478
16.7%
B 293034
13.6%
_ 224590
 
10.4%
E 224590
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2158198
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 605326
28.0%
O 449180
20.8%
D 361478
16.7%
B 293034
13.6%
_ 224590
 
10.4%
E 224590
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2158198
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 605326
28.0%
O 449180
20.8%
D 361478
16.7%
B 293034
13.6%
_ 224590
 
10.4%
E 224590
 
10.4%

name
Text

name of the remote device.

Distinct460
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.4 MiB
2024-11-22T14:01:46.173195image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters14373760
Distinct characters16
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

Unique5 ?
Unique (%)< 0.1%

Sample

1st row0bf40a842eb461b56798666b2a37656e7a4cb0b3104f997756e7b126a238a1f4
2nd row0bf40a842eb461b56798666b2a37656e7a4cb0b3104f997756e7b126a238a1f4
3rd row0bf40a842eb461b56798666b2a37656e7a4cb0b3104f997756e7b126a238a1f4
4th row0bf40a842eb461b56798666b2a37656e7a4cb0b3104f997756e7b126a238a1f4
5th row0bf40a842eb461b56798666b2a37656e7a4cb0b3104f997756e7b126a238a1f4
ValueCountFrequency (%)
f562ea4a1b6c1055b58134c771c10ce17447e9ee555efc9bef54af3a51aba432 80332
35.8%
8c1f09bd3d0dac2138860d083235a6dcf2bfb65c65ea3c0a731b382cf0f158b7 64454
28.7%
772aebfcf8a61911d663fa96215a457d7385120ef96c480d258a16cb52d65d76 31023
 
13.8%
0bf40a842eb461b56798666b2a37656e7a4cb0b3104f997756e7b126a238a1f4 7300
 
3.3%
6e6b12177aa019462756a324de6b65c459a47234469d7015ca0b626e29ac4386 5855
 
2.6%
7310105253a5faab29184d8a3c9a8c741847281345150b69b4bc9fce11bfad0b 2865
 
1.3%
c2d8788176c48e970d9cb0839401b93b8e0b3469a061f90c8b66df31e60a6f01 2752
 
1.2%
a4b662016602a21f2c8c96f409e6937bf566179edca613d72820becefada7545 2589
 
1.2%
cae7ba48250d7c4008c602648691f47c9abfe32bc188dc5742bb00481f3d02ed 2054
 
0.9%
d26a9a081aab4938fc0adfaf74273f382aaaad0322da533a6b7e0ce4e518848c 1912
 
0.9%
Other values (450) 23454
 
10.4%
2024-11-22T14:01:46.377620image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1336674
 
9.3%
1 1221225
 
8.5%
a 1132760
 
7.9%
c 1051440
 
7.3%
6 933687
 
6.5%
f 924772
 
6.4%
3 917141
 
6.4%
b 916974
 
6.4%
e 862403
 
6.0%
7 824635
 
5.7%
Other values (6) 4252049
29.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14373760
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 1336674
 
9.3%
1 1221225
 
8.5%
a 1132760
 
7.9%
c 1051440
 
7.3%
6 933687
 
6.5%
f 924772
 
6.4%
3 917141
 
6.4%
b 916974
 
6.4%
e 862403
 
6.0%
7 824635
 
5.7%
Other values (6) 4252049
29.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14373760
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 1336674
 
9.3%
1 1221225
 
8.5%
a 1132760
 
7.9%
c 1051440
 
7.3%
6 933687
 
6.5%
f 924772
 
6.4%
3 917141
 
6.4%
b 916974
 
6.4%
e 862403
 
6.0%
7 824635
 
5.7%
Other values (6) 4252049
29.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14373760
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 1336674
 
9.3%
1 1221225
 
8.5%
a 1132760
 
7.9%
c 1051440
 
7.3%
6 933687
 
6.5%
f 924772
 
6.4%
3 917141
 
6.4%
b 916974
 
6.4%
e 862403
 
6.0%
7 824635
 
5.7%
Other values (6) 4252049
29.6%

rssi
Real number (ℝ)

(Received Signal Strength Indicator) is an estimated measure of power level received from an access point or router. (dBm)

Distinct88
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-74.40966205
Minimum-106
Maximum-17
Zeros0
Zeros (%)0.0%
Negative224590
Negative (%)100.0%
Memory size1.7 MiB
2024-11-22T14:01:46.494990image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-106
5-th percentile-96
Q1-88
median-79
Q3-58
95-th percentile-47
Maximum-17
Range89
Interquartile range (IQR)30

Descriptive statistics

Standard deviation16.54538671
Coefficient of variation (CV)-0.2223553535
Kurtosis-1.054678076
Mean-74.40966205
Median Absolute Deviation (MAD)12
Skewness0.4299090471
Sum-16711666
Variance273.7498214
MonotonicityNot monotonic
2024-11-22T14:01:46.611455image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-80 7213
 
3.2%
-82 7006
 
3.1%
-83 6912
 
3.1%
-90 6691
 
3.0%
-91 6662
 
3.0%
-56 6489
 
2.9%
-92 6457
 
2.9%
-88 6390
 
2.8%
-84 6353
 
2.8%
-78 6125
 
2.7%
Other values (78) 158292
70.5%
ValueCountFrequency (%)
-106 19
 
< 0.1%
-105 40
 
< 0.1%
-104 66
 
< 0.1%
-103 71
 
< 0.1%
-102 339
0.2%
ValueCountFrequency (%)
-17 6
 
< 0.1%
-18 20
< 0.1%
-19 17
< 0.1%
-20 13
< 0.1%
-21 1
 
< 0.1%

type
Text

the type of bluetooth device {normal, low-energy}

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.0 MiB
2024-11-22T14:01:46.677296image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.417338261
Min length1

Characters and Unicode

Total characters318320
Distinct characters3
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 rowle
2nd rown
3rd rown
4th rown
5th rowle
ValueCountFrequency (%)
n 130860
58.3%
le 93730
41.7%
2024-11-22T14:01:46.845762image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 130860
41.1%
l 93730
29.4%
e 93730
29.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 318320
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 130860
41.1%
l 93730
29.4%
e 93730
29.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 318320
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 130860
41.1%
l 93730
29.4%
e 93730
29.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 318320
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 130860
41.1%
l 93730
29.4%
e 93730
29.4%

Correlations

2024-11-22T14:01:46.919060image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
rssiuserid
rssi1.000-0.246
userid-0.2461.000