Overview

Dataset statistics

Number of variables4
Number of observations7101410
Missing cells0
Missing cells (%)0.0%
Total size in memory291.2 MiB
Average record size in memory43.0 B

Variable types

Text1
Numeric1
DateTime1
Boolean1

Dataset

Description[unitless] Sensor that detects when the user is present. An example is when the user unlocks the screen. This sensor can be used in comparison to Screen status to check if the screen turn on event occurred due to the user or, for example, due to a received notification. The event user present OFF is simply when the screen turns off. 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)
statusReturn if the user is present or not

Alerts

experimentid has constant value "wenetItaly"Constant

Reproduction

Analysis started2024-11-23 05:56:42.112610
Analysis finished2024-11-23 05:57:04.368653
Duration22.26 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 size176.1 MiB
2024-11-23T06:57:04.470377image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters71014100
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 7101410
100.0%
2024-11-23T06:57:04.667656image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14202820
20.0%
t 14202820
20.0%
w 7101410
10.0%
n 7101410
10.0%
I 7101410
10.0%
a 7101410
10.0%
l 7101410
10.0%
y 7101410
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 71014100
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 14202820
20.0%
t 14202820
20.0%
w 7101410
10.0%
n 7101410
10.0%
I 7101410
10.0%
a 7101410
10.0%
l 7101410
10.0%
y 7101410
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 71014100
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 14202820
20.0%
t 14202820
20.0%
w 7101410
10.0%
n 7101410
10.0%
I 7101410
10.0%
a 7101410
10.0%
l 7101410
10.0%
y 7101410
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 71014100
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 14202820
20.0%
t 14202820
20.0%
w 7101410
10.0%
n 7101410
10.0%
I 7101410
10.0%
a 7101410
10.0%
l 7101410
10.0%
y 7101410
10.0%

userid
Real number (ℝ)

User id

Distinct221
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.8959249
Minimum0
Maximum265
Zeros4726
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size108.4 MiB
2024-11-23T06:57:04.787589image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q158
median118
Q3204
95-th percentile255
Maximum265
Range265
Interquartile range (IQR)146

Descriptive statistics

Standard deviation79.38368609
Coefficient of variation (CV)0.6018661013
Kurtosis-1.243176789
Mean131.8959249
Median Absolute Deviation (MAD)72
Skewness0.0718602361
Sum936647040
Variance6301.769617
MonotonicityIncreasing
2024-11-23T06:57:04.909951image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111 345648
 
4.9%
57 209006
 
2.9%
118 181494
 
2.6%
245 172048
 
2.4%
175 166063
 
2.3%
217 164905
 
2.3%
258 162598
 
2.3%
103 153235
 
2.2%
75 140003
 
2.0%
112 130958
 
1.8%
Other values (211) 5275452
74.3%
ValueCountFrequency (%)
0 4726
 
0.1%
1 35578
0.5%
2 28775
0.4%
3 28083
0.4%
4 10418
 
0.1%
ValueCountFrequency (%)
265 39517
0.6%
264 623
 
< 0.1%
263 21113
0.3%
262 15776
 
0.2%
260 623
 
< 0.1%

timestamp
Date

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

Distinct7085247
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size108.4 MiB
Minimum2020-11-16 07:00:00.192000
Maximum2020-12-11 21:59:51.161000
2024-11-23T06:57:05.033327image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-11-23T06:57:05.154634image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

status
Boolean

Return if the user is present or not

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.0 MiB
False
6102935 
True
998475 
ValueCountFrequency (%)
False 6102935
85.9%
True 998475
 
14.1%
2024-11-23T06:57:05.246140image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-11-23T06:57:05.298687image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
statususerid
status1.000-0.005
userid-0.0051.000