Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory52.3 B

Variable types

Text2
Categorical1
Numeric3

Alerts

기록 시각 has constant value ""Constant
로그 아이디 has unique valuesUnique
건물 아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-10 11:14:10.567359
Analysis finished2023-12-10 11:14:12.638157
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

로그 아이디
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:14:12.864436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters2400
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row6155e1699f32ea1a57ce45b7
2nd row6155e1699f32ea1a57ce45b8
3rd row6155e1699f32ea1a57ce45b9
4th row6155e1699f32ea1a57ce45ba
5th row6155e1699f32ea1a57ce45bb
ValueCountFrequency (%)
6155e1699f32ea1a57ce45b7 1
 
1.0%
6155e1699f32ea1a57ce45f5 1
 
1.0%
6155e1699f32ea1a57ce4600 1
 
1.0%
6155e1699f32ea1a57ce45ff 1
 
1.0%
6155e1699f32ea1a57ce45fe 1
 
1.0%
6155e1699f32ea1a57ce45fd 1
 
1.0%
6155e1699f32ea1a57ce45fc 1
 
1.0%
6155e1699f32ea1a57ce45fb 1
 
1.0%
6155e1699f32ea1a57ce45fa 1
 
1.0%
6155e1699f32ea1a57ce45f9 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T20:14:13.802095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 379
15.8%
e 322
13.4%
1 317
13.2%
6 233
9.7%
9 207
8.6%
a 207
8.6%
f 122
 
5.1%
c 122
 
5.1%
7 107
 
4.5%
3 106
 
4.4%
Other values (6) 278
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1590
66.2%
Lowercase Letter 810
33.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 379
23.8%
1 317
19.9%
6 233
14.7%
9 207
13.0%
7 107
 
6.7%
3 106
 
6.7%
2 106
 
6.7%
4 106
 
6.7%
0 22
 
1.4%
8 7
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 322
39.8%
a 207
25.6%
f 122
 
15.1%
c 122
 
15.1%
d 22
 
2.7%
b 15
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1590
66.2%
Latin 810
33.8%

Most frequent character per script

Common
ValueCountFrequency (%)
5 379
23.8%
1 317
19.9%
6 233
14.7%
9 207
13.0%
7 107
 
6.7%
3 106
 
6.7%
2 106
 
6.7%
4 106
 
6.7%
0 22
 
1.4%
8 7
 
0.4%
Latin
ValueCountFrequency (%)
e 322
39.8%
a 207
25.6%
f 122
 
15.1%
c 122
 
15.1%
d 22
 
2.7%
b 15
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 379
15.8%
e 322
13.4%
1 317
13.2%
6 233
9.7%
9 207
8.6%
a 207
8.6%
f 122
 
5.1%
c 122
 
5.1%
7 107
 
4.5%
3 106
 
4.4%
Other values (6) 278
11.6%

건물 아이디
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:14:14.291512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters2400
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row5f06a499153b58ec1eb3ea49
2nd row5f06a446153b58ec1eb3ea43
3rd row5f067dd8153b58ec1eb3ea12
4th row5f9b770dad60bb243eaf3f27
5th row5fb20d634bb08a560c7449e8
ValueCountFrequency (%)
5f06a499153b58ec1eb3ea49 1
 
1.0%
5ffea7fcb25c2071dcef8e71 1
 
1.0%
5f4eeeaf706250145618bb53 1
 
1.0%
5ffc21af500f896cb3d358d8 1
 
1.0%
5ffc214a500f896cb3d3546a 1
 
1.0%
5ffc15dae0a2b843dc461687 1
 
1.0%
5ffe6b79b25c2071dced04f1 1
 
1.0%
5f71604039518d7393361fa3 1
 
1.0%
5f06a21a153b58ec1eb3ea2d 1
 
1.0%
5ffea271b25c2071dcef52ec 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T20:14:14.880815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 260
 
10.8%
f 237
 
9.9%
e 210
 
8.8%
c 170
 
7.1%
1 161
 
6.7%
2 154
 
6.4%
b 150
 
6.2%
0 142
 
5.9%
3 134
 
5.6%
a 126
 
5.2%
Other values (6) 656
27.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1386
57.8%
Lowercase Letter 1014
42.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 260
18.8%
1 161
11.6%
2 154
11.1%
0 142
10.2%
3 134
9.7%
6 124
8.9%
8 117
8.4%
7 113
8.2%
4 95
 
6.9%
9 86
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
f 237
23.4%
e 210
20.7%
c 170
16.8%
b 150
14.8%
a 126
12.4%
d 121
11.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1386
57.8%
Latin 1014
42.2%

Most frequent character per script

Common
ValueCountFrequency (%)
5 260
18.8%
1 161
11.6%
2 154
11.1%
0 142
10.2%
3 134
9.7%
6 124
8.9%
8 117
8.4%
7 113
8.2%
4 95
 
6.9%
9 86
 
6.2%
Latin
ValueCountFrequency (%)
f 237
23.4%
e 210
20.7%
c 170
16.8%
b 150
14.8%
a 126
12.4%
d 121
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 260
 
10.8%
f 237
 
9.9%
e 210
 
8.8%
c 170
 
7.1%
1 161
 
6.7%
2 154
 
6.4%
b 150
 
6.2%
0 142
 
5.9%
3 134
 
5.6%
a 126
 
5.2%
Other values (6) 656
27.3%

기록 시각
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)
100 

Length

Max length56
Median length56
Mean length56
Min length56

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)
2nd rowFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)
3rd rowFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)
4th rowFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)
5th rowFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)

Common Values

ValueCountFrequency (%)
Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time) 100
100.0%

Length

2023-12-10T20:14:15.120101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:14:15.289819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
fri 100
11.1%
oct 100
11.1%
01 100
11.1%
2021 100
11.1%
01:10:15 100
11.1%
gmt+0900 100
11.1%
korean 100
11.1%
standard 100
11.1%
time 100
11.1%

온도(℃)
Real number (ℝ)

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.577
Minimum14.7
Maximum20.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:14:15.475559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.7
5-th percentile15.79
Q116.525
median17.9
Q318.4
95-th percentile18.9
Maximum20.9
Range6.2
Interquartile range (IQR)1.875

Descriptive statistics

Standard deviation1.1748075
Coefficient of variation (CV)0.066837773
Kurtosis0.33530189
Mean17.577
Median Absolute Deviation (MAD)0.7
Skewness-0.22214362
Sum1757.7
Variance1.3801727
MonotonicityNot monotonic
2023-12-10T20:14:15.705775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
18.7 16
16.0%
17.9 15
15.0%
16.3 11
11.0%
17.4 9
9.0%
18.4 9
9.0%
15.8 6
 
6.0%
17.6 6
 
6.0%
17.2 5
 
5.0%
16.2 3
 
3.0%
18.9 3
 
3.0%
Other values (12) 17
17.0%
ValueCountFrequency (%)
14.7 2
 
2.0%
15.0 1
 
1.0%
15.4 1
 
1.0%
15.6 1
 
1.0%
15.8 6
6.0%
16.2 3
 
3.0%
16.3 11
11.0%
16.6 1
 
1.0%
17.1 1
 
1.0%
17.2 5
5.0%
ValueCountFrequency (%)
20.9 2
 
2.0%
19.0 1
 
1.0%
18.9 3
 
3.0%
18.7 16
16.0%
18.5 2
 
2.0%
18.4 9
9.0%
18.2 2
 
2.0%
18.0 2
 
2.0%
17.9 15
15.0%
17.6 6
 
6.0%

습도(%)
Real number (ℝ)

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.49
Minimum80
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:14:15.926985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile85
Q188
median97
Q3100
95-th percentile100
Maximum100
Range20
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.1109192
Coefficient of variation (CV)0.064672655
Kurtosis-0.98375588
Mean94.49
Median Absolute Deviation (MAD)3
Skewness-0.6630185
Sum9449
Variance37.343333
MonotonicityNot monotonic
2023-12-10T20:14:16.138973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
100 42
42.0%
87 15
 
15.0%
97 14
 
14.0%
92 8
 
8.0%
88 8
 
8.0%
85 5
 
5.0%
95 3
 
3.0%
80 3
 
3.0%
98 2
 
2.0%
ValueCountFrequency (%)
80 3
 
3.0%
85 5
 
5.0%
87 15
 
15.0%
88 8
 
8.0%
92 8
 
8.0%
95 3
 
3.0%
97 14
 
14.0%
98 2
 
2.0%
100 42
42.0%
ValueCountFrequency (%)
100 42
42.0%
98 2
 
2.0%
97 14
 
14.0%
95 3
 
3.0%
92 8
 
8.0%
88 8
 
8.0%
87 15
 
15.0%
85 5
 
5.0%
80 3
 
3.0%

초미세먼지
Real number (ℝ)

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.08
Minimum34
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:14:16.386694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile50
Q157
median63
Q368
95-th percentile70
Maximum78
Range44
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.5340037
Coefficient of variation (CV)0.12334649
Kurtosis1.3701401
Mean61.08
Median Absolute Deviation (MAD)5
Skewness-0.67165576
Sum6108
Variance56.761212
MonotonicityNot monotonic
2023-12-10T20:14:16.607177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
63 20
20.0%
68 17
17.0%
50 10
10.0%
57 9
9.0%
59 9
9.0%
61 8
 
8.0%
55 8
 
8.0%
70 6
 
6.0%
65 5
 
5.0%
78 2
 
2.0%
Other values (5) 6
 
6.0%
ValueCountFrequency (%)
34 1
 
1.0%
38 1
 
1.0%
46 1
 
1.0%
50 10
10.0%
53 1
 
1.0%
55 8
 
8.0%
57 9
9.0%
59 9
9.0%
61 8
 
8.0%
63 20
20.0%
ValueCountFrequency (%)
78 2
 
2.0%
74 2
 
2.0%
70 6
 
6.0%
68 17
17.0%
65 5
 
5.0%
63 20
20.0%
61 8
 
8.0%
59 9
9.0%
57 9
9.0%
55 8
 
8.0%

Interactions

2023-12-10T20:14:11.846406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:10.862893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:11.334828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:11.994249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:11.023199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:11.512919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:12.157636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:11.193880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:14:11.702172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:14:16.756132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
로그 아이디건물 아이디온도(℃)습도(%)초미세먼지
로그 아이디1.0001.0001.0001.0001.000
건물 아이디1.0001.0001.0001.0001.000
온도(℃)1.0001.0001.0000.8490.626
습도(%)1.0001.0000.8491.0000.550
초미세먼지1.0001.0000.6260.5501.000
2023-12-10T20:14:16.937879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도(℃)습도(%)초미세먼지
온도(℃)1.000-0.4170.237
습도(%)-0.4171.000-0.070
초미세먼지0.237-0.0701.000

Missing values

2023-12-10T20:14:12.371589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:14:12.557493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

로그 아이디건물 아이디기록 시각온도(℃)습도(%)초미세먼지
06155e1699f32ea1a57ce45b75f06a499153b58ec1eb3ea49Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)17.48750
16155e1699f32ea1a57ce45b85f06a446153b58ec1eb3ea43Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)17.48761
26155e1699f32ea1a57ce45b95f067dd8153b58ec1eb3ea12Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)17.910068
36155e1699f32ea1a57ce45ba5f9b770dad60bb243eaf3f27Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)17.910055
46155e1699f32ea1a57ce45bb5fb20d634bb08a560c7449e8Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)17.910063
56155e1699f32ea1a57ce45bc5fdc725569ca2f1f694226faFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)17.910063
66155e1699f32ea1a57ce45bd5f069fed153b58ec1eb3ea1bFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.09834
76155e1699f32ea1a57ce45be5face271d52acb7050ff5e8fFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)14.710057
86155e1699f32ea1a57ce45bf5ff977023f92d8153a1f16fcFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.610070
96155e1699f32ea1a57ce45c05ffc1596e0a2b843dc4613a7Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)18.410068
로그 아이디건물 아이디기록 시각온도(℃)습도(%)초미세먼지
906155e1699f32ea1a57ce46115f06a24e153b58ec1eb3ea2fFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)18.78065
916155e1699f32ea1a57ce46125f72eaa739518d7393361fdeFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)18.78070
926155e1699f32ea1a57ce46135fa0d0a57ef5ae3a1c0fc8bcFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.810057
936155e1699f32ea1a57ce46145fae4053df2f284b96e468e1Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)18.78074
946155e1699f32ea1a57ce46155ffc1863e0a2b843dc4631d9Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.810057
956155e1699f32ea1a57ce46165ffc1922e0a2b843dc4639a9Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.810057
966155e1699f32ea1a57ce46175ffc1897e0a2b843dc4633e8Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.810057
976155e1699f32ea1a57ce46185ffe6963b25c2071dcecef2dFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)15.810057
986155e1699f32ea1a57ce4619600e4d9a871aeb705049561eFri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)16.210059
996155e1699f32ea1a57ce461a5f6d516339518d7393361f85Fri Oct 01 2021 01:10:15 GMT+0900 (Korean Standard Time)19.010074