Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory752.0 KiB
Average record size in memory77.0 B

Variable types

Categorical4
Text1
Numeric2
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15962/S/1/datasetView.do

Alerts

기관 명 has constant value ""Constant
모델명 has constant value ""Constant
전원상태(꺼짐:0, 켜짐 :1) has constant value ""Constant
사용전력(W) has 4680 (46.8%) zerosZeros

Reproduction

Analysis started2024-05-04 00:23:37.295475
Analysis finished2024-05-04 00:23:40.528382
Duration3.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양천구
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양천구
2nd row양천구
3rd row양천구
4th row양천구
5th row양천구

Common Values

ValueCountFrequency (%)
양천구 10000
100.0%

Length

2024-05-04T00:23:40.682244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:23:40.882115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 10000
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
340
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row340
2nd row340
3rd row340
4th row340
5th row340

Common Values

ValueCountFrequency (%)
340 10000
100.0%

Length

2024-05-04T00:23:41.101650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:23:41.345082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
340 10000
100.0%

시리얼
Text

Distinct73
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T00:23:41.796008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters100000
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

Unique0 ?
Unique (%)0.0%

Sample

1st row965fedf79d
2nd rowd7540f6457
3rd rowe1ba1dbe08
4th row6a309a539d
5th row1ee5a7ada7
ValueCountFrequency (%)
e1ba1dbe08 2204
 
22.0%
de28c29733 582
 
5.8%
ba77c59645 321
 
3.2%
08ccb88d44 269
 
2.7%
c11fce50b9 174
 
1.7%
7540803cd5 155
 
1.6%
f530a70d3a 155
 
1.6%
6a309a539d 154
 
1.5%
ea961e3698 141
 
1.4%
4c1da7fd41 141
 
1.4%
Other values (63) 5704
57.0%
2024-05-04T00:23:42.838479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
b 9015
 
9.0%
e 8771
 
8.8%
1 8123
 
8.1%
8 7906
 
7.9%
d 7820
 
7.8%
a 7429
 
7.4%
7 6323
 
6.3%
0 6243
 
6.2%
5 5627
 
5.6%
3 5527
 
5.5%
Other values (6) 27216
27.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58490
58.5%
Lowercase Letter 41510
41.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8123
13.9%
8 7906
13.5%
7 6323
10.8%
0 6243
10.7%
5 5627
9.6%
3 5527
9.4%
2 5428
9.3%
9 5179
8.9%
6 4119
7.0%
4 4015
6.9%
Lowercase Letter
ValueCountFrequency (%)
b 9015
21.7%
e 8771
21.1%
d 7820
18.8%
a 7429
17.9%
c 4800
11.6%
f 3675
8.9%

Most occurring scripts

ValueCountFrequency (%)
Common 58490
58.5%
Latin 41510
41.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8123
13.9%
8 7906
13.5%
7 6323
10.8%
0 6243
10.7%
5 5627
9.6%
3 5527
9.4%
2 5428
9.3%
9 5179
8.9%
6 4119
7.0%
4 4015
6.9%
Latin
ValueCountFrequency (%)
b 9015
21.7%
e 8771
21.1%
d 7820
18.8%
a 7429
17.9%
c 4800
11.6%
f 3675
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
b 9015
 
9.0%
e 8771
 
8.8%
1 8123
 
8.1%
8 7906
 
7.9%
d 7820
 
7.8%
a 7429
 
7.4%
7 6323
 
6.3%
0 6243
 
6.2%
5 5627
 
5.6%
3 5527
 
5.5%
Other values (6) 27216
27.2%

가동유무
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5401 
1
4599 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 5401
54.0%
1 4599
46.0%

Length

2024-05-04T00:23:43.216326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:23:43.429868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5401
54.0%
1 4599
46.0%

사용전력(W)
Real number (ℝ)

ZEROS 

Distinct245
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.4071
Minimum0
Maximum1665
Zeros4680
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:23:43.728273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q331
95-th percentile86
Maximum1665
Range1665
Interquartile range (IQR)31

Descriptive statistics

Standard deviation74.413057
Coefficient of variation (CV)2.8179186
Kurtosis148.75904
Mean26.4071
Median Absolute Deviation (MAD)1
Skewness10.461698
Sum264071
Variance5537.3031
MonotonicityNot monotonic
2024-05-04T00:23:44.163042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4680
46.8%
1 380
 
3.8%
6 312
 
3.1%
30 213
 
2.1%
15 193
 
1.9%
64 187
 
1.9%
13 180
 
1.8%
29 171
 
1.7%
28 168
 
1.7%
63 163
 
1.6%
Other values (235) 3353
33.5%
ValueCountFrequency (%)
0 4680
46.8%
1 380
 
3.8%
2 29
 
0.3%
3 101
 
1.0%
4 20
 
0.2%
5 51
 
0.5%
6 312
 
3.1%
7 22
 
0.2%
8 68
 
0.7%
9 70
 
0.7%
ValueCountFrequency (%)
1665 1
< 0.1%
1420 1
< 0.1%
1326 1
< 0.1%
1315 1
< 0.1%
1241 1
< 0.1%
1228 1
< 0.1%
1215 1
< 0.1%
1213 1
< 0.1%
1212 1
< 0.1%
1053 1
< 0.1%

빛의밝기(%)
Real number (ℝ)

Distinct61
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.8185
Minimum20
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:23:44.585933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q120
median20
Q324
95-th percentile39
Maximum88
Range68
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.5052642
Coefficient of variation (CV)0.3151023
Kurtosis12.044786
Mean23.8185
Median Absolute Deviation (MAD)0
Skewness3.1301361
Sum238185
Variance56.328991
MonotonicityNot monotonic
2024-05-04T00:23:45.046131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 5194
51.9%
21 905
 
9.0%
22 714
 
7.1%
23 583
 
5.8%
24 370
 
3.7%
25 214
 
2.1%
28 199
 
2.0%
29 185
 
1.8%
30 166
 
1.7%
27 141
 
1.4%
Other values (51) 1329
 
13.3%
ValueCountFrequency (%)
20 5194
51.9%
21 905
 
9.0%
22 714
 
7.1%
23 583
 
5.8%
24 370
 
3.7%
25 214
 
2.1%
26 129
 
1.3%
27 141
 
1.4%
28 199
 
2.0%
29 185
 
1.8%
ValueCountFrequency (%)
88 2
< 0.1%
85 1
 
< 0.1%
82 2
< 0.1%
81 1
 
< 0.1%
80 2
< 0.1%
77 1
 
< 0.1%
76 1
 
< 0.1%
75 2
< 0.1%
73 1
 
< 0.1%
72 4
< 0.1%

전원상태(꺼짐:0, 켜짐 :1)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2024-05-04T00:23:45.481754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:23:45.754086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

등록일자
Date

Distinct9893
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-29 00:00:27
Maximum2024-02-04 23:55:10
2024-05-04T00:23:46.010872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:23:46.396982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-04T00:23:39.074267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:23:38.481014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:23:39.363831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:23:38.755998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T00:23:46.661038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼가동유무사용전력(W)빛의밝기(%)
시리얼1.0000.6840.6370.674
가동유무0.6841.0000.1600.147
사용전력(W)0.6370.1601.0000.000
빛의밝기(%)0.6740.1470.0001.000
2024-05-04T00:23:46.931223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용전력(W)빛의밝기(%)가동유무
사용전력(W)1.0000.0690.160
빛의밝기(%)0.0691.0000.112
가동유무0.1600.1121.000

Missing values

2024-05-04T00:23:39.756524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T00:23:40.362825image/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

기관 명모델명시리얼가동유무사용전력(W)빛의밝기(%)전원상태(꺼짐:0, 켜짐 :1)등록일자
3731양천구340965fedf79d002012024-01-30 04:26:09
30양천구340d7540f64571342112024-01-29 00:11:20
6092양천구340e1ba1dbe081622012024-01-30 21:55:55
18115양천구3406a309a539d1292912024-02-03 13:32:16
14557양천구3401ee5a7ada7002112024-02-02 11:59:49
839양천구340f530a70d3a1712012024-01-29 05:57:03
3386양천구3409157ecd23d1212812024-01-30 00:36:02
12736양천구340e1ba1dbe08102012024-02-01 23:06:35
22282양천구3406223f89d8311002012024-02-04 22:02:40
6248양천구34005d372d93711252012024-01-30 23:03:57
기관 명모델명시리얼가동유무사용전력(W)빛의밝기(%)전원상태(꺼짐:0, 켜짐 :1)등록일자
12967양천구340a8080bd747002212024-02-02 00:37:34
21770양천구340876329b576002012024-02-04 17:55:57
2163양천구340ba77c596451234312024-01-29 14:01:42
6191양천구340477c381236003512024-01-30 22:37:14
19159양천구340d7540f64571332112024-02-03 21:25:18
7181양천구3405d2ce46157002012024-01-31 05:54:22
20964양천구3404c1da7fd41002512024-02-04 11:46:33
8722양천구340f530a70d3a002112024-01-31 17:57:47
11749양천구3407540803cd51252012024-02-01 15:50:03
4064양천구34011c90618b21922412024-01-30 07:30:35