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 4910 (49.1%) zerosZeros

Reproduction

Analysis started2024-05-04 00:24:00.549640
Analysis finished2024-05-04 00:24:03.287562
Duration2.74 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

2024-05-04T00:24:03.494894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:24:03.811467image/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

2024-05-04T00:24:04.160293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:24:04.483258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
340 10000
100.0%

시리얼
Text

Distinct69
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T00:24:05.015581image/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 row3982bd51c7
2nd rowa8080bd747
3rd row22fe865822
4th row2de72cfce9
5th rowe1ba1dbe08
ValueCountFrequency (%)
e1ba1dbe08 2403
24.0%
de28c29733 562
 
5.6%
ba77c59645 290
 
2.9%
08ccb88d44 284
 
2.8%
a8080bd747 214
 
2.1%
c11fce50b9 185
 
1.8%
6a309a539d 157
 
1.6%
7540803cd5 157
 
1.6%
ea961e3698 151
 
1.5%
7abcf2427a 149
 
1.5%
Other values (59) 5448
54.5%
2024-05-04T00:24:06.094672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
b 9517
 
9.5%
e 9043
 
9.0%
1 8481
 
8.5%
8 8064
 
8.1%
d 7873
 
7.9%
a 7627
 
7.6%
0 6534
 
6.5%
7 5984
 
6.0%
3 5408
 
5.4%
5 5381
 
5.4%
Other values (6) 26088
26.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57706
57.7%
Lowercase Letter 42294
42.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8481
14.7%
8 8064
14.0%
0 6534
11.3%
7 5984
10.4%
3 5408
9.4%
5 5381
9.3%
2 5218
9.0%
9 4883
8.5%
6 3999
6.9%
4 3754
6.5%
Lowercase Letter
ValueCountFrequency (%)
b 9517
22.5%
e 9043
21.4%
d 7873
18.6%
a 7627
18.0%
c 4699
11.1%
f 3535
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
Common 57706
57.7%
Latin 42294
42.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8481
14.7%
8 8064
14.0%
0 6534
11.3%
7 5984
10.4%
3 5408
9.4%
5 5381
9.3%
2 5218
9.0%
9 4883
8.5%
6 3999
6.9%
4 3754
6.5%
Latin
ValueCountFrequency (%)
b 9517
22.5%
e 9043
21.4%
d 7873
18.6%
a 7627
18.0%
c 4699
11.1%
f 3535
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
b 9517
 
9.5%
e 9043
 
9.0%
1 8481
 
8.5%
8 8064
 
8.1%
d 7873
 
7.9%
a 7627
 
7.6%
0 6534
 
6.5%
7 5984
 
6.0%
3 5408
 
5.4%
5 5381
 
5.4%
Other values (6) 26088
26.1%

가동유무
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5287 
1
4713 

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 5287
52.9%
1 4713
47.1%

Length

2024-05-04T00:24:06.485834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:24:06.788232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5287
52.9%
1 4713
47.1%

사용전력(W)
Real number (ℝ)

ZEROS 

Distinct240
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.4614
Minimum0
Maximum3280
Zeros4910
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:24:07.146755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q332
95-th percentile85
Maximum3280
Range3280
Interquartile range (IQR)32

Descriptive statistics

Standard deviation95.610758
Coefficient of variation (CV)3.3593132
Kurtosis243.54711
Mean28.4614
Median Absolute Deviation (MAD)1
Skewness12.922628
Sum284614
Variance9141.4171
MonotonicityNot monotonic
2024-05-04T00:24:07.734780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4910
49.1%
63 239
 
2.4%
4 231
 
2.3%
6 215
 
2.1%
30 202
 
2.0%
9 186
 
1.9%
13 179
 
1.8%
64 178
 
1.8%
32 172
 
1.7%
33 167
 
1.7%
Other values (230) 3321
33.2%
ValueCountFrequency (%)
0 4910
49.1%
1 132
 
1.3%
2 33
 
0.3%
3 81
 
0.8%
4 231
 
2.3%
5 3
 
< 0.1%
6 215
 
2.1%
7 14
 
0.1%
8 14
 
0.1%
9 186
 
1.9%
ValueCountFrequency (%)
3280 1
< 0.1%
1656 1
< 0.1%
1635 1
< 0.1%
1631 1
< 0.1%
1433 1
< 0.1%
1430 2
< 0.1%
1420 1
< 0.1%
1253 2
< 0.1%
1251 1
< 0.1%
1249 1
< 0.1%

빛의밝기(%)
Real number (ℝ)

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.7137
Minimum20
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:24:08.514827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q120
median20
Q323
95-th percentile35
Maximum68
Range48
Interquartile range (IQR)3

Descriptive statistics

Standard deviation5.4555209
Coefficient of variation (CV)0.24018636
Kurtosis10.76003
Mean22.7137
Median Absolute Deviation (MAD)0
Skewness2.9996087
Sum227137
Variance29.762709
MonotonicityNot monotonic
2024-05-04T00:24:09.082911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
20 5678
56.8%
21 1044
 
10.4%
22 639
 
6.4%
23 522
 
5.2%
24 394
 
3.9%
25 197
 
2.0%
29 184
 
1.8%
34 129
 
1.3%
26 126
 
1.3%
28 123
 
1.2%
Other values (37) 964
 
9.6%
ValueCountFrequency (%)
20 5678
56.8%
21 1044
 
10.4%
22 639
 
6.4%
23 522
 
5.2%
24 394
 
3.9%
25 197
 
2.0%
26 126
 
1.3%
27 116
 
1.2%
28 123
 
1.2%
29 184
 
1.8%
ValueCountFrequency (%)
68 1
 
< 0.1%
67 1
 
< 0.1%
66 1
 
< 0.1%
65 1
 
< 0.1%
64 1
 
< 0.1%
63 1
 
< 0.1%
62 3
< 0.1%
61 1
 
< 0.1%
59 1
 
< 0.1%
58 2
< 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

2024-05-04T00:24:09.689862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:24:10.101329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

등록일자
Date

Distinct9765
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-02-05 00:00:03
Maximum2024-02-07 23:59:51
2024-05-04T00:24:10.712768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:24:11.354653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-04T00:24:01.767522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:24:01.174433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:24:02.055980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:24:01.397676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T00:24:11.640647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼가동유무사용전력(W)빛의밝기(%)
시리얼1.0000.6460.4650.767
가동유무0.6461.0000.0770.142
사용전력(W)0.4650.0771.0000.007
빛의밝기(%)0.7670.1420.0071.000
2024-05-04T00:24:12.012303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용전력(W)빛의밝기(%)가동유무
사용전력(W)1.0000.1290.082
빛의밝기(%)0.1291.0000.109
가동유무0.0820.1091.000

Missing values

2024-05-04T00:24:02.433832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T00:24:03.078948image/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
157양천구3403982bd51c7002012024-02-05 01:21:10
7719양천구340a8080bd7471322712024-02-07 07:27:53
7318양천구34022fe8658221273512024-02-07 04:42:34
1622양천구3402de72cfce91523012024-02-05 12:04:59
3275양천구340e1ba1dbe08002012024-02-05 23:32:17
1495양천구34005d372d9371252012024-02-05 11:06:53
3486양천구3402de72cfce91322712024-02-06 01:04:53
4317양천구340e1ba1dbe08092012024-02-06 07:30:43
9593양천구3403e9552ff861152012024-02-07 20:33:49
5072양천구3406a309a539d1302912024-02-06 12:25:57
기관 명모델명시리얼가동유무사용전력(W)빛의밝기(%)전원상태(꺼짐:0, 켜짐 :1)등록일자
8066양천구340de28c29733063912024-02-07 09:37:11
802양천구340ba77c596450302012024-02-05 06:03:50
554양천구34085b819453c002012024-02-05 04:16:37
6998양천구340cfdbc88efd002012024-02-07 02:29:04
6618양천구3402747b2b764002012024-02-06 23:44:13
9944양천구340f530a70d3a1692012024-02-07 22:56:34
4134양천구3409157ecd23d1172912024-02-06 06:09:49
1211양천구34008ccb88d441292112024-02-05 08:59:09
1968양천구3402fa95a6fe2002812024-02-05 14:42:02
209양천구340e1ba1dbe08102012024-02-05 01:43:55