Overview

Dataset statistics

Number of variables5
Number of observations187
Missing cells25
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory40.7 B

Variable types

Categorical2
Text2
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21723/S/1/datasetView.do

Alerts

소재지 has 25 (13.4%) missing valuesMissing

Reproduction

Analysis started2024-04-29 21:10:54.709498
Analysis finished2024-04-29 21:10:55.610168
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct25
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
성동구
20 
강서구
19 
송파구
19 
영등포구
14 
금천구
12 
Other values (20)
103 

Length

Max length4
Median length3
Mean length3.0855615
Min length2

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
성동구 20
 
10.7%
강서구 19
 
10.2%
송파구 19
 
10.2%
영등포구 14
 
7.5%
금천구 12
 
6.4%
서초구 10
 
5.3%
종로구 9
 
4.8%
도봉구 8
 
4.3%
구로구 8
 
4.3%
강동구 8
 
4.3%
Other values (15) 60
32.1%

Length

2024-04-30T06:10:55.678103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성동구 20
 
10.7%
송파구 19
 
10.2%
강서구 19
 
10.2%
영등포구 14
 
7.5%
금천구 12
 
6.4%
서초구 10
 
5.3%
종로구 9
 
4.8%
도봉구 8
 
4.3%
구로구 8
 
4.3%
강동구 8
 
4.3%
Other values (15) 60
32.1%

사업장명
Text

Distinct171
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T06:10:55.895530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length8.5187166
Min length3

Characters and Unicode

Total characters1593
Distinct characters307
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)82.9%

Sample

1st row아쎈다스오피스사모부동산투자신탁1호
2nd row디더블유에스오피스제2호사모부동산투자신탁
3rd row(주)청솔트러스트
4th row(주)효성주얼리시티쇼핑몰
5th row주식회사 국일관드림펠리스총관리단
ValueCountFrequency (%)
주식회사 5
 
2.2%
주)강동모터스 2
 
0.9%
닥터카랜드 2
 
0.9%
주)워시스왓 2
 
0.9%
매직터치 2
 
0.9%
문화자동차공업사 2
 
0.9%
민우전자부품 2
 
0.9%
제이에스모터스 2
 
0.9%
주)신세계도금 2
 
0.9%
로얄카공업사 2
 
0.9%
Other values (197) 207
90.0%
2024-04-30T06:10:56.245689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 66
 
4.1%
) 62
 
3.9%
( 61
 
3.8%
스 49
 
3.1%
동 48
 
3.0%
차 48
 
3.0%
43
 
2.7%
자 41
 
2.6%
사 38
 
2.4%
공 29
 
1.8%
Other values (297) 1108
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1357
85.2%
Close Punctuation 62
 
3.9%
Open Punctuation 61
 
3.8%
Space Separator 43
 
2.7%
Uppercase Letter 37
 
2.3%
Lowercase Letter 21
 
1.3%
Decimal Number 8
 
0.5%
Other Punctuation 2
 
0.1%
Other Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 66
 
4.9%
스 49
 
3.6%
동 48
 
3.5%
차 48
 
3.5%
자 41
 
3.0%
사 38
 
2.8%
공 29
 
2.1%
업 29
 
2.1%
터 25
 
1.8%
대 23
 
1.7%
Other values (254) 961
70.8%
Uppercase Letter
ValueCountFrequency (%)
J 4
 
10.8%
T 4
 
10.8%
C 3
 
8.1%
S 2
 
5.4%
B 2
 
5.4%
H 2
 
5.4%
E 2
 
5.4%
L 2
 
5.4%
A 2
 
5.4%
D 2
 
5.4%
Other values (12) 12
32.4%
Lowercase Letter
ValueCountFrequency (%)
s 3
14.3%
o 3
14.3%
k 2
9.5%
r 2
9.5%
h 2
9.5%
a 2
9.5%
t 2
9.5%
c 1
 
4.8%
y 1
 
4.8%
b 1
 
4.8%
Other values (2) 2
9.5%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
1 2
25.0%
4 2
25.0%
7 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Space Separator
ValueCountFrequency (%)
43
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1359
85.3%
Common 176
 
11.0%
Latin 58
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 66
 
4.9%
스 49
 
3.6%
동 48
 
3.5%
차 48
 
3.5%
자 41
 
3.0%
사 38
 
2.8%
공 29
 
2.1%
업 29
 
2.1%
터 25
 
1.8%
대 23
 
1.7%
Other values (255) 963
70.9%
Latin
ValueCountFrequency (%)
J 4
 
6.9%
T 4
 
6.9%
C 3
 
5.2%
s 3
 
5.2%
o 3
 
5.2%
S 2
 
3.4%
k 2
 
3.4%
r 2
 
3.4%
h 2
 
3.4%
a 2
 
3.4%
Other values (24) 31
53.4%
Common
ValueCountFrequency (%)
) 62
35.2%
( 61
34.7%
43
24.4%
2 3
 
1.7%
1 2
 
1.1%
& 2
 
1.1%
4 2
 
1.1%
7 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1357
85.2%
ASCII 234
 
14.7%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 66
 
4.9%
스 49
 
3.6%
동 48
 
3.5%
차 48
 
3.5%
자 41
 
3.0%
사 38
 
2.8%
공 29
 
2.1%
업 29
 
2.1%
터 25
 
1.8%
대 23
 
1.7%
Other values (254) 961
70.8%
ASCII
ValueCountFrequency (%)
) 62
26.5%
( 61
26.1%
43
18.4%
J 4
 
1.7%
T 4
 
1.7%
C 3
 
1.3%
s 3
 
1.3%
o 3
 
1.3%
2 3
 
1.3%
1 2
 
0.9%
Other values (32) 46
19.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지
Text

MISSING 

Distinct153
Distinct (%)94.4%
Missing25
Missing (%)13.4%
Memory size1.6 KiB
2024-04-30T06:10:56.583620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length21.716049
Min length13

Characters and Unicode

Total characters3518
Distinct characters182
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)88.9%

Sample

1st row서울특별시 종로구 무악동 66-3 골든팰리스
2nd row서울특별시 종로구 인의동 48-2번지 효성주얼리시티
3rd row서울특별시 종로구 관수동
4th row서울특별시 종로구 효제동 197-1번지
5th row서울특별시 종로구 종로5가 471
ValueCountFrequency (%)
서울특별시 162
 
23.5%
송파구 19
 
2.8%
강서구 17
 
2.5%
성동구 14
 
2.0%
금천구 12
 
1.7%
영등포구 12
 
1.7%
성수동2가 11
 
1.6%
독산동 9
 
1.3%
도봉구 8
 
1.2%
구로구 8
 
1.2%
Other values (289) 418
60.6%
2024-04-30T06:10:57.037685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
528
 
15.0%
서 192
 
5.5%
동 189
 
5.4%
구 178
 
5.1%
시 166
 
4.7%
특 162
 
4.6%
별 162
 
4.6%
울 162
 
4.6%
1 147
 
4.2%
- 141
 
4.0%
Other values (172) 1491
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2110
60.0%
Decimal Number 723
 
20.6%
Space Separator 528
 
15.0%
Dash Punctuation 141
 
4.0%
Uppercase Letter 5
 
0.1%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 192
 
9.1%
동 189
 
9.0%
구 178
 
8.4%
시 166
 
7.9%
특 162
 
7.7%
별 162
 
7.7%
울 162
 
7.7%
지 67
 
3.2%
번 60
 
2.8%
가 38
 
1.8%
Other values (152) 734
34.8%
Decimal Number
ValueCountFrequency (%)
1 147
20.3%
2 111
15.4%
9 74
10.2%
3 67
9.3%
0 63
8.7%
4 58
 
8.0%
7 56
 
7.7%
6 56
 
7.7%
5 48
 
6.6%
8 43
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
M 1
20.0%
G 1
20.0%
L 1
20.0%
D 1
20.0%
E 1
20.0%
Space Separator
ValueCountFrequency (%)
528
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2110
60.0%
Common 1403
39.9%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 192
 
9.1%
동 189
 
9.0%
구 178
 
8.4%
시 166
 
7.9%
특 162
 
7.7%
별 162
 
7.7%
울 162
 
7.7%
지 67
 
3.2%
번 60
 
2.8%
가 38
 
1.8%
Other values (152) 734
34.8%
Common
ValueCountFrequency (%)
528
37.6%
1 147
 
10.5%
- 141
 
10.0%
2 111
 
7.9%
9 74
 
5.3%
3 67
 
4.8%
0 63
 
4.5%
4 58
 
4.1%
7 56
 
4.0%
6 56
 
4.0%
Other values (5) 102
 
7.3%
Latin
ValueCountFrequency (%)
M 1
20.0%
G 1
20.0%
L 1
20.0%
D 1
20.0%
E 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2110
60.0%
ASCII 1408
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
528
37.5%
1 147
 
10.4%
- 141
 
10.0%
2 111
 
7.9%
9 74
 
5.3%
3 67
 
4.8%
0 63
 
4.5%
4 58
 
4.1%
7 56
 
4.0%
6 56
 
4.0%
Other values (10) 107
 
7.6%
Hangul
ValueCountFrequency (%)
서 192
 
9.1%
동 189
 
9.0%
구 178
 
8.4%
시 166
 
7.9%
특 162
 
7.7%
별 162
 
7.7%
울 162
 
7.7%
지 67
 
3.2%
번 60
 
2.8%
가 38
 
1.8%
Other values (152) 734
34.8%

업종
Categorical

Distinct42
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
45 
자동차 세차업
29 
자동차 수리 및 세차업
19 
자동차 수리업
17 
자동차 종합 수리업
14 
Other values (37)
63 

Length

Max length21
Median length18
Mean length7.8716578
Min length2

Unique

Unique24 ?
Unique (%)12.8%

Sample

1st row<NA>
2nd row부동산업
3rd row비주거용 건물 임대업
4th row부동산업
5th row부동산업

Common Values

ValueCountFrequency (%)
<NA> 45
24.1%
자동차 세차업 29
15.5%
자동차 수리 및 세차업 19
10.2%
자동차 수리업 17
 
9.1%
자동차 종합 수리업 14
 
7.5%
종합 병원 6
 
3.2%
출판, 인쇄 및 기록매체 복제업 6
 
3.2%
자동차 전문 수리업 3
 
1.6%
자동차 및 모터사이클 수리업 3
 
1.6%
도금업 3
 
1.6%
Other values (32) 42
22.5%

Length

2024-04-30T06:10:57.173312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차 85
19.5%
세차업 48
11.0%
na 45
 
10.3%
및 39
 
8.9%
수리업 37
 
8.5%
종합 21
 
4.8%
수리 19
 
4.4%
제조업 11
 
2.5%
기타 9
 
2.1%
병원 7
 
1.6%
Other values (63) 115
26.4%

점검일자
Date

Distinct113
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2019-06-20 00:00:00
Maximum2021-02-17 00:00:00
2024-04-30T06:10:57.282988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:57.408184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2024-04-30T06:10:57.482997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종
구분1.0000.768
업종0.7681.000
2024-04-30T06:10:57.558313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분
업종1.0000.253
구분0.2531.000
2024-04-30T06:10:57.620337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종
구분1.0000.253
업종0.2531.000

Missing values

2024-04-30T06:10:55.490989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T06:10:55.570701image/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

구분사업장명소재지업종점검일자
0종로구아쎈다스오피스사모부동산투자신탁1호<NA><NA>2021.01.12
1종로구디더블유에스오피스제2호사모부동산투자신탁<NA>부동산업2020.01.09
2종로구(주)청솔트러스트서울특별시 종로구 무악동 66-3 골든팰리스비주거용 건물 임대업2021.01.12
3종로구(주)효성주얼리시티쇼핑몰서울특별시 종로구 인의동 48-2번지 효성주얼리시티부동산업2020.01.15
4종로구주식회사 국일관드림펠리스총관리단서울특별시 종로구 관수동부동산업2020.01.22
5종로구종로염색서울특별시 종로구 효제동 197-1번지섬유 염색 및 가공업2020.01.06
6종로구종암염색서울특별시 종로구 종로5가 471<NA>2020.10.07
7종로구종암염색서울특별시 종로구 종로5가 471<NA>2020.12.08
8종로구선경섬유서울특별시 종로구 종로5가 460-2섬유제품 염색, 정리 및 마무리 가공업2020.10.14
9중구에스에이명진지퍼서울특별시 중구 황학동 1154번지<NA>2020.04.17
구분사업장명소재지업종점검일자
177송파구비아이피오토서울특별시 송파구 가락동 109-8자동차 세차업2020.11.04
178송파구어썸코트서울특별시 송파구 가락동 91-2 동성빌딩자동차 세차업2020.11.13
179강동구(유)천보개발서울특별시 강동구 성내동 48-1번지비주거용 건물 임대업2020.01.13
180강동구(주)르노삼성자동차지정센터 강동정비서울특별시 강동구 길동 228-4번지<NA>2020.05.12
181강동구맨케이브서울점<NA>자동차 세차업2020.11.13
182강동구강동JJ24시셀프세차장서울특별시 강동구 성내동 423-3<NA>2020.11.27
183강동구재희카 세차장서울특별시 강동구 길동 370-2자동차 세차업2020.11.13
184강동구프로오토경정비서울특별시 강동구 성내동 420-4자동차 세차업2020.10.26
185강동구르노삼성자동차서비스코너천호점서울특별시 강동구 천호동 326-24<NA>2020.11.05
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