Overview

Dataset statistics

Number of variables13
Number of observations2749
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows160
Duplicate rows (%)5.8%
Total size in memory279.3 KiB
Average record size in memory104.0 B

Variable types

Categorical5
DateTime3
Text5

Dataset

Description강남구 공중위생업소 업종, 업태, 업소명, 소재지, 행정처분일자, 처분명, 점검일자, 영업장 면적, 법적근거 등 데이터 제공합니다
Author서울특별시 강남구
URLhttps://www.data.go.kr/data/15075959/fileData.do

Alerts

시군구 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 160 (5.8%) duplicate rowsDuplicates
업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 업종명High correlation

Reproduction

Analysis started2023-12-12 22:16:57.108695
Analysis finished2023-12-12 22:16:58.234614
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
강남구
2749 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강남구 2749
100.0%

Length

2023-12-13T07:16:58.282700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:16:58.354509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강남구 2749
100.0%

처분일자
Date

Distinct782
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
Minimum1996-02-16 00:00:00
Maximum2021-11-02 00:00:00
2023-12-13T07:16:58.434981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:16:58.555707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
숙박업(일반)
560 
이용업
450 
위생관리용역업
416 
피부미용업
385 
목욕장업
332 
Other values (18)
606 

Length

Max length23
Median length19
Mean length5.375773
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(일반) 560
20.4%
이용업 450
16.4%
위생관리용역업 416
15.1%
피부미용업 385
14.0%
목욕장업 332
12.1%
미용업 157
 
5.7%
일반미용업 128
 
4.7%
종합미용업 95
 
3.5%
세탁업 80
 
2.9%
네일미용업 58
 
2.1%
Other values (13) 88
 
3.2%

Length

2023-12-13T07:16:58.709107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 560
19.5%
이용업 450
15.6%
피부미용업 425
14.8%
위생관리용역업 416
14.5%
목욕장업 332
11.5%
미용업 199
 
6.9%
일반미용업 160
 
5.6%
네일미용업 110
 
3.8%
종합미용업 95
 
3.3%
세탁업 80
 
2.8%
Other values (4) 51
 
1.8%

업태명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
일반이용업
495 
피부미용업
429 
여관업
424 
위생관리용역업
413 
일반미용업
281 
Other values (18)
707 

Length

Max length14
Median length5
Mean length4.8908694
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row관광호텔
2nd row여관업
3rd row여관업
4th row일반호텔
5th row여관업

Common Values

ValueCountFrequency (%)
일반이용업 495
18.0%
피부미용업 429
15.6%
여관업 424
15.4%
위생관리용역업 413
15.0%
일반미용업 281
10.2%
공동탕업 225
8.2%
네일아트업 113
 
4.1%
관광호텔 77
 
2.8%
일반세탁업 72
 
2.6%
한증막업 60
 
2.2%
Other values (13) 160
 
5.8%

Length

2023-12-13T07:16:58.827135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반이용업 495
17.6%
피부미용업 429
15.3%
여관업 424
15.1%
위생관리용역업 416
14.8%
일반미용업 281
10.0%
공동탕업 225
8.0%
네일아트업 113
 
4.0%
기타 82
 
2.9%
관광호텔 77
 
2.7%
일반세탁업 72
 
2.6%
Other values (12) 196
 
7.0%

업소명
Text

Distinct1640
Distinct (%)59.7%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2023-12-13T07:16:59.019427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length29
Mean length5.7711895
Min length1

Characters and Unicode

Total characters15865
Distinct characters644
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1065 ?
Unique (%)38.7%

Sample

1st row르네상스서울호텔
2nd row하트
3rd row하이츠여관
4th row로망스호텔
5th row위투장
ValueCountFrequency (%)
코리아이용원 19
 
0.6%
에스테틱 19
 
0.6%
주식회사 15
 
0.5%
피지한증막 11
 
0.3%
라자장여관 11
 
0.3%
더 10
 
0.3%
우성장 10
 
0.3%
엠호텔 9
 
0.3%
엠 9
 
0.3%
이용원 9
 
0.3%
Other values (1820) 3039
96.1%
2023-12-13T07:16:59.344596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 629
 
4.0%
이 554
 
3.5%
) 465
 
2.9%
( 464
 
2.9%
413
 
2.6%
주 412
 
2.6%
리 276
 
1.7%
관 265
 
1.7%
텔 231
 
1.5%
아 219
 
1.4%
Other values (634) 11937
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13723
86.5%
Lowercase Letter 479
 
3.0%
Close Punctuation 465
 
2.9%
Open Punctuation 464
 
2.9%
Space Separator 413
 
2.6%
Uppercase Letter 241
 
1.5%
Decimal Number 57
 
0.4%
Other Punctuation 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 629
 
4.6%
이 554
 
4.0%
주 412
 
3.0%
리 276
 
2.0%
관 265
 
1.9%
텔 231
 
1.7%
아 219
 
1.6%
사 219
 
1.6%
에 219
 
1.6%
우 193
 
1.4%
Other values (568) 10506
76.6%
Uppercase Letter
ValueCountFrequency (%)
B 30
12.4%
A 24
 
10.0%
S 22
 
9.1%
M 19
 
7.9%
L 18
 
7.5%
E 16
 
6.6%
R 16
 
6.6%
I 13
 
5.4%
C 10
 
4.1%
K 8
 
3.3%
Other values (16) 65
27.0%
Lowercase Letter
ValueCountFrequency (%)
e 64
13.4%
a 43
 
9.0%
o 43
 
9.0%
n 38
 
7.9%
i 34
 
7.1%
l 33
 
6.9%
t 30
 
6.3%
u 26
 
5.4%
s 22
 
4.6%
m 18
 
3.8%
Other values (15) 128
26.7%
Decimal Number
ValueCountFrequency (%)
1 21
36.8%
2 11
19.3%
4 8
 
14.0%
0 6
 
10.5%
3 5
 
8.8%
7 3
 
5.3%
6 2
 
3.5%
5 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 12
52.2%
& 5
21.7%
, 5
21.7%
: 1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 465
100.0%
Open Punctuation
ValueCountFrequency (%)
( 464
100.0%
Space Separator
ValueCountFrequency (%)
413
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13722
86.5%
Common 1422
 
9.0%
Latin 720
 
4.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 629
 
4.6%
이 554
 
4.0%
주 412
 
3.0%
리 276
 
2.0%
관 265
 
1.9%
텔 231
 
1.7%
아 219
 
1.6%
사 219
 
1.6%
에 219
 
1.6%
우 193
 
1.4%
Other values (567) 10505
76.6%
Latin
ValueCountFrequency (%)
e 64
 
8.9%
a 43
 
6.0%
o 43
 
6.0%
n 38
 
5.3%
i 34
 
4.7%
l 33
 
4.6%
B 30
 
4.2%
t 30
 
4.2%
u 26
 
3.6%
A 24
 
3.3%
Other values (41) 355
49.3%
Common
ValueCountFrequency (%)
) 465
32.7%
( 464
32.6%
413
29.0%
1 21
 
1.5%
. 12
 
0.8%
2 11
 
0.8%
4 8
 
0.6%
0 6
 
0.4%
& 5
 
0.4%
3 5
 
0.4%
Other values (5) 12
 
0.8%
Han
ValueCountFrequency (%)
善 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13722
86.5%
ASCII 2142
 
13.5%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 629
 
4.6%
이 554
 
4.0%
주 412
 
3.0%
리 276
 
2.0%
관 265
 
1.9%
텔 231
 
1.7%
아 219
 
1.6%
사 219
 
1.6%
에 219
 
1.6%
우 193
 
1.4%
Other values (567) 10505
76.6%
ASCII
ValueCountFrequency (%)
) 465
21.7%
( 464
21.7%
413
19.3%
e 64
 
3.0%
a 43
 
2.0%
o 43
 
2.0%
n 38
 
1.8%
i 34
 
1.6%
l 33
 
1.5%
B 30
 
1.4%
Other values (56) 515
24.0%
CJK
ValueCountFrequency (%)
善 1
100.0%

소재지지번
Text

Distinct1580
Distinct (%)57.5%
Missing1
Missing (%)< 0.1%
Memory size21.6 KiB
2023-12-13T07:16:59.627510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length28.275473
Min length18

Characters and Unicode

Total characters77701
Distinct characters306
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1010 ?
Unique (%)36.8%

Sample

1st row서울특별시 강남구 역삼동 676번지
2nd row서울특별시 강남구 역삼동 720번지 11호
3rd row서울특별시 강남구 역삼동 720번지 13호
4th row서울특별시 강남구 역삼동 719번지 23호
5th row서울특별시 강남구 역삼동 719번지 18호
ValueCountFrequency (%)
서울특별시 2748
18.0%
강남구 2748
18.0%
역삼동 846
 
5.6%
논현동 481
 
3.2%
신사동 359
 
2.4%
삼성동 352
 
2.3%
지하1층 262
 
1.7%
대치동 258
 
1.7%
청담동 217
 
1.4%
1호 186
 
1.2%
Other values (1259) 6786
44.5%
2023-12-13T07:17:00.037354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19232
24.8%
지 3517
 
4.5%
1 3119
 
4.0%
동 2788
 
3.6%
서 2785
 
3.6%
남 2773
 
3.6%
강 2768
 
3.6%
구 2768
 
3.6%
시 2760
 
3.6%
울 2752
 
3.5%
Other values (296) 32439
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43617
56.1%
Space Separator 19232
24.8%
Decimal Number 14092
 
18.1%
Other Punctuation 208
 
0.3%
Dash Punctuation 174
 
0.2%
Open Punctuation 142
 
0.2%
Close Punctuation 140
 
0.2%
Uppercase Letter 61
 
0.1%
Math Symbol 35
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 3517
 
8.1%
동 2788
 
6.4%
서 2785
 
6.4%
남 2773
 
6.4%
강 2768
 
6.3%
구 2768
 
6.3%
시 2760
 
6.3%
울 2752
 
6.3%
특 2748
 
6.3%
별 2748
 
6.3%
Other values (268) 15210
34.9%
Decimal Number
ValueCountFrequency (%)
1 3119
22.1%
2 1993
14.1%
6 1415
10.0%
3 1197
 
8.5%
7 1188
 
8.4%
0 1128
 
8.0%
4 1058
 
7.5%
5 1057
 
7.5%
8 1032
 
7.3%
9 905
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
B 33
54.1%
A 6
 
9.8%
L 4
 
6.6%
D 4
 
6.6%
T 4
 
6.6%
K 3
 
4.9%
S 3
 
4.9%
P 2
 
3.3%
G 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 185
88.9%
. 19
 
9.1%
/ 4
 
1.9%
Math Symbol
ValueCountFrequency (%)
~ 34
97.1%
< 1
 
2.9%
Space Separator
ValueCountFrequency (%)
19232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Close Punctuation
ValueCountFrequency (%)
) 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43617
56.1%
Common 34023
43.8%
Latin 61
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 3517
 
8.1%
동 2788
 
6.4%
서 2785
 
6.4%
남 2773
 
6.4%
강 2768
 
6.3%
구 2768
 
6.3%
시 2760
 
6.3%
울 2752
 
6.3%
특 2748
 
6.3%
별 2748
 
6.3%
Other values (268) 15210
34.9%
Common
ValueCountFrequency (%)
19232
56.5%
1 3119
 
9.2%
2 1993
 
5.9%
6 1415
 
4.2%
3 1197
 
3.5%
7 1188
 
3.5%
0 1128
 
3.3%
4 1058
 
3.1%
5 1057
 
3.1%
8 1032
 
3.0%
Other values (9) 1604
 
4.7%
Latin
ValueCountFrequency (%)
B 33
54.1%
A 6
 
9.8%
L 4
 
6.6%
D 4
 
6.6%
T 4
 
6.6%
K 3
 
4.9%
S 3
 
4.9%
P 2
 
3.3%
G 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43617
56.1%
ASCII 34084
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19232
56.4%
1 3119
 
9.2%
2 1993
 
5.8%
6 1415
 
4.2%
3 1197
 
3.5%
7 1188
 
3.5%
0 1128
 
3.3%
4 1058
 
3.1%
5 1057
 
3.1%
8 1032
 
3.0%
Other values (18) 1665
 
4.9%
Hangul
ValueCountFrequency (%)
지 3517
 
8.1%
동 2788
 
6.4%
서 2785
 
6.4%
남 2773
 
6.4%
강 2768
 
6.3%
구 2768
 
6.3%
시 2760
 
6.3%
울 2752
 
6.3%
특 2748
 
6.3%
별 2748
 
6.3%
Other values (268) 15210
34.9%

지도점검일자
Date

Distinct862
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
Minimum1996-02-16 00:00:00
Maximum2021-09-23 00:00:00
2023-12-13T07:17:00.154094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:00.266970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
처분확정
2749 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
처분확정 2749
100.0%

Length

2023-12-13T07:17:00.379567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:17:00.457888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 2749
100.0%

처분명
Text

Distinct670
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2023-12-13T07:17:00.724230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length68
Mean length13.817752
Min length2

Characters and Unicode

Total characters37985
Distinct characters180
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique429 ?
Unique (%)15.6%

Sample

1st row경고
2nd row경고
3rd row경고
4th row경고
5th row시설개수명령
ValueCountFrequency (%)
과태료부과 580
 
10.4%
경고 457
 
8.2%
및 422
 
7.6%
20만원 335
 
6.0%
과태료 260
 
4.7%
개선명령 250
 
4.5%
영업소폐쇄 246
 
4.4%
20만원(16만원 193
 
3.5%
영업정지 191
 
3.4%
부과 125
 
2.2%
Other values (744) 2524
45.2%
2023-12-13T07:17:01.273248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2844
 
7.5%
0 2786
 
7.3%
과 2516
 
6.6%
2 2300
 
6.1%
1 1669
 
4.4%
부 1515
 
4.0%
원 1490
 
3.9%
만 1395
 
3.7%
료 1389
 
3.7%
. 1327
 
3.5%
Other values (170) 18754
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22085
58.1%
Decimal Number 9015
23.7%
Space Separator 2844
 
7.5%
Other Punctuation 1712
 
4.5%
Open Punctuation 997
 
2.6%
Close Punctuation 989
 
2.6%
Math Symbol 235
 
0.6%
Dash Punctuation 104
 
0.3%
Connector Punctuation 2
 
< 0.1%
Format 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 2516
 
11.4%
부 1515
 
6.9%
원 1490
 
6.7%
만 1395
 
6.3%
료 1389
 
6.3%
태 1205
 
5.5%
업 1069
 
4.8%
영 956
 
4.3%
지 813
 
3.7%
경 768
 
3.5%
Other values (141) 8969
40.6%
Decimal Number
ValueCountFrequency (%)
0 2786
30.9%
2 2300
25.5%
1 1669
18.5%
6 503
 
5.6%
3 418
 
4.6%
5 358
 
4.0%
7 287
 
3.2%
4 275
 
3.1%
9 231
 
2.6%
8 188
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 1327
77.5%
, 261
 
15.2%
% 92
 
5.4%
: 22
 
1.3%
' 3
 
0.2%
/ 2
 
0.1%
; 2
 
0.1%
* 2
 
0.1%
＊ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 220
93.6%
→ 11
 
4.7%
> 2
 
0.9%
< 2
 
0.9%
Space Separator
ValueCountFrequency (%)
2844
100.0%
Open Punctuation
ValueCountFrequency (%)
( 997
100.0%
Close Punctuation
ValueCountFrequency (%)
) 989
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Format
ValueCountFrequency (%)
­ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22085
58.1%
Common 15900
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 2516
 
11.4%
부 1515
 
6.9%
원 1490
 
6.7%
만 1395
 
6.3%
료 1389
 
6.3%
태 1205
 
5.5%
업 1069
 
4.8%
영 956
 
4.3%
지 813
 
3.7%
경 768
 
3.5%
Other values (141) 8969
40.6%
Common
ValueCountFrequency (%)
2844
17.9%
0 2786
17.5%
2 2300
14.5%
1 1669
10.5%
. 1327
8.3%
( 997
 
6.3%
) 989
 
6.2%
6 503
 
3.2%
3 418
 
2.6%
5 358
 
2.3%
Other values (19) 1709
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22085
58.1%
ASCII 15886
41.8%
Arrows 11
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2844
17.9%
0 2786
17.5%
2 2300
14.5%
1 1669
10.5%
. 1327
8.4%
( 997
 
6.3%
) 989
 
6.2%
6 503
 
3.2%
3 418
 
2.6%
5 358
 
2.3%
Other values (16) 1695
10.7%
Hangul
ValueCountFrequency (%)
과 2516
 
11.4%
부 1515
 
6.9%
원 1490
 
6.7%
만 1395
 
6.3%
료 1389
 
6.3%
태 1205
 
5.5%
업 1069
 
4.8%
영 956
 
4.3%
지 813
 
3.7%
경 768
 
3.5%
Other values (141) 8969
40.6%
Arrows
ValueCountFrequency (%)
→ 11
100.0%
None
ValueCountFrequency (%)
­ 2
66.7%
＊ 1
33.3%

법적근거
Text

Distinct215
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2023-12-13T07:17:01.572908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length50
Mean length9.1655147
Min length1

Characters and Unicode

Total characters25196
Distinct characters137
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)3.9%

Sample

1st row식품위생법
2nd row공중위생법
3rd row식품위생법
4th row식품위생법
5th row공중위생법
ValueCountFrequency (%)
법 1121
22.1%
공중위생관리법 828
16.3%
제17조 826
16.3%
공중위생법 348
 
6.9%
제11조 175
 
3.5%
및 172
 
3.4%
제3조 121
 
2.4%
제11조제3항제2호 82
 
1.6%
제4조 68
 
1.3%
제19조 66
 
1.3%
Other values (219) 1262
24.9%
2023-12-13T07:17:02.024542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 2880
11.4%
법 2804
11.1%
1 2416
9.6%
2323
9.2%
조 2239
 
8.9%
위 1505
 
6.0%
생 1479
 
5.9%
공 1418
 
5.6%
중 1416
 
5.6%
관 1071
 
4.3%
Other values (127) 5645
22.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17919
71.1%
Decimal Number 4766
 
18.9%
Space Separator 2323
 
9.2%
Other Punctuation 178
 
0.7%
Close Punctuation 6
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 2880
16.1%
법 2804
15.6%
조 2239
12.5%
위 1505
8.4%
생 1479
8.3%
공 1418
7.9%
중 1416
7.9%
관 1071
 
6.0%
리 1052
 
5.9%
항 554
 
3.1%
Other values (109) 1501
8.4%
Decimal Number
ValueCountFrequency (%)
1 2416
50.7%
7 1015
21.3%
2 483
 
10.1%
3 427
 
9.0%
4 217
 
4.6%
9 99
 
2.1%
0 50
 
1.0%
6 48
 
1.0%
8 10
 
0.2%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 174
97.8%
. 4
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 4
66.7%
」 2
33.3%
Open Punctuation
ValueCountFrequency (%)
「 2
66.7%
( 1
33.3%
Space Separator
ValueCountFrequency (%)
2323
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17919
71.1%
Common 7276
28.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 2880
16.1%
법 2804
15.6%
조 2239
12.5%
위 1505
8.4%
생 1479
8.3%
공 1418
7.9%
중 1416
7.9%
관 1071
 
6.0%
리 1052
 
5.9%
항 554
 
3.1%
Other values (109) 1501
8.4%
Common
ValueCountFrequency (%)
1 2416
33.2%
2323
31.9%
7 1015
13.9%
2 483
 
6.6%
3 427
 
5.9%
4 217
 
3.0%
, 174
 
2.4%
9 99
 
1.4%
0 50
 
0.7%
6 48
 
0.7%
Other values (7) 24
 
0.3%
Latin
ValueCountFrequency (%)
T 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17919
71.1%
ASCII 7273
28.9%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 2880
16.1%
법 2804
15.6%
조 2239
12.5%
위 1505
8.4%
생 1479
8.3%
공 1418
7.9%
중 1416
7.9%
관 1071
 
6.0%
리 1052
 
5.9%
항 554
 
3.1%
Other values (109) 1501
8.4%
ASCII
ValueCountFrequency (%)
1 2416
33.2%
2323
31.9%
7 1015
14.0%
2 483
 
6.6%
3 427
 
5.9%
4 217
 
3.0%
, 174
 
2.4%
9 99
 
1.4%
0 50
 
0.7%
6 48
 
0.7%
Other values (6) 21
 
0.3%
None
ValueCountFrequency (%)
「 2
50.0%
」 2
50.0%

위반일자
Date

Distinct867
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
Minimum1996-02-04 00:00:00
Maximum2021-09-23 00:00:00
2023-12-13T07:17:02.182402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.695465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

처분내용
Text

Distinct683
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2023-12-13T07:17:02.967696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length68
Mean length13.975264
Min length2

Characters and Unicode

Total characters38418
Distinct characters192
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique438 ?
Unique (%)15.9%

Sample

1st row경고
2nd row경고
3rd row경고
4th row경고
5th row시설개수명령
ValueCountFrequency (%)
과태료부과 575
 
10.2%
경고 457
 
8.1%
및 424
 
7.5%
20만원 338
 
6.0%
과태료 263
 
4.6%
개선명령 250
 
4.4%
영업소폐쇄 244
 
4.3%
20만원(16만원 193
 
3.4%
영업정지 190
 
3.4%
부과 128
 
2.3%
Other values (770) 2599
45.9%
2023-12-13T07:17:03.371386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2922
 
7.6%
0 2848
 
7.4%
과 2515
 
6.5%
2 2315
 
6.0%
1 1683
 
4.4%
원 1546
 
4.0%
부 1515
 
3.9%
만 1451
 
3.8%
료 1392
 
3.6%
. 1337
 
3.5%
Other values (182) 18894
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22265
58.0%
Decimal Number 9169
23.9%
Space Separator 2922
 
7.6%
Other Punctuation 1724
 
4.5%
Open Punctuation 1001
 
2.6%
Close Punctuation 993
 
2.6%
Math Symbol 236
 
0.6%
Dash Punctuation 104
 
0.3%
Connector Punctuation 2
 
< 0.1%
Format 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 2515
 
11.3%
원 1546
 
6.9%
부 1515
 
6.8%
만 1451
 
6.5%
료 1392
 
6.3%
태 1206
 
5.4%
업 1068
 
4.8%
영 954
 
4.3%
지 813
 
3.7%
경 768
 
3.4%
Other values (153) 9037
40.6%
Decimal Number
ValueCountFrequency (%)
0 2848
31.1%
2 2315
25.2%
1 1683
18.4%
6 503
 
5.5%
3 464
 
5.1%
5 367
 
4.0%
7 289
 
3.2%
4 278
 
3.0%
9 231
 
2.5%
8 191
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 1337
77.6%
, 263
 
15.3%
% 92
 
5.3%
: 22
 
1.3%
' 3
 
0.2%
/ 2
 
0.1%
* 2
 
0.1%
; 2
 
0.1%
＊ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 221
93.6%
→ 11
 
4.7%
> 2
 
0.8%
< 2
 
0.8%
Space Separator
ValueCountFrequency (%)
2922
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1001
100.0%
Close Punctuation
ValueCountFrequency (%)
) 993
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Format
ValueCountFrequency (%)
­ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22265
58.0%
Common 16153
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 2515
 
11.3%
원 1546
 
6.9%
부 1515
 
6.8%
만 1451
 
6.5%
료 1392
 
6.3%
태 1206
 
5.4%
업 1068
 
4.8%
영 954
 
4.3%
지 813
 
3.7%
경 768
 
3.4%
Other values (153) 9037
40.6%
Common
ValueCountFrequency (%)
2922
18.1%
0 2848
17.6%
2 2315
14.3%
1 1683
10.4%
. 1337
8.3%
( 1001
 
6.2%
) 993
 
6.1%
6 503
 
3.1%
3 464
 
2.9%
5 367
 
2.3%
Other values (19) 1720
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22265
58.0%
ASCII 16139
42.0%
Arrows 11
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2922
18.1%
0 2848
17.6%
2 2315
14.3%
1 1683
10.4%
. 1337
8.3%
( 1001
 
6.2%
) 993
 
6.2%
6 503
 
3.1%
3 464
 
2.9%
5 367
 
2.3%
Other values (16) 1706
10.6%
Hangul
ValueCountFrequency (%)
과 2515
 
11.3%
원 1546
 
6.9%
부 1515
 
6.8%
만 1451
 
6.5%
료 1392
 
6.3%
태 1206
 
5.4%
업 1068
 
4.8%
영 954
 
4.3%
지 813
 
3.7%
경 768
 
3.4%
Other values (153) 9037
40.6%
Arrows
ValueCountFrequency (%)
→ 11
100.0%
None
ValueCountFrequency (%)
­ 2
66.7%
＊ 1
33.3%

적발구분
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
수시
1876 
기타
571 
일제
 
141
합동
 
81
자체
 
78

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row수시
3rd row기타
4th row기타
5th row수시

Common Values

ValueCountFrequency (%)
수시 1876
68.2%
기타 571
 
20.8%
일제 141
 
5.1%
합동 81
 
2.9%
자체 78
 
2.8%
외부 2
 
0.1%

Length

2023-12-13T07:17:03.491393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:17:03.592044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 1876
68.2%
기타 571
 
20.8%
일제 141
 
5.1%
합동 81
 
2.9%
자체 78
 
2.8%
외부 2
 
0.1%

Correlations

2023-12-13T07:17:03.655802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명적발구분
업종명1.0000.9860.447
업태명0.9861.0000.406
적발구분0.4470.4061.000
2023-12-13T07:17:03.741776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명적발구분업태명
업종명1.0000.2190.682
적발구분0.2191.0000.196
업태명0.6820.1961.000
2023-12-13T07:17:03.826366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명적발구분
업종명1.0000.6820.219
업태명0.6821.0000.196
적발구분0.2190.1961.000

Missing values

2023-12-13T07:16:58.029620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:16:58.175712image/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

시군구처분일자업종명업태명업소명소재지지번지도점검일자행정처분상태처분명법적근거위반일자처분내용적발구분
0강남구1996-02-16숙박업(일반)관광호텔르네상스서울호텔서울특별시 강남구 역삼동 676번지1996-02-16처분확정경고식품위생법1996-02-16경고기타
1강남구1996-04-17숙박업(일반)여관업하트서울특별시 강남구 역삼동 720번지 11호1996-03-17처분확정경고공중위생법1996-04-17경고수시
2강남구1996-04-17숙박업(일반)여관업하이츠여관서울특별시 강남구 역삼동 720번지 13호1996-04-17처분확정경고식품위생법1996-04-17경고기타
3강남구1996-04-17숙박업(일반)일반호텔로망스호텔서울특별시 강남구 역삼동 719번지 23호1996-04-17처분확정경고식품위생법1996-02-04경고기타
4강남구1996-04-17숙박업(일반)여관업위투장서울특별시 강남구 역삼동 719번지 18호1996-03-17처분확정시설개수명령공중위생법1996-04-17시설개수명령수시
5강남구1996-04-17숙박업(일반)여관업위투장서울특별시 강남구 역삼동 719번지 18호1996-03-17처분확정경고공중위생법1996-04-17경고수시
6강남구1996-05-17숙박업(일반)여관업백제장서울특별시 강남구 신사동 563번지 37호1996-04-17처분확정영업정지2월공중위생법 제12조2항1996-04-17영업정지2월수시
7강남구1996-05-23숙박업(일반)여관업용천여관서울특별시 강남구 청담동 46번지 0호1996-04-23처분확정개선명령공중위생법1996-05-23개선명령수시
8강남구1996-05-23숙박업(일반)여관업유정여관서울특별시 강남구 청담동 125번지 11호1996-05-23처분확정경고식품위생법1996-05-23경고기타
9강남구1996-05-28숙박업(일반)여관업서반도서울특별시 강남구 논현동 118번지 8호1996-04-28처분확정시설개수명령공중위생법1996-05-28시설개수명령수시
시군구처분일자업종명업태명업소명소재지지번지도점검일자행정처분상태처분명법적근거위반일자처분내용적발구분
2739강남구2021-10-08네일미용업, 화장ㆍ분장 미용업네일아트업쉐젤르(chez elle)서울특별시 강남구 신사동 638-22021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01과태료부과 30만원자체
2740강남구2021-10-08일반미용업, 피부미용업, 화장ㆍ분장 미용업일반미용업미소지울서울특별시 강남구 신사동 592-52021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01과태료부과 30만원자체
2741강남구2021-10-13숙박업(일반)일반호텔맨하탄호텔서울특별시 강남구 삼성동 144-6 지상3,4,5층2021-06-01처분확정영업소폐쇄법 제11조제3항제2호2021-06-01영업소폐쇄자체
2742강남구2021-10-26미용업일반미용업엠서울특별시 강남구 논현동 186-5 1층2021-09-23처분확정영업정지법 제49조제3항2021-09-23영업정지 10일자체
2743강남구2021-10-26미용업일반미용업엠서울특별시 강남구 논현동 186-5 1층2021-09-23처분확정과태료부과법 제83조제2항2021-09-23과태료부과 150만원자체
2744강남구2021-10-29목욕장업공동탕업라미드남자사우나서울특별시 강남구 삼성동 112-52021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01과태료부과자체
2745강남구2021-10-29목욕장업공동탕업(주)투엑스 휘트니스서울특별시 강남구 대치동 507-2 대치퍼스트빌딩 지하2층2021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01과태료부과자체
2746강남구2021-10-29목욕장업목욕장업 기타포포인츠 바이 쉐라톤 서울 강남사우나서울특별시 강남구 신사동 587-212021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01과태료부과자체
2747강남구2021-11-02숙박업(일반)일반호텔맨하탄호텔서울특별시 강남구 삼성동 144-6 지상3,4,5층2021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01직권폐업자체
2748강남구2021-11-02목욕장업목욕장업 기타스위트캐슬서울특별시 강남구 역삼동 603-52021-07-01처분확정과태료부과법 제22조제2항제6호2021-07-01과태료부과자체

Duplicate rows

Most frequently occurring

시군구처분일자업종명업태명업소명소재지지번지도점검일자행정처분상태처분명법적근거위반일자처분내용적발구분# duplicates
56강남구2005-02-23이용업일반이용업코리아이용원서울특별시 강남구 역삼동 706번지 12호2004-04-17처분확정면허정지 2월(2005.03.02~05.01)공중위생관리법2004-04-17면허정지 2월(2005.03.02~05.01)수시6
57강남구2005-02-23이용업일반이용업코리아이용원서울특별시 강남구 역삼동 706번지 12호2004-04-17처분확정영업정지 2월(2005.03.02~05.01)공중위생관리법2004-04-17영업정지 2월(2005.03.02~05.01)수시6
130강남구2014-11-24숙박업(일반)관광호텔엠호텔서울특별시 강남구 역삼동 823번지 43호2013-04-11처분확정영업정지2월공중위생관리법 제11조2013-04-11영업정지2월수시6
58강남구2005-08-18목욕장업한증막업피지한증막서울특별시 강남구 대치동 932번지 2호2004-06-20처분확정15일및과징금100만원공중위생관리법제11조2004-06-1915일및과징금100만원수시5
106강남구2012-07-02목욕장업목욕장업 기타도토리짐서울특별시 강남구 논현동 152번지 5호 대우아이빌 지하1층 B01호2012-05-03처분확정영업소폐쇄공중위생관립버 제3조 및 동법시행규칙 제19조2012-05-03영업소폐쇄기타4
131강남구2014-12-08일반미용업일반미용업박준뷰티랩서울특별시 강남구 청담동 31번지 12호2014-11-04처분확정개선명령 및 과태료부과(40만원)-사전납부 감경부과법 제4조제4항 및 제7항2014-11-04개선명령 및 과태료부과(40만원)-사전납부 감경부과수시4
158강남구2019-10-25피부미용업피부미용업수아미서울특별시 강남구 역삼동 823번지 0호 지하1층-1012019-10-02처분확정과징금부과564천원 부과(영업정지2개월 갈음)과태료500천원(400천원 사전납부완료)법 제4조제4항 및 제7항2019-10-02과징금부과564천원 부과(영업정지2개월 갈음)과태료500천원(400천원 사전납부완료)수시4
73강남구2008-09-11목욕장업공동탕업한증막금사우나서울특별시 강남구 대치동 898번지2008-03-03처분확정영업정지공중위생관리법제102008-03-03영업정지수시3
78강남구2008-11-24이용업일반이용업성민서울특별시 강남구 역삼동 719번지 6호 지하1층2008-09-20처분확정영업정지1월 갈음 과징금156만원부과공중위생관리법 제11조 및 동법생행규칙 제19조2008-09-20영업정지1월 갈음 과징금156만원부과기타3
81강남구2009-05-12위생관리용역업위생관리용역업(주)큐비스라인서울특별시 강남구 역삼동 837번지 26호2009-04-07처분확정영업소폐쇄(09.05.12자)공중위생법2009-04-07영업소폐쇄(09.05.12자)기타3