Overview

Dataset statistics

Number of variables17
Number of observations593
Missing cells172
Missing cells (%)1.7%
Duplicate rows26
Duplicate rows (%)4.4%
Total size in memory82.4 KiB
Average record size in memory142.2 B

Variable types

Categorical5
Numeric4
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-10759/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 26 (4.4%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 처분기간High correlation
업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 업종명High correlation
처분기간 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
처분기간 is highly imbalanced (92.5%)Imbalance
소재지도로명 has 149 (25.1%) missing valuesMissing
영업장면적(㎡) has 23 (3.9%) missing valuesMissing
영업장면적(㎡) has 7 (1.2%) zerosZeros

Reproduction

Analysis started2024-05-10 23:44:28.177625
Analysis finished2024-05-10 23:44:35.599290
Duration7.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
3030000
593 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 593
100.0%

Length

2024-05-10T23:44:35.807127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:44:36.108380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 593
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct277
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20102296
Minimum20010206
Maximum20240425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-05-10T23:44:36.520245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010206
5-th percentile20011222
Q120060323
median20091229
Q320160720
95-th percentile20201104
Maximum20240425
Range230219
Interquartile range (IQR)100397

Descriptive statistics

Standard deviation60496.529
Coefficient of variation (CV)0.0030094338
Kurtosis-1.0272986
Mean20102296
Median Absolute Deviation (MAD)49898
Skewness0.30805202
Sum1.1920662 × 1010
Variance3.65983 × 109
MonotonicityDecreasing
2024-05-10T23:44:37.070278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091229 20
 
3.4%
20070423 18
 
3.0%
20170719 14
 
2.4%
20071231 13
 
2.2%
20170417 11
 
1.9%
20081217 10
 
1.7%
20120227 10
 
1.7%
20110222 9
 
1.5%
20201116 9
 
1.5%
20191209 8
 
1.3%
Other values (267) 471
79.4%
ValueCountFrequency (%)
20010206 7
1.2%
20010216 1
 
0.2%
20010226 1
 
0.2%
20010227 1
 
0.2%
20010419 3
0.5%
20010424 1
 
0.2%
20010618 1
 
0.2%
20010711 3
0.5%
20010802 1
 
0.2%
20010822 2
 
0.3%
ValueCountFrequency (%)
20240425 1
0.2%
20240219 1
0.2%
20240126 1
0.2%
20240125 2
0.3%
20230510 1
0.2%
20221223 1
0.2%
20211214 1
0.2%
20211122 1
0.2%
20210818 1
0.2%
20210622 1
0.2%

교부번호
Text

Distinct331
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:37.623135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.0067454
Min length2

Characters and Unicode

Total characters2969
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique217 ?
Unique (%)36.6%

Sample

1st row0125
2nd row2018-00002
3rd row2019-00001
4th row2022-00036
5th row2015-00004
ValueCountFrequency (%)
0135 12
 
2.0%
0006 10
 
1.7%
600 9
 
1.5%
0112 7
 
1.2%
02000430100345 7
 
1.2%
0002 7
 
1.2%
0131 6
 
1.0%
0073 6
 
1.0%
0042 6
 
1.0%
0046 5
 
0.8%
Other values (321) 518
87.4%
2024-05-10T23:44:38.659613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1178
39.7%
1 425
 
14.3%
2 293
 
9.9%
4 184
 
6.2%
3 182
 
6.1%
5 160
 
5.4%
6 150
 
5.1%
7 134
 
4.5%
8 106
 
3.6%
9 102
 
3.4%
Other values (2) 55
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2914
98.1%
Dash Punctuation 54
 
1.8%
Other Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1178
40.4%
1 425
 
14.6%
2 293
 
10.1%
4 184
 
6.3%
3 182
 
6.2%
5 160
 
5.5%
6 150
 
5.1%
7 134
 
4.6%
8 106
 
3.6%
9 102
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Other Letter
ValueCountFrequency (%)
제 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2968
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1178
39.7%
1 425
 
14.3%
2 293
 
9.9%
4 184
 
6.2%
3 182
 
6.1%
5 160
 
5.4%
6 150
 
5.1%
7 134
 
4.5%
8 106
 
3.6%
9 102
 
3.4%
Hangul
ValueCountFrequency (%)
제 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2968
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1178
39.7%
1 425
 
14.3%
2 293
 
9.9%
4 184
 
6.2%
3 182
 
6.1%
5 160
 
5.4%
6 150
 
5.1%
7 134
 
4.5%
8 106
 
3.6%
9 102
 
3.4%
Hangul
ValueCountFrequency (%)
제 1
100.0%

업종명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
숙박업(일반)
159 
이용업
116 
세탁업
67 
위생관리용역업
62 
일반미용업
49 
Other values (10)
140 

Length

Max length16
Median length12
Mean length5.0623946
Min length3

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 159
26.8%
이용업 116
19.6%
세탁업 67
11.3%
위생관리용역업 62
 
10.5%
일반미용업 49
 
8.3%
피부미용업 39
 
6.6%
목욕장업 38
 
6.4%
종합미용업 33
 
5.6%
미용업 17
 
2.9%
네일미용업 6
 
1.0%
Other values (5) 7
 
1.2%

Length

2024-05-10T23:44:39.081099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 159
26.6%
이용업 116
19.4%
세탁업 67
11.2%
위생관리용역업 62
 
10.4%
일반미용업 50
 
8.4%
피부미용업 41
 
6.9%
목욕장업 38
 
6.4%
종합미용업 33
 
5.5%
미용업 19
 
3.2%
네일미용업 8
 
1.3%
Other values (3) 5
 
0.8%

업태명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
여관업
146 
일반이용업
116 
일반미용업
95 
위생관리용역업
62 
일반세탁업
61 
Other values (15)
113 

Length

Max length14
Median length5
Mean length4.7015177
Min length2

Unique

Unique7 ?
Unique (%)1.2%

Sample

1st row여관업
2nd row위생관리용역업
3rd row일반세탁업
4th row일반미용업
5th row위생관리용역업

Common Values

ValueCountFrequency (%)
여관업 146
24.6%
일반이용업 116
19.6%
일반미용업 95
16.0%
위생관리용역업 62
10.5%
일반세탁업 61
10.3%
피부미용업 40
 
6.7%
공동탕업 36
 
6.1%
네일아트업 11
 
1.9%
여인숙업 7
 
1.2%
운동화전문세탁업 5
 
0.8%
Other values (10) 14
 
2.4%

Length

2024-05-10T23:44:39.603171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여관업 146
24.6%
일반이용업 116
19.5%
일반미용업 95
16.0%
위생관리용역업 62
10.4%
일반세탁업 61
10.3%
피부미용업 40
 
6.7%
공동탕업 36
 
6.1%
네일아트업 11
 
1.9%
여인숙업 7
 
1.2%
운동화전문세탁업 5
 
0.8%
Other values (10) 15
 
2.5%

업소명
Text

Distinct358
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:40.463097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length4.8836425
Min length1

Characters and Unicode

Total characters2896
Distinct characters340
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

Unique250 ?
Unique (%)42.2%

Sample

1st row동신여관
2nd row(주)아미티에이
3rd row그린어스
4th row필름더서울
5th row(주)에이치엔씨네트워크
ValueCountFrequency (%)
동명사 12
 
1.9%
남녀공학헤어∥ 9
 
1.4%
서중여관 7
 
1.1%
둥지 7
 
1.1%
우성 6
 
1.0%
라성보석사우나 5
 
0.8%
김예분머리모아 5
 
0.8%
현대여관 5
 
0.8%
대흥장여관 5
 
0.8%
현대 5
 
0.8%
Other values (371) 557
89.4%
2024-05-10T23:44:41.393267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
여 98
 
3.4%
관 98
 
3.4%
성 82
 
2.8%
사 73
 
2.5%
어 63
 
2.2%
) 58
 
2.0%
( 58
 
2.0%
장 58
 
2.0%
헤 57
 
2.0%
대 57
 
2.0%
Other values (330) 2194
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2639
91.1%
Uppercase Letter 69
 
2.4%
Close Punctuation 58
 
2.0%
Open Punctuation 58
 
2.0%
Space Separator 30
 
1.0%
Decimal Number 25
 
0.9%
Math Symbol 9
 
0.3%
Lowercase Letter 6
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 98
 
3.7%
관 98
 
3.7%
성 82
 
3.1%
사 73
 
2.8%
어 63
 
2.4%
장 58
 
2.2%
헤 57
 
2.2%
대 57
 
2.2%
스 54
 
2.0%
이 53
 
2.0%
Other values (293) 1946
73.7%
Uppercase Letter
ValueCountFrequency (%)
H 12
17.4%
N 7
10.1%
A 6
 
8.7%
I 5
 
7.2%
R 4
 
5.8%
W 4
 
5.8%
Y 4
 
5.8%
O 4
 
5.8%
G 3
 
4.3%
S 3
 
4.3%
Other values (10) 17
24.6%
Lowercase Letter
ValueCountFrequency (%)
y 1
16.7%
u 1
16.7%
a 1
16.7%
e 1
16.7%
b 1
16.7%
t 1
16.7%
Decimal Number
ValueCountFrequency (%)
3 8
32.0%
2 6
24.0%
4 6
24.0%
1 3
 
12.0%
0 2
 
8.0%
Other Punctuation
ValueCountFrequency (%)
? 1
50.0%
& 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Math Symbol
ValueCountFrequency (%)
∥ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2639
91.1%
Common 182
 
6.3%
Latin 75
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 98
 
3.7%
관 98
 
3.7%
성 82
 
3.1%
사 73
 
2.8%
어 63
 
2.4%
장 58
 
2.2%
헤 57
 
2.2%
대 57
 
2.2%
스 54
 
2.0%
이 53
 
2.0%
Other values (293) 1946
73.7%
Latin
ValueCountFrequency (%)
H 12
16.0%
N 7
 
9.3%
A 6
 
8.0%
I 5
 
6.7%
R 4
 
5.3%
W 4
 
5.3%
Y 4
 
5.3%
O 4
 
5.3%
G 3
 
4.0%
S 3
 
4.0%
Other values (16) 23
30.7%
Common
ValueCountFrequency (%)
) 58
31.9%
( 58
31.9%
30
16.5%
∥ 9
 
4.9%
3 8
 
4.4%
2 6
 
3.3%
4 6
 
3.3%
1 3
 
1.6%
0 2
 
1.1%
? 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2639
91.1%
ASCII 248
 
8.6%
Math Operators 9
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
여 98
 
3.7%
관 98
 
3.7%
성 82
 
3.1%
사 73
 
2.8%
어 63
 
2.4%
장 58
 
2.2%
헤 57
 
2.2%
대 57
 
2.2%
스 54
 
2.0%
이 53
 
2.0%
Other values (293) 1946
73.7%
ASCII
ValueCountFrequency (%)
) 58
23.4%
( 58
23.4%
30
12.1%
H 12
 
4.8%
3 8
 
3.2%
N 7
 
2.8%
2 6
 
2.4%
A 6
 
2.4%
4 6
 
2.4%
I 5
 
2.0%
Other values (26) 52
21.0%
Math Operators
ValueCountFrequency (%)
∥ 9
100.0%

소재지도로명
Text

MISSING 

Distinct282
Distinct (%)63.5%
Missing149
Missing (%)25.1%
Memory size4.8 KiB
2024-05-10T23:44:41.924920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length56
Mean length31.335586
Min length23

Characters and Unicode

Total characters13913
Distinct characters194
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

Unique207 ?
Unique (%)46.6%

Sample

1st row서울특별시 성동구 왕십리로20길 39, (홍익동)
2nd row서울특별시 성동구 연무장13길 9, 아이템플 8층 837호 (성수동2가)
3rd row서울특별시 성동구 독서당로 223, 래미안 옥수 리버젠 상가 상가동 제지1층 제109-1호 (옥수동)
4th row서울특별시 성동구 왕십리로 106, 3층 (성수동1가)
5th row서울특별시 성동구 연무장5길 18, 에이치디앤텍빌딩 4층 (성수동2가)
ValueCountFrequency (%)
서울특별시 444
 
17.6%
성동구 444
 
17.6%
성수동2가 69
 
2.7%
도선동 43
 
1.7%
행당동 42
 
1.7%
성수동1가 37
 
1.5%
왕십리로 34
 
1.4%
독서당로 30
 
1.2%
마장동 30
 
1.2%
용답동 28
 
1.1%
Other values (478) 1315
52.3%
2024-05-10T23:44:43.485964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2072
 
14.9%
동 957
 
6.9%
성 620
 
4.5%
, 584
 
4.2%
1 569
 
4.1%
서 493
 
3.5%
) 486
 
3.5%
( 486
 
3.5%
시 464
 
3.3%
울 454
 
3.3%
Other values (184) 6728
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8023
57.7%
Decimal Number 2132
 
15.3%
Space Separator 2072
 
14.9%
Other Punctuation 585
 
4.2%
Close Punctuation 486
 
3.5%
Open Punctuation 486
 
3.5%
Dash Punctuation 101
 
0.7%
Uppercase Letter 25
 
0.2%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 957
 
11.9%
성 620
 
7.7%
서 493
 
6.1%
시 464
 
5.8%
울 454
 
5.7%
구 447
 
5.6%
별 444
 
5.5%
특 444
 
5.5%
로 336
 
4.2%
길 270
 
3.4%
Other values (159) 3094
38.6%
Decimal Number
ValueCountFrequency (%)
1 569
26.7%
2 429
20.1%
3 243
11.4%
4 179
 
8.4%
0 170
 
8.0%
9 118
 
5.5%
6 114
 
5.3%
5 109
 
5.1%
7 105
 
4.9%
8 96
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
I 6
24.0%
B 6
24.0%
A 5
20.0%
L 3
12.0%
C 2
 
8.0%
J 1
 
4.0%
P 1
 
4.0%
T 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 584
99.8%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2072
100.0%
Close Punctuation
ValueCountFrequency (%)
) 486
100.0%
Open Punctuation
ValueCountFrequency (%)
( 486
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8023
57.7%
Common 5865
42.2%
Latin 25
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 957
 
11.9%
성 620
 
7.7%
서 493
 
6.1%
시 464
 
5.8%
울 454
 
5.7%
구 447
 
5.6%
별 444
 
5.5%
특 444
 
5.5%
로 336
 
4.2%
길 270
 
3.4%
Other values (159) 3094
38.6%
Common
ValueCountFrequency (%)
2072
35.3%
, 584
 
10.0%
1 569
 
9.7%
) 486
 
8.3%
( 486
 
8.3%
2 429
 
7.3%
3 243
 
4.1%
4 179
 
3.1%
0 170
 
2.9%
9 118
 
2.0%
Other values (7) 529
 
9.0%
Latin
ValueCountFrequency (%)
I 6
24.0%
B 6
24.0%
A 5
20.0%
L 3
12.0%
C 2
 
8.0%
J 1
 
4.0%
P 1
 
4.0%
T 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8023
57.7%
ASCII 5890
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2072
35.2%
, 584
 
9.9%
1 569
 
9.7%
) 486
 
8.3%
( 486
 
8.3%
2 429
 
7.3%
3 243
 
4.1%
4 179
 
3.0%
0 170
 
2.9%
9 118
 
2.0%
Other values (15) 554
 
9.4%
Hangul
ValueCountFrequency (%)
동 957
 
11.9%
성 620
 
7.7%
서 493
 
6.1%
시 464
 
5.8%
울 454
 
5.7%
구 447
 
5.6%
별 444
 
5.5%
특 444
 
5.5%
로 336
 
4.2%
길 270
 
3.4%
Other values (159) 3094
38.6%

소재지지번
Text

Distinct363
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:44.268165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length28.160202
Min length20

Characters and Unicode

Total characters16699
Distinct characters170
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

Unique262 ?
Unique (%)44.2%

Sample

1st row서울특별시 성동구 홍익동 168번지
2nd row서울특별시 성동구 성수동2가 273번지 19호 아이템플-837
3rd row서울특별시 성동구 옥수동 561번지 래미안 옥수 리버젠 상가
4th row서울특별시 성동구 성수동1가 656번지 967호 동일모텔
5th row서울특별시 성동구 성수동2가 314번지 7호 에이치디앤텍빌딩
ValueCountFrequency (%)
서울특별시 593
19.0%
성동구 593
19.0%
성수동2가 113
 
3.6%
1호 78
 
2.5%
행당동 74
 
2.4%
도선동 65
 
2.1%
0호 50
 
1.6%
성수동1가 48
 
1.5%
마장동 48
 
1.5%
용답동 42
 
1.3%
Other values (436) 1412
45.3%
2024-05-10T23:44:45.924400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4139
24.8%
동 1203
 
7.2%
성 769
 
4.6%
지 683
 
4.1%
1 628
 
3.8%
호 617
 
3.7%
서 597
 
3.6%
울 596
 
3.6%
시 595
 
3.6%
번 593
 
3.6%
Other values (160) 6279
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9377
56.2%
Space Separator 4139
24.8%
Decimal Number 3041
 
18.2%
Close Punctuation 46
 
0.3%
Open Punctuation 46
 
0.3%
Uppercase Letter 21
 
0.1%
Dash Punctuation 14
 
0.1%
Other Punctuation 11
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1203
12.8%
성 769
 
8.2%
지 683
 
7.3%
호 617
 
6.6%
서 597
 
6.4%
울 596
 
6.4%
시 595
 
6.3%
번 593
 
6.3%
구 593
 
6.3%
특 593
 
6.3%
Other values (136) 2538
27.1%
Decimal Number
ValueCountFrequency (%)
1 628
20.7%
2 480
15.8%
3 332
10.9%
6 291
9.6%
0 284
9.3%
9 225
 
7.4%
4 218
 
7.2%
7 204
 
6.7%
5 195
 
6.4%
8 184
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
B 7
33.3%
A 5
23.8%
I 3
14.3%
L 2
 
9.5%
C 2
 
9.5%
P 1
 
4.8%
T 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
@ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
4139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9377
56.2%
Common 7301
43.7%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1203
12.8%
성 769
 
8.2%
지 683
 
7.3%
호 617
 
6.6%
서 597
 
6.4%
울 596
 
6.4%
시 595
 
6.3%
번 593
 
6.3%
구 593
 
6.3%
특 593
 
6.3%
Other values (136) 2538
27.1%
Common
ValueCountFrequency (%)
4139
56.7%
1 628
 
8.6%
2 480
 
6.6%
3 332
 
4.5%
6 291
 
4.0%
0 284
 
3.9%
9 225
 
3.1%
4 218
 
3.0%
7 204
 
2.8%
5 195
 
2.7%
Other values (7) 305
 
4.2%
Latin
ValueCountFrequency (%)
B 7
33.3%
A 5
23.8%
I 3
14.3%
L 2
 
9.5%
C 2
 
9.5%
P 1
 
4.8%
T 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9377
56.2%
ASCII 7322
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4139
56.5%
1 628
 
8.6%
2 480
 
6.6%
3 332
 
4.5%
6 291
 
4.0%
0 284
 
3.9%
9 225
 
3.1%
4 218
 
3.0%
7 204
 
2.8%
5 195
 
2.7%
Other values (14) 326
 
4.5%
Hangul
ValueCountFrequency (%)
동 1203
12.8%
성 769
 
8.2%
지 683
 
7.3%
호 617
 
6.6%
서 597
 
6.4%
울 596
 
6.4%
시 595
 
6.3%
번 593
 
6.3%
구 593
 
6.3%
특 593
 
6.3%
Other values (136) 2538
27.1%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct257
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20100923
Minimum20001214
Maximum20240213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-05-10T23:44:46.597045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001214
5-th percentile20011108
Q120060306
median20091125
Q320160326
95-th percentile20201023
Maximum20240213
Range238999
Interquartile range (IQR)100020

Descriptive statistics

Standard deviation60544.987
Coefficient of variation (CV)0.0030120501
Kurtosis-0.98182593
Mean20100923
Median Absolute Deviation (MAD)49590
Skewness0.2914061
Sum1.1919847 × 1010
Variance3.6656954 × 109
MonotonicityNot monotonic
2024-05-10T23:44:47.397258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201023 32
 
5.4%
20191118 25
 
4.2%
20070405 18
 
3.0%
20170630 14
 
2.4%
20071206 13
 
2.2%
20170901 13
 
2.2%
20100702 12
 
2.0%
20131231 12
 
2.0%
20170417 11
 
1.9%
20121231 11
 
1.9%
Other values (247) 432
72.8%
ValueCountFrequency (%)
20001214 5
0.8%
20001220 1
 
0.2%
20001227 4
0.7%
20010103 1
 
0.2%
20010207 1
 
0.2%
20010214 1
 
0.2%
20010301 1
 
0.2%
20010502 1
 
0.2%
20010524 3
0.5%
20010713 1
 
0.2%
ValueCountFrequency (%)
20240213 1
0.2%
20240125 1
0.2%
20240115 1
0.2%
20231229 2
0.3%
20230403 1
0.2%
20221124 1
0.2%
20211122 1
0.2%
20210914 1
0.2%
20210711 1
0.2%
20210607 1
0.2%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
처분확정
593 

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 593
100.0%

Length

2024-05-10T23:44:48.014314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:44:48.338269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 593
100.0%

처분명
Text

Distinct114
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:48.811556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length52
Mean length8.6762226
Min length2

Characters and Unicode

Total characters5145
Distinct characters133
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)9.9%

Sample

1st row성매매알선 등으로 영업정지
2nd row2022년 공중위생교육 미이수 관련 과태료 부과
3rd row과태료 확정 부과
4th row사전통지기간 내 납부로 20% 감면 (48만원)
5th row사전통지 기간 내 과태료 납부로 60만원에서 20% 감면 (48만원)
ValueCountFrequency (%)
과태료부과 124
 
14.8%
영업정지 85
 
10.1%
영업소폐쇄 80
 
9.5%
개선명령 60
 
7.1%
경고 55
 
6.5%
과징금부과 42
 
5.0%
및 26
 
3.1%
2월 20
 
2.4%
과태료 16
 
1.9%
갈음 12
 
1.4%
Other values (145) 320
38.1%
2024-05-10T23:44:49.927143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 506
 
9.8%
업 267
 
5.2%
0 261
 
5.1%
부 259
 
5.0%
영 249
 
4.8%
248
 
4.8%
2 230
 
4.5%
료 184
 
3.6%
태 184
 
3.6%
지 159
 
3.1%
Other values (123) 2598
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3556
69.1%
Decimal Number 876
 
17.0%
Space Separator 248
 
4.8%
Other Punctuation 171
 
3.3%
Close Punctuation 136
 
2.6%
Open Punctuation 134
 
2.6%
Math Symbol 17
 
0.3%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 506
 
14.2%
업 267
 
7.5%
부 259
 
7.3%
영 249
 
7.0%
료 184
 
5.2%
태 184
 
5.2%
지 159
 
4.5%
정 157
 
4.4%
소 120
 
3.4%
폐 106
 
3.0%
Other values (99) 1365
38.4%
Decimal Number
ValueCountFrequency (%)
0 261
29.8%
2 230
26.3%
1 159
18.2%
3 61
 
7.0%
8 47
 
5.4%
5 35
 
4.0%
7 24
 
2.7%
4 23
 
2.6%
6 19
 
2.2%
9 17
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 137
80.1%
, 17
 
9.9%
% 11
 
6.4%
: 2
 
1.2%
* 2
 
1.2%
/ 1
 
0.6%
※ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 135
99.3%
] 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 133
99.3%
[ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
248
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3556
69.1%
Common 1589
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 506
 
14.2%
업 267
 
7.5%
부 259
 
7.3%
영 249
 
7.0%
료 184
 
5.2%
태 184
 
5.2%
지 159
 
4.5%
정 157
 
4.4%
소 120
 
3.4%
폐 106
 
3.0%
Other values (99) 1365
38.4%
Common
ValueCountFrequency (%)
0 261
16.4%
248
15.6%
2 230
14.5%
1 159
10.0%
. 137
8.6%
) 135
8.5%
( 133
8.4%
3 61
 
3.8%
8 47
 
3.0%
5 35
 
2.2%
Other values (14) 143
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3556
69.1%
ASCII 1588
30.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 506
 
14.2%
업 267
 
7.5%
부 259
 
7.3%
영 249
 
7.0%
료 184
 
5.2%
태 184
 
5.2%
지 159
 
4.5%
정 157
 
4.4%
소 120
 
3.4%
폐 106
 
3.0%
Other values (99) 1365
38.4%
ASCII
ValueCountFrequency (%)
0 261
16.4%
248
15.6%
2 230
14.5%
1 159
10.0%
. 137
8.6%
) 135
8.5%
( 133
8.4%
3 61
 
3.8%
8 47
 
3.0%
5 35
 
2.2%
Other values (13) 142
8.9%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

법적근거
Text

Distinct106
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:50.693501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length12.365936
Min length2

Characters and Unicode

Total characters7333
Distinct characters76
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)9.3%

Sample

1st row법 제11조제1항제8호
2nd row법 제22조제2항제6호
3rd row법 제22조제2항제6호
4th row법 제22조제2항제6호
5th row법 제22조제2항제6호
ValueCountFrequency (%)
공중위생관리법 307
25.3%
법 146
12.0%
제11조 130
 
10.7%
제17조 71
 
5.8%
제11조제1항 51
 
4.2%
제22조제2항제6호 41
 
3.4%
제4조 35
 
2.9%
제3조제3항 29
 
2.4%
제1항 28
 
2.3%
제3조 24
 
2.0%
Other values (98) 353
29.1%
2024-05-10T23:44:52.144735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 908
12.4%
1 766
10.4%
625
 
8.5%
법 614
 
8.4%
조 612
 
8.3%
위 430
 
5.9%
생 429
 
5.9%
중 428
 
5.8%
공 428
 
5.8%
관 382
 
5.2%
Other values (66) 1711
23.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5254
71.6%
Decimal Number 1377
 
18.8%
Space Separator 625
 
8.5%
Other Punctuation 69
 
0.9%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 908
17.3%
법 614
11.7%
조 612
11.6%
위 430
8.2%
생 429
8.2%
중 428
8.1%
공 428
8.1%
관 382
7.3%
리 379
7.2%
항 252
 
4.8%
Other values (51) 392
7.5%
Decimal Number
ValueCountFrequency (%)
1 766
55.6%
2 182
 
13.2%
7 146
 
10.6%
3 110
 
8.0%
4 82
 
6.0%
6 42
 
3.1%
8 15
 
1.1%
0 14
 
1.0%
9 13
 
0.9%
5 7
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 68
98.6%
. 1
 
1.4%
Space Separator
ValueCountFrequency (%)
625
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5254
71.6%
Common 2079
 
28.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 908
17.3%
법 614
11.7%
조 612
11.6%
위 430
8.2%
생 429
8.2%
중 428
8.1%
공 428
8.1%
관 382
7.3%
리 379
7.2%
항 252
 
4.8%
Other values (51) 392
7.5%
Common
ValueCountFrequency (%)
1 766
36.8%
625
30.1%
2 182
 
8.8%
7 146
 
7.0%
3 110
 
5.3%
4 82
 
3.9%
, 68
 
3.3%
6 42
 
2.0%
8 15
 
0.7%
0 14
 
0.7%
Other values (5) 29
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5254
71.6%
ASCII 2079
 
28.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 908
17.3%
법 614
11.7%
조 612
11.6%
위 430
8.2%
생 429
8.2%
중 428
8.1%
공 428
8.1%
관 382
7.3%
리 379
7.2%
항 252
 
4.8%
Other values (51) 392
7.5%
ASCII
ValueCountFrequency (%)
1 766
36.8%
625
30.1%
2 182
 
8.8%
7 146
 
7.0%
3 110
 
5.3%
4 82
 
3.9%
, 68
 
3.3%
6 42
 
2.0%
8 15
 
0.7%
0 14
 
0.7%
Other values (5) 29
 
1.4%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct264
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20100836
Minimum20001214
Maximum20240125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-05-10T23:44:52.763622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001214
5-th percentile20011125
Q120060306
median20091125
Q320160425
95-th percentile20201023
Maximum20240125
Range238911
Interquartile range (IQR)100119

Descriptive statistics

Standard deviation60189.568
Coefficient of variation (CV)0.0029943813
Kurtosis-0.99866214
Mean20100836
Median Absolute Deviation (MAD)49386
Skewness0.29680708
Sum1.1919796 × 1010
Variance3.6227841 × 109
MonotonicityNot monotonic
2024-05-10T23:44:53.494189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201023 32
 
5.4%
20191118 22
 
3.7%
20091125 18
 
3.0%
20070405 15
 
2.5%
20170630 14
 
2.4%
20170901 13
 
2.2%
20071206 13
 
2.2%
20131231 12
 
2.0%
20100223 11
 
1.9%
20120209 11
 
1.9%
Other values (254) 432
72.8%
ValueCountFrequency (%)
20001214 4
0.7%
20001220 1
 
0.2%
20001227 2
0.3%
20010103 1
 
0.2%
20010126 1
 
0.2%
20010214 1
 
0.2%
20010301 1
 
0.2%
20010502 1
 
0.2%
20010524 3
0.5%
20010718 1
 
0.2%
ValueCountFrequency (%)
20240125 1
 
0.2%
20231231 3
 
0.5%
20231229 1
 
0.2%
20221124 1
 
0.2%
20220104 1
 
0.2%
20210711 1
 
0.2%
20210703 1
 
0.2%
20210630 1
 
0.2%
20210607 1
 
0.2%
20201023 32
5.4%

위반내용
Text

Distinct226
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:54.506303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length136
Median length51
Mean length14.487352
Min length2

Characters and Unicode

Total characters8591
Distinct characters259
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

Unique134 ?
Unique (%)22.6%

Sample

1st row성매매알선 및 장소제공
2nd row2022년 공중위생교육 미이수
3rd row2022년도 공중위생교육 미이수
4th row2022년도 위생교육 미이수
5th row2022년도 위생교육 미이수
ValueCountFrequency (%)
미이수 74
 
4.3%
장소제공 67
 
3.9%
공중위생교육 59
 
3.4%
및 49
 
2.8%
위생교육 47
 
2.7%
청소년 47
 
2.7%
미수료 34
 
2.0%
2019년 32
 
1.8%
청소년이성혼숙 30
 
1.7%
미이행 27
 
1.6%
Other values (412) 1272
73.2%
2024-05-10T23:44:56.222965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1209
 
14.1%
위 259
 
3.0%
년 247
 
2.9%
소 231
 
2.7%
이 228
 
2.7%
미 226
 
2.6%
업 194
 
2.3%
1 190
 
2.2%
수 169
 
2.0%
공 166
 
1.9%
Other values (249) 5472
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6481
75.4%
Space Separator 1209
 
14.1%
Decimal Number 635
 
7.4%
Close Punctuation 92
 
1.1%
Open Punctuation 91
 
1.1%
Other Punctuation 75
 
0.9%
Dash Punctuation 5
 
0.1%
Uppercase Letter 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 259
 
4.0%
년 247
 
3.8%
소 231
 
3.6%
이 228
 
3.5%
미 226
 
3.5%
업 194
 
3.0%
수 169
 
2.6%
공 166
 
2.6%
생 166
 
2.6%
교 149
 
2.3%
Other values (227) 4446
68.6%
Decimal Number
ValueCountFrequency (%)
1 190
29.9%
0 164
25.8%
2 160
25.2%
9 33
 
5.2%
8 27
 
4.3%
6 25
 
3.9%
3 18
 
2.8%
5 8
 
1.3%
7 6
 
0.9%
4 4
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 49
65.3%
. 20
26.7%
: 6
 
8.0%
Close Punctuation
ValueCountFrequency (%)
) 91
98.9%
] 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 90
98.9%
[ 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
1209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6481
75.4%
Common 2108
 
24.5%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 259
 
4.0%
년 247
 
3.8%
소 231
 
3.6%
이 228
 
3.5%
미 226
 
3.5%
업 194
 
3.0%
수 169
 
2.6%
공 166
 
2.6%
생 166
 
2.6%
교 149
 
2.3%
Other values (227) 4446
68.6%
Common
ValueCountFrequency (%)
1209
57.4%
1 190
 
9.0%
0 164
 
7.8%
2 160
 
7.6%
) 91
 
4.3%
( 90
 
4.3%
, 49
 
2.3%
9 33
 
1.6%
8 27
 
1.3%
6 25
 
1.2%
Other values (10) 70
 
3.3%
Latin
ValueCountFrequency (%)
C 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6481
75.4%
ASCII 2109
 
24.5%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1209
57.3%
1 190
 
9.0%
0 164
 
7.8%
2 160
 
7.6%
) 91
 
4.3%
( 90
 
4.3%
, 49
 
2.3%
9 33
 
1.6%
8 27
 
1.3%
6 25
 
1.2%
Other values (11) 71
 
3.4%
Hangul
ValueCountFrequency (%)
위 259
 
4.0%
년 247
 
3.8%
소 231
 
3.6%
이 228
 
3.5%
미 226
 
3.5%
업 194
 
3.0%
수 169
 
2.6%
공 166
 
2.6%
생 166
 
2.6%
교 149
 
2.3%
Other values (227) 4446
68.6%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

처분내용
Text

Distinct114
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-05-10T23:44:56.920622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length52
Mean length8.6762226
Min length2

Characters and Unicode

Total characters5145
Distinct characters133
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)9.9%

Sample

1st row성매매알선 등으로 영업정지
2nd row2022년 공중위생교육 미이수 관련 과태료 부과
3rd row과태료 확정 부과
4th row사전통지기간 내 납부로 20% 감면 (48만원)
5th row사전통지 기간 내 과태료 납부로 60만원에서 20% 감면 (48만원)
ValueCountFrequency (%)
과태료부과 124
 
14.8%
영업정지 85
 
10.1%
영업소폐쇄 80
 
9.5%
개선명령 60
 
7.1%
경고 55
 
6.5%
과징금부과 42
 
5.0%
및 26
 
3.1%
2월 20
 
2.4%
과태료 16
 
1.9%
갈음 12
 
1.4%
Other values (145) 320
38.1%
2024-05-10T23:44:58.345023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 506
 
9.8%
업 267
 
5.2%
0 261
 
5.1%
부 259
 
5.0%
영 249
 
4.8%
248
 
4.8%
2 230
 
4.5%
료 184
 
3.6%
태 184
 
3.6%
지 159
 
3.1%
Other values (123) 2598
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3556
69.1%
Decimal Number 876
 
17.0%
Space Separator 248
 
4.8%
Other Punctuation 171
 
3.3%
Close Punctuation 136
 
2.6%
Open Punctuation 134
 
2.6%
Math Symbol 17
 
0.3%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 506
 
14.2%
업 267
 
7.5%
부 259
 
7.3%
영 249
 
7.0%
료 184
 
5.2%
태 184
 
5.2%
지 159
 
4.5%
정 157
 
4.4%
소 120
 
3.4%
폐 106
 
3.0%
Other values (99) 1365
38.4%
Decimal Number
ValueCountFrequency (%)
0 261
29.8%
2 230
26.3%
1 159
18.2%
3 61
 
7.0%
8 47
 
5.4%
5 35
 
4.0%
7 24
 
2.7%
4 23
 
2.6%
6 19
 
2.2%
9 17
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 137
80.1%
, 17
 
9.9%
% 11
 
6.4%
: 2
 
1.2%
* 2
 
1.2%
/ 1
 
0.6%
※ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 135
99.3%
] 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 133
99.3%
[ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
248
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3556
69.1%
Common 1589
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 506
 
14.2%
업 267
 
7.5%
부 259
 
7.3%
영 249
 
7.0%
료 184
 
5.2%
태 184
 
5.2%
지 159
 
4.5%
정 157
 
4.4%
소 120
 
3.4%
폐 106
 
3.0%
Other values (99) 1365
38.4%
Common
ValueCountFrequency (%)
0 261
16.4%
248
15.6%
2 230
14.5%
1 159
10.0%
. 137
8.6%
) 135
8.5%
( 133
8.4%
3 61
 
3.8%
8 47
 
3.0%
5 35
 
2.2%
Other values (14) 143
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3556
69.1%
ASCII 1588
30.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 506
 
14.2%
업 267
 
7.5%
부 259
 
7.3%
영 249
 
7.0%
료 184
 
5.2%
태 184
 
5.2%
지 159
 
4.5%
정 157
 
4.4%
소 120
 
3.4%
폐 106
 
3.0%
Other values (99) 1365
38.4%
ASCII
ValueCountFrequency (%)
0 261
16.4%
248
15.6%
2 230
14.5%
1 159
10.0%
. 137
8.6%
) 135
8.5%
( 133
8.4%
3 61
 
3.8%
8 47
 
3.0%
5 35
 
2.2%
Other values (13) 142
8.9%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

처분기간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
582 
15
 
9
7
 
1
25
 
1

Length

Max length4
Median length4
Mean length3.9612142
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 582
98.1%
15 9
 
1.5%
7 1
 
0.2%
25 1
 
0.2%

Length

2024-05-10T23:44:58.996589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:44:59.457712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
98.1%
15 9
 
1.5%
7 1
 
0.2%
25 1
 
0.2%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct301
Distinct (%)52.8%
Missing23
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean194.1377
Minimum0
Maximum2091.97
Zeros7
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-05-10T23:44:59.960682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.489
Q132.355
median69.845
Q3180.82
95-th percentile938
Maximum2091.97
Range2091.97
Interquartile range (IQR)148.465

Descriptive statistics

Standard deviation348.18622
Coefficient of variation (CV)1.7935013
Kurtosis12.992127
Mean194.1377
Median Absolute Deviation (MAD)48.095
Skewness3.4581715
Sum110658.49
Variance121233.64
MonotonicityNot monotonic
2024-05-10T23:45:00.632638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.82 12
 
2.0%
26.0 9
 
1.5%
33.0 9
 
1.5%
52.08 9
 
1.5%
16.5 8
 
1.3%
0.0 7
 
1.2%
49.5 7
 
1.2%
1000.0 7
 
1.2%
82.28 7
 
1.2%
230.0 7
 
1.2%
Other values (291) 488
82.3%
(Missing) 23
 
3.9%
ValueCountFrequency (%)
0.0 7
1.2%
3.3 1
 
0.2%
6.6 1
 
0.2%
6.7 4
0.7%
8.25 5
0.8%
9.0 1
 
0.2%
9.14 2
 
0.3%
10.0 2
 
0.3%
11.0 1
 
0.2%
11.9 1
 
0.2%
ValueCountFrequency (%)
2091.97 1
 
0.2%
2079.63 2
 
0.3%
1979.21 5
0.8%
1728.14 5
0.8%
1359.21 1
 
0.2%
1300.0 1
 
0.2%
1295.94 3
0.5%
1294.03 1
 
0.2%
1136.0 1
 
0.2%
1000.0 7
1.2%

Interactions

2024-05-10T23:44:33.126664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:30.402286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:31.118760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:32.153867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:33.377332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:30.570618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:31.379857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:32.418788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:33.634181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:30.741488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:31.641201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:32.669706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:33.898062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:30.916116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:31.900471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:44:32.874562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:45:01.040638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.6540.6880.9910.9910.9110.176
업종명0.6541.0000.9790.6830.6820.2190.599
업태명0.6880.9791.0000.6950.6980.2190.757
지도점검일자0.9910.6830.6951.0001.0000.6110.275
위반일자0.9910.6820.6981.0001.0000.6110.256
처분기간0.9110.2190.2190.6110.6111.0001.000
영업장면적(㎡)0.1760.5990.7570.2750.2561.0001.000
2024-05-10T23:45:01.454453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명처분기간
업종명1.0000.8230.311
업태명0.8231.0000.311
처분기간0.3110.3111.000
2024-05-10T23:45:01.871474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자영업장면적(㎡)업종명업태명처분기간
처분일자1.0000.9990.999-0.1540.3110.2900.626
지도점검일자0.9991.0000.999-0.1520.3310.2910.240
위반일자0.9990.9991.000-0.1580.3300.2930.240
영업장면적(㎡)-0.154-0.152-0.1581.0000.2910.4160.943
업종명0.3110.3310.3300.2911.0000.8230.311
업태명0.2900.2910.2930.4160.8231.0000.311
처분기간0.6260.2400.2400.9430.3110.3111.000

Missing values

2024-05-10T23:44:34.282288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:44:35.047628image/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.
2024-05-10T23:44:35.427575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
03030000202404250125숙박업(일반)여관업동신여관서울특별시 성동구 왕십리로20길 39, (홍익동)서울특별시 성동구 홍익동 168번지20240125처분확정성매매알선 등으로 영업정지법 제11조제1항제8호20240125성매매알선 및 장소제공성매매알선 등으로 영업정지<NA>57.41
13030000202402192018-00002위생관리용역업위생관리용역업(주)아미티에이서울특별시 성동구 연무장13길 9, 아이템플 8층 837호 (성수동2가)서울특별시 성동구 성수동2가 273번지 19호 아이템플-83720240213처분확정2022년 공중위생교육 미이수 관련 과태료 부과법 제22조제2항제6호202312292022년 공중위생교육 미이수2022년 공중위생교육 미이수 관련 과태료 부과<NA>6.6
23030000202401262019-00001세탁업일반세탁업그린어스서울특별시 성동구 독서당로 223, 래미안 옥수 리버젠 상가 상가동 제지1층 제109-1호 (옥수동)서울특별시 성동구 옥수동 561번지 래미안 옥수 리버젠 상가20231229처분확정과태료 확정 부과법 제22조제2항제6호202312312022년도 공중위생교육 미이수과태료 확정 부과<NA>71.85
33030000202401252022-00036일반미용업일반미용업필름더서울서울특별시 성동구 왕십리로 106, 3층 (성수동1가)서울특별시 성동구 성수동1가 656번지 967호 동일모텔20240115처분확정사전통지기간 내 납부로 20% 감면 (48만원)법 제22조제2항제6호202312312022년도 위생교육 미이수사전통지기간 내 납부로 20% 감면 (48만원)<NA>185.95
43030000202401252015-00004위생관리용역업위생관리용역업(주)에이치엔씨네트워크서울특별시 성동구 연무장5길 18, 에이치디앤텍빌딩 4층 (성수동2가)서울특별시 성동구 성수동2가 314번지 7호 에이치디앤텍빌딩20231229처분확정사전통지 기간 내 과태료 납부로 60만원에서 20% 감면 (48만원)법 제22조제2항제6호202312312022년도 위생교육 미이수사전통지 기간 내 과태료 납부로 60만원에서 20% 감면 (48만원)<NA>193.0
53030000202305100083숙박업(일반)여관업리젠트호텔서울특별시 성동구 무학로2길 43, (도선동)서울특별시 성동구 도선동 144번지 0호20230403처분확정과징금부과법 제11조제1항제8호20220104청소년 이성(남녀) 혼숙과징금부과<NA>2091.97
63030000202212232022-00077일반미용업일반미용업엘린헤어서울특별시 성동구 왕십리로 328, 2층 (도선동)서울특별시 성동구 도선동 253번지 12호20221124처분확정개선명령공중위생관리법 제11조 및 같은법 시행규칙 제19조20221124영업장 내 소독기, 자외선살균기 등 미용기구 소독장비 미구비 (공중위생관리법 제3조 제1항)개선명령<NA>99.17
73030000202112140130숙박업(일반)여관업미르서울특별시 성동구 왕십리로20길 28-1, (도선동)서울특별시 성동구 도선동 2번지 3호20210914처분확정과징금부과법 제11조제1항제8호20210703청소년 이성(남녀) 혼숙과징금부과<NA>465.0
83030000202111222020-000025화장ㆍ분장 미용업메이크업업영래쉬(YOUNGLASH)서울특별시 성동구 왕십리로 410, L동 B126-1호 (하왕십리동, 센트라스)서울특별시 성동구 하왕십리동 1070번지 센트라스20211122처분확정과태료부과법 제22조제2항제6호202106302020년 위생교육 미이수과태료부과<NA>24.88
93030000202108180079숙박업(일반)여관업쥬방스모텔서울특별시 성동구 왕십리로22길 18, (도선동)서울특별시 성동구 도선동 99번지 0호20210711처분확정과징금부과법 제11조제1항제8호20210711청소년 이성 혼숙과징금부과<NA>527.0
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
58330300002001022712000410600200숙박업(일반)여관업대흥장여관<NA>서울특별시 성동구 마장동 산 566번지 34호20010207처분확정영업정지 2월공중위생관리법 제11조제1항20010126청소년 남녀혼숙장소제공영업정지 2월<NA>162.31
58430300002001022602000430100322이용업일반이용업무학<NA>서울특별시 성동구 행당동 산 318번지 36호20010214처분확정영업정지 15일공중위생관리법 제11조제1항20010214밀실설치영업정지 15일1587.98
58530300002001021602000430100333이용업일반이용업무지개<NA>서울특별시 성동구 성수동2가 산 19번지 12호20001227처분확정개선명령공중위생관리법 제11조제1항20001227밀실설치개선명령<NA>80.0
58630300002001020602000430100325이용업일반이용업대우<NA>서울특별시 성동구 금호동1가 산 1756번지 0호20001214처분확정영업소 영업정지 3월공중위생관리법 제7조제1항, 제11조제1항, 제22조제2항제1호20001214윤락,음란행위 묵인, 윤락,음란행위에 사용할 수 있는 기구 보관, 면허대여영업소 영업정지 3월<NA>26.0
58730300002001020602000430100343이용업일반이용업성진이용원<NA>서울특별시 성동구 용답동 산 235번지 2호20010103처분확정개선명령공중위생관리법 제10조, 제11조제1항20010103칸막이 및 밀실설치개선명령<NA>99.0
58830300002001020602000430100360이용업일반이용업대우이용원<NA>서울특별시 성동구 금호동1가 산 1756번지 0호20001214처분확정이용사 업무정지공중위생관리법 제7조제1항,제11조제1항,제22조제2항제1호20001214윤락,음란행위 묵인, 윤락,음란행위에 사용할 수 있는 기구 보관, 면허대여이용사 업무정지<NA>26.0
58930300002001020602000430100320이용업일반이용업문화<NA>서울특별시 성동구 상왕십리동 산 804번지 1호20001220처분확정영업정지 2월공중위생관리법 제7조제1항, 제11조제1항20001220윤락,음란행위 묵인영업정지 2월<NA>40.0
59030300002001020602000430100360이용업일반이용업대우이용원<NA>서울특별시 성동구 금호동1가 산 1756번지 0호20001214처분확정영업소 영업정지 3월공중위생관리법 제7조제1항, 제11조제1항, 제22조제2항제1호20011214윤락,음란행위묵인, 윤락,음란행위에 사용할 수 있는 기구 보관, 면허대여영업소 영업정지 3월<NA>26.0
59130300002001020602000430100325이용업일반이용업대우<NA>서울특별시 성동구 금호동1가 산 1756번지 0호20001214처분확정과태료 50만원법 제7조제1항, 제11조제1항, 제22조제2항제1호20001214윤락,음란행위 묵인, 윤락,음락행위에 사용할 수 있는 기구 보관, 면허대여과태료 50만원<NA>26.0
59230300002001020602000430100325이용업일반이용업대우<NA>서울특별시 성동구 금호동1가 산 1756번지 0호20001214처분확정이용사 업무정지 4월법 제7조제1항, 제11조제1항, 제22조제2항제1호20001214윤락,음란행위 묵인, 윤락,음란행위에 사용할 수 있는 기구보관, 면허대여이용사 업무정지 4월<NA>26.0

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
21303000020120227289세탁업운동화전문세탁업운동화구두빨래방서울특별시 성동구 마조로9길 6-3, (행당동)서울특별시 성동구 행당동 1번지 90호20120209처분확정과태료부과공중위생관리법제17조201202092011년 위생교육 미수료과태료부과<NA>16.324
03030000200307090148이용업일반이용업금화<NA>서울특별시 성동구 성수동2가 289번지 273호20030524처분확정업무정지2월(2003.7.13~9.12)공중위생관리법 제11조20030524윤락알선업무정지2월(2003.7.13~9.12)<NA>69.02
13030000200307090148이용업일반이용업금화<NA>서울특별시 성동구 성수동2가 289번지 273호20030524처분확정영업정지2월(2003.7.13~9.12)공중위생관리법 제11조20030524윤락알선영업정지2월(2003.7.13~9.12)<NA>69.02
23030000200307160151이용업일반이용업전풍이용원<NA>서울특별시 성동구 도선동 58번지20030101처분확정업무정지2월(2003.8.1~9.30)공중위생관리법 제11조20030101윤락알선업무정지2월(2003.8.1~9.30)<NA>150.02
33030000200307160151이용업일반이용업전풍이용원<NA>서울특별시 성동구 도선동 58번지20030101처분확정영업정지2월(2003.8.1~9.30)공중위생관리법 제11조20030101윤락알선영업정지2월(2003.8.1~9.30)<NA>150.02
43030000200307310073이용업일반이용업동성<NA>서울특별시 성동구 하왕십리동 966번지 90호20030120처분확정업무정지2월(2003.8.11~10.10)공중위생관리법 제11조20030120음란행위(1차)업무정지2월(2003.8.11~10.10)<NA>54.092
53030000200307310073이용업일반이용업동성<NA>서울특별시 성동구 하왕십리동 966번지 90호20030120처분확정영업정지2월(2003.8.11~10.10)공중위생관리법 제11조20030120음란행위(1차)영업정지2월(2003.8.11~10.10)<NA>54.092
63030000200401150083이용업일반이용업장성서울특별시 성동구 동일로 81, (성수동2가)서울특별시 성동구 성수동2가 275번지 8호20040114처분확정과징금부과공중위생관리법20040114밀실설치 및 칸막이설치과징금부과<NA>95.352
73030000200505100142숙박업(일반)여관업대흥장여관서울특별시 성동구 마장로27길 2-1, (마장동)서울특별시 성동구 마장동 566번지 34호20050206처분확정영업정지2월 과징금180만원공중위생법11조20050206청소년남녀혼숙영업정지2월 과징금180만원<NA>270.02
8303000020070730059목욕장업공동탕업홍보석불가마사우나서울특별시 성동구 독서당로 336, (금호동4가)서울특별시 성동구 금호동4가 97번지 1호20070730처분확정경고제4조20070701청소년시간외출입경고<NA>761.182