Overview

Dataset statistics

Number of variables17
Number of observations746
Missing cells1220
Missing cells (%)9.6%
Duplicate rows43
Duplicate rows (%)5.8%
Total size in memory103.6 KiB
Average record size in memory142.2 B

Variable types

Categorical4
Numeric5
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-10374/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 43 (5.8%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 1 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
처분기간 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 처분기간 and 1 other fieldsHigh correlation
업태명 is highly overall correlated with 업종명High correlation
소재지도로명 has 457 (61.3%) missing valuesMissing
법적근거 has 24 (3.2%) missing valuesMissing
처분기간 has 723 (96.9%) missing valuesMissing
영업장면적(㎡) has 10 (1.3%) missing valuesMissing
영업장면적(㎡) has 12 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-03 21:59:56.152454
Analysis finished2024-05-03 22:00:10.094889
Duration13.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3050000
746 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 746
100.0%

Length

2024-05-03T22:00:10.330871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:00:10.647529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 746
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct309
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20115894
Minimum20010102
Maximum20240117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-03T22:00:10.998273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010102
5-th percentile20030951
Q120070501
median20110405
Q320170427
95-th percentile20201118
Maximum20240117
Range230015
Interquartile range (IQR)99926

Descriptive statistics

Standard deviation57618.965
Coefficient of variation (CV)0.0028643502
Kurtosis-1.1503622
Mean20115894
Median Absolute Deviation (MAD)49904
Skewness0.12322896
Sum1.5006457 × 1010
Variance3.3199451 × 109
MonotonicityNot monotonic
2024-05-03T22:00:11.543768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190422 21
 
2.8%
20130304 20
 
2.7%
20050907 17
 
2.3%
20200804 15
 
2.0%
20180412 15
 
2.0%
20170427 12
 
1.6%
20160309 11
 
1.5%
20080527 11
 
1.5%
20150401 10
 
1.3%
20040105 10
 
1.3%
Other values (299) 604
81.0%
ValueCountFrequency (%)
20010102 1
 
0.1%
20010113 1
 
0.1%
20020107 1
 
0.1%
20020204 2
0.3%
20020207 4
0.5%
20020430 4
0.5%
20020502 4
0.5%
20020503 1
 
0.1%
20020605 1
 
0.1%
20020628 1
 
0.1%
ValueCountFrequency (%)
20240117 1
 
0.1%
20231106 1
 
0.1%
20230522 3
0.4%
20230512 1
 
0.1%
20230427 1
 
0.1%
20230424 1
 
0.1%
20230324 1
 
0.1%
20230316 1
 
0.1%
20230314 1
 
0.1%
20230214 1
 
0.1%

교부번호
Text

Distinct342
Distinct (%)45.9%
Missing1
Missing (%)0.1%
Memory size6.0 KiB
2024-05-03T22:00:12.302502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length4.6845638
Min length2

Characters and Unicode

Total characters3490
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

Unique189 ?
Unique (%)25.4%

Sample

1st row02300410600130
2nd row0012
3rd row0012
4th row0012
5th row0012
ValueCountFrequency (%)
0063 17
 
2.3%
0090 16
 
2.1%
0067 10
 
1.3%
0066 10
 
1.3%
0203 10
 
1.3%
0012 9
 
1.2%
0078 8
 
1.1%
0504 8
 
1.1%
0025 7
 
0.9%
0024 7
 
0.9%
Other values (332) 643
86.3%
2024-05-03T22:00:13.505826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1411
40.4%
1 444
 
12.7%
2 377
 
10.8%
3 239
 
6.8%
4 193
 
5.5%
6 170
 
4.9%
8 167
 
4.8%
7 158
 
4.5%
9 147
 
4.2%
5 141
 
4.0%
Other values (2) 43
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3447
98.8%
Dash Punctuation 42
 
1.2%
Other Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1411
40.9%
1 444
 
12.9%
2 377
 
10.9%
3 239
 
6.9%
4 193
 
5.6%
6 170
 
4.9%
8 167
 
4.8%
7 158
 
4.6%
9 147
 
4.3%
5 141
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Other Letter
ValueCountFrequency (%)
원 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3489
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1411
40.4%
1 444
 
12.7%
2 377
 
10.8%
3 239
 
6.9%
4 193
 
5.5%
6 170
 
4.9%
8 167
 
4.8%
7 158
 
4.5%
9 147
 
4.2%
5 141
 
4.0%
Hangul
ValueCountFrequency (%)
원 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3489
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1411
40.4%
1 444
 
12.7%
2 377
 
10.8%
3 239
 
6.9%
4 193
 
5.5%
6 170
 
4.9%
8 167
 
4.8%
7 158
 
4.5%
9 147
 
4.2%
5 141
 
4.0%
Hangul
ValueCountFrequency (%)
원 1
100.0%

업종명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
숙박업(일반)
275 
목욕장업
106 
이용업
101 
위생관리용역업
65 
일반미용업
62 
Other values (9)
137 

Length

Max length12
Median length7
Mean length5.3565684
Min length3

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 275
36.9%
목욕장업 106
 
14.2%
이용업 101
 
13.5%
위생관리용역업 65
 
8.7%
일반미용업 62
 
8.3%
세탁업 48
 
6.4%
피부미용업 35
 
4.7%
미용업 26
 
3.5%
종합미용업 11
 
1.5%
네일미용업 10
 
1.3%
Other values (4) 7
 
0.9%

Length

2024-05-03T22:00:14.505979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 275
36.6%
목욕장업 106
 
14.1%
이용업 101
 
13.4%
위생관리용역업 65
 
8.6%
일반미용업 65
 
8.6%
세탁업 48
 
6.4%
피부미용업 39
 
5.2%
미용업 26
 
3.5%
네일미용업 15
 
2.0%
종합미용업 11
 
1.5%

업태명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
여관업
222 
일반이용업
101 
일반미용업
93 
위생관리용역업
64 
공동탕업
51 
Other values (15)
215 

Length

Max length14
Median length10
Mean length5.0455764
Min length2

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 222
29.8%
일반이용업 101
13.5%
일반미용업 93
12.5%
위생관리용역업 64
 
8.6%
공동탕업 51
 
6.8%
공동탕업+찜질시설서비스영업 49
 
6.6%
일반세탁업 45
 
6.0%
피부미용업 35
 
4.7%
여인숙업 32
 
4.3%
네일아트업 20
 
2.7%
Other values (10) 34
 
4.6%

Length

2024-05-03T22:00:15.101959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여관업 222
29.6%
일반이용업 101
13.5%
일반미용업 93
12.4%
위생관리용역업 65
 
8.7%
공동탕업 51
 
6.8%
공동탕업+찜질시설서비스영업 49
 
6.5%
일반세탁업 45
 
6.0%
피부미용업 35
 
4.7%
여인숙업 32
 
4.3%
네일아트업 20
 
2.7%
Other values (9) 36
 
4.8%

업소명
Text

Distinct439
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-03T22:00:15.757871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length4.9048257
Min length1

Characters and Unicode

Total characters3659
Distinct characters396
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

Unique300 ?
Unique (%)40.2%

Sample

1st row우정
2nd row우정
3rd row우정
4th row우정
5th row우정
ValueCountFrequency (%)
이용원 13
 
1.6%
우정 10
 
1.2%
연수불가마사우나 9
 
1.1%
한일 9
 
1.1%
우성불한증막 9
 
1.1%
주주헤어클럽 8
 
1.0%
황진이 7
 
0.9%
힐링테라피 7
 
0.9%
이문탕 6
 
0.7%
motel 6
 
0.7%
Other values (459) 725
89.6%
2024-05-03T22:00:16.897343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 98
 
2.7%
우 83
 
2.3%
주 83
 
2.3%
사 80
 
2.2%
) 78
 
2.1%
( 78
 
2.1%
장 77
 
2.1%
텔 68
 
1.9%
원 66
 
1.8%
63
 
1.7%
Other values (386) 2885
78.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3179
86.9%
Uppercase Letter 123
 
3.4%
Lowercase Letter 82
 
2.2%
Close Punctuation 78
 
2.1%
Open Punctuation 78
 
2.1%
Space Separator 63
 
1.7%
Decimal Number 48
 
1.3%
Other Punctuation 6
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 98
 
3.1%
우 83
 
2.6%
주 83
 
2.6%
사 80
 
2.5%
장 77
 
2.4%
텔 68
 
2.1%
원 66
 
2.1%
스 60
 
1.9%
모 56
 
1.8%
리 55
 
1.7%
Other values (337) 2453
77.2%
Uppercase Letter
ValueCountFrequency (%)
E 17
13.8%
O 12
 
9.8%
S 12
 
9.8%
T 7
 
5.7%
M 7
 
5.7%
B 7
 
5.7%
C 7
 
5.7%
L 6
 
4.9%
I 6
 
4.9%
K 6
 
4.9%
Other values (11) 36
29.3%
Lowercase Letter
ValueCountFrequency (%)
e 15
18.3%
l 14
17.1%
t 14
17.1%
o 12
14.6%
m 6
 
7.3%
y 6
 
7.3%
r 5
 
6.1%
i 2
 
2.4%
b 2
 
2.4%
a 2
 
2.4%
Other values (4) 4
 
4.9%
Decimal Number
ValueCountFrequency (%)
2 23
47.9%
0 12
25.0%
1 8
 
16.7%
4 4
 
8.3%
7 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
, 1
16.7%
& 1
16.7%
' 1
16.7%
？ 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3179
86.9%
Common 275
 
7.5%
Latin 205
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 98
 
3.1%
우 83
 
2.6%
주 83
 
2.6%
사 80
 
2.5%
장 77
 
2.4%
텔 68
 
2.1%
원 66
 
2.1%
스 60
 
1.9%
모 56
 
1.8%
리 55
 
1.7%
Other values (337) 2453
77.2%
Latin
ValueCountFrequency (%)
E 17
 
8.3%
e 15
 
7.3%
l 14
 
6.8%
t 14
 
6.8%
O 12
 
5.9%
S 12
 
5.9%
o 12
 
5.9%
T 7
 
3.4%
M 7
 
3.4%
B 7
 
3.4%
Other values (25) 88
42.9%
Common
ValueCountFrequency (%)
) 78
28.4%
( 78
28.4%
63
22.9%
2 23
 
8.4%
0 12
 
4.4%
1 8
 
2.9%
4 4
 
1.5%
. 2
 
0.7%
- 2
 
0.7%
, 1
 
0.4%
Other values (4) 4
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3179
86.9%
ASCII 479
 
13.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 98
 
3.1%
우 83
 
2.6%
주 83
 
2.6%
사 80
 
2.5%
장 77
 
2.4%
텔 68
 
2.1%
원 66
 
2.1%
스 60
 
1.9%
모 56
 
1.8%
리 55
 
1.7%
Other values (337) 2453
77.2%
ASCII
ValueCountFrequency (%)
) 78
16.3%
( 78
16.3%
63
13.2%
2 23
 
4.8%
E 17
 
3.5%
e 15
 
3.1%
l 14
 
2.9%
t 14
 
2.9%
O 12
 
2.5%
0 12
 
2.5%
Other values (38) 153
31.9%
None
ValueCountFrequency (%)
？ 1
100.0%

소재지도로명
Text

MISSING 

Distinct214
Distinct (%)74.0%
Missing457
Missing (%)61.3%
Memory size6.0 KiB
2024-05-03T22:00:17.489090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length32.363322
Min length23

Characters and Unicode

Total characters9353
Distinct characters177
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

Unique171 ?
Unique (%)59.2%

Sample

1st row서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)
2nd row서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)
3rd row서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)
4th row서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)
5th row서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)
ValueCountFrequency (%)
서울특별시 289
 
16.8%
동대문구 289
 
16.8%
장안동 56
 
3.3%
1층 42
 
2.4%
전농동 41
 
2.4%
답십리동 34
 
2.0%
용두동 30
 
1.7%
2층 23
 
1.3%
제기동 21
 
1.2%
사가정로 21
 
1.2%
Other values (369) 871
50.7%
2024-05-03T22:00:18.899343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1433
 
15.3%
동 626
 
6.7%
, 382
 
4.1%
1 363
 
3.9%
대 350
 
3.7%
문 323
 
3.5%
) 317
 
3.4%
( 317
 
3.4%
시 314
 
3.4%
서 301
 
3.2%
Other values (167) 4627
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5421
58.0%
Space Separator 1433
 
15.3%
Decimal Number 1383
 
14.8%
Other Punctuation 382
 
4.1%
Close Punctuation 317
 
3.4%
Open Punctuation 317
 
3.4%
Dash Punctuation 64
 
0.7%
Math Symbol 19
 
0.2%
Uppercase Letter 17
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 626
 
11.5%
대 350
 
6.5%
문 323
 
6.0%
시 314
 
5.8%
서 301
 
5.6%
울 299
 
5.5%
로 296
 
5.5%
구 289
 
5.3%
별 289
 
5.3%
특 289
 
5.3%
Other values (147) 2045
37.7%
Decimal Number
ValueCountFrequency (%)
1 363
26.2%
2 228
16.5%
3 203
14.7%
0 125
 
9.0%
4 114
 
8.2%
6 88
 
6.4%
5 86
 
6.2%
8 77
 
5.6%
9 52
 
3.8%
7 47
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
B 6
35.3%
K 5
29.4%
S 5
29.4%
A 1
 
5.9%
Space Separator
ValueCountFrequency (%)
1433
100.0%
Other Punctuation
ValueCountFrequency (%)
, 382
100.0%
Close Punctuation
ValueCountFrequency (%)
) 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5421
58.0%
Common 3915
41.9%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 626
 
11.5%
대 350
 
6.5%
문 323
 
6.0%
시 314
 
5.8%
서 301
 
5.6%
울 299
 
5.5%
로 296
 
5.5%
구 289
 
5.3%
별 289
 
5.3%
특 289
 
5.3%
Other values (147) 2045
37.7%
Common
ValueCountFrequency (%)
1433
36.6%
, 382
 
9.8%
1 363
 
9.3%
) 317
 
8.1%
( 317
 
8.1%
2 228
 
5.8%
3 203
 
5.2%
0 125
 
3.2%
4 114
 
2.9%
6 88
 
2.2%
Other values (6) 345
 
8.8%
Latin
ValueCountFrequency (%)
B 6
35.3%
K 5
29.4%
S 5
29.4%
A 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5421
58.0%
ASCII 3932
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1433
36.4%
, 382
 
9.7%
1 363
 
9.2%
) 317
 
8.1%
( 317
 
8.1%
2 228
 
5.8%
3 203
 
5.2%
0 125
 
3.2%
4 114
 
2.9%
6 88
 
2.2%
Other values (10) 362
 
9.2%
Hangul
ValueCountFrequency (%)
동 626
 
11.5%
대 350
 
6.5%
문 323
 
6.0%
시 314
 
5.8%
서 301
 
5.6%
울 299
 
5.5%
로 296
 
5.5%
구 289
 
5.3%
별 289
 
5.3%
특 289
 
5.3%
Other values (147) 2045
37.7%

소재지지번
Text

Distinct487
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-03T22:00:19.515516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length31.683646
Min length22

Characters and Unicode

Total characters23636
Distinct characters203
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)47.3%

Sample

1st row서울특별시 동대문구 용두동 709번지 27호
2nd row서울특별시 동대문구 용두동 709번지 27호
3rd row서울특별시 동대문구 용두동 709번지 27호 (용일서길7-2)
4th row서울특별시 동대문구 용두동 709번지 27호 (용일서길7-2)
5th row서울특별시 동대문구 용두동 709번지 27호 (용일서길7-2)
ValueCountFrequency (%)
서울특별시 746
 
17.3%
동대문구 746
 
17.3%
장안동 152
 
3.5%
전농동 117
 
2.7%
용두동 103
 
2.4%
답십리동 93
 
2.2%
이문동 57
 
1.3%
제기동 54
 
1.3%
휘경동 52
 
1.2%
2호 52
 
1.2%
Other values (657) 2140
49.6%
2024-05-03T22:00:20.556849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5469
23.1%
동 1537
 
6.5%
문 829
 
3.5%
1 823
 
3.5%
지 809
 
3.4%
대 770
 
3.3%
서 763
 
3.2%
시 759
 
3.2%
별 747
 
3.2%
구 747
 
3.2%
Other values (193) 10383
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13149
55.6%
Space Separator 5469
23.1%
Decimal Number 4275
 
18.1%
Open Punctuation 295
 
1.2%
Close Punctuation 295
 
1.2%
Dash Punctuation 67
 
0.3%
Uppercase Letter 37
 
0.2%
Other Punctuation 29
 
0.1%
Math Symbol 18
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1537
 
11.7%
문 829
 
6.3%
지 809
 
6.2%
대 770
 
5.9%
서 763
 
5.8%
시 759
 
5.8%
별 747
 
5.7%
구 747
 
5.7%
번 747
 
5.7%
특 746
 
5.7%
Other values (166) 4695
35.7%
Decimal Number
ValueCountFrequency (%)
1 823
19.3%
2 605
14.2%
3 508
11.9%
4 501
11.7%
6 339
7.9%
7 321
 
7.5%
0 319
 
7.5%
5 312
 
7.3%
9 285
 
6.7%
8 262
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 15
40.5%
K 15
40.5%
A 3
 
8.1%
B 2
 
5.4%
T 1
 
2.7%
P 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 25
86.2%
/ 2
 
6.9%
; 1
 
3.4%
& 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
g 1
50.0%
Space Separator
ValueCountFrequency (%)
5469
100.0%
Open Punctuation
ValueCountFrequency (%)
( 295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13149
55.6%
Common 10448
44.2%
Latin 39
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1537
 
11.7%
문 829
 
6.3%
지 809
 
6.2%
대 770
 
5.9%
서 763
 
5.8%
시 759
 
5.8%
별 747
 
5.7%
구 747
 
5.7%
번 747
 
5.7%
특 746
 
5.7%
Other values (166) 4695
35.7%
Common
ValueCountFrequency (%)
5469
52.3%
1 823
 
7.9%
2 605
 
5.8%
3 508
 
4.9%
4 501
 
4.8%
6 339
 
3.2%
7 321
 
3.1%
0 319
 
3.1%
5 312
 
3.0%
( 295
 
2.8%
Other values (9) 956
 
9.2%
Latin
ValueCountFrequency (%)
S 15
38.5%
K 15
38.5%
A 3
 
7.7%
B 2
 
5.1%
t 1
 
2.6%
g 1
 
2.6%
T 1
 
2.6%
P 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13149
55.6%
ASCII 10487
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5469
52.2%
1 823
 
7.8%
2 605
 
5.8%
3 508
 
4.8%
4 501
 
4.8%
6 339
 
3.2%
7 321
 
3.1%
0 319
 
3.0%
5 312
 
3.0%
( 295
 
2.8%
Other values (17) 995
 
9.5%
Hangul
ValueCountFrequency (%)
동 1537
 
11.7%
문 829
 
6.3%
지 809
 
6.2%
대 770
 
5.9%
서 763
 
5.8%
시 759
 
5.8%
별 747
 
5.7%
구 747
 
5.7%
번 747
 
5.7%
특 746
 
5.7%
Other values (166) 4695
35.7%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct322
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20113618
Minimum20001201
Maximum20230907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-03T22:00:20.834229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001201
5-th percentile20030728
Q120070402
median20110209
Q320161231
95-th percentile20200855
Maximum20230907
Range229706
Interquartile range (IQR)90828.75

Descriptive statistics

Standard deviation57689.988
Coefficient of variation (CV)0.0028682055
Kurtosis-1.1211742
Mean20113618
Median Absolute Deviation (MAD)49445.5
Skewness0.13397478
Sum1.5004759 × 1010
Variance3.3281347 × 109
MonotonicityNot monotonic
2024-05-03T22:00:21.104362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190101 31
 
4.2%
20130212 24
 
3.2%
20161231 21
 
2.8%
20050830 17
 
2.3%
20180101 15
 
2.0%
20200101 15
 
2.0%
20160513 14
 
1.9%
20151231 11
 
1.5%
20080107 11
 
1.5%
20140306 10
 
1.3%
Other values (312) 577
77.3%
ValueCountFrequency (%)
20001201 1
 
0.1%
20001213 1
 
0.1%
20011207 1
 
0.1%
20020104 2
0.3%
20020107 4
0.5%
20020330 4
0.5%
20020402 4
0.5%
20020403 1
 
0.1%
20020423 1
 
0.1%
20020505 1
 
0.1%
ValueCountFrequency (%)
20230907 1
0.1%
20230808 1
0.1%
20230420 1
0.1%
20230414 1
0.1%
20230412 1
0.1%
20230411 2
0.3%
20230403 1
0.1%
20230308 1
0.1%
20230303 1
0.1%
20230215 1
0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
처분확정
746 

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 746
100.0%

Length

2024-05-03T22:00:21.501929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:00:21.818946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 746
100.0%

처분명
Text

Distinct187
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-03T22:00:22.240464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length10.542895
Min length2

Characters and Unicode

Total characters7865
Distinct characters143
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

Unique114 ?
Unique (%)15.3%

Sample

1st row영업정지2월
2nd row영업정지1월
3rd row경고
4th row경고
5th row과태료부과 20만원
ValueCountFrequency (%)
경고 131
 
9.9%
개선명령 116
 
8.8%
과태료 88
 
6.7%
과태료부과 62
 
4.7%
부과 62
 
4.7%
영업소폐쇄 61
 
4.6%
영업정지 58
 
4.4%
및 54
 
4.1%
20만원 45
 
3.4%
16만원 36
 
2.7%
Other values (215) 607
46.0%
2024-05-03T22:00:23.147053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 666
 
8.5%
574
 
7.3%
0 519
 
6.6%
부 382
 
4.9%
원 296
 
3.8%
2 287
 
3.6%
1 262
 
3.3%
만 246
 
3.1%
업 245
 
3.1%
태 233
 
3.0%
Other values (133) 4155
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5196
66.1%
Decimal Number 1434
 
18.2%
Space Separator 574
 
7.3%
Other Punctuation 214
 
2.7%
Close Punctuation 211
 
2.7%
Open Punctuation 211
 
2.7%
Math Symbol 23
 
0.3%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 666
 
12.8%
부 382
 
7.4%
원 296
 
5.7%
만 246
 
4.7%
업 245
 
4.7%
태 233
 
4.5%
료 233
 
4.5%
영 230
 
4.4%
지 175
 
3.4%
정 157
 
3.0%
Other values (112) 2333
44.9%
Decimal Number
ValueCountFrequency (%)
0 519
36.2%
2 287
20.0%
1 262
18.3%
6 91
 
6.3%
3 68
 
4.7%
5 60
 
4.2%
8 59
 
4.1%
4 51
 
3.6%
9 20
 
1.4%
7 17
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 138
64.5%
, 67
31.3%
: 4
 
1.9%
% 3
 
1.4%
? 1
 
0.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5196
66.1%
Common 2669
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 666
 
12.8%
부 382
 
7.4%
원 296
 
5.7%
만 246
 
4.7%
업 245
 
4.7%
태 233
 
4.5%
료 233
 
4.5%
영 230
 
4.4%
지 175
 
3.4%
정 157
 
3.0%
Other values (112) 2333
44.9%
Common
ValueCountFrequency (%)
574
21.5%
0 519
19.4%
2 287
10.8%
1 262
9.8%
) 211
 
7.9%
( 211
 
7.9%
. 138
 
5.2%
6 91
 
3.4%
3 68
 
2.5%
, 67
 
2.5%
Other values (11) 241
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5183
65.9%
ASCII 2669
33.9%
Compat Jamo 13
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 666
 
12.8%
부 382
 
7.4%
원 296
 
5.7%
만 246
 
4.7%
업 245
 
4.7%
태 233
 
4.5%
료 233
 
4.5%
영 230
 
4.4%
지 175
 
3.4%
정 157
 
3.0%
Other values (111) 2320
44.8%
ASCII
ValueCountFrequency (%)
574
21.5%
0 519
19.4%
2 287
10.8%
1 262
9.8%
) 211
 
7.9%
( 211
 
7.9%
. 138
 
5.2%
6 91
 
3.4%
3 68
 
2.5%
, 67
 
2.5%
Other values (11) 241
9.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 13
100.0%

법적근거
Text

MISSING 

Distinct135
Distinct (%)18.7%
Missing24
Missing (%)3.2%
Memory size6.0 KiB
2024-05-03T22:00:23.640248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length48
Mean length13.781163
Min length2

Characters and Unicode

Total characters9950
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)7.1%

Sample

1st row공중위생관리법제11조제1항
2nd row공중위생관리법 제17조 제1항
3rd row공중위생관리법 제17조 제1항
4th row공중위생관리법 제17조 제1항
5th row공중위생관리법제11조제1항
ValueCountFrequency (%)
공중위생관리법 336
20.4%
법 229
 
13.9%
제17조 140
 
8.5%
같은법 81
 
4.9%
제11조제1항 56
 
3.4%
및 55
 
3.3%
제11조 43
 
2.6%
제3조제1항 40
 
2.4%
제1항 33
 
2.0%
시행규칙 32
 
1.9%
Other values (108) 603
36.6%
2024-05-03T22:00:24.490067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 1213
12.2%
1 973
 
9.8%
961
 
9.7%
법 801
 
8.1%
조 784
 
7.9%
위 494
 
5.0%
생 484
 
4.9%
공 465
 
4.7%
중 464
 
4.7%
관 449
 
4.5%
Other values (57) 2862
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6829
68.6%
Decimal Number 1909
 
19.2%
Space Separator 961
 
9.7%
Other Punctuation 99
 
1.0%
Open Punctuation 76
 
0.8%
Close Punctuation 76
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1213
17.8%
법 801
11.7%
조 784
11.5%
위 494
7.2%
생 484
 
7.1%
공 465
 
6.8%
중 464
 
6.8%
관 449
 
6.6%
리 447
 
6.5%
항 446
 
6.5%
Other values (41) 782
11.5%
Decimal Number
ValueCountFrequency (%)
1 973
51.0%
2 313
 
16.4%
7 241
 
12.6%
3 171
 
9.0%
4 103
 
5.4%
9 39
 
2.0%
6 33
 
1.7%
8 19
 
1.0%
0 16
 
0.8%
5 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 61
80.3%
「 15
 
19.7%
Close Punctuation
ValueCountFrequency (%)
) 61
80.3%
」 15
 
19.7%
Space Separator
ValueCountFrequency (%)
961
100.0%
Other Punctuation
ValueCountFrequency (%)
, 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6829
68.6%
Common 3121
31.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1213
17.8%
법 801
11.7%
조 784
11.5%
위 494
7.2%
생 484
 
7.1%
공 465
 
6.8%
중 464
 
6.8%
관 449
 
6.6%
리 447
 
6.5%
항 446
 
6.5%
Other values (41) 782
11.5%
Common
ValueCountFrequency (%)
1 973
31.2%
961
30.8%
2 313
 
10.0%
7 241
 
7.7%
3 171
 
5.5%
4 103
 
3.3%
, 99
 
3.2%
( 61
 
2.0%
) 61
 
2.0%
9 39
 
1.2%
Other values (6) 99
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6829
68.6%
ASCII 3091
31.1%
None 30
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 1213
17.8%
법 801
11.7%
조 784
11.5%
위 494
7.2%
생 484
 
7.1%
공 465
 
6.8%
중 464
 
6.8%
관 449
 
6.6%
리 447
 
6.5%
항 446
 
6.5%
Other values (41) 782
11.5%
ASCII
ValueCountFrequency (%)
1 973
31.5%
961
31.1%
2 313
 
10.1%
7 241
 
7.8%
3 171
 
5.5%
4 103
 
3.3%
, 99
 
3.2%
( 61
 
2.0%
) 61
 
2.0%
9 39
 
1.3%
Other values (4) 69
 
2.2%
None
ValueCountFrequency (%)
「 15
50.0%
」 15
50.0%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct350
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20113562
Minimum20001201
Maximum20230907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-03T22:00:25.002503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001201
5-th percentile20030750
Q120070402
median20105773
Q320161231
95-th percentile20200855
Maximum20230907
Range229706
Interquartile range (IQR)90829

Descriptive statistics

Standard deviation57556.272
Coefficient of variation (CV)0.0028615653
Kurtosis-1.118391
Mean20113562
Median Absolute Deviation (MAD)45450
Skewness0.14056393
Sum1.5004718 × 1010
Variance3.3127244 × 109
MonotonicityNot monotonic
2024-05-03T22:00:25.367022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190101 31
 
4.2%
20161231 22
 
2.9%
20130212 21
 
2.8%
20180101 16
 
2.1%
20050830 16
 
2.1%
20200101 15
 
2.0%
20151231 11
 
1.5%
20140306 10
 
1.3%
20181113 10
 
1.3%
20141231 9
 
1.2%
Other values (340) 585
78.4%
ValueCountFrequency (%)
20001201 1
 
0.1%
20001213 1
 
0.1%
20011207 1
 
0.1%
20020104 2
0.3%
20020107 2
0.3%
20020207 2
0.3%
20020330 4
0.5%
20020402 4
0.5%
20020403 1
 
0.1%
20020409 1
 
0.1%
ValueCountFrequency (%)
20230907 1
 
0.1%
20230425 3
0.4%
20230422 1
 
0.1%
20230410 1
 
0.1%
20230403 1
 
0.1%
20230331 1
 
0.1%
20230306 1
 
0.1%
20230227 1
 
0.1%
20230215 1
 
0.1%
20230203 1
 
0.1%

위반내용
Text

Distinct316
Distinct (%)42.6%
Missing5
Missing (%)0.7%
Memory size6.0 KiB
2024-05-03T22:00:25.797638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length80
Mean length18.57085
Min length1

Characters and Unicode

Total characters13761
Distinct characters290
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)27.8%

Sample

1st row윤락행위알선및장소제공
2nd row윤락행위장소제공
3rd row위생교육 미이수(2007년)
4th row위생교육 미이수(2007년)
5th row위생교육 미이수(2007년)
ValueCountFrequency (%)
위생교육 177
 
6.4%
미이수 143
 
5.2%
115
 
4.2%
청소년 55
 
2.0%
이성혼숙 49
 
1.8%
폐업신고 45
 
1.6%
멸실 35
 
1.3%
장소제공 34
 
1.2%
2018년 31
 
1.1%
및 30
 
1.1%
Other values (630) 2031
74.0%
2024-05-03T22:00:26.755585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2077
 
15.1%
0 536
 
3.9%
2 457
 
3.3%
위 388
 
2.8%
이 385
 
2.8%
미 378
 
2.7%
1 338
 
2.5%
년 332
 
2.4%
업 329
 
2.4%
소 280
 
2.0%
Other values (280) 8261
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8934
64.9%
Space Separator 2077
 
15.1%
Decimal Number 1851
 
13.5%
Other Punctuation 421
 
3.1%
Open Punctuation 167
 
1.2%
Close Punctuation 166
 
1.2%
Dash Punctuation 79
 
0.6%
Uppercase Letter 51
 
0.4%
Math Symbol 7
 
0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 388
 
4.3%
이 385
 
4.3%
미 378
 
4.2%
년 332
 
3.7%
업 329
 
3.7%
소 280
 
3.1%
수 278
 
3.1%
생 252
 
2.8%
교 235
 
2.6%
육 234
 
2.6%
Other values (245) 5843
65.4%
Decimal Number
ValueCountFrequency (%)
0 536
29.0%
2 457
24.7%
1 338
18.3%
5 88
 
4.8%
8 82
 
4.4%
6 80
 
4.3%
3 71
 
3.8%
7 70
 
3.8%
4 69
 
3.7%
9 60
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
C 17
33.3%
U 8
15.7%
F 7
13.7%
V 6
 
11.8%
T 6
 
11.8%
L 4
 
7.8%
P 1
 
2.0%
I 1
 
2.0%
N 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 251
59.6%
: 109
25.9%
, 28
 
6.7%
? 16
 
3.8%
/ 9
 
2.1%
※ 7
 
1.7%
; 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
m 2
33.3%
g 2
33.3%
l 2
33.3%
Space Separator
ValueCountFrequency (%)
2077
100.0%
Open Punctuation
ValueCountFrequency (%)
( 167
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8929
64.9%
Common 4770
34.7%
Latin 57
 
0.4%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 388
 
4.3%
이 385
 
4.3%
미 378
 
4.2%
년 332
 
3.7%
업 329
 
3.7%
소 280
 
3.1%
수 278
 
3.1%
생 252
 
2.8%
교 235
 
2.6%
육 234
 
2.6%
Other values (244) 5838
65.4%
Common
ValueCountFrequency (%)
2077
43.5%
0 536
 
11.2%
2 457
 
9.6%
1 338
 
7.1%
. 251
 
5.3%
( 167
 
3.5%
) 166
 
3.5%
: 109
 
2.3%
5 88
 
1.8%
8 82
 
1.7%
Other values (13) 499
 
10.5%
Latin
ValueCountFrequency (%)
C 17
29.8%
U 8
14.0%
F 7
12.3%
V 6
 
10.5%
T 6
 
10.5%
L 4
 
7.0%
m 2
 
3.5%
g 2
 
3.5%
l 2
 
3.5%
P 1
 
1.8%
Other values (2) 2
 
3.5%
Han
ValueCountFrequency (%)
字 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8929
64.9%
ASCII 4818
35.0%
Punctuation 7
 
0.1%
CJK 5
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2077
43.1%
0 536
 
11.1%
2 457
 
9.5%
1 338
 
7.0%
. 251
 
5.2%
( 167
 
3.5%
) 166
 
3.4%
: 109
 
2.3%
5 88
 
1.8%
8 82
 
1.7%
Other values (23) 547
 
11.4%
Hangul
ValueCountFrequency (%)
위 388
 
4.3%
이 385
 
4.3%
미 378
 
4.2%
년 332
 
3.7%
업 329
 
3.7%
소 280
 
3.1%
수 278
 
3.1%
생 252
 
2.8%
교 235
 
2.6%
육 234
 
2.6%
Other values (244) 5838
65.4%
Punctuation
ValueCountFrequency (%)
※ 7
100.0%
CJK
ValueCountFrequency (%)
字 5
100.0%
CJK Compat
ValueCountFrequency (%)
㎖ 2
100.0%

처분내용
Text

Distinct187
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-03T22:00:27.187568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length10.542895
Min length2

Characters and Unicode

Total characters7865
Distinct characters143
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

Unique114 ?
Unique (%)15.3%

Sample

1st row영업정지2월
2nd row영업정지1월
3rd row경고
4th row경고
5th row과태료부과 20만원
ValueCountFrequency (%)
경고 131
 
9.9%
개선명령 116
 
8.8%
과태료 88
 
6.7%
과태료부과 62
 
4.7%
부과 62
 
4.7%
영업소폐쇄 61
 
4.6%
영업정지 58
 
4.4%
및 54
 
4.1%
20만원 45
 
3.4%
16만원 36
 
2.7%
Other values (215) 607
46.0%
2024-05-03T22:00:27.979537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 666
 
8.5%
574
 
7.3%
0 519
 
6.6%
부 382
 
4.9%
원 296
 
3.8%
2 287
 
3.6%
1 262
 
3.3%
만 246
 
3.1%
업 245
 
3.1%
태 233
 
3.0%
Other values (133) 4155
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5196
66.1%
Decimal Number 1434
 
18.2%
Space Separator 574
 
7.3%
Other Punctuation 214
 
2.7%
Close Punctuation 211
 
2.7%
Open Punctuation 211
 
2.7%
Math Symbol 23
 
0.3%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 666
 
12.8%
부 382
 
7.4%
원 296
 
5.7%
만 246
 
4.7%
업 245
 
4.7%
태 233
 
4.5%
료 233
 
4.5%
영 230
 
4.4%
지 175
 
3.4%
정 157
 
3.0%
Other values (112) 2333
44.9%
Decimal Number
ValueCountFrequency (%)
0 519
36.2%
2 287
20.0%
1 262
18.3%
6 91
 
6.3%
3 68
 
4.7%
5 60
 
4.2%
8 59
 
4.1%
4 51
 
3.6%
9 20
 
1.4%
7 17
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 138
64.5%
, 67
31.3%
: 4
 
1.9%
% 3
 
1.4%
? 1
 
0.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5196
66.1%
Common 2669
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 666
 
12.8%
부 382
 
7.4%
원 296
 
5.7%
만 246
 
4.7%
업 245
 
4.7%
태 233
 
4.5%
료 233
 
4.5%
영 230
 
4.4%
지 175
 
3.4%
정 157
 
3.0%
Other values (112) 2333
44.9%
Common
ValueCountFrequency (%)
574
21.5%
0 519
19.4%
2 287
10.8%
1 262
9.8%
) 211
 
7.9%
( 211
 
7.9%
. 138
 
5.2%
6 91
 
3.4%
3 68
 
2.5%
, 67
 
2.5%
Other values (11) 241
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5183
65.9%
ASCII 2669
33.9%
Compat Jamo 13
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 666
 
12.8%
부 382
 
7.4%
원 296
 
5.7%
만 246
 
4.7%
업 245
 
4.7%
태 233
 
4.5%
료 233
 
4.5%
영 230
 
4.4%
지 175
 
3.4%
정 157
 
3.0%
Other values (111) 2320
44.8%
ASCII
ValueCountFrequency (%)
574
21.5%
0 519
19.4%
2 287
10.8%
1 262
9.8%
) 211
 
7.9%
( 211
 
7.9%
. 138
 
5.2%
6 91
 
3.4%
3 68
 
2.5%
, 67
 
2.5%
Other values (11) 241
9.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 13
100.0%

처분기간
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)39.1%
Missing723
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean13.521739
Minimum0
Maximum30
Zeros3
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-03T22:00:28.325090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median15
Q315
95-th percentile29.8
Maximum30
Range30
Interquartile range (IQR)8

Descriptive statistics

Standard deviation8.6910067
Coefficient of variation (CV)0.64274326
Kurtosis-0.22023875
Mean13.521739
Median Absolute Deviation (MAD)6
Skewness0.26980569
Sum311
Variance75.533597
MonotonicityNot monotonic
2024-05-03T22:00:28.673346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
15 9
 
1.2%
7 4
 
0.5%
0 3
 
0.4%
30 2
 
0.3%
14 1
 
0.1%
21 1
 
0.1%
28 1
 
0.1%
20 1
 
0.1%
5 1
 
0.1%
(Missing) 723
96.9%
ValueCountFrequency (%)
0 3
 
0.4%
5 1
 
0.1%
7 4
0.5%
14 1
 
0.1%
15 9
1.2%
20 1
 
0.1%
21 1
 
0.1%
28 1
 
0.1%
30 2
 
0.3%
ValueCountFrequency (%)
30 2
 
0.3%
28 1
 
0.1%
21 1
 
0.1%
20 1
 
0.1%
15 9
1.2%
14 1
 
0.1%
7 4
0.5%
5 1
 
0.1%
0 3
 
0.4%

영업장면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct316
Distinct (%)42.9%
Missing10
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean390.89183
Minimum0
Maximum11588.98
Zeros12
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-03T22:00:29.053332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q133.975
median97.085
Q3306.29
95-th percentile1573
Maximum11588.98
Range11588.98
Interquartile range (IQR)272.315

Descriptive statistics

Standard deviation820.96729
Coefficient of variation (CV)2.1002416
Kurtosis69.185867
Mean390.89183
Median Absolute Deviation (MAD)74.685
Skewness6.506239
Sum287696.39
Variance673987.28
MonotonicityNot monotonic
2024-05-03T22:00:29.491800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 13
 
1.7%
1573.0 13
 
1.7%
1315.98 12
 
1.6%
0.0 12
 
1.6%
90.0 12
 
1.6%
180.0 11
 
1.5%
108.0 11
 
1.5%
172.0 10
 
1.3%
72.0 10
 
1.3%
132.0 9
 
1.2%
Other values (306) 623
83.5%
(Missing) 10
 
1.3%
ValueCountFrequency (%)
0.0 12
1.6%
6.0 1
 
0.1%
8.7 2
 
0.3%
8.74 1
 
0.1%
9.0 1
 
0.1%
9.9 1
 
0.1%
10.0 1
 
0.1%
10.51 1
 
0.1%
11.2 1
 
0.1%
11.8 1
 
0.1%
ValueCountFrequency (%)
11588.98 1
 
0.1%
9499.34 1
 
0.1%
4183.38 2
 
0.3%
3300.0 2
 
0.3%
3215.3 5
0.7%
3159.33 1
 
0.1%
3006.0 2
 
0.3%
2627.35 3
0.4%
2600.0 2
 
0.3%
2276.0 1
 
0.1%

Interactions

2024-05-03T22:00:06.359019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:59:58.933242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:00.665729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:02.193439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:04.378601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:06.771988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:59:59.278389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:00.936573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:02.477761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:04.832447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:07.068019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:59:59.619403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:01.199658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:02.770689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:05.298847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:07.416952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:59:59.971201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:01.591962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:03.188107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:05.784098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:07.692055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:00.346455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:01.907271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:03.645852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:00:06.117230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T22:00:29.765490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.4920.6320.9740.9740.0000.173
업종명0.4921.0000.9610.4940.4900.6650.436
업태명0.6320.9611.0000.6170.6120.8230.759
지도점검일자0.9740.4940.6171.0001.0000.0000.113
위반일자0.9740.4900.6121.0001.0000.0000.094
처분기간0.0000.6650.8230.0000.0001.0000.411
영업장면적(㎡)0.1730.4360.7590.1130.0940.4111.000
2024-05-03T22:00:30.039395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.759
업태명0.7591.000
2024-05-03T22:00:30.287621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명업태명
처분일자1.0000.9990.9990.144-0.0210.2220.249
지도점검일자0.9991.0001.0000.133-0.0270.2230.241
위반일자0.9991.0001.0000.138-0.0260.2210.238
처분기간0.1440.1330.1381.000-0.0150.5520.477
영업장면적(㎡)-0.021-0.027-0.026-0.0151.0000.2300.476
업종명0.2220.2230.2210.5520.2301.0000.759
업태명0.2490.2410.2380.4770.4760.7591.000

Missing values

2024-05-03T22:00:08.147594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T22:00:09.143265image/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.
2024-05-03T22:00:09.767542image/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(㎡)
030500002002072302300410600130숙박업(일반)여관업우정<NA>서울특별시 동대문구 용두동 709번지 27호20020623처분확정영업정지2월<NA>20020623윤락행위알선및장소제공영업정지2월<NA>172.0
13050000200511140012숙박업(일반)여관업우정<NA>서울특별시 동대문구 용두동 709번지 27호20031006처분확정영업정지1월공중위생관리법제11조제1항20031006윤락행위장소제공영업정지1월<NA>172.0
23050000200803170012숙박업(일반)여관업우정<NA>서울특별시 동대문구 용두동 709번지 27호 (용일서길7-2)20080107처분확정경고공중위생관리법 제17조 제1항20080101위생교육 미이수(2007년)경고<NA>172.0
33050000200803170012숙박업(일반)여관업우정<NA>서울특별시 동대문구 용두동 709번지 27호 (용일서길7-2)20080107처분확정경고공중위생관리법 제17조 제1항20080107위생교육 미이수(2007년)경고<NA>172.0
43050000200803170012숙박업(일반)여관업우정<NA>서울특별시 동대문구 용두동 709번지 27호 (용일서길7-2)20080107처분확정과태료부과 20만원공중위생관리법 제17조 제1항20080101위생교육 미이수(2007년)과태료부과 20만원<NA>172.0
53050000201211260012숙박업(일반)여관업우정서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)서울특별시 동대문구 용두동 709번지 27호 1~2층20120918처분확정(2012.12.12~2013.02.11)공중위생관리법제11조제1항20120918숙박자에게 성매매알선등 행위(2012.12.12~2013.02.11)<NA>172.0
63050000201903060012숙박업(일반)여관업우정서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)서울특별시 동대문구 용두동 709번지 27호 1~2층20180709처분확정영업정지법 제11조제1항20180628성매매 알선 및 장소제공(위반일자 : 2018.6.28)영업정지15172.0
73050000201903060012숙박업(일반)여관업우정서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)서울특별시 동대문구 용두동 709번지 27호 1~2층20180709처분확정영업정지법 제11조제1항20181015성매매 알선 및 장소제공(위반일자 : 2018.10.15)영업정지15172.0
83050000201811010012숙박업(일반)여관업우정서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)서울특별시 동대문구 용두동 709번지 27호 1~2층20181101처분확정과태료 240,000 부과(기한 내 납부하여 20%경감금액)법 제82조제2항20181101재난및안전관리기본법 제76조제2항 위반사항으로 과태료 부과과태료 240,000 부과(기한 내 납부하여 20%경감금액)<NA>172.0
93050000202002120012숙박업(일반)여관업우정서울특별시 동대문구 왕산로26길 6-5, 1~2층 (용두동)서울특별시 동대문구 용두동 709번지 27호 1~2층20190527처분확정영업장폐쇄법 제11조제2항20190527영업정지 기간중 영업 행위 : 2019.05.27 (영업정지기간 : 2019.04.01~2019.08.13)영업장폐쇄<NA>172.0
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
7363050000201904222017-00007네일미용업네일아트업이브스네일서울특별시 동대문구 이문로 136, 1층 14호 (이문동)서울특별시 동대문구 이문동 292번지 10호20190101처분확정과태료부과법 제17조201901012018년 위생교육 미이수과태료부과<NA>36.3
7373050000202008042017-00008네일미용업네일아트업유네일서울특별시 동대문구 사가정로 33, 1층 (답십리동)서울특별시 동대문구 답십리동 467번지 45호20200101처분확정과태료 20만원「공중위생법」 제22조제2항제6호202001012019년 위생교육 미이수과태료 20만원<NA>23.0
7383050000202008042017-00018네일미용업네일아트업라엘르네일서울특별시 동대문구 왕산로 280, 1층 (전농동)서울특별시 동대문구 전농동 602번지 3호20200101처분확정과태료 20만원 부과「공중위생법」 제22조제2항제6호202001012019년 위생교육 미이수과태료 20만원 부과<NA>13.0
7393050000202305122018-00014네일미용업네일아트업더예쁜네일서울특별시 동대문구 회기로25길 3, 1층 102호 (회기동)서울특별시 동대문구 회기동 57번지 15호20230420처분확정영업소폐쇄법 제11조제3항제2호20230331사업자등록 폐업(2023.03.31)영업소폐쇄<NA>16.5
7403050000201905092017-00002일반미용업, 피부미용업일반미용업엠브론즈서울특별시 동대문구 이문로 36, 4층 (휘경동)서울특별시 동대문구 휘경동 321번지 57호20190101처분확정과태료부과법 제17조201901012018년 위생교육 미이수과태료부과<NA>92.23
7413050000202003270002일반미용업, 네일미용업네일아트업빨간네일서울특별시 동대문구 이문로 123, 1층 (이문동)서울특별시 동대문구 이문동 292번지 4호 1층20200225처분확정영업소폐쇄법 제11조제3항제2호202002252019. 2. 27. 사업자등록 폐업영업소폐쇄<NA>23.14
7423050000201804120007일반미용업, 네일미용업네일아트업프렌치네일서울특별시 동대문구 사가정로 148, 138동 222-2호 (전농동)서울특별시 동대문구 전농동 10번지20180101처분확정과태료 16만원 부과(의견제출기한 내 자진납부)법 제17조201801012017년도 위생교육 미이수과태료 16만원 부과(의견제출기한 내 자진납부)<NA>17.0
7433050000201804120002피부미용업, 네일미용업네일아트업퀸뷰티샵서울특별시 동대문구 약령시로 10, 1층 (제기동)서울특별시 동대문구 제기동 148번지 17호 1층20180101처분확정과태료 16만원 부과(의견제출기한 내 자진납부)법 제17조201801012017년도 위생교육 미이수과태료 16만원 부과(의견제출기한 내 자진납부)<NA>25.0
7443050000201704272016-00011피부미용업, 네일미용업네일아트업히카루 네일서울특별시 동대문구 한천로14길 45, 1층 (장안동)서울특별시 동대문구 장안동 398번지 11호20161231처분확정사전납부기간내에 납부하여 과태료 16만원으로 경감법 제17조201612312016년도 위생교육 미이수사전납부기간내에 납부하여 과태료 16만원으로 경감<NA>24.0
7453050000201904222016-00004피부미용업, 네일미용업네일아트업네일&속눈썹서울특별시 동대문구 약령시로21길 5, (청량리동)서울특별시 동대문구 청량리동 224번지 2호20190101처분확정과태료부과법 제17조201901012018년 위생교육 미이수과태료부과<NA>16.5

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
213050000200805160063목욕장업공동탕업+찜질시설서비스영업우성불한증막<NA>서울특별시 동대문구 전농동 6번지 1호 우성종합상가 지하 (사가정길191)20080418처분확정개선명령공중위생관리법 제4조제7항20080418영업장내 침구류(이불)비치개선명령<NA>1315.984
333050000200912160024목욕장업공동탕업이문탕<NA>서울특별시 동대문구 이문동 238번지 3호 (신이문길48)20091110처분확정개선명령공중위생관리법20091102욕조수수질기준위반개선명령<NA>210.04
030500002002043002300430100182이용업일반이용업뉴서울<NA>서울특별시 동대문구 장안동 306번지 4호20020330처분확정개선명령<NA>20020330칸막이설치개선명령<NA>61.882
130500002002043002300430100182이용업일반이용업뉴서울<NA>서울특별시 동대문구 장안동 306번지 4호20020330처분확정영업정지15일<NA>20020330칸막이설치영업정지15일1561.882
23050000200412280111미용업일반미용업혜성<NA>서울특별시 동대문구 휘경동 286번지 127호20041228처분확정경고공중위생관리법 제17조200412282004년 보수교육 미필경고<NA>19.892
33050000200412280111미용업일반미용업혜성<NA>서울특별시 동대문구 휘경동 286번지 127호20041228처분확정과태료부과(30만원)공중위생관리법 제17조200412282004년 보수교육 미필과태료부과(30만원)<NA>19.892
43050000200502050228일반미용업일반미용업정훈미용실<NA>서울특별시 동대문구 답십리동 467번지 44호20041228처분확정경고공중위생관리법 제17조200412282004년 보수교육을 받지아니함.경고<NA>16.252
53050000200502050228일반미용업일반미용업정훈미용실<NA>서울특별시 동대문구 답십리동 467번지 44호20041228처분확정과태료부과(30만원)공중위생관리법 제17조200412282004년 보수교육을 받지아니함.과태료부과(30만원)<NA>16.252
63050000200601250096이용업일반이용업동화<NA>서울특별시 동대문구 장안동 188번지 17호20051231처분확정경고공중위생관리법제17조제1항200512312005년도 위생교육미필 과태료20만원부과경고<NA>49.52
73050000200601250096이용업일반이용업동화<NA>서울특별시 동대문구 장안동 188번지 17호20051231처분확정과태료20만원부과공중위생관리법제17조제1항200512312005년도 위생교육미필 과태료20만원부과과태료20만원부과<NA>49.52