Overview

Dataset statistics

Number of variables17
Number of observations619
Missing cells71
Missing cells (%)0.7%
Duplicate rows33
Duplicate rows (%)5.3%
Total size in memory86.0 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(㎡)
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-10528/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 33 (5.3%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 처분기간High correlation
업종명 is highly overall correlated with 업태명 and 1 other fieldsHigh correlation
업태명 is highly overall correlated with 업종명High correlation
처분기간 is highly overall correlated with 처분일자 and 4 other fieldsHigh correlation
처분기간 is highly imbalanced (84.9%)Imbalance
소재지도로명 has 30 (4.8%) missing valuesMissing
영업장면적(㎡) has 41 (6.6%) missing valuesMissing
영업장면적(㎡) is highly skewed (γ1 = 24.02466097)Skewed
영업장면적(㎡) has 34 (5.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:36:14.375066
Analysis finished2024-05-11 05:36:19.709665
Duration5.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
3110000
619 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3110000
2nd row3110000
3rd row3110000
4th row3110000
5th row3110000

Common Values

ValueCountFrequency (%)
3110000 619
100.0%

Length

2024-05-11T14:36:19.818311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:19.992819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3110000 619
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct261
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20131517
Minimum20030703
Maximum20240320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T14:36:20.179354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030703
5-th percentile20040715
Q120100162
median20130408
Q320180414
95-th percentile20201127
Maximum20240320
Range209617
Interquartile range (IQR)80253

Descriptive statistics

Standard deviation50178.333
Coefficient of variation (CV)0.0024925262
Kurtosis-0.67126381
Mean20131517
Median Absolute Deviation (MAD)40123
Skewness-0.040886857
Sum1.2461409 × 1010
Variance2.5178651 × 109
MonotonicityDecreasing
2024-05-11T14:36:20.424930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130408 38
 
6.1%
20130403 36
 
5.8%
20200623 28
 
4.5%
20110504 20
 
3.2%
20130423 14
 
2.3%
20081103 11
 
1.8%
20191206 9
 
1.5%
20081126 8
 
1.3%
20180405 8
 
1.3%
20090202 7
 
1.1%
Other values (251) 440
71.1%
ValueCountFrequency (%)
20030703 2
0.3%
20030902 1
 
0.2%
20030903 1
 
0.2%
20030909 2
0.3%
20030924 1
 
0.2%
20030929 1
 
0.2%
20031015 4
0.6%
20031028 1
 
0.2%
20031106 1
 
0.2%
20031107 1
 
0.2%
ValueCountFrequency (%)
20240320 2
 
0.3%
20231229 1
 
0.2%
20231207 1
 
0.2%
20230825 1
 
0.2%
20230724 2
 
0.3%
20230703 2
 
0.3%
20230608 2
 
0.3%
20230519 1
 
0.2%
20230327 1
 
0.2%
20230221 6
1.0%

교부번호
Text

Distinct261
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:21.009883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length3.4927302
Min length1

Characters and Unicode

Total characters2162
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)23.9%

Sample

1st row178
2nd row74
3rd row136
4th row63
5th row121
ValueCountFrequency (%)
112 12
 
1.9%
121 10
 
1.6%
356 8
 
1.3%
99 8
 
1.3%
14 8
 
1.3%
93 8
 
1.3%
36 8
 
1.3%
101 8
 
1.3%
46 8
 
1.3%
116 7
 
1.1%
Other values (251) 534
86.3%
2024-05-11T14:36:21.921635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 463
21.4%
2 222
10.3%
3 184
 
8.5%
5 173
 
8.0%
4 156
 
7.2%
6 155
 
7.2%
0 154
 
7.1%
- 145
 
6.7%
9 112
 
5.2%
8 108
 
5.0%
Other values (13) 290
13.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1815
84.0%
Other Letter 198
 
9.2%
Dash Punctuation 145
 
6.7%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 463
25.5%
2 222
12.2%
3 184
 
10.1%
5 173
 
9.5%
4 156
 
8.6%
6 155
 
8.5%
0 154
 
8.5%
9 112
 
6.2%
8 108
 
6.0%
7 88
 
4.8%
Other Letter
ValueCountFrequency (%)
부 59
29.8%
피 59
29.8%
종 15
 
7.6%
합 15
 
7.6%
일 11
 
5.6%
반 11
 
5.6%
은 7
 
3.5%
평 7
 
3.5%
미 7
 
3.5%
용 7
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1964
90.8%
Hangul 198
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 463
23.6%
2 222
11.3%
3 184
 
9.4%
5 173
 
8.8%
4 156
 
7.9%
6 155
 
7.9%
0 154
 
7.8%
- 145
 
7.4%
9 112
 
5.7%
8 108
 
5.5%
Other values (3) 92
 
4.7%
Hangul
ValueCountFrequency (%)
부 59
29.8%
피 59
29.8%
종 15
 
7.6%
합 15
 
7.6%
일 11
 
5.6%
반 11
 
5.6%
은 7
 
3.5%
평 7
 
3.5%
미 7
 
3.5%
용 7
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1964
90.8%
Hangul 198
 
9.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 463
23.6%
2 222
11.3%
3 184
 
9.4%
5 173
 
8.8%
4 156
 
7.9%
6 155
 
7.9%
0 154
 
7.8%
- 145
 
7.4%
9 112
 
5.7%
8 108
 
5.5%
Other values (3) 92
 
4.7%
Hangul
ValueCountFrequency (%)
부 59
29.8%
피 59
29.8%
종 15
 
7.6%
합 15
 
7.6%
일 11
 
5.6%
반 11
 
5.6%
은 7
 
3.5%
평 7
 
3.5%
미 7
 
3.5%
용 7
 
3.5%

업종명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
숙박업(일반)
196 
이용업
87 
피부미용업
86 
일반미용업
66 
목욕장업
65 
Other values (8)
119 

Length

Max length16
Median length12
Mean length5.3166397
Min length3

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 196
31.7%
이용업 87
14.1%
피부미용업 86
13.9%
일반미용업 66
 
10.7%
목욕장업 65
 
10.5%
위생관리용역업 53
 
8.6%
세탁업 51
 
8.2%
종합미용업 7
 
1.1%
네일미용업 3
 
0.5%
피부미용업, 네일미용업 2
 
0.3%
Other values (3) 3
 
0.5%

Length

2024-05-11T14:36:22.178691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 196
31.4%
피부미용업 89
14.2%
이용업 87
13.9%
일반미용업 68
 
10.9%
목욕장업 65
 
10.4%
위생관리용역업 53
 
8.5%
세탁업 51
 
8.2%
종합미용업 7
 
1.1%
네일미용업 7
 
1.1%
화장ㆍ분장 1
 
0.2%

업태명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
여관업
174 
피부미용업
88 
일반이용업
87 
일반미용업
71 
공동탕업+찜질시설서비스영업
57 
Other values (11)
142 

Length

Max length14
Median length8
Mean length5.3812601
Min length2

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row위생관리용역업
2nd row위생관리용역업
3rd row여관업
4th row여관업
5th row공동탕업+찜질시설서비스영업

Common Values

ValueCountFrequency (%)
여관업 174
28.1%
피부미용업 88
14.2%
일반이용업 87
14.1%
일반미용업 71
11.5%
공동탕업+찜질시설서비스영업 57
 
9.2%
위생관리용역업 53
 
8.6%
일반세탁업 45
 
7.3%
여인숙업 12
 
1.9%
공동탕업 8
 
1.3%
네일아트업 6
 
1.0%
Other values (6) 18
 
2.9%

Length

2024-05-11T14:36:22.418208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여관업 174
28.1%
피부미용업 88
14.2%
일반이용업 87
14.1%
일반미용업 71
11.5%
공동탕업+찜질시설서비스영업 57
 
9.2%
위생관리용역업 53
 
8.6%
일반세탁업 45
 
7.3%
여인숙업 12
 
1.9%
공동탕업 8
 
1.3%
네일아트업 6
 
1.0%
Other values (6) 18
 
2.9%

업소명
Text

Distinct323
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:22.847963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length5.447496
Min length1

Characters and Unicode

Total characters3372
Distinct characters341
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)34.1%

Sample

1st row태백종합관리 주식회사
2nd row(주)오성토탈시스템
3rd row만토바
4th row카누
5th row메트로불한증막사우나
ValueCountFrequency (%)
모텔 12
 
1.7%
삼부건강랜드보석사우나 11
 
1.6%
메트로불한증막사우나 10
 
1.4%
일심물산 8
 
1.2%
쉴모텔 7
 
1.0%
평화장 7
 
1.0%
쉼터이용원 7
 
1.0%
만토바 6
 
0.9%
봉화장 6
 
0.9%
아비숑(b 6
 
0.9%
Other values (348) 614
88.5%
2024-05-11T14:36:23.513418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 105
 
3.1%
용 81
 
2.4%
스 77
 
2.3%
사 75
 
2.2%
75
 
2.2%
텔 71
 
2.1%
모 69
 
2.0%
원 65
 
1.9%
미 62
 
1.8%
장 62
 
1.8%
Other values (331) 2630
78.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3027
89.8%
Uppercase Letter 77
 
2.3%
Space Separator 75
 
2.2%
Close Punctuation 54
 
1.6%
Open Punctuation 54
 
1.6%
Lowercase Letter 47
 
1.4%
Decimal Number 22
 
0.7%
Other Punctuation 14
 
0.4%
Connector Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 105
 
3.5%
용 81
 
2.7%
스 77
 
2.5%
사 75
 
2.5%
텔 71
 
2.3%
모 69
 
2.3%
원 65
 
2.1%
미 62
 
2.0%
장 62
 
2.0%
우 60
 
2.0%
Other values (287) 2300
76.0%
Uppercase Letter
ValueCountFrequency (%)
M 10
13.0%
T 10
13.0%
B 9
11.7%
S 9
11.7%
O 5
 
6.5%
L 5
 
6.5%
J 5
 
6.5%
H 4
 
5.2%
N 3
 
3.9%
W 3
 
3.9%
Other values (9) 14
18.2%
Lowercase Letter
ValueCountFrequency (%)
a 9
19.1%
c 7
14.9%
o 6
12.8%
e 4
8.5%
n 4
8.5%
h 3
 
6.4%
l 3
 
6.4%
t 2
 
4.3%
u 2
 
4.3%
i 2
 
4.3%
Other values (4) 5
10.6%
Decimal Number
ValueCountFrequency (%)
8 8
36.4%
4 7
31.8%
2 7
31.8%
Other Punctuation
ValueCountFrequency (%)
. 6
42.9%
？ 5
35.7%
& 3
21.4%
Space Separator
ValueCountFrequency (%)
75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3026
89.7%
Common 221
 
6.6%
Latin 124
 
3.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 105
 
3.5%
용 81
 
2.7%
스 77
 
2.5%
사 75
 
2.5%
텔 71
 
2.3%
모 69
 
2.3%
원 65
 
2.1%
미 62
 
2.0%
장 62
 
2.0%
우 60
 
2.0%
Other values (286) 2299
76.0%
Latin
ValueCountFrequency (%)
M 10
 
8.1%
T 10
 
8.1%
B 9
 
7.3%
S 9
 
7.3%
a 9
 
7.3%
c 7
 
5.6%
o 6
 
4.8%
O 5
 
4.0%
L 5
 
4.0%
J 5
 
4.0%
Other values (23) 49
39.5%
Common
ValueCountFrequency (%)
75
33.9%
) 54
24.4%
( 54
24.4%
8 8
 
3.6%
4 7
 
3.2%
2 7
 
3.2%
. 6
 
2.7%
？ 5
 
2.3%
& 3
 
1.4%
_ 1
 
0.5%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3026
89.7%
ASCII 340
 
10.1%
None 5
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 105
 
3.5%
용 81
 
2.7%
스 77
 
2.5%
사 75
 
2.5%
텔 71
 
2.3%
모 69
 
2.3%
원 65
 
2.1%
미 62
 
2.0%
장 62
 
2.0%
우 60
 
2.0%
Other values (286) 2299
76.0%
ASCII
ValueCountFrequency (%)
75
22.1%
) 54
15.9%
( 54
15.9%
M 10
 
2.9%
T 10
 
2.9%
B 9
 
2.6%
S 9
 
2.6%
a 9
 
2.6%
8 8
 
2.4%
c 7
 
2.1%
Other values (33) 95
27.9%
None
ValueCountFrequency (%)
？ 5
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

소재지도로명
Text

MISSING 

Distinct289
Distinct (%)49.1%
Missing30
Missing (%)4.8%
Memory size5.0 KiB
2024-05-11T14:36:24.014878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length28.714771
Min length23

Characters and Unicode

Total characters16913
Distinct characters143
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)30.7%

Sample

1st row서울특별시 은평구 가좌로 164, 지상1층 가호 (응암동)
2nd row서울특별시 은평구 가좌로7길 37-1, (응암동,(2층))
3rd row서울특별시 은평구 통일로 839-1, (대조동)
4th row서울특별시 은평구 응암로12길 11-6, (응암동)
5th row서울특별시 은평구 은평로 108, (응암동,외9필지 메트로럭스주상APT 1B01,2B01)
ValueCountFrequency (%)
서울특별시 589
 
18.4%
은평구 589
 
18.4%
응암동 138
 
4.3%
대조동 93
 
2.9%
통일로 70
 
2.2%
불광동 62
 
1.9%
은평로 47
 
1.5%
응암로 42
 
1.3%
갈현동 39
 
1.2%
녹번동 32
 
1.0%
Other values (428) 1493
46.7%
2024-05-11T14:36:24.850341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2607
 
15.4%
, 780
 
4.6%
1 714
 
4.2%
서 685
 
4.1%
은 671
 
4.0%
평 670
 
4.0%
) 643
 
3.8%
( 643
 
3.8%
구 607
 
3.6%
동 603
 
3.6%
Other values (133) 8290
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9441
55.8%
Space Separator 2607
 
15.4%
Decimal Number 2551
 
15.1%
Other Punctuation 780
 
4.6%
Close Punctuation 643
 
3.8%
Open Punctuation 643
 
3.8%
Dash Punctuation 172
 
1.0%
Uppercase Letter 76
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 685
 
7.3%
은 671
 
7.1%
평 670
 
7.1%
구 607
 
6.4%
동 603
 
6.4%
로 598
 
6.3%
특 589
 
6.2%
시 589
 
6.2%
별 589
 
6.2%
울 589
 
6.2%
Other values (112) 3251
34.4%
Decimal Number
ValueCountFrequency (%)
1 714
28.0%
2 473
18.5%
8 230
 
9.0%
3 227
 
8.9%
0 204
 
8.0%
7 177
 
6.9%
5 155
 
6.1%
6 153
 
6.0%
4 117
 
4.6%
9 101
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 38
50.0%
A 14
 
18.4%
T 11
 
14.5%
P 11
 
14.5%
I 1
 
1.3%
C 1
 
1.3%
Space Separator
ValueCountFrequency (%)
2607
100.0%
Other Punctuation
ValueCountFrequency (%)
, 780
100.0%
Close Punctuation
ValueCountFrequency (%)
) 643
100.0%
Open Punctuation
ValueCountFrequency (%)
( 643
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9441
55.8%
Common 7396
43.7%
Latin 76
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 685
 
7.3%
은 671
 
7.1%
평 670
 
7.1%
구 607
 
6.4%
동 603
 
6.4%
로 598
 
6.3%
특 589
 
6.2%
시 589
 
6.2%
별 589
 
6.2%
울 589
 
6.2%
Other values (112) 3251
34.4%
Common
ValueCountFrequency (%)
2607
35.2%
, 780
 
10.5%
1 714
 
9.7%
) 643
 
8.7%
( 643
 
8.7%
2 473
 
6.4%
8 230
 
3.1%
3 227
 
3.1%
0 204
 
2.8%
7 177
 
2.4%
Other values (5) 698
 
9.4%
Latin
ValueCountFrequency (%)
B 38
50.0%
A 14
 
18.4%
T 11
 
14.5%
P 11
 
14.5%
I 1
 
1.3%
C 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9441
55.8%
ASCII 7472
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2607
34.9%
, 780
 
10.4%
1 714
 
9.6%
) 643
 
8.6%
( 643
 
8.6%
2 473
 
6.3%
8 230
 
3.1%
3 227
 
3.0%
0 204
 
2.7%
7 177
 
2.4%
Other values (11) 774
 
10.4%
Hangul
ValueCountFrequency (%)
서 685
 
7.3%
은 671
 
7.1%
평 670
 
7.1%
구 607
 
6.4%
동 603
 
6.4%
로 598
 
6.3%
특 589
 
6.2%
시 589
 
6.2%
별 589
 
6.2%
울 589
 
6.2%
Other values (112) 3251
34.4%

소재지지번
Text

Distinct301
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:25.432175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length50
Mean length27.998384
Min length22

Characters and Unicode

Total characters17331
Distinct characters135
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)30.2%

Sample

1st row서울특별시 은평구 응암동 677번지 1호 지상1층-가
2nd row서울특별시 은평구 응암동 756번지 2호 (2층)
3rd row서울특별시 은평구 대조동 185번지 82호
4th row서울특별시 은평구 응암동 749번지 49호
5th row서울특별시 은평구 응암동 110번지 9호 외9필지 메트로럭스주상APT 1B01,2B01
ValueCountFrequency (%)
서울특별시 619
 
18.1%
은평구 619
 
18.1%
응암동 210
 
6.2%
대조동 110
 
3.2%
불광동 84
 
2.5%
갈현동 53
 
1.6%
1호 48
 
1.4%
2층 42
 
1.2%
녹번동 42
 
1.2%
2호 32
 
0.9%
Other values (369) 1554
45.5%
2024-05-11T14:36:26.249716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4405
25.4%
1 745
 
4.3%
지 714
 
4.1%
번 662
 
3.8%
구 639
 
3.7%
호 636
 
3.7%
동 632
 
3.6%
은 624
 
3.6%
평 623
 
3.6%
울 619
 
3.6%
Other values (125) 7032
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9451
54.5%
Space Separator 4405
25.4%
Decimal Number 3160
 
18.2%
Close Punctuation 85
 
0.5%
Open Punctuation 85
 
0.5%
Uppercase Letter 78
 
0.5%
Other Punctuation 36
 
0.2%
Dash Punctuation 31
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 714
 
7.6%
번 662
 
7.0%
구 639
 
6.8%
호 636
 
6.7%
동 632
 
6.7%
은 624
 
6.6%
평 623
 
6.6%
울 619
 
6.5%
서 619
 
6.5%
시 619
 
6.5%
Other values (104) 3064
32.4%
Decimal Number
ValueCountFrequency (%)
1 745
23.6%
2 415
13.1%
4 338
10.7%
3 302
9.6%
0 278
 
8.8%
5 277
 
8.8%
9 251
 
7.9%
6 200
 
6.3%
8 195
 
6.2%
7 159
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 38
48.7%
A 16
20.5%
T 11
 
14.1%
P 11
 
14.1%
I 1
 
1.3%
C 1
 
1.3%
Space Separator
ValueCountFrequency (%)
4405
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9451
54.5%
Common 7802
45.0%
Latin 78
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 714
 
7.6%
번 662
 
7.0%
구 639
 
6.8%
호 636
 
6.7%
동 632
 
6.7%
은 624
 
6.6%
평 623
 
6.6%
울 619
 
6.5%
서 619
 
6.5%
시 619
 
6.5%
Other values (104) 3064
32.4%
Common
ValueCountFrequency (%)
4405
56.5%
1 745
 
9.5%
2 415
 
5.3%
4 338
 
4.3%
3 302
 
3.9%
0 278
 
3.6%
5 277
 
3.6%
9 251
 
3.2%
6 200
 
2.6%
8 195
 
2.5%
Other values (5) 396
 
5.1%
Latin
ValueCountFrequency (%)
B 38
48.7%
A 16
20.5%
T 11
 
14.1%
P 11
 
14.1%
I 1
 
1.3%
C 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9451
54.5%
ASCII 7880
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4405
55.9%
1 745
 
9.5%
2 415
 
5.3%
4 338
 
4.3%
3 302
 
3.8%
0 278
 
3.5%
5 277
 
3.5%
9 251
 
3.2%
6 200
 
2.5%
8 195
 
2.5%
Other values (11) 474
 
6.0%
Hangul
ValueCountFrequency (%)
지 714
 
7.6%
번 662
 
7.0%
구 639
 
6.8%
호 636
 
6.7%
동 632
 
6.7%
은 624
 
6.6%
평 623
 
6.6%
울 619
 
6.5%
서 619
 
6.5%
시 619
 
6.5%
Other values (104) 3064
32.4%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct267
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20129148
Minimum20030207
Maximum20240229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T14:36:26.506162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030207
5-th percentile20040611
Q120100213
median20121231
Q320180320
95-th percentile20200847
Maximum20240229
Range210022
Interquartile range (IQR)80107

Descriptive statistics

Standard deviation50320.945
Coefficient of variation (CV)0.0024999043
Kurtosis-0.69021366
Mean20129148
Median Absolute Deviation (MAD)39988
Skewness0.0082601485
Sum1.2459943 × 1010
Variance2.5321975 × 109
MonotonicityNot monotonic
2024-05-11T14:36:26.784787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121231 52
 
8.4%
20130226 33
 
5.3%
20200601 28
 
4.5%
20110415 20
 
3.2%
20180320 15
 
2.4%
20191010 15
 
2.4%
20181121 10
 
1.6%
20180619 9
 
1.5%
20070201 8
 
1.3%
20181220 7
 
1.1%
Other values (257) 422
68.2%
ValueCountFrequency (%)
20030207 1
 
0.2%
20030613 1
 
0.2%
20030614 2
0.3%
20030616 1
 
0.2%
20030829 1
 
0.2%
20030908 2
0.3%
20030923 1
 
0.2%
20030926 1
 
0.2%
20031004 1
 
0.2%
20031010 4
0.6%
ValueCountFrequency (%)
20240229 2
 
0.3%
20230718 1
 
0.2%
20230615 4
0.6%
20230522 2
 
0.3%
20230418 1
 
0.2%
20230205 1
 
0.2%
20230203 6
1.0%
20230131 1
 
0.2%
20220414 1
 
0.2%
20220207 1
 
0.2%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
처분확정
619 

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 619
100.0%

Length

2024-05-11T14:36:27.035812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:27.297950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 619
100.0%

처분명
Text

Distinct140
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:27.879677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length50
Mean length9.7915994
Min length2

Characters and Unicode

Total characters6061
Distinct characters134
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)13.6%

Sample

1st row직권말소
2nd row직권말소
3rd row과징금부과
4th row영업정지
5th row과징금부과 630,000원
ValueCountFrequency (%)
경고 97
 
9.6%
영업소폐쇄 71
 
7.0%
과징금부과 71
 
7.0%
개선명령 68
 
6.7%
영업정지 57
 
5.6%
직권말소 54
 
5.3%
갈음 34
 
3.4%
부과 33
 
3.3%
과태료부과 23
 
2.3%
과태료20만원 20
 
2.0%
Other values (200) 485
47.9%
2024-05-11T14:36:28.551755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 435
 
7.2%
394
 
6.5%
0 290
 
4.8%
2 246
 
4.1%
1 245
 
4.0%
부 244
 
4.0%
업 209
 
3.4%
영 193
 
3.2%
소 143
 
2.4%
) 141
 
2.3%
Other values (124) 3521
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4027
66.4%
Decimal Number 1138
 
18.8%
Space Separator 394
 
6.5%
Other Punctuation 192
 
3.2%
Close Punctuation 141
 
2.3%
Open Punctuation 141
 
2.3%
Dash Punctuation 18
 
0.3%
Math Symbol 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 435
 
10.8%
부 244
 
6.1%
업 209
 
5.2%
영 193
 
4.8%
소 143
 
3.6%
경 141
 
3.5%
원 140
 
3.5%
금 140
 
3.5%
징 140
 
3.5%
만 129
 
3.2%
Other values (104) 2113
52.5%
Decimal Number
ValueCountFrequency (%)
0 290
25.5%
2 246
21.6%
1 245
21.5%
6 77
 
6.8%
3 73
 
6.4%
4 62
 
5.4%
5 54
 
4.7%
8 40
 
3.5%
7 31
 
2.7%
9 20
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 122
63.5%
, 31
 
16.1%
% 30
 
15.6%
/ 9
 
4.7%
Open Punctuation
ValueCountFrequency (%)
( 140
99.3%
[ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
394
100.0%
Close Punctuation
ValueCountFrequency (%)
) 141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4027
66.4%
Common 2034
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 435
 
10.8%
부 244
 
6.1%
업 209
 
5.2%
영 193
 
4.8%
소 143
 
3.6%
경 141
 
3.5%
원 140
 
3.5%
금 140
 
3.5%
징 140
 
3.5%
만 129
 
3.2%
Other values (104) 2113
52.5%
Common
ValueCountFrequency (%)
394
19.4%
0 290
14.3%
2 246
12.1%
1 245
12.0%
) 141
 
6.9%
( 140
 
6.9%
. 122
 
6.0%
6 77
 
3.8%
3 73
 
3.6%
4 62
 
3.0%
Other values (10) 244
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4027
66.4%
ASCII 2034
33.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 435
 
10.8%
부 244
 
6.1%
업 209
 
5.2%
영 193
 
4.8%
소 143
 
3.6%
경 141
 
3.5%
원 140
 
3.5%
금 140
 
3.5%
징 140
 
3.5%
만 129
 
3.2%
Other values (104) 2113
52.5%
ASCII
ValueCountFrequency (%)
394
19.4%
0 290
14.3%
2 246
12.1%
1 245
12.0%
) 141
 
6.9%
( 140
 
6.9%
. 122
 
6.0%
6 77
 
3.8%
3 73
 
3.6%
4 62
 
3.0%
Other values (10) 244
12.0%

법적근거
Text

Distinct97
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:28.919502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length13.46042
Min length6

Characters and Unicode

Total characters8332
Distinct characters61
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)7.4%

Sample

1st row법 제11조제3항제2호
2nd row법 제11조제3항제2호
3rd row법 제11조제1항제8호
4th row법 제11조제1항제8호
5th row법 제11조제1항제4호
ValueCountFrequency (%)
공중위생관리법 315
22.5%
법 191
13.6%
제11조 191
13.6%
및 74
 
5.3%
제11조제3항제2호 62
 
4.4%
같은법 45
 
3.2%
제3조제3항 43
 
3.1%
제22조 38
 
2.7%
제11조제1항 37
 
2.6%
제4조 29
 
2.1%
Other values (89) 376
26.8%
2024-05-11T14:36:29.537936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 1097
13.2%
1 1031
12.4%
783
 
9.4%
조 704
 
8.4%
법 679
 
8.1%
위 421
 
5.1%
중 409
 
4.9%
공 409
 
4.9%
생 409
 
4.9%
관 408
 
4.9%
Other values (51) 1982
23.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5831
70.0%
Decimal Number 1693
 
20.3%
Space Separator 783
 
9.4%
Other Punctuation 25
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1097
18.8%
조 704
12.1%
법 679
11.6%
위 421
 
7.2%
중 409
 
7.0%
공 409
 
7.0%
생 409
 
7.0%
관 408
 
7.0%
리 399
 
6.8%
항 336
 
5.8%
Other values (39) 560
9.6%
Decimal Number
ValueCountFrequency (%)
1 1031
60.9%
3 231
 
13.6%
2 203
 
12.0%
4 92
 
5.4%
7 77
 
4.5%
9 21
 
1.2%
8 19
 
1.1%
6 10
 
0.6%
0 9
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 24
96.0%
/ 1
 
4.0%
Space Separator
ValueCountFrequency (%)
783
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5831
70.0%
Common 2501
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1097
18.8%
조 704
12.1%
법 679
11.6%
위 421
 
7.2%
중 409
 
7.0%
공 409
 
7.0%
생 409
 
7.0%
관 408
 
7.0%
리 399
 
6.8%
항 336
 
5.8%
Other values (39) 560
9.6%
Common
ValueCountFrequency (%)
1 1031
41.2%
783
31.3%
3 231
 
9.2%
2 203
 
8.1%
4 92
 
3.7%
7 77
 
3.1%
, 24
 
1.0%
9 21
 
0.8%
8 19
 
0.8%
6 10
 
0.4%
Other values (2) 10
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5831
70.0%
ASCII 2501
30.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 1097
18.8%
조 704
12.1%
법 679
11.6%
위 421
 
7.2%
중 409
 
7.0%
공 409
 
7.0%
생 409
 
7.0%
관 408
 
7.0%
리 399
 
6.8%
항 336
 
5.8%
Other values (39) 560
9.6%
ASCII
ValueCountFrequency (%)
1 1031
41.2%
783
31.3%
3 231
 
9.2%
2 203
 
8.1%
4 92
 
3.7%
7 77
 
3.1%
, 24
 
1.0%
9 21
 
0.8%
8 19
 
0.8%
6 10
 
0.4%
Other values (2) 10
 
0.4%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct313
Distinct (%)50.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20126198
Minimum20030207
Maximum20240229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T14:36:29.832338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030207
5-th percentile20040611
Q120090708
median20121231
Q320161013
95-th percentile20200847
Maximum20240229
Range210022
Interquartile range (IQR)70305

Descriptive statistics

Standard deviation49298.306
Coefficient of variation (CV)0.0024494595
Kurtosis-0.55466272
Mean20126198
Median Absolute Deviation (MAD)39398
Skewness0.10325029
Sum1.2458116 × 1010
Variance2.430323 × 109
MonotonicityNot monotonic
2024-05-11T14:36:30.427288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121231 88
 
14.2%
20200601 28
 
4.5%
20191010 15
 
2.4%
20091231 12
 
1.9%
20070201 8
 
1.3%
20131004 7
 
1.1%
20101206 6
 
1.0%
20141003 6
 
1.0%
20121127 6
 
1.0%
20230203 6
 
1.0%
Other values (303) 437
70.6%
ValueCountFrequency (%)
20030207 1
 
0.2%
20030613 1
 
0.2%
20030614 2
0.3%
20030616 1
 
0.2%
20030829 1
 
0.2%
20030908 2
0.3%
20030923 1
 
0.2%
20030926 1
 
0.2%
20031004 1
 
0.2%
20031010 4
0.6%
ValueCountFrequency (%)
20240229 2
 
0.3%
20230801 1
 
0.2%
20230616 1
 
0.2%
20230615 3
0.5%
20230522 2
 
0.3%
20230418 1
 
0.2%
20230210 1
 
0.2%
20230205 1
 
0.2%
20230203 6
1.0%
20220414 1
 
0.2%

위반내용
Text

Distinct293
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:30.872688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length158
Median length114
Mean length27.19063
Min length4

Characters and Unicode

Total characters16831
Distinct characters346
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique221 ?
Unique (%)35.7%

Sample

1st row사업자등록 말소에 따른 직권말소
2nd row사업자등록 말소로 인한 직권말소
3rd row2021.07.25(01:13분경) 청소년 손준우(04년생, 남)와 이보은(04년생, 여)을 청소년 이성혼숙케 함
4th row2021.6.16. 05:30 카누 모텔에서 숙박료 4만원을 대가로 청소년인 한00(여, 15세), 윤00(남, 16세)을 혼숙하도록 객실을 제공하여 청소년보호법 위반(서부경찰서 수사과 통보)
5th row목욕장 욕조수 수질검사 결과 부적합(레지오넬라균)
ValueCountFrequency (%)
위생교육 107
 
3.4%
미필 96
 
3.1%
2012년 88
 
2.8%
청소년 75
 
2.4%
관할 71
 
2.3%
이성혼숙 53
 
1.7%
경우 45
 
1.4%
사업자 45
 
1.4%
세무서장에게 43
 
1.4%
등록을 43
 
1.4%
Other values (846) 2475
78.8%
2024-05-11T14:36:31.661892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2654
 
15.8%
0 624
 
3.7%
2 532
 
3.2%
업 462
 
2.7%
1 428
 
2.5%
소 341
 
2.0%
. 336
 
2.0%
위 314
 
1.9%
년 300
 
1.8%
자 244
 
1.4%
Other values (336) 10596
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11057
65.7%
Space Separator 2654
 
15.8%
Decimal Number 2148
 
12.8%
Other Punctuation 512
 
3.0%
Close Punctuation 193
 
1.1%
Open Punctuation 193
 
1.1%
Dash Punctuation 35
 
0.2%
Uppercase Letter 14
 
0.1%
Math Symbol 9
 
0.1%
Lowercase Letter 8
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 462
 
4.2%
소 341
 
3.1%
위 314
 
2.8%
년 300
 
2.7%
자 244
 
2.2%
서 243
 
2.2%
이 242
 
2.2%
미 211
 
1.9%
에 202
 
1.8%
성 196
 
1.8%
Other values (302) 8302
75.1%
Decimal Number
ValueCountFrequency (%)
0 624
29.1%
2 532
24.8%
1 428
19.9%
8 126
 
5.9%
3 100
 
4.7%
4 75
 
3.5%
6 73
 
3.4%
5 69
 
3.2%
7 64
 
3.0%
9 57
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
C 4
28.6%
T 4
28.6%
V 2
14.3%
N 2
14.3%
U 2
14.3%
Other Punctuation
ValueCountFrequency (%)
. 336
65.6%
: 87
 
17.0%
, 81
 
15.8%
/ 8
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
c 4
50.0%
m 2
25.0%
t 1
 
12.5%
v 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 189
97.9%
] 4
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 189
97.9%
[ 4
 
2.1%
Other Symbol
ValueCountFrequency (%)
○ 4
66.7%
㎡ 2
33.3%
Space Separator
ValueCountFrequency (%)
2654
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11057
65.7%
Common 5752
34.2%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 462
 
4.2%
소 341
 
3.1%
위 314
 
2.8%
년 300
 
2.7%
자 244
 
2.2%
서 243
 
2.2%
이 242
 
2.2%
미 211
 
1.9%
에 202
 
1.8%
성 196
 
1.8%
Other values (302) 8302
75.1%
Common
ValueCountFrequency (%)
2654
46.1%
0 624
 
10.8%
2 532
 
9.2%
1 428
 
7.4%
. 336
 
5.8%
) 189
 
3.3%
( 189
 
3.3%
8 126
 
2.2%
3 100
 
1.7%
: 87
 
1.5%
Other values (15) 487
 
8.5%
Latin
ValueCountFrequency (%)
c 4
18.2%
C 4
18.2%
T 4
18.2%
V 2
9.1%
m 2
9.1%
N 2
9.1%
U 2
9.1%
t 1
 
4.5%
v 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11057
65.7%
ASCII 5766
34.3%
Geometric Shapes 4
 
< 0.1%
CJK Compat 2
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2654
46.0%
0 624
 
10.8%
2 532
 
9.2%
1 428
 
7.4%
. 336
 
5.8%
) 189
 
3.3%
( 189
 
3.3%
8 126
 
2.2%
3 100
 
1.7%
: 87
 
1.5%
Other values (20) 501
 
8.7%
Hangul
ValueCountFrequency (%)
업 462
 
4.2%
소 341
 
3.1%
위 314
 
2.8%
년 300
 
2.7%
자 244
 
2.2%
서 243
 
2.2%
이 242
 
2.2%
미 211
 
1.9%
에 202
 
1.8%
성 196
 
1.8%
Other values (302) 8302
75.1%
Geometric Shapes
ValueCountFrequency (%)
○ 4
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

처분내용
Text

Distinct140
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T14:36:32.080602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length50
Mean length9.7915994
Min length2

Characters and Unicode

Total characters6061
Distinct characters134
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)13.6%

Sample

1st row직권말소
2nd row직권말소
3rd row과징금부과
4th row영업정지
5th row과징금부과 630,000원
ValueCountFrequency (%)
경고 97
 
9.6%
영업소폐쇄 71
 
7.0%
과징금부과 71
 
7.0%
개선명령 68
 
6.7%
영업정지 57
 
5.6%
직권말소 54
 
5.3%
갈음 34
 
3.4%
부과 33
 
3.3%
과태료부과 23
 
2.3%
과태료20만원 20
 
2.0%
Other values (200) 485
47.9%
2024-05-11T14:36:32.702879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 435
 
7.2%
394
 
6.5%
0 290
 
4.8%
2 246
 
4.1%
1 245
 
4.0%
부 244
 
4.0%
업 209
 
3.4%
영 193
 
3.2%
소 143
 
2.4%
) 141
 
2.3%
Other values (124) 3521
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4027
66.4%
Decimal Number 1138
 
18.8%
Space Separator 394
 
6.5%
Other Punctuation 192
 
3.2%
Close Punctuation 141
 
2.3%
Open Punctuation 141
 
2.3%
Dash Punctuation 18
 
0.3%
Math Symbol 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 435
 
10.8%
부 244
 
6.1%
업 209
 
5.2%
영 193
 
4.8%
소 143
 
3.6%
경 141
 
3.5%
원 140
 
3.5%
금 140
 
3.5%
징 140
 
3.5%
만 129
 
3.2%
Other values (104) 2113
52.5%
Decimal Number
ValueCountFrequency (%)
0 290
25.5%
2 246
21.6%
1 245
21.5%
6 77
 
6.8%
3 73
 
6.4%
4 62
 
5.4%
5 54
 
4.7%
8 40
 
3.5%
7 31
 
2.7%
9 20
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 122
63.5%
, 31
 
16.1%
% 30
 
15.6%
/ 9
 
4.7%
Open Punctuation
ValueCountFrequency (%)
( 140
99.3%
[ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
394
100.0%
Close Punctuation
ValueCountFrequency (%)
) 141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4027
66.4%
Common 2034
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 435
 
10.8%
부 244
 
6.1%
업 209
 
5.2%
영 193
 
4.8%
소 143
 
3.6%
경 141
 
3.5%
원 140
 
3.5%
금 140
 
3.5%
징 140
 
3.5%
만 129
 
3.2%
Other values (104) 2113
52.5%
Common
ValueCountFrequency (%)
394
19.4%
0 290
14.3%
2 246
12.1%
1 245
12.0%
) 141
 
6.9%
( 140
 
6.9%
. 122
 
6.0%
6 77
 
3.8%
3 73
 
3.6%
4 62
 
3.0%
Other values (10) 244
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4027
66.4%
ASCII 2034
33.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 435
 
10.8%
부 244
 
6.1%
업 209
 
5.2%
영 193
 
4.8%
소 143
 
3.6%
경 141
 
3.5%
원 140
 
3.5%
금 140
 
3.5%
징 140
 
3.5%
만 129
 
3.2%
Other values (104) 2113
52.5%
ASCII
ValueCountFrequency (%)
394
19.4%
0 290
14.3%
2 246
12.1%
1 245
12.0%
) 141
 
6.9%
( 140
 
6.9%
. 122
 
6.0%
6 77
 
3.8%
3 73
 
3.6%
4 62
 
3.0%
Other values (10) 244
12.0%

처분기간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
586 
0
 
18
15
 
8
10
 
5
30
 
1

Length

Max length4
Median length4
Mean length3.8642973
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row10

Common Values

ValueCountFrequency (%)
<NA> 586
94.7%
0 18
 
2.9%
15 8
 
1.3%
10 5
 
0.8%
30 1
 
0.2%
28 1
 
0.2%

Length

2024-05-11T14:36:32.906923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:33.084557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 586
94.7%
0 18
 
2.9%
15 8
 
1.3%
10 5
 
0.8%
30 1
 
0.2%
28 1
 
0.2%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct249
Distinct (%)43.1%
Missing41
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean1629.8298
Minimum0
Maximum741089
Zeros34
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T14:36:33.255768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129.29
median65.5
Q3269.48
95-th percentile2208.88
Maximum741089
Range741089
Interquartile range (IQR)240.19

Descriptive statistics

Standard deviation30817.994
Coefficient of variation (CV)18.90872
Kurtosis577.45407
Mean1629.8298
Median Absolute Deviation (MAD)49.285
Skewness24.024661
Sum942041.61
Variance9.4974877 × 108
MonotonicityNot monotonic
2024-05-11T14:36:33.514862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
 
5.5%
2811.6 12
 
1.9%
2208.88 10
 
1.6%
34.0 8
 
1.3%
178.34 8
 
1.3%
115.5 7
 
1.1%
918.36 7
 
1.1%
30.0 6
 
1.0%
18.04 6
 
1.0%
23.0 6
 
1.0%
Other values (239) 474
76.6%
(Missing) 41
 
6.6%
ValueCountFrequency (%)
0.0 34
5.5%
3.3 1
 
0.2%
11.2 2
 
0.3%
11.78 4
 
0.6%
12.28 1
 
0.2%
12.8 1
 
0.2%
12.95 6
 
1.0%
13.2 1
 
0.2%
13.61 1
 
0.2%
13.83 1
 
0.2%
ValueCountFrequency (%)
741089.0 1
 
0.2%
5203.5 2
 
0.3%
2901.7 1
 
0.2%
2811.6 12
1.9%
2801.02 1
 
0.2%
2584.02 1
 
0.2%
2556.92 1
 
0.2%
2238.59 3
 
0.5%
2208.88 10
1.6%
1980.48 3
 
0.5%

Interactions

2024-05-11T14:36:18.157719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.131237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.786438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:17.443430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:18.409099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.296116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.945504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:17.636377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:18.547280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.449988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:17.096181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:17.827938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:18.712746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.624091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:17.242712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:17.979659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:36:33.713454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자법적근거위반일자처분기간영업장면적(㎡)
처분일자1.0000.5950.6360.9990.9610.9940.7860.213
업종명0.5951.0000.9610.5960.8070.5840.6420.000
업태명0.6360.9611.0000.6340.8250.6170.5420.000
지도점검일자0.9990.5960.6341.0000.9570.9970.8260.229
법적근거0.9610.8070.8250.9571.0000.9420.6890.266
위반일자0.9940.5840.6170.9970.9421.0000.8260.229
처분기간0.7860.6420.5420.8260.6890.8261.000NaN
영업장면적(㎡)0.2130.0000.0000.2290.2660.229NaN1.000
2024-05-11T14:36:33.928000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명처분기간업태명
업종명1.0000.5830.792
처분기간0.5831.0000.457
업태명0.7920.4571.000
2024-05-11T14:36:34.072138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자영업장면적(㎡)업종명업태명처분기간
처분일자1.0000.9940.991-0.2100.2930.3080.557
지도점검일자0.9941.0000.992-0.2130.2950.3070.611
위반일자0.9910.9921.000-0.1970.2860.2940.611
영업장면적(㎡)-0.210-0.213-0.1971.0000.0000.0001.000
업종명0.2930.2950.2860.0001.0000.7920.583
업태명0.3080.3070.2940.0000.7921.0000.457
처분기간0.5570.6110.6111.0000.5830.4571.000

Missing values

2024-05-11T14:36:18.976046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:36:19.385727image/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.
2024-05-11T14:36:19.607383image/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(㎡)
0311000020240320178위생관리용역업위생관리용역업태백종합관리 주식회사서울특별시 은평구 가좌로 164, 지상1층 가호 (응암동)서울특별시 은평구 응암동 677번지 1호 지상1층-가20240229처분확정직권말소법 제11조제3항제2호20240229사업자등록 말소에 따른 직권말소직권말소<NA>13.2
131100002024032074위생관리용역업위생관리용역업(주)오성토탈시스템서울특별시 은평구 가좌로7길 37-1, (응암동,(2층))서울특별시 은평구 응암동 756번지 2호 (2층)20240229처분확정직권말소법 제11조제3항제2호20240229사업자등록 말소로 인한 직권말소직권말소<NA>29.29
2311000020231229136숙박업(일반)여관업만토바서울특별시 은평구 통일로 839-1, (대조동)서울특별시 은평구 대조동 185번지 82호20210725처분확정과징금부과법 제11조제1항제8호202107252021.07.25(01:13분경) 청소년 손준우(04년생, 남)와 이보은(04년생, 여)을 청소년 이성혼숙케 함과징금부과<NA>802.24
331100002023120763숙박업(일반)여관업카누서울특별시 은평구 응암로12길 11-6, (응암동)서울특별시 은평구 응암동 749번지 49호20210616처분확정영업정지법 제11조제1항제8호202106162021.6.16. 05:30 카누 모텔에서 숙박료 4만원을 대가로 청소년인 한00(여, 15세), 윤00(남, 16세)을 혼숙하도록 객실을 제공하여 청소년보호법 위반(서부경찰서 수사과 통보)영업정지<NA>174.42
4311000020230825121목욕장업공동탕업+찜질시설서비스영업메트로불한증막사우나서울특별시 은평구 은평로 108, (응암동,외9필지 메트로럭스주상APT 1B01,2B01)서울특별시 은평구 응암동 110번지 9호 외9필지 메트로럭스주상APT 1B01,2B0120230718처분확정과징금부과 630,000원법 제11조제1항제4호20230801목욕장 욕조수 수질검사 결과 부적합(레지오넬라균)과징금부과 630,000원102208.88
5311000020230724141이용업일반이용업중앙서울특별시 은평구 연서로17길 18-6, (갈현동)서울특별시 은평구 갈현동 467번지 1호20230615처분확정영업소폐쇄법 제11조제3항제1호20230615시설물 멸실영업소폐쇄<NA>16.99
6311000020230724461이용업일반이용업가위손서울특별시 은평구 응암로 192, 지하층 B01호 (응암동)서울특별시 은평구 응암동 601번지 69호 (B01호)20230615처분확정영업소폐쇄법 제11조제3항20230616시설물 멸실영업소폐쇄<NA>12.95
7311000020230703123숙박업(일반)여관업몽호텔서울특별시 은평구 은평로 150, (응암동)서울특별시 은평구 응암동 98번지 26호20230615처분확정영업소폐쇄법 제11조제3항제1호20230615시설물 멸실영업소폐쇄<NA>741089.0
8311000020230703110숙박업(일반)여관업수모텔서울특별시 은평구 응암로21길 4-1, (응암동)서울특별시 은평구 응암동 124번지 46호20230615처분확정영업소폐쇄법 제11조제3항제1호20230615시설물 멸실영업소폐쇄<NA>292.9
93110000202306082016-7일반미용업일반미용업헤어바이에이치스타일서울특별시 은평구 증산서길 126-1, 지상1층 (증산동)서울특별시 은평구 증산동 165번지 23호 지상1층20230522처분확정직권말소법 제11조제3항제2호20230522직권말소직권말소<NA>29.7
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
609311000020031015279이용업일반이용업백제이용원서울특별시 은평구 응암로 160, (응암동)서울특별시 은평구 응암동 603번지 55호20031010처분확정개선명령공중위생관리법제4조제3항및 제7항20031010영업소내 면허증 미게시개선명령<NA>93.63
610311000020031015358이용업일반이용업은성이용원서울특별시 은평구 응암로 173, (응암동,2층)서울특별시 은평구 응암동 598번지 12호 2층20031010처분확정경고공중위생관리법 제4조제3항 및 제7항20031010영업소내 면허증미게시경고<NA><NA>
611311000020030929221이용업일반이용업뉴그린서울특별시 은평구 진흥로 101, (역촌동)서울특별시 은평구 역촌동 17번지 15호20030926처분확정개선명령공중위생관리법제4조제7항20030926요금표 미게시개선명령<NA>51.69
612311000020030924140숙박업(일반)여관업쉴모텔서울특별시 은평구 통일로82길 6, (불광동)서울특별시 은평구 불광동 484번지 64호20030923처분확정개선명령공중위생관리법제4조제7항20030923신고증, 요금표 미게시개선명령<NA>918.36
613311000020030909327이용업일반이용업궁전이용원서울특별시 은평구 은평로 205-1, (녹번동,지하1층)서울특별시 은평구 녹번동 73번지 14호 지하1층20030908처분확정개선명령공중위생관리법제11조제1항 동법시행규칙제19조20030908영업소내 신고증 등 미게첨개선명령<NA>104.65
614311000020030909257이용업일반이용업월드이용원서울특별시 은평구 은평로 225, (녹번동,지층)서울특별시 은평구 녹번동 245번지 지층20030908처분확정개선명령공중위생관리법제11조제1항 동법 시행규칙제19조20030908영업소내 신고증등 미게첨개선명령<NA>47.31
61531100002003090340이용업일반이용업미래서울특별시 은평구 갈현로 171, (구산동)서울특별시 은평구 구산동 202번지 18호20030829처분확정개선명령공중위생관리법제11조제1항 동법시행규칙제19조20030829업소내 음란물건 보관개선명령<NA>29.49
616311000020030902178이용업일반이용업신성서울특별시 은평구 통일로71길 30, (대조동)서울특별시 은평구 대조동 3번지 15호20030613처분확정영업정지 2월공중위생관리법제11조제1항 동법 시행규칙제19조20030613풍속영업의규제에관한법률 위반(음란행위)영업정지 2월<NA>70.84
617311000020030703114숙박업(일반)여관업신도장서울특별시 은평구 통일로 707, (대조동)서울특별시 은평구 대조동 15번지 120호20030614처분확정영업정지공중위생관리법제11조제1항 시행규칙제19조20030614윤락알선영업정지<NA>468.06
618311000020030703114숙박업(일반)여관업신도장서울특별시 은평구 통일로 707, (대조동)서울특별시 은평구 대조동 15번지 120호20030614처분확정영업정지풍속영업의규제에관한법률 위반20030614윤락행위방지법 위반영업정지<NA>468.06

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
30311000020170215140숙박업(일반)여관업쉴모텔서울특별시 은평구 통일로82길 6, (불광동)서울특별시 은평구 불광동 484번지 64호20161219처분확정과징금부과(156만원)법 제11조제1항201612162016.12.16.04:30경 청소년 이성혼숙 장소제공(1차) - 서울은평경찰서 적발과징금부과(156만원)<NA>918.364
31311000020170627461이용업일반이용업가위손서울특별시 은평구 응암로 192, 지하층 B01호 (응암동)서울특별시 은평구 응암동 601번지 69호 (B01호)20160519처분확정영업정지 및 이용사면허정지 각법 제11조제1항201605192016.05.19. 여종업원을 고용하여 업소를 찾아오는 불특정 다수의 남성들에게 8만원의 재산상 이익을 받고 유사성교행위를 하게하여 성매매 알선(1차)(서울지방경찰청 적발)영업정지 및 이용사면허정지 각<NA>12.954
1431100002011012113숙박업(일반)여관업문화서울특별시 은평구 불광로 25-1, (대조동)서울특별시 은평구 대조동 9번지 12호20100821처분확정영업정지 2월(2011.02.01~2011.03.31)공중위생관리법 제11조20100821성매매알선 등 행위 및 장소제공영업정지 2월(2011.02.01~2011.03.31)<NA>59.53
0311000020050907129숙박업(일반)여관업에쎄서울특별시 은평구 가좌로 252, (응암동)서울특별시 은평구 응암동 584번지 49호20041224처분확정과징금부과공중위생관리법제11조제1항20041224청소년남녀혼숙과징금부과<NA>729.042
131100002007050869숙박업(일반)여인숙업태경장여관서울특별시 은평구 통일로 585, (응암동)서울특별시 은평구 응암동 31번지 12호20070226처분확정과징금부과공중위생관리법제11조20070226청소년이성혼숙과징금부과<NA>142.022
231100002008021214숙박업(일반)여관업평화장서울특별시 은평구 은평로18길 1-3, (응암동)서울특별시 은평구 응암동 60번지 12호20080122처분확정경고공중위생관리법 17,19,22,시행규칙 19조200801222007년 위생교육미이수경고<NA>178.342
3311000020081007180이용업일반이용업광명이용원서울특별시 은평구 통일로 728, (불광동)서울특별시 은평구 불광동 281번지 104호20080908처분확정과태료부과공중위생관리법 제3조200809082007년 8월경부터 영업시설물을 전부 철거하였으나 현재까지 폐업신고를 하지 않음과태료부과<NA>50.422
4311000020081103121목욕장업공동탕업+찜질시설서비스영업메트로불한증막사우나서울특별시 은평구 은평로 108, (응암동,외9필지 메트로럭스주상APT 1B01,2B01)서울특별시 은평구 응암동 110번지 9호 외9필지 메트로럭스주상APT 1B01,2B0120080922처분확정경고공중위생관리법 제4조200807032008.07.02 16:00부터 익일 02:30까지 청소년 김예성(만9세)외2명을 보호자 동의없이 출입시켜 서울서부경찰서 녹번지구대에 적발되었음경고<NA>2208.882
5311000020081103121목욕장업공동탕업+찜질시설서비스영업메트로불한증막사우나서울특별시 은평구 은평로 108, (응암동,외9필지 메트로럭스주상APT 1B01,2B01)서울특별시 은평구 응암동 110번지 9호 외9필지 메트로럭스주상APT 1B01,2B0120080922처분확정과태료부과공중위생관리법 제4조200807032008.07.02 16:00부터 익일 02:30까지 청소년 김예성(만9세)외2명을 보호자 동의없이 출입시켜 서울서부경찰서 녹번지구대에 적발되었음과태료부과<NA>2208.882
6311000020081103180이용업일반이용업광명이용원서울특별시 은평구 통일로 728, (불광동)서울특별시 은평구 불광동 281번지 104호20080908처분확정영업소폐쇄공중위생관리법 제3조200809082007년 8월경부터 영업시설물을 전부 철거하였으나 현재까지 폐업신고를 하지 않음영업소폐쇄<NA>50.422