Overview

Dataset statistics

Number of variables17
Number of observations777
Missing cells84
Missing cells (%)0.6%
Duplicate rows39
Duplicate rows (%)5.0%
Total size in memory107.9 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(㎡)
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-10913/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 39 (5.0%) 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 2 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 업종명 and 2 other fieldsHigh correlation
업종명 is highly overall correlated with 영업장면적(㎡) and 2 other fieldsHigh correlation
업태명 is highly overall correlated with 영업장면적(㎡) and 2 other fieldsHigh correlation
처분기간 is highly overall correlated with 위반일자 and 3 other fieldsHigh correlation
처분기간 is highly imbalanced (92.1%)Imbalance
소재지도로명 has 59 (7.6%) missing valuesMissing
영업장면적(㎡) has 22 (2.8%) missing valuesMissing
영업장면적(㎡) is highly skewed (γ1 = 26.39293525)Skewed

Reproduction

Analysis started2024-05-11 04:47:22.434592
Analysis finished2024-05-11 04:47:34.191483
Duration11.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
3080000
777 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 777
100.0%

Length

2024-05-11T04:47:34.418935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:47:35.045753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 777
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct394
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20118463
Minimum20010104
Maximum20700714
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T04:47:35.594478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010104
5-th percentile20020326
Q120061016
median20111221
Q320170807
95-th percentile20230665
Maximum20700714
Range690610
Interquartile range (IQR)109791

Descriptive statistics

Standard deviation69560.586
Coefficient of variation (CV)0.0034575497
Kurtosis4.8880943
Mean20118463
Median Absolute Deviation (MAD)59499
Skewness0.79384373
Sum1.5632046 × 1010
Variance4.8386751 × 109
MonotonicityNot monotonic
2024-05-11T04:47:36.115823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20231005 24
 
3.1%
20170807 23
 
3.0%
20200316 22
 
2.8%
20211202 21
 
2.7%
20130325 20
 
2.6%
20020326 12
 
1.5%
20170421 9
 
1.2%
20050504 9
 
1.2%
20020401 8
 
1.0%
20070604 8
 
1.0%
Other values (384) 621
79.9%
ValueCountFrequency (%)
20010104 1
0.1%
20010210 1
0.1%
20010728 2
0.3%
20010809 1
0.1%
20010811 1
0.1%
20010910 1
0.1%
20011005 1
0.1%
20011006 1
0.1%
20011010 1
0.1%
20011016 2
0.3%
ValueCountFrequency (%)
20700714 1
 
0.1%
20240430 1
 
0.1%
20240402 1
 
0.1%
20240401 1
 
0.1%
20240227 1
 
0.1%
20240129 1
 
0.1%
20231228 2
0.3%
20231211 3
0.4%
20231208 1
 
0.1%
20231025 2
0.3%

교부번호
Text

Distinct389
Distinct (%)50.3%
Missing3
Missing (%)0.4%
Memory size6.2 KiB
2024-05-11T04:47:37.151876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length5.75323
Min length2

Characters and Unicode

Total characters4453
Distinct characters17
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

Unique215 ?
Unique (%)27.8%

Sample

1st row234
2nd row223
3rd row017
4th row017
5th row083
ValueCountFrequency (%)
200 13
 
1.7%
025 10
 
1.3%
217 10
 
1.3%
075 10
 
1.3%
165 10
 
1.3%
072 8
 
1.0%
003 8
 
1.0%
210 8
 
1.0%
066 8
 
1.0%
148 8
 
1.0%
Other values (379) 681
88.0%
2024-05-11T04:47:38.733617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1642
36.9%
1 610
 
13.7%
2 477
 
10.7%
5 305
 
6.8%
3 268
 
6.0%
4 252
 
5.7%
6 197
 
4.4%
- 155
 
3.5%
7 147
 
3.3%
9 139
 
3.1%
Other values (7) 261
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4154
93.3%
Dash Punctuation 155
 
3.5%
Other Letter 144
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1642
39.5%
1 610
 
14.7%
2 477
 
11.5%
5 305
 
7.3%
3 268
 
6.5%
4 252
 
6.1%
6 197
 
4.7%
7 147
 
3.5%
9 139
 
3.3%
8 117
 
2.8%
Other Letter
ValueCountFrequency (%)
강 36
25.0%
북 36
25.0%
용 19
13.2%
역 19
13.2%
세 17
11.8%
탁 17
11.8%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4309
96.8%
Hangul 144
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1642
38.1%
1 610
 
14.2%
2 477
 
11.1%
5 305
 
7.1%
3 268
 
6.2%
4 252
 
5.8%
6 197
 
4.6%
- 155
 
3.6%
7 147
 
3.4%
9 139
 
3.2%
Hangul
ValueCountFrequency (%)
강 36
25.0%
북 36
25.0%
용 19
13.2%
역 19
13.2%
세 17
11.8%
탁 17
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4309
96.8%
Hangul 144
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1642
38.1%
1 610
 
14.2%
2 477
 
11.1%
5 305
 
7.1%
3 268
 
6.2%
4 252
 
5.8%
6 197
 
4.6%
- 155
 
3.6%
7 147
 
3.4%
9 139
 
3.2%
Hangul
ValueCountFrequency (%)
강 36
25.0%
북 36
25.0%
용 19
13.2%
역 19
13.2%
세 17
11.8%
탁 17
11.8%

업종명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
숙박업(일반)
347 
이용업
139 
일반미용업
86 
목욕장업
56 
피부미용업
46 
Other values (13)
103 

Length

Max length23
Median length16
Mean length5.7245817
Min length3

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 347
44.7%
이용업 139
17.9%
일반미용업 86
 
11.1%
목욕장업 56
 
7.2%
피부미용업 46
 
5.9%
위생관리용역업 30
 
3.9%
세탁업 23
 
3.0%
미용업 12
 
1.5%
네일미용업 8
 
1.0%
종합미용업 8
 
1.0%
Other values (8) 22
 
2.8%

Length

2024-05-11T04:47:39.346310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 347
42.6%
이용업 139
17.1%
일반미용업 96
 
11.8%
목욕장업 56
 
6.9%
피부미용업 50
 
6.1%
위생관리용역업 30
 
3.7%
미용업 28
 
3.4%
세탁업 23
 
2.8%
네일미용업 20
 
2.5%
화장ㆍ분장 16
 
2.0%
Other values (2) 9
 
1.1%

업태명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
여관업
339 
일반이용업
139 
일반미용업
99 
피부미용업
56 
공동탕업
38 
Other values (13)
106 

Length

Max length14
Median length9
Mean length4.2303732
Min length2

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 339
43.6%
일반이용업 139
17.9%
일반미용업 99
 
12.7%
피부미용업 56
 
7.2%
공동탕업 38
 
4.9%
위생관리용역업 30
 
3.9%
네일아트업 20
 
2.6%
일반세탁업 17
 
2.2%
찜질시설서비스영업 15
 
1.9%
빨래방업 6
 
0.8%
Other values (8) 18
 
2.3%

Length

2024-05-11T04:47:39.964978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여관업 339
43.6%
일반이용업 139
17.9%
일반미용업 99
 
12.7%
피부미용업 56
 
7.2%
공동탕업 38
 
4.9%
위생관리용역업 30
 
3.9%
네일아트업 20
 
2.6%
일반세탁업 17
 
2.2%
찜질시설서비스영업 15
 
1.9%
빨래방업 6
 
0.8%
Other values (8) 19
 
2.4%

업소명
Text

Distinct441
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T04:47:40.920253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length4.5791506
Min length1

Characters and Unicode

Total characters3558
Distinct characters396
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)36.3%

Sample

1st row아람장
2nd row기장 아카데미하우스
3rd row신일장
4th row신일장
5th row화성
ValueCountFrequency (%)
진영 12
 
1.4%
명가 11
 
1.3%
천지장모텔 11
 
1.3%
번동여인숙 8
 
1.0%
뉴도봉장 8
 
1.0%
그림파크 8
 
1.0%
광성 8
 
1.0%
리젠트모텔 8
 
1.0%
정민장 8
 
1.0%
모텔 7
 
0.8%
Other values (461) 744
89.3%
2024-05-11T04:47:42.286510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 102
 
2.9%
장 100
 
2.8%
모 97
 
2.7%
텔 96
 
2.7%
이 84
 
2.4%
어 77
 
2.2%
원 67
 
1.9%
헤 63
 
1.8%
리 62
 
1.7%
용 58
 
1.6%
Other values (386) 2752
77.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3209
90.2%
Uppercase Letter 106
 
3.0%
Space Separator 56
 
1.6%
Close Punctuation 51
 
1.4%
Open Punctuation 51
 
1.4%
Lowercase Letter 45
 
1.3%
Decimal Number 22
 
0.6%
Other Punctuation 17
 
0.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 102
 
3.2%
장 100
 
3.1%
모 97
 
3.0%
텔 96
 
3.0%
이 84
 
2.6%
어 77
 
2.4%
원 67
 
2.1%
헤 63
 
2.0%
리 62
 
1.9%
용 58
 
1.8%
Other values (335) 2403
74.9%
Uppercase Letter
ValueCountFrequency (%)
L 11
 
10.4%
E 9
 
8.5%
T 8
 
7.5%
M 7
 
6.6%
O 7
 
6.6%
N 6
 
5.7%
R 6
 
5.7%
U 6
 
5.7%
C 6
 
5.7%
I 5
 
4.7%
Other values (11) 35
33.0%
Lowercase Letter
ValueCountFrequency (%)
h 5
11.1%
a 5
11.1%
i 4
 
8.9%
e 4
 
8.9%
s 3
 
6.7%
k 3
 
6.7%
n 3
 
6.7%
o 3
 
6.7%
l 3
 
6.7%
p 2
 
4.4%
Other values (6) 10
22.2%
Decimal Number
ValueCountFrequency (%)
2 9
40.9%
4 6
27.3%
1 4
18.2%
6 2
 
9.1%
5 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
？ 6
35.3%
. 5
29.4%
& 4
23.5%
# 1
 
5.9%
; 1
 
5.9%
Space Separator
ValueCountFrequency (%)
56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3204
90.1%
Common 198
 
5.6%
Latin 151
 
4.2%
Han 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 102
 
3.2%
장 100
 
3.1%
모 97
 
3.0%
텔 96
 
3.0%
이 84
 
2.6%
어 77
 
2.4%
원 67
 
2.1%
헤 63
 
2.0%
리 62
 
1.9%
용 58
 
1.8%
Other values (333) 2398
74.8%
Latin
ValueCountFrequency (%)
L 11
 
7.3%
E 9
 
6.0%
T 8
 
5.3%
M 7
 
4.6%
O 7
 
4.6%
N 6
 
4.0%
R 6
 
4.0%
U 6
 
4.0%
C 6
 
4.0%
I 5
 
3.3%
Other values (27) 80
53.0%
Common
ValueCountFrequency (%)
56
28.3%
) 51
25.8%
( 51
25.8%
2 9
 
4.5%
？ 6
 
3.0%
4 6
 
3.0%
. 5
 
2.5%
1 4
 
2.0%
& 4
 
2.0%
6 2
 
1.0%
Other values (4) 4
 
2.0%
Han
ValueCountFrequency (%)
愛 4
80.0%
美 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3204
90.1%
ASCII 343
 
9.6%
None 6
 
0.2%
CJK 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 102
 
3.2%
장 100
 
3.1%
모 97
 
3.0%
텔 96
 
3.0%
이 84
 
2.6%
어 77
 
2.4%
원 67
 
2.1%
헤 63
 
2.0%
리 62
 
1.9%
용 58
 
1.8%
Other values (333) 2398
74.8%
ASCII
ValueCountFrequency (%)
56
16.3%
) 51
 
14.9%
( 51
 
14.9%
L 11
 
3.2%
2 9
 
2.6%
E 9
 
2.6%
T 8
 
2.3%
M 7
 
2.0%
O 7
 
2.0%
N 6
 
1.7%
Other values (40) 128
37.3%
None
ValueCountFrequency (%)
？ 6
100.0%
CJK
ValueCountFrequency (%)
愛 4
80.0%
美 1
 
20.0%

소재지도로명
Text

MISSING 

Distinct404
Distinct (%)56.3%
Missing59
Missing (%)7.6%
Memory size6.2 KiB
2024-05-11T04:47:42.973024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length27.598886
Min length23

Characters and Unicode

Total characters19816
Distinct characters161
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

Unique258 ?
Unique (%)35.9%

Sample

1st row서울특별시 강북구 삼양로181길 101, (우이동)
2nd row서울특별시 강북구 한천로 1319, (수유동)
3rd row서울특별시 강북구 솔샘로67길 137, (미아동,(큰마을길 69))
4th row서울특별시 강북구 솔샘로67길 137, (미아동)
5th row서울특별시 강북구 도봉로10나길 4, (미아동)
ValueCountFrequency (%)
서울특별시 718
18.7%
강북구 718
18.7%
수유동 299
 
7.8%
미아동 237
 
6.2%
도봉로 85
 
2.2%
번동 85
 
2.2%
한천로 43
 
1.1%
도봉로73길 34
 
0.9%
1층 34
 
0.9%
삼양로 33
 
0.9%
Other values (480) 1549
40.4%
2024-05-11T04:47:44.059693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3117
 
15.7%
, 835
 
4.2%
) 773
 
3.9%
( 773
 
3.9%
동 734
 
3.7%
로 727
 
3.7%
서 720
 
3.6%
시 720
 
3.6%
북 719
 
3.6%
울 719
 
3.6%
Other values (151) 9979
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11214
56.6%
Space Separator 3117
 
15.7%
Decimal Number 2979
 
15.0%
Other Punctuation 839
 
4.2%
Close Punctuation 773
 
3.9%
Open Punctuation 773
 
3.9%
Dash Punctuation 105
 
0.5%
Uppercase Letter 14
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 734
 
6.5%
로 727
 
6.5%
서 720
 
6.4%
시 720
 
6.4%
북 719
 
6.4%
울 719
 
6.4%
구 719
 
6.4%
강 718
 
6.4%
특 718
 
6.4%
별 718
 
6.4%
Other values (130) 4002
35.7%
Decimal Number
ValueCountFrequency (%)
1 612
20.5%
3 405
13.6%
2 298
10.0%
4 279
9.4%
7 266
8.9%
9 238
 
8.0%
8 235
 
7.9%
5 221
 
7.4%
6 214
 
7.2%
0 211
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
B 5
35.7%
S 4
28.6%
K 4
28.6%
A 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 835
99.5%
. 4
 
0.5%
Space Separator
ValueCountFrequency (%)
3117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 773
100.0%
Open Punctuation
ValueCountFrequency (%)
( 773
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11214
56.6%
Common 8588
43.3%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 734
 
6.5%
로 727
 
6.5%
서 720
 
6.4%
시 720
 
6.4%
북 719
 
6.4%
울 719
 
6.4%
구 719
 
6.4%
강 718
 
6.4%
특 718
 
6.4%
별 718
 
6.4%
Other values (130) 4002
35.7%
Common
ValueCountFrequency (%)
3117
36.3%
, 835
 
9.7%
) 773
 
9.0%
( 773
 
9.0%
1 612
 
7.1%
3 405
 
4.7%
2 298
 
3.5%
4 279
 
3.2%
7 266
 
3.1%
9 238
 
2.8%
Other values (7) 992
 
11.6%
Latin
ValueCountFrequency (%)
B 5
35.7%
S 4
28.6%
K 4
28.6%
A 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11214
56.6%
ASCII 8602
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3117
36.2%
, 835
 
9.7%
) 773
 
9.0%
( 773
 
9.0%
1 612
 
7.1%
3 405
 
4.7%
2 298
 
3.5%
4 279
 
3.2%
7 266
 
3.1%
9 238
 
2.8%
Other values (11) 1006
 
11.7%
Hangul
ValueCountFrequency (%)
동 734
 
6.5%
로 727
 
6.5%
서 720
 
6.4%
시 720
 
6.4%
북 719
 
6.4%
울 719
 
6.4%
구 719
 
6.4%
강 718
 
6.4%
특 718
 
6.4%
별 718
 
6.4%
Other values (130) 4002
35.7%

소재지지번
Text

Distinct430
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T04:47:44.774570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length45
Mean length26.978121
Min length22

Characters and Unicode

Total characters20962
Distinct characters150
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

Unique273 ?
Unique (%)35.1%

Sample

1st row서울특별시 강북구 우이동 224번지 7호
2nd row서울특별시 강북구 수유동 산 76번지 0호
3rd row서울특별시 강북구 미아동 316번지 1호 (큰마을길 69)
4th row서울특별시 강북구 미아동 316번지 1호
5th row서울특별시 강북구 미아동 55번지 58호
ValueCountFrequency (%)
서울특별시 777
18.7%
강북구 777
18.7%
수유동 360
 
8.7%
미아동 294
 
7.1%
번동 109
 
2.6%
446번지 42
 
1.0%
5호 42
 
1.0%
3호 40
 
1.0%
1호 39
 
0.9%
9호 32
 
0.8%
Other values (466) 1644
39.6%
2024-05-11T04:47:46.138595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5544
26.4%
번 888
 
4.2%
지 814
 
3.9%
동 784
 
3.7%
서 779
 
3.7%
호 779
 
3.7%
울 778
 
3.7%
구 778
 
3.7%
시 778
 
3.7%
강 777
 
3.7%
Other values (140) 8263
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11384
54.3%
Space Separator 5544
26.4%
Decimal Number 3823
 
18.2%
Open Punctuation 67
 
0.3%
Close Punctuation 67
 
0.3%
Dash Punctuation 39
 
0.2%
Uppercase Letter 20
 
0.1%
Other Punctuation 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 888
 
7.8%
지 814
 
7.2%
동 784
 
6.9%
서 779
 
6.8%
호 779
 
6.8%
울 778
 
6.8%
구 778
 
6.8%
시 778
 
6.8%
강 777
 
6.8%
북 777
 
6.8%
Other values (119) 3452
30.3%
Decimal Number
ValueCountFrequency (%)
1 720
18.8%
4 543
14.2%
2 452
11.8%
3 424
11.1%
7 312
8.2%
6 305
8.0%
5 296
7.7%
0 286
 
7.5%
9 253
 
6.6%
8 232
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
K 7
35.0%
S 7
35.0%
B 5
25.0%
A 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 12
66.7%
. 5
27.8%
/ 1
 
5.6%
Space Separator
ValueCountFrequency (%)
5544
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11384
54.3%
Common 9558
45.6%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 888
 
7.8%
지 814
 
7.2%
동 784
 
6.9%
서 779
 
6.8%
호 779
 
6.8%
울 778
 
6.8%
구 778
 
6.8%
시 778
 
6.8%
강 777
 
6.8%
북 777
 
6.8%
Other values (119) 3452
30.3%
Common
ValueCountFrequency (%)
5544
58.0%
1 720
 
7.5%
4 543
 
5.7%
2 452
 
4.7%
3 424
 
4.4%
7 312
 
3.3%
6 305
 
3.2%
5 296
 
3.1%
0 286
 
3.0%
9 253
 
2.6%
Other values (7) 423
 
4.4%
Latin
ValueCountFrequency (%)
K 7
35.0%
S 7
35.0%
B 5
25.0%
A 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11384
54.3%
ASCII 9578
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5544
57.9%
1 720
 
7.5%
4 543
 
5.7%
2 452
 
4.7%
3 424
 
4.4%
7 312
 
3.3%
6 305
 
3.2%
5 296
 
3.1%
0 286
 
3.0%
9 253
 
2.6%
Other values (11) 443
 
4.6%
Hangul
ValueCountFrequency (%)
번 888
 
7.8%
지 814
 
7.2%
동 784
 
6.9%
서 779
 
6.8%
호 779
 
6.8%
울 778
 
6.8%
구 778
 
6.8%
시 778
 
6.8%
강 777
 
6.8%
북 777
 
6.8%
Other values (119) 3452
30.3%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct409
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20116116
Minimum20010104
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T04:47:46.897769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010104
5-th percentile20020312
Q120060628
median20110729
Q320170620
95-th percentile20230311
Maximum20240222
Range230118
Interquartile range (IQR)109992

Descriptive statistics

Standard deviation65944.609
Coefficient of variation (CV)0.0032781979
Kurtosis-1.1574532
Mean20116116
Median Absolute Deviation (MAD)59581
Skewness0.085044931
Sum1.5630222 × 1010
Variance4.3486914 × 109
MonotonicityNot monotonic
2024-05-11T04:47:47.588403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230828 24
 
3.1%
20191231 23
 
3.0%
20211115 22
 
2.8%
20170102 13
 
1.7%
20020325 12
 
1.5%
20140219 10
 
1.3%
20180206 10
 
1.3%
20150130 10
 
1.3%
20160119 9
 
1.2%
20050322 9
 
1.2%
Other values (399) 635
81.7%
ValueCountFrequency (%)
20010104 1
0.1%
20010121 1
0.1%
20010210 1
0.1%
20010728 2
0.3%
20010809 1
0.1%
20010811 1
0.1%
20010910 1
0.1%
20010919 1
0.1%
20011005 1
0.1%
20011006 1
0.1%
ValueCountFrequency (%)
20240222 1
 
0.1%
20240215 2
 
0.3%
20240205 1
 
0.1%
20240118 1
 
0.1%
20231215 2
 
0.3%
20230925 2
 
0.3%
20230922 1
 
0.1%
20230918 2
 
0.3%
20230828 24
3.1%
20230701 1
 
0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
처분확정
777 

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 777
100.0%

Length

2024-05-11T04:47:48.222502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:47:48.689998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 777
100.0%

처분명
Text

Distinct178
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T04:47:49.320987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length57
Mean length10.3861
Min length2

Characters and Unicode

Total characters8070
Distinct characters140
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

Unique124 ?
Unique (%)16.0%

Sample

1st row영업정지2월 갈음 과징금 180만원
2nd row경고 및 과태료 20만원 부과(자진납부 16만원)
3rd row과징금 부과
4th row영업정지
5th row영업정지(2003.9.29-10.28)
ValueCountFrequency (%)
영업정지 134
 
9.2%
과징금부과 106
 
7.3%
과태료부과 105
 
7.2%
경고 96
 
6.6%
개선명령 80
 
5.5%
영업소폐쇄 68
 
4.7%
과태료 68
 
4.7%
과징금 64
 
4.4%
부과 58
 
4.0%
및 54
 
3.7%
Other values (212) 619
42.6%
2024-05-11T04:47:50.339613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 723
 
9.0%
675
 
8.4%
2 382
 
4.7%
부 361
 
4.5%
0 345
 
4.3%
업 330
 
4.1%
영 301
 
3.7%
지 266
 
3.3%
1 265
 
3.3%
정 246
 
3.0%
Other values (130) 4176
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5564
68.9%
Decimal Number 1303
 
16.1%
Space Separator 675
 
8.4%
Other Punctuation 225
 
2.8%
Close Punctuation 131
 
1.6%
Open Punctuation 131
 
1.6%
Dash Punctuation 25
 
0.3%
Math Symbol 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 723
 
13.0%
부 361
 
6.5%
업 330
 
5.9%
영 301
 
5.4%
지 266
 
4.8%
정 246
 
4.4%
원 216
 
3.9%
만 207
 
3.7%
징 203
 
3.6%
금 203
 
3.6%
Other values (110) 2508
45.1%
Decimal Number
ValueCountFrequency (%)
2 382
29.3%
0 345
26.5%
1 265
20.3%
6 75
 
5.8%
4 64
 
4.9%
8 52
 
4.0%
3 48
 
3.7%
5 30
 
2.3%
9 21
 
1.6%
7 21
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 177
78.7%
, 26
 
11.6%
' 17
 
7.6%
/ 5
 
2.2%
Math Symbol
ValueCountFrequency (%)
~ 13
81.2%
→ 3
 
18.8%
Space Separator
ValueCountFrequency (%)
675
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5564
68.9%
Common 2506
31.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 723
 
13.0%
부 361
 
6.5%
업 330
 
5.9%
영 301
 
5.4%
지 266
 
4.8%
정 246
 
4.4%
원 216
 
3.9%
만 207
 
3.7%
징 203
 
3.6%
금 203
 
3.6%
Other values (110) 2508
45.1%
Common
ValueCountFrequency (%)
675
26.9%
2 382
15.2%
0 345
13.8%
1 265
 
10.6%
. 177
 
7.1%
) 131
 
5.2%
( 131
 
5.2%
6 75
 
3.0%
4 64
 
2.6%
8 52
 
2.1%
Other values (10) 209
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5564
68.9%
ASCII 2503
31.0%
Arrows 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 723
 
13.0%
부 361
 
6.5%
업 330
 
5.9%
영 301
 
5.4%
지 266
 
4.8%
정 246
 
4.4%
원 216
 
3.9%
만 207
 
3.7%
징 203
 
3.6%
금 203
 
3.6%
Other values (110) 2508
45.1%
ASCII
ValueCountFrequency (%)
675
27.0%
2 382
15.3%
0 345
13.8%
1 265
 
10.6%
. 177
 
7.1%
) 131
 
5.2%
( 131
 
5.2%
6 75
 
3.0%
4 64
 
2.6%
8 52
 
2.1%
Other values (9) 206
 
8.2%
Arrows
ValueCountFrequency (%)
→ 3
100.0%

법적근거
Text

Distinct128
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T04:47:51.098289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length14.069498
Min length5

Characters and Unicode

Total characters10932
Distinct characters63
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

Unique74 ?
Unique (%)9.5%

Sample

1st row공중위생관리법 제11조
2nd row공중위생관리법 제11조 및 같은법 제17조, 같은법 제22조
3rd row공중위생관리법 제11조 제1항
4th row법 제11조제1항
5th row공중위생관리법 제11조,동법시행ㄱ칙제19조
ValueCountFrequency (%)
공중위생관리법 425
23.4%
법 234
12.9%
제11조 215
11.8%
제17조 125
 
6.9%
제22조 88
 
4.8%
제11조제1항 88
 
4.8%
제22조제2항제6호 69
 
3.8%
및 53
 
2.9%
제11조제3항제1호 43
 
2.4%
제4조 42
 
2.3%
Other values (112) 435
23.9%
2024-05-11T04:47:52.196966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 1443
13.2%
1 1371
12.5%
1040
 
9.5%
조 966
 
8.8%
법 833
 
7.6%
위 527
 
4.8%
공 513
 
4.7%
중 512
 
4.7%
생 512
 
4.7%
관 500
 
4.6%
Other values (53) 2715
24.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7321
67.0%
Decimal Number 2350
 
21.5%
Space Separator 1040
 
9.5%
Other Punctuation 219
 
2.0%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1443
19.7%
조 966
13.2%
법 833
11.4%
위 527
 
7.2%
공 513
 
7.0%
중 512
 
7.0%
생 512
 
7.0%
관 500
 
6.8%
리 491
 
6.7%
항 354
 
4.8%
Other values (39) 670
9.2%
Decimal Number
ValueCountFrequency (%)
1 1371
58.3%
2 460
 
19.6%
7 151
 
6.4%
3 106
 
4.5%
6 72
 
3.1%
4 63
 
2.7%
0 48
 
2.0%
8 38
 
1.6%
9 37
 
1.6%
5 4
 
0.2%
Space Separator
ValueCountFrequency (%)
1040
100.0%
Other Punctuation
ValueCountFrequency (%)
, 219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7321
67.0%
Common 3611
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1443
19.7%
조 966
13.2%
법 833
11.4%
위 527
 
7.2%
공 513
 
7.0%
중 512
 
7.0%
생 512
 
7.0%
관 500
 
6.8%
리 491
 
6.7%
항 354
 
4.8%
Other values (39) 670
9.2%
Common
ValueCountFrequency (%)
1 1371
38.0%
1040
28.8%
2 460
 
12.7%
, 219
 
6.1%
7 151
 
4.2%
3 106
 
2.9%
6 72
 
2.0%
4 63
 
1.7%
0 48
 
1.3%
8 38
 
1.1%
Other values (4) 43
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7320
67.0%
ASCII 3611
33.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 1443
19.7%
조 966
13.2%
법 833
11.4%
위 527
 
7.2%
공 513
 
7.0%
중 512
 
7.0%
생 512
 
7.0%
관 500
 
6.8%
리 491
 
6.7%
항 354
 
4.8%
Other values (38) 669
9.1%
ASCII
ValueCountFrequency (%)
1 1371
38.0%
1040
28.8%
2 460
 
12.7%
, 219
 
6.1%
7 151
 
4.2%
3 106
 
2.9%
6 72
 
2.0%
4 63
 
1.7%
0 48
 
1.3%
8 38
 
1.1%
Other values (4) 43
 
1.2%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct423
Distinct (%)54.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20064687
Minimum200402
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T04:47:52.773689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200402
5-th percentile20020312
Q120060628
median20110729
Q320170531
95-th percentile20230311
Maximum20240222
Range20039820
Interquartile range (IQR)109903

Descriptive statistics

Standard deviation1011900.3
Coefficient of variation (CV)0.050431901
Kurtosis382.70375
Mean20064687
Median Absolute Deviation (MAD)59581
Skewness-19.546785
Sum1.5590262 × 1010
Variance1.0239422 × 1012
MonotonicityNot monotonic
2024-05-11T04:47:53.345274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230828 24
 
3.1%
20211115 22
 
2.8%
20191231 22
 
2.8%
20020325 12
 
1.5%
20170102 11
 
1.4%
20140219 10
 
1.3%
20150130 10
 
1.3%
20020312 10
 
1.3%
20171229 10
 
1.3%
20100101 9
 
1.2%
Other values (413) 637
82.0%
ValueCountFrequency (%)
200402 1
 
0.1%
200407 1
 
0.1%
20000104 1
 
0.1%
20000523 1
 
0.1%
20001007 1
 
0.1%
20010205 1
 
0.1%
20010315 1
 
0.1%
20010619 1
 
0.1%
20010701 3
0.4%
20010706 1
 
0.1%
ValueCountFrequency (%)
20240222 1
 
0.1%
20240215 2
 
0.3%
20240205 1
 
0.1%
20240118 1
 
0.1%
20231215 2
 
0.3%
20230925 2
 
0.3%
20230922 1
 
0.1%
20230918 2
 
0.3%
20230828 24
3.1%
20230701 1
 
0.1%

위반내용
Text

Distinct241
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T04:47:54.098821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length53
Mean length14.266409
Min length4

Characters and Unicode

Total characters11085
Distinct characters232
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

Unique165 ?
Unique (%)21.2%

Sample

1st row청소년 이성 혼숙
2nd row위생교육 미필
3rd row청소년이성혼숙(1차)
4th row성매매알선
5th row윤락행위등방지법위반(윤락행위알선제공)
ValueCountFrequency (%)
청소년 148
 
6.7%
위생교육 136
 
6.2%
이성혼숙 113
 
5.1%
미필 71
 
3.2%
미이수 58
 
2.6%
및 47
 
2.1%
위생교육미필 44
 
2.0%
아니함 36
 
1.6%
장소제공 36
 
1.6%
멸실 33
 
1.5%
Other values (435) 1479
67.2%
2024-05-11T04:47:55.407964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1446
 
13.0%
위 397
 
3.6%
2 357
 
3.2%
년 355
 
3.2%
소 326
 
2.9%
이 323
 
2.9%
0 317
 
2.9%
미 253
 
2.3%
청 247
 
2.2%
생 247
 
2.2%
Other values (222) 6817
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7922
71.5%
Space Separator 1446
 
13.0%
Decimal Number 1088
 
9.8%
Other Punctuation 225
 
2.0%
Close Punctuation 183
 
1.7%
Open Punctuation 183
 
1.7%
Dash Punctuation 22
 
0.2%
Math Symbol 11
 
0.1%
Uppercase Letter 4
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 397
 
5.0%
년 355
 
4.5%
소 326
 
4.1%
이 323
 
4.1%
미 253
 
3.2%
청 247
 
3.1%
생 247
 
3.1%
숙 233
 
2.9%
성 229
 
2.9%
교 221
 
2.8%
Other values (198) 5091
64.3%
Decimal Number
ValueCountFrequency (%)
2 357
32.8%
0 317
29.1%
1 210
19.3%
9 40
 
3.7%
6 39
 
3.6%
3 35
 
3.2%
4 30
 
2.8%
5 28
 
2.6%
7 17
 
1.6%
8 15
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 157
69.8%
: 26
 
11.6%
, 20
 
8.9%
' 17
 
7.6%
/ 5
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
T 1
25.0%
V 1
25.0%
Space Separator
ValueCountFrequency (%)
1446
100.0%
Close Punctuation
ValueCountFrequency (%)
) 183
100.0%
Open Punctuation
ValueCountFrequency (%)
( 183
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7922
71.5%
Common 3159
 
28.5%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 397
 
5.0%
년 355
 
4.5%
소 326
 
4.1%
이 323
 
4.1%
미 253
 
3.2%
청 247
 
3.1%
생 247
 
3.1%
숙 233
 
2.9%
성 229
 
2.9%
교 221
 
2.8%
Other values (198) 5091
64.3%
Common
ValueCountFrequency (%)
1446
45.8%
2 357
 
11.3%
0 317
 
10.0%
1 210
 
6.6%
) 183
 
5.8%
( 183
 
5.8%
. 157
 
5.0%
9 40
 
1.3%
6 39
 
1.2%
3 35
 
1.1%
Other values (11) 192
 
6.1%
Latin
ValueCountFrequency (%)
C 2
50.0%
T 1
25.0%
V 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7922
71.5%
ASCII 3163
 
28.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1446
45.7%
2 357
 
11.3%
0 317
 
10.0%
1 210
 
6.6%
) 183
 
5.8%
( 183
 
5.8%
. 157
 
5.0%
9 40
 
1.3%
6 39
 
1.2%
3 35
 
1.1%
Other values (14) 196
 
6.2%
Hangul
ValueCountFrequency (%)
위 397
 
5.0%
년 355
 
4.5%
소 326
 
4.1%
이 323
 
4.1%
미 253
 
3.2%
청 247
 
3.1%
생 247
 
3.1%
숙 233
 
2.9%
성 229
 
2.9%
교 221
 
2.8%
Other values (198) 5091
64.3%

처분내용
Text

Distinct178
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T04:47:56.031296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length57
Mean length10.3861
Min length2

Characters and Unicode

Total characters8070
Distinct characters140
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

Unique124 ?
Unique (%)16.0%

Sample

1st row영업정지2월 갈음 과징금 180만원
2nd row경고 및 과태료 20만원 부과(자진납부 16만원)
3rd row과징금 부과
4th row영업정지
5th row영업정지(2003.9.29-10.28)
ValueCountFrequency (%)
영업정지 134
 
9.2%
과징금부과 106
 
7.3%
과태료부과 105
 
7.2%
경고 96
 
6.6%
개선명령 80
 
5.5%
영업소폐쇄 68
 
4.7%
과태료 68
 
4.7%
과징금 64
 
4.4%
부과 58
 
4.0%
및 54
 
3.7%
Other values (212) 619
42.6%
2024-05-11T04:47:57.225856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 723
 
9.0%
675
 
8.4%
2 382
 
4.7%
부 361
 
4.5%
0 345
 
4.3%
업 330
 
4.1%
영 301
 
3.7%
지 266
 
3.3%
1 265
 
3.3%
정 246
 
3.0%
Other values (130) 4176
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5564
68.9%
Decimal Number 1303
 
16.1%
Space Separator 675
 
8.4%
Other Punctuation 225
 
2.8%
Close Punctuation 131
 
1.6%
Open Punctuation 131
 
1.6%
Dash Punctuation 25
 
0.3%
Math Symbol 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 723
 
13.0%
부 361
 
6.5%
업 330
 
5.9%
영 301
 
5.4%
지 266
 
4.8%
정 246
 
4.4%
원 216
 
3.9%
만 207
 
3.7%
징 203
 
3.6%
금 203
 
3.6%
Other values (110) 2508
45.1%
Decimal Number
ValueCountFrequency (%)
2 382
29.3%
0 345
26.5%
1 265
20.3%
6 75
 
5.8%
4 64
 
4.9%
8 52
 
4.0%
3 48
 
3.7%
5 30
 
2.3%
9 21
 
1.6%
7 21
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 177
78.7%
, 26
 
11.6%
' 17
 
7.6%
/ 5
 
2.2%
Math Symbol
ValueCountFrequency (%)
~ 13
81.2%
→ 3
 
18.8%
Space Separator
ValueCountFrequency (%)
675
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5564
68.9%
Common 2506
31.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 723
 
13.0%
부 361
 
6.5%
업 330
 
5.9%
영 301
 
5.4%
지 266
 
4.8%
정 246
 
4.4%
원 216
 
3.9%
만 207
 
3.7%
징 203
 
3.6%
금 203
 
3.6%
Other values (110) 2508
45.1%
Common
ValueCountFrequency (%)
675
26.9%
2 382
15.2%
0 345
13.8%
1 265
 
10.6%
. 177
 
7.1%
) 131
 
5.2%
( 131
 
5.2%
6 75
 
3.0%
4 64
 
2.6%
8 52
 
2.1%
Other values (10) 209
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5564
68.9%
ASCII 2503
31.0%
Arrows 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 723
 
13.0%
부 361
 
6.5%
업 330
 
5.9%
영 301
 
5.4%
지 266
 
4.8%
정 246
 
4.4%
원 216
 
3.9%
만 207
 
3.7%
징 203
 
3.6%
금 203
 
3.6%
Other values (110) 2508
45.1%
ASCII
ValueCountFrequency (%)
675
27.0%
2 382
15.3%
0 345
13.8%
1 265
 
10.6%
. 177
 
7.1%
) 131
 
5.2%
( 131
 
5.2%
6 75
 
3.0%
4 64
 
2.6%
8 52
 
2.1%
Other values (9) 206
 
8.2%
Arrows
ValueCountFrequency (%)
→ 3
100.0%

처분기간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
762 
15
 
11
11
 
3
10
 
1

Length

Max length4
Median length4
Mean length3.96139
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 762
98.1%
15 11
 
1.4%
11 3
 
0.4%
10 1
 
0.1%

Length

2024-05-11T04:47:57.686482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:47:58.114903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 762
98.1%
15 11
 
1.4%
11 3
 
0.4%
10 1
 
0.1%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct362
Distinct (%)47.9%
Missing22
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean366.87225
Minimum0
Maximum76612
Zeros6
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T04:47:58.469498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q138.3
median79.2
Q3260.12
95-th percentile1200.06
Maximum76612
Range76612
Interquartile range (IQR)221.82

Descriptive statistics

Standard deviation2816.5024
Coefficient of variation (CV)7.6770658
Kurtosis714.94634
Mean366.87225
Median Absolute Deviation (MAD)54.2
Skewness26.392935
Sum276988.55
Variance7932685.8
MonotonicityNot monotonic
2024-05-11T04:47:58.925088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.0 14
 
1.8%
33.0 12
 
1.5%
53.2 11
 
1.4%
51.34 10
 
1.3%
74.51 8
 
1.0%
506.58 8
 
1.0%
20.16 8
 
1.0%
171.36 8
 
1.0%
96.5 8
 
1.0%
33.83 8
 
1.0%
Other values (352) 660
84.9%
(Missing) 22
 
2.8%
ValueCountFrequency (%)
0.0 6
0.8%
6.0 1
 
0.1%
7.0 1
 
0.1%
10.0 2
 
0.3%
10.78 1
 
0.1%
10.86 1
 
0.1%
11.34 1
 
0.1%
11.57 1
 
0.1%
12.09 1
 
0.1%
12.8 1
 
0.1%
ValueCountFrequency (%)
76612.0 1
 
0.1%
4004.02 1
 
0.1%
2879.68 6
0.8%
2316.37 1
 
0.1%
2137.0 2
 
0.3%
2076.15 3
0.4%
1998.33 1
 
0.1%
1887.14 1
 
0.1%
1603.0 1
 
0.1%
1570.74 2
 
0.3%

Interactions

2024-05-11T04:47:30.080750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:24.745504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:25.981341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:28.013688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:30.568368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:25.048633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:26.436041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:28.797655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:30.890687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:25.341987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:26.784765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:29.269860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:31.300025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:25.652695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:27.234890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:47:29.625302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T04:47:59.451396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.5310.4650.9870.0000.0000.083
업종명0.5311.0000.9780.6260.0000.9311.000
업태명0.4650.9781.0000.5200.0000.931NaN
지도점검일자0.9870.6260.5201.0000.0900.0000.092
위반일자0.0000.0000.0000.0901.000NaN0.000
처분기간0.0000.9310.9310.000NaN1.000NaN
영업장면적(㎡)0.0831.000NaN0.0920.000NaN1.000
2024-05-11T04:47:59.794022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명처분기간업태명
업종명1.0000.6740.670
처분기간0.6741.0000.674
업태명0.6700.6741.000
2024-05-11T04:48:00.062128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자영업장면적(㎡)업종명업태명처분기간
처분일자1.0000.9970.996-0.1770.3020.2590.000
지도점검일자0.9971.0000.999-0.1810.2950.2300.000
위반일자0.9960.9991.000-0.1820.0000.0001.000
영업장면적(㎡)-0.177-0.181-0.1821.0000.9891.0001.000
업종명0.3020.2950.0000.9891.0000.6700.674
업태명0.2590.2300.0001.0000.6701.0000.674
처분기간0.0000.0001.0001.0000.6740.6741.000

Missing values

2024-05-11T04:47:32.240397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T04:47:33.402963image/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.
2024-05-11T04:47:33.949326image/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(㎡)
0308000020060530234숙박업(일반)여관업아람장서울특별시 강북구 삼양로181길 101, (우이동)서울특별시 강북구 우이동 224번지 7호20060408처분확정영업정지2월 갈음 과징금 180만원공중위생관리법 제11조20060408청소년 이성 혼숙영업정지2월 갈음 과징금 180만원<NA>227.0
1308000020110404223숙박업(일반)관광호텔기장 아카데미하우스서울특별시 강북구 한천로 1319, (수유동)서울특별시 강북구 수유동 산 76번지 0호20110103처분확정경고 및 과태료 20만원 부과(자진납부 16만원)공중위생관리법 제11조 및 같은법 제17조, 같은법 제22조20101230위생교육 미필경고 및 과태료 20만원 부과(자진납부 16만원)<NA>4004.02
2308000020110624017숙박업(일반)여관업신일장서울특별시 강북구 솔샘로67길 137, (미아동,(큰마을길 69))서울특별시 강북구 미아동 316번지 1호 (큰마을길 69)20110502처분확정과징금 부과공중위생관리법 제11조 제1항20110502청소년이성혼숙(1차)과징금 부과<NA>271.41
3308000020171106017숙박업(일반)여관업신일장서울특별시 강북구 솔샘로67길 137, (미아동)서울특별시 강북구 미아동 316번지 1호20170425처분확정영업정지법 제11조제1항20170425성매매알선영업정지<NA>271.41
4308000020030923083숙박업(일반)여관업화성서울특별시 강북구 도봉로10나길 4, (미아동)서울특별시 강북구 미아동 55번지 58호20030821처분확정영업정지(2003.9.29-10.28)공중위생관리법 제11조,동법시행ㄱ칙제19조20030821윤락행위등방지법위반(윤락행위알선제공)영업정지(2003.9.29-10.28)<NA>167.59
5308000020040714014숙박업(일반)여관업태흥 여관<NA>서울특별시 강북구 수유동 174번지 24호20040708처분확정영업정지공중위생관리법제11조1항20040611윤락행위 알선 및 장소제공영업정지<NA>60.2
6308000020050708101숙박업(일반)여관업한성여관서울특별시 강북구 솔매로30길 12, (미아동)서울특별시 강북구 미아동 762번지 43호20050531처분확정영업정지2월 갈음 과징금 180만원 부과공중위생관리법 제11조제1항20050531청소년이성혼숙영업정지2월 갈음 과징금 180만원 부과<NA>92.49
7308000020031202040숙박업(일반)여관업C.L서울특별시 강북구 덕릉로28길 53, (미아동)서울특별시 강북구 미아동 187번지 3호20031006처분확정영업정지2월갈음과징금부과청소년보호법20030827청소년혼숙영업정지2월갈음과징금부과<NA>151.38
8308000020140213040숙박업(일반)여관업CL모텔서울특별시 강북구 덕릉로28길 53, (미아동)서울특별시 강북구 미아동 187번지 3호20140109처분확정경고공중위생관리법 제11조, 제17조, 제22조20140109위생교육 미필경고<NA>151.38
9308000020140213040숙박업(일반)여관업CL모텔서울특별시 강북구 덕릉로28길 53, (미아동)서울특별시 강북구 미아동 187번지 3호20140109처분확정과태료부과(자진납부 16만원)공중위생관리법 제11조, 제17조, 제22조20140109위생교육미필과태료부과(자진납부 16만원)<NA>151.38
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
7673080000202112012020-00001일반미용업, 화장ㆍ분장 미용업메이크업업마리즈 브라이덜서울특별시 강북구 도봉로 16, 빅토리아호텔 5층 (미아동)서울특별시 강북구 미아동 42번지 8호 빅토리아호텔20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>83.0
7683080000202112022017-00002피부미용업, 화장ㆍ분장 미용업피부미용업브로우션(BROWSSUN)서울특별시 강북구 도봉로10길 30, 3층 (미아동)서울특별시 강북구 미아동 54번지 88호20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>79.75
7693080000202112022019-00002피부미용업, 화장ㆍ분장 미용업피부미용업유얼더샵(yourtheshop)서울특별시 강북구 덕릉로 147-12, 1층 (번동)서울특별시 강북구 번동 411번지 92호 1층20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>53.79
7703080000202112022019-00001네일미용업, 화장ㆍ분장 미용업네일아트업더(The) 감동서울특별시 강북구 한천로124길 19, (번동)서울특별시 강북구 번동 459번지 62호20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>22.0
7713080000202112022018-00001네일미용업, 화장ㆍ분장 미용업네일아트업니타네일(Nita nail)서울특별시 강북구 인수봉로68길 42, 1층 (수유동)서울특별시 강북구 수유동 363번지 8호 1층20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>20.0
7723080000202112022019-00003네일미용업, 화장ㆍ분장 미용업네일아트업네일도 사랑스럽게서울특별시 강북구 노해로8가길 9, 반석빌딩 (수유동)서울특별시 강북구 수유동 223번지 5호 반석빌딩20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>33.0
7733080000202112022019-00004네일미용업, 화장ㆍ분장 미용업네일아트업이룸뷰티서울특별시 강북구 삼양로74길 63, 1층 (수유동)서울특별시 강북구 수유동 55번지 46호 1층20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>17.25
7743080000202112022019-00007네일미용업, 화장ㆍ분장 미용업네일아트업로제아네일서울특별시 강북구 도봉로87길 40, 3층 (수유동)서울특별시 강북구 수유동 222번지 66호 3층20211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>82.5
7753080000202112022019-00003네일미용업, 화장ㆍ분장 미용업네일아트업마레스튜디오서울특별시 강북구 솔샘로68길 25, 제이에스캐슬빌리지 201호 (미아동)서울특별시 강북구 미아동 460번지 100호 제이에스캐슬빌리지-20120211115처분확정과태료부과법 제22조제2항제6호202111152020년 기존영업자 위생교육 미이수과태료부과<NA>14.61
7763080000202003162017-00004일반미용업, 네일미용업, 화장ㆍ분장 미용업네일아트업네일해요서울특별시 강북구 한천로131길 41, (번동, B01호)서울특별시 강북구 번동 415번지 6호 B01호20191231처분확정과태료부과법 제22조제2항제6호201912312019년 위생교육미필과태료부과<NA>130.52

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
3308000020061109210숙박업(일반)여관업그림파크서울특별시 강북구 도봉로83길 9, (수유동)서울특별시 강북구 수유동 230번지 9호20060808처분확정영업정지 2월갈음 과징금180만원부과공중위생관리법 제11조20060808청소년 이성혼숙영업정지 2월갈음 과징금180만원부과<NA>171.364
4308000020061116157숙박업(일반)여관업나두모텔서울특별시 강북구 도봉로73길 13, (수유동)서울특별시 강북구 수유동 87번지 5호20060316처분확정영업정지2개월 갈음 과징금 246만원 부과공중위생관리법 제11조20060316청소년 이성혼숙영업정지2개월 갈음 과징금 246만원 부과<NA>272.044
5308000020070216148숙박업(일반)여관업번동여인숙서울특별시 강북구 덕릉로 130, (번동)서울특별시 강북구 번동 441번지 9호20070104처분확정영업정지 3월갈음 과징금 270만원 부과공중위생관리법 제11조20070104청소년 이성혼숙(2차)영업정지 3월갈음 과징금 270만원 부과<NA>33.834
6308000020070306246숙박업(일반)여관업선화장서울특별시 강북구 수유로 80, (수유동)서울특별시 강북구 수유동 7번지 13호20061226처분확정영업정지2월 갈음 180만원 부과공중위생관리법 제11조20061226청소년 이성혼숙영업정지2월 갈음 180만원 부과<NA>230.853
8308000020070509013숙박업(일반)여관업덕원장서울특별시 강북구 도봉로 34-8, (미아동)서울특별시 강북구 미아동 35번지 27호20070319처분확정영업정지 2월 갈음 과징금 246만원공중위생관리법 제11조20070319청소년 이성혼숙영업정지 2월 갈음 과징금 246만원<NA>113.063
13308000020070613075숙박업(일반)여관업명진여관서울특별시 강북구 도봉로6길 24, (미아동)서울특별시 강북구 미아동 44번지 5호20070509처분확정영업정지2월갈음 과징금180만원 부과공중위생관리법 제11조제1항20070509청소년이성혼숙영업정지2월갈음 과징금180만원 부과<NA>96.53
03080000200503210166미용업일반미용업박정미헤어연출서울특별시 강북구 노해로11길 6, (수유동)서울특별시 강북구 수유동 30번지 64호20050221처분확정경고 및 과태료부과(30만원)공중위생관리법 제11조 및 동법시행규칙 제19조20050223위생교육미필경고 및 과태료부과(30만원)<NA><NA>2
1308000020061016148숙박업(일반)여관업번동여인숙서울특별시 강북구 덕릉로 130, (번동)서울특별시 강북구 번동 441번지 9호20060808처분확정영업정지 4월갈음 과징금 360만원 부과공중위생관리법 제11조20060808청소년 이성혼숙영업정지 4월갈음 과징금 360만원 부과<NA>33.832
2308000020061027200이용업일반이용업진영서울특별시 강북구 한천로 1064, (수유동)서울특별시 강북구 수유동 178번지 45호20060912처분확정영업정지공중위생관리법제11조제1항20060912윤락행위알선 및 장소제공영업정지<NA>48.02
7308000020070320강북용역24위생관리용역업위생관리용역업(주)가호안전시스템서울특별시 강북구 삼각산로 82, (수유동)서울특별시 강북구 수유동 605번지 261호20061220처분확정경고 및 과태료 20만원공중위생관리법 제17조 및 제22조, 동법시행규칙 제19조20061220위생교육미필(2006년도분)경고 및 과태료 20만원<NA>66.02