Overview

Dataset statistics

Number of variables18
Number of observations8142
Missing cells12944
Missing cells (%)8.8%
Duplicate rows346
Duplicate rows (%)4.2%
Total size in memory1.2 MiB
Average record size in memory151.0 B

Variable types

Categorical4
Numeric6
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡),운영형태
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-10604/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 346 (4.2%) duplicate rowsDuplicates
운영형태 is highly overall correlated with 위반일자 and 2 other fieldsHigh correlation
업종명 is highly overall correlated with 운영형태High correlation
처분일자 is highly overall correlated with 교부번호 and 2 other fieldsHigh correlation
교부번호 is highly overall correlated with 처분일자 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 3 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 운영형태High correlation
업종명 is highly imbalanced (51.8%)Imbalance
운영형태 is highly imbalanced (94.6%)Imbalance
소재지도로명 has 638 (7.8%) missing valuesMissing
처분기간 has 7459 (91.6%) missing valuesMissing
영업장면적(㎡) has 4759 (58.5%) missing valuesMissing
위반일자 is highly skewed (γ1 = -60.14487753)Skewed

Reproduction

Analysis started2024-05-18 05:22:22.420644
Analysis finished2024-05-18 05:22:46.960973
Duration24.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
3190000
8142 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 8142
100.0%

Length

2024-05-18T14:22:47.172130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:22:47.474541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 8142
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2559
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20133109
Minimum19990424
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-05-18T14:22:47.823235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19990424
5-th percentile20021127
Q120080906
median20140409
Q320190403
95-th percentile20230309
Maximum20240516
Range250092
Interquartile range (IQR)109496.75

Descriptive statistics

Standard deviation62813.406
Coefficient of variation (CV)0.0031199059
Kurtosis-1.0573484
Mean20133109
Median Absolute Deviation (MAD)50204.5
Skewness-0.23442081
Sum1.6392377 × 1011
Variance3.9455239 × 109
MonotonicityNot monotonic
2024-05-18T14:22:48.295488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201222 251
 
3.1%
20211201 201
 
2.5%
20230320 117
 
1.4%
20110908 73
 
0.9%
20200129 69
 
0.8%
20110613 53
 
0.7%
20230202 44
 
0.5%
20151027 44
 
0.5%
20150609 37
 
0.5%
20191218 31
 
0.4%
Other values (2549) 7222
88.7%
ValueCountFrequency (%)
19990424 3
< 0.1%
20010206 1
 
< 0.1%
20010213 2
 
< 0.1%
20010227 2
 
< 0.1%
20010228 1
 
< 0.1%
20010403 1
 
< 0.1%
20010430 6
0.1%
20010517 1
 
< 0.1%
20010521 2
 
< 0.1%
20010531 6
0.1%
ValueCountFrequency (%)
20240516 1
 
< 0.1%
20240514 14
0.2%
20240513 6
 
0.1%
20240405 15
0.2%
20240404 9
0.1%
20240402 2
 
< 0.1%
20240319 2
 
< 0.1%
20240314 1
 
< 0.1%
20240313 1
 
< 0.1%
20240312 1
 
< 0.1%

교부번호
Real number (ℝ)

HIGH CORRELATION 

Distinct4453
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0036571 × 1010
Minimum1.9290091 × 1010
Maximum2.0240127 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-05-18T14:22:48.784595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9290091 × 1010
5-th percentile1.9880091 × 1010
Q11.9980091 × 1010
median2.0030092 × 1010
Q32.0110091 × 1010
95-th percentile2.0180092 × 1010
Maximum2.0240127 × 1010
Range9.5003601 × 108
Interquartile range (IQR)1.2999993 × 108

Descriptive statistics

Standard deviation93887276
Coefficient of variation (CV)0.0046857955
Kurtosis0.55464125
Mean2.0036571 × 1010
Median Absolute Deviation (MAD)69999588
Skewness-0.42835168
Sum1.6313777 × 1014
Variance8.8148206 × 1015
MonotonicityNot monotonic
2024-05-18T14:22:49.220210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020091273 40
 
0.5%
20040091018 36
 
0.4%
20150091159 36
 
0.4%
19890091275 27
 
0.3%
20000091618 27
 
0.3%
19920091652 24
 
0.3%
20000091433 22
 
0.3%
20120091180 22
 
0.3%
20020091157 22
 
0.3%
20020091001 20
 
0.2%
Other values (4443) 7866
96.6%
ValueCountFrequency (%)
19290091002 1
 
< 0.1%
19680091001 1
 
< 0.1%
19700091009 4
< 0.1%
19700091011 1
 
< 0.1%
19700091013 1
 
< 0.1%
19710091006 2
 
< 0.1%
19710091008 4
< 0.1%
19720091002 1
 
< 0.1%
19720091007 2
 
< 0.1%
19720091009 8
0.1%
ValueCountFrequency (%)
20240127013 1
< 0.1%
20230120870 1
< 0.1%
20230120811 1
< 0.1%
20230120745 1
< 0.1%
20230120556 1
< 0.1%
20230120548 1
< 0.1%
20230120535 1
< 0.1%
20230120493 1
< 0.1%
20230120474 1
< 0.1%
20230120277 1
< 0.1%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct21
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
일반음식점
5203 
휴게음식점
641 
즉석판매제조가공업
 
496
유흥주점영업
 
383
식품제조가공업
 
346
Other values (16)
1073 

Length

Max length13
Median length5
Mean length5.6053795
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 5203
63.9%
휴게음식점 641
 
7.9%
즉석판매제조가공업 496
 
6.1%
유흥주점영업 383
 
4.7%
식품제조가공업 346
 
4.2%
단란주점 332
 
4.1%
건강기능식품일반판매업 181
 
2.2%
식품등 수입판매업 170
 
2.1%
제과점영업 119
 
1.5%
집단급식소 82
 
1.0%
Other values (11) 189
 
2.3%

Length

2024-05-18T14:22:49.634475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 5203
62.6%
휴게음식점 641
 
7.7%
즉석판매제조가공업 496
 
6.0%
유흥주점영업 383
 
4.6%
식품제조가공업 346
 
4.2%
단란주점 332
 
4.0%
건강기능식품일반판매업 181
 
2.2%
식품등 170
 
2.0%
수입판매업 170
 
2.0%
제과점영업 119
 
1.4%
Other values (12) 271
 
3.3%

업태명
Text

Distinct64
Distinct (%)0.8%
Missing20
Missing (%)0.2%
Memory size63.7 KiB
2024-05-18T14:22:50.054241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length4.268653
Min length2

Characters and Unicode

Total characters34670
Distinct characters142
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

Unique9 ?
Unique (%)0.1%

Sample

1st row정종/대포집/소주방
2nd row중국식
3rd row중국식
4th row중국식
5th row중국식
ValueCountFrequency (%)
한식 2095
24.8%
호프/통닭 534
 
6.3%
분식 505
 
6.0%
즉석판매제조가공업 496
 
5.9%
기타 494
 
5.9%
정종/대포집/소주방 446
 
5.3%
식품제조가공업 346
 
4.1%
룸살롱 341
 
4.0%
단란주점 332
 
3.9%
경양식 313
 
3.7%
Other values (53) 2533
30.0%
2024-05-18T14:22:50.901019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 4316
 
12.4%
한 2095
 
6.0%
업 1467
 
4.2%
/ 1426
 
4.1%
매 1081
 
3.1%
판 1081
 
3.1%
조 976
 
2.8%
제 962
 
2.8%
가 843
 
2.4%
공 842
 
2.4%
Other values (132) 19581
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32373
93.4%
Other Punctuation 1432
 
4.1%
Space Separator 313
 
0.9%
Close Punctuation 276
 
0.8%
Open Punctuation 276
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 4316
 
13.3%
한 2095
 
6.5%
업 1467
 
4.5%
매 1081
 
3.3%
판 1081
 
3.3%
조 976
 
3.0%
제 962
 
3.0%
가 843
 
2.6%
공 842
 
2.6%
통 798
 
2.5%
Other values (126) 17912
55.3%
Other Punctuation
ValueCountFrequency (%)
/ 1426
99.6%
, 5
 
0.3%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 276
100.0%
Open Punctuation
ValueCountFrequency (%)
( 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32373
93.4%
Common 2297
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 4316
 
13.3%
한 2095
 
6.5%
업 1467
 
4.5%
매 1081
 
3.3%
판 1081
 
3.3%
조 976
 
3.0%
제 962
 
3.0%
가 843
 
2.6%
공 842
 
2.6%
통 798
 
2.5%
Other values (126) 17912
55.3%
Common
ValueCountFrequency (%)
/ 1426
62.1%
313
 
13.6%
) 276
 
12.0%
( 276
 
12.0%
, 5
 
0.2%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32373
93.4%
ASCII 2297
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 4316
 
13.3%
한 2095
 
6.5%
업 1467
 
4.5%
매 1081
 
3.3%
판 1081
 
3.3%
조 976
 
3.0%
제 962
 
3.0%
가 843
 
2.6%
공 842
 
2.6%
통 798
 
2.5%
Other values (126) 17912
55.3%
ASCII
ValueCountFrequency (%)
/ 1426
62.1%
313
 
13.6%
) 276
 
12.0%
( 276
 
12.0%
, 5
 
0.2%
. 1
 
< 0.1%

업소명
Text

Distinct4551
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-05-18T14:22:51.488312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length5.6144682
Min length1

Characters and Unicode

Total characters45713
Distinct characters965
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2939 ?
Unique (%)36.1%

Sample

1st row부킹
2nd row덕성원
3rd row안동장
4th row안동장
5th row안동장
ValueCountFrequency (%)
노량진점 44
 
0.5%
김밥천국 39
 
0.4%
탄 38
 
0.4%
주식회사 33
 
0.3%
사당점 31
 
0.3%
상도점 28
 
0.3%
주)커피나무 28
 
0.3%
주)브레인그룹 27
 
0.3%
넝쿨분식 27
 
0.3%
다원갈비 24
 
0.3%
Other values (4954) 9168
96.6%
2024-05-18T14:22:52.400169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1350
 
3.0%
이 1117
 
2.4%
점 816
 
1.8%
) 762
 
1.7%
( 761
 
1.7%
리 670
 
1.5%
주 670
 
1.5%
스 651
 
1.4%
식 600
 
1.3%
대 530
 
1.2%
Other values (955) 37786
82.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39982
87.5%
Space Separator 1350
 
3.0%
Uppercase Letter 1065
 
2.3%
Lowercase Letter 1049
 
2.3%
Close Punctuation 762
 
1.7%
Open Punctuation 761
 
1.7%
Decimal Number 523
 
1.1%
Other Punctuation 201
 
0.4%
Dash Punctuation 13
 
< 0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1117
 
2.8%
점 816
 
2.0%
리 670
 
1.7%
주 670
 
1.7%
스 651
 
1.6%
식 600
 
1.5%
대 530
 
1.3%
수 496
 
1.2%
당 429
 
1.1%
마 422
 
1.1%
Other values (878) 33581
84.0%
Uppercase Letter
ValueCountFrequency (%)
B 110
 
10.3%
C 110
 
10.3%
O 83
 
7.8%
A 79
 
7.4%
S 75
 
7.0%
L 60
 
5.6%
R 55
 
5.2%
P 44
 
4.1%
T 44
 
4.1%
F 41
 
3.8%
Other values (16) 364
34.2%
Lowercase Letter
ValueCountFrequency (%)
e 182
17.3%
a 125
11.9%
o 86
 
8.2%
r 79
 
7.5%
t 66
 
6.3%
n 59
 
5.6%
i 56
 
5.3%
c 46
 
4.4%
f 45
 
4.3%
s 41
 
3.9%
Other values (14) 264
25.2%
Other Punctuation
ValueCountFrequency (%)
& 87
43.3%
. 63
31.3%
, 15
 
7.5%
' 9
 
4.5%
; 6
 
3.0%
# 6
 
3.0%
? 4
 
2.0%
？ 4
 
2.0%
! 3
 
1.5%
: 3
 
1.5%
Decimal Number
ValueCountFrequency (%)
0 150
28.7%
2 116
22.2%
1 70
13.4%
4 46
 
8.8%
5 38
 
7.3%
9 32
 
6.1%
3 30
 
5.7%
8 21
 
4.0%
7 15
 
2.9%
6 5
 
1.0%
Space Separator
ValueCountFrequency (%)
1350
100.0%
Close Punctuation
ValueCountFrequency (%)
) 762
100.0%
Open Punctuation
ValueCountFrequency (%)
( 761
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39923
87.3%
Common 3611
 
7.9%
Latin 2120
 
4.6%
Han 59
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1117
 
2.8%
점 816
 
2.0%
리 670
 
1.7%
주 670
 
1.7%
스 651
 
1.6%
식 600
 
1.5%
대 530
 
1.3%
수 496
 
1.2%
당 429
 
1.1%
마 422
 
1.1%
Other values (854) 33522
84.0%
Latin
ValueCountFrequency (%)
e 182
 
8.6%
a 125
 
5.9%
B 110
 
5.2%
C 110
 
5.2%
o 86
 
4.1%
O 83
 
3.9%
r 79
 
3.7%
A 79
 
3.7%
S 75
 
3.5%
t 66
 
3.1%
Other values (41) 1125
53.1%
Common
ValueCountFrequency (%)
1350
37.4%
) 762
21.1%
( 761
21.1%
0 150
 
4.2%
2 116
 
3.2%
& 87
 
2.4%
1 70
 
1.9%
. 63
 
1.7%
4 46
 
1.3%
5 38
 
1.1%
Other values (16) 168
 
4.7%
Han
ValueCountFrequency (%)
酒 9
15.3%
愛 7
11.9%
波 6
10.2%
丹 6
10.2%
浪 4
 
6.8%
家 4
 
6.8%
日 3
 
5.1%
秀 2
 
3.4%
鷄 2
 
3.4%
林 2
 
3.4%
Other values (14) 14
23.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39923
87.3%
ASCII 5720
 
12.5%
CJK 58
 
0.1%
Number Forms 6
 
< 0.1%
None 4
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1350
23.6%
) 762
 
13.3%
( 761
 
13.3%
e 182
 
3.2%
0 150
 
2.6%
a 125
 
2.2%
2 116
 
2.0%
B 110
 
1.9%
C 110
 
1.9%
& 87
 
1.5%
Other values (64) 1967
34.4%
Hangul
ValueCountFrequency (%)
이 1117
 
2.8%
점 816
 
2.0%
리 670
 
1.7%
주 670
 
1.7%
스 651
 
1.6%
식 600
 
1.5%
대 530
 
1.3%
수 496
 
1.2%
당 429
 
1.1%
마 422
 
1.1%
Other values (854) 33522
84.0%
CJK
ValueCountFrequency (%)
酒 9
15.5%
愛 7
12.1%
波 6
10.3%
丹 6
10.3%
浪 4
 
6.9%
家 4
 
6.9%
日 3
 
5.2%
秀 2
 
3.4%
鷄 2
 
3.4%
林 2
 
3.4%
Other values (13) 13
22.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
None
ValueCountFrequency (%)
？ 4
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
樂 1
100.0%

소재지도로명
Text

MISSING 

Distinct3483
Distinct (%)46.4%
Missing638
Missing (%)7.8%
Memory size63.7 KiB
2024-05-18T14:22:52.928531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length58
Mean length29.266391
Min length22

Characters and Unicode

Total characters219615
Distinct characters309
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1995 ?
Unique (%)26.6%

Sample

1st row서울특별시 동작구 만양로 89-1, (노량진동)
2nd row서울특별시 동작구 서달로14길 30, (흑석동)
3rd row서울특별시 동작구 흑석로 105-1, (흑석동)
4th row서울특별시 동작구 흑석로 105-1, (흑석동)
5th row서울특별시 동작구 흑석로 105-1, (흑석동)
ValueCountFrequency (%)
서울특별시 7504
18.2%
동작구 7504
18.2%
사당동 2020
 
4.9%
상도동 1310
 
3.2%
노량진동 1273
 
3.1%
1층 927
 
2.2%
신대방동 647
 
1.6%
흑석동 567
 
1.4%
상도로 554
 
1.3%
대방동 457
 
1.1%
Other values (1864) 18562
44.9%
2024-05-18T14:22:53.892318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33831
 
15.4%
동 16724
 
7.6%
, 9375
 
4.3%
작 8890
 
4.0%
1 8795
 
4.0%
서 7796
 
3.5%
) 7771
 
3.5%
( 7771
 
3.5%
시 7659
 
3.5%
구 7523
 
3.4%
Other values (299) 103480
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128783
58.6%
Space Separator 33831
 
15.4%
Decimal Number 30852
 
14.0%
Other Punctuation 9391
 
4.3%
Close Punctuation 7771
 
3.5%
Open Punctuation 7771
 
3.5%
Dash Punctuation 991
 
0.5%
Uppercase Letter 194
 
0.1%
Math Symbol 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16724
 
13.0%
작 8890
 
6.9%
서 7796
 
6.1%
시 7659
 
5.9%
구 7523
 
5.8%
울 7512
 
5.8%
별 7504
 
5.8%
특 7504
 
5.8%
로 7159
 
5.6%
길 4322
 
3.4%
Other values (262) 46190
35.9%
Uppercase Letter
ValueCountFrequency (%)
B 107
55.2%
A 21
 
10.8%
T 18
 
9.3%
D 13
 
6.7%
K 11
 
5.7%
P 6
 
3.1%
E 3
 
1.5%
G 3
 
1.5%
C 2
 
1.0%
I 2
 
1.0%
Other values (6) 8
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 8795
28.5%
2 5307
17.2%
3 2791
 
9.0%
4 2458
 
8.0%
6 2283
 
7.4%
0 2261
 
7.3%
5 2026
 
6.6%
7 1929
 
6.3%
8 1591
 
5.2%
9 1411
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 9375
99.8%
. 7
 
0.1%
@ 3
 
< 0.1%
/ 3
 
< 0.1%
: 2
 
< 0.1%
？ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
33831
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7771
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7771
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 991
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128783
58.6%
Common 90638
41.3%
Latin 194
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16724
 
13.0%
작 8890
 
6.9%
서 7796
 
6.1%
시 7659
 
5.9%
구 7523
 
5.8%
울 7512
 
5.8%
별 7504
 
5.8%
특 7504
 
5.8%
로 7159
 
5.6%
길 4322
 
3.4%
Other values (262) 46190
35.9%
Common
ValueCountFrequency (%)
33831
37.3%
, 9375
 
10.3%
1 8795
 
9.7%
) 7771
 
8.6%
( 7771
 
8.6%
2 5307
 
5.9%
3 2791
 
3.1%
4 2458
 
2.7%
6 2283
 
2.5%
0 2261
 
2.5%
Other values (11) 7995
 
8.8%
Latin
ValueCountFrequency (%)
B 107
55.2%
A 21
 
10.8%
T 18
 
9.3%
D 13
 
6.7%
K 11
 
5.7%
P 6
 
3.1%
E 3
 
1.5%
G 3
 
1.5%
C 2
 
1.0%
I 2
 
1.0%
Other values (6) 8
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128782
58.6%
ASCII 90831
41.4%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33831
37.2%
, 9375
 
10.3%
1 8795
 
9.7%
) 7771
 
8.6%
( 7771
 
8.6%
2 5307
 
5.8%
3 2791
 
3.1%
4 2458
 
2.7%
6 2283
 
2.5%
0 2261
 
2.5%
Other values (26) 8188
 
9.0%
Hangul
ValueCountFrequency (%)
동 16724
 
13.0%
작 8890
 
6.9%
서 7796
 
6.1%
시 7659
 
5.9%
구 7523
 
5.8%
울 7512
 
5.8%
별 7504
 
5.8%
특 7504
 
5.8%
로 7159
 
5.6%
길 4322
 
3.4%
Other values (261) 46189
35.9%
None
ValueCountFrequency (%)
？ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

소재지지번
Text

Distinct3380
Distinct (%)41.8%
Missing62
Missing (%)0.8%
Memory size63.7 KiB
2024-05-18T14:22:54.564941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length53
Mean length27.527351
Min length20

Characters and Unicode

Total characters222421
Distinct characters317
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1827 ?
Unique (%)22.6%

Sample

1st row서울특별시 동작구 노량진동 119번지 74호
2nd row서울특별시 동작구 흑석동 50번지 12호
3rd row서울특별시 동작구 흑석동 184번지 18호
4th row서울특별시 동작구 흑석동 184번지 18호
5th row서울특별시 동작구 흑석동 184번지 18호
ValueCountFrequency (%)
서울특별시 8080
18.8%
동작구 8080
18.8%
사당동 2326
 
5.4%
상도동 1630
 
3.8%
노량진동 1565
 
3.6%
신대방동 920
 
2.1%
1호 743
 
1.7%
흑석동 725
 
1.7%
1층 551
 
1.3%
대방동 541
 
1.3%
Other values (1570) 17838
41.5%
2024-05-18T14:22:55.471618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56929
25.6%
동 16407
 
7.4%
1 9501
 
4.3%
지 8610
 
3.9%
시 8180
 
3.7%
작 8138
 
3.7%
구 8099
 
3.6%
서 8098
 
3.6%
울 8087
 
3.6%
번 8084
 
3.6%
Other values (307) 82288
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124185
55.8%
Space Separator 56929
25.6%
Decimal Number 40030
 
18.0%
Close Punctuation 290
 
0.1%
Open Punctuation 290
 
0.1%
Dash Punctuation 266
 
0.1%
Other Punctuation 253
 
0.1%
Uppercase Letter 141
 
0.1%
Math Symbol 27
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16407
13.2%
지 8610
 
6.9%
시 8180
 
6.6%
작 8138
 
6.6%
구 8099
 
6.5%
서 8098
 
6.5%
울 8087
 
6.5%
번 8084
 
6.5%
별 8080
 
6.5%
특 8080
 
6.5%
Other values (261) 34322
27.6%
Uppercase Letter
ValueCountFrequency (%)
B 64
45.4%
A 17
 
12.1%
T 17
 
12.1%
K 11
 
7.8%
D 10
 
7.1%
P 5
 
3.5%
G 3
 
2.1%
V 2
 
1.4%
R 2
 
1.4%
L 2
 
1.4%
Other values (6) 8
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 9501
23.7%
3 5260
13.1%
2 4967
12.4%
0 3745
 
9.4%
4 3593
 
9.0%
5 2933
 
7.3%
6 2773
 
6.9%
7 2561
 
6.4%
8 2402
 
6.0%
9 2295
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
y 2
20.0%
a 2
20.0%
e 1
10.0%
h 1
10.0%
w 1
10.0%
t 1
10.0%
u 1
10.0%
b 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 229
90.5%
. 12
 
4.7%
/ 4
 
1.6%
@ 3
 
1.2%
& 2
 
0.8%
: 2
 
0.8%
？ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
56929
100.0%
Close Punctuation
ValueCountFrequency (%)
) 290
100.0%
Open Punctuation
ValueCountFrequency (%)
( 290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 266
100.0%
Math Symbol
ValueCountFrequency (%)
~ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124185
55.8%
Common 98085
44.1%
Latin 151
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16407
13.2%
지 8610
 
6.9%
시 8180
 
6.6%
작 8138
 
6.6%
구 8099
 
6.5%
서 8098
 
6.5%
울 8087
 
6.5%
번 8084
 
6.5%
별 8080
 
6.5%
특 8080
 
6.5%
Other values (261) 34322
27.6%
Latin
ValueCountFrequency (%)
B 64
42.4%
A 17
 
11.3%
T 17
 
11.3%
K 11
 
7.3%
D 10
 
6.6%
P 5
 
3.3%
G 3
 
2.0%
V 2
 
1.3%
y 2
 
1.3%
R 2
 
1.3%
Other values (14) 18
 
11.9%
Common
ValueCountFrequency (%)
56929
58.0%
1 9501
 
9.7%
3 5260
 
5.4%
2 4967
 
5.1%
0 3745
 
3.8%
4 3593
 
3.7%
5 2933
 
3.0%
6 2773
 
2.8%
7 2561
 
2.6%
8 2402
 
2.4%
Other values (12) 3421
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124184
55.8%
ASCII 98235
44.2%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56929
58.0%
1 9501
 
9.7%
3 5260
 
5.4%
2 4967
 
5.1%
0 3745
 
3.8%
4 3593
 
3.7%
5 2933
 
3.0%
6 2773
 
2.8%
7 2561
 
2.6%
8 2402
 
2.4%
Other values (35) 3571
 
3.6%
Hangul
ValueCountFrequency (%)
동 16407
13.2%
지 8610
 
6.9%
시 8180
 
6.6%
작 8138
 
6.6%
구 8099
 
6.5%
서 8098
 
6.5%
울 8087
 
6.5%
번 8084
 
6.5%
별 8080
 
6.5%
특 8080
 
6.5%
Other values (260) 34321
27.6%
None
ValueCountFrequency (%)
？ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2727
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20132197
Minimum20000919
Maximum20240313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-05-18T14:22:55.745713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000919
5-th percentile20021016
Q120080721
median20140217
Q320190220
95-th percentile20221208
Maximum20240313
Range239394
Interquartile range (IQR)109498.75

Descriptive statistics

Standard deviation62636.208
Coefficient of variation (CV)0.0031112456
Kurtosis-1.0577043
Mean20132197
Median Absolute Deviation (MAD)50305
Skewness-0.2493109
Sum1.6391635 × 1011
Variance3.9232946 × 109
MonotonicityNot monotonic
2024-05-18T14:22:56.049691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211104 110
 
1.4%
20070412 95
 
1.2%
20201112 93
 
1.1%
20221208 90
 
1.1%
20201113 84
 
1.0%
20110805 78
 
1.0%
20201117 70
 
0.9%
20200113 69
 
0.8%
20211110 67
 
0.8%
20230112 59
 
0.7%
Other values (2717) 7327
90.0%
ValueCountFrequency (%)
20000919 1
 
< 0.1%
20000923 1
 
< 0.1%
20001118 1
 
< 0.1%
20010105 1
 
< 0.1%
20010109 1
 
< 0.1%
20010112 2
 
< 0.1%
20010202 1
 
< 0.1%
20010216 5
0.1%
20010219 1
 
< 0.1%
20010314 1
 
< 0.1%
ValueCountFrequency (%)
20240313 2
 
< 0.1%
20240312 4
 
< 0.1%
20240307 1
 
< 0.1%
20240305 12
0.1%
20240304 3
 
< 0.1%
20240228 3
 
< 0.1%
20240227 2
 
< 0.1%
20240226 1
 
< 0.1%
20240223 1
 
< 0.1%
20240222 1
 
< 0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
처분확정
8142 

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 8142
100.0%

Length

2024-05-18T14:22:56.425266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:22:56.722257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 8142
100.0%

처분명
Text

Distinct642
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-05-18T14:22:57.124042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length55
Mean length7.0927291
Min length2

Characters and Unicode

Total characters57749
Distinct characters236
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)4.3%

Sample

1st row과태료부과 20만원
2nd row시정명령
3rd row과태료부과 50만원
4th row과태료부과
5th row과태료부과 25만원(즉시시정 1/2) 자진납부 20만원
ValueCountFrequency (%)
과태료부과 1705
15.7%
영업소폐쇄 1127
 
10.4%
시정명령 1109
 
10.2%
영업정지 915
 
8.4%
직권말소 744
 
6.9%
시설개수명령 656
 
6.1%
과태료 331
 
3.1%
부과 292
 
2.7%
과징금부과 228
 
2.1%
10만원 203
 
1.9%
Other values (718) 3523
32.5%
2024-05-18T14:22:58.184413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 5887
 
10.2%
부 2927
 
5.1%
2819
 
4.9%
영 2672
 
4.6%
료 2654
 
4.6%
업 2646
 
4.6%
태 2646
 
4.6%
정 2591
 
4.5%
시 2098
 
3.6%
소 1986
 
3.4%
Other values (226) 28823
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47156
81.7%
Decimal Number 5579
 
9.7%
Space Separator 2819
 
4.9%
Open Punctuation 793
 
1.4%
Close Punctuation 793
 
1.4%
Other Punctuation 559
 
1.0%
Math Symbol 29
 
0.1%
Dash Punctuation 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 5887
 
12.5%
부 2927
 
6.2%
영 2672
 
5.7%
료 2654
 
5.6%
업 2646
 
5.6%
태 2646
 
5.6%
정 2591
 
5.5%
시 2098
 
4.4%
소 1986
 
4.2%
명 1922
 
4.1%
Other values (202) 19127
40.6%
Decimal Number
ValueCountFrequency (%)
0 1702
30.5%
1 1176
21.1%
2 961
17.2%
5 390
 
7.0%
3 351
 
6.3%
6 334
 
6.0%
4 316
 
5.7%
7 144
 
2.6%
8 141
 
2.5%
9 64
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 305
54.6%
, 133
23.8%
/ 47
 
8.4%
% 39
 
7.0%
* 16
 
2.9%
: 9
 
1.6%
? 6
 
1.1%
※ 2
 
0.4%
' 2
 
0.4%
Space Separator
ValueCountFrequency (%)
2819
100.0%
Open Punctuation
ValueCountFrequency (%)
( 793
100.0%
Close Punctuation
ValueCountFrequency (%)
) 793
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47156
81.7%
Common 10593
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 5887
 
12.5%
부 2927
 
6.2%
영 2672
 
5.7%
료 2654
 
5.6%
업 2646
 
5.6%
태 2646
 
5.6%
정 2591
 
5.5%
시 2098
 
4.4%
소 1986
 
4.2%
명 1922
 
4.1%
Other values (202) 19127
40.6%
Common
ValueCountFrequency (%)
2819
26.6%
0 1702
16.1%
1 1176
11.1%
2 961
 
9.1%
( 793
 
7.5%
) 793
 
7.5%
5 390
 
3.7%
3 351
 
3.3%
6 334
 
3.2%
4 316
 
3.0%
Other values (14) 958
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47110
81.6%
ASCII 10591
 
18.3%
Compat Jamo 46
 
0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 5887
 
12.5%
부 2927
 
6.2%
영 2672
 
5.7%
료 2654
 
5.6%
업 2646
 
5.6%
태 2646
 
5.6%
정 2591
 
5.5%
시 2098
 
4.5%
소 1986
 
4.2%
명 1922
 
4.1%
Other values (201) 19081
40.5%
ASCII
ValueCountFrequency (%)
2819
26.6%
0 1702
16.1%
1 1176
11.1%
2 961
 
9.1%
( 793
 
7.5%
) 793
 
7.5%
5 390
 
3.7%
3 351
 
3.3%
6 334
 
3.2%
4 316
 
3.0%
Other values (13) 956
 
9.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 46
100.0%
Punctuation
ValueCountFrequency (%)
※ 2
100.0%

법적근거
Text

Distinct802
Distinct (%)9.9%
Missing1
Missing (%)< 0.1%
Memory size63.7 KiB
2024-05-18T14:22:58.729383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length14.820292
Min length3

Characters and Unicode

Total characters120652
Distinct characters136
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique395 ?
Unique (%)4.9%

Sample

1st row식품위생법 제40조 및 제101조
2nd row식품위생법 제31조
3rd row식품위생법 제26조제1항 및 제3항
4th row법 제101조제2항제1호 및 영 제67조
5th row법 제101조제2항제1호 및 영 제67조
ValueCountFrequency (%)
법 5595
20.6%
식품위생법 3651
13.5%
및 2482
 
9.2%
제75조 2081
 
7.7%
제71조 1392
 
5.1%
제37조 1052
 
3.9%
제74조 711
 
2.6%
7항 710
 
2.6%
제101조제2항제1호 510
 
1.9%
제101조제4항1호 412
 
1.5%
Other values (456) 8513
31.4%
2024-05-18T14:22:59.728515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19314
16.0%
제 15230
12.6%
조 12228
10.1%
법 11099
 
9.2%
1 7679
 
6.4%
7 7302
 
6.1%
위 4631
 
3.8%
품 4544
 
3.8%
식 4536
 
3.8%
생 4444
 
3.7%
Other values (126) 29645
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69066
57.2%
Decimal Number 30565
25.3%
Space Separator 19314
 
16.0%
Other Punctuation 1636
 
1.4%
Close Punctuation 36
 
< 0.1%
Open Punctuation 35
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 15230
22.1%
조 12228
17.7%
법 11099
16.1%
위 4631
 
6.7%
품 4544
 
6.6%
식 4536
 
6.6%
생 4444
 
6.4%
항 3169
 
4.6%
및 2583
 
3.7%
호 1402
 
2.0%
Other values (107) 5200
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 7679
25.1%
7 7302
23.9%
5 2911
 
9.5%
2 2835
 
9.3%
3 2767
 
9.1%
4 2550
 
8.3%
0 1939
 
6.3%
6 1166
 
3.8%
8 948
 
3.1%
9 468
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 1624
99.3%
. 9
 
0.6%
: 2
 
0.1%
? 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 26
72.2%
] 10
 
27.8%
Open Punctuation
ValueCountFrequency (%)
( 25
71.4%
[ 10
 
28.6%
Space Separator
ValueCountFrequency (%)
19314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69066
57.2%
Common 51586
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 15230
22.1%
조 12228
17.7%
법 11099
16.1%
위 4631
 
6.7%
품 4544
 
6.6%
식 4536
 
6.6%
생 4444
 
6.4%
항 3169
 
4.6%
및 2583
 
3.7%
호 1402
 
2.0%
Other values (107) 5200
 
7.5%
Common
ValueCountFrequency (%)
19314
37.4%
1 7679
 
14.9%
7 7302
 
14.2%
5 2911
 
5.6%
2 2835
 
5.5%
3 2767
 
5.4%
4 2550
 
4.9%
0 1939
 
3.8%
, 1624
 
3.1%
6 1166
 
2.3%
Other values (9) 1499
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69066
57.2%
ASCII 51586
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19314
37.4%
1 7679
 
14.9%
7 7302
 
14.2%
5 2911
 
5.6%
2 2835
 
5.5%
3 2767
 
5.4%
4 2550
 
4.9%
0 1939
 
3.8%
, 1624
 
3.1%
6 1166
 
2.3%
Other values (9) 1499
 
2.9%
Hangul
ValueCountFrequency (%)
제 15230
22.1%
조 12228
17.7%
법 11099
16.1%
위 4631
 
6.7%
품 4544
 
6.6%
식 4536
 
6.6%
생 4444
 
6.4%
항 3169
 
4.6%
및 2583
 
3.7%
호 1402
 
2.0%
Other values (107) 5200
 
7.5%

위반일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2814
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20127210
Minimum200109
Maximum20240401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-05-18T14:23:00.158526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200109
5-th percentile20021115
Q120080726
median20140217
Q320190222
95-th percentile20221208
Maximum20240401
Range20040292
Interquartile range (IQR)109496

Descriptive statistics

Standard deviation318564.73
Coefficient of variation (CV)0.015827565
Kurtosis3761.0749
Mean20127210
Median Absolute Deviation (MAD)50304
Skewness-60.144878
Sum1.6387574 × 1011
Variance1.0148349 × 1011
MonotonicityNot monotonic
2024-05-18T14:23:00.628626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210401 195
 
2.4%
20221208 93
 
1.1%
20201112 91
 
1.1%
20201118 85
 
1.0%
20110805 74
 
0.9%
20201117 71
 
0.9%
20200113 70
 
0.9%
20230112 59
 
0.7%
20191231 55
 
0.7%
20151001 50
 
0.6%
Other values (2804) 7299
89.6%
ValueCountFrequency (%)
200109 2
 
< 0.1%
19990408 3
< 0.1%
20000919 1
 
< 0.1%
20000923 1
 
< 0.1%
20001118 1
 
< 0.1%
20010105 1
 
< 0.1%
20010216 5
0.1%
20010219 1
 
< 0.1%
20010412 1
 
< 0.1%
20010418 6
0.1%
ValueCountFrequency (%)
20240401 1
 
< 0.1%
20240313 2
 
< 0.1%
20240312 4
 
< 0.1%
20240307 1
 
< 0.1%
20240306 2
 
< 0.1%
20240305 11
0.1%
20240304 2
 
< 0.1%
20240228 3
 
< 0.1%
20240227 2
 
< 0.1%
20240226 5
0.1%

위반내용
Text

Distinct3860
Distinct (%)47.4%
Missing5
Missing (%)0.1%
Memory size63.7 KiB
2024-05-18T14:23:01.420743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length178
Median length120
Mean length30.37311
Min length1

Characters and Unicode

Total characters247146
Distinct characters664
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2763 ?
Unique (%)34.0%

Sample

1st row영업주 건강진단미필
2nd row환풍기 및 주변(닥트),냉장고청소상태불량2009.3.4
3rd row건강진단미필(2/6)(2008.2.27, 21:27)
4th row조리실 위생상태 불량 - 적발일시 : 2019. 3. 4. 21:00경 - 적발기관 : 보건위생과(식품안전팀)
5th row식품 등의 취급기준 위반(조리실 내부 등 불청결)
ValueCountFrequency (%)
7231
 
15.0%
적발기관 1907
 
4.0%
적발일시 1393
 
2.9%
폐업 751
 
1.6%
및 670
 
1.4%
건강진단 664
 
1.4%
미필 615
 
1.3%
위생교육 541
 
1.1%
사업자등록 456
 
0.9%
영업시설물 416
 
0.9%
Other values (5823) 33626
69.7%
2024-05-18T14:23:02.402199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41741
 
16.9%
1 8984
 
3.6%
0 8775
 
3.6%
2 8488
 
3.4%
. 7638
 
3.1%
: 7470
 
3.0%
업 5748
 
2.3%
- 5163
 
2.1%
적 4609
 
1.9%
) 4508
 
1.8%
Other values (654) 144022
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138225
55.9%
Space Separator 41742
 
16.9%
Decimal Number 36066
 
14.6%
Other Punctuation 16447
 
6.7%
Dash Punctuation 5163
 
2.1%
Close Punctuation 4522
 
1.8%
Open Punctuation 4518
 
1.8%
Lowercase Letter 307
 
0.1%
Uppercase Letter 104
 
< 0.1%
Math Symbol 26
 
< 0.1%
Other values (2) 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 5748
 
4.2%
적 4609
 
3.3%
기 4483
 
3.2%
시 4263
 
3.1%
발 4228
 
3.1%
미 4056
 
2.9%
위 3480
 
2.5%
자 3234
 
2.3%
관 2825
 
2.0%
영 2766
 
2.0%
Other values (579) 98533
71.3%
Lowercase Letter
ValueCountFrequency (%)
g 79
25.7%
w 28
 
9.1%
m 27
 
8.8%
o 27
 
8.8%
c 20
 
6.5%
e 19
 
6.2%
a 19
 
6.2%
t 12
 
3.9%
l 12
 
3.9%
r 10
 
3.3%
Other values (10) 54
17.6%
Uppercase Letter
ValueCountFrequency (%)
S 12
11.5%
T 10
9.6%
O 10
9.6%
E 9
 
8.7%
M 8
 
7.7%
A 8
 
7.7%
R 8
 
7.7%
X 5
 
4.8%
L 5
 
4.8%
V 5
 
4.8%
Other values (7) 24
23.1%
Decimal Number
ValueCountFrequency (%)
1 8984
24.9%
0 8775
24.3%
2 8488
23.5%
3 1975
 
5.5%
5 1684
 
4.7%
4 1467
 
4.1%
8 1294
 
3.6%
6 1229
 
3.4%
9 1184
 
3.3%
7 986
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 7638
46.4%
: 7470
45.4%
/ 629
 
3.8%
, 568
 
3.5%
? 43
 
0.3%
* 41
 
0.2%
' 24
 
0.1%
; 17
 
0.1%
% 15
 
0.1%
？ 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 21
80.8%
+ 2
 
7.7%
⇒ 2
 
7.7%
× 1
 
3.8%
Other Symbol
ValueCountFrequency (%)
㈜ 12
48.0%
○ 11
44.0%
㎡ 1
 
4.0%
㎜ 1
 
4.0%
Close Punctuation
ValueCountFrequency (%)
) 4508
99.7%
] 10
 
0.2%
」 4
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 4506
99.7%
[ 8
 
0.2%
「 4
 
0.1%
Space Separator
ValueCountFrequency (%)
41741
> 99.9%
　 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 5163
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138234
55.9%
Common 108498
43.9%
Latin 411
 
0.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 5748
 
4.2%
적 4609
 
3.3%
기 4483
 
3.2%
시 4263
 
3.1%
발 4228
 
3.1%
미 4056
 
2.9%
위 3480
 
2.5%
자 3234
 
2.3%
관 2825
 
2.0%
영 2766
 
2.0%
Other values (577) 98542
71.3%
Common
ValueCountFrequency (%)
41741
38.5%
1 8984
 
8.3%
0 8775
 
8.1%
2 8488
 
7.8%
. 7638
 
7.0%
: 7470
 
6.9%
- 5163
 
4.8%
) 4508
 
4.2%
( 4506
 
4.2%
3 1975
 
1.8%
Other values (27) 9250
 
8.5%
Latin
ValueCountFrequency (%)
g 79
19.2%
w 28
 
6.8%
m 27
 
6.6%
o 27
 
6.6%
c 20
 
4.9%
e 19
 
4.6%
a 19
 
4.6%
t 12
 
2.9%
S 12
 
2.9%
l 12
 
2.9%
Other values (27) 156
38.0%
Han
ValueCountFrequency (%)
岵 1
33.3%
湧 1
33.3%
躍 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138213
55.9%
ASCII 108882
44.1%
None 24
 
< 0.1%
Geometric Shapes 11
 
< 0.1%
Compat Jamo 9
 
< 0.1%
CJK 3
 
< 0.1%
Arrows 2
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41741
38.3%
1 8984
 
8.3%
0 8775
 
8.1%
2 8488
 
7.8%
. 7638
 
7.0%
: 7470
 
6.9%
- 5163
 
4.7%
) 4508
 
4.1%
( 4506
 
4.1%
3 1975
 
1.8%
Other values (55) 9634
 
8.8%
Hangul
ValueCountFrequency (%)
업 5748
 
4.2%
적 4609
 
3.3%
기 4483
 
3.2%
시 4263
 
3.1%
발 4228
 
3.1%
미 4056
 
2.9%
위 3480
 
2.5%
자 3234
 
2.3%
관 2825
 
2.0%
영 2766
 
2.0%
Other values (571) 98521
71.3%
None
ValueCountFrequency (%)
㈜ 12
50.0%
「 4
 
16.7%
」 4
 
16.7%
？ 2
 
8.3%
　 1
 
4.2%
× 1
 
4.2%
Geometric Shapes
ValueCountFrequency (%)
○ 11
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅊ 3
33.3%
ㅁ 2
22.2%
ㅐ 2
22.2%
ㅋ 1
 
11.1%
ㅌ 1
 
11.1%
Arrows
ValueCountFrequency (%)
⇒ 2
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
50.0%
㎜ 1
50.0%
CJK
ValueCountFrequency (%)
岵 1
33.3%
湧 1
33.3%
躍 1
33.3%

처분내용
Text

Distinct642
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-05-18T14:23:02.898234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length55
Mean length7.0927291
Min length2

Characters and Unicode

Total characters57749
Distinct characters236
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)4.3%

Sample

1st row과태료부과 20만원
2nd row시정명령
3rd row과태료부과 50만원
4th row과태료부과
5th row과태료부과 25만원(즉시시정 1/2) 자진납부 20만원
ValueCountFrequency (%)
과태료부과 1705
15.7%
영업소폐쇄 1127
 
10.4%
시정명령 1109
 
10.2%
영업정지 915
 
8.4%
직권말소 744
 
6.9%
시설개수명령 656
 
6.1%
과태료 331
 
3.1%
부과 292
 
2.7%
과징금부과 228
 
2.1%
10만원 203
 
1.9%
Other values (718) 3523
32.5%
2024-05-18T14:23:03.731341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 5887
 
10.2%
부 2927
 
5.1%
2819
 
4.9%
영 2672
 
4.6%
료 2654
 
4.6%
업 2646
 
4.6%
태 2646
 
4.6%
정 2591
 
4.5%
시 2098
 
3.6%
소 1986
 
3.4%
Other values (226) 28823
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47156
81.7%
Decimal Number 5579
 
9.7%
Space Separator 2819
 
4.9%
Open Punctuation 793
 
1.4%
Close Punctuation 793
 
1.4%
Other Punctuation 559
 
1.0%
Math Symbol 29
 
0.1%
Dash Punctuation 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 5887
 
12.5%
부 2927
 
6.2%
영 2672
 
5.7%
료 2654
 
5.6%
업 2646
 
5.6%
태 2646
 
5.6%
정 2591
 
5.5%
시 2098
 
4.4%
소 1986
 
4.2%
명 1922
 
4.1%
Other values (202) 19127
40.6%
Decimal Number
ValueCountFrequency (%)
0 1702
30.5%
1 1176
21.1%
2 961
17.2%
5 390
 
7.0%
3 351
 
6.3%
6 334
 
6.0%
4 316
 
5.7%
7 144
 
2.6%
8 141
 
2.5%
9 64
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 305
54.6%
, 133
23.8%
/ 47
 
8.4%
% 39
 
7.0%
* 16
 
2.9%
: 9
 
1.6%
? 6
 
1.1%
※ 2
 
0.4%
' 2
 
0.4%
Space Separator
ValueCountFrequency (%)
2819
100.0%
Open Punctuation
ValueCountFrequency (%)
( 793
100.0%
Close Punctuation
ValueCountFrequency (%)
) 793
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47156
81.7%
Common 10593
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 5887
 
12.5%
부 2927
 
6.2%
영 2672
 
5.7%
료 2654
 
5.6%
업 2646
 
5.6%
태 2646
 
5.6%
정 2591
 
5.5%
시 2098
 
4.4%
소 1986
 
4.2%
명 1922
 
4.1%
Other values (202) 19127
40.6%
Common
ValueCountFrequency (%)
2819
26.6%
0 1702
16.1%
1 1176
11.1%
2 961
 
9.1%
( 793
 
7.5%
) 793
 
7.5%
5 390
 
3.7%
3 351
 
3.3%
6 334
 
3.2%
4 316
 
3.0%
Other values (14) 958
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47110
81.6%
ASCII 10591
 
18.3%
Compat Jamo 46
 
0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 5887
 
12.5%
부 2927
 
6.2%
영 2672
 
5.7%
료 2654
 
5.6%
업 2646
 
5.6%
태 2646
 
5.6%
정 2591
 
5.5%
시 2098
 
4.5%
소 1986
 
4.2%
명 1922
 
4.1%
Other values (201) 19081
40.5%
ASCII
ValueCountFrequency (%)
2819
26.6%
0 1702
16.1%
1 1176
11.1%
2 961
 
9.1%
( 793
 
7.5%
) 793
 
7.5%
5 390
 
3.7%
3 351
 
3.3%
6 334
 
3.2%
4 316
 
3.0%
Other values (13) 956
 
9.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 46
100.0%
Punctuation
ValueCountFrequency (%)
※ 2
100.0%

처분기간
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)3.1%
Missing7459
Missing (%)91.6%
Infinite0
Infinite (%)0.0%
Mean12.322108
Minimum0
Maximum181
Zeros22
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-05-18T14:23:03.988263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q17
median15
Q315
95-th percentile20
Maximum181
Range181
Interquartile range (IQR)8

Descriptive statistics

Standard deviation10.598728
Coefficient of variation (CV)0.8601392
Kurtosis187.00129
Mean12.322108
Median Absolute Deviation (MAD)3
Skewness11.834078
Sum8416
Variance112.33304
MonotonicityNot monotonic
2024-05-18T14:23:04.206705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
15 325
 
4.0%
7 180
 
2.2%
10 42
 
0.5%
5 34
 
0.4%
0 22
 
0.3%
20 16
 
0.2%
17 13
 
0.2%
25 12
 
0.1%
6 6
 
0.1%
30 5
 
0.1%
Other values (11) 28
 
0.3%
(Missing) 7459
91.6%
ValueCountFrequency (%)
0 22
 
0.3%
1 4
 
< 0.1%
2 3
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 34
 
0.4%
6 6
 
0.1%
7 180
2.2%
8 3
 
< 0.1%
10 42
 
0.5%
ValueCountFrequency (%)
181 2
 
< 0.1%
30 5
 
0.1%
29 1
 
< 0.1%
25 12
 
0.1%
22 5
 
0.1%
20 16
 
0.2%
18 4
 
< 0.1%
17 13
 
0.2%
15 325
4.0%
14 2
 
< 0.1%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1505
Distinct (%)44.5%
Missing4759
Missing (%)58.5%
Infinite0
Infinite (%)0.0%
Mean79.542554
Minimum0
Maximum1497.23
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-05-18T14:23:04.561641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.11
Q129
median60
Q396.5
95-th percentile197.775
Maximum1497.23
Range1497.23
Interquartile range (IQR)67.5

Descriptive statistics

Standard deviation98.527668
Coefficient of variation (CV)1.2386787
Kurtosis76.463937
Mean79.542554
Median Absolute Deviation (MAD)33
Skewness6.9814886
Sum269092.46
Variance9707.7014
MonotonicityNot monotonic
2024-05-18T14:23:04.827412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 24
 
0.3%
10.0 19
 
0.2%
9.0 18
 
0.2%
138.36 18
 
0.2%
16.5 17
 
0.2%
55.03 15
 
0.2%
77.43 14
 
0.2%
66.0 14
 
0.2%
5.96 14
 
0.2%
49.5 14
 
0.2%
Other values (1495) 3216
39.5%
(Missing) 4759
58.5%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
2.77 1
 
< 0.1%
3.0 2
 
< 0.1%
3.21 2
 
< 0.1%
3.3 5
0.1%
3.75 1
 
< 0.1%
4.03 1
 
< 0.1%
4.95 4
< 0.1%
5.0 6
0.1%
5.13 1
 
< 0.1%
ValueCountFrequency (%)
1497.23 2
< 0.1%
1452.36 3
< 0.1%
1070.32 2
< 0.1%
1049.34 1
 
< 0.1%
956.11 1
 
< 0.1%
944.72 2
< 0.1%
834.9 1
 
< 0.1%
747.92 2
< 0.1%
628.32 2
< 0.1%
627.0 1
 
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
8061 
직영
 
73
(조합)위탁
 
8

Length

Max length6
Median length4
Mean length3.9840334
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8061
99.0%
직영 73
 
0.9%
(조합)위탁 8
 
0.1%

Length

2024-05-18T14:23:05.251786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:23:05.596953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8061
99.0%
직영 73
 
0.9%
조합)위탁 8
 
0.1%

Interactions

2024-05-18T14:22:42.771783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:30.984757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:32.997288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:35.407803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:37.545057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:40.455216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:43.102415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:31.310056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:33.378849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:35.793905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:37.968159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:40.975285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:43.383407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:31.665815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:33.711869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:36.153915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:38.419105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:41.363815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:43.659510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:31.997923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:34.183060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:36.475830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:38.843014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:41.907455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:43.953157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:32.305284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:34.547403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:36.879264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:39.281489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:42.218943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:44.307553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:32.593884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:35.002606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:37.230831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:39.977888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:22:42.514934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:23:05.816082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.0000.5360.4130.5360.986NaN0.2630.1020.000
교부번호0.5361.0000.4320.5870.538NaN0.0000.2310.000
업종명0.4130.4321.0001.0000.432NaN0.2460.429NaN
업태명0.5360.5871.0001.0000.543NaN0.2210.6430.572
지도점검일자0.9860.5380.4320.5431.000NaN0.2020.0870.000
위반일자NaNNaNNaNNaNNaN1.000NaNNaNNaN
처분기간0.2630.0000.2460.2210.202NaN1.0000.000NaN
영업장면적(㎡)0.1020.2310.4290.6430.087NaN0.0001.000NaN
운영형태0.0000.000NaN0.5720.000NaNNaNNaN1.000
2024-05-18T14:23:06.127883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영형태업종명
운영형태1.0001.000
업종명1.0001.000
2024-05-18T14:23:06.328151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.5601.0000.999-0.110-0.1480.1650.000
교부번호0.5601.0000.5610.560-0.078-0.0520.1900.000
지도점검일자1.0000.5611.0000.999-0.109-0.1510.1740.000
위반일자0.9990.5600.9991.000-0.110-0.1500.0501.000
처분기간-0.110-0.078-0.109-0.1101.0000.0530.1390.000
영업장면적(㎡)-0.148-0.052-0.151-0.1500.0531.0000.1991.000
업종명0.1650.1900.1740.0500.1390.1991.0001.000
운영형태0.0000.0000.0001.0000.0001.0001.0001.000

Missing values

2024-05-18T14:22:45.463461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:22:46.181040image/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.
2024-05-18T14:22:46.719556image/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(㎡)운영형태
031900002010032319290091002일반음식점정종/대포집/소주방부킹서울특별시 동작구 만양로 89-1, (노량진동)서울특별시 동작구 노량진동 119번지 74호20100218처분확정과태료부과 20만원식품위생법 제40조 및 제101조20100218영업주 건강진단미필과태료부과 20만원<NA><NA><NA>
131900002009030519680091001일반음식점중국식덕성원서울특별시 동작구 서달로14길 30, (흑석동)서울특별시 동작구 흑석동 50번지 12호20090304처분확정시정명령식품위생법 제31조20090304환풍기 및 주변(닥트),냉장고청소상태불량2009.3.4시정명령<NA><NA><NA>
231900002008031319720091009일반음식점중국식안동장서울특별시 동작구 흑석로 105-1, (흑석동)서울특별시 동작구 흑석동 184번지 18호20080227처분확정과태료부과 50만원식품위생법 제26조제1항 및 제3항20080227건강진단미필(2/6)(2008.2.27, 21:27)과태료부과 50만원<NA>321.03<NA>
331900002019043019720091009일반음식점중국식안동장서울특별시 동작구 흑석로 105-1, (흑석동)서울특별시 동작구 흑석동 184번지 18호20190304처분확정과태료부과법 제101조제2항제1호 및 영 제67조20190304조리실 위생상태 불량 - 적발일시 : 2019. 3. 4. 21:00경 - 적발기관 : 보건위생과(식품안전팀)과태료부과<NA>321.03<NA>
431900002020102919720091009일반음식점중국식안동장서울특별시 동작구 흑석로 105-1, (흑석동)서울특별시 동작구 흑석동 184번지 18호20201006처분확정과태료부과 25만원(즉시시정 1/2) 자진납부 20만원법 제101조제2항제1호 및 영 제67조20201006식품 등의 취급기준 위반(조리실 내부 등 불청결)과태료부과 25만원(즉시시정 1/2) 자진납부 20만원<NA>321.03<NA>
531900002001122619750091013일반음식점일식엔젤서울특별시 동작구 동작대로27길 20-7, (사당동)서울특별시 동작구 사당동 130번지 16호20011226처분확정영업정지식품위생법제58조20011226윤락및유흥접객영업'1차'영업정지<NA>71.41<NA>
631900002001122619750091013일반음식점일식엔젤서울특별시 동작구 동작대로27길 20-7, (사당동)서울특별시 동작구 사당동 130번지 16호20011226처분확정영업정지식품위생법제58조20011226윤락및유흥접객영업'1차'영업정지<NA>49.97<NA>
731900002019031319750091034일반음식점정종/대포집/소주방야채순대곱창서울특별시 동작구 동작대로27길 16-7, (사당동)서울특별시 동작구 사당동 130번지 13호20190209처분확정영업정지법 제75조20190209청소년 주류제공(1차) - 적발일시 : 2019. 2. 9. 18:40경 - 적발기관 : 서울동작경찰서영업정지<NA>23.19<NA>
831900002013080219750091009일반음식점중국식향림원서울특별시 동작구 동작대로7길 94, (사당동)서울특별시 동작구 사당동 1046번지 36호20130801처분확정시정명령식품위생법 제7조 및 제71조20130801조리식품에 이물(바퀴벌레) 혼입 - 제 품 명 : 간짜장 - 확인일시 : 2013.8.1 - 확인기관 : 자체(식품위생팀)시정명령<NA>39.54<NA>
931900002004032619760091024일반음식점정종/대포집/소주방7광구<NA>서울특별시 동작구 노량진동 202번지 2호20040312처분확정영업소폐쇄식품위생법 제58조20040312지방세3회이상체납 및 시설물무단멸실영업소폐쇄<NA>18.51<NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
813231900002021120320190091546건강기능식품일반판매업영업장판매상도풀무질센터서울특별시 동작구 상도로30길 40, 상도커뮤니티 복합문화센터동 206호 (상도동, 상도2차두산위브트레지움아파트)서울특별시 동작구 상도동 535번지 상도2차두산위브트레지움아파트20211105처분확정과태료부과법 제47조제1항제6호202101012020년도 건강기능식품판매업 영업자 안전위생교육 미이수과태료부과<NA><NA><NA>
813331900002021121620190091556건강기능식품일반판매업영업장판매애터미노량진중심센터서울특별시 동작구 노량진로 228, 녹천약국 지하1층 (본동)서울특별시 동작구 본동 400번지 녹천약국20211105처분확정과태료부과법 제47조제1항제6호202101012020년도 건강기능식품판매업 영업자 안전위생교육 미이수과태료부과<NA><NA><NA>
813431900002021121520190091559건강기능식품일반판매업영업장판매보떼화장품 신대방삼거리점서울특별시 동작구 국사봉1길 4, 1층 (상도동)서울특별시 동작구 상도동 328번지 10호20211105처분확정과태료부과법 제47조제1항제6호202101012020년도 건강기능식품판매업 영업자 안전위생교육 미이수과태료부과<NA><NA><NA>
813531900002021120120190091648건강기능식품일반판매업전자상거래(통신판매업)타미리스서울특별시 동작구 현충로18길 24, 201호 (흑석동, 협동주택)서울특별시 동작구 흑석동 270번지 4호 협동주택20211105처분확정과태료부과법 제47조제1항제6호202101012020년도 건강기능식품판매업 영업자 안전위생교육 미이수과태료부과<NA><NA><NA>
813631900002021120320190091690건강기능식품일반판매업전자상거래(통신판매업)컴 얼라이브(come alive)서울특별시 동작구 사당로14길 81, 301호 (사당동)서울특별시 동작구 사당동 293번지 11호20211105처분확정과태료부과법 제47조제1항제6호202101012020년도 건강기능식품판매업 영업자 안전위생교육 미이수과태료부과<NA><NA><NA>
813731900002023122920190091929건강기능식품일반판매업전자상거래(통신판매업)심플리시티서울특별시 동작구 동작대로29길 119, 111동 414호 (사당동, 극동아파트)서울특별시 동작구 사당동 105번지 극동아파트20231205처분확정직권말소법 제6조 6항20231205사업자등록 폐업 후 구청 폐업 미신고직권말소<NA><NA><NA>
813831900002015070120080091295건강기능식품유통전문판매업건강기능식품유통전문판매업(주)대장송에너지 유에스에이서울특별시 동작구 대림로 23-1, (신대방동,(지상 2층))서울특별시 동작구 신대방동 693번지 3호 (지상 2층)20150504처분확정영업소폐쇄건강기능식품에 관한 법률 제32조20150504정당한 사유없이 계속하여 6월이상 휴업함영업소폐쇄<NA><NA><NA>
813931900002020060520100084134건강기능식품유통전문판매업건강기능식품유통전문판매업(주)마더스팜서울특별시 동작구 보라매로5길 51, 6층 607호 (신대방동, 롯데타워)서울특별시 동작구 신대방동 395번지 67호 롯데타워20200525처분확정과태료부과16만원법 제47조제1항제6호202005252019년 안전보수교육 미수료과태료부과16만원<NA>257.33<NA>
814031900002020060520100084134건강기능식품유통전문판매업건강기능식품유통전문판매업(주)마더스팜서울특별시 동작구 보라매로5길 51, 6층 607호 (신대방동, 롯데타워)서울특별시 동작구 신대방동 395번지 67호 롯데타워20200525처분확정과태료부과16만원법 제47조제1항제6호202005252019년 안전보수교육 미수료과태료부과16만원<NA>834.9<NA>
814131900002021120120180091033건강기능식품유통전문판매업건강기능식품유통전문판매업주식회사 더큰서울특별시 동작구 사당로26길 38, 대림빌딩 1층 (사당동)서울특별시 동작구 사당동 1015번지 48호 대림빌딩20211105처분확정과태료부과법 제47조제1항제6호202101012020년도 건강기능식품판매업 영업자 안전위생교육 미이수과태료부과<NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
27831900002019081420140091308일반음식점기타미친노가리 노량진점서울특별시 동작구 장승배기로 123-1, 1층 (노량진동)<NA>20190723처분확정과태료 8만원법 제101조제2항 제1호20190723영업주 건강진단 미필과태료 8만원<NA><NA><NA>5
6731900002005090819960091246기타식품판매업기타식품판매업성대유통(주)서울특별시 동작구 상도로 102, (상도동)서울특별시 동작구 상도동 324번지 1호20050803처분확정과징금부과식품위생법 제58조20050803유통기한 경과제품진열판매과징금부과7<NA><NA>4
6831900002005090819960091246기타식품판매업기타식품판매업성대유통(주)서울특별시 동작구 상도로 102, (상도동)서울특별시 동작구 상도동 324번지 1호20050803처분확정과징금부과식품위생법 제58조20050803유통기한경과제품 진열판매과징금부과7<NA><NA>4
15731900002011090820060091242식품등 수입판매업식품등 수입판매업아이수마서울특별시 동작구 현충로 70, (흑석동,씨티빌딩 지하1층)서울특별시 동작구 흑석동 118번지 2호 씨티빌딩 지하1층20110805처분확정영업소폐쇄식품위생법 제36조및제37조, 제75조20110805시설물전부철거 및 6월이상무단휴업영업소폐쇄<NA><NA><NA>4
16731900002012091219970091197일반음식점한식한솥서울특별시 동작구 보라매로5길 23, (신대방동)서울특별시 동작구 신대방동 395번지 62호20120823처분확정시정명령식품위생법 제37조 제4항 및 같은법 제71조 제1항20120823영업장 면적변경신고 미이행(영업장 확장영업) - 확인일시 : 2012. 8. 23 - 확인기관 : 자체(식품위생팀)시정명령<NA>17.17<NA>4
19631900002015041520070091209식품등 수입판매업식품등 수입판매업(주)프라센코리아서울특별시 동작구 신대방1가길 38, (신대방동,성원상떼빌 106동 2406호)서울특별시 동작구 신대방동 719번지 성원상떼빌 106동 2406호20150313처분확정영업소폐쇄식품위생법 제37조 및 제75조20150313영업시설 전부 철거영업소폐쇄<NA><NA><NA>4
931900002002082219990091024일반음식점중국식칸꼬시서울특별시 동작구 동작대로27가길 20, (사당동)서울특별시 동작구 사당동 137번지 15호20020728처분확정영업정지 2월식품위생법제31조20020728청소년주류제공1차영업정지 2월<NA>55.03<NA>3
1031900002002100119990091024일반음식점중국식칸꼬시서울특별시 동작구 동작대로27가길 20, (사당동)서울특별시 동작구 사당동 137번지 15호20020728처분확정과징금120만원부과(재판부조정권고안수용)식품위생법제31조20020728청소년주류제공1차과징금120만원부과(재판부조정권고안수용)1555.03<NA>3
1131900002002100119990091024일반음식점중국식칸꼬시서울특별시 동작구 동작대로27가길 20, (사당동)서울특별시 동작구 사당동 137번지 15호20020728처분확정영업정지15일(재판부조정권고안수용)식품위생법제31조20020728청소년주류제공1차영업정지15일(재판부조정권고안수용)1555.03<NA>3
7831900002006122919970091497일반음식점분식나들이김밥<NA>서울특별시 동작구 사당동 139번지 36호20061204처분확정과태료부과식품위생법 제26조20061204종사자(1/3) 건강진단 미필과태료부과<NA>21.12<NA>3