Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells19886
Missing cells (%)11.0%
Duplicate rows402
Duplicate rows (%)4.0%
Total size in memory1.5 MiB
Average record size in memory159.0 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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-11528/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 402 (4.0%) duplicate rowsDuplicates
운영형태 is highly overall correlated with 처분일자 and 4 other fieldsHigh correlation
업종명 is highly overall correlated with 운영형태High correlation
처분일자 is highly overall correlated with 지도점검일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 운영형태High correlation
업종명 is highly imbalanced (56.1%)Imbalance
운영형태 is highly imbalanced (97.8%)Imbalance
소재지도로명 has 5461 (54.6%) missing valuesMissing
처분기간 has 8972 (89.7%) missing valuesMissing
영업장면적(㎡) has 5334 (53.3%) missing valuesMissing

Reproduction

Analysis started2024-05-18 07:17:41.105440
Analysis finished2024-05-18 07:17:57.340679
Duration16.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3200000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 10000
100.0%

Length

2024-05-18T16:17:57.530780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:17:57.777863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3136
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20125617
Minimum20010104
Maximum20240509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T16:17:57.983126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010104
5-th percentile20030805
Q120090831
median20130123
Q320170102
95-th percentile20210326
Maximum20240509
Range230405
Interquartile range (IQR)79271

Descriptive statistics

Standard deviation52907.597
Coefficient of variation (CV)0.0026288683
Kurtosis-0.5744528
Mean20125617
Median Absolute Deviation (MAD)39292
Skewness-0.07658878
Sum2.0125617 × 1011
Variance2.7992138 × 109
MonotonicityNot monotonic
2024-05-18T16:17:58.361441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130405 330
 
3.3%
20090522 46
 
0.5%
20231230 45
 
0.4%
20141208 32
 
0.3%
20160113 31
 
0.3%
20150112 31
 
0.3%
20160330 29
 
0.3%
20130422 25
 
0.2%
20110418 24
 
0.2%
20201203 23
 
0.2%
Other values (3126) 9384
93.8%
ValueCountFrequency (%)
20010104 2
< 0.1%
20010817 1
 
< 0.1%
20010927 1
 
< 0.1%
20011012 4
< 0.1%
20011016 1
 
< 0.1%
20011019 1
 
< 0.1%
20011022 1
 
< 0.1%
20011029 3
< 0.1%
20011031 4
< 0.1%
20011105 3
< 0.1%
ValueCountFrequency (%)
20240509 1
 
< 0.1%
20240416 3
< 0.1%
20240409 1
 
< 0.1%
20240403 1
 
< 0.1%
20240402 2
< 0.1%
20240401 1
 
< 0.1%
20240327 1
 
< 0.1%
20240326 4
< 0.1%
20240325 2
< 0.1%
20240322 3
< 0.1%

교부번호
Real number (ℝ)

Distinct5253
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0035138 × 1010
Minimum1.8990094 × 1010
Maximum2.0230125 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T16:17:58.767400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8990094 × 1010
5-th percentile1.9890094 × 1010
Q12.0000094 × 1010
median2.0030095 × 1010
Q32.0090095 × 1010
95-th percentile2.0160095 × 1010
Maximum2.0230125 × 1010
Range1.2400311 × 109
Interquartile range (IQR)90001064

Descriptive statistics

Standard deviation83946395
Coefficient of variation (CV)0.0041899584
Kurtosis7.5519885
Mean2.0035138 × 1010
Median Absolute Deviation (MAD)49999660
Skewness-1.0288322
Sum2.0035138 × 1014
Variance7.0469972 × 1015
MonotonicityNot monotonic
2024-05-18T16:17:59.047699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080094225 55
 
0.5%
20000094678 32
 
0.3%
20030094780 31
 
0.3%
20000094179 31
 
0.3%
19990094152 30
 
0.3%
20010094331 26
 
0.3%
20010095164 24
 
0.2%
19990094162 24
 
0.2%
20060094326 21
 
0.2%
20150094306 21
 
0.2%
Other values (5243) 9705
97.0%
ValueCountFrequency (%)
18990094002 3
< 0.1%
19700094001 2
< 0.1%
19720094002 2
< 0.1%
19720094003 1
 
< 0.1%
19720094009 1
 
< 0.1%
19730094001 3
< 0.1%
19740094001 2
< 0.1%
19740094004 1
 
< 0.1%
19750094009 1
 
< 0.1%
19760094023 1
 
< 0.1%
ValueCountFrequency (%)
20230125143 1
< 0.1%
20230124880 1
< 0.1%
20230124818 1
< 0.1%
20230124490 2
< 0.1%
20230124398 1
< 0.1%
20230124200 1
< 0.1%
20230124133 1
< 0.1%
20230124117 2
< 0.1%
20230124105 1
< 0.1%
20230124083 1
< 0.1%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
6657 
유흥주점영업
1167 
단란주점
 
424
휴게음식점
 
413
즉석판매제조가공업
 
386
Other values (16)
953 

Length

Max length13
Median length5
Mean length5.513
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 6657
66.6%
유흥주점영업 1167
 
11.7%
단란주점 424
 
4.2%
휴게음식점 413
 
4.1%
즉석판매제조가공업 386
 
3.9%
건강기능식품일반판매업 256
 
2.6%
식품제조가공업 179
 
1.8%
제과점영업 147
 
1.5%
식품등 수입판매업 122
 
1.2%
유통전문판매업 77
 
0.8%
Other values (11) 172
 
1.7%

Length

2024-05-18T16:17:59.690310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 6657
65.8%
유흥주점영업 1167
 
11.5%
단란주점 424
 
4.2%
휴게음식점 413
 
4.1%
즉석판매제조가공업 386
 
3.8%
건강기능식품일반판매업 256
 
2.5%
식품제조가공업 179
 
1.8%
제과점영업 147
 
1.5%
식품등 122
 
1.2%
수입판매업 122
 
1.2%
Other values (12) 249
 
2.5%

업태명
Text

Distinct66
Distinct (%)0.7%
Missing30
Missing (%)0.3%
Memory size156.2 KiB
2024-05-18T16:18:00.099958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length3.7449348
Min length2

Characters and Unicode

Total characters37337
Distinct characters145
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row기타
2nd row경양식
3rd row한식
4th row경양식
5th row한식
ValueCountFrequency (%)
한식 2528
24.9%
호프/통닭 1131
11.2%
룸살롱 966
 
9.5%
분식 770
 
7.6%
기타 691
 
6.8%
단란주점 424
 
4.2%
중국식 418
 
4.1%
즉석판매제조가공업 385
 
3.8%
경양식 284
 
2.8%
통닭(치킨 210
 
2.1%
Other values (56) 2333
23.0%
2024-05-18T16:18:00.992043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 4731
 
12.7%
한 2528
 
6.8%
/ 1487
 
4.0%
통 1467
 
3.9%
닭 1341
 
3.6%
업 1235
 
3.3%
호 1131
 
3.0%
프 1131
 
3.0%
살 998
 
2.7%
롱 998
 
2.7%
Other values (135) 20290
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34871
93.4%
Other Punctuation 1502
 
4.0%
Close Punctuation 397
 
1.1%
Open Punctuation 397
 
1.1%
Space Separator 170
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 4731
 
13.6%
한 2528
 
7.2%
통 1467
 
4.2%
닭 1341
 
3.8%
업 1235
 
3.5%
호 1131
 
3.2%
프 1131
 
3.2%
살 998
 
2.9%
롱 998
 
2.9%
매 975
 
2.8%
Other values (129) 18336
52.6%
Other Punctuation
ValueCountFrequency (%)
/ 1487
99.0%
, 12
 
0.8%
. 3
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 397
100.0%
Open Punctuation
ValueCountFrequency (%)
( 397
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34871
93.4%
Common 2466
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 4731
 
13.6%
한 2528
 
7.2%
통 1467
 
4.2%
닭 1341
 
3.8%
업 1235
 
3.5%
호 1131
 
3.2%
프 1131
 
3.2%
살 998
 
2.9%
롱 998
 
2.9%
매 975
 
2.8%
Other values (129) 18336
52.6%
Common
ValueCountFrequency (%)
/ 1487
60.3%
) 397
 
16.1%
( 397
 
16.1%
170
 
6.9%
, 12
 
0.5%
. 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34871
93.4%
ASCII 2466
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 4731
 
13.6%
한 2528
 
7.2%
통 1467
 
4.2%
닭 1341
 
3.8%
업 1235
 
3.5%
호 1131
 
3.2%
프 1131
 
3.2%
살 998
 
2.9%
롱 998
 
2.9%
매 975
 
2.8%
Other values (129) 18336
52.6%
ASCII
ValueCountFrequency (%)
/ 1487
60.3%
) 397
 
16.1%
( 397
 
16.1%
170
 
6.9%
, 12
 
0.5%
. 3
 
0.1%

업소명
Text

Distinct5311
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T16:18:01.422047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length5.3707
Min length1

Characters and Unicode

Total characters53707
Distinct characters1004
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3417 ?
Unique (%)34.2%

Sample

1st row정글북
2nd row캠프데이비드
3rd row청양센타
4th row무쏘 신림점1
5th row왕십리 고 곱창
ValueCountFrequency (%)
청양센타 55
 
0.5%
신림점 52
 
0.5%
김밥천국 40
 
0.4%
주식회사 33
 
0.3%
신림역점 32
 
0.3%
만리장성 32
 
0.3%
서울대입구역점 31
 
0.3%
전주삼백식당 29
 
0.3%
조개천하 26
 
0.2%
봉구비어 24
 
0.2%
Other values (5642) 10887
96.9%
2024-05-18T16:18:02.308011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1241
 
2.3%
이 1170
 
2.2%
점 927
 
1.7%
스 920
 
1.7%
리 817
 
1.5%
주 725
 
1.3%
식 689
 
1.3%
) 633
 
1.2%
( 627
 
1.2%
대 567
 
1.1%
Other values (994) 45391
84.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48075
89.5%
Space Separator 1241
 
2.3%
Lowercase Letter 1069
 
2.0%
Uppercase Letter 1049
 
2.0%
Decimal Number 715
 
1.3%
Close Punctuation 633
 
1.2%
Open Punctuation 627
 
1.2%
Other Punctuation 267
 
0.5%
Dash Punctuation 23
 
< 0.1%
Letter Number 3
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1170
 
2.4%
점 927
 
1.9%
스 920
 
1.9%
리 817
 
1.7%
주 725
 
1.5%
식 689
 
1.4%
대 567
 
1.2%
장 536
 
1.1%
비 516
 
1.1%
마 510
 
1.1%
Other values (913) 40698
84.7%
Lowercase Letter
ValueCountFrequency (%)
e 160
15.0%
o 118
 
11.0%
a 100
 
9.4%
i 94
 
8.8%
n 86
 
8.0%
u 42
 
3.9%
l 42
 
3.9%
h 41
 
3.8%
t 40
 
3.7%
m 39
 
3.6%
Other values (16) 307
28.7%
Uppercase Letter
ValueCountFrequency (%)
B 89
 
8.5%
S 84
 
8.0%
C 79
 
7.5%
E 73
 
7.0%
A 71
 
6.8%
O 68
 
6.5%
N 58
 
5.5%
F 50
 
4.8%
T 48
 
4.6%
L 45
 
4.3%
Other values (16) 384
36.6%
Other Punctuation
ValueCountFrequency (%)
. 126
47.2%
& 68
25.5%
; 20
 
7.5%
, 20
 
7.5%
? 13
 
4.9%
! 6
 
2.2%
' 5
 
1.9%
？ 4
 
1.5%
% 3
 
1.1%
# 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 153
21.4%
0 148
20.7%
1 100
14.0%
3 77
10.8%
4 57
 
8.0%
9 53
 
7.4%
7 45
 
6.3%
8 39
 
5.5%
5 26
 
3.6%
6 17
 
2.4%
Space Separator
ValueCountFrequency (%)
1241
100.0%
Close Punctuation
ValueCountFrequency (%)
) 633
100.0%
Open Punctuation
ValueCountFrequency (%)
( 627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
100.0%
Other Symbol
ValueCountFrequency (%)
♡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48038
89.4%
Common 3511
 
6.5%
Latin 2121
 
3.9%
Han 37
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1170
 
2.4%
점 927
 
1.9%
스 920
 
1.9%
리 817
 
1.7%
주 725
 
1.5%
식 689
 
1.4%
대 567
 
1.2%
장 536
 
1.1%
비 516
 
1.1%
마 510
 
1.1%
Other values (891) 40661
84.6%
Latin
ValueCountFrequency (%)
e 160
 
7.5%
o 118
 
5.6%
a 100
 
4.7%
i 94
 
4.4%
B 89
 
4.2%
n 86
 
4.1%
S 84
 
4.0%
C 79
 
3.7%
E 73
 
3.4%
A 71
 
3.3%
Other values (43) 1167
55.0%
Common
ValueCountFrequency (%)
1241
35.3%
) 633
18.0%
( 627
17.9%
2 153
 
4.4%
0 148
 
4.2%
. 126
 
3.6%
1 100
 
2.8%
3 77
 
2.2%
& 68
 
1.9%
4 57
 
1.6%
Other values (18) 281
 
8.0%
Han
ValueCountFrequency (%)
秀 5
 
13.5%
家 3
 
8.1%
生 2
 
5.4%
地 2
 
5.4%
堂 2
 
5.4%
女 2
 
5.4%
子 2
 
5.4%
球 2
 
5.4%
唐 2
 
5.4%
命 2
 
5.4%
Other values (12) 13
35.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48026
89.4%
ASCII 5624
 
10.5%
CJK 35
 
0.1%
Compat Jamo 12
 
< 0.1%
None 4
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1241
22.1%
) 633
 
11.3%
( 627
 
11.1%
e 160
 
2.8%
2 153
 
2.7%
0 148
 
2.6%
. 126
 
2.2%
o 118
 
2.1%
a 100
 
1.8%
1 100
 
1.8%
Other values (68) 2218
39.4%
Hangul
ValueCountFrequency (%)
이 1170
 
2.4%
점 927
 
1.9%
스 920
 
1.9%
리 817
 
1.7%
주 725
 
1.5%
식 689
 
1.4%
대 567
 
1.2%
장 536
 
1.1%
비 516
 
1.1%
마 510
 
1.1%
Other values (888) 40649
84.6%
CJK
ValueCountFrequency (%)
秀 5
14.3%
家 3
 
8.6%
生 2
 
5.7%
地 2
 
5.7%
堂 2
 
5.7%
子 2
 
5.7%
球 2
 
5.7%
唐 2
 
5.7%
命 2
 
5.7%
大 2
 
5.7%
Other values (11) 11
31.4%
Compat Jamo
ValueCountFrequency (%)
ㄴ 4
33.3%
ㄷ 4
33.3%
ㄱ 4
33.3%
None
ValueCountFrequency (%)
？ 4
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
女 2
100.0%
Misc Symbols
ValueCountFrequency (%)
♡ 1
100.0%

소재지도로명
Text

MISSING 

Distinct2456
Distinct (%)54.1%
Missing5461
Missing (%)54.6%
Memory size156.2 KiB
2024-05-18T16:18:02.989022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length57
Mean length29.695968
Min length22

Characters and Unicode

Total characters134790
Distinct characters280
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

Unique1524 ?
Unique (%)33.6%

Sample

1st row서울특별시 관악구 남부순환로161가길 51, (신림동,지상1층)
2nd row서울특별시 관악구 남부순환로 1600-7, (신림동,지상3층)
3rd row서울특별시 관악구 봉천로 229, (봉천동,(972번지 3호))
4th row서울특별시 관악구 봉천로12길 39, 1층 125호 (신림동, 가야위드안)
5th row서울특별시 관악구 신림로 366, 지하1층 (신림동)
ValueCountFrequency (%)
서울특별시 4539
17.2%
관악구 4539
17.2%
신림동 2292
 
8.7%
봉천동 1495
 
5.7%
1층 1357
 
5.1%
남부순환로 668
 
2.5%
지하1층 395
 
1.5%
신림로 371
 
1.4%
지상1층 343
 
1.3%
봉천로 322
 
1.2%
Other values (1590) 10129
38.3%
2024-05-18T16:18:03.802811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21922
 
16.3%
1 6514
 
4.8%
, 5688
 
4.2%
관 5005
 
3.7%
악 4933
 
3.7%
동 4732
 
3.5%
시 4613
 
3.4%
) 4592
 
3.4%
( 4592
 
3.4%
서 4574
 
3.4%
Other values (270) 67625
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76677
56.9%
Space Separator 21922
 
16.3%
Decimal Number 20554
 
15.2%
Other Punctuation 5694
 
4.2%
Close Punctuation 4592
 
3.4%
Open Punctuation 4592
 
3.4%
Dash Punctuation 592
 
0.4%
Uppercase Letter 118
 
0.1%
Math Symbol 47
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 5005
 
6.5%
악 4933
 
6.4%
동 4732
 
6.2%
시 4613
 
6.0%
서 4574
 
6.0%
울 4557
 
5.9%
구 4555
 
5.9%
특 4544
 
5.9%
별 4539
 
5.9%
로 3830
 
5.0%
Other values (236) 30795
40.2%
Uppercase Letter
ValueCountFrequency (%)
B 61
51.7%
T 9
 
7.6%
S 9
 
7.6%
W 7
 
5.9%
E 6
 
5.1%
K 6
 
5.1%
D 5
 
4.2%
O 4
 
3.4%
R 4
 
3.4%
A 3
 
2.5%
Other values (3) 4
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 6514
31.7%
2 2936
14.3%
3 1967
 
9.6%
6 1649
 
8.0%
5 1632
 
7.9%
4 1359
 
6.6%
0 1352
 
6.6%
9 1054
 
5.1%
8 1049
 
5.1%
7 1042
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 5688
99.9%
@ 3
 
0.1%
. 2
 
< 0.1%
/ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
a 1
50.0%
Space Separator
ValueCountFrequency (%)
21922
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4592
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4592
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 592
100.0%
Math Symbol
ValueCountFrequency (%)
~ 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76677
56.9%
Common 57993
43.0%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 5005
 
6.5%
악 4933
 
6.4%
동 4732
 
6.2%
시 4613
 
6.0%
서 4574
 
6.0%
울 4557
 
5.9%
구 4555
 
5.9%
특 4544
 
5.9%
별 4539
 
5.9%
로 3830
 
5.0%
Other values (236) 30795
40.2%
Common
ValueCountFrequency (%)
21922
37.8%
1 6514
 
11.2%
, 5688
 
9.8%
) 4592
 
7.9%
( 4592
 
7.9%
2 2936
 
5.1%
3 1967
 
3.4%
6 1649
 
2.8%
5 1632
 
2.8%
4 1359
 
2.3%
Other values (9) 5142
 
8.9%
Latin
ValueCountFrequency (%)
B 61
50.8%
T 9
 
7.5%
S 9
 
7.5%
W 7
 
5.8%
E 6
 
5.0%
K 6
 
5.0%
D 5
 
4.2%
O 4
 
3.3%
R 4
 
3.3%
A 3
 
2.5%
Other values (5) 6
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76677
56.9%
ASCII 58113
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21922
37.7%
1 6514
 
11.2%
, 5688
 
9.8%
) 4592
 
7.9%
( 4592
 
7.9%
2 2936
 
5.1%
3 1967
 
3.4%
6 1649
 
2.8%
5 1632
 
2.8%
4 1359
 
2.3%
Other values (24) 5262
 
9.1%
Hangul
ValueCountFrequency (%)
관 5005
 
6.5%
악 4933
 
6.4%
동 4732
 
6.2%
시 4613
 
6.0%
서 4574
 
6.0%
울 4557
 
5.9%
구 4555
 
5.9%
특 4544
 
5.9%
별 4539
 
5.9%
로 3830
 
5.0%
Other values (236) 30795
40.2%

소재지지번
Text

Distinct4255
Distinct (%)42.7%
Missing37
Missing (%)0.4%
Memory size156.2 KiB
2024-05-18T16:18:04.514083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length59
Mean length28.09184
Min length21

Characters and Unicode

Total characters279879
Distinct characters266
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

Unique2320 ?
Unique (%)23.3%

Sample

1st row서울특별시 관악구 신림동 1640번지 1호 지하1층
2nd row서울특별시 관악구 신림동 1652번지 9호 지상1층
3rd row서울특별시 관악구 신림동 512번지 2호 지상1층
4th row서울특별시 관악구 신림동 1640번지 26호 지상3층
5th row서울특별시 관악구 신림동 241번지 111호 지상1층
ValueCountFrequency (%)
관악구 9964
18.4%
서울특별시 9963
18.4%
신림동 5667
 
10.5%
봉천동 3774
 
7.0%
지상1층 1412
 
2.6%
1호 1051
 
1.9%
2호 663
 
1.2%
지하1층 550
 
1.0%
남현동 522
 
1.0%
4호 439
 
0.8%
Other values (1532) 20005
37.0%
2024-05-18T16:18:05.762455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70342
25.1%
1 15103
 
5.4%
지 12912
 
4.6%
호 10145
 
3.6%
동 10046
 
3.6%
관 10018
 
3.6%
악 10011
 
3.6%
서 9983
 
3.6%
울 9981
 
3.6%
구 9980
 
3.6%
Other values (256) 111358
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151633
54.2%
Space Separator 70342
25.1%
Decimal Number 56449
 
20.2%
Other Punctuation 523
 
0.2%
Dash Punctuation 347
 
0.1%
Close Punctuation 195
 
0.1%
Open Punctuation 195
 
0.1%
Uppercase Letter 149
 
0.1%
Math Symbol 40
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 12912
 
8.5%
호 10145
 
6.7%
동 10046
 
6.6%
관 10018
 
6.6%
악 10011
 
6.6%
서 9983
 
6.6%
울 9981
 
6.6%
구 9980
 
6.6%
번 9978
 
6.6%
시 9972
 
6.6%
Other values (218) 48607
32.1%
Uppercase Letter
ValueCountFrequency (%)
B 48
32.2%
A 32
21.5%
S 14
 
9.4%
T 12
 
8.1%
K 9
 
6.0%
E 5
 
3.4%
D 4
 
2.7%
R 4
 
2.7%
W 4
 
2.7%
O 4
 
2.7%
Other values (6) 13
 
8.7%
Decimal Number
ValueCountFrequency (%)
1 15103
26.8%
2 6626
11.7%
6 5971
 
10.6%
4 5265
 
9.3%
3 5057
 
9.0%
5 4981
 
8.8%
0 3833
 
6.8%
8 3445
 
6.1%
7 3142
 
5.6%
9 3026
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 498
95.2%
@ 12
 
2.3%
. 10
 
1.9%
/ 3
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
s 4
66.7%
g 1
 
16.7%
c 1
 
16.7%
Space Separator
ValueCountFrequency (%)
70342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 347
100.0%
Close Punctuation
ValueCountFrequency (%)
) 195
100.0%
Open Punctuation
ValueCountFrequency (%)
( 195
100.0%
Math Symbol
ValueCountFrequency (%)
~ 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151633
54.2%
Common 128091
45.8%
Latin 155
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 12912
 
8.5%
호 10145
 
6.7%
동 10046
 
6.6%
관 10018
 
6.6%
악 10011
 
6.6%
서 9983
 
6.6%
울 9981
 
6.6%
구 9980
 
6.6%
번 9978
 
6.6%
시 9972
 
6.6%
Other values (218) 48607
32.1%
Common
ValueCountFrequency (%)
70342
54.9%
1 15103
 
11.8%
2 6626
 
5.2%
6 5971
 
4.7%
4 5265
 
4.1%
3 5057
 
3.9%
5 4981
 
3.9%
0 3833
 
3.0%
8 3445
 
2.7%
7 3142
 
2.5%
Other values (9) 4326
 
3.4%
Latin
ValueCountFrequency (%)
B 48
31.0%
A 32
20.6%
S 14
 
9.0%
T 12
 
7.7%
K 9
 
5.8%
E 5
 
3.2%
D 4
 
2.6%
s 4
 
2.6%
R 4
 
2.6%
W 4
 
2.6%
Other values (9) 19
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151633
54.2%
ASCII 128246
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70342
54.8%
1 15103
 
11.8%
2 6626
 
5.2%
6 5971
 
4.7%
4 5265
 
4.1%
3 5057
 
3.9%
5 4981
 
3.9%
0 3833
 
3.0%
8 3445
 
2.7%
7 3142
 
2.4%
Other values (28) 4481
 
3.5%
Hangul
ValueCountFrequency (%)
지 12912
 
8.5%
호 10145
 
6.7%
동 10046
 
6.6%
관 10018
 
6.6%
악 10011
 
6.6%
서 9983
 
6.6%
울 9981
 
6.6%
구 9980
 
6.6%
번 9978
 
6.6%
시 9972
 
6.6%
Other values (218) 48607
32.1%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3341
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124246
Minimum20001118
Maximum20240317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T16:18:06.140088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001118
5-th percentile20030626
Q120090728
median20121212
Q320161023
95-th percentile20210218
Maximum20240317
Range239199
Interquartile range (IQR)70295

Descriptive statistics

Standard deviation52968.131
Coefficient of variation (CV)0.0026320554
Kurtosis-0.53348141
Mean20124246
Median Absolute Deviation (MAD)39102
Skewness-0.083620288
Sum2.0124246 × 1011
Variance2.8056229 × 109
MonotonicityNot monotonic
2024-05-18T16:18:06.580966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130308 202
 
2.0%
20130307 93
 
0.9%
20180101 81
 
0.8%
20170101 74
 
0.7%
20141110 57
 
0.6%
20151120 40
 
0.4%
20130408 31
 
0.3%
20240119 30
 
0.3%
20170601 29
 
0.3%
20130311 28
 
0.3%
Other values (3331) 9335
93.3%
ValueCountFrequency (%)
20001118 1
< 0.1%
20001208 1
< 0.1%
20001223 1
< 0.1%
20010114 1
< 0.1%
20010121 1
< 0.1%
20010318 1
< 0.1%
20010410 1
< 0.1%
20010508 1
< 0.1%
20010515 1
< 0.1%
20010625 1
< 0.1%
ValueCountFrequency (%)
20240317 2
 
< 0.1%
20240311 3
< 0.1%
20240309 2
 
< 0.1%
20240308 1
 
< 0.1%
20240229 4
< 0.1%
20240222 1
 
< 0.1%
20240220 7
0.1%
20240219 7
0.1%
20240216 1
 
< 0.1%
20240215 3
< 0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
처분확정
10000 

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 10000
100.0%

Length

2024-05-18T16:18:06.965126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:18:07.246402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%

처분명
Text

Distinct1211
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T16:18:07.686484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length68
Mean length7.8842
Min length2

Characters and Unicode

Total characters78842
Distinct characters233
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique772 ?
Unique (%)7.7%

Sample

1st row영업정지
2nd row영업소폐쇄
3rd row시정명령
4th row과태료부과
5th row과징금부과-15,600,000원
ValueCountFrequency (%)
과태료부과 1987
15.4%
시정명령 1730
 
13.4%
영업소폐쇄 1674
 
13.0%
영업정지 1107
 
8.6%
시설개수명령 1035
 
8.0%
부과 268
 
2.1%
과징금부과 209
 
1.6%
과태료 183
 
1.4%
및 181
 
1.4%
과징금 154
 
1.2%
Other values (1274) 4357
33.8%
2024-05-18T16:18:08.764651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7664
 
9.7%
부 4094
 
5.2%
정 3787
 
4.8%
업 3678
 
4.7%
영 3632
 
4.6%
0 3281
 
4.2%
료 3199
 
4.1%
태 3192
 
4.0%
시 3086
 
3.9%
명 2975
 
3.8%
Other values (223) 40254
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61485
78.0%
Decimal Number 10328
 
13.1%
Space Separator 2893
 
3.7%
Other Punctuation 1568
 
2.0%
Open Punctuation 1162
 
1.5%
Close Punctuation 1157
 
1.5%
Math Symbol 131
 
0.2%
Dash Punctuation 116
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7664
 
12.5%
부 4094
 
6.7%
정 3787
 
6.2%
업 3678
 
6.0%
영 3632
 
5.9%
료 3199
 
5.2%
태 3192
 
5.2%
시 3086
 
5.0%
명 2975
 
4.8%
령 2964
 
4.8%
Other values (195) 23214
37.8%
Decimal Number
ValueCountFrequency (%)
0 3281
31.8%
2 2003
19.4%
1 1869
18.1%
4 647
 
6.3%
3 617
 
6.0%
6 586
 
5.7%
5 567
 
5.5%
7 365
 
3.5%
8 236
 
2.3%
9 157
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 936
59.7%
, 435
27.7%
% 138
 
8.8%
/ 28
 
1.8%
: 27
 
1.7%
' 2
 
0.1%
？ 1
 
0.1%
* 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 124
94.7%
+ 6
 
4.6%
→ 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 1155
99.4%
[ 7
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 1150
99.4%
] 7
 
0.6%
Space Separator
ValueCountFrequency (%)
2893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61485
78.0%
Common 17357
 
22.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7664
 
12.5%
부 4094
 
6.7%
정 3787
 
6.2%
업 3678
 
6.0%
영 3632
 
5.9%
료 3199
 
5.2%
태 3192
 
5.2%
시 3086
 
5.0%
명 2975
 
4.8%
령 2964
 
4.8%
Other values (195) 23214
37.8%
Common
ValueCountFrequency (%)
0 3281
18.9%
2893
16.7%
2 2003
11.5%
1 1869
10.8%
( 1155
 
6.7%
) 1150
 
6.6%
. 936
 
5.4%
4 647
 
3.7%
3 617
 
3.6%
6 586
 
3.4%
Other values (18) 2220
12.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61437
77.9%
ASCII 17355
 
22.0%
Compat Jamo 48
 
0.1%
Arrows 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7664
 
12.5%
부 4094
 
6.7%
정 3787
 
6.2%
업 3678
 
6.0%
영 3632
 
5.9%
료 3199
 
5.2%
태 3192
 
5.2%
시 3086
 
5.0%
명 2975
 
4.8%
령 2964
 
4.8%
Other values (194) 23166
37.7%
ASCII
ValueCountFrequency (%)
0 3281
18.9%
2893
16.7%
2 2003
11.5%
1 1869
10.8%
( 1155
 
6.7%
) 1150
 
6.6%
. 936
 
5.4%
4 647
 
3.7%
3 617
 
3.6%
6 586
 
3.4%
Other values (16) 2218
12.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 48
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

법적근거
Text

Distinct837
Distinct (%)8.4%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-18T16:18:09.249569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length13.798039
Min length3

Characters and Unicode

Total characters137939
Distinct characters160
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)4.4%

Sample

1st row식품위생법 제31조
2nd row식품위생법 제37조
3rd row식품위생법 제71조, 제72조 및 제75조
4th row법 제101조제2항제1호 및 영 제67조
5th row식품위생법 제44조
ValueCountFrequency (%)
법 5177
18.2%
식품위생법 4453
15.7%
및 2354
 
8.3%
제75조 1688
 
5.9%
제71조 1292
 
4.5%
제101조제2항제1호 1079
 
3.8%
제37조 1052
 
3.7%
제74조 648
 
2.3%
제67조 605
 
2.1%
영 601
 
2.1%
Other values (579) 9489
33.4%
2024-05-18T16:18:10.328041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18457
13.4%
제 17604
12.8%
조 13988
10.1%
법 12298
 
8.9%
1 8721
 
6.3%
위 6815
 
4.9%
7 6664
 
4.8%
식 6473
 
4.7%
품 6473
 
4.7%
생 6376
 
4.6%
Other values (150) 34070
24.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83136
60.3%
Decimal Number 33468
24.3%
Space Separator 18457
 
13.4%
Other Punctuation 1610
 
1.2%
Open Punctuation 633
 
0.5%
Close Punctuation 631
 
0.5%
Letter Number 2
 
< 0.1%
Other Symbol 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 17604
21.2%
조 13988
16.8%
법 12298
14.8%
위 6815
 
8.2%
식 6473
 
7.8%
품 6473
 
7.8%
생 6376
 
7.7%
및 2386
 
2.9%
항 2358
 
2.8%
호 1791
 
2.2%
Other values (126) 6574
 
7.9%
Decimal Number
ValueCountFrequency (%)
1 8721
26.1%
7 6664
19.9%
3 4191
12.5%
2 3594
10.7%
4 2853
 
8.5%
5 2392
 
7.1%
6 2314
 
6.9%
0 2208
 
6.6%
8 474
 
1.4%
9 57
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1557
96.7%
: 35
 
2.2%
. 10
 
0.6%
; 5
 
0.3%
？ 2
 
0.1%
? 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 632
99.8%
「 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 630
99.8%
」 1
 
0.2%
Space Separator
ValueCountFrequency (%)
18457
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Other Symbol
ValueCountFrequency (%)
○ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83136
60.3%
Common 54800
39.7%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 17604
21.2%
조 13988
16.8%
법 12298
14.8%
위 6815
 
8.2%
식 6473
 
7.8%
품 6473
 
7.8%
생 6376
 
7.7%
및 2386
 
2.9%
항 2358
 
2.8%
호 1791
 
2.2%
Other values (126) 6574
 
7.9%
Common
ValueCountFrequency (%)
18457
33.7%
1 8721
15.9%
7 6664
 
12.2%
3 4191
 
7.6%
2 3594
 
6.6%
4 2853
 
5.2%
5 2392
 
4.4%
6 2314
 
4.2%
0 2208
 
4.0%
, 1557
 
2.8%
Other values (12) 1849
 
3.4%
Latin
ValueCountFrequency (%)
Ⅱ 2
66.7%
X 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83132
60.3%
ASCII 54796
39.7%
None 4
 
< 0.1%
Compat Jamo 4
 
< 0.1%
Number Forms 2
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18457
33.7%
1 8721
15.9%
7 6664
 
12.2%
3 4191
 
7.6%
2 3594
 
6.6%
4 2853
 
5.2%
5 2392
 
4.4%
6 2314
 
4.2%
0 2208
 
4.0%
, 1557
 
2.8%
Other values (9) 1845
 
3.4%
Hangul
ValueCountFrequency (%)
제 17604
21.2%
조 13988
16.8%
법 12298
14.8%
위 6815
 
8.2%
식 6473
 
7.8%
품 6473
 
7.8%
생 6376
 
7.7%
및 2386
 
2.9%
항 2358
 
2.8%
호 1791
 
2.2%
Other values (122) 6570
 
7.9%
None
ValueCountFrequency (%)
？ 2
50.0%
「 1
25.0%
」 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅔ 1
25.0%
ㅈ 1
25.0%
ㄱ 1
25.0%
ㅗ 1
25.0%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3389
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124066
Minimum19980722
Maximum20240317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T16:18:10.604919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980722
5-th percentile20030623
Q120090715
median20121212
Q320161026
95-th percentile20210208
Maximum20240317
Range259595
Interquartile range (IQR)70311.25

Descriptive statistics

Standard deviation52755.129
Coefficient of variation (CV)0.0026214945
Kurtosis-0.56376062
Mean20124066
Median Absolute Deviation (MAD)39091
Skewness-0.1036633
Sum2.0124066 × 1011
Variance2.7831036 × 109
MonotonicityNot monotonic
2024-05-18T16:18:10.996195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130308 213
 
2.1%
20170101 99
 
1.0%
20130307 93
 
0.9%
20180101 90
 
0.9%
20141110 57
 
0.6%
20230101 53
 
0.5%
20160101 45
 
0.4%
20151120 40
 
0.4%
20201231 32
 
0.3%
20130408 31
 
0.3%
Other values (3379) 9247
92.5%
ValueCountFrequency (%)
19980722 1
< 0.1%
20000301 1
< 0.1%
20001118 1
< 0.1%
20001208 1
< 0.1%
20001223 1
< 0.1%
20010114 1
< 0.1%
20010410 1
< 0.1%
20010508 1
< 0.1%
20010515 1
< 0.1%
20010625 1
< 0.1%
ValueCountFrequency (%)
20240317 2
 
< 0.1%
20240311 3
< 0.1%
20240309 2
 
< 0.1%
20240308 1
 
< 0.1%
20240229 3
< 0.1%
20240222 1
 
< 0.1%
20240220 7
0.1%
20240219 7
0.1%
20240216 1
 
< 0.1%
20240215 3
< 0.1%

위반내용
Text

Distinct3136
Distinct (%)31.5%
Missing49
Missing (%)0.5%
Memory size156.2 KiB
2024-05-18T16:18:11.379354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length388
Median length133
Mean length16.58577
Min length4

Characters and Unicode

Total characters165045
Distinct characters662
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2023 ?
Unique (%)20.3%

Sample

1st row청소년 주류제공
2nd row영업시설의 전부철거
3rd row2014.9.23.21:30경 관악구식품접객업소합동단속반점검시 곱창볶음에 벌레 등 이물혼입된 사실이 적발됨.
4th row조리실 위생 불량
5th row청소년 주류제공
ValueCountFrequency (%)
영업시설의 791
 
2.4%
위생교육 648
 
1.9%
영업장외 568
 
1.7%
철거 561
 
1.7%
영업 528
 
1.6%
건강진단 474
 
1.4%
미필 470
 
1.4%
기존영업자 459
 
1.4%
전부를 457
 
1.4%
주방내 444
 
1.3%
Other values (4555) 27941
83.8%
2024-05-18T16:18:12.134284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23964
 
14.5%
업 6983
 
4.2%
영 4851
 
2.9%
미 3561
 
2.2%
1 3388
 
2.1%
) 2714
 
1.6%
( 2656
 
1.6%
2 2557
 
1.5%
기 2541
 
1.5%
위 2460
 
1.5%
Other values (652) 109370
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121208
73.4%
Space Separator 23964
 
14.5%
Decimal Number 11052
 
6.7%
Other Punctuation 2961
 
1.8%
Close Punctuation 2719
 
1.6%
Open Punctuation 2661
 
1.6%
Dash Punctuation 328
 
0.2%
Other Symbol 48
 
< 0.1%
Lowercase Letter 38
 
< 0.1%
Uppercase Letter 38
 
< 0.1%
Other values (5) 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6983
 
5.8%
영 4851
 
4.0%
미 3561
 
2.9%
기 2541
 
2.1%
위 2460
 
2.0%
시 2198
 
1.8%
장 2184
 
1.8%
소 2111
 
1.7%
주 2100
 
1.7%
설 1853
 
1.5%
Other values (586) 90366
74.6%
Uppercase Letter
ValueCountFrequency (%)
O 10
26.3%
T 5
13.2%
V 4
 
10.5%
R 4
 
10.5%
B 3
 
7.9%
G 3
 
7.9%
S 2
 
5.3%
K 1
 
2.6%
N 1
 
2.6%
E 1
 
2.6%
Other values (4) 4
 
10.5%
Lowercase Letter
ValueCountFrequency (%)
g 16
42.1%
c 7
18.4%
w 3
 
7.9%
v 2
 
5.3%
m 2
 
5.3%
o 2
 
5.3%
e 1
 
2.6%
i 1
 
2.6%
l 1
 
2.6%
k 1
 
2.6%
Other values (2) 2
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 3388
30.7%
2 2557
23.1%
0 2197
19.9%
3 799
 
7.2%
5 530
 
4.8%
4 469
 
4.2%
6 452
 
4.1%
7 291
 
2.6%
9 197
 
1.8%
8 172
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 1618
54.6%
, 686
23.2%
: 382
 
12.9%
/ 225
 
7.6%
? 31
 
1.0%
% 11
 
0.4%
* 3
 
0.1%
？ 3
 
0.1%
' 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 2714
99.8%
] 3
 
0.1%
」 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2656
99.8%
[ 3
 
0.1%
「 2
 
0.1%
Other Symbol
ValueCountFrequency (%)
○ 26
54.2%
㎡ 20
41.7%
● 2
 
4.2%
Math Symbol
ValueCountFrequency (%)
~ 10
55.6%
→ 7
38.9%
+ 1
 
5.6%
Other Number
ValueCountFrequency (%)
③ 1
33.3%
② 1
33.3%
① 1
33.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
Space Separator
ValueCountFrequency (%)
23964
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 328
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121204
73.4%
Common 43757
 
26.5%
Latin 80
 
< 0.1%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6983
 
5.8%
영 4851
 
4.0%
미 3561
 
2.9%
기 2541
 
2.1%
위 2460
 
2.0%
시 2198
 
1.8%
장 2184
 
1.8%
소 2111
 
1.7%
주 2100
 
1.7%
설 1853
 
1.5%
Other values (584) 90362
74.6%
Common
ValueCountFrequency (%)
23964
54.8%
1 3388
 
7.7%
) 2714
 
6.2%
( 2656
 
6.1%
2 2557
 
5.8%
0 2197
 
5.0%
. 1618
 
3.7%
3 799
 
1.8%
, 686
 
1.6%
5 530
 
1.2%
Other values (28) 2648
 
6.1%
Latin
ValueCountFrequency (%)
g 16
20.0%
O 10
12.5%
c 7
 
8.8%
T 5
 
6.2%
V 4
 
5.0%
R 4
 
5.0%
w 3
 
3.8%
B 3
 
3.8%
G 3
 
3.8%
v 2
 
2.5%
Other values (18) 23
28.7%
Han
ValueCountFrequency (%)
麗 2
50.0%
駙 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121129
73.4%
ASCII 43765
 
26.5%
Compat Jamo 75
 
< 0.1%
Geometric Shapes 28
 
< 0.1%
CJK Compat 20
 
< 0.1%
Arrows 7
 
< 0.1%
None 7
 
< 0.1%
Number Forms 4
 
< 0.1%
Punctuation 3
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23964
54.8%
1 3388
 
7.7%
) 2714
 
6.2%
( 2656
 
6.1%
2 2557
 
5.8%
0 2197
 
5.0%
. 1618
 
3.7%
3 799
 
1.8%
, 686
 
1.6%
5 530
 
1.2%
Other values (42) 2656
 
6.1%
Hangul
ValueCountFrequency (%)
업 6983
 
5.8%
영 4851
 
4.0%
미 3561
 
2.9%
기 2541
 
2.1%
위 2460
 
2.0%
시 2198
 
1.8%
장 2184
 
1.8%
소 2111
 
1.7%
주 2100
 
1.7%
설 1853
 
1.5%
Other values (576) 90287
74.5%
Compat Jamo
ValueCountFrequency (%)
ㅇ 66
88.0%
ㆍ 3
 
4.0%
ㅂ 1
 
1.3%
ㄹ 1
 
1.3%
ㅁ 1
 
1.3%
ㄴ 1
 
1.3%
ㄱ 1
 
1.3%
ㅌ 1
 
1.3%
Geometric Shapes
ValueCountFrequency (%)
○ 26
92.9%
● 2
 
7.1%
CJK Compat
ValueCountFrequency (%)
㎡ 20
100.0%
Arrows
ValueCountFrequency (%)
→ 7
100.0%
None
ValueCountFrequency (%)
？ 3
42.9%
「 2
28.6%
」 2
28.6%
Punctuation
ValueCountFrequency (%)
“ 2
66.7%
” 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
麗 2
100.0%
CJK
ValueCountFrequency (%)
駙 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
③ 1
33.3%
② 1
33.3%
① 1
33.3%

처분내용
Text

Distinct1211
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T16:18:12.663456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length68
Mean length7.8842
Min length2

Characters and Unicode

Total characters78842
Distinct characters233
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique772 ?
Unique (%)7.7%

Sample

1st row영업정지
2nd row영업소폐쇄
3rd row시정명령
4th row과태료부과
5th row과징금부과-15,600,000원
ValueCountFrequency (%)
과태료부과 1987
15.4%
시정명령 1730
 
13.4%
영업소폐쇄 1674
 
13.0%
영업정지 1107
 
8.6%
시설개수명령 1035
 
8.0%
부과 268
 
2.1%
과징금부과 209
 
1.6%
과태료 183
 
1.4%
및 181
 
1.4%
과징금 154
 
1.2%
Other values (1274) 4357
33.8%
2024-05-18T16:18:13.685876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7664
 
9.7%
부 4094
 
5.2%
정 3787
 
4.8%
업 3678
 
4.7%
영 3632
 
4.6%
0 3281
 
4.2%
료 3199
 
4.1%
태 3192
 
4.0%
시 3086
 
3.9%
명 2975
 
3.8%
Other values (223) 40254
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61485
78.0%
Decimal Number 10328
 
13.1%
Space Separator 2893
 
3.7%
Other Punctuation 1568
 
2.0%
Open Punctuation 1162
 
1.5%
Close Punctuation 1157
 
1.5%
Math Symbol 131
 
0.2%
Dash Punctuation 116
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7664
 
12.5%
부 4094
 
6.7%
정 3787
 
6.2%
업 3678
 
6.0%
영 3632
 
5.9%
료 3199
 
5.2%
태 3192
 
5.2%
시 3086
 
5.0%
명 2975
 
4.8%
령 2964
 
4.8%
Other values (195) 23214
37.8%
Decimal Number
ValueCountFrequency (%)
0 3281
31.8%
2 2003
19.4%
1 1869
18.1%
4 647
 
6.3%
3 617
 
6.0%
6 586
 
5.7%
5 567
 
5.5%
7 365
 
3.5%
8 236
 
2.3%
9 157
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 936
59.7%
, 435
27.7%
% 138
 
8.8%
/ 28
 
1.8%
: 27
 
1.7%
' 2
 
0.1%
？ 1
 
0.1%
* 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 124
94.7%
+ 6
 
4.6%
→ 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 1155
99.4%
[ 7
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 1150
99.4%
] 7
 
0.6%
Space Separator
ValueCountFrequency (%)
2893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61485
78.0%
Common 17357
 
22.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7664
 
12.5%
부 4094
 
6.7%
정 3787
 
6.2%
업 3678
 
6.0%
영 3632
 
5.9%
료 3199
 
5.2%
태 3192
 
5.2%
시 3086
 
5.0%
명 2975
 
4.8%
령 2964
 
4.8%
Other values (195) 23214
37.8%
Common
ValueCountFrequency (%)
0 3281
18.9%
2893
16.7%
2 2003
11.5%
1 1869
10.8%
( 1155
 
6.7%
) 1150
 
6.6%
. 936
 
5.4%
4 647
 
3.7%
3 617
 
3.6%
6 586
 
3.4%
Other values (18) 2220
12.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61437
77.9%
ASCII 17355
 
22.0%
Compat Jamo 48
 
0.1%
Arrows 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7664
 
12.5%
부 4094
 
6.7%
정 3787
 
6.2%
업 3678
 
6.0%
영 3632
 
5.9%
료 3199
 
5.2%
태 3192
 
5.2%
시 3086
 
5.0%
명 2975
 
4.8%
령 2964
 
4.8%
Other values (194) 23166
37.7%
ASCII
ValueCountFrequency (%)
0 3281
18.9%
2893
16.7%
2 2003
11.5%
1 1869
10.8%
( 1155
 
6.7%
) 1150
 
6.6%
. 936
 
5.4%
4 647
 
3.7%
3 617
 
3.6%
6 586
 
3.4%
Other values (16) 2218
12.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 48
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

처분기간
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)2.7%
Missing8972
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean11.075875
Minimum0
Maximum43
Zeros89
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T16:18:13.974557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median15
Q315
95-th percentile20
Maximum43
Range43
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.1104793
Coefficient of variation (CV)0.55169267
Kurtosis1.5747071
Mean11.075875
Median Absolute Deviation (MAD)5
Skewness0.3439065
Sum11386
Variance37.337957
MonotonicityNot monotonic
2024-05-18T16:18:14.346280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
15 448
 
4.5%
7 295
 
2.9%
0 89
 
0.9%
10 58
 
0.6%
20 33
 
0.3%
3 16
 
0.2%
22 14
 
0.1%
5 13
 
0.1%
1 9
 
0.1%
13 7
 
0.1%
Other values (18) 46
 
0.5%
(Missing) 8972
89.7%
ValueCountFrequency (%)
0 89
 
0.9%
1 9
 
0.1%
2 3
 
< 0.1%
3 16
 
0.2%
4 6
 
0.1%
5 13
 
0.1%
6 6
 
0.1%
7 295
2.9%
10 58
 
0.6%
11 2
 
< 0.1%
ValueCountFrequency (%)
43 1
 
< 0.1%
40 3
< 0.1%
31 2
< 0.1%
30 1
 
< 0.1%
29 3
< 0.1%
28 2
< 0.1%
27 2
< 0.1%
25 1
 
< 0.1%
24 4
< 0.1%
23 1
 
< 0.1%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1987
Distinct (%)42.6%
Missing5334
Missing (%)53.3%
Infinite0
Infinite (%)0.0%
Mean92.535628
Minimum0
Maximum1862.21
Zeros7
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T16:18:14.715906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.07
Q136
median71
Q3108.81
95-th percentile250.81
Maximum1862.21
Range1862.21
Interquartile range (IQR)72.81

Descriptive statistics

Standard deviation106.87633
Coefficient of variation (CV)1.1549749
Kurtosis75.04232
Mean92.535628
Median Absolute Deviation (MAD)36.35
Skewness6.6632346
Sum431771.24
Variance11422.549
MonotonicityNot monotonic
2024-05-18T16:18:15.147538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.0 37
 
0.4%
33.0 30
 
0.3%
52.88 21
 
0.2%
45.0 21
 
0.2%
26.4 19
 
0.2%
99.0 19
 
0.2%
49.5 19
 
0.2%
86.82 17
 
0.2%
23.1 16
 
0.2%
67.0 16
 
0.2%
Other values (1977) 4451
44.5%
(Missing) 5334
53.3%
ValueCountFrequency (%)
0.0 7
0.1%
3.0 1
 
< 0.1%
3.12 1
 
< 0.1%
3.3 2
 
< 0.1%
3.97 1
 
< 0.1%
5.0 3
< 0.1%
5.51 1
 
< 0.1%
5.6 1
 
< 0.1%
5.96 1
 
< 0.1%
6.0 1
 
< 0.1%
ValueCountFrequency (%)
1862.21 3
< 0.1%
1302.26 3
< 0.1%
1075.66 5
0.1%
968.06 1
 
< 0.1%
955.28 4
< 0.1%
830.12 1
 
< 0.1%
827.16 1
 
< 0.1%
825.0 1
 
< 0.1%
824.13 3
< 0.1%
764.91 1
 
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9964 
직영
 
35
(조합)위탁
 
1

Length

Max length6
Median length4
Mean length3.9932
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> 9964
99.6%
직영 35
 
0.4%
(조합)위탁 1
 
< 0.1%

Length

2024-05-18T16:18:15.440426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:18:15.635345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9964
99.6%
직영 35
 
0.4%
조합)위탁 1
 
< 0.1%

Interactions

2024-05-18T16:17:54.307725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:46.830373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:48.586428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:50.067315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:51.625741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:52.946738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:54.486080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:47.094842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:48.859868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:50.279236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:51.872593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:53.205101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:54.679113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:47.368534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:49.144163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:50.545264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:52.106351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:53.465474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:54.908604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:47.633363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:49.449669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:50.800774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:52.326883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:53.633363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:55.182516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:48.049598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:49.686093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:51.083231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:52.495549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:53.850091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:55.453991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:48.301500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:49.880044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:51.346792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:52.696658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:17:54.092686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T16:18:15.764552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.0000.5590.3390.4890.9890.9840.3580.0981.000
교부번호0.5591.0000.3450.4840.5600.5660.1830.0630.000
업종명0.3390.3451.0001.0000.3270.3350.5110.397NaN
업태명0.4890.4841.0001.0000.4860.4790.7410.6911.000
지도점검일자0.9890.5600.3270.4861.0000.9770.3410.0811.000
위반일자0.9840.5660.3350.4790.9771.0000.4360.0920.830
처분기간0.3580.1830.5110.7410.3410.4361.0000.119NaN
영업장면적(㎡)0.0980.0630.3970.6910.0810.0920.1191.000NaN
운영형태1.0000.000NaN1.0001.0000.830NaNNaN1.000
2024-05-18T16:18:15.991437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영형태업종명
운영형태1.0001.000
업종명1.0001.000
2024-05-18T16:18:16.459852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.4770.9990.999-0.080-0.0850.1320.939
교부번호0.4771.0000.4780.477-0.032-0.0200.1580.000
지도점검일자0.9990.4781.0001.000-0.086-0.0860.1270.924
위반일자0.9990.4771.0001.000-0.083-0.0850.1300.594
처분기간-0.080-0.032-0.086-0.0831.000-0.0450.2370.000
영업장면적(㎡)-0.085-0.020-0.086-0.085-0.0451.0000.1781.000
업종명0.1320.1580.1270.1300.2370.1781.0001.000
운영형태0.9390.0000.9240.5940.0001.0001.0001.000

Missing values

2024-05-18T16:17:55.875705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T16:17:56.575999image/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.
2024-05-18T16:17:57.075553image/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
196732000002008052219990095069일반음식점기타정글북<NA>서울특별시 관악구 신림동 1640번지 1호 지하1층20060901처분확정영업정지식품위생법 제31조20060901청소년 주류제공영업정지0251.08<NA>
363432000002011092120020094190일반음식점경양식캠프데이비드<NA>서울특별시 관악구 신림동 1652번지 9호 지상1층20110725처분확정영업소폐쇄식품위생법 제37조20110725영업시설의 전부철거영업소폐쇄<NA><NA><NA>
594032000002014110720080094225일반음식점한식청양센타서울특별시 관악구 남부순환로161가길 51, (신림동,지상1층)서울특별시 관악구 신림동 512번지 2호 지상1층20140923처분확정시정명령식품위생법 제71조, 제72조 및 제75조201409232014.9.23.21:30경 관악구식품접객업소합동단속반점검시 곱창볶음에 벌레 등 이물혼입된 사실이 적발됨.시정명령<NA>52.88<NA>
506432000002021010420050094865일반음식점경양식무쏘 신림점1서울특별시 관악구 남부순환로 1600-7, (신림동,지상3층)서울특별시 관악구 신림동 1640번지 26호 지상3층20201109처분확정과태료부과법 제101조제2항제1호 및 영 제67조20201109조리실 위생 불량과태료부과<NA><NA><NA>
655132000002012120520100094267일반음식점한식왕십리 고 곱창<NA>서울특별시 관악구 신림동 241번지 111호 지상1층20120503처분확정과징금부과-15,600,000원식품위생법 제44조20120503청소년 주류제공과징금부과-15,600,000원<NA><NA><NA>
942632000002005121420030094131유흥주점영업룸살롱던힐<NA>서울특별시 관악구 신림동 1425번지 29호 지하1층20051106처분확정시정명령식품위생법 제25조20051106영업자 지위승계 미이행시정명령<NA>90.8<NA>
164832000002004030819980094587일반음식점분식냉천면옥<NA>서울특별시 관악구 신림동 727번지 13호20040114처분확정영업소폐쇄식품위생법제21조20040114무단폐업영업소폐쇄<NA>23.24<NA>
1224832000002010042020040094506건강기능식품일반판매업영업장판매앨트웰다단계<NA>서울특별시 관악구 봉천동 635번지 327호 평주빌라301호20100405처분확정과태료100만원부과(80만원사전납부완료)건강기능식품에 관한 법률 제6조3항20100405영업장 소재지 변경신고를 하지 아니하고 무단변경과태료100만원부과(80만원사전납부완료)<NA>25.0<NA>
112632000002015102719950094488일반음식점한식양평해장국서울특별시 관악구 봉천로 229, (봉천동,(972번지 3호))서울특별시 관악구 봉천동 972번지 4호 (972번지 3호)20150908처분확정시정명령법 제71조, 법 제72조 및 법 제75조20150908음식물 이물혼입시정명령<NA>67.47<NA>
776632000002016101920150094262일반음식점한식술한잔고기한판서울특별시 관악구 봉천로12길 39, 1층 125호 (신림동, 가야위드안)서울특별시 관악구 신림동 1426번지 7호20160922처분확정시정명령법 제71조 및 법 제75조20160922영업장외 영업시정명령<NA>41.8<NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
418132000002017120520030094530일반음식점분식김밥천국서울특별시 관악구 은천로 109, 1층 (봉천동)서울특별시 관악구 봉천동 495번지 1호20171107처분확정과태료부과법 제101조제2항 제1호20171107종업원 건강진단 미필과태료부과<NA><NA><NA>
783332000002017101620150094706일반음식점분식마뇨떡볶이서울특별시 관악구 신원로 35, 2층 (신림동)서울특별시 관악구 신림동 1638번지 1호20170915처분확정과태료부과법 제101조제2항제1호 및 영 제67조20170915조리장 청소불량과태료부과<NA><NA><NA>
557832000002012061220070094038일반음식점한식어슬렁<NA>서울특별시 관악구 신림동 1536번지 16호 지하1층20120427처분확정영업정지식품위생법 제44조 2항20120427청소년주류제공영업정지<NA>126.0<NA>
1026132000002008071420070094308단란주점단란주점구로준코노래주점<NA>서울특별시 관악구 신림동 1643번지 5호 태정빌딩2층20080617처분확정영업정지 갈음 과징금 부과, 시설개수명령식품위생법 제21조20080617영업장 중앙에 룸 설치, 객실 불투명 유리로 설치(2차)영업정지 갈음 과징금 부과, 시설개수명령0106.48<NA>
596532000002018091420080094225일반음식점한식청양센타서울특별시 관악구 조원로 129, 지하1층 B01호 (신림동)서울특별시 관악구 신림동 503번지 4호20180813처분확정과태료부과법 제101조제2항 제1호20180813종업원 건강진단 미필(2/6)과태료부과<NA>86.82<NA>
682332000002014040820110094198일반음식점통닭(치킨)MR.Lee<NA>서울특별시 관악구 봉천동 1542번지 48호20140213처분확정과태료200,000원부과식품위생법 제101조201402132013년도 일반음식점기존영업자 위생교육미수료과태료200,000원부과<NA><NA><NA>
1179332000002015120820070094732식품등 수입판매업식품등 수입판매업(주)유앤아이엔젤스서울특별시 관악구 남부순환로 1984, (봉천동,지상1층)서울특별시 관악구 봉천동 1654번지 4호 지상1층20150410처분확정과태료부과20만원법 제101조제1항제1호20150410실제측정값이 영양표시량 대비 허용오차범위를 넘음과태료부과20만원<NA><NA><NA>
1204432000002012020219940094880제과점영업제과점영업크라운베이커리<NA>서울특별시 관악구 신림동 517번지 1호20111208처분확정영업소폐쇄식품위생법 제37조20111208영업시설의 전부철거영업소폐쇄<NA><NA><NA>
464832000002007092820040094836일반음식점한식다사랑<NA>서울특별시 관악구 신림동 1422번지 5호 지상7층16호20070911처분확정과태료 60만원 부과식품위생법 제26조20070911건강진단미필(영업주 1명, 종업원 1명중 1명)과태료 60만원 부과<NA><NA><NA>
641332000002013042220090095131일반음식점한식빨간오뎅<NA>서울특별시 관악구 봉천동 1637번지 1호 지상1층20130408처분확정과태료부과식품위생법제40조20130408건강진단미필(영업주1명)과태료부과<NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
10932000002007120620070094102유흥주점영업고고(디스코)클럽골든벨중년나이트메들리<NA>서울특별시 관악구 신림동 529번지 4호 외 3필지(지하1층)20071108처분확정과태료30만원부과식품위생법26조,31조20071108종업원명부미비치,건강진단미필(3명중1명)과태료30만원부과<NA><NA><NA>6
11032000002007120620070094102유흥주점영업고고(디스코)클럽골든벨중년나이트메들리<NA>서울특별시 관악구 신림동 529번지 4호 외 3필지(지하1층)20071108처분확정시정명령식품위생법26조,31조20071108종업원명부미비치,건강진단미필(3명중1명)시정명령<NA><NA><NA>5
12432000002008121020050094740건강기능식품일반판매업영업장판매라온상사<NA>서울특별시 관악구 신림동 1459번지 20호20081114처분확정영업정지 1월(2008.12.11~2009.01.10)건강기능식품에 관한 법률 제18조20081114허위?과대의 표시광고 금지위반영업정지 1월(2008.12.11~2009.01.10)<NA><NA><NA>4
20832000002011112520010095215유흥주점영업룸살롱마농비너스<NA>서울특별시 관악구 신림동 1639번지 64호 지층120111101처분확정과태료부과(20만원)-2011. 11.18 자진납부식품위생법 제40조20111101건강진단미필(영업주 1명)과태료부과(20만원)-2011. 11.18 자진납부<NA><NA><NA>4
24032000002012121019980094725일반음식점한식낙성곱창<NA>서울특별시 관악구 봉천동 1661번지 7호20121114처분확정영업소폐쇄식품위생법 제37조20121114영업시설의 전부철거영업소폐쇄<NA>66.48<NA>4
31832000002017063020030094780일반음식점기타조개천하서울특별시 관악구 신림로 258, (신림동)서울특별시 관악구 신림동 808번지 372호20170530처분확정과태료부과법 제101조제2항제1호20170530건강진단미필과태료부과<NA><NA><NA>4
32032000002017063020030094780일반음식점기타조개천하서울특별시 관악구 신림로 258, (신림동)서울특별시 관악구 신림동 808번지 372호20170530처분확정과태료부과법 제71조, 법 제74조 및 법 제75조20170530영업장외 영업과태료부과<NA><NA><NA>4
32232000002017070320030094780일반음식점기타조개천하서울특별시 관악구 신림로 258, (신림동)서울특별시 관악구 신림동 808번지 372호20170530처분확정시정명령법 제101조제2항제1호20170530건강진단미필시정명령<NA><NA><NA>4
32332000002017070320030094780일반음식점기타조개천하서울특별시 관악구 신림로 258, (신림동)서울특별시 관악구 신림동 808번지 372호20170530처분확정시정명령법 제71조, 법 제74조 및 법 제75조20170530영업장외 영업시정명령<NA><NA><NA>4
832000002003061420010094048유흥주점영업룸살롱홍콩<NA>서울특별시 관악구 신림동 1513번지 2호20030612처분확정시정명령식품위생법제31조20030612종업원명부미비치시정명령<NA><NA><NA>3