Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells20581
Missing cells (%)11.4%
Duplicate rows135
Duplicate rows (%)1.4%
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-11297/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 135 (1.4%) duplicate rowsDuplicates
운영형태 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
업종명 is highly overall correlated with 운영형태High correlation
처분일자 is highly overall correlated with 교부번호 and 3 other fieldsHigh correlation
교부번호 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
업종명 is highly imbalanced (62.5%)Imbalance
운영형태 is highly imbalanced (99.4%)Imbalance
소재지도로명 has 6398 (64.0%) missing valuesMissing
처분기간 has 8379 (83.8%) missing valuesMissing
영업장면적(㎡) has 5751 (57.5%) missing valuesMissing
처분일자 is highly skewed (γ1 = 49.85357154)Skewed
지도점검일자 is highly skewed (γ1 = -78.49533092)Skewed
위반일자 is highly skewed (γ1 = -62.38326866)Skewed

Reproduction

Analysis started2024-05-17 23:56:41.623500
Analysis finished2024-05-17 23:57:05.814062
Duration24.19 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
3220000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 10000
100.0%

Length

2024-05-18T08:57:06.000686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:57:06.360353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct3906
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20090618
Minimum19840406
Maximum30031020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:57:06.801733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19840406
5-th percentile19970120
Q120040329
median20090416
Q320150623
95-th percentile20210604
Maximum30031020
Range10190614
Interquartile range (IQR)110294

Descriptive statistics

Standard deviation125359.27
Coefficient of variation (CV)0.0062396923
Kurtosis3953.648
Mean20090618
Median Absolute Deviation (MAD)59214
Skewness49.853572
Sum2.0090618 × 1011
Variance1.5714947 × 1010
MonotonicityNot monotonic
2024-05-18T08:57:07.257667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050201 407
 
4.1%
20070911 253
 
2.5%
20050131 102
 
1.0%
20170614 71
 
0.7%
20061229 57
 
0.6%
20201026 56
 
0.6%
20190318 38
 
0.4%
20220111 35
 
0.4%
20061222 35
 
0.4%
20190826 29
 
0.3%
Other values (3896) 8917
89.2%
ValueCountFrequency (%)
19840406 1
< 0.1%
19850418 1
< 0.1%
19860826 1
< 0.1%
19860926 1
< 0.1%
19861110 1
< 0.1%
19870101 1
< 0.1%
19870116 1
< 0.1%
19870427 1
< 0.1%
19870510 1
< 0.1%
19871110 1
< 0.1%
ValueCountFrequency (%)
30031020 1
 
< 0.1%
20240412 1
 
< 0.1%
20240409 1
 
< 0.1%
20240401 3
< 0.1%
20240329 1
 
< 0.1%
20240327 2
< 0.1%
20240325 2
< 0.1%
20240319 1
 
< 0.1%
20240315 3
< 0.1%
20240314 4
< 0.1%

교부번호
Real number (ℝ)

HIGH CORRELATION 

Distinct6192
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0008199 × 1010
Minimum1.8990105 × 1010
Maximum2.0230142 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:57:07.613005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8990105 × 1010
5-th percentile1.9860106 × 1010
Q11.9950105 × 1010
median2.0000107 × 1010
Q32.0070105 × 1010
95-th percentile2.0170106 × 1010
Maximum2.0230142 × 1010
Range1.2400365 × 109
Interquartile range (IQR)1.2000046 × 108

Descriptive statistics

Standard deviation89880765
Coefficient of variation (CV)0.0044921968
Kurtosis5.7302837
Mean2.0008199 × 1010
Median Absolute Deviation (MAD)59999807
Skewness-0.43933151
Sum2.0008199 × 1014
Variance8.078552 × 1015
MonotonicityNot monotonic
2024-05-18T08:57:08.023539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19860105824 30
 
0.3%
20000107033 23
 
0.2%
20030105326 21
 
0.2%
19870105022 16
 
0.2%
20050106251 15
 
0.1%
20110107311 15
 
0.1%
20070106434 14
 
0.1%
20170105481 13
 
0.1%
19950105296 13
 
0.1%
20000106551 13
 
0.1%
Other values (6182) 9827
98.3%
ValueCountFrequency (%)
18990105009 1
 
< 0.1%
18990105012 2
 
< 0.1%
19040105001 1
 
< 0.1%
19750105004 2
 
< 0.1%
19760105001 1
 
< 0.1%
19760105010 1
 
< 0.1%
19760105025 1
 
< 0.1%
19770105003 2
 
< 0.1%
19770105011 7
0.1%
19770105020 1
 
< 0.1%
ValueCountFrequency (%)
20230141556 1
< 0.1%
20230141291 1
< 0.1%
20230140535 2
< 0.1%
20230139056 1
< 0.1%
20230138487 2
< 0.1%
20230138302 1
< 0.1%
20230138086 1
< 0.1%
20230138010 1
< 0.1%
20230137552 1
< 0.1%
20230137034 1
< 0.1%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
6927 
유흥주점영업
1170 
단란주점
1065 
휴게음식점
 
192
건강기능식품일반판매업
 
144
Other values (15)
 
502

Length

Max length13
Median length5
Mean length5.2377
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row일반음식점
2nd row일반음식점
3rd row유흥주점영업
4th row단란주점
5th row휴게음식점

Common Values

ValueCountFrequency (%)
일반음식점 6927
69.3%
유흥주점영업 1170
 
11.7%
단란주점 1065
 
10.7%
휴게음식점 192
 
1.9%
건강기능식품일반판매업 144
 
1.4%
즉석판매제조가공업 130
 
1.3%
유통전문판매업 129
 
1.3%
식품제조가공업 122
 
1.2%
건강기능식품유통전문판매업 30
 
0.3%
식품등 수입판매업 26
 
0.3%
Other values (10) 65
 
0.7%

Length

2024-05-18T08:57:08.331067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 6927
69.1%
유흥주점영업 1170
 
11.7%
단란주점 1065
 
10.6%
휴게음식점 192
 
1.9%
건강기능식품일반판매업 144
 
1.4%
즉석판매제조가공업 130
 
1.3%
유통전문판매업 129
 
1.3%
식품제조가공업 122
 
1.2%
건강기능식품유통전문판매업 30
 
0.3%
수입판매업 26
 
0.3%
Other values (11) 91
 
0.9%

업태명
Text

Distinct69
Distinct (%)0.7%
Missing13
Missing (%)0.1%
Memory size156.2 KiB
2024-05-18T08:57:08.614479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.2652448
Min length2

Characters and Unicode

Total characters32610
Distinct characters144
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 row한식
2nd row경양식
3rd row룸살롱
4th row단란주점
5th row일반조리판매
ValueCountFrequency (%)
경양식 2789
27.8%
한식 2500
24.9%
단란주점 1065
 
10.6%
룸살롱 891
 
8.9%
분식 508
 
5.1%
일식 294
 
2.9%
기타 207
 
2.1%
중국식 192
 
1.9%
카바레 146
 
1.5%
즉석판매제조가공업 130
 
1.3%
Other values (60) 1319
13.1%
2024-05-18T08:57:09.285600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 6563
20.1%
경 2789
 
8.6%
양 2789
 
8.6%
한 2500
 
7.7%
점 1185
 
3.6%
주 1146
 
3.5%
단 1086
 
3.3%
란 1065
 
3.3%
살 904
 
2.8%
롱 904
 
2.8%
Other values (134) 11679
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31809
97.5%
Close Punctuation 282
 
0.9%
Open Punctuation 282
 
0.9%
Other Punctuation 183
 
0.6%
Space Separator 54
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 6563
20.6%
경 2789
 
8.8%
양 2789
 
8.8%
한 2500
 
7.9%
점 1185
 
3.7%
주 1146
 
3.6%
단 1086
 
3.4%
란 1065
 
3.3%
살 904
 
2.8%
롱 904
 
2.8%
Other values (129) 10878
34.2%
Other Punctuation
ValueCountFrequency (%)
/ 172
94.0%
, 11
 
6.0%
Close Punctuation
ValueCountFrequency (%)
) 282
100.0%
Open Punctuation
ValueCountFrequency (%)
( 282
100.0%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31809
97.5%
Common 801
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 6563
20.6%
경 2789
 
8.8%
양 2789
 
8.8%
한 2500
 
7.9%
점 1185
 
3.7%
주 1146
 
3.6%
단 1086
 
3.4%
란 1065
 
3.3%
살 904
 
2.8%
롱 904
 
2.8%
Other values (129) 10878
34.2%
Common
ValueCountFrequency (%)
) 282
35.2%
( 282
35.2%
/ 172
21.5%
54
 
6.7%
, 11
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31809
97.5%
ASCII 801
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 6563
20.6%
경 2789
 
8.8%
양 2789
 
8.8%
한 2500
 
7.9%
점 1185
 
3.7%
주 1146
 
3.6%
단 1086
 
3.4%
란 1065
 
3.3%
살 904
 
2.8%
롱 904
 
2.8%
Other values (129) 10878
34.2%
ASCII
ValueCountFrequency (%)
) 282
35.2%
( 282
35.2%
/ 172
21.5%
54
 
6.7%
, 11
 
1.4%

업소명
Text

Distinct5907
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:57:09.960078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length4.3937
Min length1

Characters and Unicode

Total characters43937
Distinct characters995
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4083 ?
Unique (%)40.8%

Sample

1st row이오
2nd row삐아제
3rd row클럽에스
4th row비젼
5th row커피스튜디오
ValueCountFrequency (%)
주식회사 38
 
0.3%
엠 29
 
0.3%
앤 27
 
0.2%
노래바 25
 
0.2%
파티 20
 
0.2%
필 20
 
0.2%
비스트로 19
 
0.2%
센스 19
 
0.2%
18
 
0.2%
lounge 18
 
0.2%
Other values (6165) 10642
97.9%
2024-05-18T08:57:11.231914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 1445
 
3.3%
이 1366
 
3.1%
881
 
2.0%
리 863
 
2.0%
) 779
 
1.8%
( 773
 
1.8%
라 663
 
1.5%
주 652
 
1.5%
아 589
 
1.3%
비 507
 
1.2%
Other values (985) 35419
80.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39193
89.2%
Uppercase Letter 1015
 
2.3%
Space Separator 881
 
2.0%
Close Punctuation 779
 
1.8%
Open Punctuation 773
 
1.8%
Lowercase Letter 741
 
1.7%
Decimal Number 468
 
1.1%
Other Punctuation 80
 
0.2%
Letter Number 4
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1445
 
3.7%
이 1366
 
3.5%
리 863
 
2.2%
라 663
 
1.7%
주 652
 
1.7%
아 589
 
1.5%
비 507
 
1.3%
점 473
 
1.2%
지 427
 
1.1%
마 422
 
1.1%
Other values (910) 31786
81.1%
Uppercase Letter
ValueCountFrequency (%)
E 83
 
8.2%
O 71
 
7.0%
S 68
 
6.7%
B 67
 
6.6%
I 62
 
6.1%
L 61
 
6.0%
A 60
 
5.9%
G 58
 
5.7%
W 47
 
4.6%
R 43
 
4.2%
Other values (16) 395
38.9%
Lowercase Letter
ValueCountFrequency (%)
e 83
11.2%
i 73
9.9%
o 73
9.9%
a 68
9.2%
n 55
 
7.4%
r 52
 
7.0%
t 52
 
7.0%
u 47
 
6.3%
s 45
 
6.1%
l 41
 
5.5%
Other values (15) 152
20.5%
Decimal Number
ValueCountFrequency (%)
2 101
21.6%
1 84
17.9%
0 60
12.8%
3 49
10.5%
4 40
 
8.5%
5 38
 
8.1%
9 30
 
6.4%
7 26
 
5.6%
8 26
 
5.6%
6 14
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 29
36.2%
& 21
26.2%
？ 8
 
10.0%
' 7
 
8.8%
, 7
 
8.8%
? 6
 
7.5%
: 1
 
1.2%
; 1
 
1.2%
Letter Number
ValueCountFrequency (%)
Ⅰ 3
75.0%
Ⅱ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
881
100.0%
Close Punctuation
ValueCountFrequency (%)
) 779
100.0%
Open Punctuation
ValueCountFrequency (%)
( 773
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39190
89.2%
Common 2984
 
6.8%
Latin 1760
 
4.0%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1445
 
3.7%
이 1366
 
3.5%
리 863
 
2.2%
라 663
 
1.7%
주 652
 
1.7%
아 589
 
1.5%
비 507
 
1.3%
점 473
 
1.2%
지 427
 
1.1%
마 422
 
1.1%
Other values (907) 31783
81.1%
Latin
ValueCountFrequency (%)
e 83
 
4.7%
E 83
 
4.7%
i 73
 
4.1%
o 73
 
4.1%
O 71
 
4.0%
S 68
 
3.9%
a 68
 
3.9%
B 67
 
3.8%
I 62
 
3.5%
L 61
 
3.5%
Other values (43) 1051
59.7%
Common
ValueCountFrequency (%)
881
29.5%
) 779
26.1%
( 773
25.9%
2 101
 
3.4%
1 84
 
2.8%
0 60
 
2.0%
3 49
 
1.6%
4 40
 
1.3%
5 38
 
1.3%
9 30
 
1.0%
Other values (12) 149
 
5.0%
Han
ValueCountFrequency (%)
味 1
33.3%
酒 1
33.3%
里 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39190
89.2%
ASCII 4732
 
10.8%
None 8
 
< 0.1%
Number Forms 4
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 1445
 
3.7%
이 1366
 
3.5%
리 863
 
2.2%
라 663
 
1.7%
주 652
 
1.7%
아 589
 
1.5%
비 507
 
1.3%
점 473
 
1.2%
지 427
 
1.1%
마 422
 
1.1%
Other values (907) 31783
81.1%
ASCII
ValueCountFrequency (%)
881
18.6%
) 779
16.5%
( 773
16.3%
2 101
 
2.1%
1 84
 
1.8%
e 83
 
1.8%
E 83
 
1.8%
i 73
 
1.5%
o 73
 
1.5%
O 71
 
1.5%
Other values (62) 1731
36.6%
None
ValueCountFrequency (%)
？ 8
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 3
75.0%
Ⅱ 1
 
25.0%
CJK
ValueCountFrequency (%)
味 1
33.3%
酒 1
33.3%
里 1
33.3%

소재지도로명
Text

MISSING 

Distinct2195
Distinct (%)60.9%
Missing6398
Missing (%)64.0%
Memory size156.2 KiB
2024-05-18T08:57:11.722253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length56
Mean length32.137146
Min length24

Characters and Unicode

Total characters115758
Distinct characters359
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1566 ?
Unique (%)43.5%

Sample

1st row서울특별시 강남구 강남대로102길 32, 지하1,지하2층 (역삼동)
2nd row서울특별시 강남구 언주로134길 15, (논현동,지상1층)
3rd row서울특별시 강남구 봉은사로29길 8, 지하1층 (논현동)
4th row서울특별시 강남구 강남대로66길 14, 1층 105호 (역삼동, 강남역와이즈플레이스)
5th row서울특별시 강남구 영동대로 704, (청담동)
ValueCountFrequency (%)
서울특별시 3602
 
17.3%
강남구 3602
 
17.3%
지하1층 666
 
3.2%
역삼동 625
 
3.0%
논현동 506
 
2.4%
신사동 397
 
1.9%
지상1층 296
 
1.4%
청담동 247
 
1.2%
도산대로 213
 
1.0%
삼성동 196
 
0.9%
Other values (1885) 10435
50.2%
2024-05-18T08:57:12.754912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17185
 
14.8%
1 5903
 
5.1%
, 5561
 
4.8%
남 4018
 
3.5%
강 3972
 
3.4%
동 3942
 
3.4%
구 3794
 
3.3%
서 3642
 
3.1%
) 3633
 
3.1%
( 3633
 
3.1%
Other values (349) 60475
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66577
57.5%
Decimal Number 18639
 
16.1%
Space Separator 17185
 
14.8%
Other Punctuation 5599
 
4.8%
Close Punctuation 3633
 
3.1%
Open Punctuation 3633
 
3.1%
Dash Punctuation 281
 
0.2%
Uppercase Letter 163
 
0.1%
Math Symbol 36
 
< 0.1%
Lowercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 4018
 
6.0%
강 3972
 
6.0%
동 3942
 
5.9%
구 3794
 
5.7%
서 3642
 
5.5%
시 3623
 
5.4%
로 3617
 
5.4%
울 3609
 
5.4%
별 3605
 
5.4%
특 3602
 
5.4%
Other values (305) 29153
43.8%
Uppercase Letter
ValueCountFrequency (%)
B 73
44.8%
A 20
 
12.3%
S 12
 
7.4%
L 8
 
4.9%
G 8
 
4.9%
K 7
 
4.3%
E 6
 
3.7%
F 5
 
3.1%
J 4
 
2.5%
H 4
 
2.5%
Other values (8) 16
 
9.8%
Decimal Number
ValueCountFrequency (%)
1 5903
31.7%
2 2527
13.6%
3 1841
 
9.9%
5 1513
 
8.1%
4 1420
 
7.6%
0 1283
 
6.9%
6 1166
 
6.3%
7 1135
 
6.1%
8 1040
 
5.6%
9 811
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
k 2
16.7%
l 2
16.7%
a 2
16.7%
o 2
16.7%
n 1
8.3%
s 1
8.3%
b 1
8.3%
m 1
8.3%
Other Punctuation
ValueCountFrequency (%)
, 5561
99.3%
. 37
 
0.7%
？ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
17185
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3633
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3633
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 281
100.0%
Math Symbol
ValueCountFrequency (%)
~ 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66575
57.5%
Common 49006
42.3%
Latin 175
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 4018
 
6.0%
강 3972
 
6.0%
동 3942
 
5.9%
구 3794
 
5.7%
서 3642
 
5.5%
시 3623
 
5.4%
로 3617
 
5.4%
울 3609
 
5.4%
별 3605
 
5.4%
특 3602
 
5.4%
Other values (303) 29151
43.8%
Latin
ValueCountFrequency (%)
B 73
41.7%
A 20
 
11.4%
S 12
 
6.9%
L 8
 
4.6%
G 8
 
4.6%
K 7
 
4.0%
E 6
 
3.4%
F 5
 
2.9%
J 4
 
2.3%
H 4
 
2.3%
Other values (16) 28
 
16.0%
Common
ValueCountFrequency (%)
17185
35.1%
1 5903
 
12.0%
, 5561
 
11.3%
) 3633
 
7.4%
( 3633
 
7.4%
2 2527
 
5.2%
3 1841
 
3.8%
5 1513
 
3.1%
4 1420
 
2.9%
0 1283
 
2.6%
Other values (8) 4507
 
9.2%
Han
ValueCountFrequency (%)
奉 1
50.0%
錦 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66575
57.5%
ASCII 49180
42.5%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17185
34.9%
1 5903
 
12.0%
, 5561
 
11.3%
) 3633
 
7.4%
( 3633
 
7.4%
2 2527
 
5.1%
3 1841
 
3.7%
5 1513
 
3.1%
4 1420
 
2.9%
0 1283
 
2.6%
Other values (33) 4681
 
9.5%
Hangul
ValueCountFrequency (%)
남 4018
 
6.0%
강 3972
 
6.0%
동 3942
 
5.9%
구 3794
 
5.7%
서 3642
 
5.5%
시 3623
 
5.4%
로 3617
 
5.4%
울 3609
 
5.4%
별 3605
 
5.4%
특 3602
 
5.4%
Other values (303) 29151
43.8%
CJK
ValueCountFrequency (%)
奉 1
50.0%
錦 1
50.0%
None
ValueCountFrequency (%)
？ 1
100.0%

소재지지번
Text

Distinct5574
Distinct (%)55.8%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-18T08:57:13.408919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length56
Mean length28.205462
Min length20

Characters and Unicode

Total characters281970
Distinct characters410
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3638 ?
Unique (%)36.4%

Sample

1st row서울특별시 강남구 신사동 511번지 6호
2nd row서울특별시 강남구 신사동 582번지 1호 지하2층
3rd row서울특별시 강남구 역삼동 831번지 30호 지하1층
4th row서울특별시 강남구 역삼동 817번지 8호
5th row서울특별시 강남구 역삼동 618번지 15호 지하1층,지하2층
ValueCountFrequency (%)
서울특별시 9997
18.0%
강남구 9997
18.0%
역삼동 2532
 
4.6%
논현동 2052
 
3.7%
지하1층 1571
 
2.8%
신사동 1556
 
2.8%
삼성동 1051
 
1.9%
대치동 952
 
1.7%
청담동 944
 
1.7%
0호 871
 
1.6%
Other values (2108) 23988
43.2%
2024-05-18T08:57:14.671059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70319
24.9%
지 14200
 
5.0%
1 12903
 
4.6%
호 10224
 
3.6%
동 10115
 
3.6%
구 10113
 
3.6%
서 10103
 
3.6%
남 10060
 
3.6%
강 10047
 
3.6%
시 10031
 
3.6%
Other values (400) 113855
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159190
56.5%
Space Separator 70319
24.9%
Decimal Number 50746
 
18.0%
Other Punctuation 887
 
0.3%
Dash Punctuation 224
 
0.1%
Open Punctuation 183
 
0.1%
Close Punctuation 174
 
0.1%
Uppercase Letter 170
 
0.1%
Math Symbol 56
 
< 0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 14200
 
8.9%
호 10224
 
6.4%
동 10115
 
6.4%
구 10113
 
6.4%
서 10103
 
6.3%
남 10060
 
6.3%
강 10047
 
6.3%
시 10031
 
6.3%
번 10011
 
6.3%
울 10010
 
6.3%
Other values (352) 54276
34.1%
Uppercase Letter
ValueCountFrequency (%)
B 57
33.5%
A 30
17.6%
L 13
 
7.6%
S 9
 
5.3%
K 8
 
4.7%
C 8
 
4.7%
D 7
 
4.1%
F 7
 
4.1%
G 6
 
3.5%
T 5
 
2.9%
Other values (9) 20
 
11.8%
Decimal Number
ValueCountFrequency (%)
1 12903
25.4%
2 6551
12.9%
6 5017
 
9.9%
3 4121
 
8.1%
5 3954
 
7.8%
0 3813
 
7.5%
4 3739
 
7.4%
8 3731
 
7.4%
7 3667
 
7.2%
9 3250
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
a 3
20.0%
l 2
13.3%
o 2
13.3%
b 2
13.3%
k 2
13.3%
m 1
 
6.7%
n 1
 
6.7%
s 1
 
6.7%
e 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 719
81.1%
. 164
 
18.5%
/ 4
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 55
98.2%
> 1
 
1.8%
Space Separator
ValueCountFrequency (%)
70319
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 224
100.0%
Open Punctuation
ValueCountFrequency (%)
( 183
100.0%
Close Punctuation
ValueCountFrequency (%)
) 174
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159188
56.5%
Common 122595
43.5%
Latin 185
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 14200
 
8.9%
호 10224
 
6.4%
동 10115
 
6.4%
구 10113
 
6.4%
서 10103
 
6.3%
남 10060
 
6.3%
강 10047
 
6.3%
시 10031
 
6.3%
번 10011
 
6.3%
울 10010
 
6.3%
Other values (350) 54274
34.1%
Latin
ValueCountFrequency (%)
B 57
30.8%
A 30
16.2%
L 13
 
7.0%
S 9
 
4.9%
K 8
 
4.3%
C 8
 
4.3%
D 7
 
3.8%
F 7
 
3.8%
G 6
 
3.2%
T 5
 
2.7%
Other values (18) 35
18.9%
Common
ValueCountFrequency (%)
70319
57.4%
1 12903
 
10.5%
2 6551
 
5.3%
6 5017
 
4.1%
3 4121
 
3.4%
5 3954
 
3.2%
0 3813
 
3.1%
4 3739
 
3.0%
8 3731
 
3.0%
7 3667
 
3.0%
Other values (10) 4780
 
3.9%
Han
ValueCountFrequency (%)
奉 1
50.0%
錦 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159187
56.5%
ASCII 122780
43.5%
CJK 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70319
57.3%
1 12903
 
10.5%
2 6551
 
5.3%
6 5017
 
4.1%
3 4121
 
3.4%
5 3954
 
3.2%
0 3813
 
3.1%
4 3739
 
3.0%
8 3731
 
3.0%
7 3667
 
3.0%
Other values (38) 4965
 
4.0%
Hangul
ValueCountFrequency (%)
지 14200
 
8.9%
호 10224
 
6.4%
동 10115
 
6.4%
구 10113
 
6.4%
서 10103
 
6.3%
남 10060
 
6.3%
강 10047
 
6.3%
시 10031
 
6.3%
번 10011
 
6.3%
울 10010
 
6.3%
Other values (349) 54273
34.1%
CJK
ValueCountFrequency (%)
奉 1
50.0%
錦 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4185
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20085891
Minimum2005011
Maximum20240306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:57:15.116977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005011
5-th percentile19961209
Q120040204
median20090115
Q320150318
95-th percentile20201127
Maximum20240306
Range18235295
Interquartile range (IQR)110114

Descriptive statistics

Standard deviation196025.79
Coefficient of variation (CV)0.0097593774
Kurtosis7240.2309
Mean20085891
Median Absolute Deviation (MAD)58909
Skewness-78.495331
Sum2.0085891 × 1011
Variance3.842611 × 1010
MonotonicityNot monotonic
2024-05-18T08:57:15.641690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050113 505
 
5.1%
20070911 156
 
1.6%
20200101 83
 
0.8%
20070912 73
 
0.7%
20161231 71
 
0.7%
20210101 70
 
0.7%
20061212 62
 
0.6%
20190101 55
 
0.5%
20210401 36
 
0.4%
20050831 30
 
0.3%
Other values (4175) 8859
88.6%
ValueCountFrequency (%)
2005011 1
< 0.1%
19840306 1
< 0.1%
19850318 1
< 0.1%
19860726 1
< 0.1%
19860826 1
< 0.1%
19861010 1
< 0.1%
19861201 1
< 0.1%
19861216 1
< 0.1%
19870327 1
< 0.1%
19870410 1
< 0.1%
ValueCountFrequency (%)
20240306 1
 
< 0.1%
20240305 1
 
< 0.1%
20240223 2
 
< 0.1%
20240205 1
 
< 0.1%
20240201 2
 
< 0.1%
20240130 1
 
< 0.1%
20240126 1
 
< 0.1%
20240109 2
 
< 0.1%
20240107 1
 
< 0.1%
20240101 12
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

2024-05-18T08:57:16.081179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:57:16.361578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%

처분명
Text

Distinct5494
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:57:16.948646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length180
Median length125
Mean length20.482
Min length2

Characters and Unicode

Total characters204820
Distinct characters325
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4468 ?
Unique (%)44.7%

Sample

1st row강남서유선통보
2nd row과태료 50만원부과
3rd row영업허가취소(09.08.21자)
4th row영업정지3월(2000.4.24-7.23)
5th row시정명령(즉시시정후 2013.9.2까지)
ValueCountFrequency (%)
영업소폐쇄 728
 
4.2%
영업정지 655
 
3.8%
시정명령 525
 
3.0%
및 403
 
2.3%
과징금 372
 
2.1%
갈음 353
 
2.0%
과태료 346
 
2.0%
자진납부 335
 
1.9%
과태료부과 282
 
1.6%
영업소폐쇄(07.9.11일자 248
 
1.4%
Other values (6632) 13161
75.6%
2024-05-18T08:57:18.177982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17681
 
8.6%
. 17040
 
8.3%
1 16334
 
8.0%
2 12282
 
6.0%
( 7613
 
3.7%
) 7606
 
3.7%
7434
 
3.6%
정 6124
 
3.0%
업 6001
 
2.9%
영 5888
 
2.9%
Other values (315) 100817
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90125
44.0%
Decimal Number 69327
33.8%
Other Punctuation 19602
 
9.6%
Open Punctuation 7629
 
3.7%
Close Punctuation 7621
 
3.7%
Space Separator 7434
 
3.6%
Math Symbol 2149
 
1.0%
Dash Punctuation 879
 
0.4%
Modifier Symbol 17
 
< 0.1%
Lowercase Letter 17
 
< 0.1%
Other values (3) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 6124
 
6.8%
업 6001
 
6.7%
영 5888
 
6.5%
지 5729
 
6.4%
과 5340
 
5.9%
원 4072
 
4.5%
시 3801
 
4.2%
만 3606
 
4.0%
명 3149
 
3.5%
령 3126
 
3.5%
Other values (267) 43289
48.0%
Decimal Number
ValueCountFrequency (%)
0 17681
25.5%
1 16334
23.6%
2 12282
17.7%
5 4146
 
6.0%
3 4127
 
6.0%
9 3433
 
5.0%
7 3115
 
4.5%
4 2851
 
4.1%
6 2694
 
3.9%
8 2664
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 17040
86.9%
, 1812
 
9.2%
: 269
 
1.4%
/ 196
 
1.0%
※ 171
 
0.9%
% 91
 
0.5%
' 13
 
0.1%
* 7
 
< 0.1%
; 2
 
< 0.1%
＊ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
l 4
23.5%
r 2
11.8%
t 2
11.8%
w 2
11.8%
d 2
11.8%
m 1
 
5.9%
x 1
 
5.9%
h 1
 
5.9%
u 1
 
5.9%
j 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
~ 1832
85.2%
→ 277
 
12.9%
+ 23
 
1.1%
× 8
 
0.4%
> 8
 
0.4%
= 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7613
99.8%
[ 16
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 7606
99.8%
] 15
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
O 2
50.0%
N 2
50.0%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
7434
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 879
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 114674
56.0%
Hangul 90125
44.0%
Latin 21
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 6124
 
6.8%
업 6001
 
6.7%
영 5888
 
6.5%
지 5729
 
6.4%
과 5340
 
5.9%
원 4072
 
4.5%
시 3801
 
4.2%
만 3606
 
4.0%
명 3149
 
3.5%
령 3126
 
3.5%
Other values (267) 43289
48.0%
Common
ValueCountFrequency (%)
0 17681
15.4%
. 17040
14.9%
1 16334
14.2%
2 12282
10.7%
( 7613
6.6%
) 7606
6.6%
7434
6.5%
5 4146
 
3.6%
3 4127
 
3.6%
9 3433
 
3.0%
Other values (26) 16978
14.8%
Latin
ValueCountFrequency (%)
l 4
19.0%
r 2
9.5%
t 2
9.5%
w 2
9.5%
d 2
9.5%
O 2
9.5%
N 2
9.5%
m 1
 
4.8%
x 1
 
4.8%
h 1
 
4.8%
Other values (2) 2
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114236
55.8%
Hangul 90115
44.0%
Arrows 277
 
0.1%
Punctuation 171
 
0.1%
Compat Jamo 10
 
< 0.1%
None 9
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17681
15.5%
. 17040
14.9%
1 16334
14.3%
2 12282
10.8%
( 7613
6.7%
) 7606
6.7%
7434
6.5%
5 4146
 
3.6%
3 4127
 
3.6%
9 3433
 
3.0%
Other values (32) 16540
14.5%
Hangul
ValueCountFrequency (%)
정 6124
 
6.8%
업 6001
 
6.7%
영 5888
 
6.5%
지 5729
 
6.4%
과 5340
 
5.9%
원 4072
 
4.5%
시 3801
 
4.2%
만 3606
 
4.0%
명 3149
 
3.5%
령 3126
 
3.5%
Other values (264) 43279
48.0%
Arrows
ValueCountFrequency (%)
→ 277
100.0%
Punctuation
ValueCountFrequency (%)
※ 171
100.0%
None
ValueCountFrequency (%)
× 8
88.9%
＊ 1
 
11.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
80.0%
ㅘ 1
 
10.0%
ㅈ 1
 
10.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

법적근거
Text

Distinct515
Distinct (%)5.2%
Missing37
Missing (%)0.4%
Memory size156.2 KiB
2024-05-18T08:57:18.833002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length10.215999
Min length1

Characters and Unicode

Total characters101782
Distinct characters116
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)3.1%

Sample

1st row식품위생법
2nd row식품위생법 제78조
3rd row식품위생법
4th row식품위생법
5th row식품위생법 제71조 및 제75조
ValueCountFrequency (%)
식품위생법 6489
27.6%
법 4927
20.9%
및 2008
 
8.5%
제75조 1993
 
8.5%
제71조 1704
 
7.2%
제58조 1329
 
5.6%
제74조 1002
 
4.3%
제101조제2항제1호 387
 
1.6%
58조 243
 
1.0%
제55조 178
 
0.8%
Other values (427) 3274
13.9%
2024-05-18T08:57:20.402908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13625
13.4%
법 11944
11.7%
제 10516
10.3%
조 9500
9.3%
위 6958
 
6.8%
식 6957
 
6.8%
품 6896
 
6.8%
생 6861
 
6.7%
7 5719
 
5.6%
1 4832
 
4.7%
Other values (106) 17974
17.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64517
63.4%
Decimal Number 22173
 
21.8%
Space Separator 13625
 
13.4%
Other Punctuation 1447
 
1.4%
Dash Punctuation 11
 
< 0.1%
Uppercase Letter 5
 
< 0.1%
Math Symbol 2
 
< 0.1%
Modifier Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
법 11944
18.5%
제 10516
16.3%
조 9500
14.7%
위 6958
10.8%
식 6957
10.8%
품 6896
10.7%
생 6861
10.6%
및 2009
 
3.1%
항 887
 
1.4%
호 758
 
1.2%
Other values (84) 1231
 
1.9%
Decimal Number
ValueCountFrequency (%)
7 5719
25.8%
1 4832
21.8%
5 4721
21.3%
8 2172
 
9.8%
2 1449
 
6.5%
4 1435
 
6.5%
0 855
 
3.9%
6 495
 
2.2%
3 451
 
2.0%
9 44
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1437
99.3%
. 6
 
0.4%
? 3
 
0.2%
; 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
F 2
40.0%
D 1
20.0%
K 1
20.0%
S 1
20.0%
Space Separator
ValueCountFrequency (%)
13625
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64517
63.4%
Common 37260
36.6%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
법 11944
18.5%
제 10516
16.3%
조 9500
14.7%
위 6958
10.8%
식 6957
10.8%
품 6896
10.7%
생 6861
10.6%
및 2009
 
3.1%
항 887
 
1.4%
호 758
 
1.2%
Other values (84) 1231
 
1.9%
Common
ValueCountFrequency (%)
13625
36.6%
7 5719
15.3%
1 4832
 
13.0%
5 4721
 
12.7%
8 2172
 
5.8%
2 1449
 
3.9%
, 1437
 
3.9%
4 1435
 
3.9%
0 855
 
2.3%
6 495
 
1.3%
Other values (8) 520
 
1.4%
Latin
ValueCountFrequency (%)
F 2
40.0%
D 1
20.0%
K 1
20.0%
S 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64517
63.4%
ASCII 37265
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13625
36.6%
7 5719
15.3%
1 4832
 
13.0%
5 4721
 
12.7%
8 2172
 
5.8%
2 1449
 
3.9%
, 1437
 
3.9%
4 1435
 
3.9%
0 855
 
2.3%
6 495
 
1.3%
Other values (12) 525
 
1.4%
Hangul
ValueCountFrequency (%)
법 11944
18.5%
제 10516
16.3%
조 9500
14.7%
위 6958
10.8%
식 6957
10.8%
품 6896
10.7%
생 6861
10.6%
및 2009
 
3.1%
항 887
 
1.4%
호 758
 
1.2%
Other values (84) 1231
 
1.9%

위반일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4290
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20084268
Minimum1990127
Maximum20240306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:57:21.024963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1990127
5-th percentile19970114
Q120040206
median20090129
Q320150326
95-th percentile20201127
Maximum20240306
Range18250179
Interquartile range (IQR)110120.5

Descriptive statistics

Standard deviation266753.67
Coefficient of variation (CV)0.013281723
Kurtosis4229.1961
Mean20084268
Median Absolute Deviation (MAD)58923
Skewness-62.383269
Sum2.0084268 × 1011
Variance7.1157519 × 1010
MonotonicityNot monotonic
2024-05-18T08:57:21.659187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050113 503
 
5.0%
20070910 152
 
1.5%
20070911 101
 
1.0%
20190101 79
 
0.8%
20200101 77
 
0.8%
20161231 71
 
0.7%
20210101 64
 
0.6%
20061212 62
 
0.6%
20210401 42
 
0.4%
20050831 30
 
0.3%
Other values (4280) 8819
88.2%
ValueCountFrequency (%)
1990127 1
< 0.1%
2000126 1
< 0.1%
19840306 1
< 0.1%
19850318 1
< 0.1%
19860726 1
< 0.1%
19860826 1
< 0.1%
19861010 1
< 0.1%
19861201 1
< 0.1%
19861216 1
< 0.1%
19870327 1
< 0.1%
ValueCountFrequency (%)
20240306 1
 
< 0.1%
20240305 1
 
< 0.1%
20240223 2
 
< 0.1%
20240205 1
 
< 0.1%
20240201 2
 
< 0.1%
20240131 1
 
< 0.1%
20240126 1
 
< 0.1%
20240109 1
 
< 0.1%
20240107 1
 
< 0.1%
20240101 12
0.1%

위반내용
Text

Distinct3975
Distinct (%)39.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:57:22.567626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length238
Median length115
Mean length14.8859
Min length2

Characters and Unicode

Total characters148859
Distinct characters671
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

Unique2989 ?
Unique (%)29.9%

Sample

1st row시간외영업(01:30)
2nd row건강진단미필(종업원2/3)
3rd row09.07.21 건축물 신축으로 기존 시설물 전부 멸실
4th row유흥접객부고용.유흥주점형태영업
5th row영업장외 테이블 영업
ValueCountFrequency (%)
및 863
 
3.2%
무단폐업 852
 
3.2%
미필 489
 
1.8%
시설물멸실 482
 
1.8%
설치 464
 
1.7%
영업장 381
 
1.4%
위생교육 370
 
1.4%
유흥접객원고용 359
 
1.3%
멸실 342
 
1.3%
종업원 329
 
1.2%
Other values (4762) 22053
81.7%
2024-05-18T08:57:24.007515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17305
 
11.6%
업 5852
 
3.9%
영 3547
 
2.4%
미 3260
 
2.2%
설 3252
 
2.2%
단 2636
 
1.8%
시 2531
 
1.7%
( 2474
 
1.7%
) 2474
 
1.7%
고 2379
 
1.6%
Other values (661) 103149
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115667
77.7%
Space Separator 17305
 
11.6%
Decimal Number 7353
 
4.9%
Other Punctuation 3109
 
2.1%
Open Punctuation 2481
 
1.7%
Close Punctuation 2480
 
1.7%
Dash Punctuation 188
 
0.1%
Uppercase Letter 127
 
0.1%
Lowercase Letter 50
 
< 0.1%
Math Symbol 44
 
< 0.1%
Other values (5) 55
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 5852
 
5.1%
영 3547
 
3.1%
미 3260
 
2.8%
설 3252
 
2.8%
단 2636
 
2.3%
시 2531
 
2.2%
고 2379
 
2.1%
기 2368
 
2.0%
장 2127
 
1.8%
치 2045
 
1.8%
Other values (582) 85670
74.1%
Uppercase Letter
ValueCountFrequency (%)
A 16
12.6%
R 14
11.0%
C 13
10.2%
S 11
8.7%
H 10
7.9%
I 10
7.9%
N 8
 
6.3%
D 8
 
6.3%
E 8
 
6.3%
G 7
 
5.5%
Other values (10) 22
17.3%
Lowercase Letter
ValueCountFrequency (%)
g 18
36.0%
m 9
18.0%
o 5
 
10.0%
b 4
 
8.0%
e 3
 
6.0%
l 3
 
6.0%
d 2
 
4.0%
a 2
 
4.0%
r 1
 
2.0%
n 1
 
2.0%
Other values (2) 2
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 1264
40.7%
/ 842
27.1%
. 818
26.3%
: 87
 
2.8%
? 67
 
2.2%
' 8
 
0.3%
* 7
 
0.2%
% 5
 
0.2%
; 5
 
0.2%
？ 4
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 1800
24.5%
2 1729
23.5%
0 1154
15.7%
3 633
 
8.6%
6 440
 
6.0%
9 409
 
5.6%
4 400
 
5.4%
8 295
 
4.0%
5 293
 
4.0%
7 200
 
2.7%
Math Symbol
ValueCountFrequency (%)
> 15
34.1%
~ 11
25.0%
+ 8
18.2%
= 5
 
11.4%
< 3
 
6.8%
→ 2
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 2474
99.7%
[ 4
 
0.2%
「 2
 
0.1%
【 1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
㎡ 24
88.9%
♧ 1
 
3.7%
┛ 1
 
3.7%
℃ 1
 
3.7%
Close Punctuation
ValueCountFrequency (%)
) 2474
99.8%
] 4
 
0.2%
」 2
 
0.1%
Other Number
ValueCountFrequency (%)
① 8
80.0%
② 2
 
20.0%
Final Punctuation
ValueCountFrequency (%)
” 4
66.7%
’ 2
33.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
50.0%
“ 2
50.0%
Space Separator
ValueCountFrequency (%)
17305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115664
77.7%
Common 33015
 
22.2%
Latin 177
 
0.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 5852
 
5.1%
영 3547
 
3.1%
미 3260
 
2.8%
설 3252
 
2.8%
단 2636
 
2.3%
시 2531
 
2.2%
고 2379
 
2.1%
기 2368
 
2.0%
장 2127
 
1.8%
치 2045
 
1.8%
Other values (579) 85667
74.1%
Common
ValueCountFrequency (%)
17305
52.4%
( 2474
 
7.5%
) 2474
 
7.5%
1 1800
 
5.5%
2 1729
 
5.2%
, 1264
 
3.8%
0 1154
 
3.5%
/ 842
 
2.6%
. 818
 
2.5%
3 633
 
1.9%
Other values (37) 2522
 
7.6%
Latin
ValueCountFrequency (%)
g 18
 
10.2%
A 16
 
9.0%
R 14
 
7.9%
C 13
 
7.3%
S 11
 
6.2%
H 10
 
5.6%
I 10
 
5.6%
m 9
 
5.1%
N 8
 
4.5%
D 8
 
4.5%
Other values (22) 60
33.9%
Han
ValueCountFrequency (%)
河 1
33.3%
囹 1
33.3%
憫 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115663
77.7%
ASCII 33132
 
22.3%
CJK Compat 24
 
< 0.1%
Punctuation 12
 
< 0.1%
Enclosed Alphanum 10
 
< 0.1%
None 9
 
< 0.1%
CJK 3
 
< 0.1%
Arrows 2
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Box Drawing 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17305
52.2%
( 2474
 
7.5%
) 2474
 
7.5%
1 1800
 
5.4%
2 1729
 
5.2%
, 1264
 
3.8%
0 1154
 
3.5%
/ 842
 
2.5%
. 818
 
2.5%
3 633
 
1.9%
Other values (53) 2639
 
8.0%
Hangul
ValueCountFrequency (%)
업 5852
 
5.1%
영 3547
 
3.1%
미 3260
 
2.8%
설 3252
 
2.8%
단 2636
 
2.3%
시 2531
 
2.2%
고 2379
 
2.1%
기 2368
 
2.0%
장 2127
 
1.8%
치 2045
 
1.8%
Other values (578) 85666
74.1%
CJK Compat
ValueCountFrequency (%)
㎡ 24
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 8
80.0%
② 2
 
20.0%
None
ValueCountFrequency (%)
？ 4
44.4%
」 2
22.2%
「 2
22.2%
【 1
 
11.1%
Punctuation
ValueCountFrequency (%)
” 4
33.3%
※ 2
16.7%
‘ 2
16.7%
’ 2
16.7%
“ 2
16.7%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Misc Symbols
ValueCountFrequency (%)
♧ 1
100.0%
Box Drawing
ValueCountFrequency (%)
┛ 1
100.0%
CJK
ValueCountFrequency (%)
河 1
33.3%
囹 1
33.3%
憫 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

처분내용
Text

Distinct5494
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:57:24.836169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length180
Median length125
Mean length20.482
Min length2

Characters and Unicode

Total characters204820
Distinct characters325
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4468 ?
Unique (%)44.7%

Sample

1st row강남서유선통보
2nd row과태료 50만원부과
3rd row영업허가취소(09.08.21자)
4th row영업정지3월(2000.4.24-7.23)
5th row시정명령(즉시시정후 2013.9.2까지)
ValueCountFrequency (%)
영업소폐쇄 728
 
4.2%
영업정지 655
 
3.8%
시정명령 525
 
3.0%
및 403
 
2.3%
과징금 372
 
2.1%
갈음 353
 
2.0%
과태료 346
 
2.0%
자진납부 335
 
1.9%
과태료부과 282
 
1.6%
영업소폐쇄(07.9.11일자 248
 
1.4%
Other values (6632) 13161
75.6%
2024-05-18T08:57:26.228190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17681
 
8.6%
. 17040
 
8.3%
1 16334
 
8.0%
2 12282
 
6.0%
( 7613
 
3.7%
) 7606
 
3.7%
7434
 
3.6%
정 6124
 
3.0%
업 6001
 
2.9%
영 5888
 
2.9%
Other values (315) 100817
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90125
44.0%
Decimal Number 69327
33.8%
Other Punctuation 19602
 
9.6%
Open Punctuation 7629
 
3.7%
Close Punctuation 7621
 
3.7%
Space Separator 7434
 
3.6%
Math Symbol 2149
 
1.0%
Dash Punctuation 879
 
0.4%
Modifier Symbol 17
 
< 0.1%
Lowercase Letter 17
 
< 0.1%
Other values (3) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 6124
 
6.8%
업 6001
 
6.7%
영 5888
 
6.5%
지 5729
 
6.4%
과 5340
 
5.9%
원 4072
 
4.5%
시 3801
 
4.2%
만 3606
 
4.0%
명 3149
 
3.5%
령 3126
 
3.5%
Other values (267) 43289
48.0%
Decimal Number
ValueCountFrequency (%)
0 17681
25.5%
1 16334
23.6%
2 12282
17.7%
5 4146
 
6.0%
3 4127
 
6.0%
9 3433
 
5.0%
7 3115
 
4.5%
4 2851
 
4.1%
6 2694
 
3.9%
8 2664
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 17040
86.9%
, 1812
 
9.2%
: 269
 
1.4%
/ 196
 
1.0%
※ 171
 
0.9%
% 91
 
0.5%
' 13
 
0.1%
* 7
 
< 0.1%
; 2
 
< 0.1%
＊ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
l 4
23.5%
r 2
11.8%
t 2
11.8%
w 2
11.8%
d 2
11.8%
m 1
 
5.9%
x 1
 
5.9%
h 1
 
5.9%
u 1
 
5.9%
j 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
~ 1832
85.2%
→ 277
 
12.9%
+ 23
 
1.1%
× 8
 
0.4%
> 8
 
0.4%
= 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7613
99.8%
[ 16
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 7606
99.8%
] 15
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
O 2
50.0%
N 2
50.0%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
7434
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 879
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 114674
56.0%
Hangul 90125
44.0%
Latin 21
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 6124
 
6.8%
업 6001
 
6.7%
영 5888
 
6.5%
지 5729
 
6.4%
과 5340
 
5.9%
원 4072
 
4.5%
시 3801
 
4.2%
만 3606
 
4.0%
명 3149
 
3.5%
령 3126
 
3.5%
Other values (267) 43289
48.0%
Common
ValueCountFrequency (%)
0 17681
15.4%
. 17040
14.9%
1 16334
14.2%
2 12282
10.7%
( 7613
6.6%
) 7606
6.6%
7434
6.5%
5 4146
 
3.6%
3 4127
 
3.6%
9 3433
 
3.0%
Other values (26) 16978
14.8%
Latin
ValueCountFrequency (%)
l 4
19.0%
r 2
9.5%
t 2
9.5%
w 2
9.5%
d 2
9.5%
O 2
9.5%
N 2
9.5%
m 1
 
4.8%
x 1
 
4.8%
h 1
 
4.8%
Other values (2) 2
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114236
55.8%
Hangul 90115
44.0%
Arrows 277
 
0.1%
Punctuation 171
 
0.1%
Compat Jamo 10
 
< 0.1%
None 9
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17681
15.5%
. 17040
14.9%
1 16334
14.3%
2 12282
10.8%
( 7613
6.7%
) 7606
6.7%
7434
6.5%
5 4146
 
3.6%
3 4127
 
3.6%
9 3433
 
3.0%
Other values (32) 16540
14.5%
Hangul
ValueCountFrequency (%)
정 6124
 
6.8%
업 6001
 
6.7%
영 5888
 
6.5%
지 5729
 
6.4%
과 5340
 
5.9%
원 4072
 
4.5%
시 3801
 
4.2%
만 3606
 
4.0%
명 3149
 
3.5%
령 3126
 
3.5%
Other values (264) 43279
48.0%
Arrows
ValueCountFrequency (%)
→ 277
100.0%
Punctuation
ValueCountFrequency (%)
※ 171
100.0%
None
ValueCountFrequency (%)
× 8
88.9%
＊ 1
 
11.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
80.0%
ㅘ 1
 
10.0%
ㅈ 1
 
10.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

처분기간
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)1.7%
Missing8379
Missing (%)83.8%
Infinite0
Infinite (%)0.0%
Mean13.228254
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:57:26.689224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q18
median15
Q315
95-th percentile20
Maximum30
Range29
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.6621371
Coefficient of variation (CV)0.35243782
Kurtosis1.1997164
Mean13.228254
Median Absolute Deviation (MAD)0
Skewness0.15559532
Sum21443
Variance21.735522
MonotonicityNot monotonic
2024-05-18T08:57:27.142389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
15 1007
 
10.1%
7 337
 
3.4%
10 56
 
0.6%
22 27
 
0.3%
8 24
 
0.2%
5 21
 
0.2%
20 18
 
0.2%
29 18
 
0.2%
18 18
 
0.2%
3 15
 
0.1%
Other values (17) 80
 
0.8%
(Missing) 8379
83.8%
ValueCountFrequency (%)
1 7
 
0.1%
2 3
 
< 0.1%
3 15
 
0.1%
4 5
 
0.1%
5 21
 
0.2%
6 5
 
0.1%
7 337
3.4%
8 24
 
0.2%
10 56
 
0.6%
11 2
 
< 0.1%
ValueCountFrequency (%)
30 4
 
< 0.1%
29 18
0.2%
28 6
 
0.1%
27 1
 
< 0.1%
25 1
 
< 0.1%
24 3
 
< 0.1%
23 12
0.1%
22 27
0.3%
21 4
 
< 0.1%
20 18
0.2%

영업장면적(㎡)
Real number (ℝ)

MISSING 

Distinct2213
Distinct (%)52.1%
Missing5751
Missing (%)57.5%
Infinite0
Infinite (%)0.0%
Mean217.55659
Minimum0
Maximum3784.87
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:57:27.534525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24.772
Q170.11
median134.45
Q3245.69
95-th percentile720.99
Maximum3784.87
Range3784.87
Interquartile range (IQR)175.58

Descriptive statistics

Standard deviation285.88604
Coefficient of variation (CV)1.3140767
Kurtosis27.871882
Mean217.55659
Median Absolute Deviation (MAD)75.67
Skewness4.3229606
Sum924397.96
Variance81730.829
MonotonicityNot monotonic
2024-05-18T08:57:27.998631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
132.23 28
 
0.3%
66.11 28
 
0.3%
59.5 23
 
0.2%
198.34 21
 
0.2%
29.75 17
 
0.2%
99.17 16
 
0.2%
82.64 16
 
0.2%
231.4 15
 
0.1%
62.81 15
 
0.1%
92.56 15
 
0.1%
Other values (2203) 4055
40.6%
(Missing) 5751
57.5%
ValueCountFrequency (%)
0.0 2
 
< 0.1%
1.3 1
 
< 0.1%
1.65 1
 
< 0.1%
3.0 1
 
< 0.1%
3.3 6
0.1%
3.5 1
 
< 0.1%
3.98 1
 
< 0.1%
4.0 1
 
< 0.1%
4.76 1
 
< 0.1%
5.25 1
 
< 0.1%
ValueCountFrequency (%)
3784.87 1
 
< 0.1%
3544.36 1
 
< 0.1%
2942.03 1
 
< 0.1%
2939.99 1
 
< 0.1%
2594.15 1
 
< 0.1%
2429.0 1
 
< 0.1%
2356.0 4
< 0.1%
2187.47 5
0.1%
2163.93 1
 
< 0.1%
2065.58 1
 
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9993 
직영
 
4
(조합)위탁
 
3

Length

Max length6
Median length4
Mean length3.9998
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> 9993
99.9%
직영 4
 
< 0.1%
(조합)위탁 3
 
< 0.1%

Length

2024-05-18T08:57:28.413434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:57:28.754677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9993
99.9%
직영 4
 
< 0.1%
조합)위탁 3
 
< 0.1%

Interactions

2024-05-18T08:56:59.886275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:48.735687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:50.811630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:52.985938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:55.352661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:57.432900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:57:00.455611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:49.059242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:51.118165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:53.564473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:55.670267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:57.812364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:57:00.905198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:49.347532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:51.472114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:53.914660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:56.002253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:58.410594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:57:01.336878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:49.693046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:51.840522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:54.226545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:56.412508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:58.844529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:57:01.752063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:50.172585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:52.226084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:54.544790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:56.840779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:59.176937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:57:02.134353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:50.488068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:52.586129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:54.895477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:57.130697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:56:59.559125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T08:57:28.920998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.0000.0000.0000.000NaN0.000NaNNaNNaN
교부번호0.0001.0000.5010.638NaN0.0000.1870.1770.000
업종명0.0000.5011.0001.000NaN0.0000.2880.349NaN
업태명0.0000.6381.0001.000NaN0.0000.3780.7060.433
지도점검일자NaNNaNNaNNaN1.000NaNNaNNaNNaN
위반일자0.0000.0000.0000.000NaN1.000NaNNaNNaN
처분기간NaN0.1870.2880.378NaNNaN1.0000.000NaN
영업장면적(㎡)NaN0.1770.3490.706NaNNaN0.0001.000NaN
운영형태NaN0.000NaN0.433NaNNaNNaNNaN1.000
2024-05-18T08:57:29.254471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영형태업종명
운영형태1.0001.000
업종명1.0001.000
2024-05-18T08:57:29.515542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.6270.9990.999-0.0510.1000.0001.000
교부번호0.6271.0000.6260.626-0.0390.0030.2390.000
지도점검일자0.9990.6261.0001.000-0.0530.0950.0001.000
위반일자0.9990.6261.0001.000-0.0530.0960.0001.000
처분기간-0.051-0.039-0.053-0.0531.000-0.0870.1230.000
영업장면적(㎡)0.1000.0030.0950.096-0.0871.0000.1570.000
업종명0.0000.2390.0000.0000.1230.1571.0001.000
운영형태1.0000.0001.0001.0000.0000.0001.0001.000

Missing values

2024-05-18T08:57:03.123634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T08:57:04.906884image/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.
2024-05-18T08:57:05.544587image/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
288232200001998082719950105850일반음식점한식이오<NA>서울특별시 강남구 신사동 511번지 6호19980727처분확정강남서유선통보식품위생법19980827시간외영업(01:30)강남서유선통보<NA><NA><NA>
2459932200002005082220030105757일반음식점경양식삐아제<NA>서울특별시 강남구 신사동 582번지 1호 지하2층20050704처분확정과태료 50만원부과식품위생법 제78조20050704건강진단미필(종업원2/3)과태료 50만원부과<NA><NA><NA>
1211532200002009082119990108638유흥주점영업룸살롱클럽에스<NA>서울특별시 강남구 역삼동 831번지 30호 지하1층20090730처분확정영업허가취소(09.08.21자)식품위생법2009073009.07.21 건축물 신축으로 기존 시설물 전부 멸실영업허가취소(09.08.21자)<NA><NA><NA>
1391132200002000040419940105212단란주점단란주점비젼<NA>서울특별시 강남구 역삼동 817번지 8호20000304처분확정영업정지3월(2000.4.24-7.23)식품위생법20000404유흥접객부고용.유흥주점형태영업영업정지3월(2000.4.24-7.23)<NA><NA><NA>
1539732200002013082620040109025휴게음식점일반조리판매커피스튜디오서울특별시 강남구 강남대로102길 32, 지하1,지하2층 (역삼동)서울특별시 강남구 역삼동 618번지 15호 지하1층,지하2층20130725처분확정시정명령(즉시시정후 2013.9.2까지)식품위생법 제71조 및 제75조20130725영업장외 테이블 영업시정명령(즉시시정후 2013.9.2까지)<NA>230.0<NA>
135032200002005031619910105025일반음식점한식남원골월매추어탕<NA>서울특별시 강남구 논현동 115번지 10호20050216처분확정행정처분철회-관허사업제한철회요청서(분납)접수:강남세무서(2005.3.16)식품위생법 제58조20050216국세3회이상체납행정처분철회-관허사업제한철회요청서(분납)접수:강남세무서(2005.3.16)<NA><NA><NA>
2753532200002020102620090107222일반음식점한식돈수백논현점서울특별시 강남구 언주로134길 15, (논현동,지상1층)서울특별시 강남구 논현동 114번지 26호 지상1층20200101처분확정과태료부과(20만원) 자진납부 16만원법 제101조제2항제1호202001012019 위생교육 미필과태료부과(20만원) 자진납부 16만원<NA><NA><NA>
380432200002011092619980105419일반음식점경양식구이마을<NA>서울특별시 강남구 역삼동 797번지 3호20110608처분확정시정명령(11.10.24까지) 및 과태료20만원(11.08.31 16만원 자진납부)식품위생법20110608영업장외 테이블 영업,건강진단서 미필(1/4)시정명령(11.10.24까지) 및 과태료20만원(11.08.31 16만원 자진납부)<NA><NA><NA>
464832200002000041119990107639일반음식점호프/통닭데니쉬숯불바베큐치킨<NA>서울특별시 강남구 개포동 1168번지 4호 1층20000311처분확정영업정지2월(2000.4.13-6.12)식품위생법20000411청소년주류제공(2000.2.25위반)영업정지2월(2000.4.13-6.12)<NA><NA><NA>
2650932200002010100620070105525일반음식점경양식티씩스<NA>서울특별시 강남구 청담동 83번지 21호 6층20100722처분확정시정명령식품위생법20100722신고된 영업장 이외의 장소에서 영업시정명령<NA>139.33<NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
1701332200002022011120110107541유통전문판매업유통전문판매업메디파트너(주)서울특별시 강남구 봉은사로 218, 지상8층 (역삼동)서울특별시 강남구 역삼동 651번지 5호20210401처분확정과태료부과법 제101조제4항4호202104012020년 유통전문판매업 식품위생교육 미필과태료부과<NA>347.45<NA>
1842932200001996011819860105321일반음식점한식광동성<NA>서울특별시 강남구 역삼동 648번지 3호 .4.5.6.7.819951218처분확정과태료(100만원).시정지시식품위생법19960118건강진단미필.방충망미설치과태료(100만원).시정지시<NA><NA><NA>
1289032200002017092520090107555유흥주점영업룸살롱비비서울특별시 강남구 테헤란로20길 9, (역삼동,지하1층)서울특별시 강남구 역삼동 736번지 17호 지하1층20151231처분확정과태료60만원법 제101조제2항 제1호20151231건강진단미필(종업원)과태료60만원<NA><NA><NA>
2562132200002008110420050105990일반음식점한식플젠선릉점<NA>서울특별시 강남구 대치동 895번지 0호 호성빌딩지하1층20080923처분확정시정명령식품위생법20080923영업장외 테이블영업시정명령<NA>277.82<NA>
577732200002005051620010107711일반음식점분식김가네코엑스점<NA>서울특별시 강남구 삼성동 159번지 0호 한무컨벤션부속동지하2층월드푸드코트16-1호20050404처분확정영업정지 15일(05.5.23 ~ 6.6)식품위생법 제58조20050404유통기한경과제품보관영업정지 15일(05.5.23 ~ 6.6)1526.38<NA>
2679432200002010020220070106647일반음식점한식소막골한우숯불갈비<NA>서울특별시 강남구 신사동 655번지 4호 지상1층20100115처분확정영업소폐쇄(2010.02.02)식품위생법20100115계속하여 영업을 하지 아니하며 영업변경신고를 하지 않음 (2007.12.05 사업자등록 폐업함)영업소폐쇄(2010.02.02)<NA><NA><NA>
2063132200002017092119950105296일반음식점한식(주)새벽집서울특별시 강남구 도산대로101길 6, (청담동)서울특별시 강남구 청담동 129번지 10호20170821처분확정시정명령(2017.10.31까지)법 제101조제2항제1호 및 영 제67조20170821조리장,조리기구 위생불량시정명령(2017.10.31까지)<NA>396.0<NA>
3373832200002004091419990107733단란주점단란주점에비앙<NA>서울특별시 강남구 논현동 106번지 8호20040707처분확정시설개수명령,시정명령(04.10.4까지)식품위생법 58조20040707투명유리미설치, 신고와 상이한 간판설치시설개수명령,시정명령(04.10.4까지)<NA><NA><NA>
603332200002016061620020106297일반음식점한식으악새서울특별시 강남구 도산대로81길 5, (청담동,1층)서울특별시 강남구 청담동 119번지 9호 1층20160526처분확정시정명령(즉시)법 제71조, 법 제74조 및 법 제75조20160526영업장외 영업시정명령(즉시)<NA>66.11<NA>
483632200002007030920000105574일반음식점경양식봄<NA>서울특별시 강남구 논현동 65번지 5호20061218처분확정영업정지1월15일 갈음 과징금 1,980만원,시설개수명령(07.3.31한),시정명령(07.3.31한)식품위생법 제57조,65조20061218음향 및 반주시설을 갖추고 손님이 노래를 부르도록 허용(1차2회) 객실안에 음향 및 반주시설 설치(1차2회) 간판에 업종구분에 혼란을 줄 수 있는 사항 표시(1차) -> 대외13,18 병합영업정지1월15일 갈음 과징금 1,980만원,시설개수명령(07.3.31한),시정명령(07.3.31한)15<NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
1432200002003120220030105386유통전문판매업유통전문판매업월드종합라이센스(주)<NA>서울특별시 강남구 역삼동 732번지 27호 대양빌딩5층20030905처분확정시정명령법 제10조20030905보관방법 표기 부적정(품목신고시 실온가능한 제품을 포장지에 냉장으로 표기하여 소비자 혼동 초래)시정명령<NA><NA><NA>3
5732200002009072920050105951식품제조가공업식품제조가공업사계절먹거리마을<NA>서울특별시 강남구 역삼동 788번지 28호 지하1층20090610처분확정영업소폐쇄(09.07.29까지)식품위생법20090610변경신고를 하지 아니하고 영업시설 전부 철거영업소폐쇄(09.07.29까지)<NA><NA><NA>3
5932200002009101420060105990건강기능식품일반판매업영업장판매(주)에코에프앤비<NA>서울특별시 강남구 역삼동 645번지 9호 하정빌딩지상1층20090910처분확정영업정지2월(2009.10.23~2009.12.22)건강기능식품에 관한 법20090910기능성표시 및 광고 심의 또는 변경통보 없이아웃팻HCA제품의 판매광고, HCA성분을 섭취하는 시험을 하였음에도 마치 보령 아웃팻HCA제품 자체로 인체시험을 한것처럼 허위 과대광고영업정지2월(2009.10.23~2009.12.22)<NA><NA><NA>3
8232200002012121420110107006일반음식점한식지서울특별시 강남구 강남대로 616, (신사동,지상16층)서울특별시 강남구 신사동 501번지 지상16층20120520처분확정영업정지2개월(2013.04.03~2013.06.01)식품위생법20120520영상반주기설치영업정지2개월(2013.04.03~2013.06.01)<NA><NA><NA>3
10132200002016020419940106921식품등 수입판매업식품등 수입판매업(주)신화팝빌리지서울특별시 강남구 개포로17길 13-14, 3층 (개포동)서울특별시 강남구 개포동 1241번지 5호 3층20160111처분확정과태료50만원(40만원 2016.1.30 자진납부)법 제101조제1항제1호20160111영양표시 기준 위반과태료50만원(40만원 2016.1.30 자진납부)<NA><NA><NA>3
032200001995072119910105621일반음식점경양식송이<NA>서울특별시 강남구 논현동 113번지 25호19950621처분확정영업정지15일갈음과징금 및 시설개수명령식품위생법19950621무단구조변경영업정지15일갈음과징금 및 시설개수명령15<NA><NA>2
132200001999081219980106649식품제조가공업식품제조가공업동현김밥<NA>서울특별시 강남구 논현동 산 105번지 0호19990812처분확정과징금 부과식품위생법19990812무표시제품제조판매(김밥)과징금 부과<NA><NA><NA>2
232200001999081819870105755유흥주점영업룸살롱대정<NA>서울특별시 강남구 삼성동 45번지 10호19990718처분확정영업정지1월(99.9.8~10.7)가름과징금1590만원대체식품위생법19990818도박행위방조(99.6.9적발)영업정지1월(99.9.8~10.7)가름과징금1590만원대체<NA>866.0<NA>2
332200002001081019980106649식품제조가공업식품제조가공업동현김밥<NA>서울특별시 강남구 논현동 산 105번지 0호20010810처분확정영업정지18일갈음,과태료,시정명령식품위생법20010810원료수불대장,생산일지미기재등영업정지18일갈음,과태료,시정명령18<NA><NA>2
432200002001082120000105156일반음식점정종/대포집/소주방풍금<NA>서울특별시 강남구 청담동 96번지 22호 지하1층20010721처분확정영업정지1월갈음과징금900만원부과식품위생법20010821단란주점형태영업영업정지1월갈음과징금900만원부과<NA><NA><NA>2