Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells21675
Missing cells (%)12.0%
Duplicate rows283
Duplicate rows (%)2.8%
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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-9911/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 283 (2.8%) duplicate rowsDuplicates
업종명 is highly overall correlated with 운영형태High correlation
운영형태 is highly overall correlated with 위반일자 and 3 other fieldsHigh correlation
처분일자 is highly overall correlated with 교부번호 and 2 other fieldsHigh correlation
교부번호 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
처분기간 is highly overall correlated with 운영형태High correlation
영업장면적(㎡) is highly overall correlated with 운영형태High correlation
업종명 is highly imbalanced (62.0%)Imbalance
운영형태 is highly imbalanced (98.1%)Imbalance
소재지도로명 has 7345 (73.5%) missing valuesMissing
법적근거 has 4521 (45.2%) missing valuesMissing
처분기간 has 6233 (62.3%) missing valuesMissing
영업장면적(㎡) has 3510 (35.1%) missing valuesMissing
위반일자 is highly skewed (γ1 = -45.35910554)Skewed
영업장면적(㎡) is highly skewed (γ1 = 28.06081143)Skewed
처분기간 has 1399 (14.0%) zerosZeros

Reproduction

Analysis started2024-05-04 06:48:11.157107
Analysis finished2024-05-04 06:48:27.422552
Duration16.27 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
3040000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 10000
100.0%

Length

2024-05-04T06:48:27.546643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:48:27.744742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2117
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20055986
Minimum19871106
Maximum20240418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:48:28.076789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19871106
5-th percentile19940997
Q119970714
median20040115
Q320130312
95-th percentile20230405
Maximum20240418
Range369312
Interquartile range (IQR)159598.5

Descriptive statistics

Standard deviation93998.52
Coefficient of variation (CV)0.0046868062
Kurtosis-1.0159459
Mean20055986
Median Absolute Deviation (MAD)70202
Skewness0.51903242
Sum2.0055986 × 1011
Variance8.8357218 × 109
MonotonicityNot monotonic
2024-05-04T06:48:28.450011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20231122 327
 
3.3%
20000811 232
 
2.3%
20071228 111
 
1.1%
20220228 105
 
1.1%
20131218 71
 
0.7%
20000930 62
 
0.6%
20230314 62
 
0.6%
19940514 55
 
0.5%
19950704 51
 
0.5%
20071226 49
 
0.5%
Other values (2107) 8875
88.8%
ValueCountFrequency (%)
19871106 1
 
< 0.1%
19880414 2
< 0.1%
19900209 1
 
< 0.1%
19900710 1
 
< 0.1%
19920114 1
 
< 0.1%
19920212 2
< 0.1%
19920309 1
 
< 0.1%
19920504 1
 
< 0.1%
19920512 3
< 0.1%
19920526 1
 
< 0.1%
ValueCountFrequency (%)
20240418 1
 
< 0.1%
20240417 2
< 0.1%
20240404 1
 
< 0.1%
20240401 1
 
< 0.1%
20240307 1
 
< 0.1%
20240306 1
 
< 0.1%
20240223 2
< 0.1%
20240220 1
 
< 0.1%
20240219 3
< 0.1%
20240202 2
< 0.1%

교부번호
Real number (ℝ)

HIGH CORRELATION 

Distinct5148
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9980037 × 1010
Minimum1.9720039 × 1010
Maximum2.0230054 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:48:28.737598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9720039 × 1010
5-th percentile1.9830039 × 1010
Q11.9930039 × 1010
median1.996004 × 1010
Q32.003004 × 1010
95-th percentile2.0170039 × 1010
Maximum2.0230054 × 1010
Range5.100149 × 108
Interquartile range (IQR)1.0000044 × 108

Descriptive statistics

Standard deviation95225942
Coefficient of variation (CV)0.0047660544
Kurtosis-0.01233403
Mean1.9980037 × 1010
Median Absolute Deviation (MAD)50000162
Skewness0.38241996
Sum1.9980037 × 1014
Variance9.06798 × 1015
MonotonicityNot monotonic
2024-05-04T06:48:29.022402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090039391 37
 
0.4%
19940039262 30
 
0.3%
19970039581 30
 
0.3%
19990040044 25
 
0.2%
19880039195 24
 
0.2%
19860039162 20
 
0.2%
20170039094 17
 
0.2%
19990039239 17
 
0.2%
19860039021 16
 
0.2%
19790039055 16
 
0.2%
Other values (5138) 9768
97.7%
ValueCountFrequency (%)
19720039006 8
0.1%
19720039007 1
 
< 0.1%
19730039001 1
 
< 0.1%
19740039004 3
 
< 0.1%
19740039005 6
0.1%
19740039007 4
 
< 0.1%
19750039006 6
0.1%
19750039007 10
0.1%
19750039008 9
0.1%
19760039006 12
0.1%
ValueCountFrequency (%)
20230053908 1
 
< 0.1%
20230053414 1
 
< 0.1%
20230053370 1
 
< 0.1%
20220130928 2
 
< 0.1%
20220045713 1
 
< 0.1%
20220045655 1
 
< 0.1%
20220045597 1
 
< 0.1%
20220045468 1
 
< 0.1%
20220045300 10
0.1%
20220045277 1
 
< 0.1%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
7152 
단란주점
1357 
휴게음식점
 
472
식품제조가공업
 
223
유흥주점영업
 
166
Other values (14)
 
630

Length

Max length13
Median length5
Mean length5.1135
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 7152
71.5%
단란주점 1357
 
13.6%
휴게음식점 472
 
4.7%
식품제조가공업 223
 
2.2%
유흥주점영업 166
 
1.7%
즉석판매제조가공업 156
 
1.6%
제과점영업 106
 
1.1%
건강기능식품일반판매업 81
 
0.8%
식품등 수입판매업 74
 
0.7%
유통전문판매업 72
 
0.7%
Other values (9) 141
 
1.4%

Length

2024-05-04T06:48:29.415134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 7152
71.0%
단란주점 1357
 
13.5%
휴게음식점 472
 
4.7%
식품제조가공업 223
 
2.2%
유흥주점영업 166
 
1.6%
즉석판매제조가공업 156
 
1.5%
제과점영업 106
 
1.1%
건강기능식품일반판매업 81
 
0.8%
식품등 74
 
0.7%
수입판매업 74
 
0.7%
Other values (10) 213
 
2.1%

업태명
Text

Distinct61
Distinct (%)0.6%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-04T06:48:29.742260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length3.588147
Min length2

Characters and Unicode

Total characters35842
Distinct characters136
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

Unique4 ?
Unique (%)< 0.1%

Sample

1st row호프/통닭
2nd row한식
3rd row한식
4th row경양식
5th row한식
ValueCountFrequency (%)
한식 2050
20.2%
호프/통닭 1434
14.1%
단란주점 1357
13.4%
경양식 1119
11.0%
분식 1117
11.0%
까페 322
 
3.2%
일식 301
 
3.0%
중국식 242
 
2.4%
기타 224
 
2.2%
식품제조가공업 223
 
2.2%
Other values (51) 1758
17.3%
2024-05-04T06:48:30.348167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 5429
 
15.1%
한 2050
 
5.7%
점 1608
 
4.5%
/ 1596
 
4.5%
통 1591
 
4.4%
닭 1488
 
4.2%
주 1458
 
4.1%
호 1442
 
4.0%
프 1434
 
4.0%
단 1378
 
3.8%
Other values (126) 16368
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33762
94.2%
Other Punctuation 1606
 
4.5%
Space Separator 158
 
0.4%
Close Punctuation 158
 
0.4%
Open Punctuation 158
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 5429
 
16.1%
한 2050
 
6.1%
점 1608
 
4.8%
통 1591
 
4.7%
닭 1488
 
4.4%
주 1458
 
4.3%
호 1442
 
4.3%
프 1434
 
4.2%
단 1378
 
4.1%
란 1357
 
4.0%
Other values (121) 14527
43.0%
Other Punctuation
ValueCountFrequency (%)
/ 1596
99.4%
, 10
 
0.6%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 158
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33762
94.2%
Common 2080
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 5429
 
16.1%
한 2050
 
6.1%
점 1608
 
4.8%
통 1591
 
4.7%
닭 1488
 
4.4%
주 1458
 
4.3%
호 1442
 
4.3%
프 1434
 
4.2%
단 1378
 
4.1%
란 1357
 
4.0%
Other values (121) 14527
43.0%
Common
ValueCountFrequency (%)
/ 1596
76.7%
158
 
7.6%
) 158
 
7.6%
( 158
 
7.6%
, 10
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33762
94.2%
ASCII 2080
 
5.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 5429
 
16.1%
한 2050
 
6.1%
점 1608
 
4.8%
통 1591
 
4.7%
닭 1488
 
4.4%
주 1458
 
4.3%
호 1442
 
4.3%
프 1434
 
4.2%
단 1378
 
4.1%
란 1357
 
4.0%
Other values (121) 14527
43.0%
ASCII
ValueCountFrequency (%)
/ 1596
76.7%
158
 
7.6%
) 158
 
7.6%
( 158
 
7.6%
, 10
 
0.5%

업소명
Text

Distinct4911
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T06:48:30.877641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length25
Mean length4.9718
Min length1

Characters and Unicode

Total characters49718
Distinct characters960
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2939 ?
Unique (%)29.4%

Sample

1st row파레스
2nd row지리산참숯불갈비
3rd row세바스챤
4th row뱅크
5th row강변식당
ValueCountFrequency (%)
호야초밥참치전문점 37
 
0.4%
주식회사 34
 
0.3%
한강 24
 
0.2%
올인(allin 23
 
0.2%
단란주점 23
 
0.2%
코리아나단란주점 22
 
0.2%
주)갈릴리유통 22
 
0.2%
월드컵단란주점 22
 
0.2%
토크쇼 22
 
0.2%
어린이회관구내식당 20
 
0.2%
Other values (5071) 10208
97.6%
2024-05-04T06:48:31.978362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1355
 
2.7%
점 1301
 
2.6%
이 1213
 
2.4%
스 1043
 
2.1%
리 843
 
1.7%
란 781
 
1.6%
식 776
 
1.6%
단 770
 
1.5%
) 610
 
1.2%
( 607
 
1.2%
Other values (950) 40419
81.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46160
92.8%
Uppercase Letter 743
 
1.5%
Close Punctuation 610
 
1.2%
Open Punctuation 607
 
1.2%
Decimal Number 542
 
1.1%
Lowercase Letter 488
 
1.0%
Space Separator 460
 
0.9%
Other Punctuation 90
 
0.2%
Dash Punctuation 11
 
< 0.1%
Letter Number 5
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1355
 
2.9%
점 1301
 
2.8%
이 1213
 
2.6%
스 1043
 
2.3%
리 843
 
1.8%
란 781
 
1.7%
식 776
 
1.7%
단 770
 
1.7%
프 572
 
1.2%
호 559
 
1.2%
Other values (870) 36947
80.0%
Uppercase Letter
ValueCountFrequency (%)
A 70
 
9.4%
B 67
 
9.0%
L 67
 
9.0%
I 59
 
7.9%
C 46
 
6.2%
O 44
 
5.9%
N 43
 
5.8%
E 42
 
5.7%
S 33
 
4.4%
P 32
 
4.3%
Other values (16) 240
32.3%
Lowercase Letter
ValueCountFrequency (%)
o 66
13.5%
e 64
13.1%
a 54
11.1%
l 33
 
6.8%
r 32
 
6.6%
n 29
 
5.9%
c 25
 
5.1%
b 20
 
4.1%
s 20
 
4.1%
p 19
 
3.9%
Other values (15) 126
25.8%
Other Punctuation
ValueCountFrequency (%)
. 39
43.3%
& 21
23.3%
! 5
 
5.6%
; 5
 
5.6%
' 4
 
4.4%
, 4
 
4.4%
？ 4
 
4.4%
? 3
 
3.3%
# 2
 
2.2%
＃ 1
 
1.1%
Other values (2) 2
 
2.2%
Decimal Number
ValueCountFrequency (%)
2 134
24.7%
0 118
21.8%
1 60
11.1%
5 47
 
8.7%
7 43
 
7.9%
4 42
 
7.7%
8 35
 
6.5%
3 30
 
5.5%
9 22
 
4.1%
6 11
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 610
100.0%
Open Punctuation
ValueCountFrequency (%)
( 607
100.0%
Space Separator
ValueCountFrequency (%)
460
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46129
92.8%
Common 2322
 
4.7%
Latin 1236
 
2.5%
Han 31
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1355
 
2.9%
점 1301
 
2.8%
이 1213
 
2.6%
스 1043
 
2.3%
리 843
 
1.8%
란 781
 
1.7%
식 776
 
1.7%
단 770
 
1.7%
프 572
 
1.2%
호 559
 
1.2%
Other values (854) 36916
80.0%
Latin
ValueCountFrequency (%)
A 70
 
5.7%
B 67
 
5.4%
L 67
 
5.4%
o 66
 
5.3%
e 64
 
5.2%
I 59
 
4.8%
a 54
 
4.4%
C 46
 
3.7%
O 44
 
3.6%
N 43
 
3.5%
Other values (42) 656
53.1%
Common
ValueCountFrequency (%)
) 610
26.3%
( 607
26.1%
460
19.8%
2 134
 
5.8%
0 118
 
5.1%
1 60
 
2.6%
5 47
 
2.0%
7 43
 
1.9%
4 42
 
1.8%
. 39
 
1.7%
Other values (18) 162
 
7.0%
Han
ValueCountFrequency (%)
土 9
29.0%
酒 3
 
9.7%
五 2
 
6.5%
水 2
 
6.5%
門 2
 
6.5%
尹 2
 
6.5%
集 2
 
6.5%
秀 1
 
3.2%
多 1
 
3.2%
安 1
 
3.2%
Other values (6) 6
19.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46129
92.8%
ASCII 3547
 
7.1%
CJK 31
 
0.1%
None 6
 
< 0.1%
Number Forms 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1355
 
2.9%
점 1301
 
2.8%
이 1213
 
2.6%
스 1043
 
2.3%
리 843
 
1.8%
란 781
 
1.7%
식 776
 
1.7%
단 770
 
1.7%
프 572
 
1.2%
호 559
 
1.2%
Other values (854) 36916
80.0%
ASCII
ValueCountFrequency (%)
) 610
17.2%
( 607
17.1%
460
 
13.0%
2 134
 
3.8%
0 118
 
3.3%
A 70
 
2.0%
B 67
 
1.9%
L 67
 
1.9%
o 66
 
1.9%
e 64
 
1.8%
Other values (66) 1284
36.2%
CJK
ValueCountFrequency (%)
土 9
29.0%
酒 3
 
9.7%
五 2
 
6.5%
水 2
 
6.5%
門 2
 
6.5%
尹 2
 
6.5%
集 2
 
6.5%
秀 1
 
3.2%
多 1
 
3.2%
安 1
 
3.2%
Other values (6) 6
19.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
100.0%
None
ValueCountFrequency (%)
？ 4
66.7%
＃ 1
 
16.7%
₂ 1
 
16.7%

소재지도로명
Text

MISSING 

Distinct1612
Distinct (%)60.7%
Missing7345
Missing (%)73.5%
Memory size156.2 KiB
2024-05-04T06:48:32.743425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length51
Mean length29.669303
Min length22

Characters and Unicode

Total characters78772
Distinct characters263
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

Unique1090 ?
Unique (%)41.1%

Sample

1st row서울특별시 광진구 능동로31길 16, 1층 (군자동)
2nd row서울특별시 광진구 자양로13길 40, (자양동)
3rd row서울특별시 광진구 아차산로 297, 1층 (자양동)
4th row서울특별시 광진구 뚝섬로23길 34, 1층 (자양동)
5th row서울특별시 광진구 자양로22길 58, (구의동,2층)
ValueCountFrequency (%)
서울특별시 2655
 
17.4%
광진구 2655
 
17.4%
1층 699
 
4.6%
화양동 510
 
3.3%
구의동 488
 
3.2%
자양동 459
 
3.0%
중곡동 454
 
3.0%
아차산로 176
 
1.2%
면목로 176
 
1.2%
동일로22길 171
 
1.1%
Other values (1215) 6782
44.5%
2024-05-04T06:48:33.894673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12574
 
16.0%
동 3471
 
4.4%
, 3412
 
4.3%
구 3363
 
4.3%
1 3312
 
4.2%
광 2979
 
3.8%
) 2939
 
3.7%
( 2939
 
3.7%
진 2696
 
3.4%
시 2678
 
3.4%
Other values (253) 38409
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44424
56.4%
Space Separator 12574
 
16.0%
Decimal Number 11992
 
15.2%
Other Punctuation 3418
 
4.3%
Close Punctuation 2939
 
3.7%
Open Punctuation 2939
 
3.7%
Dash Punctuation 286
 
0.4%
Uppercase Letter 109
 
0.1%
Lowercase Letter 65
 
0.1%
Math Symbol 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3471
 
7.8%
구 3363
 
7.6%
광 2979
 
6.7%
진 2696
 
6.1%
시 2678
 
6.0%
서 2665
 
6.0%
로 2662
 
6.0%
울 2661
 
6.0%
별 2658
 
6.0%
특 2655
 
6.0%
Other values (214) 15936
35.9%
Uppercase Letter
ValueCountFrequency (%)
B 55
50.5%
A 16
 
14.7%
P 10
 
9.2%
H 10
 
9.2%
D 6
 
5.5%
C 5
 
4.6%
L 2
 
1.8%
K 2
 
1.8%
V 1
 
0.9%
I 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 3312
27.6%
2 1982
16.5%
3 1276
 
10.6%
5 893
 
7.4%
0 862
 
7.2%
4 835
 
7.0%
6 816
 
6.8%
8 748
 
6.2%
9 642
 
5.4%
7 626
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
i 21
32.3%
h 10
15.4%
m 10
15.4%
e 10
15.4%
l 10
15.4%
b 1
 
1.5%
t 1
 
1.5%
k 1
 
1.5%
n 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 3412
99.8%
/ 4
 
0.1%
@ 1
 
< 0.1%
? 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2939
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2939
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 286
100.0%
Math Symbol
ValueCountFrequency (%)
~ 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44424
56.4%
Common 34174
43.4%
Latin 174
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3471
 
7.8%
구 3363
 
7.6%
광 2979
 
6.7%
진 2696
 
6.1%
시 2678
 
6.0%
서 2665
 
6.0%
로 2662
 
6.0%
울 2661
 
6.0%
별 2658
 
6.0%
특 2655
 
6.0%
Other values (214) 15936
35.9%
Latin
ValueCountFrequency (%)
B 55
31.6%
i 21
 
12.1%
A 16
 
9.2%
h 10
 
5.7%
P 10
 
5.7%
m 10
 
5.7%
e 10
 
5.7%
H 10
 
5.7%
l 10
 
5.7%
D 6
 
3.4%
Other values (10) 16
 
9.2%
Common
ValueCountFrequency (%)
12574
36.8%
, 3412
 
10.0%
1 3312
 
9.7%
) 2939
 
8.6%
( 2939
 
8.6%
2 1982
 
5.8%
3 1276
 
3.7%
5 893
 
2.6%
0 862
 
2.5%
4 835
 
2.4%
Other values (9) 3150
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44424
56.4%
ASCII 34348
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12574
36.6%
, 3412
 
9.9%
1 3312
 
9.6%
) 2939
 
8.6%
( 2939
 
8.6%
2 1982
 
5.8%
3 1276
 
3.7%
5 893
 
2.6%
0 862
 
2.5%
4 835
 
2.4%
Other values (29) 3324
 
9.7%
Hangul
ValueCountFrequency (%)
동 3471
 
7.8%
구 3363
 
7.6%
광 2979
 
6.7%
진 2696
 
6.1%
시 2678
 
6.0%
서 2665
 
6.0%
로 2662
 
6.0%
울 2661
 
6.0%
별 2658
 
6.0%
특 2655
 
6.0%
Other values (214) 15936
35.9%

소재지지번
Text

Distinct4267
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T06:48:34.711961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length48
Mean length27.1702
Min length18

Characters and Unicode

Total characters271702
Distinct characters276
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2301 ?
Unique (%)23.0%

Sample

1st row서울특별시 광진구 구의동 246번지 12호
2nd row서울특별시 광진구 중곡동 산 18번지 74호
3rd row서울특별시 광진구 화양동 산 226번지 0호
4th row서울특별시 광진구 구의동 산 248번지 88호
5th row서울특별시 광진구 자양동 산 49번지 295호
ValueCountFrequency (%)
서울특별시 10000
17.6%
광진구 10000
17.6%
산 4532
 
8.0%
화양동 2681
 
4.7%
자양동 2149
 
3.8%
구의동 2096
 
3.7%
중곡동 1774
 
3.1%
1호 812
 
1.4%
1층 700
 
1.2%
군자동 644
 
1.1%
Other values (1286) 21573
37.9%
2024-05-04T06:48:36.254038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74841
27.5%
구 12112
 
4.5%
지 10445
 
3.8%
광 10387
 
3.8%
동 10106
 
3.7%
호 10085
 
3.7%
진 10044
 
3.7%
시 10030
 
3.7%
서 10019
 
3.7%
울 10015
 
3.7%
Other values (266) 103618
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150049
55.2%
Space Separator 74841
27.5%
Decimal Number 44918
 
16.5%
Close Punctuation 573
 
0.2%
Open Punctuation 573
 
0.2%
Other Punctuation 382
 
0.1%
Uppercase Letter 162
 
0.1%
Dash Punctuation 132
 
< 0.1%
Lowercase Letter 64
 
< 0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 12112
 
8.1%
지 10445
 
7.0%
광 10387
 
6.9%
동 10106
 
6.7%
호 10085
 
6.7%
진 10044
 
6.7%
시 10030
 
6.7%
서 10019
 
6.7%
울 10015
 
6.7%
별 10007
 
6.7%
Other values (220) 46799
31.2%
Uppercase Letter
ValueCountFrequency (%)
B 65
40.1%
A 26
 
16.0%
F 13
 
8.0%
D 11
 
6.8%
P 11
 
6.8%
H 10
 
6.2%
C 7
 
4.3%
I 6
 
3.7%
K 3
 
1.9%
L 2
 
1.2%
Other values (6) 8
 
4.9%
Decimal Number
ValueCountFrequency (%)
1 9482
21.1%
2 8064
18.0%
4 4535
10.1%
3 4304
9.6%
5 3986
8.9%
6 3823
8.5%
7 3215
 
7.2%
0 2648
 
5.9%
9 2637
 
5.9%
8 2224
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
i 21
32.8%
h 10
15.6%
l 10
15.6%
m 10
15.6%
e 10
15.6%
k 1
 
1.6%
n 1
 
1.6%
t 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 362
94.8%
/ 15
 
3.9%
？ 2
 
0.5%
@ 1
 
0.3%
. 1
 
0.3%
? 1
 
0.3%
Space Separator
ValueCountFrequency (%)
74841
100.0%
Close Punctuation
ValueCountFrequency (%)
) 573
100.0%
Open Punctuation
ValueCountFrequency (%)
( 573
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150049
55.2%
Common 121423
44.7%
Latin 230
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 12112
 
8.1%
지 10445
 
7.0%
광 10387
 
6.9%
동 10106
 
6.7%
호 10085
 
6.7%
진 10044
 
6.7%
시 10030
 
6.7%
서 10019
 
6.7%
울 10015
 
6.7%
별 10007
 
6.7%
Other values (220) 46799
31.2%
Latin
ValueCountFrequency (%)
B 65
28.3%
A 26
 
11.3%
i 21
 
9.1%
F 13
 
5.7%
D 11
 
4.8%
P 11
 
4.8%
h 10
 
4.3%
l 10
 
4.3%
m 10
 
4.3%
e 10
 
4.3%
Other values (15) 43
18.7%
Common
ValueCountFrequency (%)
74841
61.6%
1 9482
 
7.8%
2 8064
 
6.6%
4 4535
 
3.7%
3 4304
 
3.5%
5 3986
 
3.3%
6 3823
 
3.1%
7 3215
 
2.6%
0 2648
 
2.2%
9 2637
 
2.2%
Other values (11) 3888
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150049
55.2%
ASCII 121647
44.8%
Number Forms 4
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74841
61.5%
1 9482
 
7.8%
2 8064
 
6.6%
4 4535
 
3.7%
3 4304
 
3.5%
5 3986
 
3.3%
6 3823
 
3.1%
7 3215
 
2.6%
0 2648
 
2.2%
9 2637
 
2.2%
Other values (34) 4112
 
3.4%
Hangul
ValueCountFrequency (%)
구 12112
 
8.1%
지 10445
 
7.0%
광 10387
 
6.9%
동 10106
 
6.7%
호 10085
 
6.7%
진 10044
 
6.7%
시 10030
 
6.7%
서 10019
 
6.7%
울 10015
 
6.7%
별 10007
 
6.7%
Other values (220) 46799
31.2%
Number Forms
ValueCountFrequency (%)
Ⅲ 4
100.0%
None
ValueCountFrequency (%)
？ 2
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2670
Distinct (%)26.8%
Missing53
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean20055144
Minimum19871106
Maximum20240315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:48:37.151491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19871106
5-th percentile19940929
Q119970704
median20040115
Q320130131
95-th percentile20230213
Maximum20240315
Range369209
Interquartile range (IQR)159427

Descriptive statistics

Standard deviation93330.959
Coefficient of variation (CV)0.0046537168
Kurtosis-1.0113846
Mean20055144
Median Absolute Deviation (MAD)70193
Skewness0.51748985
Sum1.9948851 × 1011
Variance8.7106678 × 109
MonotonicityNot monotonic
2024-05-04T06:48:38.044674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000623 233
 
2.3%
20211222 165
 
1.7%
20230125 136
 
1.4%
20230926 114
 
1.1%
20000627 67
 
0.7%
19940514 55
 
0.5%
19950704 51
 
0.5%
20071206 50
 
0.5%
20230907 47
 
0.5%
20230908 47
 
0.5%
Other values (2660) 8982
89.8%
(Missing) 53
 
0.5%
ValueCountFrequency (%)
19871106 1
 
< 0.1%
19880414 2
< 0.1%
19900209 1
 
< 0.1%
19900710 1
 
< 0.1%
19920114 1
 
< 0.1%
19920212 2
< 0.1%
19920309 1
 
< 0.1%
19920504 1
 
< 0.1%
19920512 3
< 0.1%
19920526 1
 
< 0.1%
ValueCountFrequency (%)
20240315 1
 
< 0.1%
20240228 1
 
< 0.1%
20240219 2
< 0.1%
20240214 1
 
< 0.1%
20240126 2
< 0.1%
20240119 3
< 0.1%
20240118 1
 
< 0.1%
20240111 1
 
< 0.1%
20231228 1
 
< 0.1%
20231205 1
 
< 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

2024-05-04T06:48:38.952060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:48:39.430804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%

처분명
Text

Distinct892
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T06:48:40.428237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length130
Median length88
Mean length6.5129
Min length2

Characters and Unicode

Total characters65129
Distinct characters227
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique526 ?
Unique (%)5.3%

Sample

1st row영업소폐쇄
2nd row()
3rd row()
4th row()
5th row()
ValueCountFrequency (%)
3745
28.0%
영업소폐쇄 1005
 
7.5%
과태료부과 1004
 
7.5%
영업정지 984
 
7.4%
시정명령 768
 
5.7%
과태료 336
 
2.5%
부과 300
 
2.2%
및 231
 
1.7%
시설개수명령 161
 
1.2%
영업정지2월 142
 
1.1%
Other values (919) 4684
35.1%
2024-05-04T06:48:41.887833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 5835
 
9.0%
( 5832
 
9.0%
과 4380
 
6.7%
3399
 
5.2%
정 2881
 
4.4%
영 2834
 
4.4%
업 2810
 
4.3%
0 2716
 
4.2%
부 2135
 
3.3%
2 1955
 
3.0%
Other values (217) 30352
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39098
60.0%
Decimal Number 9180
 
14.1%
Close Punctuation 5835
 
9.0%
Open Punctuation 5832
 
9.0%
Space Separator 3399
 
5.2%
Other Punctuation 1533
 
2.4%
Math Symbol 223
 
0.3%
Dash Punctuation 28
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 4380
 
11.2%
정 2881
 
7.4%
영 2834
 
7.2%
업 2810
 
7.2%
부 2135
 
5.5%
지 1954
 
5.0%
료 1946
 
5.0%
태 1944
 
5.0%
시 1515
 
3.9%
원 1314
 
3.4%
Other values (192) 15385
39.3%
Decimal Number
ValueCountFrequency (%)
0 2716
29.6%
2 1955
21.3%
1 1922
20.9%
5 613
 
6.7%
3 540
 
5.9%
4 425
 
4.6%
6 333
 
3.6%
8 262
 
2.9%
9 221
 
2.4%
7 193
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 1115
72.7%
, 201
 
13.1%
% 181
 
11.8%
/ 30
 
2.0%
' 2
 
0.1%
: 2
 
0.1%
* 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 219
98.2%
> 2
 
0.9%
+ 2
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 5835
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5832
100.0%
Space Separator
ValueCountFrequency (%)
3399
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39098
60.0%
Common 26031
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 4380
 
11.2%
정 2881
 
7.4%
영 2834
 
7.2%
업 2810
 
7.2%
부 2135
 
5.5%
지 1954
 
5.0%
료 1946
 
5.0%
태 1944
 
5.0%
시 1515
 
3.9%
원 1314
 
3.4%
Other values (192) 15385
39.3%
Common
ValueCountFrequency (%)
) 5835
22.4%
( 5832
22.4%
3399
13.1%
0 2716
10.4%
2 1955
 
7.5%
1 1922
 
7.4%
. 1115
 
4.3%
5 613
 
2.4%
3 540
 
2.1%
4 425
 
1.6%
Other values (15) 1679
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39095
60.0%
ASCII 26031
40.0%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 5835
22.4%
( 5832
22.4%
3399
13.1%
0 2716
10.4%
2 1955
 
7.5%
1 1922
 
7.4%
. 1115
 
4.3%
5 613
 
2.4%
3 540
 
2.1%
4 425
 
1.6%
Other values (15) 1679
 
6.5%
Hangul
ValueCountFrequency (%)
과 4380
 
11.2%
정 2881
 
7.4%
영 2834
 
7.2%
업 2810
 
7.2%
부 2135
 
5.5%
지 1954
 
5.0%
료 1946
 
5.0%
태 1944
 
5.0%
시 1515
 
3.9%
원 1314
 
3.4%
Other values (191) 15382
39.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%

법적근거
Text

MISSING 

Distinct674
Distinct (%)12.3%
Missing4521
Missing (%)45.2%
Memory size156.2 KiB
2024-05-04T06:48:42.509155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length13.726957
Min length4

Characters and Unicode

Total characters75210
Distinct characters110
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique323 ?
Unique (%)5.9%

Sample

1st row제31조 제58조
2nd row식품위생법 제21조
3rd row법 제101조제4항1호
4th row식품위생법 제27조
5th row법 제75조
ValueCountFrequency (%)
식품위생법 2698
18.3%
법 2644
18.0%
제75조 1028
 
7.0%
및 731
 
5.0%
제58조 670
 
4.6%
제71조 506
 
3.4%
제101조제4항1호 503
 
3.4%
제31조 348
 
2.4%
제44조 314
 
2.1%
제37조 250
 
1.7%
Other values (462) 5032
34.2%
2024-05-04T06:48:43.708683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 9733
12.9%
9260
12.3%
조 8399
11.2%
법 6346
 
8.4%
1 5580
 
7.4%
식 3460
 
4.6%
품 3453
 
4.6%
위 3431
 
4.6%
생 3374
 
4.5%
7 3074
 
4.1%
Other values (100) 19100
25.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43611
58.0%
Decimal Number 20566
27.3%
Space Separator 9260
 
12.3%
Other Punctuation 1699
 
2.3%
Close Punctuation 37
 
< 0.1%
Open Punctuation 34
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 9733
22.3%
조 8399
19.3%
법 6346
14.6%
식 3460
 
7.9%
품 3453
 
7.9%
위 3431
 
7.9%
생 3374
 
7.7%
항 1647
 
3.8%
호 1084
 
2.5%
및 1026
 
2.4%
Other values (81) 1658
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 5580
27.1%
7 3074
14.9%
5 2616
12.7%
4 2064
 
10.0%
2 1998
 
9.7%
3 1640
 
8.0%
8 1394
 
6.8%
0 1346
 
6.5%
6 673
 
3.3%
9 181
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 1654
97.4%
. 44
 
2.6%
? 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 34
91.9%
〕 3
 
8.1%
Open Punctuation
ValueCountFrequency (%)
( 31
91.2%
〔 3
 
8.8%
Space Separator
ValueCountFrequency (%)
9260
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43611
58.0%
Common 31596
42.0%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 9733
22.3%
조 8399
19.3%
법 6346
14.6%
식 3460
 
7.9%
품 3453
 
7.9%
위 3431
 
7.9%
생 3374
 
7.7%
항 1647
 
3.8%
호 1084
 
2.5%
및 1026
 
2.4%
Other values (81) 1658
 
3.8%
Common
ValueCountFrequency (%)
9260
29.3%
1 5580
17.7%
7 3074
 
9.7%
5 2616
 
8.3%
4 2064
 
6.5%
2 1998
 
6.3%
, 1654
 
5.2%
3 1640
 
5.2%
8 1394
 
4.4%
0 1346
 
4.3%
Other values (8) 970
 
3.1%
Latin
ValueCountFrequency (%)
Ⅱ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43611
58.0%
ASCII 31590
42.0%
None 6
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 9733
22.3%
조 8399
19.3%
법 6346
14.6%
식 3460
 
7.9%
품 3453
 
7.9%
위 3431
 
7.9%
생 3374
 
7.7%
항 1647
 
3.8%
호 1084
 
2.5%
및 1026
 
2.4%
Other values (81) 1658
 
3.8%
ASCII
ValueCountFrequency (%)
9260
29.3%
1 5580
17.7%
7 3074
 
9.7%
5 2616
 
8.3%
4 2064
 
6.5%
2 1998
 
6.3%
, 1654
 
5.2%
3 1640
 
5.2%
8 1394
 
4.4%
0 1346
 
4.3%
Other values (6) 964
 
3.1%
None
ValueCountFrequency (%)
〔 3
50.0%
〕 3
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

위반일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2695
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20047563
Minimum2001106
Maximum20240315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:48:44.309752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001106
5-th percentile19940929
Q119970714
median20031208
Q320130125
95-th percentile20230101
Maximum20240315
Range18239209
Interquartile range (IQR)159411

Descriptive statistics

Standard deviation372573.14
Coefficient of variation (CV)0.018584461
Kurtosis2193.9316
Mean20047563
Median Absolute Deviation (MAD)70005
Skewness-45.359106
Sum2.0047563 × 1011
Variance1.3881075 × 1011
MonotonicityNot monotonic
2024-05-04T06:48:44.852025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230101 351
 
3.5%
20000623 233
 
2.3%
20211222 169
 
1.7%
20230125 135
 
1.4%
20000627 67
 
0.7%
19940514 55
 
0.5%
19950704 51
 
0.5%
20071206 50
 
0.5%
20191231 46
 
0.5%
20190521 43
 
0.4%
Other values (2685) 8800
88.0%
ValueCountFrequency (%)
2001106 1
< 0.1%
2002127 1
< 0.1%
2003103 1
< 0.1%
2051017 1
< 0.1%
19871106 1
< 0.1%
19880414 2
< 0.1%
19900209 1
< 0.1%
19900710 1
< 0.1%
19920114 1
< 0.1%
19920212 2
< 0.1%
ValueCountFrequency (%)
20240315 1
< 0.1%
20240228 1
< 0.1%
20240219 2
< 0.1%
20240206 1
< 0.1%
20240126 2
< 0.1%
20240118 1
< 0.1%
20240105 1
< 0.1%
20231205 1
< 0.1%
20231126 1
< 0.1%
20231112 2
< 0.1%

위반내용
Text

Distinct2232
Distinct (%)22.3%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-04T06:48:45.561664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length321
Median length238
Mean length15.357972
Min length2

Characters and Unicode

Total characters153549
Distinct characters686
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1458 ?
Unique (%)14.6%

Sample

1st row청소년 유흥접객원 고용영업
2nd row()식육중량당가격미표시
3rd row()
4th row()
5th row()
ValueCountFrequency (%)
3928
 
12.2%
위생교육 1026
 
3.2%
기존영업자 920
 
2.9%
미이수 497
 
1.5%
영업장 472
 
1.5%
시설물 435
 
1.4%
청소년 432
 
1.3%
및 347
 
1.1%
미이수(1차 337
 
1.0%
2022년 282
 
0.9%
Other values (4457) 23479
73.0%
2024-05-04T06:48:46.992255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22727
 
14.8%
) 6814
 
4.4%
( 6806
 
4.4%
2 5407
 
3.5%
업 3992
 
2.6%
1 3785
 
2.5%
0 3703
 
2.4%
영 3164
 
2.1%
. 2931
 
1.9%
미 2667
 
1.7%
Other values (676) 91553
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94469
61.5%
Space Separator 22727
 
14.8%
Decimal Number 16638
 
10.8%
Close Punctuation 6949
 
4.5%
Open Punctuation 6946
 
4.5%
Other Punctuation 5132
 
3.3%
Dash Punctuation 271
 
0.2%
Lowercase Letter 201
 
0.1%
Other Symbol 83
 
0.1%
Uppercase Letter 83
 
0.1%
Other values (3) 50
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 3992
 
4.2%
영 3164
 
3.3%
미 2667
 
2.8%
위 2438
 
2.6%
시 2220
 
2.3%
이 2084
 
2.2%
기 2051
 
2.2%
년 1914
 
2.0%
자 1756
 
1.9%
설 1576
 
1.7%
Other values (608) 70607
74.7%
Lowercase Letter
ValueCountFrequency (%)
m 59
29.4%
g 50
24.9%
x 24
11.9%
t 21
 
10.4%
k 19
 
9.5%
l 5
 
2.5%
n 5
 
2.5%
e 4
 
2.0%
c 3
 
1.5%
u 3
 
1.5%
Other values (7) 8
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
O 28
33.7%
K 15
18.1%
B 12
14.5%
X 6
 
7.2%
A 6
 
7.2%
L 3
 
3.6%
G 3
 
3.6%
N 2
 
2.4%
S 2
 
2.4%
M 2
 
2.4%
Other values (3) 4
 
4.8%
Decimal Number
ValueCountFrequency (%)
2 5407
32.5%
1 3785
22.7%
0 3703
22.3%
3 917
 
5.5%
5 626
 
3.8%
4 592
 
3.6%
6 419
 
2.5%
9 417
 
2.5%
7 394
 
2.4%
8 378
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 2931
57.1%
, 943
 
18.4%
: 856
 
16.7%
/ 220
 
4.3%
? 115
 
2.2%
* 43
 
0.8%
' 14
 
0.3%
% 6
 
0.1%
; 3
 
0.1%
？ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6814
98.1%
] 77
 
1.1%
】 44
 
0.6%
」 14
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 6806
98.0%
[ 82
 
1.2%
【 44
 
0.6%
「 14
 
0.2%
Other Symbol
ValueCountFrequency (%)
○ 59
71.1%
㎡ 21
 
25.3%
℃ 2
 
2.4%
┸ 1
 
1.2%
Math Symbol
ValueCountFrequency (%)
~ 45
97.8%
> 1
 
2.2%
Space Separator
ValueCountFrequency (%)
22727
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 271
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94467
61.5%
Common 58796
38.3%
Latin 284
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 3992
 
4.2%
영 3164
 
3.3%
미 2667
 
2.8%
위 2438
 
2.6%
시 2220
 
2.4%
이 2084
 
2.2%
기 2051
 
2.2%
년 1914
 
2.0%
자 1756
 
1.9%
설 1576
 
1.7%
Other values (606) 70605
74.7%
Common
ValueCountFrequency (%)
22727
38.7%
) 6814
 
11.6%
( 6806
 
11.6%
2 5407
 
9.2%
1 3785
 
6.4%
0 3703
 
6.3%
. 2931
 
5.0%
, 943
 
1.6%
3 917
 
1.6%
: 856
 
1.5%
Other values (28) 3907
 
6.6%
Latin
ValueCountFrequency (%)
m 59
20.8%
g 50
17.6%
O 28
9.9%
x 24
8.5%
t 21
 
7.4%
k 19
 
6.7%
K 15
 
5.3%
B 12
 
4.2%
X 6
 
2.1%
A 6
 
2.1%
Other values (20) 44
15.5%
Han
ValueCountFrequency (%)
諮 1
50.0%
彭 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94465
61.5%
ASCII 58878
38.3%
None 117
 
0.1%
Geometric Shapes 59
 
< 0.1%
CJK Compat 21
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
Punctuation 2
 
< 0.1%
CJK 2
 
< 0.1%
Box Drawing 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22727
38.6%
) 6814
 
11.6%
( 6806
 
11.6%
2 5407
 
9.2%
1 3785
 
6.4%
0 3703
 
6.3%
. 2931
 
5.0%
, 943
 
1.6%
3 917
 
1.6%
: 856
 
1.5%
Other values (48) 3989
 
6.8%
Hangul
ValueCountFrequency (%)
업 3992
 
4.2%
영 3164
 
3.3%
미 2667
 
2.8%
위 2438
 
2.6%
시 2220
 
2.4%
이 2084
 
2.2%
기 2051
 
2.2%
년 1914
 
2.0%
자 1756
 
1.9%
설 1576
 
1.7%
Other values (605) 70603
74.7%
Geometric Shapes
ValueCountFrequency (%)
○ 59
100.0%
None
ValueCountFrequency (%)
【 44
37.6%
】 44
37.6%
」 14
 
12.0%
「 14
 
12.0%
？ 1
 
0.9%
CJK Compat
ValueCountFrequency (%)
㎡ 21
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 2
100.0%
Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
CJK
ValueCountFrequency (%)
諮 1
50.0%
彭 1
50.0%
Box Drawing
ValueCountFrequency (%)
┸ 1
100.0%

처분내용
Text

Distinct892
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T06:48:47.644933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length130
Median length88
Mean length6.5129
Min length2

Characters and Unicode

Total characters65129
Distinct characters227
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique526 ?
Unique (%)5.3%

Sample

1st row영업소폐쇄
2nd row()
3rd row()
4th row()
5th row()
ValueCountFrequency (%)
3745
28.0%
영업소폐쇄 1005
 
7.5%
과태료부과 1004
 
7.5%
영업정지 984
 
7.4%
시정명령 768
 
5.7%
과태료 336
 
2.5%
부과 300
 
2.2%
및 231
 
1.7%
시설개수명령 161
 
1.2%
영업정지2월 142
 
1.1%
Other values (919) 4684
35.1%
2024-05-04T06:48:48.750463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 5835
 
9.0%
( 5832
 
9.0%
과 4380
 
6.7%
3399
 
5.2%
정 2881
 
4.4%
영 2834
 
4.4%
업 2810
 
4.3%
0 2716
 
4.2%
부 2135
 
3.3%
2 1955
 
3.0%
Other values (217) 30352
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39098
60.0%
Decimal Number 9180
 
14.1%
Close Punctuation 5835
 
9.0%
Open Punctuation 5832
 
9.0%
Space Separator 3399
 
5.2%
Other Punctuation 1533
 
2.4%
Math Symbol 223
 
0.3%
Dash Punctuation 28
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 4380
 
11.2%
정 2881
 
7.4%
영 2834
 
7.2%
업 2810
 
7.2%
부 2135
 
5.5%
지 1954
 
5.0%
료 1946
 
5.0%
태 1944
 
5.0%
시 1515
 
3.9%
원 1314
 
3.4%
Other values (192) 15385
39.3%
Decimal Number
ValueCountFrequency (%)
0 2716
29.6%
2 1955
21.3%
1 1922
20.9%
5 613
 
6.7%
3 540
 
5.9%
4 425
 
4.6%
6 333
 
3.6%
8 262
 
2.9%
9 221
 
2.4%
7 193
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 1115
72.7%
, 201
 
13.1%
% 181
 
11.8%
/ 30
 
2.0%
' 2
 
0.1%
: 2
 
0.1%
* 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 219
98.2%
> 2
 
0.9%
+ 2
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 5835
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5832
100.0%
Space Separator
ValueCountFrequency (%)
3399
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39098
60.0%
Common 26031
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 4380
 
11.2%
정 2881
 
7.4%
영 2834
 
7.2%
업 2810
 
7.2%
부 2135
 
5.5%
지 1954
 
5.0%
료 1946
 
5.0%
태 1944
 
5.0%
시 1515
 
3.9%
원 1314
 
3.4%
Other values (192) 15385
39.3%
Common
ValueCountFrequency (%)
) 5835
22.4%
( 5832
22.4%
3399
13.1%
0 2716
10.4%
2 1955
 
7.5%
1 1922
 
7.4%
. 1115
 
4.3%
5 613
 
2.4%
3 540
 
2.1%
4 425
 
1.6%
Other values (15) 1679
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39095
60.0%
ASCII 26031
40.0%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 5835
22.4%
( 5832
22.4%
3399
13.1%
0 2716
10.4%
2 1955
 
7.5%
1 1922
 
7.4%
. 1115
 
4.3%
5 613
 
2.4%
3 540
 
2.1%
4 425
 
1.6%
Other values (15) 1679
 
6.5%
Hangul
ValueCountFrequency (%)
과 4380
 
11.2%
정 2881
 
7.4%
영 2834
 
7.2%
업 2810
 
7.2%
부 2135
 
5.5%
지 1954
 
5.0%
료 1946
 
5.0%
태 1944
 
5.0%
시 1515
 
3.9%
원 1314
 
3.4%
Other values (191) 15382
39.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%

처분기간
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct69
Distinct (%)1.8%
Missing6233
Missing (%)62.3%
Infinite0
Infinite (%)0.0%
Mean31.703212
Minimum0
Maximum900
Zeros1399
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:48:49.149639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15
Q330
95-th percentile90
Maximum900
Range900
Interquartile range (IQR)30

Descriptive statistics

Standard deviation75.820949
Coefficient of variation (CV)2.3915857
Kurtosis57.269009
Mean31.703212
Median Absolute Deviation (MAD)15
Skewness6.8750903
Sum119426
Variance5748.8163
MonotonicityNot monotonic
2024-05-04T06:48:50.065265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1399
 
14.0%
15 658
 
6.6%
60 461
 
4.6%
30 382
 
3.8%
7 254
 
2.5%
90 136
 
1.4%
10 44
 
0.4%
31 41
 
0.4%
300 32
 
0.3%
61 31
 
0.3%
Other values (59) 329
 
3.3%
(Missing) 6233
62.3%
ValueCountFrequency (%)
0 1399
14.0%
1 3
 
< 0.1%
2 2
 
< 0.1%
3 3
 
< 0.1%
4 3
 
< 0.1%
5 16
 
0.2%
6 1
 
< 0.1%
7 254
 
2.5%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
900 5
 
0.1%
830 1
 
< 0.1%
750 3
 
< 0.1%
680 1
 
< 0.1%
640 1
 
< 0.1%
600 28
0.3%
450 1
 
< 0.1%
300 32
0.3%
230 1
 
< 0.1%
200 1
 
< 0.1%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct2569
Distinct (%)39.6%
Missing3510
Missing (%)35.1%
Infinite0
Infinite (%)0.0%
Mean96.662296
Minimum0
Maximum10192.28
Zeros23
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:48:50.596980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.88
Q134.34
median70.79
Q3109.5
95-th percentile213.3735
Maximum10192.28
Range10192.28
Interquartile range (IQR)75.16

Descriptive statistics

Standard deviation184.87183
Coefficient of variation (CV)1.9125537
Kurtosis1392.2074
Mean96.662296
Median Absolute Deviation (MAD)37.79
Skewness28.060811
Sum627338.3
Variance34177.593
MonotonicityNot monotonic
2024-05-04T06:48:51.179081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 26
 
0.3%
97.42 24
 
0.2%
0.0 23
 
0.2%
153.4 19
 
0.2%
80.31 19
 
0.2%
19.8 19
 
0.2%
23.1 17
 
0.2%
59.4 17
 
0.2%
16.5 16
 
0.2%
18.76 15
 
0.1%
Other values (2559) 6295
62.9%
(Missing) 3510
35.1%
ValueCountFrequency (%)
0.0 23
0.2%
1.53 1
 
< 0.1%
2.4 3
 
< 0.1%
2.52 1
 
< 0.1%
3.3 1
 
< 0.1%
4.67 1
 
< 0.1%
5.21 1
 
< 0.1%
5.7 1
 
< 0.1%
6.0 1
 
< 0.1%
6.6 1
 
< 0.1%
ValueCountFrequency (%)
10192.28 1
 
< 0.1%
2284.02 1
 
< 0.1%
2069.0 1
 
< 0.1%
1982.99 4
< 0.1%
1868.2 1
 
< 0.1%
1667.39 3
< 0.1%
1580.61 3
< 0.1%
1382.02 6
0.1%
1367.5 1
 
< 0.1%
1336.13 1
 
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9973 
직영
 
14
(조합)위탁
 
13

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> 9973
99.7%
직영 14
 
0.1%
(조합)위탁 13
 
0.1%

Length

2024-05-04T06:48:51.639530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:48:52.035014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9973
99.7%
직영 14
 
0.1%
조합)위탁 13
 
0.1%

Interactions

2024-05-04T06:48:24.539258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:16.616922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:18.115034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:19.577995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:21.276501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:23.032776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:24.777566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:16.892659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:18.313763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:19.871215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:21.569259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:23.306391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:24.961248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:17.081773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:18.493776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:20.148928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:21.844578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:23.565026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:25.149022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:17.326616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:18.781945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:20.444048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:22.149394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:23.841445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:25.341043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:17.615119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:19.069181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:20.729943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:22.493369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:24.117504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:25.508022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:17.880609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:19.318118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:21.000858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:22.756737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:48:24.369122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T06:48:52.309270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.0000.7830.4380.6601.0000.0500.2500.0540.000
교부번호0.7831.0000.6360.7670.7820.0000.0850.1380.332
업종명0.4380.6361.0001.0000.4420.0000.0000.735NaN
업태명0.6600.7671.0001.0000.6590.0000.0000.7910.393
지도점검일자1.0000.7820.4420.6591.0000.0490.2500.0510.000
위반일자0.0500.0000.0000.0000.0491.000NaN0.000NaN
처분기간0.2500.0850.0000.0000.250NaN1.0000.000NaN
영업장면적(㎡)0.0540.1380.7350.7910.0510.0000.0001.000NaN
운영형태0.0000.332NaN0.3930.000NaNNaNNaN1.000
2024-05-04T06:48:52.643357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명운영형태
업종명1.0001.000
운영형태1.0001.000
2024-05-04T06:48:52.999225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.7021.0000.999-0.257-0.0760.1800.000
교부번호0.7021.0000.7030.701-0.0620.0320.3030.203
지도점검일자1.0000.7031.0000.999-0.255-0.0740.1820.000
위반일자0.9990.7010.9991.000-0.258-0.0740.0001.000
처분기간-0.257-0.062-0.255-0.2581.0000.0200.0001.000
영업장면적(㎡)-0.0760.032-0.074-0.0740.0201.0000.4311.000
업종명0.1800.3030.1820.0000.0000.4311.0001.000
운영형태0.0000.2030.0001.0001.0001.0001.0001.000

Missing values

2024-05-04T06:48:25.834438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T06:48:26.544276image/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.
2024-05-04T06:48:27.206649image/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
782430400002002112920020039592일반음식점호프/통닭파레스<NA>서울특별시 광진구 구의동 246번지 12호20021009처분확정영업소폐쇄제31조 제58조20021130청소년 유흥접객원 고용영업영업소폐쇄<NA><NA><NA>
296730400002000041119930039581일반음식점한식지리산참숯불갈비<NA>서울특별시 광진구 중곡동 산 18번지 74호<NA>처분확정()<NA>20000411()식육중량당가격미표시()046.22<NA>
83330400001993030919860039127일반음식점한식세바스챤<NA>서울특별시 광진구 화양동 산 226번지 0호19930309처분확정()<NA>19930309()()600116.26<NA>
448430400002000081119950039452일반음식점경양식뱅크<NA>서울특별시 광진구 구의동 산 248번지 88호20000623처분확정()<NA>20000623()()023.04<NA>
425630400001995121119950039461일반음식점한식강변식당<NA>서울특별시 광진구 자양동 산 49번지 295호19951211처분확정()<NA>19951211()()6049.62<NA>
135730400002003072519880039195일반음식점경양식올인(ALLIN)<NA>서울특별시 광진구 구의동 246번지 39호20030609처분확정시정명령식품위생법 제21조20030609객실 노래방기기 설치시정명령<NA>97.42<NA>
1124330400001994111719930039610단란주점단란주점만남단란주점<NA>서울특별시 광진구 자양동 산 607번지 14호19941117처분확정()<NA>19941117()()4566.24<NA>
629230400002000051219990039009일반음식점분식투미<NA>서울특별시 광진구 자양동 산 2번지 9호20000415처분확정()과징금28만원부과<NA>20000415()타업종표기 (간판)()과징금28만원부과065.62<NA>
1034030400002023031420180039535일반음식점한식마왕족발군자점서울특별시 광진구 능동로31길 16, 1층 (군자동)서울특별시 광진구 군자동 476번지 9호20230125처분확정과태료(20만원) 부과법 제101조제4항1호202301252021년 기존영업자 위생교육 미이수(1차)과태료(20만원) 부과<NA><NA><NA>
1444530400002009031020080039273즉석판매제조가공업즉석판매제조가공업(주)이앤지커피 카리부커피 이마트 자양점<NA>서울특별시 광진구 자양동 227번지 7호20090102처분확정시정명령식품위생법 제27조20090102위생교육 미수료시정명령<NA><NA><NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
876930400002010060320070039133일반음식점한식춘천골닭갈비<NA>서울특별시 광진구 군자동 374번지 7호 나동1층4,5호20100503처분확정과태료 16만원 부과식품위생법 제40조제1항및제101조20100503영업자 건강진단 미필과태료 16만원 부과<NA><NA><NA>
990130400002021031620140039111일반음식점정종/대포집/소주방경성포차서울특별시 광진구 동일로22길 64, 1층 (화양동)서울특별시 광진구 화양동 48번지 28호 (1층)20210204처분확정과태료 150만원 부과 및 1차 경고법 제83조제2항20210204일반음식점 핵심방역수칙 위반 (시설 소독대장 미작성- 1차, 2021. 2. 4. 20:06경)과태료 150만원 부과 및 1차 경고<NA><NA><NA>
1512330400002011022220100039525건강기능식품일반판매업영업장판매모세슈택<NA>서울특별시 광진구 자양동 605번지 18호 지하1층20101029처분확정영업정지1월건강기능식품에관한법률 제10조 및 제32조20101029판매사례품 또는 경품제공 등 사행심을 조장하여 제품을 판매하는 행위영업정지1월<NA>198.0<NA>
1025830400002020040120170039860일반음식점경양식치어스구의점서울특별시 광진구 아차산로 471, 1층 105호 (구의동)서울특별시 광진구 구의동 212번지 3호20200117처분확정영업정지법 제75조202001172020. 1. 17. 21:30경 청소년(정○○,만17세)의 신원을 확인하지 않고 주류(소주 2병, 맥주 1병)를 제공하여 광진경찰서에 적발됨 [1차 위반]영업정지<NA><NA><NA>
113330400002000081119870039261일반음식점경양식경향곱창<NA>서울특별시 광진구 구의동 산 229번지 45호20000623처분확정()<NA>20000623()()031.67<NA>
1213030400001997122219950039053단란주점단란주점카네기단란주점<NA>서울특별시 광진구 구의동 산 55번지 13호19971222처분확정()<NA>19971222()()<NA>102.01<NA>
1274930400002016062119960039778단란주점단란주점궁전노래주점서울특별시 광진구 능동로 380, (중곡동)서울특별시 광진구 중곡동 31번지 10호20150812처분확정시정명령법 제71조 및 법 제75조20150812업종 구분에 혼동을 줄 수 있는 사항을 표시함(궁전노래방)시정명령<NA>135.61<NA>
1198830400001996052719940039525단란주점단란주점물망초단란주점<NA>서울특별시 광진구 중곡동 산 37번지 4호19960527처분확정()<NA>19960527()()<NA>123.93<NA>
920930400002019062620090039391일반음식점일식호야초밥참치전문점서울특별시 광진구 능동로13길 36, (화양동,(1층))서울특별시 광진구 화양동 12번지 36호 (1층)20190521처분확정시정명령법 제101조제2항 제1호20190521상기 업소는 2019. 5. 21. 15:20경 서울시 민관 합동 점검 시 종사자 7명중 1명 소경준의 건강진단 미실시함(건강검진일: 2018.3.28.)시정명령<NA>50.19<NA>
1439730400002006042720020039068즉석판매제조가공업즉석판매제조가공업백세건강원<NA>서울특별시 광진구 군자동 469번지 21호 B동20060323처분확정영업소폐쇄식품위생법 제58조20060427영업시설의전부철거영업소폐쇄<NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
8230400002003111319970039581식품제조가공업식품제조가공업(주)갈릴리유통<NA>서울특별시 광진구 군자동 346번지 23호20031020처분확정품목제조정지식품위생법제19조20031020자가품질검사 시험항목 전부 미실시품목제조정지<NA><NA><NA>4
8330400002003111319970039581식품제조가공업식품제조가공업(주)갈릴리유통<NA>서울특별시 광진구 군자동 346번지 23호20031020처분확정품목제조정지식품위생법제31조20031020생산 및 작업기록에 관한 서류 미작성 및 원료수불관계서류 미작성품목제조정지<NA><NA><NA>4
8430400002003111319970039581식품제조가공업식품제조가공업(주)갈릴리유통<NA>서울특별시 광진구 군자동 346번지 23호20031020처분확정품목제조정지식품위생법제31조20031020자가품질검사 시헝항목 전부 미실시(10개품목)품목제조정지<NA><NA><NA>4
12730400002005022820040039560식품제조가공업식품제조가공업위드식품<NA>서울특별시 광진구 중곡동 238번지 4호20050216처분확정영업정지 1월식품위생법 제56조, 58조20050216허용한 식품첨가물외의 식품첨가물을 사용(삭카린나트륨 검출)영업정지 1월31<NA><NA>4
22330400002016031619920039451일반음식점호프/통닭정선생 건대점서울특별시 광진구 동일로22길 89, (화양동)서울특별시 광진구 화양동 9번지 86호20160219처분확정과태료부과법 제101조제2항제1호201512312015년 식품위생교육 미이수과태료부과<NA>59.58<NA>4
23830400002019062620090039391일반음식점일식호야초밥참치전문점서울특별시 광진구 능동로13길 36, (화양동,(1층))서울특별시 광진구 화양동 12번지 36호 (1층)20190521처분확정과태료 32만원(의견제출기한내 자진납부함)법 제71조, 법 제74조 및 법 제75조20190521상기 업소는 2019. 5. 21. 15:20경 서울시 민관 합동 점검 시 1층 뒷편 부분 가설물(가로 약 2.5m xt세러 약 2m)을 설치하여 영업장(객석)으로 사용함.과태료 32만원(의견제출기한내 자진납부함)<NA>27.54<NA>4
24030400002019062620090039391일반음식점일식호야초밥참치전문점서울특별시 광진구 능동로13길 36, (화양동,(1층))서울특별시 광진구 화양동 12번지 36호 (1층)20190521처분확정과태료 32만원(의견제출기한내 자진납부함)법 제71조, 법 제74조 및 법 제75조20190521상기 업소는 2019. 5. 21. 15:20경 서울시 민관 합동 점검 시 1층 뒷편 부분 가설물(가로 약 2.5m xt세러 약 2m)을 설치하여 영업장(객석)으로 사용함.과태료 32만원(의견제출기한내 자진납부함)<NA>271.08<NA>4
730400001994110519910039109일반음식점뷔페식겔럭시<NA>서울특별시 광진구 구의동 산 595번지 0호19941105처분확정()<NA>19941105()()<NA><NA><NA>3
1930400001996031819950039525단란주점단란주점동서울비지니스<NA>서울특별시 광진구 구의동 산 243번지 30호19960318처분확정()<NA>19960318()()<NA>78.37<NA>3
6630400002003072519880039195일반음식점경양식올인(ALLIN)<NA>서울특별시 광진구 구의동 246번지 39호20030609처분확정시설개수명령식품위생법 제21조20030609객실 노래방기기 설치시설개수명령<NA>97.42<NA>3