Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells15227
Missing cells (%)8.5%
Duplicate rows345
Duplicate rows (%)3.5%
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-10450/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 345 (3.5%) duplicate rowsDuplicates
업종명 is highly overall correlated with 운영형태High correlation
운영형태 is highly overall correlated with 교부번호 and 3 other fieldsHigh correlation
처분일자 is highly overall correlated with 교부번호 and 3 other fieldsHigh correlation
교부번호 is highly overall correlated with 처분일자 and 3 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
처분기간 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 운영형태High correlation
업종명 is highly imbalanced (52.1%)Imbalance
운영형태 is highly imbalanced (98.6%)Imbalance
소재지도로명 has 2458 (24.6%) missing valuesMissing
처분기간 has 7593 (75.9%) missing valuesMissing
영업장면적(㎡) has 5130 (51.3%) missing valuesMissing
교부번호 is highly skewed (γ1 = -67.39991101)Skewed
처분기간 has 1405 (14.1%) zerosZeros

Reproduction

Analysis started2024-05-10 23:00:43.347887
Analysis finished2024-05-10 23:01:00.479317
Duration17.13 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
3180000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 10000
100.0%

Length

2024-05-10T23:01:00.665981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:01:00.952783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2736
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20102124
Minimum19940111
Maximum20240325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:01:01.282503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940111
5-th percentile19981117
Q120050426
median20110905
Q320161011
95-th percentile20210730
Maximum20240325
Range300214
Interquartile range (IQR)110585

Descriptive statistics

Standard deviation74393.857
Coefficient of variation (CV)0.0037007958
Kurtosis-1.0093707
Mean20102124
Median Absolute Deviation (MAD)59311
Skewness-0.20717481
Sum2.0102124 × 1011
Variance5.534446 × 109
MonotonicityNot monotonic
2024-05-10T23:01:01.727623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060530 534
 
5.3%
20110905 202
 
2.0%
19990201 69
 
0.7%
20201110 45
 
0.4%
19960523 45
 
0.4%
20201125 43
 
0.4%
19990410 40
 
0.4%
19990326 39
 
0.4%
19990428 38
 
0.4%
19991216 33
 
0.3%
Other values (2726) 8912
89.1%
ValueCountFrequency (%)
19940111 2
 
< 0.1%
19941119 1
 
< 0.1%
19950205 1
 
< 0.1%
19951130 5
 
0.1%
19951201 1
 
< 0.1%
19951208 2
 
< 0.1%
19951215 5
 
0.1%
19951228 6
0.1%
19951229 14
0.1%
19951230 9
0.1%
ValueCountFrequency (%)
20240325 2
 
< 0.1%
20240307 2
 
< 0.1%
20240216 5
0.1%
20240214 2
 
< 0.1%
20240206 3
< 0.1%
20240201 2
 
< 0.1%
20240131 2
 
< 0.1%
20240130 1
 
< 0.1%
20240129 3
< 0.1%
20240123 6
0.1%

교부번호
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5339
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0006322 × 1010
Minimum1.990086 × 109
Maximum2.0230116 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:01:02.151797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.990086 × 109
5-th percentile1.9840086 × 1010
Q11.9950087 × 1010
median2.0010087 × 1010
Q32.0080086 × 1010
95-th percentile2.0160087 × 1010
Maximum2.0230116 × 1010
Range1.824003 × 1010
Interquartile range (IQR)1.2999974 × 108

Descriptive statistics

Standard deviation2.0555412 × 108
Coefficient of variation (CV)0.010274458
Kurtosis5902.6964
Mean2.0006322 × 1010
Median Absolute Deviation (MAD)60000461
Skewness-67.399911
Sum2.0006322 × 1014
Variance4.2252496 × 1016
MonotonicityNot monotonic
2024-05-10T23:01:02.527102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19690086003 43
 
0.4%
20010088222 42
 
0.4%
19860086479 31
 
0.3%
19990086402 29
 
0.3%
19820086019 28
 
0.3%
19940086208 26
 
0.3%
20050086016 26
 
0.3%
19890086272 26
 
0.3%
19920086860 21
 
0.2%
19960086822 20
 
0.2%
Other values (5329) 9708
97.1%
ValueCountFrequency (%)
1990086001 1
 
< 0.1%
19300086001 3
 
< 0.1%
19660086004 2
 
< 0.1%
19670086002 2
 
< 0.1%
19670086007 1
 
< 0.1%
19670086008 6
 
0.1%
19690086003 43
0.4%
19690086006 1
 
< 0.1%
19700086006 1
 
< 0.1%
19700086007 1
 
< 0.1%
ValueCountFrequency (%)
20230115861 1
< 0.1%
20230115775 1
< 0.1%
20230115274 2
< 0.1%
20230114982 1
< 0.1%
20230114353 2
< 0.1%
20230114286 1
< 0.1%
20220393339 2
< 0.1%
20220108121 2
< 0.1%
20220107655 1
< 0.1%
20220107451 1
< 0.1%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
6235 
단란주점
1202 
유흥주점영업
948 
휴게음식점
 
457
식품제조가공업
 
261
Other values (14)
897 

Length

Max length13
Median length5
Mean length5.2793
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row단란주점
2nd row일반음식점
3rd row일반음식점
4th row단란주점
5th row식품등 수입판매업

Common Values

ValueCountFrequency (%)
일반음식점 6235
62.4%
단란주점 1202
 
12.0%
유흥주점영업 948
 
9.5%
휴게음식점 457
 
4.6%
식품제조가공업 261
 
2.6%
식품등 수입판매업 240
 
2.4%
즉석판매제조가공업 171
 
1.7%
유통전문판매업 129
 
1.3%
제과점영업 105
 
1.1%
식품소분업 85
 
0.9%
Other values (9) 167
 
1.7%

Length

2024-05-10T23:01:03.024161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 6235
60.9%
단란주점 1202
 
11.7%
유흥주점영업 948
 
9.3%
휴게음식점 457
 
4.5%
식품제조가공업 261
 
2.5%
식품등 240
 
2.3%
수입판매업 240
 
2.3%
즉석판매제조가공업 171
 
1.7%
유통전문판매업 129
 
1.3%
제과점영업 105
 
1.0%
Other values (10) 252
 
2.5%

업태명
Text

Distinct68
Distinct (%)0.7%
Missing42
Missing (%)0.4%
Memory size156.2 KiB
2024-05-10T23:01:03.483535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length3.5908817
Min length2

Characters and Unicode

Total characters35758
Distinct characters150
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

Unique7 ?
Unique (%)0.1%

Sample

1st row단란주점
2nd row호프/통닭
3rd row경양식
4th row단란주점
5th row식품등 수입판매업
ValueCountFrequency (%)
한식 2535
24.7%
단란주점 1202
11.7%
분식 918
 
8.9%
호프/통닭 842
 
8.2%
룸살롱 703
 
6.8%
경양식 577
 
5.6%
기타 397
 
3.9%
중국식 386
 
3.8%
식품제조가공업 249
 
2.4%
식품등 240
 
2.3%
Other values (58) 2214
21.6%
2024-05-10T23:01:04.602498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 5379
 
15.0%
한 2535
 
7.1%
점 1437
 
4.0%
주 1359
 
3.8%
단 1216
 
3.4%
란 1202
 
3.4%
통 1161
 
3.2%
업 1084
 
3.0%
/ 1034
 
2.9%
닭 1011
 
2.8%
Other values (140) 18340
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33867
94.7%
Other Punctuation 1050
 
2.9%
Space Separator 305
 
0.9%
Close Punctuation 268
 
0.7%
Open Punctuation 268
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 5379
 
15.9%
한 2535
 
7.5%
점 1437
 
4.2%
주 1359
 
4.0%
단 1216
 
3.6%
란 1202
 
3.5%
통 1161
 
3.4%
업 1084
 
3.2%
닭 1011
 
3.0%
분 1003
 
3.0%
Other values (134) 16480
48.7%
Other Punctuation
ValueCountFrequency (%)
/ 1034
98.5%
, 15
 
1.4%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
305
100.0%
Close Punctuation
ValueCountFrequency (%)
) 268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33867
94.7%
Common 1891
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 5379
 
15.9%
한 2535
 
7.5%
점 1437
 
4.2%
주 1359
 
4.0%
단 1216
 
3.6%
란 1202
 
3.5%
통 1161
 
3.4%
업 1084
 
3.2%
닭 1011
 
3.0%
분 1003
 
3.0%
Other values (134) 16480
48.7%
Common
ValueCountFrequency (%)
/ 1034
54.7%
305
 
16.1%
) 268
 
14.2%
( 268
 
14.2%
, 15
 
0.8%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33867
94.7%
ASCII 1891
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 5379
 
15.9%
한 2535
 
7.5%
점 1437
 
4.2%
주 1359
 
4.0%
단 1216
 
3.6%
란 1202
 
3.5%
통 1161
 
3.4%
업 1084
 
3.2%
닭 1011
 
3.0%
분 1003
 
3.0%
Other values (134) 16480
48.7%
ASCII
ValueCountFrequency (%)
/ 1034
54.7%
305
 
16.1%
) 268
 
14.2%
( 268
 
14.2%
, 15
 
0.8%
. 1
 
0.1%

업소명
Text

Distinct5074
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:01:05.428787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length4.9986
Min length1

Characters and Unicode

Total characters49986
Distinct characters988
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3095 ?
Unique (%)30.9%

Sample

1st row오빠야
2nd row다온
3rd row오클럽
4th row아마존
5th row재민무역
ValueCountFrequency (%)
롯데제과(주 61
 
0.6%
주식회사 42
 
0.4%
해연판점 29
 
0.3%
삼성테스코(주)홈플러스영등포점 29
 
0.3%
코끼리 26
 
0.2%
동해골뱅이전문점 26
 
0.2%
갤러리 22
 
0.2%
여의도관광호텔나이트크럽 21
 
0.2%
서울지엔비 21
 
0.2%
두원푸드 19
 
0.2%
Other values (5282) 10336
97.2%
2024-05-10T23:01:06.954711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 1196
 
2.4%
이 1139
 
2.3%
주 966
 
1.9%
리 859
 
1.7%
( 855
 
1.7%
) 855
 
1.7%
점 773
 
1.5%
식 700
 
1.4%
636
 
1.3%
당 545
 
1.1%
Other values (978) 41462
82.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45499
91.0%
Uppercase Letter 1049
 
2.1%
Open Punctuation 855
 
1.7%
Close Punctuation 855
 
1.7%
Space Separator 636
 
1.3%
Lowercase Letter 481
 
1.0%
Decimal Number 476
 
1.0%
Other Punctuation 104
 
0.2%
Dash Punctuation 16
 
< 0.1%
Letter Number 12
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1196
 
2.6%
이 1139
 
2.5%
주 966
 
2.1%
리 859
 
1.9%
점 773
 
1.7%
식 700
 
1.5%
당 545
 
1.2%
라 501
 
1.1%
프 500
 
1.1%
비 487
 
1.1%
Other values (900) 37833
83.2%
Uppercase Letter
ValueCountFrequency (%)
E 108
 
10.3%
O 93
 
8.9%
C 85
 
8.1%
A 77
 
7.3%
S 75
 
7.1%
B 66
 
6.3%
M 53
 
5.1%
F 50
 
4.8%
L 47
 
4.5%
R 45
 
4.3%
Other values (16) 350
33.4%
Lowercase Letter
ValueCountFrequency (%)
e 81
16.8%
a 63
13.1%
i 45
9.4%
s 43
8.9%
n 42
8.7%
o 33
 
6.9%
g 22
 
4.6%
r 21
 
4.4%
t 20
 
4.2%
f 17
 
3.5%
Other values (15) 94
19.5%
Decimal Number
ValueCountFrequency (%)
0 127
26.7%
2 94
19.7%
1 55
11.6%
8 45
 
9.5%
7 44
 
9.2%
3 31
 
6.5%
6 25
 
5.3%
5 19
 
4.0%
4 18
 
3.8%
9 18
 
3.8%
Other Punctuation
ValueCountFrequency (%)
& 36
34.6%
. 33
31.7%
, 12
 
11.5%
' 7
 
6.7%
; 6
 
5.8%
？ 4
 
3.8%
! 3
 
2.9%
′ 1
 
1.0%
/ 1
 
1.0%
# 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 855
100.0%
Close Punctuation
ValueCountFrequency (%)
) 855
100.0%
Space Separator
ValueCountFrequency (%)
636
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Symbol
ValueCountFrequency (%)
★ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45398
90.8%
Common 2945
 
5.9%
Latin 1542
 
3.1%
Han 101
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1196
 
2.6%
이 1139
 
2.5%
주 966
 
2.1%
리 859
 
1.9%
점 773
 
1.7%
식 700
 
1.5%
당 545
 
1.2%
라 501
 
1.1%
프 500
 
1.1%
비 487
 
1.1%
Other values (864) 37732
83.1%
Latin
ValueCountFrequency (%)
E 108
 
7.0%
O 93
 
6.0%
C 85
 
5.5%
e 81
 
5.3%
A 77
 
5.0%
S 75
 
4.9%
B 66
 
4.3%
a 63
 
4.1%
M 53
 
3.4%
F 50
 
3.2%
Other values (42) 791
51.3%
Han
ValueCountFrequency (%)
士 18
17.8%
紳 18
17.8%
肉 8
 
7.9%
辛 5
 
5.0%
館 5
 
5.0%
面 4
 
4.0%
牛 3
 
3.0%
骨 3
 
3.0%
元 3
 
3.0%
天 2
 
2.0%
Other values (26) 32
31.7%
Common
ValueCountFrequency (%)
( 855
29.0%
) 855
29.0%
636
21.6%
0 127
 
4.3%
2 94
 
3.2%
1 55
 
1.9%
8 45
 
1.5%
7 44
 
1.5%
& 36
 
1.2%
. 33
 
1.1%
Other values (16) 165
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45398
90.8%
ASCII 4469
 
8.9%
CJK 101
 
0.2%
Number Forms 12
 
< 0.1%
None 4
 
< 0.1%
Punctuation 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 1196
 
2.6%
이 1139
 
2.5%
주 966
 
2.1%
리 859
 
1.9%
점 773
 
1.7%
식 700
 
1.5%
당 545
 
1.2%
라 501
 
1.1%
프 500
 
1.1%
비 487
 
1.1%
Other values (864) 37732
83.1%
ASCII
ValueCountFrequency (%)
( 855
19.1%
) 855
19.1%
636
14.2%
0 127
 
2.8%
E 108
 
2.4%
2 94
 
2.1%
O 93
 
2.1%
C 85
 
1.9%
e 81
 
1.8%
A 77
 
1.7%
Other values (64) 1458
32.6%
CJK
ValueCountFrequency (%)
士 18
17.8%
紳 18
17.8%
肉 8
 
7.9%
辛 5
 
5.0%
館 5
 
5.0%
面 4
 
4.0%
牛 3
 
3.0%
骨 3
 
3.0%
元 3
 
3.0%
天 2
 
2.0%
Other values (26) 32
31.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 12
100.0%
None
ValueCountFrequency (%)
？ 4
100.0%
Punctuation
ValueCountFrequency (%)
′ 1
100.0%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%

소재지도로명
Text

MISSING 

Distinct3753
Distinct (%)49.8%
Missing2458
Missing (%)24.6%
Memory size156.2 KiB
2024-05-10T23:01:07.482477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length63
Mean length34.142535
Min length23

Characters and Unicode

Total characters257503
Distinct characters373
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2198 ?
Unique (%)29.1%

Sample

1st row서울특별시 영등포구 디지털로 391, (대림동, 지하1층)
2nd row서울특별시 영등포구 의사당대로1길 25, (여의도동, 하남빌딩 지하1층 B125호)
3rd row서울특별시 영등포구 영등포로 164, (당산동1가)
4th row서울특별시 영등포구 디지털로64길 22-1, 1층 (대림동)
5th row서울특별시 영등포구 선유로49길 29, (양평동4가)
ValueCountFrequency (%)
서울특별시 7542
 
17.3%
영등포구 7542
 
17.3%
대림동 931
 
2.1%
1층 817
 
1.9%
신길동 733
 
1.7%
여의도동 672
 
1.5%
영등포동3가 585
 
1.3%
지하1층 470
 
1.1%
당산동3가 325
 
0.7%
영등포로 322
 
0.7%
Other values (2931) 23649
54.3%
2024-05-10T23:01:08.621671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36100
 
14.0%
, 12090
 
4.7%
영 10944
 
4.3%
1 10807
 
4.2%
포 9924
 
3.9%
등 9906
 
3.8%
동 8091
 
3.1%
) 7874
 
3.1%
( 7874
 
3.1%
서 7721
 
3.0%
Other values (363) 136172
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151307
58.8%
Decimal Number 39678
 
15.4%
Space Separator 36100
 
14.0%
Other Punctuation 12247
 
4.8%
Close Punctuation 7874
 
3.1%
Open Punctuation 7874
 
3.1%
Dash Punctuation 1618
 
0.6%
Uppercase Letter 592
 
0.2%
Math Symbol 162
 
0.1%
Lowercase Letter 51
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 10944
 
7.2%
포 9924
 
6.6%
등 9906
 
6.5%
동 8091
 
5.3%
서 7721
 
5.1%
시 7674
 
5.1%
로 7603
 
5.0%
울 7568
 
5.0%
구 7554
 
5.0%
별 7545
 
5.0%
Other values (313) 66777
44.1%
Uppercase Letter
ValueCountFrequency (%)
B 208
35.1%
C 70
 
11.8%
S 69
 
11.7%
A 69
 
11.7%
K 53
 
9.0%
F 23
 
3.9%
I 13
 
2.2%
D 13
 
2.2%
L 13
 
2.2%
M 11
 
1.9%
Other values (10) 50
 
8.4%
Decimal Number
ValueCountFrequency (%)
1 10807
27.2%
2 5686
14.3%
3 5531
13.9%
0 3395
 
8.6%
4 3302
 
8.3%
6 2482
 
6.3%
5 2392
 
6.0%
7 2346
 
5.9%
8 2055
 
5.2%
9 1682
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
c 17
33.3%
e 10
19.6%
k 8
15.7%
u 4
 
7.8%
r 3
 
5.9%
n 3
 
5.9%
l 2
 
3.9%
s 2
 
3.9%
t 1
 
2.0%
a 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 12090
98.7%
. 92
 
0.8%
？ 53
 
0.4%
/ 10
 
0.1%
@ 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
36100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7874
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7874
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1618
100.0%
Math Symbol
ValueCountFrequency (%)
~ 162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151307
58.8%
Common 105553
41.0%
Latin 643
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 10944
 
7.2%
포 9924
 
6.6%
등 9906
 
6.5%
동 8091
 
5.3%
서 7721
 
5.1%
시 7674
 
5.1%
로 7603
 
5.0%
울 7568
 
5.0%
구 7554
 
5.0%
별 7545
 
5.0%
Other values (313) 66777
44.1%
Latin
ValueCountFrequency (%)
B 208
32.3%
C 70
 
10.9%
S 69
 
10.7%
A 69
 
10.7%
K 53
 
8.2%
F 23
 
3.6%
c 17
 
2.6%
I 13
 
2.0%
D 13
 
2.0%
L 13
 
2.0%
Other values (20) 95
14.8%
Common
ValueCountFrequency (%)
36100
34.2%
, 12090
 
11.5%
1 10807
 
10.2%
) 7874
 
7.5%
( 7874
 
7.5%
2 5686
 
5.4%
3 5531
 
5.2%
0 3395
 
3.2%
4 3302
 
3.1%
6 2482
 
2.4%
Other values (10) 10412
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151307
58.8%
ASCII 106143
41.2%
None 53
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36100
34.0%
, 12090
 
11.4%
1 10807
 
10.2%
) 7874
 
7.4%
( 7874
 
7.4%
2 5686
 
5.4%
3 5531
 
5.2%
0 3395
 
3.2%
4 3302
 
3.1%
6 2482
 
2.3%
Other values (39) 11002
 
10.4%
Hangul
ValueCountFrequency (%)
영 10944
 
7.2%
포 9924
 
6.6%
등 9906
 
6.5%
동 8091
 
5.3%
서 7721
 
5.1%
시 7674
 
5.1%
로 7603
 
5.0%
울 7568
 
5.0%
구 7554
 
5.0%
별 7545
 
5.0%
Other values (313) 66777
44.1%
None
ValueCountFrequency (%)
？ 53
100.0%

소재지지번
Text

Distinct5086
Distinct (%)50.9%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-10T23:01:09.235736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length58
Mean length31.454236
Min length23

Characters and Unicode

Total characters314448
Distinct characters394
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2991 ?
Unique (%)29.9%

Sample

1st row서울특별시 영등포구 대림동 861번지 21호 지하1층
2nd row서울특별시 영등포구 여의도동 44번지 23호 하남빌딩 지하1층 B125호
3rd row서울특별시 영등포구 여의도동 산 37번지 0호 거평빌딩5층
4th row서울특별시 영등포구 당산동1가 6번지 0호
5th row서울특별시 영등포구 대림동 972번지 6호 1층
ValueCountFrequency (%)
서울특별시 9997
 
17.0%
영등포구 9997
 
17.0%
여의도동 2124
 
3.6%
산 1912
 
3.2%
대림동 1475
 
2.5%
신길동 1350
 
2.3%
영등포동3가 1173
 
2.0%
1호 1010
 
1.7%
0호 943
 
1.6%
1층 828
 
1.4%
Other values (2692) 28092
47.7%
2024-05-10T23:01:10.344149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73685
23.4%
1 13459
 
4.3%
영 12317
 
3.9%
포 12261
 
3.9%
등 12243
 
3.9%
지 12075
 
3.8%
호 10500
 
3.3%
동 10332
 
3.3%
서 10103
 
3.2%
시 10085
 
3.2%
Other values (384) 137388
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183173
58.3%
Space Separator 73685
23.4%
Decimal Number 54362
 
17.3%
Other Punctuation 909
 
0.3%
Dash Punctuation 796
 
0.3%
Uppercase Letter 537
 
0.2%
Open Punctuation 396
 
0.1%
Close Punctuation 396
 
0.1%
Math Symbol 143
 
< 0.1%
Lowercase Letter 51
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 12317
 
6.7%
포 12261
 
6.7%
등 12243
 
6.7%
지 12075
 
6.6%
호 10500
 
5.7%
동 10332
 
5.6%
서 10103
 
5.5%
시 10085
 
5.5%
울 10027
 
5.5%
구 10011
 
5.5%
Other values (333) 73219
40.0%
Uppercase Letter
ValueCountFrequency (%)
B 157
29.2%
S 70
13.0%
A 63
11.7%
C 63
11.7%
K 55
 
10.2%
F 17
 
3.2%
D 16
 
3.0%
M 16
 
3.0%
I 13
 
2.4%
L 12
 
2.2%
Other values (11) 55
 
10.2%
Decimal Number
ValueCountFrequency (%)
1 13459
24.8%
3 7407
13.6%
2 7204
13.3%
4 5905
10.9%
0 5220
 
9.6%
5 4245
 
7.8%
6 3330
 
6.1%
7 2793
 
5.1%
8 2457
 
4.5%
9 2342
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
c 17
33.3%
e 10
19.6%
k 8
15.7%
u 4
 
7.8%
n 3
 
5.9%
r 3
 
5.9%
l 2
 
3.9%
s 2
 
3.9%
t 1
 
2.0%
a 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 729
80.2%
. 112
 
12.3%
？ 53
 
5.8%
/ 13
 
1.4%
@ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
73685
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 796
100.0%
Open Punctuation
ValueCountFrequency (%)
( 396
100.0%
Close Punctuation
ValueCountFrequency (%)
) 396
100.0%
Math Symbol
ValueCountFrequency (%)
~ 143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 183173
58.3%
Common 130687
41.6%
Latin 588
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 12317
 
6.7%
포 12261
 
6.7%
등 12243
 
6.7%
지 12075
 
6.6%
호 10500
 
5.7%
동 10332
 
5.6%
서 10103
 
5.5%
시 10085
 
5.5%
울 10027
 
5.5%
구 10011
 
5.5%
Other values (333) 73219
40.0%
Latin
ValueCountFrequency (%)
B 157
26.7%
S 70
11.9%
A 63
10.7%
C 63
10.7%
K 55
 
9.4%
F 17
 
2.9%
c 17
 
2.9%
D 16
 
2.7%
M 16
 
2.7%
I 13
 
2.2%
Other values (21) 101
17.2%
Common
ValueCountFrequency (%)
73685
56.4%
1 13459
 
10.3%
3 7407
 
5.7%
2 7204
 
5.5%
4 5905
 
4.5%
0 5220
 
4.0%
5 4245
 
3.2%
6 3330
 
2.5%
7 2793
 
2.1%
8 2457
 
1.9%
Other values (10) 4982
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183172
58.3%
ASCII 131222
41.7%
None 53
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73685
56.2%
1 13459
 
10.3%
3 7407
 
5.6%
2 7204
 
5.5%
4 5905
 
4.5%
0 5220
 
4.0%
5 4245
 
3.2%
6 3330
 
2.5%
7 2793
 
2.1%
8 2457
 
1.9%
Other values (40) 5517
 
4.2%
Hangul
ValueCountFrequency (%)
영 12317
 
6.7%
포 12261
 
6.7%
등 12243
 
6.7%
지 12075
 
6.6%
호 10500
 
5.7%
동 10332
 
5.6%
서 10103
 
5.5%
시 10085
 
5.5%
울 10027
 
5.5%
구 10011
 
5.5%
Other values (332) 73218
40.0%
None
ValueCountFrequency (%)
？ 53
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3384
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20100966
Minimum19940111
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:01:10.746380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940111
5-th percentile19981019
Q120050282
median20110412
Q320160825
95-th percentile20210607
Maximum20240305
Range300194
Interquartile range (IQR)110542.5

Descriptive statistics

Standard deviation74432.608
Coefficient of variation (CV)0.0037029369
Kurtosis-1.0116929
Mean20100966
Median Absolute Deviation (MAD)59387.5
Skewness-0.20581244
Sum2.0100966 × 1011
Variance5.5402131 × 109
MonotonicityNot monotonic
2024-05-10T23:01:11.196565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110412 191
 
1.9%
20060414 93
 
0.9%
20200101 93
 
0.9%
20060403 90
 
0.9%
20060407 85
 
0.9%
20060408 76
 
0.8%
20060413 74
 
0.7%
20190221 56
 
0.6%
20060405 55
 
0.5%
20150102 52
 
0.5%
Other values (3374) 9135
91.3%
ValueCountFrequency (%)
19940111 2
 
< 0.1%
19940403 1
 
< 0.1%
19941119 1
 
< 0.1%
19950130 1
 
< 0.1%
19951101 1
 
< 0.1%
19951130 5
 
0.1%
19951208 2
 
< 0.1%
19951215 5
 
0.1%
19951228 6
0.1%
19951229 14
0.1%
ValueCountFrequency (%)
20240305 1
 
< 0.1%
20240224 1
 
< 0.1%
20240222 1
 
< 0.1%
20240205 1
 
< 0.1%
20240124 4
< 0.1%
20240123 1
 
< 0.1%
20240122 2
< 0.1%
20240115 3
< 0.1%
20240110 1
 
< 0.1%
20240105 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

2024-05-10T23:01:11.603158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:01:11.889070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%

처분명
Text

Distinct1530
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:01:12.256871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length62
Mean length9.91
Min length2

Characters and Unicode

Total characters99100
Distinct characters255
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

Unique987 ?
Unique (%)9.9%

Sample

1st row영업정지 1개월 갈음 과징금부과 240만원
2nd row과태료부과16만원
3rd row(과태료(구수입))
4th row영업허가취소
5th row시정명령
ValueCountFrequency (%)
시정명령 2315
 
16.9%
과태료부과 1112
 
8.1%
영업소폐쇄 1107
 
8.1%
영업정지 980
 
7.2%
시설개수명령 402
 
2.9%
부과 298
 
2.2%
및 249
 
1.8%
과징금 182
 
1.3%
갈음 175
 
1.3%
과징금부과 164
 
1.2%
Other values (1589) 6698
49.0%
2024-05-10T23:01:13.145871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7076
 
7.1%
정 5776
 
5.8%
시 4122
 
4.2%
업 4103
 
4.1%
영 4046
 
4.1%
0 3729
 
3.8%
( 3701
 
3.7%
) 3691
 
3.7%
3688
 
3.7%
1 3488
 
3.5%
Other values (245) 55680
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68282
68.9%
Decimal Number 16165
 
16.3%
Open Punctuation 3703
 
3.7%
Close Punctuation 3693
 
3.7%
Space Separator 3688
 
3.7%
Other Punctuation 3072
 
3.1%
Math Symbol 429
 
0.4%
Dash Punctuation 63
 
0.1%
Modifier Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7076
 
10.4%
정 5776
 
8.5%
시 4122
 
6.0%
업 4103
 
6.0%
영 4046
 
5.9%
명 3474
 
5.1%
령 3455
 
5.1%
부 3281
 
4.8%
료 3252
 
4.8%
태 3069
 
4.5%
Other values (220) 26628
39.0%
Decimal Number
ValueCountFrequency (%)
0 3729
23.1%
1 3488
21.6%
2 3273
20.2%
6 1015
 
6.3%
5 987
 
6.1%
4 958
 
5.9%
3 908
 
5.6%
8 692
 
4.3%
7 633
 
3.9%
9 482
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2583
84.1%
, 212
 
6.9%
: 197
 
6.4%
/ 39
 
1.3%
% 33
 
1.1%
* 7
 
0.2%
! 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3701
99.9%
[ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 3691
99.9%
] 2
 
0.1%
Space Separator
ValueCountFrequency (%)
3688
100.0%
Math Symbol
ValueCountFrequency (%)
~ 429
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68282
68.9%
Common 30818
31.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7076
 
10.4%
정 5776
 
8.5%
시 4122
 
6.0%
업 4103
 
6.0%
영 4046
 
5.9%
명 3474
 
5.1%
령 3455
 
5.1%
부 3281
 
4.8%
료 3252
 
4.8%
태 3069
 
4.5%
Other values (220) 26628
39.0%
Common
ValueCountFrequency (%)
0 3729
12.1%
( 3701
12.0%
) 3691
12.0%
3688
12.0%
1 3488
11.3%
2 3273
10.6%
. 2583
8.4%
6 1015
 
3.3%
5 987
 
3.2%
4 958
 
3.1%
Other values (15) 3705
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68258
68.9%
ASCII 30818
31.1%
Compat Jamo 24
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7076
 
10.4%
정 5776
 
8.5%
시 4122
 
6.0%
업 4103
 
6.0%
영 4046
 
5.9%
명 3474
 
5.1%
령 3455
 
5.1%
부 3281
 
4.8%
료 3252
 
4.8%
태 3069
 
4.5%
Other values (217) 26604
39.0%
ASCII
ValueCountFrequency (%)
0 3729
12.1%
( 3701
12.0%
) 3691
12.0%
3688
12.0%
1 3488
11.3%
2 3273
10.6%
. 2583
8.4%
6 1015
 
3.3%
5 987
 
3.2%
4 958
 
3.1%
Other values (15) 3705
12.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 22
91.7%
ㅅ 1
 
4.2%
ㅇ 1
 
4.2%

법적근거
Text

Distinct698
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:01:13.760559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length11.4036
Min length1

Characters and Unicode

Total characters114036
Distinct characters111
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)3.5%

Sample

1st row법 제75조
2nd row법 제101조제2항제1호
3rd row식품위생법
4th row법제37조
5th row식품위생법제19조
ValueCountFrequency (%)
법 5624
22.6%
식품위생법 4134
16.6%
제75조 2106
 
8.5%
제71조 1777
 
7.1%
및 1707
 
6.9%
제101조제2항제1호 688
 
2.8%
제74조 653
 
2.6%
제72조 418
 
1.7%
위반 413
 
1.7%
식품위생법제21조위반 388
 
1.6%
Other values (475) 6967
28.0%
2024-05-10T23:01:15.150357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14902
13.1%
제 13766
12.1%
법 12374
10.9%
조 11491
10.1%
1 7836
 
6.9%
위 6634
 
5.8%
7 6246
 
5.5%
식 5705
 
5.0%
품 5612
 
4.9%
생 5531
 
4.9%
Other values (101) 23939
21.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69643
61.1%
Decimal Number 27469
 
24.1%
Space Separator 14902
 
13.1%
Other Punctuation 1918
 
1.7%
Close Punctuation 52
 
< 0.1%
Open Punctuation 52
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 13766
19.8%
법 12374
17.8%
조 11491
16.5%
위 6634
9.5%
식 5705
8.2%
품 5612
8.1%
생 5531
7.9%
및 1723
 
2.5%
항 1565
 
2.2%
호 1314
 
1.9%
Other values (84) 3928
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 7836
28.5%
7 6246
22.7%
2 3490
12.7%
5 2561
 
9.3%
4 2028
 
7.4%
0 1944
 
7.1%
3 1709
 
6.2%
6 1104
 
4.0%
8 482
 
1.8%
9 69
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 1912
99.7%
. 6
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 51
98.1%
] 1
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 51
98.1%
[ 1
 
1.9%
Space Separator
ValueCountFrequency (%)
14902
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69643
61.1%
Common 44393
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 13766
19.8%
법 12374
17.8%
조 11491
16.5%
위 6634
9.5%
식 5705
8.2%
품 5612
8.1%
생 5531
7.9%
및 1723
 
2.5%
항 1565
 
2.2%
호 1314
 
1.9%
Other values (84) 3928
 
5.6%
Common
ValueCountFrequency (%)
14902
33.6%
1 7836
17.7%
7 6246
14.1%
2 3490
 
7.9%
5 2561
 
5.8%
4 2028
 
4.6%
0 1944
 
4.4%
, 1912
 
4.3%
3 1709
 
3.8%
6 1104
 
2.5%
Other values (7) 661
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69643
61.1%
ASCII 44393
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14902
33.6%
1 7836
17.7%
7 6246
14.1%
2 3490
 
7.9%
5 2561
 
5.8%
4 2028
 
4.6%
0 1944
 
4.4%
, 1912
 
4.3%
3 1709
 
3.8%
6 1104
 
2.5%
Other values (7) 661
 
1.5%
Hangul
ValueCountFrequency (%)
제 13766
19.8%
법 12374
17.8%
조 11491
16.5%
위 6634
9.5%
식 5705
8.2%
품 5612
8.1%
생 5531
7.9%
및 1723
 
2.5%
항 1565
 
2.2%
호 1314
 
1.9%
Other values (84) 3928
 
5.6%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3433
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20100923
Minimum19940111
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:01:15.535708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940111
5-th percentile19981019
Q120050303
median20110412
Q320160818
95-th percentile20210607
Maximum20240305
Range300194
Interquartile range (IQR)110515.25

Descriptive statistics

Standard deviation74419.207
Coefficient of variation (CV)0.0037022781
Kurtosis-1.010955
Mean20100923
Median Absolute Deviation (MAD)59302
Skewness-0.2048572
Sum2.0100923 × 1011
Variance5.5382184 × 109
MonotonicityNot monotonic
2024-05-10T23:01:15.971002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110412 192
 
1.9%
20200101 95
 
0.9%
20060414 93
 
0.9%
20190101 92
 
0.9%
20060403 90
 
0.9%
20060407 85
 
0.9%
20060408 76
 
0.8%
20060413 74
 
0.7%
20060405 53
 
0.5%
20150102 52
 
0.5%
Other values (3423) 9098
91.0%
ValueCountFrequency (%)
19940111 2
 
< 0.1%
19940403 1
 
< 0.1%
19941119 1
 
< 0.1%
19950130 1
 
< 0.1%
19951101 1
 
< 0.1%
19951130 5
 
0.1%
19951208 2
 
< 0.1%
19951215 5
 
0.1%
19951228 6
0.1%
19951229 14
0.1%
ValueCountFrequency (%)
20240305 1
 
< 0.1%
20240222 1
 
< 0.1%
20240207 1
 
< 0.1%
20240205 1
 
< 0.1%
20240124 4
< 0.1%
20240123 1
 
< 0.1%
20240122 2
< 0.1%
20240115 3
< 0.1%
20240110 1
 
< 0.1%
20240105 1
 
< 0.1%

위반내용
Text

Distinct3412
Distinct (%)34.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-10T23:01:16.539432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length241
Median length159
Mean length17.123512
Min length2

Characters and Unicode

Total characters171218
Distinct characters755
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2164 ?
Unique (%)21.6%

Sample

1st row청소년주류제공
2nd row종업원 건강진단 미필(2명중 1명)
3rd row(건강진단미필)
4th row영업시설의 전부를 철거한 경우(정당한 사유없이 6개월이상 휴업한 때)
5th row신고하지 않은 식품첨가물 검출
ValueCountFrequency (%)
건강진단 850
 
2.7%
영업장 757
 
2.4%
702
 
2.2%
미필 579
 
1.9%
및 570
 
1.8%
무단폐업 459
 
1.5%
위생교육 389
 
1.2%
종업원 381
 
1.2%
기존영업자 360
 
1.2%
외부영업 351
 
1.1%
Other values (4743) 25894
82.7%
2024-05-10T23:01:17.640014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21883
 
12.8%
업 7076
 
4.1%
영 5098
 
3.0%
( 4435
 
2.6%
) 4422
 
2.6%
미 4121
 
2.4%
단 3031
 
1.8%
위 2634
 
1.5%
기 2405
 
1.4%
시 2281
 
1.3%
Other values (745) 113832
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130028
75.9%
Space Separator 21883
 
12.8%
Decimal Number 7019
 
4.1%
Open Punctuation 4465
 
2.6%
Close Punctuation 4452
 
2.6%
Other Punctuation 2393
 
1.4%
Dash Punctuation 542
 
0.3%
Lowercase Letter 186
 
0.1%
Uppercase Letter 167
 
0.1%
Other Symbol 45
 
< 0.1%
Other values (3) 38
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 7076
 
5.4%
영 5098
 
3.9%
미 4121
 
3.2%
단 3031
 
2.3%
위 2634
 
2.0%
기 2405
 
1.8%
시 2281
 
1.8%
건 2131
 
1.6%
장 2086
 
1.6%
진 2069
 
1.6%
Other values (669) 97096
74.7%
Lowercase Letter
ValueCountFrequency (%)
g 62
33.3%
m 19
 
10.2%
l 17
 
9.1%
t 12
 
6.5%
c 9
 
4.8%
i 9
 
4.8%
a 8
 
4.3%
o 8
 
4.3%
k 8
 
4.3%
e 6
 
3.2%
Other values (9) 28
15.1%
Uppercase Letter
ValueCountFrequency (%)
E 27
16.2%
C 21
12.6%
M 14
8.4%
S 14
8.4%
O 12
 
7.2%
L 12
 
7.2%
A 11
 
6.6%
P 10
 
6.0%
H 8
 
4.8%
R 7
 
4.2%
Other values (9) 31
18.6%
Other Punctuation
ValueCountFrequency (%)
. 762
31.8%
/ 555
23.2%
: 517
21.6%
, 464
19.4%
? 24
 
1.0%
* 23
 
1.0%
？ 20
 
0.8%
% 17
 
0.7%
' 8
 
0.3%
; 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 2240
31.9%
2 1551
22.1%
0 1017
14.5%
6 496
 
7.1%
3 485
 
6.9%
4 326
 
4.6%
5 303
 
4.3%
8 210
 
3.0%
7 206
 
2.9%
9 185
 
2.6%
Other Symbol
ValueCountFrequency (%)
㎡ 26
57.8%
○ 7
 
15.6%
㈜ 6
 
13.3%
℃ 3
 
6.7%
□ 2
 
4.4%
㎎ 1
 
2.2%
Math Symbol
ValueCountFrequency (%)
~ 17
81.0%
+ 3
 
14.3%
= 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 4435
99.3%
[ 30
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 4422
99.3%
] 30
 
0.7%
Space Separator
ValueCountFrequency (%)
21883
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 542
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 16
100.0%
Modifier Letter
ValueCountFrequency (%)
ː 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130030
75.9%
Common 40831
 
23.8%
Latin 353
 
0.2%
Han 3
 
< 0.1%
Hiragana 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 7076
 
5.4%
영 5098
 
3.9%
미 4121
 
3.2%
단 3031
 
2.3%
위 2634
 
2.0%
기 2405
 
1.8%
시 2281
 
1.8%
건 2131
 
1.6%
장 2086
 
1.6%
진 2069
 
1.6%
Other values (666) 97098
74.7%
Latin
ValueCountFrequency (%)
g 62
17.6%
E 27
 
7.6%
C 21
 
5.9%
m 19
 
5.4%
l 17
 
4.8%
M 14
 
4.0%
S 14
 
4.0%
O 12
 
3.4%
t 12
 
3.4%
L 12
 
3.4%
Other values (28) 143
40.5%
Common
ValueCountFrequency (%)
21883
53.6%
( 4435
 
10.9%
) 4422
 
10.8%
1 2240
 
5.5%
2 1551
 
3.8%
0 1017
 
2.5%
. 762
 
1.9%
/ 555
 
1.4%
- 542
 
1.3%
: 517
 
1.3%
Other values (27) 2907
 
7.1%
Han
ValueCountFrequency (%)
彭 1
33.3%
肉 1
33.3%
諮 1
33.3%
Hiragana
ValueCountFrequency (%)
ち 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130011
75.9%
ASCII 41123
 
24.0%
CJK Compat 27
 
< 0.1%
None 26
 
< 0.1%
Compat Jamo 13
 
< 0.1%
Geometric Shapes 9
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%
CJK 3
 
< 0.1%
Punctuation 1
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21883
53.2%
( 4435
 
10.8%
) 4422
 
10.8%
1 2240
 
5.4%
2 1551
 
3.8%
0 1017
 
2.5%
. 762
 
1.9%
/ 555
 
1.3%
- 542
 
1.3%
: 517
 
1.3%
Other values (57) 3199
 
7.8%
Hangul
ValueCountFrequency (%)
업 7076
 
5.4%
영 5098
 
3.9%
미 4121
 
3.2%
단 3031
 
2.3%
위 2634
 
2.0%
기 2405
 
1.8%
시 2281
 
1.8%
건 2131
 
1.6%
장 2086
 
1.6%
진 2069
 
1.6%
Other values (664) 97079
74.7%
CJK Compat
ValueCountFrequency (%)
㎡ 26
96.3%
㎎ 1
 
3.7%
None
ValueCountFrequency (%)
？ 20
76.9%
㈜ 6
 
23.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 13
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 7
77.8%
□ 2
 
22.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%
CJK
ValueCountFrequency (%)
彭 1
33.3%
肉 1
33.3%
諮 1
33.3%
Modifier Letters
ValueCountFrequency (%)
ː 1
100.0%
Hiragana
ValueCountFrequency (%)
ち 1
100.0%

처분내용
Text

Distinct1530
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:01:18.090464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length62
Mean length9.91
Min length2

Characters and Unicode

Total characters99100
Distinct characters255
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

Unique987 ?
Unique (%)9.9%

Sample

1st row영업정지 1개월 갈음 과징금부과 240만원
2nd row과태료부과16만원
3rd row(과태료(구수입))
4th row영업허가취소
5th row시정명령
ValueCountFrequency (%)
시정명령 2315
 
16.9%
과태료부과 1112
 
8.1%
영업소폐쇄 1107
 
8.1%
영업정지 980
 
7.2%
시설개수명령 402
 
2.9%
부과 298
 
2.2%
및 249
 
1.8%
과징금 182
 
1.3%
갈음 175
 
1.3%
과징금부과 164
 
1.2%
Other values (1589) 6698
49.0%
2024-05-10T23:01:18.986633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7076
 
7.1%
정 5776
 
5.8%
시 4122
 
4.2%
업 4103
 
4.1%
영 4046
 
4.1%
0 3729
 
3.8%
( 3701
 
3.7%
) 3691
 
3.7%
3688
 
3.7%
1 3488
 
3.5%
Other values (245) 55680
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68282
68.9%
Decimal Number 16165
 
16.3%
Open Punctuation 3703
 
3.7%
Close Punctuation 3693
 
3.7%
Space Separator 3688
 
3.7%
Other Punctuation 3072
 
3.1%
Math Symbol 429
 
0.4%
Dash Punctuation 63
 
0.1%
Modifier Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7076
 
10.4%
정 5776
 
8.5%
시 4122
 
6.0%
업 4103
 
6.0%
영 4046
 
5.9%
명 3474
 
5.1%
령 3455
 
5.1%
부 3281
 
4.8%
료 3252
 
4.8%
태 3069
 
4.5%
Other values (220) 26628
39.0%
Decimal Number
ValueCountFrequency (%)
0 3729
23.1%
1 3488
21.6%
2 3273
20.2%
6 1015
 
6.3%
5 987
 
6.1%
4 958
 
5.9%
3 908
 
5.6%
8 692
 
4.3%
7 633
 
3.9%
9 482
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2583
84.1%
, 212
 
6.9%
: 197
 
6.4%
/ 39
 
1.3%
% 33
 
1.1%
* 7
 
0.2%
! 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3701
99.9%
[ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 3691
99.9%
] 2
 
0.1%
Space Separator
ValueCountFrequency (%)
3688
100.0%
Math Symbol
ValueCountFrequency (%)
~ 429
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68282
68.9%
Common 30818
31.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7076
 
10.4%
정 5776
 
8.5%
시 4122
 
6.0%
업 4103
 
6.0%
영 4046
 
5.9%
명 3474
 
5.1%
령 3455
 
5.1%
부 3281
 
4.8%
료 3252
 
4.8%
태 3069
 
4.5%
Other values (220) 26628
39.0%
Common
ValueCountFrequency (%)
0 3729
12.1%
( 3701
12.0%
) 3691
12.0%
3688
12.0%
1 3488
11.3%
2 3273
10.6%
. 2583
8.4%
6 1015
 
3.3%
5 987
 
3.2%
4 958
 
3.1%
Other values (15) 3705
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68258
68.9%
ASCII 30818
31.1%
Compat Jamo 24
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7076
 
10.4%
정 5776
 
8.5%
시 4122
 
6.0%
업 4103
 
6.0%
영 4046
 
5.9%
명 3474
 
5.1%
령 3455
 
5.1%
부 3281
 
4.8%
료 3252
 
4.8%
태 3069
 
4.5%
Other values (217) 26604
39.0%
ASCII
ValueCountFrequency (%)
0 3729
12.1%
( 3701
12.0%
) 3691
12.0%
3688
12.0%
1 3488
11.3%
2 3273
10.6%
. 2583
8.4%
6 1015
 
3.3%
5 987
 
3.2%
4 958
 
3.1%
Other values (15) 3705
12.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 22
91.7%
ㅅ 1
 
4.2%
ㅇ 1
 
4.2%

처분기간
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct22
Distinct (%)0.9%
Missing7593
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean4.3834649
Minimum0
Maximum29
Zeros1405
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:01:19.295358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile15
Maximum29
Range29
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.3317492
Coefficient of variation (CV)1.4444622
Kurtosis0.20735152
Mean4.3834649
Median Absolute Deviation (MAD)0
Skewness1.1927583
Sum10551
Variance40.091048
MonotonicityNot monotonic
2024-05-10T23:01:19.603674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 1405
 
14.1%
15 405
 
4.0%
7 386
 
3.9%
1 95
 
0.9%
20 30
 
0.3%
5 18
 
0.2%
25 15
 
0.1%
10 11
 
0.1%
2 9
 
0.1%
3 8
 
0.1%
Other values (12) 25
 
0.2%
(Missing) 7593
75.9%
ValueCountFrequency (%)
0 1405
14.1%
1 95
 
0.9%
2 9
 
0.1%
3 8
 
0.1%
5 18
 
0.2%
6 1
 
< 0.1%
7 386
 
3.9%
8 2
 
< 0.1%
10 11
 
0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
29 3
 
< 0.1%
25 15
 
0.1%
23 1
 
< 0.1%
22 6
 
0.1%
21 2
 
< 0.1%
20 30
 
0.3%
19 3
 
< 0.1%
18 1
 
< 0.1%
17 2
 
< 0.1%
15 405
4.0%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2322
Distinct (%)47.7%
Missing5130
Missing (%)51.3%
Infinite0
Infinite (%)0.0%
Mean111.08162
Minimum0
Maximum3780.18
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:01:20.001788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20
Q141.04
median74.91
Q3119.16
95-th percentile316.11
Maximum3780.18
Range3780.18
Interquartile range (IQR)78.12

Descriptive statistics

Standard deviation162.2901
Coefficient of variation (CV)1.4609987
Kurtosis98.019249
Mean111.08162
Median Absolute Deviation (MAD)37.775
Skewness7.6179058
Sum540967.47
Variance26338.076
MonotonicityNot monotonic
2024-05-10T23:01:20.466398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
543.53 26
 
0.3%
56.1 24
 
0.2%
117.72 21
 
0.2%
66.0 18
 
0.2%
62.62 16
 
0.2%
0.0 15
 
0.1%
49.5 14
 
0.1%
27.88 13
 
0.1%
119.16 13
 
0.1%
93.62 13
 
0.1%
Other values (2312) 4697
47.0%
(Missing) 5130
51.3%
ValueCountFrequency (%)
0.0 15
0.1%
3.56 1
 
< 0.1%
5.0 1
 
< 0.1%
6.6 1
 
< 0.1%
7.4 1
 
< 0.1%
7.5 2
 
< 0.1%
7.59 1
 
< 0.1%
8.28 1
 
< 0.1%
8.68 1
 
< 0.1%
9.1 3
 
< 0.1%
ValueCountFrequency (%)
3780.18 1
 
< 0.1%
2534.23 1
 
< 0.1%
2195.21 1
 
< 0.1%
1867.0 2
< 0.1%
1850.96 1
 
< 0.1%
1590.54 2
< 0.1%
1550.0 3
< 0.1%
1542.08 3
< 0.1%
1537.89 2
< 0.1%
1429.08 2
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9980 
직영
 
14
(조합)위탁
 
6

Length

Max length6
Median length4
Mean length3.9984
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> 9980
99.8%
직영 14
 
0.1%
(조합)위탁 6
 
0.1%

Length

2024-05-10T23:01:20.861061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:01:21.058636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9980
99.8%
직영 14
 
0.1%
조합)위탁 6
 
0.1%

Interactions

2024-05-10T23:00:57.271693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:49.218432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:50.838529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:52.311871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:53.679311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:55.557287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:57.552577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:49.479697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:51.129333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:52.507270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:53.865766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:55.842955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:57.842932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:49.759204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:51.412844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:52.771539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:54.425366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:56.126845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:58.132644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:50.040517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:51.702382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:53.060504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:54.716523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:56.404235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:58.418139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:50.316586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:51.926449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:53.287881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:54.997508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:56.680391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:58.692777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:50.551993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:52.117695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:53.477380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:55.273647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:00:56.992336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:01:21.214921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.000NaN0.4450.5861.0001.0000.7640.0910.136
교부번호NaN1.000NaNNaNNaNNaNNaNNaNNaN
업종명0.445NaN1.0001.0000.4450.4420.4530.324NaN
업태명0.586NaN1.0001.0000.5850.5840.5970.6440.000
지도점검일자1.000NaN0.4450.5851.0001.0000.7620.0980.136
위반일자1.000NaN0.4420.5841.0001.0000.7620.0980.136
처분기간0.764NaN0.4530.5970.7620.7621.0000.000NaN
영업장면적(㎡)0.091NaN0.3240.6440.0980.0980.0001.000NaN
운영형태0.136NaNNaN0.0000.1360.136NaNNaN1.000
2024-05-10T23:01:21.527624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명운영형태
업종명1.0001.000
운영형태1.0001.000
2024-05-10T23:01:21.780710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.5561.0000.9990.6100.0340.1830.111
교부번호0.5561.0000.5560.5560.4020.0770.0001.000
지도점검일자1.0000.5561.0001.0000.6090.0340.1830.111
위반일자0.9990.5561.0001.0000.6090.0340.1820.111
처분기간0.6100.4020.6090.6091.0000.0300.1961.000
영업장면적(㎡)0.0340.0770.0340.0340.0301.0000.1521.000
업종명0.1830.0000.1830.1820.1960.1521.0001.000
운영형태0.1111.0000.1110.1111.0001.0001.0001.000

Missing values

2024-05-10T23:00:59.117420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:00:59.827564image/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.
2024-05-10T23:01:00.213149image/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
2431800002024013019980086014단란주점단란주점오빠야서울특별시 영등포구 디지털로 391, (대림동, 지하1층)서울특별시 영등포구 대림동 861번지 21호 지하1층20231229처분확정영업정지 1개월 갈음 과징금부과 240만원법 제75조20231229청소년주류제공영업정지 1개월 갈음 과징금부과 240만원<NA><NA><NA>
125931800002020010320140086757일반음식점호프/통닭다온서울특별시 영등포구 의사당대로1길 25, (여의도동, 하남빌딩 지하1층 B125호)서울특별시 영등포구 여의도동 44번지 23호 하남빌딩 지하1층 B125호20191217처분확정과태료부과16만원법 제101조제2항제1호20191217종업원 건강진단 미필(2명중 1명)과태료부과16만원<NA><NA><NA>
1088531800001999042719810086061일반음식점경양식오클럽<NA>서울특별시 영등포구 여의도동 산 37번지 0호 거평빌딩5층19990305처분확정(과태료(구수입))식품위생법19990305(건강진단미필)(과태료(구수입))0475.95<NA>
535231800002012070619940087138단란주점단란주점아마존서울특별시 영등포구 영등포로 164, (당산동1가)서울특별시 영등포구 당산동1가 6번지 0호20120604처분확정영업허가취소법제37조20120604영업시설의 전부를 철거한 경우(정당한 사유없이 6개월이상 휴업한 때)영업허가취소<NA>39.9<NA>
424631800002014042520130086842식품등 수입판매업식품등 수입판매업재민무역서울특별시 영등포구 디지털로64길 22-1, 1층 (대림동)서울특별시 영등포구 대림동 972번지 6호 1층20131202처분확정시정명령식품위생법제19조20131202신고하지 않은 식품첨가물 검출시정명령<NA><NA><NA>
867231800002005112319980086047일반음식점한식장군주먹고기서울특별시 영등포구 선유로49길 29, (양평동4가)서울특별시 영등포구 양평동4가 91번지 0호20050422처분확정영업정지1월갈음과징금660만원으로변경식품위생법제21조20050721영업장무단확장2차영업정지1월갈음과징금660만원으로변경<NA><NA><NA>
1110831800001999020119930086717단란주점단란주점양주전<NA>서울특별시 영등포구 여의도동 산 44번지 13호 3 충무빌딩-30119981111처분확정(영업정지)영업정지2월식품위생법19981111(유흥주점영업행위를한때)유흥형태영업행위(영업정지)영업정지2월0<NA><NA>
901631800002004080520020086297일반음식점한식시골밥상서울특별시 영등포구 영등포로36길 10-11, (영등포동4가)서울특별시 영등포구 영등포동4가 133번지20040708처분확정영업소폐쇄식품위생법제58조20040707정당한 사유없이 계속하여 6월이상 휴업영업소폐쇄<NA><NA><NA>
635731800002010100820010088222유통전문판매업유통전문판매업삼성테스코(주)홈플러스영등포점서울특별시 영등포구 당산로 42, (문래동3가)서울특별시 영등포구 문래동3가 55번지 3호20100721처분확정시정명령법 제71조20100721표시기준 위반시정명령<NA><NA><NA>
265831800002017051820020086471유흥주점영업룸살롱승리서울특별시 영등포구 영등포로 370, (신길동)서울특별시 영등포구 신길동 95번지 62호20170427처분확정과태료부과 50만원법 제101조제2항제1호20170427종사자 건강진단 미필 및 명부미비치과태료부과 50만원<NA><NA><NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
561231800002011122720110087019일반음식점한식영등포식당<NA>서울특별시 영등포구 당산동3가 386번지 3호 비동 지상5층(일부)20111028처분확정시정명령식품위생법 제37조20111028영업신고된 상호 및 업종 미표시시정명령<NA><NA><NA>
648031800002010060119970086096일반음식점한식장충동 왕족발 보쌈 본점서울특별시 영등포구 도림로47길 22, (대림동)서울특별시 영등포구 대림동 766번지 5호20100420처분확정과태료부과법 제40조20100420건강진단미필영업(1/4명)과태료부과<NA>40.42<NA>
1057231800001999101419950086409일반음식점한식풍년식당<NA>서울특별시 영등포구 당산동6가 산 3번지 12호19990914처분확정(시정명령)시정명령(즉시)식품위생법19990914(기타사항을위반한때)식품용기보관 부적정(시정명령)시정명령(즉시)029.58<NA>
186831800002019012120170086175제과점영업제과점영업웰빙쌀빵서울특별시 영등포구 양평로 40, 2층 (당산동6가, 당산역9호선)서울특별시 영등포구 당산동6가 227번지 1호20190117처분확정과태료16만원부과법 제101조제2항제1호201901012018년도 기존영업자 위생교육 미이수과태료16만원부과<NA><NA><NA>
84231800002021020220140086222일반음식점한식돼지집서울특별시 영등포구 선유로47길 6, (양평동4가, 지상1층)서울특별시 영등포구 양평동4가 34번지 9호 지상1층20210108처분확정과태료부과 8만원법 제101조제2항 제1호20210108영업자 건강진단 미필과태료부과 8만원<NA><NA><NA>
364731800002015041520130087220일반음식점중국식(주)안도오리목서울특별시 영등포구 도림로38길 6-1, (대림동, 1층 일부)서울특별시 영등포구 대림동 1057번지 31호 1층 일부20150226처분확정시정명령(영업장 면적 변경 즉시 신고)법 제71조, 법 제72조 및 법 제75조20150226영업장 면적 변경 미신고시정명령(영업장 면적 변경 즉시 신고)<NA><NA><NA>
181731800002019021319970086976일반음식점호프/통닭호프데이서울특별시 영등포구 도신로 120, (신길동)서울특별시 영등포구 신길동 289번지 6호20181221처분확정영업정지1개월 갈음 과징금480만원부과법 제75조20181221청소년 주류제공영업정지1개월 갈음 과징금480만원부과<NA>79.2<NA>
432331800002014030320020086155식품소분업식품소분업서울식품서울특별시 영등포구 가마산로 364, (대림동,성락빌딩 지하101호)서울특별시 영등포구 대림동 682번지 2호 성락빌딩 지하101호20140212처분확정시정명령식품위생법 제10조위반20120212식품 포장재질 미표시시정명령<NA><NA><NA>
740631800002007122420070086570일반음식점까페다소니서울특별시 영등포구 국회대로72길 21, (여의도동,지하1층)서울특별시 영등포구 여의도동 13번지 24호 지하1층20071113처분확정과태료부과50만원법제31조20071113종사원건강진단미필과태료부과50만원<NA>76.2<NA>
1084431800001999042819950086271단란주점단란주점리베<NA>서울특별시 영등포구 여의도동 산 14번지 28호 26.28호 장덕빌딩지하105호19990305처분확정(영업정지)영업정지2월식품위생법19990305(유흥주점영업행위를한때)(영업정지)영업정지2월069.02<NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
2431800002003042919890086272유흥주점영업룸살롱여의도관광호텔나이트크럽서울특별시 영등포구 은행로 62, (여의도동)서울특별시 영등포구 여의도동 10번지 3호20030403처분확정과태료부과(종업원건강진단미필 1/19 ), 40만원.식품위생법제31조20031010유통기한지난식품(스모크햄)보관과태료부과(종업원건강진단미필 1/19 ), 40만원.<NA>543.53<NA>4
3031800002004022019890086272유흥주점영업룸살롱여의도관광호텔나이트크럽서울특별시 영등포구 은행로 62, (여의도동)서울특별시 영등포구 여의도동 10번지 3호20030403처분확정과징금부과식품위생법제31조20031010유통기한지난식품(스모크햄)보관과징금부과15543.53<NA>4
4631800002006062319940086208일반음식점한식동해골뱅이전문점서울특별시 영등포구 국제금융로8길 27-9, 103동 비호 (여의도동,동북빌딩)서울특별시 영등포구 여의도동 45번지 20호 103 동북빌딩-비20060607처분확정과징금420만원식품위생법제22조20060607영업장무단확장과징금420만원7117.72<NA>4
6831800002008060419690086003식품제조가공업식품제조가공업롯데제과(주)<NA>서울특별시 영등포구 양평동4가 20번지20080515처분확정시정명령식품위생법 제7조20080508이물검출 - 제품명 : 가나마일드 - 이물종류 : 섬유시정명령<NA><NA><NA>4
7131800002008070920010088222유통전문판매업유통전문판매업삼성테스코(주)홈플러스영등포점서울특별시 영등포구 당산로 42, (문래동3가)서울특별시 영등포구 문래동3가 55번지 3호20080630처분확정품목제조정지 15일식품위생법 제7조20080630대장균군 검출제출 유통전문판매 - 제품명 : 웰빙플러스 양배추샐러드 (130g) 유통기한 `08.7.1. - 제품명 : 웰빙플러스 양배추샐러드 (250g) 유통기한 `08.7.2. - 제조원 : (주)싱싱원품목제조정지 15일15<NA><NA>4
7231800002008073120010088222유통전문판매업유통전문판매업삼성테스코(주)홈플러스영등포점서울특별시 영등포구 당산로 42, (문래동3가)서울특별시 영등포구 문래동3가 55번지 3호20080630처분확정품목제조정지식품위생법 제7조20080630대장균군 검출제출 유통전문판매 - 제품명 : 웰빙플러스 양배추샐러드 (130g) 유통기한 `08.7.1. - 제품명 : 웰빙플러스 양배추샐러드 (250g) 유통기한 `08.7.2. - 제조원 : (주)싱싱원품목제조정지15<NA><NA>4
7431800002008090319940086208일반음식점한식동해골뱅이전문점서울특별시 영등포구 국제금융로8길 27-9, (여의도동,동북빌딩 103-A ,103-B ,101-A ,101-B)서울특별시 영등포구 여의도동 45번지 20호 동북빌딩 103-A ,103-B ,101-A ,101-B20080708처분확정시정명령법제22조위반20080708영업장무단확장시정명령<NA>117.72<NA>4
8831800002009072120050086016유흥주점영업룸살롱코끼리서울특별시 영등포구 영중로10길 36, (영등포동3가,지하1층)서울특별시 영등포구 영등포동3가 14번지 4호 지하1층20090615처분확정시정명령(즉시)식위58조20090615종업원명부 미기재시정명령(즉시)<NA>60.23<NA>4
8931800002009072120050086016유흥주점영업룸살롱코끼리서울특별시 영등포구 영중로10길 36, (영등포동3가,지하1층)서울특별시 영등포구 영등포동3가 14번지 4호 지하1층20090615처분확정시정명령(즉시)식위58조20090615종업원명부 미기재시정명령(즉시)<NA>162.75<NA>4
9031800002009072120050086016유흥주점영업룸살롱코끼리서울특별시 영등포구 영중로10길 36, (영등포동3가,지하1층)서울특별시 영등포구 영등포동3가 14번지 4호 지하1층20090615처분확정시정명령(즉시)식위58조20090615종업원명부 미기재시정명령(즉시)<NA>165.7<NA>4