Overview

Dataset statistics

Number of variables44
Number of observations378
Missing cells3392
Missing cells (%)20.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory139.3 KiB
Average record size in memory377.3 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-18405/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
남성종사자수 is highly imbalanced (53.4%)Imbalance
영업장주변구분명 is highly imbalanced (65.4%)Imbalance
등급구분명 is highly imbalanced (71.6%)Imbalance
총인원 is highly imbalanced (77.1%)Imbalance
본사종업원수 is highly imbalanced (75.9%)Imbalance
공장사무직종업원수 is highly imbalanced (75.9%)Imbalance
공장판매직종업원수 is highly imbalanced (75.9%)Imbalance
공장생산직종업원수 is highly imbalanced (75.9%)Imbalance
보증액 is highly imbalanced (75.9%)Imbalance
월세액 is highly imbalanced (75.9%)Imbalance
다중이용업소여부 is highly imbalanced (90.7%)Imbalance
전통업소지정번호 is highly imbalanced (97.4%)Imbalance
인허가취소일자 has 378 (100.0%) missing valuesMissing
폐업일자 has 137 (36.2%) missing valuesMissing
휴업시작일자 has 378 (100.0%) missing valuesMissing
휴업종료일자 has 378 (100.0%) missing valuesMissing
재개업일자 has 378 (100.0%) missing valuesMissing
전화번호 has 174 (46.0%) missing valuesMissing
소재지면적 has 7 (1.9%) missing valuesMissing
도로명주소 has 72 (19.0%) missing valuesMissing
도로명우편번호 has 80 (21.2%) missing valuesMissing
좌표정보(X) has 10 (2.6%) missing valuesMissing
좌표정보(Y) has 10 (2.6%) missing valuesMissing
건물소유구분명 has 378 (100.0%) missing valuesMissing
다중이용업소여부 has 126 (33.3%) missing valuesMissing
시설총규모 has 126 (33.3%) missing valuesMissing
전통업소주된음식 has 378 (100.0%) missing valuesMissing
홈페이지 has 378 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 6 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-11 00:25:14.270694
Analysis finished2024-05-11 00:25:16.476534
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3030000
378 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 378
100.0%

Length

2024-05-11T00:25:16.711178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:16.986200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 378
100.0%

관리번호
Text

UNIQUE 

Distinct378
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-05-11T00:25:17.410748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8316
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique378 ?
Unique (%)100.0%

Sample

1st row3030000-121-1980-00001
2nd row3030000-121-1983-00001
3rd row3030000-121-1983-00002
4th row3030000-121-1984-00001
5th row3030000-121-1985-00001
ValueCountFrequency (%)
3030000-121-1980-00001 1
 
0.3%
3030000-121-2018-00004 1
 
0.3%
3030000-121-2018-00013 1
 
0.3%
3030000-121-2018-00012 1
 
0.3%
3030000-121-2018-00011 1
 
0.3%
3030000-121-2018-00010 1
 
0.3%
3030000-121-2018-00009 1
 
0.3%
3030000-121-2018-00008 1
 
0.3%
3030000-121-2018-00007 1
 
0.3%
3030000-121-2019-00005 1
 
0.3%
Other values (368) 368
97.4%
2024-05-11T00:25:18.210084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3734
44.9%
1 1174
 
14.1%
- 1134
 
13.6%
2 933
 
11.2%
3 850
 
10.2%
9 134
 
1.6%
4 88
 
1.1%
8 70
 
0.8%
7 68
 
0.8%
5 67
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7182
86.4%
Dash Punctuation 1134
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3734
52.0%
1 1174
 
16.3%
2 933
 
13.0%
3 850
 
11.8%
9 134
 
1.9%
4 88
 
1.2%
8 70
 
1.0%
7 68
 
0.9%
5 67
 
0.9%
6 64
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8316
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3734
44.9%
1 1174
 
14.1%
- 1134
 
13.6%
2 933
 
11.2%
3 850
 
10.2%
9 134
 
1.6%
4 88
 
1.1%
8 70
 
0.8%
7 68
 
0.8%
5 67
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3734
44.9%
1 1174
 
14.1%
- 1134
 
13.6%
2 933
 
11.2%
3 850
 
10.2%
9 134
 
1.6%
4 88
 
1.1%
8 70
 
0.8%
7 68
 
0.8%
5 67
 
0.8%

인허가일자
Date

Distinct358
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum1980-07-24 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T00:25:18.811152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:25:19.276170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3
241 
1
137 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 241
63.8%
1 137
36.2%

Length

2024-05-11T00:25:19.774636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:20.112617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 241
63.8%
1 137
36.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
폐업
241 
영업/정상
137 

Length

Max length5
Median length2
Mean length3.0873016
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 241
63.8%
영업/정상 137
36.2%

Length

2024-05-11T00:25:20.505462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:20.876712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 241
63.8%
영업/정상 137
36.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2
241 
1
137 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 241
63.8%
1 137
36.2%

Length

2024-05-11T00:25:21.292512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:21.618912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 241
63.8%
1 137
36.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
폐업
241 
영업
137 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 241
63.8%
영업 137
36.2%

Length

2024-05-11T00:25:22.042777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:22.444961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 241
63.8%
영업 137
36.2%

폐업일자
Date

MISSING 

Distinct215
Distinct (%)89.2%
Missing137
Missing (%)36.2%
Memory size3.1 KiB
Minimum2005-12-09 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T00:25:22.838204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:25:23.313722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

전화번호
Text

MISSING 

Distinct191
Distinct (%)93.6%
Missing174
Missing (%)46.0%
Memory size3.1 KiB
2024-05-11T00:25:23.874115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.77451
Min length7

Characters and Unicode

Total characters2198
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)88.2%

Sample

1st row02 4637589
2nd row0222948250
3rd row0204662029
4th row0222923538
5th row02 4678949
ValueCountFrequency (%)
02 78
 
24.9%
070 4
 
1.3%
461 4
 
1.3%
462 4
 
1.3%
1687 3
 
1.0%
22001020 3
 
1.0%
031 3
 
1.0%
0222812300 2
 
0.6%
4517 2
 
0.6%
466 2
 
0.6%
Other values (197) 208
66.5%
2024-05-11T00:25:24.919701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 556
25.3%
0 418
19.0%
9 167
 
7.6%
166
 
7.6%
4 164
 
7.5%
5 137
 
6.2%
1 135
 
6.1%
8 129
 
5.9%
6 123
 
5.6%
3 107
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2032
92.4%
Space Separator 166
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 556
27.4%
0 418
20.6%
9 167
 
8.2%
4 164
 
8.1%
5 137
 
6.7%
1 135
 
6.6%
8 129
 
6.3%
6 123
 
6.1%
3 107
 
5.3%
7 96
 
4.7%
Space Separator
ValueCountFrequency (%)
166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2198
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 556
25.3%
0 418
19.0%
9 167
 
7.6%
166
 
7.6%
4 164
 
7.5%
5 137
 
6.2%
1 135
 
6.1%
8 129
 
5.9%
6 123
 
5.6%
3 107
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 556
25.3%
0 418
19.0%
9 167
 
7.6%
166
 
7.6%
4 164
 
7.5%
5 137
 
6.2%
1 135
 
6.1%
8 129
 
5.9%
6 123
 
5.6%
3 107
 
4.9%

소재지면적
Real number (ℝ)

MISSING 

Distinct295
Distinct (%)79.5%
Missing7
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean47.269218
Minimum0
Maximum426
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T00:25:25.409915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.85
Q123.825
median38.86
Q358.27
95-th percentile108.105
Maximum426
Range426
Interquartile range (IQR)34.445

Descriptive statistics

Standard deviation39.270905
Coefficient of variation (CV)0.83079235
Kurtosis28.758341
Mean47.269218
Median Absolute Deviation (MAD)16.9
Skewness3.9924623
Sum17536.88
Variance1542.204
MonotonicityNot monotonic
2024-05-11T00:25:25.892589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 10
 
2.6%
20.0 6
 
1.6%
21.0 5
 
1.3%
26.4 5
 
1.3%
20.4 4
 
1.1%
23.0 4
 
1.1%
30.0 4
 
1.1%
40.0 4
 
1.1%
6.6 3
 
0.8%
66.0 3
 
0.8%
Other values (285) 323
85.4%
(Missing) 7
 
1.9%
ValueCountFrequency (%)
0.0 1
 
0.3%
2.4 1
 
0.3%
3.3 3
0.8%
4.0 2
0.5%
4.8 1
 
0.3%
6.0 1
 
0.3%
6.39 1
 
0.3%
6.6 3
0.8%
8.0 2
0.5%
8.25 1
 
0.3%
ValueCountFrequency (%)
426.0 1
0.3%
280.0 1
0.3%
276.8 1
0.3%
164.48 1
0.3%
150.45 1
0.3%
150.0 1
0.3%
144.0 1
0.3%
141.72 1
0.3%
133.9 1
0.3%
133.0 1
0.3%

소재지우편번호
Text

Distinct102
Distinct (%)27.1%
Missing2
Missing (%)0.5%
Memory size3.1 KiB
2024-05-11T00:25:26.658328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2154255
Min length6

Characters and Unicode

Total characters2337
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)7.7%

Sample

1st row133831
2nd row133814
3rd row133836
4th row133883
5th row133120
ValueCountFrequency (%)
133866 18
 
4.8%
133070 17
 
4.5%
133834 15
 
4.0%
133803 12
 
3.2%
133871 11
 
2.9%
133839 10
 
2.7%
133822 10
 
2.7%
133809 9
 
2.4%
133823 9
 
2.4%
133827 9
 
2.4%
Other values (92) 256
68.1%
2024-05-11T00:25:28.147713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 852
36.5%
1 438
18.7%
8 377
16.1%
0 139
 
5.9%
2 134
 
5.7%
7 88
 
3.8%
- 81
 
3.5%
6 66
 
2.8%
4 61
 
2.6%
5 58
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2256
96.5%
Dash Punctuation 81
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 852
37.8%
1 438
19.4%
8 377
16.7%
0 139
 
6.2%
2 134
 
5.9%
7 88
 
3.9%
6 66
 
2.9%
4 61
 
2.7%
5 58
 
2.6%
9 43
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2337
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 852
36.5%
1 438
18.7%
8 377
16.1%
0 139
 
5.9%
2 134
 
5.7%
7 88
 
3.8%
- 81
 
3.5%
6 66
 
2.8%
4 61
 
2.6%
5 58
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2337
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 852
36.5%
1 438
18.7%
8 377
16.1%
0 139
 
5.9%
2 134
 
5.7%
7 88
 
3.8%
- 81
 
3.5%
6 66
 
2.8%
4 61
 
2.6%
5 58
 
2.5%

지번주소
Text

Distinct359
Distinct (%)95.5%
Missing2
Missing (%)0.5%
Memory size3.1 KiB
2024-05-11T00:25:28.771842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length26.526596
Min length17

Characters and Unicode

Total characters9974
Distinct characters209
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique344 ?
Unique (%)91.5%

Sample

1st row서울특별시 성동구 성수동2가 275-6번지
2nd row서울특별시 성동구 마장동 533-6
3rd row서울특별시 성동구 송정동 66-259번지
4th row서울특별시 성동구 도선동 404번지
5th row서울특별시 성동구 성수동2가 573-7번지 ,12
ValueCountFrequency (%)
서울특별시 376
20.9%
성동구 375
20.8%
행당동 71
 
3.9%
성수동1가 68
 
3.8%
성수동2가 67
 
3.7%
지상1층 51
 
2.8%
옥수동 27
 
1.5%
하왕십리동 23
 
1.3%
용답동 17
 
0.9%
금호동4가 16
 
0.9%
Other values (502) 709
39.4%
2024-05-11T00:25:29.979090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1663
 
16.7%
동 769
 
7.7%
성 522
 
5.2%
1 519
 
5.2%
울 384
 
3.9%
서 383
 
3.8%
구 377
 
3.8%
특 376
 
3.8%
별 376
 
3.8%
시 376
 
3.8%
Other values (199) 4229
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5846
58.6%
Decimal Number 2056
 
20.6%
Space Separator 1663
 
16.7%
Dash Punctuation 269
 
2.7%
Close Punctuation 48
 
0.5%
Open Punctuation 48
 
0.5%
Uppercase Letter 24
 
0.2%
Other Punctuation 19
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 769
13.2%
성 522
 
8.9%
울 384
 
6.6%
서 383
 
6.6%
구 377
 
6.4%
특 376
 
6.4%
별 376
 
6.4%
시 376
 
6.4%
지 322
 
5.5%
가 210
 
3.6%
Other values (168) 1751
30.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
20.8%
T 3
12.5%
E 3
12.5%
C 2
 
8.3%
I 2
 
8.3%
A 2
 
8.3%
S 1
 
4.2%
R 1
 
4.2%
N 1
 
4.2%
V 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
1 519
25.2%
2 296
14.4%
3 217
10.6%
6 182
 
8.9%
0 180
 
8.8%
4 168
 
8.2%
7 135
 
6.6%
5 132
 
6.4%
8 125
 
6.1%
9 102
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 15
78.9%
@ 3
 
15.8%
/ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
1663
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 269
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5846
58.6%
Common 4104
41.1%
Latin 24
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 769
13.2%
성 522
 
8.9%
울 384
 
6.6%
서 383
 
6.6%
구 377
 
6.4%
특 376
 
6.4%
별 376
 
6.4%
시 376
 
6.4%
지 322
 
5.5%
가 210
 
3.6%
Other values (168) 1751
30.0%
Common
ValueCountFrequency (%)
1663
40.5%
1 519
 
12.6%
2 296
 
7.2%
- 269
 
6.6%
3 217
 
5.3%
6 182
 
4.4%
0 180
 
4.4%
4 168
 
4.1%
7 135
 
3.3%
5 132
 
3.2%
Other values (8) 343
 
8.4%
Latin
ValueCountFrequency (%)
B 5
20.8%
T 3
12.5%
E 3
12.5%
C 2
 
8.3%
I 2
 
8.3%
A 2
 
8.3%
S 1
 
4.2%
R 1
 
4.2%
N 1
 
4.2%
V 1
 
4.2%
Other values (3) 3
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5846
58.6%
ASCII 4128
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1663
40.3%
1 519
 
12.6%
2 296
 
7.2%
- 269
 
6.5%
3 217
 
5.3%
6 182
 
4.4%
0 180
 
4.4%
4 168
 
4.1%
7 135
 
3.3%
5 132
 
3.2%
Other values (21) 367
 
8.9%
Hangul
ValueCountFrequency (%)
동 769
13.2%
성 522
 
8.9%
울 384
 
6.6%
서 383
 
6.6%
구 377
 
6.4%
특 376
 
6.4%
별 376
 
6.4%
시 376
 
6.4%
지 322
 
5.5%
가 210
 
3.6%
Other values (168) 1751
30.0%

도로명주소
Text

MISSING 

Distinct302
Distinct (%)98.7%
Missing72
Missing (%)19.0%
Memory size3.1 KiB
2024-05-11T00:25:30.815944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length53
Mean length35.232026
Min length23

Characters and Unicode

Total characters10781
Distinct characters210
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)97.7%

Sample

1st row서울특별시 성동구 마장로 223 (마장동)
2nd row서울특별시 성동구 성덕정길 127 (성수동2가,,12)
3rd row서울특별시 성동구 성수일로 39 (성수동1가)
4th row서울특별시 성동구 왕십리로 328, 1,2층 (도선동)
5th row서울특별시 성동구 성덕정길 29 (성수동1가)
ValueCountFrequency (%)
서울특별시 306
 
15.0%
성동구 305
 
14.9%
1층 140
 
6.8%
성수동1가 63
 
3.1%
성수동2가 50
 
2.4%
행당동 41
 
2.0%
왕십리로 32
 
1.6%
옥수동 26
 
1.3%
2층 19
 
0.9%
지상1층 18
 
0.9%
Other values (500) 1046
51.1%
2024-05-11T00:25:32.327167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1740
 
16.1%
1 668
 
6.2%
동 658
 
6.1%
성 467
 
4.3%
, 374
 
3.5%
서 350
 
3.2%
울 331
 
3.1%
) 324
 
3.0%
( 324
 
3.0%
구 312
 
2.9%
Other values (200) 5233
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6085
56.4%
Decimal Number 1824
 
16.9%
Space Separator 1740
 
16.1%
Other Punctuation 375
 
3.5%
Close Punctuation 324
 
3.0%
Open Punctuation 324
 
3.0%
Dash Punctuation 86
 
0.8%
Uppercase Letter 18
 
0.2%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 658
 
10.8%
성 467
 
7.7%
서 350
 
5.8%
울 331
 
5.4%
구 312
 
5.1%
시 307
 
5.0%
특 306
 
5.0%
별 306
 
5.0%
층 261
 
4.3%
로 204
 
3.4%
Other values (174) 2583
42.4%
Decimal Number
ValueCountFrequency (%)
1 668
36.6%
2 304
16.7%
3 174
 
9.5%
0 156
 
8.6%
4 143
 
7.8%
7 100
 
5.5%
5 86
 
4.7%
6 71
 
3.9%
8 67
 
3.7%
9 55
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
27.8%
L 3
16.7%
I 2
 
11.1%
T 2
 
11.1%
R 2
 
11.1%
D 1
 
5.6%
J 1
 
5.6%
C 1
 
5.6%
E 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 374
99.7%
? 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1740
100.0%
Close Punctuation
ValueCountFrequency (%)
) 324
100.0%
Open Punctuation
ValueCountFrequency (%)
( 324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6085
56.4%
Common 4678
43.4%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 658
 
10.8%
성 467
 
7.7%
서 350
 
5.8%
울 331
 
5.4%
구 312
 
5.1%
시 307
 
5.0%
특 306
 
5.0%
별 306
 
5.0%
층 261
 
4.3%
로 204
 
3.4%
Other values (174) 2583
42.4%
Common
ValueCountFrequency (%)
1740
37.2%
1 668
 
14.3%
, 374
 
8.0%
) 324
 
6.9%
( 324
 
6.9%
2 304
 
6.5%
3 174
 
3.7%
0 156
 
3.3%
4 143
 
3.1%
7 100
 
2.1%
Other values (7) 371
 
7.9%
Latin
ValueCountFrequency (%)
B 5
27.8%
L 3
16.7%
I 2
 
11.1%
T 2
 
11.1%
R 2
 
11.1%
D 1
 
5.6%
J 1
 
5.6%
C 1
 
5.6%
E 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6085
56.4%
ASCII 4696
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1740
37.1%
1 668
 
14.2%
, 374
 
8.0%
) 324
 
6.9%
( 324
 
6.9%
2 304
 
6.5%
3 174
 
3.7%
0 156
 
3.3%
4 143
 
3.0%
7 100
 
2.1%
Other values (16) 389
 
8.3%
Hangul
ValueCountFrequency (%)
동 658
 
10.8%
성 467
 
7.7%
서 350
 
5.8%
울 331
 
5.4%
구 312
 
5.1%
시 307
 
5.0%
특 306
 
5.0%
별 306
 
5.0%
층 261
 
4.3%
로 204
 
3.4%
Other values (174) 2583
42.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct78
Distinct (%)26.2%
Missing80
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean4757.3188
Minimum4700
Maximum6008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T00:25:32.837823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4700
5-th percentile4701
Q14724.25
median4757
Q34781
95-th percentile4801
Maximum6008
Range1308
Interquartile range (IQR)56.75

Descriptive statistics

Standard deviation79.676972
Coefficient of variation (CV)0.016748294
Kurtosis205.59982
Mean4757.3188
Median Absolute Deviation (MAD)27.5
Skewness13.075282
Sum1417681
Variance6348.4199
MonotonicityNot monotonic
2024-05-11T00:25:33.423394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4768 14
 
3.7%
4781 13
 
3.4%
4782 13
 
3.4%
4779 10
 
2.6%
4701 9
 
2.4%
4733 8
 
2.1%
4750 8
 
2.1%
4735 8
 
2.1%
4778 8
 
2.1%
4700 7
 
1.9%
Other values (68) 200
52.9%
(Missing) 80
 
21.2%
ValueCountFrequency (%)
4700 7
1.9%
4701 9
2.4%
4702 2
 
0.5%
4703 1
 
0.3%
4704 1
 
0.3%
4705 1
 
0.3%
4706 1
 
0.3%
4707 6
1.6%
4708 2
 
0.5%
4709 4
1.1%
ValueCountFrequency (%)
6008 1
 
0.3%
4805 5
1.3%
4804 6
1.6%
4801 6
1.6%
4800 2
 
0.5%
4799 2
 
0.5%
4797 1
 
0.3%
4795 3
0.8%
4794 6
1.6%
4793 2
 
0.5%

사업장명
Text

Distinct342
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-05-11T00:25:34.237956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length8.047619
Min length2

Characters and Unicode

Total characters3042
Distinct characters393
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

Unique318 ?
Unique (%)84.1%

Sample

1st row파티오
2nd row뚜레쥬르
3rd row시모네빵집
4th row로망스베이커리
5th row독일제과
ValueCountFrequency (%)
파리바게뜨 17
 
3.2%
뚜레쥬르 10
 
1.9%
파리바게트 9
 
1.7%
성수점 8
 
1.5%
크라운베이커리 5
 
0.9%
브레드 5
 
0.9%
블랑제리 5
 
0.9%
boulanger 5
 
0.9%
브레댄코 4
 
0.7%
앤 4
 
0.7%
Other values (408) 462
86.5%
2024-05-11T00:25:35.552618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
 
5.1%
리 148
 
4.9%
점 99
 
3.3%
이 94
 
3.1%
) 75
 
2.5%
( 75
 
2.5%
베 55
 
1.8%
바 46
 
1.5%
파 45
 
1.5%
빵 45
 
1.5%
Other values (383) 2204
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2327
76.5%
Lowercase Letter 215
 
7.1%
Space Separator 156
 
5.1%
Uppercase Letter 156
 
5.1%
Close Punctuation 75
 
2.5%
Open Punctuation 75
 
2.5%
Decimal Number 27
 
0.9%
Other Punctuation 6
 
0.2%
Dash Punctuation 4
 
0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 148
 
6.4%
점 99
 
4.3%
이 94
 
4.0%
베 55
 
2.4%
바 46
 
2.0%
파 45
 
1.9%
빵 45
 
1.9%
레 42
 
1.8%
커 42
 
1.8%
수 40
 
1.7%
Other values (321) 1671
71.8%
Uppercase Letter
ValueCountFrequency (%)
A 19
12.2%
B 17
10.9%
L 14
 
9.0%
O 11
 
7.1%
E 10
 
6.4%
N 10
 
6.4%
P 10
 
6.4%
M 9
 
5.8%
T 8
 
5.1%
I 7
 
4.5%
Other values (13) 41
26.3%
Lowercase Letter
ValueCountFrequency (%)
e 31
14.4%
o 25
11.6%
a 23
10.7%
n 21
9.8%
r 17
 
7.9%
i 12
 
5.6%
t 9
 
4.2%
m 9
 
4.2%
g 9
 
4.2%
s 8
 
3.7%
Other values (12) 51
23.7%
Decimal Number
ValueCountFrequency (%)
1 6
22.2%
2 5
18.5%
7 4
14.8%
4 3
11.1%
5 3
11.1%
6 2
 
7.4%
0 2
 
7.4%
3 2
 
7.4%
Other Punctuation
ValueCountFrequency (%)
! 2
33.3%
. 2
33.3%
＆ 1
16.7%
? 1
16.7%
Space Separator
ValueCountFrequency (%)
156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2327
76.5%
Latin 371
 
12.2%
Common 344
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 148
 
6.4%
점 99
 
4.3%
이 94
 
4.0%
베 55
 
2.4%
바 46
 
2.0%
파 45
 
1.9%
빵 45
 
1.9%
레 42
 
1.8%
커 42
 
1.8%
수 40
 
1.7%
Other values (321) 1671
71.8%
Latin
ValueCountFrequency (%)
e 31
 
8.4%
o 25
 
6.7%
a 23
 
6.2%
n 21
 
5.7%
A 19
 
5.1%
B 17
 
4.6%
r 17
 
4.6%
L 14
 
3.8%
i 12
 
3.2%
O 11
 
3.0%
Other values (35) 181
48.8%
Common
ValueCountFrequency (%)
156
45.3%
) 75
21.8%
( 75
21.8%
1 6
 
1.7%
2 5
 
1.5%
- 4
 
1.2%
7 4
 
1.2%
4 3
 
0.9%
5 3
 
0.9%
! 2
 
0.6%
Other values (7) 11
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2327
76.5%
ASCII 714
 
23.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
21.8%
) 75
 
10.5%
( 75
 
10.5%
e 31
 
4.3%
o 25
 
3.5%
a 23
 
3.2%
n 21
 
2.9%
A 19
 
2.7%
B 17
 
2.4%
r 17
 
2.4%
Other values (51) 255
35.7%
Hangul
ValueCountFrequency (%)
리 148
 
6.4%
점 99
 
4.3%
이 94
 
4.0%
베 55
 
2.4%
바 46
 
2.0%
파 45
 
1.9%
빵 45
 
1.9%
레 42
 
1.8%
커 42
 
1.8%
수 40
 
1.7%
Other values (321) 1671
71.8%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정일자
Date

Distinct373
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2001-11-28 00:00:00
Maximum2024-05-09 15:53:02
2024-05-11T00:25:36.072745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:25:36.824420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
I
228 
U
150 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 228
60.3%
U 150
39.7%

Length

2024-05-11T00:25:37.286754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:37.686817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 228
60.3%
u 150
39.7%

데이터갱신일자
Date

Distinct183
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T00:25:38.238630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:25:38.832330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
제과점영업
378 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 378
100.0%

Length

2024-05-11T00:25:39.299933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:39.701532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 378
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct281
Distinct (%)76.4%
Missing10
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean203351.33
Minimum200886.87
Maximum206289.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T00:25:40.279965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200886.87
5-th percentile201301.59
Q1202326.5
median203441.82
Q3204464.99
95-th percentile205031.91
Maximum206289.26
Range5402.3934
Interquartile range (IQR)2138.491

Descriptive statistics

Standard deviation1255.0002
Coefficient of variation (CV)0.0061715858
Kurtosis-0.95626139
Mean203351.33
Median Absolute Deviation (MAD)1068.9122
Skewness-0.079394505
Sum74833288
Variance1575025.4
MonotonicityNot monotonic
2024-05-11T00:25:40.744653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203292.151898869 9
 
2.4%
202326.503044305 9
 
2.4%
202113.869605464 7
 
1.9%
202372.912023599 6
 
1.6%
203684.127182478 5
 
1.3%
204614.272744322 5
 
1.3%
204966.098616157 5
 
1.3%
203321.562330114 4
 
1.1%
201369.051858107 3
 
0.8%
204830.977323063 3
 
0.8%
Other values (271) 312
82.5%
(Missing) 10
 
2.6%
ValueCountFrequency (%)
200886.870660767 1
0.3%
200913.361072125 1
0.3%
200951.206580662 1
0.3%
200967.537033206 1
0.3%
201059.703833592 1
0.3%
201145.389175397 1
0.3%
201153.981577199 1
0.3%
201165.950245642 2
0.5%
201170.960314149 2
0.5%
201174.525137191 1
0.3%
ValueCountFrequency (%)
206289.264108547 1
0.3%
206062.153579888 1
0.3%
205966.616588739 1
0.3%
205937.135398965 1
0.3%
205912.571031198 1
0.3%
205850.077784085 1
0.3%
205788.686163691 1
0.3%
205773.876761108 1
0.3%
205697.619105269 1
0.3%
205659.048354262 2
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct281
Distinct (%)76.4%
Missing10
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean450022.9
Minimum447369.58
Maximum452001.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T00:25:41.155259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447369.58
5-th percentile448532.03
Q1449159.45
median449731.93
Q3450997.1
95-th percentile451720.63
Maximum452001.15
Range4631.5664
Interquartile range (IQR)1837.6436

Descriptive statistics

Standard deviation1052.6463
Coefficient of variation (CV)0.002339095
Kurtosis-1.1841708
Mean450022.9
Median Absolute Deviation (MAD)856.12147
Skewness0.19777172
Sum1.6560843 × 108
Variance1108064.2
MonotonicityNot monotonic
2024-05-11T00:25:41.592495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451267.730901002 9
 
2.4%
450625.58422744 9
 
2.4%
451897.581865192 7
 
1.9%
451536.680876573 6
 
1.6%
450698.570810848 5
 
1.3%
448607.441251647 5
 
1.3%
449159.452779834 5
 
1.3%
451001.868687869 4
 
1.1%
448875.808288849 3
 
0.8%
449477.448459906 3
 
0.8%
Other values (271) 312
82.5%
(Missing) 10
 
2.6%
ValueCountFrequency (%)
447369.579851952 1
0.3%
448270.804197558 1
0.3%
448277.387756454 1
0.3%
448281.331149262 1
0.3%
448310.561851329 1
0.3%
448340.701266811 1
0.3%
448366.505563017 1
0.3%
448382.86739377 1
0.3%
448392.897796591 1
0.3%
448428.969669622 1
0.3%
ValueCountFrequency (%)
452001.146207471 1
 
0.3%
451995.716760547 1
 
0.3%
451970.785176715 1
 
0.3%
451908.86237999 3
0.8%
451897.581865192 7
1.9%
451880.117871 2
 
0.5%
451824.598496233 1
 
0.3%
451809.190992068 2
 
0.5%
451736.787195355 1
 
0.3%
451690.619041616 1
 
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
제과점영업
252 
<NA>
126 

Length

Max length5
Median length5
Mean length4.6666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 252
66.7%
<NA> 126
33.3%

Length

2024-05-11T00:25:42.055868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:42.413559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 252
66.7%
na 126
33.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
295 
0
70 
1
 
7
2
 
6

Length

Max length4
Median length4
Mean length3.3412698
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row2
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 295
78.0%
0 70
 
18.5%
1 7
 
1.9%
2 6
 
1.6%

Length

2024-05-11T00:25:42.777458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:43.132924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 295
78.0%
0 70
 
18.5%
1 7
 
1.9%
2 6
 
1.6%

여성종사자수
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
295 
0
73 
1
 
10

Length

Max length4
Median length4
Mean length3.3412698
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 295
78.0%
0 73
 
19.3%
1 10
 
2.6%

Length

2024-05-11T00:25:43.599075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:43.972477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 295
78.0%
0 73
 
19.3%
1 10
 
2.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
320 
주택가주변
 
24
기타
 
19
아파트지역
 
12
학교정화(상대)
 
2

Length

Max length8
Median length4
Mean length4.026455
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 320
84.7%
주택가주변 24
 
6.3%
기타 19
 
5.0%
아파트지역 12
 
3.2%
학교정화(상대) 2
 
0.5%
학교정화(절대) 1
 
0.3%

Length

2024-05-11T00:25:44.618320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:45.163262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 320
84.7%
주택가주변 24
 
6.3%
기타 19
 
5.0%
아파트지역 12
 
3.2%
학교정화(상대 2
 
0.5%
학교정화(절대 1
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
330 
기타
40 
을
 
5
자율
 
2
갑
 
1

Length

Max length4
Median length4
Mean length3.7301587
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 330
87.3%
기타 40
 
10.6%
을 5
 
1.3%
자율 2
 
0.5%
갑 1
 
0.3%

Length

2024-05-11T00:25:45.669369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:46.239800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 330
87.3%
기타 40
 
10.6%
을 5
 
1.3%
자율 2
 
0.5%
갑 1
 
0.3%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
297 
상수도전용
81 

Length

Max length5
Median length4
Mean length4.2142857
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 297
78.6%
상수도전용 81
 
21.4%

Length

2024-05-11T00:25:46.874624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:47.263844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 297
78.6%
상수도전용 81
 
21.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
364 
0
 
14

Length

Max length4
Median length4
Mean length3.8888889
Min length1

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> 364
96.3%
0 14
 
3.7%

Length

2024-05-11T00:25:47.880142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:48.281425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 364
96.3%
0 14
 
3.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
363 
0
 
15

Length

Max length4
Median length4
Mean length3.8809524
Min length1

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> 363
96.0%
0 15
 
4.0%

Length

2024-05-11T00:25:48.667395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:49.099014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
96.0%
0 15
 
4.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
363 
0
 
15

Length

Max length4
Median length4
Mean length3.8809524
Min length1

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> 363
96.0%
0 15
 
4.0%

Length

2024-05-11T00:25:49.576628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:49.939616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
96.0%
0 15
 
4.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
363 
0
 
15

Length

Max length4
Median length4
Mean length3.8809524
Min length1

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> 363
96.0%
0 15
 
4.0%

Length

2024-05-11T00:25:50.406583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:50.839645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
96.0%
0 15
 
4.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
363 
0
 
15

Length

Max length4
Median length4
Mean length3.8809524
Min length1

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> 363
96.0%
0 15
 
4.0%

Length

2024-05-11T00:25:51.330824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:51.754426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
96.0%
0 15
 
4.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
363 
0
 
15

Length

Max length4
Median length4
Mean length3.8809524
Min length1

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> 363
96.0%
0 15
 
4.0%

Length

2024-05-11T00:25:52.258680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:52.733355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
96.0%
0 15
 
4.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
363 
0
 
15

Length

Max length4
Median length4
Mean length3.8809524
Min length1

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> 363
96.0%
0 15
 
4.0%

Length

2024-05-11T00:25:53.835490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:54.407314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
96.0%
0 15
 
4.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.8%
Missing126
Missing (%)33.3%
Memory size888.0 B
False
249 
True
 
3
(Missing)
126 
ValueCountFrequency (%)
False 249
65.9%
True 3
 
0.8%
(Missing) 126
33.3%
2024-05-11T00:25:54.928741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct213
Distinct (%)84.5%
Missing126
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean44.835079
Minimum0
Maximum280
Zeros6
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T00:25:55.365016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.5055
Q122.9675
median37.44
Q356.985
95-th percentile99.4525
Maximum280
Range280
Interquartile range (IQR)34.0175

Descriptive statistics

Standard deviation35.221802
Coefficient of variation (CV)0.78558581
Kurtosis14.580351
Mean44.835079
Median Absolute Deviation (MAD)16.26
Skewness2.8556252
Sum11298.44
Variance1240.5754
MonotonicityNot monotonic
2024-05-11T00:25:55.984460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
1.6%
33.0 5
 
1.3%
20.4 4
 
1.1%
26.4 4
 
1.1%
25.3 3
 
0.8%
21.0 3
 
0.8%
25.5 2
 
0.5%
25.0 2
 
0.5%
21.06 2
 
0.5%
52.5 2
 
0.5%
Other values (203) 219
57.9%
(Missing) 126
33.3%
ValueCountFrequency (%)
0.0 6
1.6%
2.4 1
 
0.3%
3.3 2
 
0.5%
4.0 2
 
0.5%
4.8 1
 
0.3%
6.39 1
 
0.3%
6.6 1
 
0.3%
8.0 1
 
0.3%
9.0 1
 
0.3%
9.75 1
 
0.3%
ValueCountFrequency (%)
280.0 1
0.3%
276.8 1
0.3%
144.0 1
0.3%
141.72 1
0.3%
133.9 1
0.3%
133.0 1
0.3%
132.0 2
0.5%
120.0 1
0.3%
115.67 1
0.3%
115.0 1
0.3%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
377 
2413
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
99.7%
2413 1
 
0.3%

Length

2024-05-11T00:25:56.546239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:25:57.124518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
99.7%
2413 1
 
0.3%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing378
Missing (%)100.0%
Memory size3.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030300003030000-121-1980-0000119801114<NA>3폐업2폐업20100203<NA><NA><NA>02 463758943.42133831서울특별시 성동구 성수동2가 275-6번지<NA><NA>파티오2009-02-06 16:22:26I2018-08-31 23:59:59.0제과점영업205464.596033448682.53615제과점영업11기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.42<NA><NA><NA>
130300003030000-121-1983-0000119830319<NA>3폐업2폐업20220930<NA><NA><NA>02229482500.0133814서울특별시 성동구 마장동 533-6서울특별시 성동구 마장로 223 (마장동)4705뚜레쥬르2022-09-30 16:34:37U2021-10-31 00:02:00.0제과점영업202992.906141451575.440367<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230300003030000-121-1983-0000219830310<NA>3폐업2폐업20111206<NA><NA><NA>020466202979.83133836서울특별시 성동구 송정동 66-259번지<NA><NA>시모네빵집2010-09-20 16:34:02I2018-08-31 23:59:59.0제과점영업205659.048354449568.452389제과점영업20기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N79.83<NA><NA><NA>
330300003030000-121-1984-0000119840618<NA>3폐업2폐업20060821<NA><NA><NA>022292353842.24133883서울특별시 성동구 도선동 404번지<NA><NA>로망스베이커리2005-07-08 00:00:00I2018-08-31 23:59:59.0제과점영업202607.3996451395.620156제과점영업00주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.24<NA><NA><NA>
430300003030000-121-1985-0000119850926<NA>3폐업2폐업20121231<NA><NA><NA>02 467894931.82133120서울특별시 성동구 성수동2가 573-7번지 ,12서울특별시 성동구 성덕정길 127 (성수동2가,,12)4777독일제과2012-12-31 17:29:31I2018-08-31 23:59:59.0제과점영업205017.047053448277.387756제과점영업11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N31.82<NA><NA><NA>
530300003030000-121-1987-0000119870210<NA>3폐업2폐업20100311<NA><NA><NA>022292473369.29133812서울특별시 성동구 마장동 478-38번지<NA><NA>에센브르과자점2002-06-17 00:00:00I2018-08-31 23:59:59.0제과점영업203231.123463451970.785177제과점영업11주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N69.29<NA><NA><NA>
630300003030000-121-1987-0000219871014<NA>3폐업2폐업20181012<NA><NA><NA><NA>56.8133819서울특별시 성동구 성수동1가 22-5번지서울특별시 성동구 성수일로 39 (성수동1가)4779파리바게뜨 성수동1가점2018-10-12 16:30:18U2018-10-12 23:59:59.0제과점영업204269.337017449119.290164제과점영업11기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N56.8<NA><NA><NA>
730300003030000-121-1988-0000119880603<NA>3폐업2폐업20100520<NA><NA><NA>022294602046.99133858서울특별시 성동구 하왕십리동 983-8번지<NA><NA>에센브르2008-05-20 16:03:05I2018-08-31 23:59:59.0제과점영업202583.502332450960.616695제과점영업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N46.99<NA><NA><NA>
830300003030000-121-1988-0000219880425<NA>3폐업2폐업20090626<NA><NA><NA>022297140829.0133094서울특별시 성동구 금호동4가 1391-2번지 ,3,4<NA><NA>뉴욕빵제과2009-02-06 16:18:22I2018-08-31 23:59:59.0제과점영업201488.505107449558.276304제과점영업10주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.0<NA><NA><NA>
930300003030000-121-1991-0000119911112<NA>3폐업2폐업20080304<NA><NA><NA>022295811142.26133812서울특별시 성동구 마장동 474-27번지<NA><NA>마운틴하우스2004-05-21 00:00:00I2018-08-31 23:59:59.0제과점영업203202.925514452001.146207제과점영업20주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.26<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
36830300003030000-121-2024-000052024-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.4133-881서울특별시 성동구 홍익동 429서울특별시 성동구 무학로14길 6 (홍익동)4706다올찰떡2024-03-06 14:29:12I2023-12-03 00:08:00.0제과점영업202656.120169451690.619042<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36930300003030000-121-2024-000062024-03-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 2203880818.27133-831서울특별시 성동구 성수동2가 271-12서울특별시 성동구 뚝섬로13길 36, 1층 (성수동2가)4785니커버커베이글 성수2024-03-07 14:53:34I2023-12-03 00:09:00.0제과점영업205064.79198448781.395002<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37030300003030000-121-2024-000072024-03-15<NA>3폐업2폐업2024-03-16<NA><NA><NA><NA><NA>133-825서울특별시 성동구 성수동1가 685-704 언더 스탠드 에비뉴서울특별시 성동구 왕십리로 63, 언더 스탠드 에비뉴 (성수동1가)4769오베흐트2024-03-17 04:15:09U2023-12-02 23:09:00.0제과점영업203787.299658449039.575793<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37130300003030000-121-2024-000082024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.66133-020서울특별시 성동구 하왕십리동 1070 센트라스서울특별시 성동구 왕십리로 410, J동 1층 136호 (하왕십리동, 센트라스)4701위클리베이글2024-03-22 12:56:39I2023-12-02 22:04:00.0제과점영업202372.912024451536.680877<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37230300003030000-121-2024-000092024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>106.11133-871서울특별시 성동구 행당동 1-90서울특별시 성동구 마조로9길 6-3, 1층 (행당동)4760AUG.741(어거스트 칠사일)2024-04-03 13:48:33I2023-12-04 00:05:00.0제과점영업203537.510849451015.485483<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37330300003030000-121-2024-000102024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 462 224549.5133-827서울특별시 성동구 성수동2가 321-74서울특별시 성동구 연무장길 56-1, 1층 (성수동2가)4781자연도소금빵in성수2024-04-09 14:22:57I2023-12-03 23:01:00.0제과점영업204831.523987448895.264709<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37430300003030000-121-2024-000112024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 462 224554.59133-819서울특별시 성동구 성수동1가 278-4서울특별시 성동구 성덕정9가길 14, 1층 (성수동1가)4775자연도소금빵in성수2024-04-09 14:29:22I2023-12-03 23:01:00.0제과점영업204464.928649448513.720035<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37530300003030000-121-2024-000122024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.0133-835서울특별시 성동구 성수동2가 316-74서울특별시 성동구 연무장길 43-1, 1층 (성수동2가)4782한정선2024-04-15 17:20:07I2023-12-03 23:07:00.0제과점영업204718.760838448964.576579<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37630300003030000-121-2024-000132024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA>02 466 775730.0133-825서울특별시 성동구 성수동1가 685-418서울특별시 성동구 서울숲2길 17-16, 지1층 (성수동1가)4768리틀바잇모어2024-04-19 17:00:11I2023-12-03 22:01:00.0제과점영업203548.046641449466.348492<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37730300003030000-121-2024-000142024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA>02 2291495297.57133-810서울특별시 성동구 금호동4가 1550 브라운스톤 금호2차서울특별시 성동구 동호로 93, 401동 지2층 4호 (금호동4가, 브라운스톤 금호2차)4733파리바게뜨 금호역점2024-04-22 11:42:15I2023-12-03 22:04:00.0제과점영업201286.016742449480.09166<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>