Overview

Dataset statistics

Number of variables44
Number of observations501
Missing cells5958
Missing cells (%)27.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory184.1 KiB
Average record size in memory376.3 B

Variable types

Categorical17
Text6
DateTime4
Unsupported7
Numeric9
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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-18265/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업장주변구분명 is highly imbalanced (58.3%)Imbalance
등급구분명 is highly imbalanced (62.9%)Imbalance
총인원 is highly imbalanced (80.6%)Imbalance
인허가취소일자 has 501 (100.0%) missing valuesMissing
폐업일자 has 79 (15.8%) missing valuesMissing
휴업시작일자 has 501 (100.0%) missing valuesMissing
휴업종료일자 has 501 (100.0%) missing valuesMissing
재개업일자 has 501 (100.0%) missing valuesMissing
전화번호 has 130 (25.9%) missing valuesMissing
소재지면적 has 19 (3.8%) missing valuesMissing
도로명주소 has 179 (35.7%) missing valuesMissing
도로명우편번호 has 184 (36.7%) missing valuesMissing
좌표정보(X) has 14 (2.8%) missing valuesMissing
좌표정보(Y) has 14 (2.8%) missing valuesMissing
남성종사자수 has 404 (80.6%) missing valuesMissing
여성종사자수 has 410 (81.8%) missing valuesMissing
보증액 has 435 (86.8%) missing valuesMissing
월세액 has 437 (87.2%) missing valuesMissing
다중이용업소여부 has 71 (14.2%) missing valuesMissing
시설총규모 has 71 (14.2%) missing valuesMissing
전통업소지정번호 has 501 (100.0%) missing valuesMissing
전통업소주된음식 has 501 (100.0%) missing valuesMissing
홈페이지 has 501 (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
전통업소지정번호 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
소재지면적 has 16 (3.2%) zerosZeros
남성종사자수 has 31 (6.2%) zerosZeros
여성종사자수 has 30 (6.0%) zerosZeros
보증액 has 54 (10.8%) zerosZeros
월세액 has 54 (10.8%) zerosZeros
시설총규모 has 342 (68.3%) zerosZeros

Reproduction

Analysis started2024-05-11 05:54:38.268158
Analysis finished2024-05-11 05:54:39.604919
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
3130000
501 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 501
100.0%

Length

2024-05-11T14:54:39.705675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:39.856646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 501
100.0%

관리번호
Text

UNIQUE 

Distinct501
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-05-11T14:54:40.113350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters11022
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

Unique501 ?
Unique (%)100.0%

Sample

1st row3130000-106-1971-00012
2nd row3130000-106-1971-00026
3rd row3130000-106-1971-00027
4th row3130000-106-1973-00008
5th row3130000-106-1973-00029
ValueCountFrequency (%)
3130000-106-1971-00012 1
 
0.2%
3130000-106-2013-00035 1
 
0.2%
3130000-106-2014-00027 1
 
0.2%
3130000-106-2014-00026 1
 
0.2%
3130000-106-2014-00025 1
 
0.2%
3130000-106-2014-00024 1
 
0.2%
3130000-106-2014-00023 1
 
0.2%
3130000-106-2014-00022 1
 
0.2%
3130000-106-2014-00021 1
 
0.2%
3130000-106-2014-00020 1
 
0.2%
Other values (491) 491
98.0%
2024-05-11T14:54:40.681672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4853
44.0%
1 1587
 
14.4%
- 1503
 
13.6%
3 1158
 
10.5%
2 658
 
6.0%
6 583
 
5.3%
9 199
 
1.8%
4 144
 
1.3%
5 124
 
1.1%
7 114
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9519
86.4%
Dash Punctuation 1503
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4853
51.0%
1 1587
 
16.7%
3 1158
 
12.2%
2 658
 
6.9%
6 583
 
6.1%
9 199
 
2.1%
4 144
 
1.5%
5 124
 
1.3%
7 114
 
1.2%
8 99
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1503
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11022
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4853
44.0%
1 1587
 
14.4%
- 1503
 
13.6%
3 1158
 
10.5%
2 658
 
6.0%
6 583
 
5.3%
9 199
 
1.8%
4 144
 
1.3%
5 124
 
1.1%
7 114
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11022
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4853
44.0%
1 1587
 
14.4%
- 1503
 
13.6%
3 1158
 
10.5%
2 658
 
6.0%
6 583
 
5.3%
9 199
 
1.8%
4 144
 
1.3%
5 124
 
1.1%
7 114
 
1.0%

인허가일자
Date

Distinct457
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum1971-03-17 00:00:00
Maximum2024-03-06 00:00:00
2024-05-11T14:54:40.983798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:41.370526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
3
422 
1
79 

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 (%)
3 422
84.2%
1 79
 
15.8%

Length

2024-05-11T14:54:41.704848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:41.905910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 422
84.2%
1 79
 
15.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
폐업
422 
영업/정상
79 

Length

Max length5
Median length2
Mean length2.4730539
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 422
84.2%
영업/정상 79
 
15.8%

Length

2024-05-11T14:54:42.120708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:42.284660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 422
84.2%
영업/정상 79
 
15.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
422 
1
79 

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 (%)
2 422
84.2%
1 79
 
15.8%

Length

2024-05-11T14:54:42.474134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:42.639593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 422
84.2%
1 79
 
15.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
폐업
422 
영업
79 

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 422
84.2%
영업 79
 
15.8%

Length

2024-05-11T14:54:42.836200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:43.015335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 422
84.2%
영업 79
 
15.8%

폐업일자
Date

MISSING 

Distinct394
Distinct (%)93.4%
Missing79
Missing (%)15.8%
Memory size4.0 KiB
Minimum1995-09-05 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:54:43.216316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:43.446069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

전화번호
Text

MISSING 

Distinct343
Distinct (%)92.5%
Missing130
Missing (%)25.9%
Memory size4.0 KiB
2024-05-11T14:54:43.875552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9110512
Min length2

Characters and Unicode

Total characters3677
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

Unique331 ?
Unique (%)89.2%

Sample

1st row02 3242073
2nd row02 7159459
3rd row02 3245739
4th row02
5th row02 7120961
ValueCountFrequency (%)
02 256
37.8%
070 14
 
2.1%
325 5
 
0.7%
336 4
 
0.6%
7169812 2
 
0.3%
3357770 2
 
0.3%
031 2
 
0.3%
712 2
 
0.3%
7071668 2
 
0.3%
711 2
 
0.3%
Other values (370) 387
57.1%
2024-05-11T14:54:44.516577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 675
18.4%
2 603
16.4%
3 461
12.5%
381
10.4%
7 342
9.3%
1 255
 
6.9%
5 219
 
6.0%
8 218
 
5.9%
4 201
 
5.5%
6 197
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3296
89.6%
Space Separator 381
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 675
20.5%
2 603
18.3%
3 461
14.0%
7 342
10.4%
1 255
 
7.7%
5 219
 
6.6%
8 218
 
6.6%
4 201
 
6.1%
6 197
 
6.0%
9 125
 
3.8%
Space Separator
ValueCountFrequency (%)
381
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 675
18.4%
2 603
16.4%
3 461
12.5%
381
10.4%
7 342
9.3%
1 255
 
6.9%
5 219
 
6.0%
8 218
 
5.9%
4 201
 
5.5%
6 197
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 675
18.4%
2 603
16.4%
3 461
12.5%
381
10.4%
7 342
9.3%
1 255
 
6.9%
5 219
 
6.0%
8 218
 
5.9%
4 201
 
5.5%
6 197
 
5.4%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct420
Distinct (%)87.1%
Missing19
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean62.341162
Minimum0
Maximum506.93
Zeros16
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:44.785148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.033
Q121.93
median41.845
Q382.3
95-th percentile192.232
Maximum506.93
Range506.93
Interquartile range (IQR)60.37

Descriptive statistics

Standard deviation66.341868
Coefficient of variation (CV)1.0641744
Kurtosis11.451023
Mean62.341162
Median Absolute Deviation (MAD)23.85
Skewness2.8394049
Sum30048.44
Variance4401.2435
MonotonicityNot monotonic
2024-05-11T14:54:45.051986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
3.2%
61.0 9
 
1.8%
10.0 5
 
1.0%
33.0 4
 
0.8%
13.2 3
 
0.6%
20.0 3
 
0.6%
50.0 3
 
0.6%
19.0 3
 
0.6%
16.5 3
 
0.6%
15.0 3
 
0.6%
Other values (410) 430
85.8%
(Missing) 19
 
3.8%
ValueCountFrequency (%)
0.0 16
3.2%
3.02 1
 
0.2%
3.43 1
 
0.2%
3.74 1
 
0.2%
5.12 1
 
0.2%
5.18 1
 
0.2%
6.0 1
 
0.2%
7.0 2
 
0.4%
7.02 1
 
0.2%
7.28 1
 
0.2%
ValueCountFrequency (%)
506.93 1
0.2%
461.56 1
0.2%
457.92 1
0.2%
368.79 1
0.2%
330.96 1
0.2%
330.0 1
0.2%
325.8 1
0.2%
288.23 1
0.2%
277.98 1
0.2%
273.48 1
0.2%

소재지우편번호
Text

Distinct127
Distinct (%)25.5%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2024-05-11T14:54:45.589001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0901804
Min length6

Characters and Unicode

Total characters3039
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

Unique46 ?
Unique (%)9.2%

Sample

1st row121824
2nd row121811
3rd row121826
4th row121889
5th row121803
ValueCountFrequency (%)
121837 14
 
2.8%
121809 13
 
2.6%
121865 12
 
2.4%
121839 12
 
2.4%
121836 12
 
2.4%
121844 12
 
2.4%
121842 11
 
2.2%
121869 11
 
2.2%
121880 11
 
2.2%
121856 11
 
2.2%
Other values (117) 380
76.2%
2024-05-11T14:54:46.307736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1088
35.8%
2 599
19.7%
8 573
18.9%
0 125
 
4.1%
4 123
 
4.0%
9 110
 
3.6%
6 110
 
3.6%
3 94
 
3.1%
7 89
 
2.9%
5 83
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2994
98.5%
Dash Punctuation 45
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1088
36.3%
2 599
20.0%
8 573
19.1%
0 125
 
4.2%
4 123
 
4.1%
9 110
 
3.7%
6 110
 
3.7%
3 94
 
3.1%
7 89
 
3.0%
5 83
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3039
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1088
35.8%
2 599
19.7%
8 573
18.9%
0 125
 
4.1%
4 123
 
4.0%
9 110
 
3.6%
6 110
 
3.6%
3 94
 
3.1%
7 89
 
2.9%
5 83
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1088
35.8%
2 599
19.7%
8 573
18.9%
0 125
 
4.1%
4 123
 
4.0%
9 110
 
3.6%
6 110
 
3.6%
3 94
 
3.1%
7 89
 
2.9%
5 83
 
2.7%

지번주소
Text

Distinct489
Distinct (%)98.0%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2024-05-11T14:54:46.767135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length40
Mean length25.563126
Min length17

Characters and Unicode

Total characters12756
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique483 ?
Unique (%)96.8%

Sample

1st row서울특별시 마포구 망원동 436-14번지 2F동
2nd row서울특별시 마포구 대흥동 436-1번지
3rd row서울특별시 마포구 망원동 469-39번지 (지층.1층)
4th row서울특별시 마포구 망원동 455-48번지
5th row서울특별시 마포구 공덕동 242-4번지 (1,2층)
ValueCountFrequency (%)
서울특별시 499
20.6%
마포구 499
20.6%
1층 117
 
4.8%
서교동 96
 
4.0%
망원동 58
 
2.4%
성산동 52
 
2.2%
지층 44
 
1.8%
연남동 39
 
1.6%
합정동 35
 
1.4%
2층 30
 
1.2%
Other values (601) 949
39.2%
2024-05-11T14:54:47.461355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2330
18.3%
서 615
 
4.8%
1 534
 
4.2%
동 529
 
4.1%
울 513
 
4.0%
지 512
 
4.0%
마 505
 
4.0%
포 505
 
4.0%
구 502
 
3.9%
시 501
 
3.9%
Other values (165) 5710
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7259
56.9%
Decimal Number 2531
 
19.8%
Space Separator 2330
 
18.3%
Dash Punctuation 459
 
3.6%
Open Punctuation 64
 
0.5%
Close Punctuation 64
 
0.5%
Other Punctuation 35
 
0.3%
Uppercase Letter 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 615
 
8.5%
동 529
 
7.3%
울 513
 
7.1%
지 512
 
7.1%
마 505
 
7.0%
포 505
 
7.0%
구 502
 
6.9%
시 501
 
6.9%
별 500
 
6.9%
특 499
 
6.9%
Other values (138) 2078
28.6%
Decimal Number
ValueCountFrequency (%)
1 534
21.1%
3 341
13.5%
2 336
13.3%
4 314
12.4%
5 212
 
8.4%
0 184
 
7.3%
6 182
 
7.2%
7 165
 
6.5%
8 145
 
5.7%
9 118
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 4
28.6%
E 2
14.3%
A 1
 
7.1%
S 1
 
7.1%
K 1
 
7.1%
R 1
 
7.1%
P 1
 
7.1%
C 1
 
7.1%
J 1
 
7.1%
F 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 31
88.6%
. 3
 
8.6%
& 1
 
2.9%
Space Separator
ValueCountFrequency (%)
2330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 459
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7259
56.9%
Common 5483
43.0%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 615
 
8.5%
동 529
 
7.3%
울 513
 
7.1%
지 512
 
7.1%
마 505
 
7.0%
포 505
 
7.0%
구 502
 
6.9%
시 501
 
6.9%
별 500
 
6.9%
특 499
 
6.9%
Other values (138) 2078
28.6%
Common
ValueCountFrequency (%)
2330
42.5%
1 534
 
9.7%
- 459
 
8.4%
3 341
 
6.2%
2 336
 
6.1%
4 314
 
5.7%
5 212
 
3.9%
0 184
 
3.4%
6 182
 
3.3%
7 165
 
3.0%
Other values (7) 426
 
7.8%
Latin
ValueCountFrequency (%)
B 4
28.6%
E 2
14.3%
A 1
 
7.1%
S 1
 
7.1%
K 1
 
7.1%
R 1
 
7.1%
P 1
 
7.1%
C 1
 
7.1%
J 1
 
7.1%
F 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7259
56.9%
ASCII 5497
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2330
42.4%
1 534
 
9.7%
- 459
 
8.4%
3 341
 
6.2%
2 336
 
6.1%
4 314
 
5.7%
5 212
 
3.9%
0 184
 
3.3%
6 182
 
3.3%
7 165
 
3.0%
Other values (17) 440
 
8.0%
Hangul
ValueCountFrequency (%)
서 615
 
8.5%
동 529
 
7.3%
울 513
 
7.1%
지 512
 
7.1%
마 505
 
7.0%
포 505
 
7.0%
구 502
 
6.9%
시 501
 
6.9%
별 500
 
6.9%
특 499
 
6.9%
Other values (138) 2078
28.6%

도로명주소
Text

MISSING 

Distinct315
Distinct (%)97.8%
Missing179
Missing (%)35.7%
Memory size4.0 KiB
2024-05-11T14:54:47.919332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length51
Mean length31.552795
Min length22

Characters and Unicode

Total characters10160
Distinct characters196
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

Unique312 ?
Unique (%)96.9%

Sample

1st row서울특별시 마포구 마포대로12길 32 (공덕동, (1,2층))
2nd row서울특별시 마포구 굴레방로7길 5 (아현동, (1층))
3rd row서울특별시 마포구 마포대로20길 18 (아현동, (지층))
4th row서울특별시 마포구 월드컵북로8길 3, 지층 (연남동)
5th row서울특별시 마포구 대흥로20길 4 (대흥동, (지층))
ValueCountFrequency (%)
서울특별시 322
 
15.8%
마포구 322
 
15.8%
1층 138
 
6.8%
서교동 71
 
3.5%
2층 34
 
1.7%
성산동 32
 
1.6%
지하1층 30
 
1.5%
망원동 29
 
1.4%
연남동 28
 
1.4%
공덕동 23
 
1.1%
Other values (463) 1013
49.6%
2024-05-11T14:54:48.644471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1720
 
16.9%
1 463
 
4.6%
서 416
 
4.1%
동 371
 
3.7%
포 346
 
3.4%
) 344
 
3.4%
( 344
 
3.4%
마 341
 
3.4%
, 341
 
3.4%
울 339
 
3.3%
Other values (186) 5135
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5882
57.9%
Space Separator 1720
 
16.9%
Decimal Number 1455
 
14.3%
Close Punctuation 344
 
3.4%
Open Punctuation 344
 
3.4%
Other Punctuation 341
 
3.4%
Dash Punctuation 56
 
0.6%
Uppercase Letter 15
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 416
 
7.1%
동 371
 
6.3%
포 346
 
5.9%
마 341
 
5.8%
울 339
 
5.8%
시 324
 
5.5%
구 324
 
5.5%
특 322
 
5.5%
별 322
 
5.5%
로 312
 
5.3%
Other values (163) 2465
41.9%
Decimal Number
ValueCountFrequency (%)
1 463
31.8%
2 254
17.5%
3 147
 
10.1%
4 100
 
6.9%
0 93
 
6.4%
5 91
 
6.3%
6 89
 
6.1%
9 76
 
5.2%
7 75
 
5.2%
8 67
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 8
53.3%
E 2
 
13.3%
R 1
 
6.7%
K 1
 
6.7%
P 1
 
6.7%
A 1
 
6.7%
S 1
 
6.7%
Space Separator
ValueCountFrequency (%)
1720
100.0%
Close Punctuation
ValueCountFrequency (%)
) 344
100.0%
Open Punctuation
ValueCountFrequency (%)
( 344
100.0%
Other Punctuation
ValueCountFrequency (%)
, 341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5882
57.9%
Common 4263
42.0%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 416
 
7.1%
동 371
 
6.3%
포 346
 
5.9%
마 341
 
5.8%
울 339
 
5.8%
시 324
 
5.5%
구 324
 
5.5%
특 322
 
5.5%
별 322
 
5.5%
로 312
 
5.3%
Other values (163) 2465
41.9%
Common
ValueCountFrequency (%)
1720
40.3%
1 463
 
10.9%
) 344
 
8.1%
( 344
 
8.1%
, 341
 
8.0%
2 254
 
6.0%
3 147
 
3.4%
4 100
 
2.3%
0 93
 
2.2%
5 91
 
2.1%
Other values (6) 366
 
8.6%
Latin
ValueCountFrequency (%)
B 8
53.3%
E 2
 
13.3%
R 1
 
6.7%
K 1
 
6.7%
P 1
 
6.7%
A 1
 
6.7%
S 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5882
57.9%
ASCII 4278
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1720
40.2%
1 463
 
10.8%
) 344
 
8.0%
( 344
 
8.0%
, 341
 
8.0%
2 254
 
5.9%
3 147
 
3.4%
4 100
 
2.3%
0 93
 
2.2%
5 91
 
2.1%
Other values (13) 381
 
8.9%
Hangul
ValueCountFrequency (%)
서 416
 
7.1%
동 371
 
6.3%
포 346
 
5.9%
마 341
 
5.8%
울 339
 
5.8%
시 324
 
5.5%
구 324
 
5.5%
특 322
 
5.5%
별 322
 
5.5%
로 312
 
5.3%
Other values (163) 2465
41.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct144
Distinct (%)45.4%
Missing184
Missing (%)36.7%
Infinite0
Infinite (%)0.0%
Mean4051.6435
Minimum3901
Maximum4214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:48.910037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3901
5-th percentile3950.6
Q13993
median4043
Q34098
95-th percentile4190
Maximum4214
Range313
Interquartile range (IQR)105

Descriptive statistics

Standard deviation74.249978
Coefficient of variation (CV)0.018325891
Kurtosis-0.66140263
Mean4051.6435
Median Absolute Deviation (MAD)52
Skewness0.4396671
Sum1284371
Variance5513.0592
MonotonicityNot monotonic
2024-05-11T14:54:49.468365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4147 8
 
1.6%
3964 7
 
1.4%
4039 6
 
1.2%
4061 6
 
1.2%
3999 6
 
1.2%
4059 6
 
1.2%
4003 6
 
1.2%
3975 6
 
1.2%
4002 5
 
1.0%
3978 5
 
1.0%
Other values (134) 256
51.1%
(Missing) 184
36.7%
ValueCountFrequency (%)
3901 1
 
0.2%
3909 1
 
0.2%
3911 2
0.4%
3920 1
 
0.2%
3927 3
0.6%
3930 2
0.4%
3940 1
 
0.2%
3946 1
 
0.2%
3948 1
 
0.2%
3949 3
0.6%
ValueCountFrequency (%)
4214 1
 
0.2%
4211 2
0.4%
4210 1
 
0.2%
4207 4
0.8%
4206 1
 
0.2%
4205 1
 
0.2%
4204 1
 
0.2%
4202 1
 
0.2%
4196 1
 
0.2%
4195 2
0.4%

사업장명
Text

Distinct482
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-05-11T14:54:49.857091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length7.0439122
Min length2

Characters and Unicode

Total characters3529
Distinct characters473
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

Unique466 ?
Unique (%)93.0%

Sample

1st row궁중병과
2nd row대왕식품
3rd row성산식품
4th row라이프식품
5th row마포묵집
ValueCountFrequency (%)
주식회사 12
 
2.0%
coffee 5
 
0.8%
수라한 3
 
0.5%
홍삼나라 3
 
0.5%
roasters 3
 
0.5%
커피 3
 
0.5%
진미식품 3
 
0.5%
한양식품 2
 
0.3%
주)마마스푸드 2
 
0.3%
랑데자뷰 2
 
0.3%
Other values (539) 554
93.6%
2024-05-11T14:54:50.463459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 147
 
4.2%
( 147
 
4.2%
스 132
 
3.7%
주 129
 
3.7%
식 92
 
2.6%
91
 
2.6%
이 88
 
2.5%
피 88
 
2.5%
커 81
 
2.3%
품 69
 
2.0%
Other values (463) 2465
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2825
80.1%
Lowercase Letter 150
 
4.3%
Close Punctuation 147
 
4.2%
Open Punctuation 147
 
4.2%
Uppercase Letter 138
 
3.9%
Space Separator 91
 
2.6%
Decimal Number 20
 
0.6%
Other Punctuation 9
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 132
 
4.7%
주 129
 
4.6%
식 92
 
3.3%
이 88
 
3.1%
피 88
 
3.1%
커 81
 
2.9%
품 69
 
2.4%
리 60
 
2.1%
드 53
 
1.9%
로 46
 
1.6%
Other values (405) 1987
70.3%
Uppercase Letter
ValueCountFrequency (%)
C 16
11.6%
F 15
10.9%
E 15
10.9%
A 10
 
7.2%
R 10
 
7.2%
N 10
 
7.2%
S 10
 
7.2%
O 8
 
5.8%
T 7
 
5.1%
I 7
 
5.1%
Other values (13) 30
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 27
18.0%
a 16
10.7%
o 15
10.0%
n 11
 
7.3%
r 10
 
6.7%
i 9
 
6.0%
t 9
 
6.0%
s 9
 
6.0%
y 8
 
5.3%
f 8
 
5.3%
Other values (12) 28
18.7%
Decimal Number
ValueCountFrequency (%)
1 6
30.0%
9 3
15.0%
0 3
15.0%
3 3
15.0%
2 3
15.0%
4 1
 
5.0%
6 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
& 7
77.8%
. 2
 
22.2%
Close Punctuation
ValueCountFrequency (%)
) 147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 147
100.0%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2825
80.1%
Common 416
 
11.8%
Latin 288
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 132
 
4.7%
주 129
 
4.6%
식 92
 
3.3%
이 88
 
3.1%
피 88
 
3.1%
커 81
 
2.9%
품 69
 
2.4%
리 60
 
2.1%
드 53
 
1.9%
로 46
 
1.6%
Other values (405) 1987
70.3%
Latin
ValueCountFrequency (%)
e 27
 
9.4%
C 16
 
5.6%
a 16
 
5.6%
o 15
 
5.2%
F 15
 
5.2%
E 15
 
5.2%
n 11
 
3.8%
A 10
 
3.5%
R 10
 
3.5%
N 10
 
3.5%
Other values (35) 143
49.7%
Common
ValueCountFrequency (%)
) 147
35.3%
( 147
35.3%
91
21.9%
& 7
 
1.7%
1 6
 
1.4%
9 3
 
0.7%
0 3
 
0.7%
3 3
 
0.7%
2 3
 
0.7%
. 2
 
0.5%
Other values (3) 4
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2825
80.1%
ASCII 704
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 147
20.9%
( 147
20.9%
91
12.9%
e 27
 
3.8%
C 16
 
2.3%
a 16
 
2.3%
o 15
 
2.1%
F 15
 
2.1%
E 15
 
2.1%
n 11
 
1.6%
Other values (48) 204
29.0%
Hangul
ValueCountFrequency (%)
스 132
 
4.7%
주 129
 
4.6%
식 92
 
3.3%
이 88
 
3.1%
피 88
 
3.1%
커 81
 
2.9%
품 69
 
2.4%
리 60
 
2.1%
드 53
 
1.9%
로 46
 
1.6%
Other values (405) 1987
70.3%

최종수정일자
Date

Distinct461
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum1999-04-26 00:00:00
Maximum2024-05-08 11:41:49
2024-05-11T14:54:50.711330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:50.976003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
I
385 
U
116 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 385
76.8%
U 116
 
23.2%

Length

2024-05-11T14:54:51.229378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:51.390528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 385
76.8%
u 116
 
23.2%

데이터갱신일자
Date

Distinct133
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:00:00
2024-05-11T14:54:51.557347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:51.795530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
식품제조가공업
371 
기타 식품제조가공업
130 

Length

Max length10
Median length7
Mean length7.7784431
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 371
74.1%
기타 식품제조가공업 130
 
25.9%

Length

2024-05-11T14:54:52.023203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:52.224390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 501
79.4%
기타 130
 
20.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct428
Distinct (%)87.9%
Missing14
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean193254.15
Minimum189855.43
Maximum196591.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:52.415468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189855.43
5-th percentile191282.38
Q1192173.68
median192981.45
Q3194386.62
95-th percentile195854.16
Maximum196591.61
Range6736.1737
Interquartile range (IQR)2212.9369

Descriptive statistics

Standard deviation1448.6078
Coefficient of variation (CV)0.0074958687
Kurtosis-0.70418703
Mean193254.15
Median Absolute Deviation (MAD)1017.8963
Skewness0.37017028
Sum94114772
Variance2098464.4
MonotonicityNot monotonic
2024-05-11T14:54:52.657904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195509.580070948 8
 
1.6%
194973.522057692 4
 
0.8%
195277.885388974 3
 
0.6%
193187.802952358 3
 
0.6%
194109.860156647 3
 
0.6%
193375.138347374 3
 
0.6%
194360.808986768 3
 
0.6%
192640.977688405 3
 
0.6%
192476.013385166 3
 
0.6%
192723.838327775 3
 
0.6%
Other values (418) 451
90.0%
(Missing) 14
 
2.8%
ValueCountFrequency (%)
189855.433985731 1
0.2%
190204.923593825 2
0.4%
190293.979873354 1
0.2%
190521.358196451 1
0.2%
190550.75245758 1
0.2%
190560.932391065 1
0.2%
190629.327891292 1
0.2%
190658.42111541 1
0.2%
190786.194134663 1
0.2%
190786.809031067 1
0.2%
ValueCountFrequency (%)
196591.607707416 1
0.2%
196532.181700477 1
0.2%
196489.584597974 1
0.2%
196455.938299264 1
0.2%
196361.69342531 1
0.2%
196343.707794615 1
0.2%
196215.472761903 1
0.2%
196200.034954729 1
0.2%
196181.31736142 2
0.4%
196133.885513854 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct428
Distinct (%)87.9%
Missing14
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean450200.84
Minimum448236.66
Maximum453614.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:52.944452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448236.66
5-th percentile448927.06
Q1449544.92
median450172.18
Q3450707.41
95-th percentile451605.65
Maximum453614.58
Range5377.9279
Interquartile range (IQR)1162.4906

Descriptive statistics

Standard deviation868.84572
Coefficient of variation (CV)0.0019299069
Kurtosis0.70120448
Mean450200.84
Median Absolute Deviation (MAD)581.11809
Skewness0.57988528
Sum2.1924781 × 108
Variance754892.88
MonotonicityNot monotonic
2024-05-11T14:54:53.183791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449388.269219974 8
 
1.6%
449352.14991363 4
 
0.8%
448919.647035291 3
 
0.6%
450172.178899424 3
 
0.6%
449424.293487216 3
 
0.6%
449183.946919867 3
 
0.6%
448982.671515068 3
 
0.6%
449935.631575753 3
 
0.6%
451016.864330381 3
 
0.6%
449304.864311421 3
 
0.6%
Other values (418) 451
90.0%
(Missing) 14
 
2.8%
ValueCountFrequency (%)
448236.655548283 1
0.2%
448343.958279787 1
0.2%
448383.800703065 1
0.2%
448495.565766859 1
0.2%
448502.032041451 1
0.2%
448528.828102455 2
0.4%
448561.096565337 1
0.2%
448575.779442887 2
0.4%
448580.450852417 1
0.2%
448589.76644586 2
0.4%
ValueCountFrequency (%)
453614.583448105 1
0.2%
452969.084027083 1
0.2%
452862.522009516 1
0.2%
452845.757389594 1
0.2%
452815.74447831 1
0.2%
452795.78859222 1
0.2%
452763.733033021 1
0.2%
452751.198896623 1
0.2%
452694.976414446 1
0.2%
452609.00161076 1
0.2%

위생업태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
식품제조가공업
352 
기타 식품제조가공업
78 
<NA>
71 

Length

Max length10
Median length7
Mean length7.0419162
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 352
70.3%
기타 식품제조가공업 78
 
15.6%
<NA> 71
 
14.2%

Length

2024-05-11T14:54:53.419240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:53.696703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 430
74.3%
기타 78
 
13.5%
na 71
 
12.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)9.3%
Missing404
Missing (%)80.6%
Infinite0
Infinite (%)0.0%
Mean1.814433
Minimum0
Maximum15
Zeros31
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:53.905319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5.2
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4804649
Coefficient of variation (CV)1.3670744
Kurtosis12.443316
Mean1.814433
Median Absolute Deviation (MAD)1
Skewness3.1273491
Sum176
Variance6.1527062
MonotonicityNot monotonic
2024-05-11T14:54:54.166307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 31
 
6.2%
2 23
 
4.6%
1 22
 
4.4%
3 9
 
1.8%
4 5
 
1.0%
5 2
 
0.4%
12 2
 
0.4%
6 2
 
0.4%
15 1
 
0.2%
(Missing) 404
80.6%
ValueCountFrequency (%)
0 31
6.2%
1 22
4.4%
2 23
4.6%
3 9
 
1.8%
4 5
 
1.0%
5 2
 
0.4%
6 2
 
0.4%
12 2
 
0.4%
15 1
 
0.2%
ValueCountFrequency (%)
15 1
 
0.2%
12 2
 
0.4%
6 2
 
0.4%
5 2
 
0.4%
4 5
 
1.0%
3 9
 
1.8%
2 23
4.6%
1 22
4.4%
0 31
6.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)12.1%
Missing410
Missing (%)81.8%
Infinite0
Infinite (%)0.0%
Mean2.3186813
Minimum0
Maximum20
Zeros30
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:54.416862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile11.5
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.2969734
Coefficient of variation (CV)1.8531971
Kurtosis11.08903
Mean2.3186813
Median Absolute Deviation (MAD)1
Skewness3.3709482
Sum211
Variance18.46398
MonotonicityNot monotonic
2024-05-11T14:54:54.636992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 30
 
6.0%
1 24
 
4.8%
2 15
 
3.0%
3 12
 
2.4%
20 3
 
0.6%
4 2
 
0.4%
5 1
 
0.2%
7 1
 
0.2%
6 1
 
0.2%
16 1
 
0.2%
(Missing) 410
81.8%
ValueCountFrequency (%)
0 30
6.0%
1 24
4.8%
2 15
3.0%
3 12
 
2.4%
4 2
 
0.4%
5 1
 
0.2%
6 1
 
0.2%
7 1
 
0.2%
16 1
 
0.2%
19 1
 
0.2%
ValueCountFrequency (%)
20 3
 
0.6%
19 1
 
0.2%
16 1
 
0.2%
7 1
 
0.2%
6 1
 
0.2%
5 1
 
0.2%
4 2
 
0.4%
3 12
2.4%
2 15
3.0%
1 24
4.8%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
419 
기타
46 
주택가주변
 
33
아파트지역
 
3

Length

Max length5
Median length4
Mean length3.8882236
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row주택가주변
3rd row주택가주변
4th row주택가주변
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 419
83.6%
기타 46
 
9.2%
주택가주변 33
 
6.6%
아파트지역 3
 
0.6%

Length

2024-05-11T14:54:54.924853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:55.159224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 419
83.6%
기타 46
 
9.2%
주택가주변 33
 
6.6%
아파트지역 3
 
0.6%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
419 
기타
73 
우수
 
6
자율
 
3

Length

Max length4
Median length4
Mean length3.6726547
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 419
83.6%
기타 73
 
14.6%
우수 6
 
1.2%
자율 3
 
0.6%

Length

2024-05-11T14:54:55.396302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:55.579136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 419
83.6%
기타 73
 
14.6%
우수 6
 
1.2%
자율 3
 
0.6%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
312 
상수도전용
188 
간이상수도
 
1

Length

Max length5
Median length4
Mean length4.3772455
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 312
62.3%
상수도전용 188
37.5%
간이상수도 1
 
0.2%

Length

2024-05-11T14:54:55.755157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:55.909010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 312
62.3%
상수도전용 188
37.5%
간이상수도 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
486 
0
 
15

Length

Max length4
Median length4
Mean length3.9101796
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> 486
97.0%
0 15
 
3.0%

Length

2024-05-11T14:54:56.095835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:56.269491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 486
97.0%
0 15
 
3.0%

본사종업원수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
291 
0
209 
2
 
1

Length

Max length4
Median length4
Mean length2.742515
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 291
58.1%
0 209
41.7%
2 1
 
0.2%

Length

2024-05-11T14:54:56.440537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:56.635926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 291
58.1%
0 209
41.7%
2 1
 
0.2%

공장사무직종업원수
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
287 
0
206 
1
 
7
3
 
1

Length

Max length4
Median length4
Mean length2.7185629
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 287
57.3%
0 206
41.1%
1 7
 
1.4%
3 1
 
0.2%

Length

2024-05-11T14:54:56.892259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.143902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 287
57.3%
0 206
41.1%
1 7
 
1.4%
3 1
 
0.2%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
289 
0
207 
1
 
5

Length

Max length4
Median length4
Mean length2.7305389
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 289
57.7%
0 207
41.3%
1 5
 
1.0%

Length

2024-05-11T14:54:57.378388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.576081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
57.7%
0 207
41.3%
1 5
 
1.0%

공장생산직종업원수
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
277 
0
195 
1
 
23
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length2.6586826
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 277
55.3%
0 195
38.9%
1 23
 
4.6%
2 4
 
0.8%
3 1
 
0.2%
5 1
 
0.2%

Length

2024-05-11T14:54:57.781444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.961279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 277
55.3%
0 195
38.9%
1 23
 
4.6%
2 4
 
0.8%
3 1
 
0.2%
5 1
 
0.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
280 
임대
162 
자가
59 

Length

Max length4
Median length4
Mean length3.1177645
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> 280
55.9%
임대 162
32.3%
자가 59
 
11.8%

Length

2024-05-11T14:54:58.169999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:58.364175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 280
55.9%
임대 162
32.3%
자가 59
 
11.8%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)9.1%
Missing435
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean3636363.6
Minimum0
Maximum40000000
Zeros54
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:58.564602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20000000
Maximum40000000
Range40000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8662272.5
Coefficient of variation (CV)2.3821249
Kurtosis5.9942099
Mean3636363.6
Median Absolute Deviation (MAD)0
Skewness2.5231839
Sum2.4 × 108
Variance7.5034965 × 1013
MonotonicityNot monotonic
2024-05-11T14:54:58.772781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 54
 
10.8%
20000000 4
 
0.8%
10000000 3
 
0.6%
30000000 2
 
0.4%
15000000 2
 
0.4%
40000000 1
 
0.2%
(Missing) 435
86.8%
ValueCountFrequency (%)
0 54
10.8%
10000000 3
 
0.6%
15000000 2
 
0.4%
20000000 4
 
0.8%
30000000 2
 
0.4%
40000000 1
 
0.2%
ValueCountFrequency (%)
40000000 1
 
0.2%
30000000 2
 
0.4%
20000000 4
 
0.8%
15000000 2
 
0.4%
10000000 3
 
0.6%
0 54
10.8%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)12.5%
Missing437
Missing (%)87.2%
Infinite0
Infinite (%)0.0%
Mean250781.25
Minimum0
Maximum3500000
Zeros54
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:58.987434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1925000
Maximum3500000
Range3500000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation700990.92
Coefficient of variation (CV)2.7952286
Kurtosis10.645901
Mean250781.25
Median Absolute Deviation (MAD)0
Skewness3.2376869
Sum16050000
Variance4.9138827 × 1011
MonotonicityNot monotonic
2024-05-11T14:54:59.405110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 54
 
10.8%
2000000 2
 
0.4%
1000000 2
 
0.4%
800000 2
 
0.4%
1500000 1
 
0.2%
450000 1
 
0.2%
3500000 1
 
0.2%
3000000 1
 
0.2%
(Missing) 437
87.2%
ValueCountFrequency (%)
0 54
10.8%
450000 1
 
0.2%
800000 2
 
0.4%
1000000 2
 
0.4%
1500000 1
 
0.2%
2000000 2
 
0.4%
3000000 1
 
0.2%
3500000 1
 
0.2%
ValueCountFrequency (%)
3500000 1
 
0.2%
3000000 1
 
0.2%
2000000 2
 
0.4%
1500000 1
 
0.2%
1000000 2
 
0.4%
800000 2
 
0.4%
450000 1
 
0.2%
0 54
10.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing71
Missing (%)14.2%
Memory size1.1 KiB
False
430 
(Missing)
71 
ValueCountFrequency (%)
False 430
85.8%
(Missing) 71
 
14.2%
2024-05-11T14:54:59.625296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct87
Distinct (%)20.2%
Missing71
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean6.1226279
Minimum0
Maximum230
Zeros342
Zeros (%)68.3%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-05-11T14:54:59.808119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28.0075
Maximum230
Range230
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24.805671
Coefficient of variation (CV)4.0514745
Kurtosis52.252332
Mean6.1226279
Median Absolute Deviation (MAD)0
Skewness6.7551448
Sum2632.73
Variance615.3213
MonotonicityNot monotonic
2024-05-11T14:55:00.128222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 342
68.3%
24.78 2
 
0.4%
13.1 2
 
0.4%
6.44 1
 
0.2%
1.65 1
 
0.2%
3.6 1
 
0.2%
12.34 1
 
0.2%
7.06 1
 
0.2%
2.3 1
 
0.2%
4.39 1
 
0.2%
Other values (77) 77
 
15.4%
(Missing) 71
 
14.2%
ValueCountFrequency (%)
0.0 342
68.3%
1.5 1
 
0.2%
1.65 1
 
0.2%
1.66 1
 
0.2%
1.7 1
 
0.2%
1.78 1
 
0.2%
1.82 1
 
0.2%
2.0 1
 
0.2%
2.16 1
 
0.2%
2.3 1
 
0.2%
ValueCountFrequency (%)
230.0 1
0.2%
221.0 1
0.2%
217.2 1
0.2%
213.51 1
0.2%
113.74 1
0.2%
103.95 1
0.2%
87.62 1
0.2%
76.66 1
0.2%
70.5 1
0.2%
66.65 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing501
Missing (%)100.0%
Memory size4.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031300003130000-106-1971-0001219710317<NA>3폐업2폐업20030414<NA><NA><NA>02 3242073135.66121824서울특별시 마포구 망원동 436-14번지 2F동<NA><NA>궁중병과2001-02-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업191296.011077450900.597635식품제조가공업34기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131300003130000-106-1971-0002619710612<NA>3폐업2폐업19950905<NA><NA><NA>02 7159459113.0121811서울특별시 마포구 대흥동 436-1번지<NA><NA>대왕식품2001-10-05 00:00:00I2018-08-31 23:59:59.0식품제조가공업194965.128164449297.139445식품제조가공업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231300003130000-106-1971-0002719710730<NA>3폐업2폐업20040726<NA><NA><NA>02 3245739167.12121826서울특별시 마포구 망원동 469-39번지 (지층.1층)<NA><NA>성산식품2000-11-17 00:00:00I2018-08-31 23:59:59.0식품제조가공업191336.450669451081.752688식품제조가공업50주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331300003130000-106-1973-0000819731031<NA>3폐업2폐업20010620<NA><NA><NA>0276.18121889서울특별시 마포구 망원동 455-48번지<NA><NA>라이프식품2001-06-20 00:00:00I2018-08-31 23:59:59.0식품제조가공업191115.640353450310.65119식품제조가공업22주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431300003130000-106-1973-0002919730602<NA>3폐업2폐업20140602<NA><NA><NA>02 7120961118.75121803서울특별시 마포구 공덕동 242-4번지 (1,2층)서울특별시 마포구 마포대로12길 32 (공덕동, (1,2층))4211마포묵집2012-08-23 17:20:13I2018-08-31 23:59:59.0식품제조가공업195925.079127449475.011743식품제조가공업31주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531300003130000-106-1974-0004319740627<NA>3폐업2폐업20000523<NA><NA><NA>020.0121820서울특별시 마포구 망원동 377-3번지<NA><NA>한국식용얼름2000-05-23 00:00:00I2018-08-31 23:59:59.0식품제조가공업191963.553383450408.777619식품제조가공업31기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631300003130000-106-1976-0002819761028<NA>3폐업2폐업20051205<NA><NA><NA>02 7175454229.38121801서울특별시 마포구 공덕동 105-144번지 (1층)<NA><NA>농가식품2005-02-22 00:00:00I2018-08-31 23:59:59.0식품제조가공업196181.317361449716.543346식품제조가공업42주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731300003130000-106-1977-007851977-08-17<NA>3폐업2폐업2023-10-11<NA><NA><NA>02 364448882.8121-859서울특별시 마포구 아현동 291-20 (1층)서울특별시 마포구 굴레방로7길 5 (아현동, (1층))4116진미식품2023-10-11 13:43:03U2022-10-30 23:03:00.0식품제조가공업195973.111495450443.280691<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831300003130000-106-1981-0073719810920<NA>3폐업2폐업20041230<NA><NA><NA>02 336542268.12121826서울특별시 마포구 망원동 469-4번지 (1층, 2층)<NA><NA>형선제과2000-11-17 00:00:00I2018-08-31 23:59:59.0식품제조가공업191295.900089451103.613294식품제조가공업31기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931300003130000-106-1982-0000919820312<NA>3폐업2폐업19990426<NA><NA><NA>02183.15121866서울특별시 마포구 연남동 361-42번지<NA><NA>바로방제과주식회사1999-04-26 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업1520기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
49131300003130000-106-2023-000062023-06-19<NA>3폐업2폐업2024-05-08<NA><NA><NA>0708065015861.0121-804서울특별시 마포구 공덕동 370-4 서울창업허브, 서울복지타운서울특별시 마포구 백범로31길 21, 서울창업허브, 서울복지타운 3층 키친인큐베이터(제조주방)호 (공덕동)4147케이맛스타2024-05-08 11:41:49U2023-12-04 23:00:00.0기타 식품제조가공업195509.580071449388.26922<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49231300003130000-106-2023-000072023-06-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.0121-804서울특별시 마포구 공덕동 370-4 서울창업허브, 서울복지타운서울특별시 마포구 백범로31길 21, 서울창업허브, 서울복지타운 3층 키친인큐베이터(제조주방)호 (공덕동)4147슬런치팩토리2023-11-20 09:09:14U2022-10-31 22:02:00.0기타 식품제조가공업195509.580071449388.26922<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49331300003130000-106-2023-000082023-07-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.0121-804서울특별시 마포구 공덕동 370-4 서울창업허브, 서울복지타운서울특별시 마포구 백범로31길 21, 서울창업허브, 서울복지타운 3층 키친인큐베이터(제조주방)호 (공덕동)4147위가코리아2023-07-05 09:38:33I2022-12-07 00:07:00.0기타 식품제조가공업195509.580071449388.26922<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49431300003130000-106-2023-000092023-09-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 335777912.0121-816서울특별시 마포구 동교동 117-3서울특별시 마포구 연희로 29-1, 2층 일부호 (동교동)3985센트럴사이트 연남점2023-09-08 14:43:14I2022-12-08 23:00:00.0기타 식품제조가공업193466.01451033.836667<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49531300003130000-106-2023-000102023-12-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0121-837서울특별시 마포구 서교동 486 서교푸르지오서울특별시 마포구 홍익로 10, 상가 101동 1층 128호 (서교동, 서교푸르지오)4055카츠업푸드2023-12-04 15:03:52I2022-11-02 00:06:00.0기타 식품제조가공업193187.802952450172.178899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49631300003130000-106-2023-000112023-12-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>54.75121-800서울특별시 마포구 공덕동 1-48서울특별시 마포구 만리재로 132, 1층 (공덕동)4183어니언(onion)2023-12-19 10:03:18I2022-11-01 22:01:00.0기타 식품제조가공업196591.607707449876.371361<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49731300003130000-106-2024-000012024-01-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.86121-842서울특별시 마포구 서교동 468-25서울특별시 마포구 잔다리로 99-2, 1층 (서교동)4003공명 합정점(서울작업실)2024-01-09 10:03:13I2023-11-30 23:01:00.0기타 식품제조가공업192385.126331450423.883916<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49831300003130000-106-2024-000022024-01-15<NA>1영업/정상1영업<NA><NA><NA><NA>02307282013.9121-830서울특별시 마포구 상암동 2-10서울특별시 마포구 성암로 223-1, 1층 (상암동)3927레프트커피컴퍼니2024-01-16 10:41:24I2023-11-30 23:08:00.0기타 식품제조가공업190658.421115452969.084027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49931300003130000-106-2024-000032024-01-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.0121-804서울특별시 마포구 공덕동 370-4 서울창업허브서울특별시 마포구 백범로31길 21, 서울창업허브 3층 키친인큐베이터(제조주방)호 (공덕동)4147빈크런치2024-01-26 11:08:07I2023-11-30 22:08:00.0기타 식품제조가공업195509.580071449388.26922<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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