Overview

Dataset statistics

Number of variables44
Number of observations229
Missing cells2350
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory84.2 KiB
Average record size in memory376.6 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric7
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18261/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (61.4%)Imbalance
위생업태명 is highly imbalanced (50.8%)Imbalance
남성종사자수 is highly imbalanced (56.3%)Imbalance
여성종사자수 is highly imbalanced (57.7%)Imbalance
총인원 is highly imbalanced (80.3%)Imbalance
인허가취소일자 has 229 (100.0%) missing valuesMissing
폐업일자 has 28 (12.2%) missing valuesMissing
휴업시작일자 has 229 (100.0%) missing valuesMissing
휴업종료일자 has 229 (100.0%) missing valuesMissing
재개업일자 has 229 (100.0%) missing valuesMissing
전화번호 has 58 (25.3%) missing valuesMissing
소재지면적 has 20 (8.7%) missing valuesMissing
도로명주소 has 122 (53.3%) missing valuesMissing
도로명우편번호 has 126 (55.0%) missing valuesMissing
좌표정보(X) has 6 (2.6%) missing valuesMissing
좌표정보(Y) has 6 (2.6%) missing valuesMissing
보증액 has 180 (78.6%) missing valuesMissing
월세액 has 181 (79.0%) missing valuesMissing
다중이용업소여부 has 10 (4.4%) missing valuesMissing
시설총규모 has 10 (4.4%) missing valuesMissing
전통업소지정번호 has 229 (100.0%) missing valuesMissing
전통업소주된음식 has 229 (100.0%) missing valuesMissing
홈페이지 has 229 (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
보증액 has 36 (15.7%) zerosZeros
월세액 has 36 (15.7%) zerosZeros
시설총규모 has 185 (80.8%) zerosZeros

Reproduction

Analysis started2024-04-29 19:40:31.660904
Analysis finished2024-04-29 19:40:32.587660
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3090000
229 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 229
100.0%

Length

2024-04-30T04:40:32.645031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:32.713901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 229
100.0%

관리번호
Text

UNIQUE 

Distinct229
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-30T04:40:32.848170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5038
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

Unique229 ?
Unique (%)100.0%

Sample

1st row3090000-106-1968-00383
2nd row3090000-106-1976-00033
3rd row3090000-106-1982-00001
4th row3090000-106-1984-00001
5th row3090000-106-1991-00001
ValueCountFrequency (%)
3090000-106-1968-00383 1
 
0.4%
3090000-106-2005-00005 1
 
0.4%
3090000-106-2008-00004 1
 
0.4%
3090000-106-2008-00005 1
 
0.4%
3090000-106-2008-00006 1
 
0.4%
3090000-106-2009-00001 1
 
0.4%
3090000-106-2009-00002 1
 
0.4%
3090000-106-2009-00003 1
 
0.4%
3090000-106-2009-00004 1
 
0.4%
3090000-106-2009-00005 1
 
0.4%
Other values (219) 219
95.6%
2024-04-30T04:40:33.162678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2473
49.1%
- 687
 
13.6%
1 437
 
8.7%
9 404
 
8.0%
3 300
 
6.0%
6 286
 
5.7%
2 244
 
4.8%
4 60
 
1.2%
8 53
 
1.1%
7 50
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4351
86.4%
Dash Punctuation 687
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2473
56.8%
1 437
 
10.0%
9 404
 
9.3%
3 300
 
6.9%
6 286
 
6.6%
2 244
 
5.6%
4 60
 
1.4%
8 53
 
1.2%
7 50
 
1.1%
5 44
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5038
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2473
49.1%
- 687
 
13.6%
1 437
 
8.7%
9 404
 
8.0%
3 300
 
6.0%
6 286
 
5.7%
2 244
 
4.8%
4 60
 
1.2%
8 53
 
1.1%
7 50
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5038
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2473
49.1%
- 687
 
13.6%
1 437
 
8.7%
9 404
 
8.0%
3 300
 
6.0%
6 286
 
5.7%
2 244
 
4.8%
4 60
 
1.2%
8 53
 
1.1%
7 50
 
1.0%

인허가일자
Date

Distinct224
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1968-01-08 00:00:00
Maximum2022-07-22 00:00:00
2024-04-30T04:40:33.302831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:33.435923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
201 
1
28 

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 (%)
3 201
87.8%
1 28
 
12.2%

Length

2024-04-30T04:40:33.561845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:33.631968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 201
87.8%
1 28
 
12.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
201 
영업/정상
28 

Length

Max length5
Median length2
Mean length2.3668122
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 201
87.8%
영업/정상 28
 
12.2%

Length

2024-04-30T04:40:33.715845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:33.802093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 201
87.8%
영업/정상 28
 
12.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2
201 
1
28 

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 (%)
2 201
87.8%
1 28
 
12.2%

Length

2024-04-30T04:40:33.878418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:33.948821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 201
87.8%
1 28
 
12.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
201 
영업
28 

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 201
87.8%
영업 28
 
12.2%

Length

2024-04-30T04:40:34.020650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:34.090524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 201
87.8%
영업 28
 
12.2%

폐업일자
Date

MISSING 

Distinct188
Distinct (%)93.5%
Missing28
Missing (%)12.2%
Memory size1.9 KiB
Minimum1996-01-22 00:00:00
Maximum2023-04-10 00:00:00
2024-04-30T04:40:34.191819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:34.313240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

전화번호
Text

MISSING 

Distinct164
Distinct (%)95.9%
Missing58
Missing (%)25.3%
Memory size1.9 KiB
2024-04-30T04:40:34.515816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.7192982
Min length2

Characters and Unicode

Total characters1662
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)95.3%

Sample

1st row02 9927882
2nd row02 9547536
3rd row02 9921191
4th row9930312
5th row02 9561232
ValueCountFrequency (%)
02 118
38.3%
070 3
 
1.0%
902 2
 
0.6%
990 2
 
0.6%
955 2
 
0.6%
02954 2
 
0.6%
954 2
 
0.6%
907 2
 
0.6%
9930312 2
 
0.6%
9561232 1
 
0.3%
Other values (172) 172
55.8%
2024-04-30T04:40:34.856397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 296
17.8%
9 245
14.7%
2 243
14.6%
160
9.6%
4 127
7.6%
5 124
7.5%
3 109
 
6.6%
8 98
 
5.9%
1 90
 
5.4%
6 87
 
5.2%
Other values (2) 83
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1501
90.3%
Space Separator 160
 
9.6%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 296
19.7%
9 245
16.3%
2 243
16.2%
4 127
8.5%
5 124
8.3%
3 109
 
7.3%
8 98
 
6.5%
1 90
 
6.0%
6 87
 
5.8%
7 82
 
5.5%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1662
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 296
17.8%
9 245
14.7%
2 243
14.6%
160
9.6%
4 127
7.6%
5 124
7.5%
3 109
 
6.6%
8 98
 
5.9%
1 90
 
5.4%
6 87
 
5.2%
Other values (2) 83
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 296
17.8%
9 245
14.7%
2 243
14.6%
160
9.6%
4 127
7.6%
5 124
7.5%
3 109
 
6.6%
8 98
 
5.9%
1 90
 
5.4%
6 87
 
5.2%
Other values (2) 83
 
5.0%

소재지면적
Real number (ℝ)

MISSING 

Distinct177
Distinct (%)84.7%
Missing20
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean73.976938
Minimum0
Maximum495
Zeros2
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:34.986609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.588
Q126.4
median53
Q398.46
95-th percentile189.382
Maximum495
Range495
Interquartile range (IQR)72.06

Descriptive statistics

Standard deviation75.254824
Coefficient of variation (CV)1.0172741
Kurtosis12.78682
Mean73.976938
Median Absolute Deviation (MAD)29.92
Skewness3.0245149
Sum15461.18
Variance5663.2885
MonotonicityNot monotonic
2024-04-30T04:40:35.099370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 7
 
3.1%
66.0 4
 
1.7%
60.0 3
 
1.3%
165.0 3
 
1.3%
10.0 3
 
1.3%
26.4 3
 
1.3%
25.0 2
 
0.9%
29.8 2
 
0.9%
87.0 2
 
0.9%
0.0 2
 
0.9%
Other values (167) 178
77.7%
(Missing) 20
 
8.7%
ValueCountFrequency (%)
0.0 2
0.9%
3.3 1
 
0.4%
5.6 1
 
0.4%
6.36 1
 
0.4%
7.41 1
 
0.4%
8.4 1
 
0.4%
9.86 1
 
0.4%
10.0 3
1.3%
11.47 1
 
0.4%
12.64 1
 
0.4%
ValueCountFrequency (%)
495.0 1
0.4%
493.91 1
0.4%
471.34 1
0.4%
385.0 1
0.4%
284.0 1
0.4%
227.0 1
0.4%
218.29 1
0.4%
206.0 1
0.4%
200.0 1
0.4%
199.8 1
0.4%

소재지우편번호
Text

Distinct81
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-30T04:40:35.334003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0218341
Min length6

Characters and Unicode

Total characters1379
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

Unique34 ?
Unique (%)14.8%

Sample

1st row132920
2nd row132-821
3rd row132854
4th row132919
5th row132809
ValueCountFrequency (%)
132919 12
 
5.2%
132917 11
 
4.8%
132920 9
 
3.9%
132010 8
 
3.5%
132924 8
 
3.5%
132918 7
 
3.1%
132896 7
 
3.1%
132822 7
 
3.1%
132916 6
 
2.6%
132913 6
 
2.6%
Other values (71) 148
64.6%
2024-04-30T04:40:35.668203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 310
22.5%
2 302
21.9%
3 261
18.9%
8 167
12.1%
9 126
9.1%
0 69
 
5.0%
4 45
 
3.3%
6 43
 
3.1%
5 30
 
2.2%
7 21
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1374
99.6%
Dash Punctuation 5
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 310
22.6%
2 302
22.0%
3 261
19.0%
8 167
12.2%
9 126
9.2%
0 69
 
5.0%
4 45
 
3.3%
6 43
 
3.1%
5 30
 
2.2%
7 21
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 310
22.5%
2 302
21.9%
3 261
18.9%
8 167
12.1%
9 126
9.1%
0 69
 
5.0%
4 45
 
3.3%
6 43
 
3.1%
5 30
 
2.2%
7 21
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 310
22.5%
2 302
21.9%
3 261
18.9%
8 167
12.1%
9 126
9.1%
0 69
 
5.0%
4 45
 
3.3%
6 43
 
3.1%
5 30
 
2.2%
7 21
 
1.5%

지번주소
Text

Distinct217
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-30T04:40:35.910805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length39
Mean length24.668122
Min length19

Characters and Unicode

Total characters5649
Distinct characters99
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

Unique206 ?
Unique (%)90.0%

Sample

1st row서울특별시 도봉구 창동 629-9번지
2nd row서울특별시 도봉구 도봉동 626-117
3rd row서울특별시 도봉구 방학동 720번지
4th row서울특별시 도봉구 창동 607-25번지
5th row서울특별시 도봉구 도봉동 470-6번지
ValueCountFrequency (%)
서울특별시 229
21.7%
도봉구 229
21.7%
창동 89
 
8.5%
방학동 49
 
4.7%
쌍문동 49
 
4.7%
도봉동 42
 
4.0%
1층 25
 
2.4%
2층 14
 
1.3%
지하1층 11
 
1.0%
657번지 5
 
0.5%
Other values (268) 311
29.5%
2024-04-30T04:40:36.260429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1033
18.3%
도 276
 
4.9%
봉 276
 
4.9%
동 237
 
4.2%
지 232
 
4.1%
서 230
 
4.1%
구 230
 
4.1%
특 229
 
4.1%
별 229
 
4.1%
시 229
 
4.1%
Other values (89) 2448
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3202
56.7%
Decimal Number 1183
 
20.9%
Space Separator 1033
 
18.3%
Dash Punctuation 204
 
3.6%
Other Punctuation 9
 
0.2%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 276
 
8.6%
봉 276
 
8.6%
동 237
 
7.4%
지 232
 
7.2%
서 230
 
7.2%
구 230
 
7.2%
특 229
 
7.2%
별 229
 
7.2%
시 229
 
7.2%
울 229
 
7.2%
Other values (69) 805
25.1%
Decimal Number
ValueCountFrequency (%)
1 198
16.7%
6 157
13.3%
3 138
11.7%
2 133
11.2%
5 126
10.7%
7 110
9.3%
4 100
8.5%
0 98
8.3%
8 64
 
5.4%
9 59
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
G 1
25.0%
I 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 6
66.7%
@ 3
33.3%
Space Separator
ValueCountFrequency (%)
1033
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3202
56.7%
Common 2443
43.2%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 276
 
8.6%
봉 276
 
8.6%
동 237
 
7.4%
지 232
 
7.2%
서 230
 
7.2%
구 230
 
7.2%
특 229
 
7.2%
별 229
 
7.2%
시 229
 
7.2%
울 229
 
7.2%
Other values (69) 805
25.1%
Common
ValueCountFrequency (%)
1033
42.3%
- 204
 
8.4%
1 198
 
8.1%
6 157
 
6.4%
3 138
 
5.6%
2 133
 
5.4%
5 126
 
5.2%
7 110
 
4.5%
4 100
 
4.1%
0 98
 
4.0%
Other values (6) 146
 
6.0%
Latin
ValueCountFrequency (%)
L 1
25.0%
G 1
25.0%
I 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3202
56.7%
ASCII 2447
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1033
42.2%
- 204
 
8.3%
1 198
 
8.1%
6 157
 
6.4%
3 138
 
5.6%
2 133
 
5.4%
5 126
 
5.1%
7 110
 
4.5%
4 100
 
4.1%
0 98
 
4.0%
Other values (10) 150
 
6.1%
Hangul
ValueCountFrequency (%)
도 276
 
8.6%
봉 276
 
8.6%
동 237
 
7.4%
지 232
 
7.2%
서 230
 
7.2%
구 230
 
7.2%
특 229
 
7.2%
별 229
 
7.2%
시 229
 
7.2%
울 229
 
7.2%
Other values (69) 805
25.1%

도로명주소
Text

MISSING 

Distinct104
Distinct (%)97.2%
Missing122
Missing (%)53.3%
Memory size1.9 KiB
2024-04-30T04:40:36.503826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length29.953271
Min length22

Characters and Unicode

Total characters3205
Distinct characters92
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

Unique101 ?
Unique (%)94.4%

Sample

1st row서울특별시 도봉구 도봉로104길 69 (창동)
2nd row서울특별시 도봉구 도봉로164길 41 (도봉동)
3rd row서울특별시 도봉구 도봉로 452 (창동)
4th row서울특별시 도봉구 시루봉로 307 (도봉동)
5th row서울특별시 도봉구 도봉로136다길 25 (창동)
ValueCountFrequency (%)
서울특별시 107
16.9%
도봉구 107
16.9%
창동 38
 
6.0%
방학동 26
 
4.1%
1층 25
 
3.9%
도봉동 19
 
3.0%
쌍문동 17
 
2.7%
2층 13
 
2.1%
지하1층 10
 
1.6%
마들로 10
 
1.6%
Other values (188) 261
41.2%
2024-04-30T04:40:36.885663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
526
 
16.4%
봉 170
 
5.3%
도 168
 
5.2%
1 139
 
4.3%
시 118
 
3.7%
동 111
 
3.5%
( 108
 
3.4%
) 108
 
3.4%
울 107
 
3.3%
서 107
 
3.3%
Other values (82) 1543
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1803
56.3%
Decimal Number 540
 
16.8%
Space Separator 526
 
16.4%
Open Punctuation 108
 
3.4%
Close Punctuation 108
 
3.4%
Other Punctuation 103
 
3.2%
Dash Punctuation 15
 
0.5%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 170
 
9.4%
도 168
 
9.3%
시 118
 
6.5%
동 111
 
6.2%
울 107
 
5.9%
서 107
 
5.9%
특 107
 
5.9%
구 107
 
5.9%
별 107
 
5.9%
로 104
 
5.8%
Other values (65) 597
33.1%
Decimal Number
ValueCountFrequency (%)
1 139
25.7%
2 91
16.9%
3 58
10.7%
4 48
 
8.9%
6 43
 
8.0%
0 39
 
7.2%
5 38
 
7.0%
7 33
 
6.1%
9 27
 
5.0%
8 24
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 102
99.0%
@ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
526
100.0%
Open Punctuation
ValueCountFrequency (%)
( 108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1803
56.3%
Common 1400
43.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 170
 
9.4%
도 168
 
9.3%
시 118
 
6.5%
동 111
 
6.2%
울 107
 
5.9%
서 107
 
5.9%
특 107
 
5.9%
구 107
 
5.9%
별 107
 
5.9%
로 104
 
5.8%
Other values (65) 597
33.1%
Common
ValueCountFrequency (%)
526
37.6%
1 139
 
9.9%
( 108
 
7.7%
) 108
 
7.7%
, 102
 
7.3%
2 91
 
6.5%
3 58
 
4.1%
4 48
 
3.4%
6 43
 
3.1%
0 39
 
2.8%
Other values (6) 138
 
9.9%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1803
56.3%
ASCII 1402
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
526
37.5%
1 139
 
9.9%
( 108
 
7.7%
) 108
 
7.7%
, 102
 
7.3%
2 91
 
6.5%
3 58
 
4.1%
4 48
 
3.4%
6 43
 
3.1%
0 39
 
2.8%
Other values (7) 140
 
10.0%
Hangul
ValueCountFrequency (%)
봉 170
 
9.4%
도 168
 
9.3%
시 118
 
6.5%
동 111
 
6.2%
울 107
 
5.9%
서 107
 
5.9%
특 107
 
5.9%
구 107
 
5.9%
별 107
 
5.9%
로 104
 
5.8%
Other values (65) 597
33.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)62.1%
Missing126
Missing (%)55.0%
Infinite0
Infinite (%)0.0%
Mean1392.0388
Minimum1301
Maximum1486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:37.014094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1301
5-th percentile1310.4
Q11330
median1376
Q31457.5
95-th percentile1476.9
Maximum1486
Range185
Interquartile range (IQR)127.5

Descriptive statistics

Standard deviation63.192815
Coefficient of variation (CV)0.04539587
Kurtosis-1.6194932
Mean1392.0388
Median Absolute Deviation (MAD)60
Skewness0.13657586
Sum143380
Variance3993.3318
MonotonicityNot monotonic
2024-04-30T04:40:37.167156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1325 7
 
3.1%
1457 4
 
1.7%
1471 4
 
1.7%
1340 4
 
1.7%
1314 4
 
1.7%
1368 3
 
1.3%
1476 3
 
1.3%
1453 3
 
1.3%
1357 3
 
1.3%
1316 2
 
0.9%
Other values (54) 66
28.8%
(Missing) 126
55.0%
ValueCountFrequency (%)
1301 1
 
0.4%
1302 2
 
0.9%
1305 2
 
0.9%
1310 1
 
0.4%
1314 4
1.7%
1315 1
 
0.4%
1316 2
 
0.9%
1318 1
 
0.4%
1322 2
 
0.9%
1325 7
3.1%
ValueCountFrequency (%)
1486 1
 
0.4%
1482 1
 
0.4%
1479 2
0.9%
1477 2
0.9%
1476 3
1.3%
1475 1
 
0.4%
1474 1
 
0.4%
1473 2
0.9%
1472 1
 
0.4%
1471 4
1.7%

사업장명
Text

Distinct221
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-30T04:40:37.400099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length5.8384279
Min length2

Characters and Unicode

Total characters1337
Distinct characters340
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

Unique215 ?
Unique (%)93.9%

Sample

1st row삼성식품
2nd row신영산업사
3rd row서울미원(주)
4th row창성식품
5th row승원실업(주)
ValueCountFrequency (%)
주식회사 8
 
3.1%
창성식품 3
 
1.2%
영식품 3
 
1.2%
작은아이 2
 
0.8%
두부명가 2
 
0.8%
청원식품 2
 
0.8%
성원식품 2
 
0.8%
시스템 2
 
0.8%
친구네식품 1
 
0.4%
웰미식품 1
 
0.4%
Other values (230) 230
89.8%
2024-04-30T04:40:37.895445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 83
 
6.2%
품 72
 
5.4%
이 34
 
2.5%
주 30
 
2.2%
27
 
2.0%
) 24
 
1.8%
( 24
 
1.8%
드 24
 
1.8%
스 19
 
1.4%
사 19
 
1.4%
Other values (330) 981
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1181
88.3%
Lowercase Letter 44
 
3.3%
Space Separator 27
 
2.0%
Close Punctuation 24
 
1.8%
Open Punctuation 24
 
1.8%
Uppercase Letter 21
 
1.6%
Other Punctuation 9
 
0.7%
Decimal Number 6
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 83
 
7.0%
품 72
 
6.1%
이 34
 
2.9%
주 30
 
2.5%
드 24
 
2.0%
스 19
 
1.6%
사 19
 
1.6%
리 18
 
1.5%
제 17
 
1.4%
푸 16
 
1.4%
Other values (287) 849
71.9%
Lowercase Letter
ValueCountFrequency (%)
a 9
20.5%
e 5
11.4%
o 4
9.1%
n 3
 
6.8%
s 3
 
6.8%
r 3
 
6.8%
y 2
 
4.5%
t 2
 
4.5%
l 2
 
4.5%
c 2
 
4.5%
Other values (8) 9
20.5%
Uppercase Letter
ValueCountFrequency (%)
C 3
14.3%
J 3
14.3%
O 2
9.5%
M 2
9.5%
R 2
9.5%
F 2
9.5%
U 1
 
4.8%
L 1
 
4.8%
S 1
 
4.8%
P 1
 
4.8%
Other values (3) 3
14.3%
Other Punctuation
ValueCountFrequency (%)
. 5
55.6%
? 2
 
22.2%
' 1
 
11.1%
& 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
5 1
 
16.7%
0 1
 
16.7%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1181
88.3%
Common 91
 
6.8%
Latin 65
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 83
 
7.0%
품 72
 
6.1%
이 34
 
2.9%
주 30
 
2.5%
드 24
 
2.0%
스 19
 
1.6%
사 19
 
1.6%
리 18
 
1.5%
제 17
 
1.4%
푸 16
 
1.4%
Other values (287) 849
71.9%
Latin
ValueCountFrequency (%)
a 9
 
13.8%
e 5
 
7.7%
o 4
 
6.2%
n 3
 
4.6%
C 3
 
4.6%
s 3
 
4.6%
r 3
 
4.6%
J 3
 
4.6%
O 2
 
3.1%
M 2
 
3.1%
Other values (21) 28
43.1%
Common
ValueCountFrequency (%)
27
29.7%
) 24
26.4%
( 24
26.4%
. 5
 
5.5%
2 3
 
3.3%
? 2
 
2.2%
' 1
 
1.1%
5 1
 
1.1%
0 1
 
1.1%
& 1
 
1.1%
Other values (2) 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1181
88.3%
ASCII 156
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 83
 
7.0%
품 72
 
6.1%
이 34
 
2.9%
주 30
 
2.5%
드 24
 
2.0%
스 19
 
1.6%
사 19
 
1.6%
리 18
 
1.5%
제 17
 
1.4%
푸 16
 
1.4%
Other values (287) 849
71.9%
ASCII
ValueCountFrequency (%)
27
17.3%
) 24
15.4%
( 24
15.4%
a 9
 
5.8%
e 5
 
3.2%
. 5
 
3.2%
o 4
 
2.6%
n 3
 
1.9%
C 3
 
1.9%
s 3
 
1.9%
Other values (33) 49
31.4%

최종수정일자
Date

Distinct174
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1999-10-13 00:00:00
Maximum2024-02-28 14:06:40
2024-04-30T04:40:38.016084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:38.132254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
I
196 
U
33 

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 196
85.6%
U 33
 
14.4%

Length

2024-04-30T04:40:38.255761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:38.333384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 196
85.6%
u 33
 
14.4%

데이터갱신일자
Date

Distinct42
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:01:00
2024-04-30T04:40:38.415399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:38.528617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
식품제조가공업
197 
기타 식품제조가공업
31 
<NA>
 
1

Length

Max length10
Median length7
Mean length7.3930131
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 197
86.0%
기타 식품제조가공업 31
 
13.5%
<NA> 1
 
0.4%

Length

2024-04-30T04:40:38.635752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:38.726577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 228
87.7%
기타 31
 
11.9%
na 1
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)85.2%
Missing6
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean203227.43
Minimum201081.92
Maximum204623.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:38.832025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201081.92
5-th percentile201945.69
Q1202993.45
median203307.1
Q3203647.95
95-th percentile204136.58
Maximum204623.02
Range3541.1036
Interquartile range (IQR)654.49724

Descriptive statistics

Standard deviation671.42169
Coefficient of variation (CV)0.0033037946
Kurtosis1.5441724
Mean203227.43
Median Absolute Deviation (MAD)321.74818
Skewness-1.0311782
Sum45319717
Variance450807.09
MonotonicityNot monotonic
2024-04-30T04:40:38.967721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204136.58447783 6
 
2.6%
202416.898467468 3
 
1.3%
201081.915285607 3
 
1.3%
203235.396325322 3
 
1.3%
203669.142410867 2
 
0.9%
202448.880217889 2
 
0.9%
203490.790188128 2
 
0.9%
203475.847626004 2
 
0.9%
201975.484196351 2
 
0.9%
203346.677922805 2
 
0.9%
Other values (180) 196
85.6%
(Missing) 6
 
2.6%
ValueCountFrequency (%)
201081.915285607 3
1.3%
201098.838622013 1
 
0.4%
201260.986030305 1
 
0.4%
201265.181994906 1
 
0.4%
201295.449760602 1
 
0.4%
201317.612596564 1
 
0.4%
201476.197702978 1
 
0.4%
201939.391046019 2
0.9%
201942.379109617 1
 
0.4%
201975.484196351 2
0.9%
ValueCountFrequency (%)
204623.018873403 1
 
0.4%
204428.262955437 1
 
0.4%
204258.587772043 1
 
0.4%
204222.46195029 1
 
0.4%
204214.210632572 1
 
0.4%
204177.919417522 1
 
0.4%
204172.527806715 1
 
0.4%
204169.847670316 2
 
0.9%
204169.765708943 1
 
0.4%
204136.58447783 6
2.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)85.2%
Missing6
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean461610.48
Minimum458968.63
Maximum465136.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:39.084601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum458968.63
5-th percentile459442.65
Q1460321.6
median461495.8
Q3462772.83
95-th percentile464120.58
Maximum465136.86
Range6168.2356
Interquartile range (IQR)2451.23

Descriptive statistics

Standard deviation1518.6855
Coefficient of variation (CV)0.0032899718
Kurtosis-0.89360633
Mean461610.48
Median Absolute Deviation (MAD)1214.6418
Skewness0.23502036
Sum1.0293914 × 108
Variance2306405.6
MonotonicityNot monotonic
2024-04-30T04:40:39.190626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463573.102150294 6
 
2.6%
462426.291677059 3
 
1.3%
461041.616228676 3
 
1.3%
459662.168255828 3
 
1.3%
461292.646459301 2
 
0.9%
462334.998539526 2
 
0.9%
459954.442916591 2
 
0.9%
461952.850754331 2
 
0.9%
460821.931092721 2
 
0.9%
460442.741638715 2
 
0.9%
Other values (180) 196
85.6%
(Missing) 6
 
2.6%
ValueCountFrequency (%)
458968.625259996 1
0.4%
459134.623667706 1
0.4%
459219.034904213 1
0.4%
459243.225833224 1
0.4%
459267.671057311 1
0.4%
459279.741770737 1
0.4%
459286.989226971 1
0.4%
459334.795917304 1
0.4%
459343.972359472 1
0.4%
459344.705834513 1
0.4%
ValueCountFrequency (%)
465136.8608906 1
0.4%
465025.246646886 1
0.4%
464945.629321349 1
0.4%
464907.336540817 1
0.4%
464814.717432497 2
0.9%
464751.482559612 1
0.4%
464674.288790614 2
0.9%
464203.913871704 1
0.4%
464134.681988189 2
0.9%
463993.614523962 1
0.4%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
식품제조가공업
192 
기타 식품제조가공업
26 
<NA>
 
11

Length

Max length10
Median length7
Mean length7.1965066
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 192
83.8%
기타 식품제조가공업 26
 
11.4%
<NA> 11
 
4.8%

Length

2024-04-30T04:40:39.318222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:39.421834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 218
85.5%
기타 26
 
10.2%
na 11
 
4.3%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
175 
0
35 
1
 
12
2
 
4
5
 
2

Length

Max length4
Median length4
Mean length3.2925764
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row5
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 175
76.4%
0 35
 
15.3%
1 12
 
5.2%
2 4
 
1.7%
5 2
 
0.9%
3 1
 
0.4%

Length

2024-04-30T04:40:39.527822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:39.636608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 175
76.4%
0 35
 
15.3%
1 12
 
5.2%
2 4
 
1.7%
5 2
 
0.9%
3 1
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
176 
0
37 
1
 
10
2
 
2
3
 
2

Length

Max length4
Median length4
Mean length3.3056769
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 176
76.9%
0 37
 
16.2%
1 10
 
4.4%
2 2
 
0.9%
3 2
 
0.9%
4 2
 
0.9%

Length

2024-04-30T04:40:39.748456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:39.844821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
76.9%
0 37
 
16.2%
1 10
 
4.4%
2 2
 
0.9%
3 2
 
0.9%
4 2
 
0.9%

영업장주변구분명
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
168 
주택가주변
31 
기타
25 
아파트지역
 
5

Length

Max length5
Median length4
Mean length3.9388646
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 168
73.4%
주택가주변 31
 
13.5%
기타 25
 
10.9%
아파트지역 5
 
2.2%

Length

2024-04-30T04:40:39.949125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:40.042778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 168
73.4%
주택가주변 31
 
13.5%
기타 25
 
10.9%
아파트지역 5
 
2.2%

등급구분명
Categorical

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
168 
자율
37 
기타
19 
지도
 
4
우수
 
1

Length

Max length4
Median length4
Mean length3.4672489
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 168
73.4%
자율 37
 
16.2%
기타 19
 
8.3%
지도 4
 
1.7%
우수 1
 
0.4%

Length

2024-04-30T04:40:40.140335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:40.232713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 168
73.4%
자율 37
 
16.2%
기타 19
 
8.3%
지도 4
 
1.7%
우수 1
 
0.4%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
116 
상수도전용
113 

Length

Max length5
Median length4
Mean length4.4934498
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 116
50.7%
상수도전용 113
49.3%

Length

2024-04-30T04:40:40.335730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:40.412506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 116
50.7%
상수도전용 113
49.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
222 
0
 
7

Length

Max length4
Median length4
Mean length3.9082969
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> 222
96.9%
0 7
 
3.1%

Length

2024-04-30T04:40:40.498160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:40.590328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
96.9%
0 7
 
3.1%

본사종업원수
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
165 
<NA>
63 
1
 
1

Length

Max length4
Median length1
Mean length1.8253275
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 165
72.1%
<NA> 63
 
27.5%
1 1
 
0.4%

Length

2024-04-30T04:40:40.693696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:40.778224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 165
72.1%
na 63
 
27.5%
1 1
 
0.4%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
160 
<NA>
61 
1
 
8

Length

Max length4
Median length1
Mean length1.7991266
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 160
69.9%
<NA> 61
 
26.6%
1 8
 
3.5%

Length

2024-04-30T04:40:40.873861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:40.971086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 160
69.9%
na 61
 
26.6%
1 8
 
3.5%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
162 
<NA>
63 
1
 
4

Length

Max length4
Median length1
Mean length1.8253275
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 162
70.7%
<NA> 63
 
27.5%
1 4
 
1.7%

Length

2024-04-30T04:40:41.076193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:41.155789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 162
70.7%
na 63
 
27.5%
1 4
 
1.7%

공장생산직종업원수
Categorical

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
150 
<NA>
59 
1
 
12
2
 
6
4
 
1

Length

Max length4
Median length1
Mean length1.7729258
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 150
65.5%
<NA> 59
 
25.8%
1 12
 
5.2%
2 6
 
2.6%
4 1
 
0.4%
3 1
 
0.4%

Length

2024-04-30T04:40:41.241592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:41.331367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
65.5%
na 59
 
25.8%
1 12
 
5.2%
2 6
 
2.6%
4 1
 
0.4%
3 1
 
0.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
121 
임대
82 
자가
26 

Length

Max length4
Median length4
Mean length3.0567686
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> 121
52.8%
임대 82
35.8%
자가 26
 
11.4%

Length

2024-04-30T04:40:41.431992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:41.553642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
52.8%
임대 82
35.8%
자가 26
 
11.4%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)14.3%
Missing180
Missing (%)78.6%
Infinite0
Infinite (%)0.0%
Mean6183673.5
Minimum0
Maximum1.7 × 108
Zeros36
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:41.628693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35000000
95-th percentile18000000
Maximum1.7 × 108
Range1.7 × 108
Interquartile range (IQR)5000000

Descriptive statistics

Standard deviation24480156
Coefficient of variation (CV)3.9588372
Kurtosis44.153097
Mean6183673.5
Median Absolute Deviation (MAD)0
Skewness6.505295
Sum3.03 × 108
Variance5.9927806 × 1014
MonotonicityNot monotonic
2024-04-30T04:40:41.718382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 36
 
15.7%
10000000 6
 
2.6%
5000000 2
 
0.9%
20000000 2
 
0.9%
15000000 1
 
0.4%
8000000 1
 
0.4%
170000000 1
 
0.4%
(Missing) 180
78.6%
ValueCountFrequency (%)
0 36
15.7%
5000000 2
 
0.9%
8000000 1
 
0.4%
10000000 6
 
2.6%
15000000 1
 
0.4%
20000000 2
 
0.9%
170000000 1
 
0.4%
ValueCountFrequency (%)
170000000 1
 
0.4%
20000000 2
 
0.9%
15000000 1
 
0.4%
10000000 6
 
2.6%
8000000 1
 
0.4%
5000000 2
 
0.9%
0 36
15.7%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)20.8%
Missing181
Missing (%)79.0%
Infinite0
Infinite (%)0.0%
Mean153208.33
Minimum0
Maximum1350000
Zeros36
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:41.825235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31000
95-th percentile912500
Maximum1350000
Range1350000
Interquartile range (IQR)1000

Descriptive statistics

Standard deviation324883.68
Coefficient of variation (CV)2.1205353
Kurtosis4.2016871
Mean153208.33
Median Absolute Deviation (MAD)0
Skewness2.2007501
Sum7354000
Variance1.055494 × 1011
MonotonicityNot monotonic
2024-04-30T04:40:41.933106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 36
 
15.7%
600000 2
 
0.9%
300000 2
 
0.9%
1000000 2
 
0.9%
250000 1
 
0.4%
1350000 1
 
0.4%
4000 1
 
0.4%
500000 1
 
0.4%
700000 1
 
0.4%
750000 1
 
0.4%
(Missing) 181
79.0%
ValueCountFrequency (%)
0 36
15.7%
4000 1
 
0.4%
250000 1
 
0.4%
300000 2
 
0.9%
500000 1
 
0.4%
600000 2
 
0.9%
700000 1
 
0.4%
750000 1
 
0.4%
1000000 2
 
0.9%
1350000 1
 
0.4%
ValueCountFrequency (%)
1350000 1
 
0.4%
1000000 2
 
0.9%
750000 1
 
0.4%
700000 1
 
0.4%
600000 2
 
0.9%
500000 1
 
0.4%
300000 2
 
0.9%
250000 1
 
0.4%
4000 1
 
0.4%
0 36
15.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing10
Missing (%)4.4%
Memory size590.0 B
False
219 
(Missing)
 
10
ValueCountFrequency (%)
False 219
95.6%
(Missing) 10
 
4.4%
2024-04-30T04:40:42.052963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)15.5%
Missing10
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean8.1218721
Minimum0
Maximum227
Zeros185
Zeros (%)80.8%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-30T04:40:42.163878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile51.4
Maximum227
Range227
Interquartile range (IQR)0

Descriptive statistics

Standard deviation28.473316
Coefficient of variation (CV)3.5057577
Kurtosis28.244182
Mean8.1218721
Median Absolute Deviation (MAD)0
Skewness4.9421826
Sum1778.69
Variance810.72972
MonotonicityNot monotonic
2024-04-30T04:40:42.265382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.0 185
80.8%
33.0 2
 
0.9%
196.35 1
 
0.4%
43.27 1
 
0.4%
22.49 1
 
0.4%
40.18 1
 
0.4%
1.0 1
 
0.4%
7.61 1
 
0.4%
29.34 1
 
0.4%
8.36 1
 
0.4%
Other values (24) 24
 
10.5%
(Missing) 10
 
4.4%
ValueCountFrequency (%)
0.0 185
80.8%
1.0 1
 
0.4%
2.0 1
 
0.4%
7.41 1
 
0.4%
7.61 1
 
0.4%
7.92 1
 
0.4%
8.0 1
 
0.4%
8.36 1
 
0.4%
10.45 1
 
0.4%
13.05 1
 
0.4%
ValueCountFrequency (%)
227.0 1
0.4%
196.35 1
0.4%
149.0 1
0.4%
114.87 1
0.4%
105.6 1
0.4%
98.44 1
0.4%
97.0 1
0.4%
74.0 1
0.4%
73.49 1
0.4%
66.0 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing229
Missing (%)100.0%
Memory size2.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030900003090000-106-1968-0038319680108<NA>3폐업2폐업20180710<NA><NA><NA>02 9927882174.24132920서울특별시 도봉구 창동 629-9번지서울특별시 도봉구 도봉로104길 69 (창동)1460삼성식품2018-08-07 15:01:02I2018-08-31 23:59:59.0식품제조가공업203093.401893460121.938675식품제조가공업52기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130900003090000-106-1976-000331976-08-31<NA>3폐업2폐업2023-04-10<NA><NA><NA>02 9547536100.74132-821서울특별시 도봉구 도봉동 626-117서울특별시 도봉구 도봉로164길 41 (도봉동)1322신영산업사2023-04-10 10:56:03U2022-12-03 23:02:00.0식품제조가공업204083.80991463671.401443<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230900003090000-106-1982-0000119820703<NA>3폐업2폐업19971203<NA><NA><NA>02 9921191<NA>132854서울특별시 도봉구 방학동 720번지<NA><NA>서울미원(주)2002-02-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업204086.050996462924.421741식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330900003090000-106-1984-0000119840710<NA>3폐업2폐업19970710<NA><NA><NA>9930312<NA>132919서울특별시 도봉구 창동 607-25번지<NA><NA>창성식품2002-02-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업203413.925329460108.877441식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430900003090000-106-1991-0000119910207<NA>3폐업2폐업19981119<NA><NA><NA>02 9561232<NA>132809서울특별시 도봉구 도봉동 470-6번지<NA><NA>승원실업(주)2002-02-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업203317.388234463993.614524식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530900003090000-106-1992-0000319920423<NA>3폐업2폐업20010409<NA><NA><NA>02 927405173.45132881서울특별시 도봉구 쌍문동 349-7번지<NA><NA>수정식품2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업202171.969377460681.323344식품제조가공업10주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630900003090000-106-1992-0027619920624<NA>3폐업2폐업20060407<NA><NA><NA>02 956957082.92132819서울특별시 도봉구 도봉동 601-52번지<NA><NA>두메식품2002-02-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업203828.686286463603.119828식품제조가공업13기타지도<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730900003090000-106-1993-0003419930513<NA>3폐업2폐업20131022<NA><NA><NA>02 9919523137.25132923서울특별시 도봉구 창동 650-58번지서울특별시 도봉구 도봉로 452 (창동)1459상현식품2012-12-13 10:37:58I2018-08-31 23:59:59.0식품제조가공업202885.638503460405.010846식품제조가공업11기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830900003090000-106-1993-0003519930220<NA>3폐업2폐업20001006<NA><NA><NA>02 9967136<NA>132923서울특별시 도봉구 창동 647-2번지<NA><NA>샘표식품주식회사2002-02-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930900003090000-106-1993-0003619931103<NA>3폐업2폐업19960122<NA><NA><NA>02 9939682<NA>132919서울특별시 도봉구 창동 608-167번지<NA><NA>성원식품2002-02-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업203449.08079460323.477909식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
21930900003090000-106-2019-0000120190110<NA>1영업/정상1영업<NA><NA><NA><NA>02 90533996.36132917서울특별시 도봉구 창동 557-97번지 2층서울특별시 도봉구 덕릉로 232, 2층 (창동)1473카페502&바리스타2019-09-25 14:00:30U2019-09-27 02:40:00.0기타 식품제조가공업203296.89955459562.721418기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
22030900003090000-106-2019-0000220190315<NA>3폐업2폐업20201209<NA><NA><NA><NA>22.88132898서울특별시 도봉구 창동 7 창동월가타워 201호서울특별시 도봉구 마들로11가길 6-25, 201호 (창동, 창동월가타워)1414백번가 코다리2020-12-09 10:57:44U2020-12-11 02:40:00.0기타 식품제조가공업204258.587772461096.296962기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
22130900003090000-106-2019-0000320190612<NA>3폐업2폐업20211201<NA><NA><NA><NA>59.28132959서울특별시 도봉구 창동 578-146 지하1층서울특별시 도봉구 덕릉로 235, 지하1층 (창동)1471해연식품2021-12-01 09:25:21U2021-12-03 02:40:00.0기타 식품제조가공업203293.185108459619.821804기타 식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
22230900003090000-106-2019-0000420190729<NA>1영업/정상1영업<NA><NA><NA><NA><NA>168.0132838서울특별시 도봉구 방학동 602-19번지 2층서울특별시 도봉구 시루봉로 227, 2층 (방학동)1314미리내푸드2020-02-25 13:28:01U2020-02-27 02:40:00.0기타 식품제조가공업203020.174244462923.320118기타 식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
22330900003090000-106-2020-0000120200206<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.76132919서울특별시 도봉구 창동 608-105번지 1층서울특별시 도봉구 도봉로108길 86, 1층 (창동)1457미라클바이오주식회사2020-02-06 17:34:04I2020-02-08 00:23:23.0기타 식품제조가공업203343.796504460367.535961기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
22430900003090000-106-2021-0000120210104<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.0132918서울특별시 도봉구 창동 581-20서울특별시 도봉구 덕릉로59다길 3, 1층 (창동)1470나이브커피2021-01-06 09:58:48I2021-01-08 00:23:04.0기타 식품제조가공업203307.095748459803.567058기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N8.0<NA><NA><NA>
22530900003090000-106-2021-0000220210719<NA>1영업/정상1영업<NA><NA><NA><NA><NA>134.96132020서울특별시 도봉구 방학동 447-1서울특별시 도봉구 방학로 214, 5층 (방학동)1359고루푸드 주식회사2021-07-19 09:46:24I2021-07-21 00:22:53.0기타 식품제조가공업202423.86745462191.974337기타 식품제조가공업00<NA><NA><NA>00000<NA>00N16.14<NA><NA><NA>
22630900003090000-106-2022-0000120220318<NA>1영업/정상1영업<NA><NA><NA><NA><NA>84.36132851서울특별시 도봉구 방학동 692-9서울특별시 도봉구 방학로 152, 2층 (방학동)1343스토리앤테이블2022-03-18 13:47:54I2022-03-20 00:22:35.0기타 식품제조가공업203043.467244462270.145923기타 식품제조가공업00<NA><NA><NA>00000<NA>00N39.36<NA><NA><NA>
22730900003090000-106-2022-0000220220712<NA>1영업/정상1영업<NA><NA><NA><NA><NA>82.5132885서울특별시 도봉구 쌍문동 423-17서울특별시 도봉구 삼양로 544, 1층 (쌍문동)1368카멜로테크 주식회사2022-07-12 13:51:37I2021-12-06 23:04:00.0기타 식품제조가공업201081.915286461041.616229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22830900003090000-106-2022-0000320220722<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.35132010서울특별시 도봉구 도봉동 657 도봉한양수자인서울특별시 도봉구 마들로 724, B07,B08호 (도봉동, 도봉한양수자인)1325이에스제이홀딩스 주식회사2022-07-22 11:10:22I2021-12-06 22:04:00.0기타 식품제조가공업204136.584478463573.10215<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>