Overview

Dataset statistics

Number of variables44
Number of observations280
Missing cells2456
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory102.9 KiB
Average record size in memory376.5 B

Variable types

Categorical20
Text6
DateTime4
Unsupported7
Numeric6
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18253/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (65.9%)Imbalance
여성종사자수 is highly imbalanced (68.1%)Imbalance
영업장주변구분명 is highly imbalanced (66.7%)Imbalance
등급구분명 is highly imbalanced (69.0%)Imbalance
본사종업원수 is highly imbalanced (70.5%)Imbalance
공장사무직종업원수 is highly imbalanced (68.0%)Imbalance
공장판매직종업원수 is highly imbalanced (69.5%)Imbalance
보증액 is highly imbalanced (64.9%)Imbalance
월세액 is highly imbalanced (64.9%)Imbalance
인허가취소일자 has 280 (100.0%) missing valuesMissing
폐업일자 has 37 (13.2%) missing valuesMissing
휴업시작일자 has 280 (100.0%) missing valuesMissing
휴업종료일자 has 280 (100.0%) missing valuesMissing
재개업일자 has 280 (100.0%) missing valuesMissing
전화번호 has 72 (25.7%) missing valuesMissing
소재지면적 has 22 (7.9%) missing valuesMissing
도로명주소 has 126 (45.0%) missing valuesMissing
도로명우편번호 has 126 (45.0%) missing valuesMissing
좌표정보(X) has 7 (2.5%) missing valuesMissing
좌표정보(Y) has 7 (2.5%) missing valuesMissing
공장생산직종업원수 has 33 (11.8%) missing valuesMissing
다중이용업소여부 has 33 (11.8%) missing valuesMissing
시설총규모 has 33 (11.8%) missing valuesMissing
전통업소지정번호 has 280 (100.0%) missing valuesMissing
전통업소주된음식 has 280 (100.0%) missing valuesMissing
홈페이지 has 280 (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
공장생산직종업원수 has 220 (78.6%) zerosZeros
시설총규모 has 223 (79.6%) zerosZeros

Reproduction

Analysis started2024-05-11 05:31:29.649885
Analysis finished2024-05-11 05:31:30.742193
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3010000
280 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 280
100.0%

Length

2024-05-11T14:31:30.830861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:30.956645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 280
100.0%

관리번호
Text

UNIQUE 

Distinct280
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T14:31:31.173854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6160
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

Unique280 ?
Unique (%)100.0%

Sample

1st row3010000-106-1972-00001
2nd row3010000-106-1974-00583
3rd row3010000-106-1981-00001
4th row3010000-106-1985-00001
5th row3010000-106-1989-00001
ValueCountFrequency (%)
3010000-106-1972-00001 1
 
0.4%
3010000-106-2011-00001 1
 
0.4%
3010000-106-2011-00007 1
 
0.4%
3010000-106-2011-00006 1
 
0.4%
3010000-106-2011-00005 1
 
0.4%
3010000-106-2011-00004 1
 
0.4%
3010000-106-2011-00003 1
 
0.4%
3010000-106-2012-00003 1
 
0.4%
3010000-106-2010-00013 1
 
0.4%
3010000-106-2011-00009 1
 
0.4%
Other values (270) 270
96.4%
2024-05-11T14:31:31.730854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3051
49.5%
- 840
 
13.6%
1 825
 
13.4%
2 365
 
5.9%
3 357
 
5.8%
6 348
 
5.6%
9 119
 
1.9%
4 76
 
1.2%
5 69
 
1.1%
7 61
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5320
86.4%
Dash Punctuation 840
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3051
57.3%
1 825
 
15.5%
2 365
 
6.9%
3 357
 
6.7%
6 348
 
6.5%
9 119
 
2.2%
4 76
 
1.4%
5 69
 
1.3%
7 61
 
1.1%
8 49
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3051
49.5%
- 840
 
13.6%
1 825
 
13.4%
2 365
 
5.9%
3 357
 
5.8%
6 348
 
5.6%
9 119
 
1.9%
4 76
 
1.2%
5 69
 
1.1%
7 61
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3051
49.5%
- 840
 
13.6%
1 825
 
13.4%
2 365
 
5.9%
3 357
 
5.8%
6 348
 
5.6%
9 119
 
1.9%
4 76
 
1.2%
5 69
 
1.1%
7 61
 
1.0%

인허가일자
Date

Distinct255
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1972-09-11 00:00:00
Maximum2024-01-15 00:00:00
2024-05-11T14:31:31.970416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:32.212165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3
243 
1
37 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 243
86.8%
1 37
 
13.2%

Length

2024-05-11T14:31:32.414895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:32.602741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 243
86.8%
1 37
 
13.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
243 
영업/정상
37 

Length

Max length5
Median length2
Mean length2.3964286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 243
86.8%
영업/정상 37
 
13.2%

Length

2024-05-11T14:31:32.779747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:32.960068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 243
86.8%
영업/정상 37
 
13.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2
243 
1
37 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 243
86.8%
1 37
 
13.2%

Length

2024-05-11T14:31:33.119575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:33.307048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 243
86.8%
1 37
 
13.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
243 
영업
37 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 243
86.8%
영업 37
 
13.2%

Length

2024-05-11T14:31:33.506499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:33.707939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 243
86.8%
영업 37
 
13.2%

폐업일자
Date

MISSING 

Distinct225
Distinct (%)92.6%
Missing37
Missing (%)13.2%
Memory size2.3 KiB
Minimum1998-04-17 00:00:00
Maximum2024-03-22 00:00:00
2024-05-11T14:31:33.909540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:34.138701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

전화번호
Text

MISSING 

Distinct194
Distinct (%)93.3%
Missing72
Missing (%)25.7%
Memory size2.3 KiB
2024-05-11T14:31:34.573313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9567308
Min length2

Characters and Unicode

Total characters2071
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

Unique188 ?
Unique (%)90.4%

Sample

1st row0222346700
2nd row0202342011
3rd row02 7711000
4th row0222792210
5th row02 3126055
ValueCountFrequency (%)
02 71
 
24.8%
07077108592 2
 
0.7%
0222355119 2
 
0.7%
0222655708 2
 
0.7%
7711000 2
 
0.7%
0222523514 2
 
0.7%
02755 2
 
0.7%
8161 1
 
0.3%
7491002 1
 
0.3%
32888108 1
 
0.3%
Other values (200) 200
69.9%
2024-05-11T14:31:35.214387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 599
28.9%
0 361
17.4%
3 206
 
9.9%
7 156
 
7.5%
5 127
 
6.1%
1 114
 
5.5%
6 109
 
5.3%
8 106
 
5.1%
106
 
5.1%
4 101
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1965
94.9%
Space Separator 106
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 599
30.5%
0 361
18.4%
3 206
 
10.5%
7 156
 
7.9%
5 127
 
6.5%
1 114
 
5.8%
6 109
 
5.5%
8 106
 
5.4%
4 101
 
5.1%
9 86
 
4.4%
Space Separator
ValueCountFrequency (%)
106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2071
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 599
28.9%
0 361
17.4%
3 206
 
9.9%
7 156
 
7.5%
5 127
 
6.1%
1 114
 
5.5%
6 109
 
5.3%
8 106
 
5.1%
106
 
5.1%
4 101
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2071
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 599
28.9%
0 361
17.4%
3 206
 
9.9%
7 156
 
7.5%
5 127
 
6.1%
1 114
 
5.5%
6 109
 
5.3%
8 106
 
5.1%
106
 
5.1%
4 101
 
4.9%

소재지면적
Real number (ℝ)

MISSING 

Distinct221
Distinct (%)85.7%
Missing22
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean52.809496
Minimum0
Maximum399.7
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:31:35.489892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.085
Q120.3625
median40
Q366
95-th percentile141.9375
Maximum399.7
Range399.7
Interquartile range (IQR)45.6375

Descriptive statistics

Standard deviation46.521763
Coefficient of variation (CV)0.88093556
Kurtosis13.680245
Mean52.809496
Median Absolute Deviation (MAD)21
Skewness2.7844447
Sum13624.85
Variance2164.2744
MonotonicityNot monotonic
2024-05-11T14:31:35.770319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 5
 
1.8%
30.0 4
 
1.4%
20.0 4
 
1.4%
15.0 3
 
1.1%
39.0 3
 
1.1%
46.2 3
 
1.1%
45.0 3
 
1.1%
49.5 3
 
1.1%
66.0 3
 
1.1%
16.0 3
 
1.1%
Other values (211) 224
80.0%
(Missing) 22
 
7.9%
ValueCountFrequency (%)
0.0 1
0.4%
4.84 1
0.4%
5.76 1
0.4%
6.46 1
0.4%
6.6 1
0.4%
6.95 1
0.4%
8.0 2
0.7%
9.5 1
0.4%
10.0 2
0.7%
10.8 1
0.4%
ValueCountFrequency (%)
399.7 1
0.4%
275.17 1
0.4%
226.2 1
0.4%
180.0 1
0.4%
171.7 1
0.4%
158.44 1
0.4%
154.57 1
0.4%
148.92 1
0.4%
148.88 1
0.4%
145.5 1
0.4%

소재지우편번호
Text

Distinct93
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T14:31:36.241737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.075
Min length6

Characters and Unicode

Total characters1701
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

Unique48 ?
Unique (%)17.1%

Sample

1st row100834
2nd row100869
3rd row100070
4th row100400
5th row100858
ValueCountFrequency (%)
100869 65
23.2%
100819 14
 
5.0%
100310 13
 
4.6%
100070 10
 
3.6%
100870 8
 
2.9%
100868 8
 
2.9%
100833 6
 
2.1%
100834 5
 
1.8%
100810 5
 
1.8%
100042 5
 
1.8%
Other values (83) 141
50.4%
2024-05-11T14:31:36.909241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 673
39.6%
1 363
21.3%
8 204
 
12.0%
9 105
 
6.2%
6 87
 
5.1%
3 69
 
4.1%
2 54
 
3.2%
4 46
 
2.7%
7 45
 
2.6%
5 34
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1680
98.8%
Dash Punctuation 21
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 673
40.1%
1 363
21.6%
8 204
 
12.1%
9 105
 
6.2%
6 87
 
5.2%
3 69
 
4.1%
2 54
 
3.2%
4 46
 
2.7%
7 45
 
2.7%
5 34
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1701
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 673
39.6%
1 363
21.3%
8 204
 
12.0%
9 105
 
6.2%
6 87
 
5.1%
3 69
 
4.1%
2 54
 
3.2%
4 46
 
2.7%
7 45
 
2.6%
5 34
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1701
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 673
39.6%
1 363
21.3%
8 204
 
12.0%
9 105
 
6.2%
6 87
 
5.1%
3 69
 
4.1%
2 54
 
3.2%
4 46
 
2.7%
7 45
 
2.6%
5 34
 
2.0%

지번주소
Text

Distinct264
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T14:31:37.469552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length39
Mean length23.296429
Min length16

Characters and Unicode

Total characters6523
Distinct characters184
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)89.6%

Sample

1st row서울특별시 중구 신당동 378-9번지
2nd row서울특별시 중구 황학동 415-0번지
3rd row서울특별시 중구 소공동 1번지 (주)호텔롯데
4th row서울특별시 중구 쌍림동 182번지
5th row서울특별시 중구 중림동 149-6번지
ValueCountFrequency (%)
서울특별시 280
21.3%
중구 280
21.3%
황학동 85
 
6.5%
신당동 56
 
4.3%
1층 43
 
3.3%
2층 18
 
1.4%
오장동 17
 
1.3%
지하1층 16
 
1.2%
소공동 11
 
0.8%
명동2가 8
 
0.6%
Other values (398) 498
38.0%
2024-05-11T14:31:38.418663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1270
19.5%
1 304
 
4.7%
중 287
 
4.4%
시 283
 
4.3%
서 281
 
4.3%
구 281
 
4.3%
울 281
 
4.3%
특 280
 
4.3%
별 280
 
4.3%
지 274
 
4.2%
Other values (174) 2702
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3771
57.8%
Space Separator 1270
 
19.5%
Decimal Number 1252
 
19.2%
Dash Punctuation 168
 
2.6%
Uppercase Letter 22
 
0.3%
Lowercase Letter 17
 
0.3%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%
Other Punctuation 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 287
 
7.6%
시 283
 
7.5%
서 281
 
7.5%
구 281
 
7.5%
울 281
 
7.5%
특 280
 
7.4%
별 280
 
7.4%
지 274
 
7.3%
동 264
 
7.0%
번 233
 
6.2%
Other values (134) 1027
27.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
18.2%
F 3
13.6%
R 3
13.6%
E 2
9.1%
C 1
 
4.5%
D 1
 
4.5%
G 1
 
4.5%
I 1
 
4.5%
L 1
 
4.5%
W 1
 
4.5%
Other values (4) 4
18.2%
Decimal Number
ValueCountFrequency (%)
1 304
24.3%
2 197
15.7%
3 148
11.8%
4 130
10.4%
0 105
 
8.4%
5 103
 
8.2%
6 80
 
6.4%
7 80
 
6.4%
9 53
 
4.2%
8 52
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
n 4
23.5%
e 3
17.6%
i 3
17.6%
a 2
11.8%
c 1
 
5.9%
h 1
 
5.9%
s 1
 
5.9%
r 1
 
5.9%
t 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1270
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3771
57.8%
Common 2713
41.6%
Latin 39
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 287
 
7.6%
시 283
 
7.5%
서 281
 
7.5%
구 281
 
7.5%
울 281
 
7.5%
특 280
 
7.4%
별 280
 
7.4%
지 274
 
7.3%
동 264
 
7.0%
번 233
 
6.2%
Other values (134) 1027
27.2%
Latin
ValueCountFrequency (%)
B 4
 
10.3%
n 4
 
10.3%
F 3
 
7.7%
e 3
 
7.7%
R 3
 
7.7%
i 3
 
7.7%
a 2
 
5.1%
E 2
 
5.1%
C 1
 
2.6%
c 1
 
2.6%
Other values (13) 13
33.3%
Common
ValueCountFrequency (%)
1270
46.8%
1 304
 
11.2%
2 197
 
7.3%
- 168
 
6.2%
3 148
 
5.5%
4 130
 
4.8%
0 105
 
3.9%
5 103
 
3.8%
6 80
 
2.9%
7 80
 
2.9%
Other values (7) 128
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3771
57.8%
ASCII 2752
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1270
46.1%
1 304
 
11.0%
2 197
 
7.2%
- 168
 
6.1%
3 148
 
5.4%
4 130
 
4.7%
0 105
 
3.8%
5 103
 
3.7%
6 80
 
2.9%
7 80
 
2.9%
Other values (30) 167
 
6.1%
Hangul
ValueCountFrequency (%)
중 287
 
7.6%
시 283
 
7.5%
서 281
 
7.5%
구 281
 
7.5%
울 281
 
7.5%
특 280
 
7.4%
별 280
 
7.4%
지 274
 
7.3%
동 264
 
7.0%
번 233
 
6.2%
Other values (134) 1027
27.2%

도로명주소
Text

MISSING 

Distinct151
Distinct (%)98.1%
Missing126
Missing (%)45.0%
Memory size2.3 KiB
2024-05-11T14:31:39.269540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46
Mean length30.603896
Min length23

Characters and Unicode

Total characters4713
Distinct characters176
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)96.1%

Sample

1st row서울특별시 중구 다산로19길 8 (신당동)
2nd row서울특별시 중구 을지로 30 (소공동, (주)호텔롯데)
3rd row서울특별시 중구 퇴계로87길 39-3 (황학동)
4th row서울특별시 중구 을지로32길 35-26 (오장동)
5th row서울특별시 중구 퇴계로87길 15-24, 1층 (황학동)
ValueCountFrequency (%)
서울특별시 154
 
16.6%
중구 154
 
16.6%
1층 53
 
5.7%
황학동 48
 
5.2%
퇴계로87길 40
 
4.3%
신당동 21
 
2.3%
2층 12
 
1.3%
오장동 11
 
1.2%
을지로32길 11
 
1.2%
지하1층 10
 
1.1%
Other values (318) 413
44.6%
2024-05-11T14:31:40.227808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
773
 
16.4%
1 222
 
4.7%
동 175
 
3.7%
로 159
 
3.4%
) 159
 
3.4%
( 159
 
3.4%
중 158
 
3.4%
구 158
 
3.4%
시 157
 
3.3%
서 156
 
3.3%
Other values (166) 2437
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2511
53.3%
Decimal Number 868
 
18.4%
Space Separator 773
 
16.4%
Close Punctuation 159
 
3.4%
Open Punctuation 159
 
3.4%
Other Punctuation 130
 
2.8%
Dash Punctuation 76
 
1.6%
Uppercase Letter 19
 
0.4%
Lowercase Letter 17
 
0.4%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 175
 
7.0%
로 159
 
6.3%
중 158
 
6.3%
구 158
 
6.3%
시 157
 
6.3%
서 156
 
6.2%
별 155
 
6.2%
울 155
 
6.2%
특 154
 
6.1%
길 115
 
4.6%
Other values (127) 969
38.6%
Uppercase Letter
ValueCountFrequency (%)
R 3
15.8%
E 2
10.5%
F 2
10.5%
B 2
10.5%
D 1
 
5.3%
C 1
 
5.3%
W 1
 
5.3%
G 1
 
5.3%
I 1
 
5.3%
L 1
 
5.3%
Other values (4) 4
21.1%
Decimal Number
ValueCountFrequency (%)
1 222
25.6%
2 139
16.0%
3 113
13.0%
8 81
 
9.3%
7 66
 
7.6%
4 60
 
6.9%
5 57
 
6.6%
0 50
 
5.8%
9 44
 
5.1%
6 36
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
n 4
23.5%
i 3
17.6%
e 3
17.6%
a 2
11.8%
s 1
 
5.9%
h 1
 
5.9%
r 1
 
5.9%
t 1
 
5.9%
c 1
 
5.9%
Space Separator
ValueCountFrequency (%)
773
100.0%
Close Punctuation
ValueCountFrequency (%)
) 159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 159
100.0%
Other Punctuation
ValueCountFrequency (%)
, 130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2511
53.3%
Common 2166
46.0%
Latin 36
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 175
 
7.0%
로 159
 
6.3%
중 158
 
6.3%
구 158
 
6.3%
시 157
 
6.3%
서 156
 
6.2%
별 155
 
6.2%
울 155
 
6.2%
특 154
 
6.1%
길 115
 
4.6%
Other values (127) 969
38.6%
Latin
ValueCountFrequency (%)
n 4
 
11.1%
i 3
 
8.3%
e 3
 
8.3%
R 3
 
8.3%
E 2
 
5.6%
F 2
 
5.6%
B 2
 
5.6%
a 2
 
5.6%
D 1
 
2.8%
s 1
 
2.8%
Other values (13) 13
36.1%
Common
ValueCountFrequency (%)
773
35.7%
1 222
 
10.2%
) 159
 
7.3%
( 159
 
7.3%
2 139
 
6.4%
, 130
 
6.0%
3 113
 
5.2%
8 81
 
3.7%
- 76
 
3.5%
7 66
 
3.0%
Other values (6) 248
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2511
53.3%
ASCII 2202
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
773
35.1%
1 222
 
10.1%
) 159
 
7.2%
( 159
 
7.2%
2 139
 
6.3%
, 130
 
5.9%
3 113
 
5.1%
8 81
 
3.7%
- 76
 
3.5%
7 66
 
3.0%
Other values (29) 284
 
12.9%
Hangul
ValueCountFrequency (%)
동 175
 
7.0%
로 159
 
6.3%
중 158
 
6.3%
구 158
 
6.3%
시 157
 
6.3%
서 156
 
6.2%
별 155
 
6.2%
울 155
 
6.2%
특 154
 
6.1%
길 115
 
4.6%
Other values (127) 969
38.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)39.6%
Missing126
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean4573.0649
Minimum4501
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:31:40.500611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4501
5-th percentile4526.25
Q14547
median4576
Q34590
95-th percentile4626
Maximum4637
Range136
Interquartile range (IQR)43

Descriptive statistics

Standard deviation30.112138
Coefficient of variation (CV)0.0065846732
Kurtosis-0.34804009
Mean4573.0649
Median Absolute Deviation (MAD)23
Skewness0.036110489
Sum704252
Variance906.74085
MonotonicityNot monotonic
2024-05-11T14:31:40.846948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4576 46
 
16.4%
4547 16
 
5.7%
4575 4
 
1.4%
4626 4
 
1.4%
4533 3
 
1.1%
4549 3
 
1.1%
4570 3
 
1.1%
4594 2
 
0.7%
4598 2
 
0.7%
4618 2
 
0.7%
Other values (51) 69
24.6%
(Missing) 126
45.0%
ValueCountFrequency (%)
4501 1
 
0.4%
4502 1
 
0.4%
4508 2
0.7%
4518 1
 
0.4%
4519 2
0.7%
4523 1
 
0.4%
4528 1
 
0.4%
4532 1
 
0.4%
4533 3
1.1%
4534 1
 
0.4%
ValueCountFrequency (%)
4637 1
 
0.4%
4633 1
 
0.4%
4631 2
0.7%
4630 1
 
0.4%
4629 2
0.7%
4626 4
1.4%
4624 1
 
0.4%
4622 1
 
0.4%
4618 2
0.7%
4617 1
 
0.4%

사업장명
Text

Distinct264
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T14:31:41.273718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length6.3285714
Min length1

Characters and Unicode

Total characters1772
Distinct characters357
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

Unique251 ?
Unique (%)89.6%

Sample

1st row영림식품
2nd row현대식품
3rd row(주)호텔롯데
4th row(주)거보비앤에프
5th row순창식품
ValueCountFrequency (%)
주식회사 5
 
1.5%
주)조선호텔 3
 
0.9%
왕십리복떡 3
 
0.9%
대성농산 3
 
0.9%
주)호텔롯데 2
 
0.6%
주)핫시즈너 2
 
0.6%
커피 2
 
0.6%
보그너 2
 
0.6%
카페골든컵 2
 
0.6%
서울농산 2
 
0.6%
Other values (296) 304
92.1%
2024-05-11T14:31:42.019974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 68
 
3.8%
) 68
 
3.8%
주 67
 
3.8%
식 54
 
3.0%
50
 
2.8%
품 47
 
2.7%
이 46
 
2.6%
회 39
 
2.2%
상 36
 
2.0%
스 28
 
1.6%
Other values (347) 1269
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1457
82.2%
Open Punctuation 68
 
3.8%
Close Punctuation 68
 
3.8%
Lowercase Letter 61
 
3.4%
Uppercase Letter 60
 
3.4%
Space Separator 50
 
2.8%
Other Punctuation 6
 
0.3%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 67
 
4.6%
식 54
 
3.7%
품 47
 
3.2%
이 46
 
3.2%
회 39
 
2.7%
상 36
 
2.5%
스 28
 
1.9%
리 25
 
1.7%
커 21
 
1.4%
피 20
 
1.4%
Other values (301) 1074
73.7%
Uppercase Letter
ValueCountFrequency (%)
A 8
13.3%
C 5
 
8.3%
R 5
 
8.3%
T 5
 
8.3%
B 5
 
8.3%
O 4
 
6.7%
S 4
 
6.7%
L 4
 
6.7%
E 3
 
5.0%
K 3
 
5.0%
Other values (10) 14
23.3%
Lowercase Letter
ValueCountFrequency (%)
e 14
23.0%
o 8
13.1%
f 4
 
6.6%
r 4
 
6.6%
a 4
 
6.6%
y 3
 
4.9%
k 3
 
4.9%
t 3
 
4.9%
i 3
 
4.9%
m 2
 
3.3%
Other values (8) 13
21.3%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
& 2
33.3%
? 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1457
82.2%
Common 194
 
10.9%
Latin 121
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 67
 
4.6%
식 54
 
3.7%
품 47
 
3.2%
이 46
 
3.2%
회 39
 
2.7%
상 36
 
2.5%
스 28
 
1.9%
리 25
 
1.7%
커 21
 
1.4%
피 20
 
1.4%
Other values (301) 1074
73.7%
Latin
ValueCountFrequency (%)
e 14
 
11.6%
o 8
 
6.6%
A 8
 
6.6%
C 5
 
4.1%
R 5
 
4.1%
T 5
 
4.1%
B 5
 
4.1%
O 4
 
3.3%
S 4
 
3.3%
L 4
 
3.3%
Other values (28) 59
48.8%
Common
ValueCountFrequency (%)
( 68
35.1%
) 68
35.1%
50
25.8%
. 3
 
1.5%
& 2
 
1.0%
3 1
 
0.5%
? 1
 
0.5%
2 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1457
82.2%
ASCII 315
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 68
21.6%
) 68
21.6%
50
15.9%
e 14
 
4.4%
o 8
 
2.5%
A 8
 
2.5%
C 5
 
1.6%
R 5
 
1.6%
T 5
 
1.6%
B 5
 
1.6%
Other values (36) 79
25.1%
Hangul
ValueCountFrequency (%)
주 67
 
4.6%
식 54
 
3.7%
품 47
 
3.2%
이 46
 
3.2%
회 39
 
2.7%
상 36
 
2.5%
스 28
 
1.9%
리 25
 
1.7%
커 21
 
1.4%
피 20
 
1.4%
Other values (301) 1074
73.7%

최종수정일자
Date

Distinct263
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1999-05-27 00:00:00
Maximum2024-04-23 13:48:16
2024-05-11T14:31:42.299038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:42.636548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
I
220 
U
60 

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 220
78.6%
U 60
 
21.4%

Length

2024-05-11T14:31:42.929612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:43.130712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 220
78.6%
u 60
 
21.4%

데이터갱신일자
Date

Distinct64
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:05:00
2024-05-11T14:31:43.287726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:43.506818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
식품제조가공업
232 
기타 식품제조가공업
48 

Length

Max length10
Median length7
Mean length7.5142857
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 232
82.9%
기타 식품제조가공업 48
 
17.1%

Length

2024-05-11T14:31:43.748510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:43.932330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 280
85.4%
기타 48
 
14.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct234
Distinct (%)85.7%
Missing7
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean200385.28
Minimum196722.52
Maximum202049.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:31:44.138873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196722.52
5-th percentile197734.54
Q1199412.18
median200896.02
Q3201703.92
95-th percentile201777.74
Maximum202049.07
Range5326.5516
Interquartile range (IQR)2291.7414

Descriptive statistics

Standard deviation1436.6293
Coefficient of variation (CV)0.0071693357
Kurtosis-0.56691326
Mean200385.28
Median Absolute Deviation (MAD)842.27233
Skewness-0.78198655
Sum54705181
Variance2063903.8
MonotonicityNot monotonic
2024-05-11T14:31:44.421897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198259.65357739 6
 
2.1%
197867.156641113 3
 
1.1%
199412.181912212 3
 
1.1%
200015.499568016 3
 
1.1%
201723.583784138 3
 
1.1%
201735.746519349 3
 
1.1%
201853.827140376 3
 
1.1%
201738.292515221 2
 
0.7%
201469.901425071 2
 
0.7%
201736.062984851 2
 
0.7%
Other values (224) 243
86.8%
(Missing) 7
 
2.5%
ValueCountFrequency (%)
196722.521964636 1
0.4%
196864.942838297 2
0.7%
196925.261778408 1
0.4%
197010.426880715 1
0.4%
197037.368787577 1
0.4%
197082.023108025 1
0.4%
197091.014515178 1
0.4%
197144.128731285 1
0.4%
197229.4768656 1
0.4%
197249.357745588 1
0.4%
ValueCountFrequency (%)
202049.073601681 1
 
0.4%
201952.615367725 1
 
0.4%
201900.024233571 1
 
0.4%
201882.940610742 1
 
0.4%
201866.039519433 1
 
0.4%
201853.827140376 3
1.1%
201852.228128772 1
 
0.4%
201823.908977364 1
 
0.4%
201800.5220472 1
 
0.4%
201798.360095636 1
 
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct234
Distinct (%)85.7%
Missing7
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean451249.22
Minimum449638.82
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:31:44.669561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449638.82
5-th percentile450254.15
Q1450951.94
median451397.03
Q3451627.48
95-th percentile451733.22
Maximum452076.82
Range2437.9944
Interquartile range (IQR)675.54111

Descriptive statistics

Standard deviation482.90603
Coefficient of variation (CV)0.0010701537
Kurtosis0.22793403
Mean451249.22
Median Absolute Deviation (MAD)256.19883
Skewness-1.0434726
Sum1.2319104 × 108
Variance233198.23
MonotonicityNot monotonic
2024-05-11T14:31:44.875137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451392.198218657 6
 
2.1%
451779.880897566 3
 
1.1%
451480.730279886 3
 
1.1%
451485.349952584 3
 
1.1%
451626.421164189 3
 
1.1%
451707.033484276 3
 
1.1%
451639.554040469 3
 
1.1%
451602.445360303 2
 
0.7%
451561.745940866 2
 
0.7%
451679.503191228 2
 
0.7%
Other values (224) 243
86.8%
(Missing) 7
 
2.5%
ValueCountFrequency (%)
449638.824308081 1
0.4%
449809.744684888 1
0.4%
449969.146324508 1
0.4%
450038.888747528 1
0.4%
450072.485315804 1
0.4%
450086.538701135 1
0.4%
450099.447208811 1
0.4%
450118.110225733 2
0.7%
450138.549769796 1
0.4%
450147.376945098 1
0.4%
ValueCountFrequency (%)
452076.818664092 1
 
0.4%
451880.853920662 1
 
0.4%
451836.458256618 1
 
0.4%
451812.090141168 1
 
0.4%
451779.880897566 3
1.1%
451771.29832459 2
0.7%
451744.306626505 1
 
0.4%
451743.191549823 2
0.7%
451735.372101829 1
 
0.4%
451735.100108064 1
 
0.4%

위생업태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
식품제조가공업
221 
<NA>
33 
기타 식품제조가공업
26 

Length

Max length10
Median length7
Mean length6.925
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 221
78.9%
<NA> 33
 
11.8%
기타 식품제조가공업 26
 
9.3%

Length

2024-05-11T14:31:45.090453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:45.283535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 247
80.7%
na 33
 
10.8%
기타 26
 
8.5%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
233 
<NA>
33 
1
 
8
2
 
3
8
 
2

Length

Max length4
Median length1
Mean length1.3571429
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row2
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 233
83.2%
<NA> 33
 
11.8%
1 8
 
2.9%
2 3
 
1.1%
8 2
 
0.7%
12 1
 
0.4%

Length

2024-05-11T14:31:45.534878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:45.748430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 233
83.2%
na 33
 
11.8%
1 8
 
2.9%
2 3
 
1.1%
8 2
 
0.7%
12 1
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
236 
<NA>
33 
1
 
5
4
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.3535714
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 236
84.3%
<NA> 33
 
11.8%
1 5
 
1.8%
4 3
 
1.1%
3 2
 
0.7%
2 1
 
0.4%

Length

2024-05-11T14:31:45.946292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:46.130249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 236
84.3%
na 33
 
11.8%
1 5
 
1.8%
4 3
 
1.1%
3 2
 
0.7%
2 1
 
0.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
239 
기타
38 
주택가주변
 
2
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.75
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 239
85.4%
기타 38
 
13.6%
주택가주변 2
 
0.7%
유흥업소밀집지역 1
 
0.4%

Length

2024-05-11T14:31:46.371487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:46.596716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
85.4%
기타 38
 
13.6%
주택가주변 2
 
0.7%
유흥업소밀집지역 1
 
0.4%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
239 
기타
35 
자율
 
3
갑
 
2
을
 
1

Length

Max length4
Median length4
Mean length3.6964286
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 239
85.4%
기타 35
 
12.5%
자율 3
 
1.1%
갑 2
 
0.7%
을 1
 
0.4%

Length

2024-05-11T14:31:46.830595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:47.004592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
85.4%
기타 35
 
12.5%
자율 3
 
1.1%
갑 2
 
0.7%
을 1
 
0.4%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
177 
상수도전용
103 

Length

Max length5
Median length4
Mean length4.3678571
Min length4

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> 177
63.2%
상수도전용 103
36.8%

Length

2024-05-11T14:31:47.191125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:47.369939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
63.2%
상수도전용 103
36.8%

총인원
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
247 
<NA>
33 

Length

Max length4
Median length1
Mean length1.3535714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 247
88.2%
<NA> 33
 
11.8%

Length

2024-05-11T14:31:47.605757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:47.780702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 247
88.2%
na 33
 
11.8%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
245 
<NA>
33 
4
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.3535714
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 245
87.5%
<NA> 33
 
11.8%
4 1
 
0.4%
2 1
 
0.4%

Length

2024-05-11T14:31:48.072556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:48.256859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 245
87.5%
na 33
 
11.8%
4 1
 
0.4%
2 1
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
243 
<NA>
33 
1
 
3
2
 
1

Length

Max length4
Median length1
Mean length1.3535714
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 243
86.8%
<NA> 33
 
11.8%
1 3
 
1.1%
2 1
 
0.4%

Length

2024-05-11T14:31:48.471564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:48.662668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 243
86.8%
na 33
 
11.8%
1 3
 
1.1%
2 1
 
0.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
237 
<NA>
33 
1
 
7
5
 
1
4
 
1

Length

Max length4
Median length1
Mean length1.3535714
Min length1

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 237
84.6%
<NA> 33
 
11.8%
1 7
 
2.5%
5 1
 
0.4%
4 1
 
0.4%
3 1
 
0.4%

Length

2024-05-11T14:31:48.866015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:49.085182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 237
84.6%
na 33
 
11.8%
1 7
 
2.5%
5 1
 
0.4%
4 1
 
0.4%
3 1
 
0.4%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.8%
Missing33
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean0.2388664
Minimum0
Maximum10
Zeros220
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:31:49.239232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9346685
Coefficient of variation (CV)3.9129342
Kurtosis54.294895
Mean0.2388664
Median Absolute Deviation (MAD)0
Skewness6.4627081
Sum59
Variance0.87360521
MonotonicityNot monotonic
2024-05-11T14:31:49.423489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 220
78.6%
1 13
 
4.6%
2 8
 
2.9%
5 2
 
0.7%
3 2
 
0.7%
10 1
 
0.4%
4 1
 
0.4%
(Missing) 33
 
11.8%
ValueCountFrequency (%)
0 220
78.6%
1 13
 
4.6%
2 8
 
2.9%
3 2
 
0.7%
4 1
 
0.4%
5 2
 
0.7%
10 1
 
0.4%
ValueCountFrequency (%)
10 1
 
0.4%
5 2
 
0.7%
4 1
 
0.4%
3 2
 
0.7%
2 8
 
2.9%
1 13
 
4.6%
0 220
78.6%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
147 
임대
88 
자가
45 

Length

Max length4
Median length4
Mean length3.05
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> 147
52.5%
임대 88
31.4%
자가 45
 
16.1%

Length

2024-05-11T14:31:49.658606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:49.935614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
52.5%
임대 88
31.4%
자가 45
 
16.1%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
246 
<NA>
33 
30000000
 
1

Length

Max length8
Median length1
Mean length1.3785714
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 246
87.9%
<NA> 33
 
11.8%
30000000 1
 
0.4%

Length

2024-05-11T14:31:50.168605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:50.364483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 246
87.9%
na 33
 
11.8%
30000000 1
 
0.4%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
246 
<NA>
33 
150
 
1

Length

Max length4
Median length1
Mean length1.3607143
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 246
87.9%
<NA> 33
 
11.8%
150 1
 
0.4%

Length

2024-05-11T14:31:50.551532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:50.767039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 246
87.9%
na 33
 
11.8%
150 1
 
0.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing33
Missing (%)11.8%
Memory size692.0 B
False
247 
(Missing)
33 
ValueCountFrequency (%)
False 247
88.2%
(Missing) 33
 
11.8%
2024-05-11T14:31:50.907560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)9.7%
Missing33
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean3.5558704
Minimum0
Maximum158.44
Zeros223
Zeros (%)79.6%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:31:51.067382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile21.545
Maximum158.44
Range158.44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17.486469
Coefficient of variation (CV)4.9176338
Kurtosis51.660666
Mean3.5558704
Median Absolute Deviation (MAD)0
Skewness6.8760264
Sum878.3
Variance305.77659
MonotonicityNot monotonic
2024-05-11T14:31:51.736167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 223
79.6%
2.5 2
 
0.7%
158.44 1
 
0.4%
22.14 1
 
0.4%
21.23 1
 
0.4%
30.38 1
 
0.4%
20.26 1
 
0.4%
26.0 1
 
0.4%
40.0 1
 
0.4%
6.95 1
 
0.4%
Other values (14) 14
 
5.0%
(Missing) 33
 
11.8%
ValueCountFrequency (%)
0.0 223
79.6%
2.5 2
 
0.7%
3.06 1
 
0.4%
3.25 1
 
0.4%
5.76 1
 
0.4%
6.95 1
 
0.4%
7.65 1
 
0.4%
8.68 1
 
0.4%
9.15 1
 
0.4%
20.26 1
 
0.4%
ValueCountFrequency (%)
158.44 1
0.4%
141.75 1
0.4%
130.0 1
0.4%
70.0 1
0.4%
55.92 1
0.4%
40.0 1
0.4%
36.0 1
0.4%
33.0 1
0.4%
30.38 1
0.4%
26.0 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing280
Missing (%)100.0%
Memory size2.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-106-1972-0000119720911<NA>1영업/정상1영업<NA><NA><NA><NA>022234670091.5100834서울특별시 중구 신당동 378-9번지서울특별시 중구 다산로19길 8 (신당동)4607영림식품2018-05-15 17:58:33I2018-08-31 23:59:59.0식품제조가공업200944.421918450575.31865식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
130100003010000-106-1974-0058319741023<NA>3폐업2폐업20110706<NA><NA><NA>0202342011108.9100869서울특별시 중구 황학동 415-0번지<NA><NA>현대식품2001-04-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업201711.068142451626.30644식품제조가공업21기타을<NA>00000<NA>00N0.0<NA><NA><NA>
230100003010000-106-1981-0000119810901<NA>3폐업2폐업20151211<NA><NA><NA>02 771100096.0100070서울특별시 중구 소공동 1번지 (주)호텔롯데서울특별시 중구 을지로 30 (소공동, (주)호텔롯데)4533(주)호텔롯데2014-01-03 11:32:27I2018-08-31 23:59:59.0식품제조가공업198259.653577451392.198219식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
330100003010000-106-1985-0000119850504<NA>3폐업2폐업20050721<NA><NA><NA>0222792210<NA>100400서울특별시 중구 쌍림동 182번지<NA><NA>(주)거보비앤에프2003-12-16 00:00:00I2018-08-31 23:59:59.0식품제조가공업200436.761116451157.499427식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
430100003010000-106-1989-0000119890522<NA>3폐업2폐업20141015<NA><NA><NA>02 3126055<NA>100858서울특별시 중구 중림동 149-6번지<NA><NA>순창식품2002-01-19 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
530100003010000-106-1990-0000119900807<NA>3폐업2폐업20040412<NA><NA><NA>0222529264<NA>100869서울특별시 중구 황학동 601번지<NA><NA>중앙식품2002-01-19 00:00:00I2018-08-31 23:59:59.0식품제조가공업201738.292515451602.44536식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
630100003010000-106-1992-0017219920214<NA>3폐업2폐업19980417<NA><NA><NA>02 232259220.55100869서울특별시 중구 황학동 423-0번지<NA><NA>장수식품2001-10-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업201689.764558451637.093514식품제조가공업13기타갑상수도전용00000<NA>00N0.0<NA><NA><NA>
730100003010000-106-1992-0035119920403<NA>3폐업2폐업20080402<NA><NA><NA>022232470154.6100869서울특별시 중구 황학동 393번지<NA><NA>미래식품2004-01-14 00:00:00I2018-08-31 23:59:59.0식품제조가공업201721.335424451565.190606식품제조가공업14기타갑상수도전용00000<NA>00N0.0<NA><NA><NA>
830100003010000-106-1992-0035219920701<NA>3폐업2폐업20180705<NA><NA><NA>0222342311<NA>100869서울특별시 중구 황학동 567번지서울특별시 중구 퇴계로87길 39-3 (황학동)4576유림국수2018-07-05 09:52:22I2018-08-31 23:59:59.0식품제조가공업201769.790042451664.928557식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
930100003010000-106-1993-0016819930915<NA>3폐업2폐업20030919<NA><NA><NA>020279221075.49100855서울특별시 중구 장충동2가 186-19번지<NA><NA>(주)초당식품2000-07-14 00:00:00I2018-08-31 23:59:59.0식품제조가공업200265.977445451012.092948식품제조가공업00기타기타상수도전용00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
27030100003010000-106-2021-000032021-11-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>73.26100-290서울특별시 중구 예관동 30-4 1층서울특별시 중구 창경궁로 28-24, 1층 (예관동)4547주식회사 리사르2024-04-23 13:48:16U2023-12-03 22:05:00.0기타 식품제조가공업199817.767134451419.085609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27130100003010000-106-2022-0000120220203<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0100391서울특별시 중구 장충동1가 54-1 분도빌딩서울특별시 중구 장충단로 188, 분도빌딩 1층 103호 (장충동1가)4606제이로스터(J.Roaster)2022-07-19 11:26:55U2021-12-06 22:01:00.0기타 식품제조가공업200520.859671450972.42635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27230100003010000-106-2022-0000220220517<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.46100868서울특별시 중구 황학동 246서울특별시 중구 퇴계로83길 30-14, 1층 (황학동)4576로투스랩(LOTUSLAB)2022-05-17 15:54:41I2021-12-04 23:09:00.0기타 식품제조가공업201593.427841451635.86507<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27330100003010000-106-2022-000032022-08-09<NA>3폐업2폐업2024-03-22<NA><NA><NA>02380 5817123.33100-440서울특별시 중구 황학동 2545서울특별시 중구 청계천로 400, 지하2층 (황학동, 롯데캐슬베네치아)4572(주)이마트 CK 청계천2024-03-22 13:44:38U2023-12-02 22:04:00.0기타 식품제조가공업201823.908977452076.818664<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27430100003010000-106-2022-0000420221208<NA>1영업/정상1영업<NA><NA><NA><NA>022265570848.66100310서울특별시 중구 오장동 148-55서울특별시 중구 을지로32길 41, 1층 (오장동)4547대영농산2022-12-08 10:32:14I2021-11-01 23:00:00.0기타 식품제조가공업199975.253082451389.639473<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27530100003010000-106-2023-000012023-04-18<NA>1영업/정상1영업<NA><NA><NA><NA>0222655708106.0100-310서울특별시 중구 오장동 69-2서울특별시 중구 을지로32길 42, 1층 (오장동)4547대왕농산2023-11-16 10:56:29U2022-10-31 23:08:00.0기타 식품제조가공업199953.83615451382.944613<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27630100003010000-106-2023-000022023-06-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.74100-834서울특별시 중구 신당동 377-59 인봉빌딩서울특별시 중구 동호로 222, 인봉빌딩 2층 (신당동)4607에이유알(AUR)2024-04-19 10:36:52U2023-12-03 22:01:00.0기타 식품제조가공업200723.5321450605.980277<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27730100003010000-106-2023-000032023-08-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.13100-859서울특별시 중구 중림동 200 102-2호서울특별시 중구 중림로 10, 102-2호 (중림동, 중림동 삼성 사이버 빌리지)4502호랑이소금2023-08-29 14:47:29I2022-12-07 21:01:00.0기타 식품제조가공업196864.942838450649.698043<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27830100003010000-106-2023-000042023-12-12<NA>1영업/정상1영업<NA><NA><NA><NA>0708821998815.04100-310서울특별시 중구 오장동 127-1 센트마상가 1022호서울특별시 중구 동호로33길 24, 센트마상가 1층 1022호 (오장동)4547씨엔에프씨2024-01-12 14:20:09U2023-11-30 23:04:00.0기타 식품제조가공업200015.499568451485.349953<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27930100003010000-106-2024-000012024-01-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.79100-869서울특별시 중구 황학동 754서울특별시 중구 퇴계로81길 32, 1층 (황학동)4576태와재2024-01-15 15:37:36I2023-11-30 23:07:00.0기타 식품제조가공업201540.899632451623.103928<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>