Overview

Dataset statistics

Number of variables44
Number of observations313
Missing cells3087
Missing cells (%)22.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.8 KiB
Average record size in memory375.4 B

Variable types

Categorical19
Text7
DateTime4
Unsupported6
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18271/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
홈페이지 has constant value ""Constant
영업상태코드 is highly imbalanced (57.6%)Imbalance
영업상태명 is highly imbalanced (57.6%)Imbalance
상세영업상태코드 is highly imbalanced (57.6%)Imbalance
상세영업상태명 is highly imbalanced (57.6%)Imbalance
총인원 is highly imbalanced (82.8%)Imbalance
공장사무직종업원수 is highly imbalanced (50.2%)Imbalance
공장판매직종업원수 is highly imbalanced (53.5%)Imbalance
보증액 is highly imbalanced (71.3%)Imbalance
월세액 is highly imbalanced (56.5%)Imbalance
인허가취소일자 has 313 (100.0%) missing valuesMissing
폐업일자 has 27 (8.6%) missing valuesMissing
휴업시작일자 has 313 (100.0%) missing valuesMissing
휴업종료일자 has 313 (100.0%) missing valuesMissing
재개업일자 has 313 (100.0%) missing valuesMissing
전화번호 has 108 (34.5%) missing valuesMissing
소재지면적 has 16 (5.1%) missing valuesMissing
도로명주소 has 154 (49.2%) missing valuesMissing
도로명우편번호 has 156 (49.8%) missing valuesMissing
좌표정보(X) has 12 (3.8%) missing valuesMissing
좌표정보(Y) has 12 (3.8%) missing valuesMissing
남성종사자수 has 227 (72.5%) missing valuesMissing
공장생산직종업원수 has 155 (49.5%) missing valuesMissing
다중이용업소여부 has 14 (4.5%) missing valuesMissing
시설총규모 has 14 (4.5%) missing valuesMissing
전통업소지정번호 has 313 (100.0%) missing valuesMissing
전통업소주된음식 has 313 (100.0%) missing valuesMissing
홈페이지 has 312 (99.7%) 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
소재지면적 has 9 (2.9%) zerosZeros
남성종사자수 has 27 (8.6%) zerosZeros
공장생산직종업원수 has 143 (45.7%) zerosZeros
시설총규모 has 276 (88.2%) zerosZeros

Reproduction

Analysis started2024-05-11 08:03:18.479629
Analysis finished2024-05-11 08:03:19.269888
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3190000
313 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 313
100.0%

Length

2024-05-11T17:03:19.374058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:19.509137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 313
100.0%

관리번호
Text

UNIQUE 

Distinct313
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T17:03:19.691763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6886
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

Unique313 ?
Unique (%)100.0%

Sample

1st row3190000-106-1970-00016
2nd row3190000-106-1970-00360
3rd row3190000-106-1971-00022
4th row3190000-106-1971-00376
5th row3190000-106-1972-00015
ValueCountFrequency (%)
3190000-106-1970-00016 1
 
0.3%
3190000-106-2012-00005 1
 
0.3%
3190000-106-2013-00004 1
 
0.3%
3190000-106-2013-00003 1
 
0.3%
3190000-106-2013-00002 1
 
0.3%
3190000-106-2013-00001 1
 
0.3%
3190000-106-2012-00008 1
 
0.3%
3190000-106-2012-00007 1
 
0.3%
3190000-106-2013-00010 1
 
0.3%
3190000-106-2012-00004 1
 
0.3%
Other values (303) 303
96.8%
2024-05-11T17:03:20.058918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3025
43.9%
1 961
 
14.0%
- 939
 
13.6%
9 500
 
7.3%
6 407
 
5.9%
3 399
 
5.8%
2 359
 
5.2%
4 86
 
1.2%
5 85
 
1.2%
8 63
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5947
86.4%
Dash Punctuation 939
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3025
50.9%
1 961
 
16.2%
9 500
 
8.4%
6 407
 
6.8%
3 399
 
6.7%
2 359
 
6.0%
4 86
 
1.4%
5 85
 
1.4%
8 63
 
1.1%
7 62
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 939
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3025
43.9%
1 961
 
14.0%
- 939
 
13.6%
9 500
 
7.3%
6 407
 
5.9%
3 399
 
5.8%
2 359
 
5.2%
4 86
 
1.2%
5 85
 
1.2%
8 63
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3025
43.9%
1 961
 
14.0%
- 939
 
13.6%
9 500
 
7.3%
6 407
 
5.9%
3 399
 
5.8%
2 359
 
5.2%
4 86
 
1.2%
5 85
 
1.2%
8 63
 
0.9%

인허가일자
Date

Distinct299
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1970-07-22 00:00:00
Maximum2023-05-22 00:00:00
2024-05-11T17:03:20.247937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:20.438332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3
286 
1
 
27

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 (%)
3 286
91.4%
1 27
 
8.6%

Length

2024-05-11T17:03:20.657144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:20.780368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 286
91.4%
1 27
 
8.6%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
286 
영업/정상
 
27

Length

Max length5
Median length2
Mean length2.2587859
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 286
91.4%
영업/정상 27
 
8.6%

Length

2024-05-11T17:03:20.899683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:21.026696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 286
91.4%
영업/정상 27
 
8.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2
286 
1
 
27

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 (%)
2 286
91.4%
1 27
 
8.6%

Length

2024-05-11T17:03:21.148603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:21.252049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 286
91.4%
1 27
 
8.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
286 
영업
 
27

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 286
91.4%
영업 27
 
8.6%

Length

2024-05-11T17:03:21.361018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:21.462232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 286
91.4%
영업 27
 
8.6%

폐업일자
Date

MISSING 

Distinct258
Distinct (%)90.2%
Missing27
Missing (%)8.6%
Memory size2.6 KiB
Minimum1994-06-28 00:00:00
Maximum2024-04-05 00:00:00
2024-05-11T17:03:21.600314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:21.794231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

전화번호
Text

MISSING 

Distinct195
Distinct (%)95.1%
Missing108
Missing (%)34.5%
Memory size2.6 KiB
2024-05-11T17:03:22.091043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.092683
Min length2

Characters and Unicode

Total characters2069
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

Unique192 ?
Unique (%)93.7%

Sample

1st row0208213952
2nd row0208136661
3rd row02 8154321
4th row02 22548053
5th row02
ValueCountFrequency (%)
02 163
39.2%
070 6
 
1.4%
821 4
 
1.0%
815 4
 
1.0%
822 4
 
1.0%
0 3
 
0.7%
823 2
 
0.5%
813 2
 
0.5%
583 2
 
0.5%
817 2
 
0.5%
Other values (222) 224
53.8%
2024-05-11T17:03:22.586971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 377
18.2%
0 328
15.9%
276
13.3%
8 230
11.1%
5 158
7.6%
1 156
7.5%
3 146
 
7.1%
4 112
 
5.4%
7 98
 
4.7%
9 97
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1793
86.7%
Space Separator 276
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 377
21.0%
0 328
18.3%
8 230
12.8%
5 158
8.8%
1 156
8.7%
3 146
 
8.1%
4 112
 
6.2%
7 98
 
5.5%
9 97
 
5.4%
6 91
 
5.1%
Space Separator
ValueCountFrequency (%)
276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2069
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 377
18.2%
0 328
15.9%
276
13.3%
8 230
11.1%
5 158
7.6%
1 156
7.5%
3 146
 
7.1%
4 112
 
5.4%
7 98
 
4.7%
9 97
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 377
18.2%
0 328
15.9%
276
13.3%
8 230
11.1%
5 158
7.6%
1 156
7.5%
3 146
 
7.1%
4 112
 
5.4%
7 98
 
4.7%
9 97
 
4.7%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct276
Distinct (%)92.9%
Missing16
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean62.889192
Minimum0
Maximum577.5
Zeros9
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:23.023849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.028
Q122
median46.03
Q379.33
95-th percentile185.992
Maximum577.5
Range577.5
Interquartile range (IQR)57.33

Descriptive statistics

Standard deviation66.782393
Coefficient of variation (CV)1.0619057
Kurtosis16.190171
Mean62.889192
Median Absolute Deviation (MAD)26.17
Skewness3.2415138
Sum18678.09
Variance4459.8881
MonotonicityNot monotonic
2024-05-11T17:03:23.179408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9
 
2.9%
30.0 3
 
1.0%
16.5 3
 
1.0%
95.4 2
 
0.6%
49.5 2
 
0.6%
22.0 2
 
0.6%
60.0 2
 
0.6%
33.0 2
 
0.6%
68.78 2
 
0.6%
47.14 2
 
0.6%
Other values (266) 268
85.6%
(Missing) 16
 
5.1%
ValueCountFrequency (%)
0.0 9
2.9%
5.33 1
 
0.3%
5.72 1
 
0.3%
6.0 1
 
0.3%
6.27 1
 
0.3%
6.43 1
 
0.3%
6.62 1
 
0.3%
7.13 1
 
0.3%
7.41 1
 
0.3%
8.0 1
 
0.3%
ValueCountFrequency (%)
577.5 1
0.3%
401.5 1
0.3%
378.91 1
0.3%
327.55 1
0.3%
327.28 1
0.3%
259.05 1
0.3%
236.0 1
0.3%
221.48 1
0.3%
217.0 1
0.3%
207.48 1
0.3%

소재지우편번호
Text

Distinct73
Distinct (%)23.4%
Missing1
Missing (%)0.3%
Memory size2.6 KiB
2024-05-11T17:03:23.455258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0224359
Min length6

Characters and Unicode

Total characters1879
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

Unique17 ?
Unique (%)5.4%

Sample

1st row156846
2nd row156808
3rd row156859
4th row156800
5th row156807
ValueCountFrequency (%)
156800 23
 
7.4%
156030 13
 
4.2%
156811 11
 
3.5%
156824 11
 
3.5%
156844 9
 
2.9%
156832 9
 
2.9%
156857 9
 
2.9%
156816 8
 
2.6%
156807 8
 
2.6%
156859 8
 
2.6%
Other values (63) 203
65.1%
2024-05-11T17:03:23.962749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 395
21.0%
5 366
19.5%
6 346
18.4%
8 301
16.0%
0 160
8.5%
3 76
 
4.0%
4 71
 
3.8%
7 66
 
3.5%
2 63
 
3.4%
9 28
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1872
99.6%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 395
21.1%
5 366
19.6%
6 346
18.5%
8 301
16.1%
0 160
8.5%
3 76
 
4.1%
4 71
 
3.8%
7 66
 
3.5%
2 63
 
3.4%
9 28
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1879
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 395
21.0%
5 366
19.5%
6 346
18.4%
8 301
16.0%
0 160
8.5%
3 76
 
4.0%
4 71
 
3.8%
7 66
 
3.5%
2 63
 
3.4%
9 28
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1879
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 395
21.0%
5 366
19.5%
6 346
18.4%
8 301
16.0%
0 160
8.5%
3 76
 
4.0%
4 71
 
3.8%
7 66
 
3.5%
2 63
 
3.4%
9 28
 
1.5%

지번주소
Text

Distinct284
Distinct (%)91.0%
Missing1
Missing (%)0.3%
Memory size2.6 KiB
2024-05-11T17:03:24.326820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length25.224359
Min length19

Characters and Unicode

Total characters7870
Distinct characters139
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

Unique262 ?
Unique (%)84.0%

Sample

1st row서울특별시 동작구 상도동 285-13번지
2nd row서울특별시 동작구 대방동 353-14번지
3rd row서울특별시 동작구 흑석동 95-108번지
4th row서울특별시 동작구 노량진동 13-6 노량진수산물도매시장
5th row서울특별시 동작구 대방동 11-85번지
ValueCountFrequency (%)
서울특별시 312
21.8%
동작구 312
21.8%
사당동 88
 
6.1%
상도동 67
 
4.7%
노량진동 46
 
3.2%
신대방동 32
 
2.2%
흑석동 31
 
2.2%
1층 24
 
1.7%
대방동 23
 
1.6%
상도1동 16
 
1.1%
Other values (357) 482
33.6%
2024-05-11T17:03:24.770020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1398
17.8%
동 644
 
8.2%
1 374
 
4.8%
시 321
 
4.1%
작 315
 
4.0%
서 312
 
4.0%
구 312
 
4.0%
울 312
 
4.0%
별 312
 
4.0%
특 312
 
4.0%
Other values (129) 3258
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4610
58.6%
Decimal Number 1542
 
19.6%
Space Separator 1398
 
17.8%
Dash Punctuation 276
 
3.5%
Close Punctuation 17
 
0.2%
Open Punctuation 17
 
0.2%
Uppercase Letter 6
 
0.1%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 644
14.0%
시 321
 
7.0%
작 315
 
6.8%
서 312
 
6.8%
구 312
 
6.8%
울 312
 
6.8%
별 312
 
6.8%
특 312
 
6.8%
지 301
 
6.5%
번 266
 
5.8%
Other values (110) 1203
26.1%
Decimal Number
ValueCountFrequency (%)
1 374
24.3%
2 207
13.4%
3 207
13.4%
0 151
9.8%
4 123
 
8.0%
5 112
 
7.3%
8 111
 
7.2%
6 110
 
7.1%
9 80
 
5.2%
7 67
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
? 1
25.0%
@ 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
83.3%
C 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1398
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4610
58.6%
Common 3254
41.3%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 644
14.0%
시 321
 
7.0%
작 315
 
6.8%
서 312
 
6.8%
구 312
 
6.8%
울 312
 
6.8%
별 312
 
6.8%
특 312
 
6.8%
지 301
 
6.5%
번 266
 
5.8%
Other values (110) 1203
26.1%
Common
ValueCountFrequency (%)
1398
43.0%
1 374
 
11.5%
- 276
 
8.5%
2 207
 
6.4%
3 207
 
6.4%
0 151
 
4.6%
4 123
 
3.8%
5 112
 
3.4%
8 111
 
3.4%
6 110
 
3.4%
Other values (7) 185
 
5.7%
Latin
ValueCountFrequency (%)
B 5
83.3%
C 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4610
58.6%
ASCII 3260
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1398
42.9%
1 374
 
11.5%
- 276
 
8.5%
2 207
 
6.3%
3 207
 
6.3%
0 151
 
4.6%
4 123
 
3.8%
5 112
 
3.4%
8 111
 
3.4%
6 110
 
3.4%
Other values (9) 191
 
5.9%
Hangul
ValueCountFrequency (%)
동 644
14.0%
시 321
 
7.0%
작 315
 
6.8%
서 312
 
6.8%
구 312
 
6.8%
울 312
 
6.8%
별 312
 
6.8%
특 312
 
6.8%
지 301
 
6.5%
번 266
 
5.8%
Other values (110) 1203
26.1%

도로명주소
Text

MISSING 

Distinct154
Distinct (%)96.9%
Missing154
Missing (%)49.2%
Memory size2.6 KiB
2024-05-11T17:03:25.105463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length31.421384
Min length22

Characters and Unicode

Total characters4996
Distinct characters141
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

Unique150 ?
Unique (%)94.3%

Sample

1st row서울특별시 동작구 여의대방로46길 22 (대방동)
2nd row서울특별시 동작구 노들로 674, 노량진수산물도매시장 지하1층 (노량진동)
3rd row서울특별시 동작구 사당로28가길 20 (사당동)
4th row서울특별시 동작구 사당로8길 32 (사당동,(1층))
5th row서울특별시 동작구 사당로2자길 2-13 (사당동,지층)
ValueCountFrequency (%)
서울특별시 159
 
16.4%
동작구 159
 
16.4%
사당동 40
 
4.1%
상도동 31
 
3.2%
1층 26
 
2.7%
노량진동 25
 
2.6%
흑석동 21
 
2.2%
2층 17
 
1.8%
지하1층 17
 
1.8%
신대방동 15
 
1.5%
Other values (280) 458
47.3%
2024-05-11T17:03:25.651724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
809
 
16.2%
동 353
 
7.1%
1 185
 
3.7%
작 177
 
3.5%
시 168
 
3.4%
서 165
 
3.3%
( 163
 
3.3%
) 163
 
3.3%
울 159
 
3.2%
구 159
 
3.2%
Other values (131) 2495
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2978
59.6%
Space Separator 809
 
16.2%
Decimal Number 731
 
14.6%
Open Punctuation 163
 
3.3%
Close Punctuation 163
 
3.3%
Other Punctuation 127
 
2.5%
Dash Punctuation 16
 
0.3%
Uppercase Letter 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 353
 
11.9%
작 177
 
5.9%
시 168
 
5.6%
서 165
 
5.5%
울 159
 
5.3%
구 159
 
5.3%
별 159
 
5.3%
특 159
 
5.3%
로 149
 
5.0%
길 111
 
3.7%
Other values (112) 1219
40.9%
Decimal Number
ValueCountFrequency (%)
1 185
25.3%
2 133
18.2%
3 72
 
9.8%
4 69
 
9.4%
0 53
 
7.3%
5 51
 
7.0%
6 51
 
7.0%
7 49
 
6.7%
8 37
 
5.1%
9 31
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 5
55.6%
A 2
 
22.2%
C 1
 
11.1%
D 1
 
11.1%
Space Separator
ValueCountFrequency (%)
809
100.0%
Open Punctuation
ValueCountFrequency (%)
( 163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Other Punctuation
ValueCountFrequency (%)
, 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2978
59.6%
Common 2009
40.2%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 353
 
11.9%
작 177
 
5.9%
시 168
 
5.6%
서 165
 
5.5%
울 159
 
5.3%
구 159
 
5.3%
별 159
 
5.3%
특 159
 
5.3%
로 149
 
5.0%
길 111
 
3.7%
Other values (112) 1219
40.9%
Common
ValueCountFrequency (%)
809
40.3%
1 185
 
9.2%
( 163
 
8.1%
) 163
 
8.1%
2 133
 
6.6%
, 127
 
6.3%
3 72
 
3.6%
4 69
 
3.4%
0 53
 
2.6%
5 51
 
2.5%
Other values (5) 184
 
9.2%
Latin
ValueCountFrequency (%)
B 5
55.6%
A 2
 
22.2%
C 1
 
11.1%
D 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2978
59.6%
ASCII 2018
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
809
40.1%
1 185
 
9.2%
( 163
 
8.1%
) 163
 
8.1%
2 133
 
6.6%
, 127
 
6.3%
3 72
 
3.6%
4 69
 
3.4%
0 53
 
2.6%
5 51
 
2.5%
Other values (9) 193
 
9.6%
Hangul
ValueCountFrequency (%)
동 353
 
11.9%
작 177
 
5.9%
시 168
 
5.6%
서 165
 
5.5%
울 159
 
5.3%
구 159
 
5.3%
별 159
 
5.3%
특 159
 
5.3%
로 149
 
5.0%
길 111
 
3.7%
Other values (112) 1219
40.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct80
Distinct (%)51.0%
Missing156
Missing (%)49.8%
Infinite0
Infinite (%)0.0%
Mean6982.121
Minimum6900
Maximum7071
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:25.840207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6900
5-th percentile6900
Q16945
median6982
Q37025
95-th percentile7059.8
Maximum7071
Range171
Interquartile range (IQR)80

Descriptive statistics

Standard deviation51.23705
Coefficient of variation (CV)0.0073383216
Kurtosis-1.087203
Mean6982.121
Median Absolute Deviation (MAD)41
Skewness-0.1598144
Sum1096193
Variance2625.2353
MonotonicityNot monotonic
2024-05-11T17:03:26.055031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6900 14
 
4.5%
7008 7
 
2.2%
7025 5
 
1.6%
6904 5
 
1.6%
6959 4
 
1.3%
7030 4
 
1.3%
6982 4
 
1.3%
6981 4
 
1.3%
7068 4
 
1.3%
6965 4
 
1.3%
Other values (70) 102
32.6%
(Missing) 156
49.8%
ValueCountFrequency (%)
6900 14
4.5%
6902 1
 
0.3%
6904 5
 
1.6%
6907 1
 
0.3%
6908 2
 
0.6%
6914 3
 
1.0%
6917 2
 
0.6%
6918 1
 
0.3%
6919 1
 
0.3%
6921 1
 
0.3%
ValueCountFrequency (%)
7071 1
 
0.3%
7069 1
 
0.3%
7068 4
1.3%
7064 1
 
0.3%
7063 1
 
0.3%
7059 1
 
0.3%
7056 3
1.0%
7055 1
 
0.3%
7053 3
1.0%
7049 2
0.6%

사업장명
Text

Distinct297
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T17:03:26.373665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length6.1629393
Min length2

Characters and Unicode

Total characters1929
Distinct characters398
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

Unique282 ?
Unique (%)90.1%

Sample

1st row강남제과
2nd row영남두부
3rd row경남식품
4th row수협노량진수산주식회사
5th row태광제과
ValueCountFrequency (%)
주식회사 6
 
1.6%
홍삼나라 4
 
1.1%
성화식품 3
 
0.8%
스테이지 2
 
0.5%
산해수산 2
 
0.5%
신풍수산(주 2
 
0.5%
조경연베이커리 2
 
0.5%
식품 2
 
0.5%
food 2
 
0.5%
한국대주통상(주 2
 
0.5%
Other values (331) 345
92.7%
2024-05-11T17:03:26.869411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 78
 
4.0%
품 67
 
3.5%
주 60
 
3.1%
) 59
 
3.1%
59
 
3.1%
( 59
 
3.1%
스 40
 
2.1%
이 32
 
1.7%
리 27
 
1.4%
산 26
 
1.3%
Other values (388) 1422
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1607
83.3%
Lowercase Letter 70
 
3.6%
Close Punctuation 59
 
3.1%
Space Separator 59
 
3.1%
Open Punctuation 59
 
3.1%
Uppercase Letter 52
 
2.7%
Decimal Number 11
 
0.6%
Other Punctuation 10
 
0.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 78
 
4.9%
품 67
 
4.2%
주 60
 
3.7%
스 40
 
2.5%
이 32
 
2.0%
리 27
 
1.7%
산 26
 
1.6%
드 24
 
1.5%
푸 20
 
1.2%
에 20
 
1.2%
Other values (341) 1213
75.5%
Lowercase Letter
ValueCountFrequency (%)
o 11
15.7%
a 10
14.3%
e 8
11.4%
s 7
10.0%
r 6
8.6%
l 5
7.1%
n 4
 
5.7%
i 4
 
5.7%
d 3
 
4.3%
t 2
 
2.9%
Other values (7) 10
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 9
17.3%
F 9
17.3%
B 7
13.5%
P 4
7.7%
D 3
 
5.8%
T 3
 
5.8%
O 2
 
3.8%
E 2
 
3.8%
N 2
 
3.8%
A 2
 
3.8%
Other values (7) 9
17.3%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
0 3
27.3%
3 2
18.2%
9 2
18.2%
1 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 5
50.0%
& 3
30.0%
? 1
 
10.0%
, 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1607
83.3%
Common 200
 
10.4%
Latin 122
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 78
 
4.9%
품 67
 
4.2%
주 60
 
3.7%
스 40
 
2.5%
이 32
 
2.0%
리 27
 
1.7%
산 26
 
1.6%
드 24
 
1.5%
푸 20
 
1.2%
에 20
 
1.2%
Other values (341) 1213
75.5%
Latin
ValueCountFrequency (%)
o 11
 
9.0%
a 10
 
8.2%
C 9
 
7.4%
F 9
 
7.4%
e 8
 
6.6%
B 7
 
5.7%
s 7
 
5.7%
r 6
 
4.9%
l 5
 
4.1%
P 4
 
3.3%
Other values (24) 46
37.7%
Common
ValueCountFrequency (%)
) 59
29.5%
59
29.5%
( 59
29.5%
. 5
 
2.5%
2 3
 
1.5%
& 3
 
1.5%
0 3
 
1.5%
3 2
 
1.0%
- 2
 
1.0%
9 2
 
1.0%
Other values (3) 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1607
83.3%
ASCII 322
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 78
 
4.9%
품 67
 
4.2%
주 60
 
3.7%
스 40
 
2.5%
이 32
 
2.0%
리 27
 
1.7%
산 26
 
1.6%
드 24
 
1.5%
푸 20
 
1.2%
에 20
 
1.2%
Other values (341) 1213
75.5%
ASCII
ValueCountFrequency (%)
) 59
18.3%
59
18.3%
( 59
18.3%
o 11
 
3.4%
a 10
 
3.1%
C 9
 
2.8%
F 9
 
2.8%
e 8
 
2.5%
B 7
 
2.2%
s 7
 
2.2%
Other values (37) 84
26.1%

최종수정일자
Date

Distinct289
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1999-01-15 00:00:00
Maximum2024-04-05 15:48:16
2024-05-11T17:03:27.030552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:27.220060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
I
246 
U
67 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 246
78.6%
U 67
 
21.4%

Length

2024-05-11T17:03:27.416084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:27.542034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 246
78.6%
u 67
 
21.4%

데이터갱신일자
Date

Distinct63
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-05-11T17:03:27.674868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:27.840236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
식품제조가공업
257 
기타 식품제조가공업
56 

Length

Max length10
Median length7
Mean length7.5367412
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 257
82.1%
기타 식품제조가공업 56
 
17.9%

Length

2024-05-11T17:03:27.995795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:28.110827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 313
84.8%
기타 56
 
15.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct242
Distinct (%)80.4%
Missing12
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean195542.71
Minimum191484.23
Maximum198371.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:28.264764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191484.23
5-th percentile192949.08
Q1194163.46
median195228.45
Q3197240.77
95-th percentile198217.63
Maximum198371.1
Range6886.8672
Interquartile range (IQR)3077.3157

Descriptive statistics

Standard deviation1814.1783
Coefficient of variation (CV)0.0092776577
Kurtosis-1.0921162
Mean195542.71
Median Absolute Deviation (MAD)1464.1491
Skewness-0.047179349
Sum58858355
Variance3291242.9
MonotonicityNot monotonic
2024-05-11T17:03:28.434814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194807.845295028 13
 
4.2%
194346.156670595 8
 
2.6%
193273.484014052 4
 
1.3%
194571.152376388 4
 
1.3%
194006.277146586 3
 
1.0%
197240.772071795 3
 
1.0%
194422.119122943 3
 
1.0%
195975.975679468 3
 
1.0%
196874.591319262 3
 
1.0%
195846.558326437 2
 
0.6%
Other values (232) 255
81.5%
(Missing) 12
 
3.8%
ValueCountFrequency (%)
191484.231170935 1
0.3%
191853.593009781 1
0.3%
191858.575856447 1
0.3%
191883.069816087 2
0.6%
191921.480800674 1
0.3%
191934.535683403 2
0.6%
191942.624662357 1
0.3%
191946.135275517 1
0.3%
192113.200600983 1
0.3%
192120.823991709 1
0.3%
ValueCountFrequency (%)
198371.098321744 1
0.3%
198341.017757812 1
0.3%
198303.527071078 1
0.3%
198297.907079009 1
0.3%
198294.299502142 1
0.3%
198278.65240338 1
0.3%
198261.938633463 1
0.3%
198258.866837061 2
0.6%
198243.208842536 1
0.3%
198241.841531642 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct242
Distinct (%)80.4%
Missing12
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean443996.08
Minimum441543.54
Maximum445901.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:28.609140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441543.54
5-th percentile442005.01
Q1442899.88
median444140.1
Q3444965.45
95-th percentile445823.5
Maximum445901.41
Range4357.8758
Interquartile range (IQR)2065.5702

Descriptive statistics

Standard deviation1219.6373
Coefficient of variation (CV)0.0027469551
Kurtosis-1.0757192
Mean443996.08
Median Absolute Deviation (MAD)966.41944
Skewness-0.21192294
Sum1.3364282 × 108
Variance1487515.2
MonotonicityNot monotonic
2024-05-11T17:03:28.771836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445901.413432497 13
 
4.2%
445823.500892497 8
 
2.6%
445011.250115029 4
 
1.3%
445790.549860682 4
 
1.3%
444284.703356202 3
 
1.0%
444965.446982195 3
 
1.0%
443649.637984534 3
 
1.0%
445303.904436624 3
 
1.0%
444555.900566914 3
 
1.0%
444527.107280431 2
 
0.6%
Other values (232) 255
81.5%
(Missing) 12
 
3.8%
ValueCountFrequency (%)
441543.537610587 2
0.6%
441588.861462309 1
0.3%
441659.149738346 1
0.3%
441673.103634257 1
0.3%
441702.598478923 1
0.3%
441727.989039694 1
0.3%
441846.23470247 1
0.3%
441847.93259161 2
0.6%
441883.096617834 1
0.3%
441923.208739063 1
0.3%
ValueCountFrequency (%)
445901.413432497 13
4.2%
445836.993606646 1
 
0.3%
445823.500892497 8
2.6%
445820.883711428 1
 
0.3%
445790.549860682 4
 
1.3%
445764.45259219 1
 
0.3%
445763.962955131 1
 
0.3%
445623.835477523 1
 
0.3%
445610.160717686 1
 
0.3%
445605.494074381 1
 
0.3%

위생업태명
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
식품제조가공업
253 
기타 식품제조가공업
46 
<NA>
 
14

Length

Max length10
Median length7
Mean length7.3067093
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 253
80.8%
기타 식품제조가공업 46
 
14.7%
<NA> 14
 
4.5%

Length

2024-05-11T17:03:28.932427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:29.057711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 299
83.3%
기타 46
 
12.8%
na 14
 
3.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)7.0%
Missing227
Missing (%)72.5%
Infinite0
Infinite (%)0.0%
Mean1.1046512
Minimum0
Maximum10
Zeros27
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:29.176438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3375049
Coefficient of variation (CV)1.2107939
Kurtosis22.363747
Mean1.1046512
Median Absolute Deviation (MAD)1
Skewness3.7310186
Sum95
Variance1.7889193
MonotonicityNot monotonic
2024-05-11T17:03:29.310878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 39
 
12.5%
0 27
 
8.6%
2 12
 
3.8%
3 6
 
1.9%
10 1
 
0.3%
4 1
 
0.3%
(Missing) 227
72.5%
ValueCountFrequency (%)
0 27
8.6%
1 39
12.5%
2 12
 
3.8%
3 6
 
1.9%
4 1
 
0.3%
10 1
 
0.3%
ValueCountFrequency (%)
10 1
 
0.3%
4 1
 
0.3%
3 6
 
1.9%
2 12
 
3.8%
1 39
12.5%
0 27
8.6%

여성종사자수
Categorical

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
226 
0
36 
1
25 
2
 
14
3
 
11

Length

Max length4
Median length4
Mean length3.1661342
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row3
2nd row2
3rd row<NA>
4th row0
5th row3

Common Values

ValueCountFrequency (%)
<NA> 226
72.2%
0 36
 
11.5%
1 25
 
8.0%
2 14
 
4.5%
3 11
 
3.5%
5 1
 
0.3%

Length

2024-05-11T17:03:29.447004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:29.570137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 226
72.2%
0 36
 
11.5%
1 25
 
8.0%
2 14
 
4.5%
3 11
 
3.5%
5 1
 
0.3%

영업장주변구분명
Categorical

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
230 
주택가주변
50 
기타
31 
아파트지역
 
2

Length

Max length5
Median length4
Mean length3.9680511
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 230
73.5%
주택가주변 50
 
16.0%
기타 31
 
9.9%
아파트지역 2
 
0.6%

Length

2024-05-11T17:03:29.715455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:29.850652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
73.5%
주택가주변 50
 
16.0%
기타 31
 
9.9%
아파트지역 2
 
0.6%

등급구분명
Categorical

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
230 
자율
46 
관리
 
18
기타
 
17
을
 
2

Length

Max length4
Median length4
Mean length3.4632588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 230
73.5%
자율 46
 
14.7%
관리 18
 
5.8%
기타 17
 
5.4%
을 2
 
0.6%

Length

2024-05-11T17:03:29.973469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:30.086907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
73.5%
자율 46
 
14.7%
관리 18
 
5.8%
기타 17
 
5.4%
을 2
 
0.6%

급수시설구분명
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
상수도전용
192 
<NA>
119 
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length5
Mean length4.6964856
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row상수도(음용)지하수(주방용)겸용
3rd row상수도전용
4th row상수도전용
5th row상수도전용

Common Values

ValueCountFrequency (%)
상수도전용 192
61.3%
<NA> 119
38.0%
상수도(음용)지하수(주방용)겸용 2
 
0.6%

Length

2024-05-11T17:03:30.219563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:30.383103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 192
61.3%
na 119
38.0%
상수도(음용)지하수(주방용)겸용 2
 
0.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
305 
0
 
8

Length

Max length4
Median length4
Mean length3.9233227
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> 305
97.4%
0 8
 
2.6%

Length

2024-05-11T17:03:30.521487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:30.652599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 305
97.4%
0 8
 
2.6%

본사종업원수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
166 
0
147 

Length

Max length4
Median length4
Mean length2.5910543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 166
53.0%
0 147
47.0%

Length

2024-05-11T17:03:30.761420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:30.866667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 166
53.0%
0 147
47.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
160 
0
146 
1
 
5
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length2.5335463
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 160
51.1%
0 146
46.6%
1 5
 
1.6%
2 1
 
0.3%
3 1
 
0.3%

Length

2024-05-11T17:03:30.967740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:31.070607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 160
51.1%
0 146
46.6%
1 5
 
1.6%
2 1
 
0.3%
3 1
 
0.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
165 
0
145 
5
 
1
2
 
1
1
 
1

Length

Max length4
Median length4
Mean length2.5814696
Min length1

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 165
52.7%
0 145
46.3%
5 1
 
0.3%
2 1
 
0.3%
1 1
 
0.3%

Length

2024-05-11T17:03:31.450141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:31.554919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 165
52.7%
0 145
46.3%
5 1
 
0.3%
2 1
 
0.3%
1 1
 
0.3%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)4.4%
Missing155
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean0.24050633
Minimum0
Maximum13
Zeros143
Zeros (%)45.7%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:31.646546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2020703
Coefficient of variation (CV)4.9980817
Kurtosis83.463302
Mean0.24050633
Median Absolute Deviation (MAD)0
Skewness8.4386709
Sum38
Variance1.444973
MonotonicityNot monotonic
2024-05-11T17:03:31.749929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 143
45.7%
1 9
 
2.9%
2 2
 
0.6%
3 1
 
0.3%
5 1
 
0.3%
13 1
 
0.3%
4 1
 
0.3%
(Missing) 155
49.5%
ValueCountFrequency (%)
0 143
45.7%
1 9
 
2.9%
2 2
 
0.6%
3 1
 
0.3%
4 1
 
0.3%
5 1
 
0.3%
13 1
 
0.3%
ValueCountFrequency (%)
13 1
 
0.3%
5 1
 
0.3%
4 1
 
0.3%
3 1
 
0.3%
2 2
 
0.6%
1 9
 
2.9%
0 143
45.7%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
138 
임대
124 
자가
51 

Length

Max length4
Median length2
Mean length2.8817891
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 138
44.1%
임대 124
39.6%
자가 51
 
16.3%

Length

2024-05-11T17:03:31.884237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:31.996055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 138
44.1%
임대 124
39.6%
자가 51
 
16.3%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
285 
0
 
27
10000000
 
1

Length

Max length8
Median length4
Mean length3.7539936
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 285
91.1%
0 27
 
8.6%
10000000 1
 
0.3%

Length

2024-05-11T17:03:32.112545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:32.217616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 285
91.1%
0 27
 
8.6%
10000000 1
 
0.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
285 
0
 
28

Length

Max length4
Median length4
Mean length3.7316294
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> 285
91.1%
0 28
 
8.9%

Length

2024-05-11T17:03:32.333800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:32.438497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 285
91.1%
0 28
 
8.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing14
Missing (%)4.5%
Memory size758.0 B
False
299 
(Missing)
 
14
ValueCountFrequency (%)
False 299
95.5%
(Missing) 14
 
4.5%
2024-05-11T17:03:32.543600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)8.0%
Missing14
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean3.2991973
Minimum0
Maximum193
Zeros276
Zeros (%)88.2%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T17:03:32.642503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7.2
Maximum193
Range193
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.658361
Coefficient of variation (CV)5.6554244
Kurtosis68.391113
Mean3.2991973
Median Absolute Deviation (MAD)0
Skewness7.8500558
Sum986.46
Variance348.13444
MonotonicityNot monotonic
2024-05-11T17:03:32.786166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 276
88.2%
6.6 1
 
0.3%
41.28 1
 
0.3%
54.5 1
 
0.3%
15.4 1
 
0.3%
10.0 1
 
0.3%
6.9 1
 
0.3%
4.82 1
 
0.3%
26.1 1
 
0.3%
176.85 1
 
0.3%
Other values (14) 14
 
4.5%
(Missing) 14
 
4.5%
ValueCountFrequency (%)
0.0 276
88.2%
2.1 1
 
0.3%
2.96 1
 
0.3%
3.07 1
 
0.3%
4.82 1
 
0.3%
6.6 1
 
0.3%
6.72 1
 
0.3%
6.76 1
 
0.3%
6.9 1
 
0.3%
9.9 1
 
0.3%
ValueCountFrequency (%)
193.0 1
0.3%
176.85 1
0.3%
132.29 1
0.3%
67.93 1
0.3%
66.0 1
0.3%
54.5 1
0.3%
45.29 1
0.3%
41.5 1
0.3%
41.28 1
0.3%
33.49 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing313
Missing (%)100.0%
Memory size2.9 KiB

홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing312
Missing (%)99.7%
Memory size2.6 KiB
2024-05-11T17:03:32.943933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowssdd2230@naver.com
ValueCountFrequency (%)
ssdd2230@naver.com 1
100.0%
2024-05-11T17:03:33.179802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 2
 
11.1%
d 2
 
11.1%
2 2
 
11.1%
3 1
 
5.6%
0 1
 
5.6%
@ 1
 
5.6%
n 1
 
5.6%
a 1
 
5.6%
v 1
 
5.6%
e 1
 
5.6%
Other values (5) 5
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
66.7%
Decimal Number 4
 
22.2%
Other Punctuation 2
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2
16.7%
d 2
16.7%
n 1
8.3%
a 1
8.3%
v 1
8.3%
e 1
8.3%
r 1
8.3%
c 1
8.3%
o 1
8.3%
m 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
0 1
25.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
50.0%
. 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
66.7%
Common 6
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2
16.7%
d 2
16.7%
n 1
8.3%
a 1
8.3%
v 1
8.3%
e 1
8.3%
r 1
8.3%
c 1
8.3%
o 1
8.3%
m 1
8.3%
Common
ValueCountFrequency (%)
2 2
33.3%
3 1
16.7%
0 1
16.7%
@ 1
16.7%
. 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2
 
11.1%
d 2
 
11.1%
2 2
 
11.1%
3 1
 
5.6%
0 1
 
5.6%
@ 1
 
5.6%
n 1
 
5.6%
a 1
 
5.6%
v 1
 
5.6%
e 1
 
5.6%
Other values (5) 5
27.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031900003190000-106-1970-0001619701205<NA>3폐업2폐업20020328<NA><NA><NA>0208213952110.04156846서울특별시 동작구 상도동 285-13번지<NA><NA>강남제과2000-04-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업194095.231582443612.10079식품제조가공업13주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131900003190000-106-1970-0036019700722<NA>3폐업2폐업20120618<NA><NA><NA>0208136661174.52156808서울특별시 동작구 대방동 353-14번지서울특별시 동작구 여의대방로46길 22 (대방동)6941영남두부2011-11-17 15:40:15I2018-08-31 23:59:59.0식품제조가공업193378.832637445351.333867식품제조가공업32주택가주변자율상수도(음용)지하수(주방용)겸용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
231900003190000-106-1971-0002219710403<NA>3폐업2폐업19970212<NA><NA><NA>02 81543210.0156859서울특별시 동작구 흑석동 95-108번지<NA><NA>경남식품2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331900003190000-106-1971-0037619710819<NA>3폐업2폐업20201008<NA><NA><NA>02 22548053577.5156800서울특별시 동작구 노량진동 13-6 노량진수산물도매시장서울특별시 동작구 노들로 674, 노량진수산물도매시장 지하1층 (노량진동)6900수협노량진수산주식회사2020-10-08 11:54:43U2020-10-10 02:40:00.0식품제조가공업194346.156671445823.500892식품제조가공업100기타자율상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
431900003190000-106-1972-0001519721128<NA>3폐업2폐업20020214<NA><NA><NA>02173.41156807서울특별시 동작구 대방동 11-85번지<NA><NA>태광제과2000-10-21 00:00:00I2018-08-31 23:59:59.0식품제조가공업193963.143385444878.641948식품제조가공업23주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531900003190000-106-1990-0036519900308<NA>3폐업2폐업20010817<NA><NA><NA>0273.4156821서울특별시 동작구 사당동 272-47번지<NA><NA>혜성식품2001-08-17 00:00:00I2018-08-31 23:59:59.0식품제조가공업197268.99558442368.385767식품제조가공업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631900003190000-106-1991-0001719911209<NA>3폐업2폐업19980616<NA><NA><NA>02 5882962123.2156827서울특별시 동작구 사당동 1049-16번지<NA><NA>리꼬후드1999-01-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업197645.496563441588.861462식품제조가공업23주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731900003190000-106-1992-0001419920128<NA>3폐업2폐업19940628<NA><NA><NA>02 82367490.0156836서울특별시 동작구 상도1동 359-3번지<NA><NA>대건교역2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업195608.253027444232.447808식품제조가공업32주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831900003190000-106-1992-0023319921030<NA>3폐업2폐업20070529<NA><NA><NA>02 8458336119.6156854서울특별시 동작구 신대방동 690-16번지<NA><NA>포천식품2006-01-23 00:00:00I2018-08-31 23:59:59.0식품제조가공업191921.480801442825.301375식품제조가공업31기타을상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
931900003190000-106-1992-0036619920208<NA>3폐업2폐업19980924<NA><NA><NA>02 522460074.11156823서울특별시 동작구 사당동 318-65번지<NA><NA>두성식품1999-01-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업197640.086909442236.665657식품제조가공업30기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
30331900003190000-106-2020-0000120200304<NA>3폐업2폐업20220121<NA><NA><NA><NA>36.36156070서울특별시 동작구 흑석동 336 흑석한강푸르지오상가 C동 304호서울특별시 동작구 흑석한강로 27, C동 304호 (흑석동, 흑석한강푸르지오)6981닥터오빈2022-01-21 16:19:01U2022-01-23 02:40:00.0기타 식품제조가공업196874.591319444555.900567기타 식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
30431900003190000-106-2020-0000220200724<NA>3폐업2폐업20220314<NA><NA><NA>02 837 388316.5156852서울특별시 동작구 신대방동 591-10서울특별시 동작구 신대방길 98, 1층 (신대방동)7068이원제과2022-03-14 10:39:39U2022-03-16 02:40:00.0기타 식품제조가공업191883.069816443085.276981기타 식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
30531900003190000-106-2020-0000320200903<NA>3폐업2폐업20201230<NA><NA><NA>02 1877859229.38156030서울특별시 동작구 상도동 535 상도2차두산위브트레지움아파트서울특별시 동작구 상도로30길 40, 상가B동 1층 115호 (상도동, 상도2차두산위브트레지움아파트)6964정담유통(주)상도지점2020-12-30 14:26:11U2021-01-01 02:40:00.0기타 식품제조가공업194870.384384444631.112679기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
30631900003190000-106-2020-0000420200923<NA>1영업/정상1영업<NA><NA><NA><NA>02 822901299.29156839서울특별시 동작구 상도동 354-2서울특별시 동작구 상도로15길 38, 지층 (상도동)6950(주)포에스글로벌2020-09-23 10:12:18I2020-09-25 00:23:12.0기타 식품제조가공업194100.406724444454.676193기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
30731900003190000-106-2020-000052020-11-30<NA>3폐업2폐업2023-03-23<NA><NA><NA><NA>77.31156-030서울특별시 동작구 상도동 427 커피나무빌딩서울특별시 동작구 상도로53길 65, 커피나무빌딩 (상도동)6970정담에프앤비 상도지점2023-03-23 11:17:49U2022-12-02 22:05:00.0기타 식품제조가공업195846.558326444527.10728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30831900003190000-106-2021-0000120210405<NA>1영업/정상1영업<NA><NA><NA><NA>0232809989124.52156859서울특별시 동작구 흑석동 97-2 명수대아파트상가서울특별시 동작구 서달로 158, 2층 (흑석동, 명수대아파트)6979리치몽브레2021-04-05 10:40:09I2021-04-07 00:22:58.0기타 식품제조가공업196598.048336445014.002982기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
30931900003190000-106-2021-0000220210615<NA>1영업/정상1영업<NA><NA><NA><NA>02522 865118.15156879서울특별시 동작구 사당동 204-13서울특별시 동작구 사당로2차길 27, 1층 (사당동)7030아맘.픽2021-06-24 11:42:39U2021-06-26 02:40:00.0기타 식품제조가공업196917.289209442787.332127기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
31031900003190000-106-2021-000032021-11-22<NA>1영업/정상1영업<NA><NA><NA><NA>02 555369960.8156-800서울특별시 동작구 노량진동 16-1 노량진 드림스퀘어 복합빌딩서울특별시 동작구 노들로2길 7, 노량진 드림스퀘어 복합빌딩 B5층 6호 (노량진동)6900해초록2023-02-03 11:26:20U2022-12-02 00:05:00.0기타 식품제조가공업194571.152376445790.549861<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31131900003190000-106-2021-000042021-11-22<NA>3폐업2폐업2024-02-01<NA><NA><NA>02 555707057.7156-800서울특별시 동작구 노량진동 16-1 노량진 드림스퀘어 복합빌딩서울특별시 동작구 노들로2길 7, 노량진 드림스퀘어 복합빌딩 B4층 7호 (노량진동)6900(주)해초록2024-02-01 14:37:55U2023-12-02 00:03:00.0기타 식품제조가공업194571.152376445790.549861<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31231900003190000-106-2023-000012023-05-22<NA>3폐업2폐업2023-06-23<NA><NA><NA><NA>22.0156-839서울특별시 동작구 상도동 350-20서울특별시 동작구 상도로15길 11, 201호 (상도동)6952한입건강2023-06-23 09:52:11U2022-12-05 22:05:00.0기타 식품제조가공업193994.826689444368.294784<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>