Overview

Dataset statistics

Number of variables44
Number of observations465
Missing cells4307
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.4 KiB
Average record size in memory375.3 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18269/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (73.9%)Imbalance
여성종사자수 is highly imbalanced (69.9%)Imbalance
영업장주변구분명 is highly imbalanced (61.7%)Imbalance
등급구분명 is highly imbalanced (61.7%)Imbalance
총인원 is highly imbalanced (77.4%)Imbalance
본사종업원수 is highly imbalanced (54.4%)Imbalance
보증액 is highly imbalanced (73.2%)Imbalance
월세액 is highly imbalanced (73.2%)Imbalance
인허가취소일자 has 465 (100.0%) missing valuesMissing
폐업일자 has 94 (20.2%) missing valuesMissing
휴업시작일자 has 465 (100.0%) missing valuesMissing
휴업종료일자 has 465 (100.0%) missing valuesMissing
재개업일자 has 465 (100.0%) missing valuesMissing
전화번호 has 153 (32.9%) missing valuesMissing
소재지면적 has 28 (6.0%) missing valuesMissing
도로명주소 has 209 (44.9%) missing valuesMissing
도로명우편번호 has 211 (45.4%) missing valuesMissing
공장생산직종업원수 has 223 (48.0%) missing valuesMissing
다중이용업소여부 has 64 (13.8%) missing valuesMissing
시설총규모 has 64 (13.8%) missing valuesMissing
전통업소지정번호 has 465 (100.0%) missing valuesMissing
전통업소주된음식 has 465 (100.0%) missing valuesMissing
홈페이지 has 465 (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 232 (49.9%) zerosZeros
시설총규모 has 324 (69.7%) zerosZeros

Reproduction

Analysis started2024-04-17 16:34:33.586727
Analysis finished2024-04-17 16:34:34.219666
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3170000
465 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 465
100.0%

Length

2024-04-18T01:34:34.266009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:34.330957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 465
100.0%

관리번호
Text

UNIQUE 

Distinct465
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-04-18T01:34:34.484267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10230
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

Unique465 ?
Unique (%)100.0%

Sample

1st row3170000-106-1969-00265
2nd row3170000-106-1982-00230
3rd row3170000-106-1985-00264
4th row3170000-106-1986-00243
5th row3170000-106-1987-00251
ValueCountFrequency (%)
3170000-106-1969-00265 1
 
0.2%
3170000-106-2013-00003 1
 
0.2%
3170000-106-2014-00003 1
 
0.2%
3170000-106-2014-00002 1
 
0.2%
3170000-106-2014-00001 1
 
0.2%
3170000-106-2013-00013 1
 
0.2%
3170000-106-2013-00012 1
 
0.2%
3170000-106-2013-00011 1
 
0.2%
3170000-106-2013-00010 1
 
0.2%
3170000-106-2013-00009 1
 
0.2%
Other values (455) 455
97.8%
2024-04-18T01:34:34.726703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4505
44.0%
1 1450
 
14.2%
- 1395
 
13.6%
2 637
 
6.2%
3 591
 
5.8%
6 568
 
5.6%
7 545
 
5.3%
9 238
 
2.3%
4 107
 
1.0%
8 101
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8835
86.4%
Dash Punctuation 1395
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4505
51.0%
1 1450
 
16.4%
2 637
 
7.2%
3 591
 
6.7%
6 568
 
6.4%
7 545
 
6.2%
9 238
 
2.7%
4 107
 
1.2%
8 101
 
1.1%
5 93
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1395
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4505
44.0%
1 1450
 
14.2%
- 1395
 
13.6%
2 637
 
6.2%
3 591
 
5.8%
6 568
 
5.6%
7 545
 
5.3%
9 238
 
2.3%
4 107
 
1.0%
8 101
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4505
44.0%
1 1450
 
14.2%
- 1395
 
13.6%
2 637
 
6.2%
3 591
 
5.8%
6 568
 
5.6%
7 545
 
5.3%
9 238
 
2.3%
4 107
 
1.0%
8 101
 
1.0%
Distinct435
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1969-12-04 00:00:00
Maximum2024-02-19 00:00:00
2024-04-18T01:34:34.838887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:34:34.949524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
371 
1
94 

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 (%)
3 371
79.8%
1 94
 
20.2%

Length

2024-04-18T01:34:35.047734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:35.325377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 371
79.8%
1 94
 
20.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
371 
영업/정상
94 

Length

Max length5
Median length2
Mean length2.6064516
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 371
79.8%
영업/정상 94
 
20.2%

Length

2024-04-18T01:34:35.402975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:35.480474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 371
79.8%
영업/정상 94
 
20.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
371 
1
94 

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 (%)
2 371
79.8%
1 94
 
20.2%

Length

2024-04-18T01:34:35.550956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:35.615987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 371
79.8%
1 94
 
20.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
371 
영업
94 

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 371
79.8%
영업 94
 
20.2%

Length

2024-04-18T01:34:35.687750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:35.754104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 371
79.8%
영업 94
 
20.2%

폐업일자
Date

MISSING 

Distinct338
Distinct (%)91.1%
Missing94
Missing (%)20.2%
Memory size3.8 KiB
Minimum1991-02-02 00:00:00
Maximum2024-04-04 00:00:00
2024-04-18T01:34:35.834809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:34:35.937037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct291
Distinct (%)93.3%
Missing153
Missing (%)32.9%
Memory size3.8 KiB
2024-04-18T01:34:36.148453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.128205
Min length2

Characters and Unicode

Total characters3160
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

Unique281 ?
Unique (%)90.1%

Sample

1st row02 8676161
2nd row02 8558442
3rd row02 8534408
4th row02 8664119
5th row02 8028773
ValueCountFrequency (%)
02 233
38.4%
070 15
 
2.5%
858 5
 
0.8%
8948080 3
 
0.5%
804 3
 
0.5%
868 3
 
0.5%
803 3
 
0.5%
855 3
 
0.5%
8950744 2
 
0.3%
8940167 2
 
0.3%
Other values (321) 335
55.2%
2024-04-18T01:34:36.472505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 582
18.4%
2 434
13.7%
8 407
12.9%
400
12.7%
3 214
 
6.8%
5 204
 
6.5%
9 190
 
6.0%
4 188
 
5.9%
7 186
 
5.9%
6 185
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2760
87.3%
Space Separator 400
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 582
21.1%
2 434
15.7%
8 407
14.7%
3 214
 
7.8%
5 204
 
7.4%
9 190
 
6.9%
4 188
 
6.8%
7 186
 
6.7%
6 185
 
6.7%
1 170
 
6.2%
Space Separator
ValueCountFrequency (%)
400
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 582
18.4%
2 434
13.7%
8 407
12.9%
400
12.7%
3 214
 
6.8%
5 204
 
6.5%
9 190
 
6.0%
4 188
 
5.9%
7 186
 
5.9%
6 185
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 582
18.4%
2 434
13.7%
8 407
12.9%
400
12.7%
3 214
 
6.8%
5 204
 
6.5%
9 190
 
6.0%
4 188
 
5.9%
7 186
 
5.9%
6 185
 
5.9%

소재지면적
Text

MISSING 

Distinct408
Distinct (%)93.4%
Missing28
Missing (%)6.0%
Memory size3.8 KiB
2024-04-18T01:34:36.756976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.4759725
Min length3

Characters and Unicode

Total characters2393
Distinct characters12
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

Unique384 ?
Unique (%)87.9%

Sample

1st row548.56
2nd row134.46
3rd row264.67
4th row174.20
5th row161.34
ValueCountFrequency (%)
00 5
 
1.1%
132.00 3
 
0.7%
927.40 3
 
0.7%
416.38 2
 
0.5%
120.91 2
 
0.5%
168.50 2
 
0.5%
119.31 2
 
0.5%
208.60 2
 
0.5%
21.70 2
 
0.5%
134.30 2
 
0.5%
Other values (398) 412
94.3%
2024-04-18T01:34:37.140542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 437
18.3%
0 292
12.2%
1 276
11.5%
2 240
10.0%
3 209
8.7%
4 184
7.7%
6 174
 
7.3%
7 155
 
6.5%
8 151
 
6.3%
5 142
 
5.9%
Other values (2) 133
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1955
81.7%
Other Punctuation 438
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 292
14.9%
1 276
14.1%
2 240
12.3%
3 209
10.7%
4 184
9.4%
6 174
8.9%
7 155
7.9%
8 151
7.7%
5 142
7.3%
9 132
6.8%
Other Punctuation
ValueCountFrequency (%)
. 437
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2393
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 437
18.3%
0 292
12.2%
1 276
11.5%
2 240
10.0%
3 209
8.7%
4 184
7.7%
6 174
 
7.3%
7 155
 
6.5%
8 151
 
6.3%
5 142
 
5.9%
Other values (2) 133
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 437
18.3%
0 292
12.2%
1 276
11.5%
2 240
10.0%
3 209
8.7%
4 184
7.7%
6 174
 
7.3%
7 155
 
6.5%
8 151
 
6.3%
5 142
 
5.9%
Other values (2) 133
 
5.6%
Distinct72
Distinct (%)15.5%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-04-18T01:34:37.328796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0948276
Min length6

Characters and Unicode

Total characters2828
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

Unique31 ?
Unique (%)6.7%

Sample

1st row153801
2nd row153812
3rd row153803
4th row153813
5th row153829
ValueCountFrequency (%)
153803 87
18.8%
153801 51
 
11.0%
153802 43
 
9.3%
153813 34
 
7.3%
153829 17
 
3.7%
153814 17
 
3.7%
153-803 14
 
3.0%
153861 12
 
2.6%
153825 10
 
2.2%
153-802 10
 
2.2%
Other values (62) 169
36.4%
2024-04-18T01:34:37.601834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 647
22.9%
1 618
21.9%
5 512
18.1%
8 462
16.3%
0 254
 
9.0%
2 103
 
3.6%
6 77
 
2.7%
- 44
 
1.6%
7 43
 
1.5%
4 39
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2784
98.4%
Dash Punctuation 44
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 647
23.2%
1 618
22.2%
5 512
18.4%
8 462
16.6%
0 254
 
9.1%
2 103
 
3.7%
6 77
 
2.8%
7 43
 
1.5%
4 39
 
1.4%
9 29
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 647
22.9%
1 618
21.9%
5 512
18.1%
8 462
16.3%
0 254
 
9.0%
2 103
 
3.6%
6 77
 
2.7%
- 44
 
1.6%
7 43
 
1.5%
4 39
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 647
22.9%
1 618
21.9%
5 512
18.1%
8 462
16.3%
0 254
 
9.0%
2 103
 
3.6%
6 77
 
2.7%
- 44
 
1.6%
7 43
 
1.5%
4 39
 
1.4%
Distinct420
Distinct (%)90.5%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-04-18T01:34:37.799656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length29.411638
Min length18

Characters and Unicode

Total characters13647
Distinct characters219
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

Unique386 ?
Unique (%)83.2%

Sample

1st row서울특별시 금천구 가산동 234-42번지 [사당길 11]
2nd row서울특별시 금천구 독산동 289-3번지
3rd row서울특별시 금천구 가산동 664-0번지
4th row서울특별시 금천구 독산동 297-6번지
5th row서울특별시 금천구 독산동 1006-185번지
ValueCountFrequency (%)
금천구 465
19.4%
서울특별시 464
19.3%
가산동 233
 
9.7%
독산동 144
 
6.0%
시흥동 87
 
3.6%
지상1층 18
 
0.8%
지하1층 18
 
0.8%
지상2층 15
 
0.6%
1층 13
 
0.5%
336-8번지 11
 
0.5%
Other values (653) 931
38.8%
2024-04-18T01:34:38.110496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2297
 
16.8%
1 565
 
4.1%
562
 
4.1%
502
 
3.7%
475
 
3.5%
469
 
3.4%
469
 
3.4%
467
 
3.4%
466
 
3.4%
465
 
3.4%
Other values (209) 6910
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7644
56.0%
Decimal Number 2858
 
20.9%
Space Separator 2297
 
16.8%
Dash Punctuation 445
 
3.3%
Close Punctuation 139
 
1.0%
Open Punctuation 139
 
1.0%
Uppercase Letter 81
 
0.6%
Other Punctuation 37
 
0.3%
Math Symbol 6
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
562
 
7.4%
502
 
6.6%
475
 
6.2%
469
 
6.1%
469
 
6.1%
467
 
6.1%
466
 
6.1%
465
 
6.1%
464
 
6.1%
464
 
6.1%
Other values (179) 2841
37.2%
Decimal Number
ValueCountFrequency (%)
1 565
19.8%
3 355
12.4%
2 336
11.8%
0 318
11.1%
4 281
9.8%
5 257
9.0%
9 236
8.3%
8 181
 
6.3%
6 173
 
6.1%
7 156
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 30
37.0%
T 10
 
12.3%
K 9
 
11.1%
S 9
 
11.1%
I 9
 
11.1%
A 6
 
7.4%
C 6
 
7.4%
X 1
 
1.2%
V 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 32
86.5%
/ 4
 
10.8%
: 1
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 73
52.5%
] 66
47.5%
Open Punctuation
ValueCountFrequency (%)
( 73
52.5%
[ 66
47.5%
Space Separator
ValueCountFrequency (%)
2297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 445
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7644
56.0%
Common 5921
43.4%
Latin 82
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
562
 
7.4%
502
 
6.6%
475
 
6.2%
469
 
6.1%
469
 
6.1%
467
 
6.1%
466
 
6.1%
465
 
6.1%
464
 
6.1%
464
 
6.1%
Other values (179) 2841
37.2%
Common
ValueCountFrequency (%)
2297
38.8%
1 565
 
9.5%
- 445
 
7.5%
3 355
 
6.0%
2 336
 
5.7%
0 318
 
5.4%
4 281
 
4.7%
5 257
 
4.3%
9 236
 
4.0%
8 181
 
3.1%
Other values (10) 650
 
11.0%
Latin
ValueCountFrequency (%)
B 30
36.6%
T 10
 
12.2%
K 9
 
11.0%
S 9
 
11.0%
I 9
 
11.0%
A 6
 
7.3%
C 6
 
7.3%
c 1
 
1.2%
X 1
 
1.2%
V 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7644
56.0%
ASCII 6003
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2297
38.3%
1 565
 
9.4%
- 445
 
7.4%
3 355
 
5.9%
2 336
 
5.6%
0 318
 
5.3%
4 281
 
4.7%
5 257
 
4.3%
9 236
 
3.9%
8 181
 
3.0%
Other values (20) 732
 
12.2%
Hangul
ValueCountFrequency (%)
562
 
7.4%
502
 
6.6%
475
 
6.2%
469
 
6.1%
469
 
6.1%
467
 
6.1%
466
 
6.1%
465
 
6.1%
464
 
6.1%
464
 
6.1%
Other values (179) 2841
37.2%

도로명주소
Text

MISSING 

Distinct249
Distinct (%)97.3%
Missing209
Missing (%)44.9%
Memory size3.8 KiB
2024-04-18T01:34:38.324985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length54
Mean length40.230469
Min length24

Characters and Unicode

Total characters10299
Distinct characters197
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

Unique242 ?
Unique (%)94.5%

Sample

1st row서울특별시 금천구 벚꽃로56길 66 (가산동,[순환샛길 58])
2nd row서울특별시 금천구 범안로19길 11 (독산동)
3rd row서울특별시 금천구 범안로11길 61, 1층 (독산동)
4th row서울특별시 금천구 독산로35길 15-7 (시흥동,[방죽길 17])
5th row서울특별시 금천구 독산로64길 34 (독산동,[정훈1길 34])
ValueCountFrequency (%)
서울특별시 256
 
14.2%
금천구 256
 
14.2%
가산동 152
 
8.4%
가산디지털1로 62
 
3.4%
독산동 48
 
2.7%
가산디지털2로 39
 
2.2%
지하1층 27
 
1.5%
1층 24
 
1.3%
시흥동 24
 
1.3%
벚꽃로 20
 
1.1%
Other values (493) 898
49.7%
2024-04-18T01:34:38.651289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1551
 
15.1%
1 550
 
5.3%
400
 
3.9%
, 346
 
3.4%
329
 
3.2%
297
 
2.9%
282
 
2.7%
277
 
2.7%
) 274
 
2.7%
( 274
 
2.7%
Other values (187) 5719
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5767
56.0%
Decimal Number 1858
 
18.0%
Space Separator 1551
 
15.1%
Other Punctuation 351
 
3.4%
Close Punctuation 291
 
2.8%
Open Punctuation 291
 
2.8%
Uppercase Letter 122
 
1.2%
Dash Punctuation 58
 
0.6%
Math Symbol 9
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
400
 
6.9%
329
 
5.7%
297
 
5.1%
282
 
4.9%
277
 
4.8%
262
 
4.5%
257
 
4.5%
257
 
4.5%
256
 
4.4%
256
 
4.4%
Other values (156) 2894
50.2%
Decimal Number
ValueCountFrequency (%)
1 550
29.6%
2 245
13.2%
0 221
11.9%
4 151
 
8.1%
3 149
 
8.0%
8 130
 
7.0%
5 123
 
6.6%
6 116
 
6.2%
9 87
 
4.7%
7 86
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 59
48.4%
K 15
 
12.3%
S 15
 
12.3%
T 11
 
9.0%
I 10
 
8.2%
C 4
 
3.3%
A 4
 
3.3%
F 2
 
1.6%
X 1
 
0.8%
V 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 346
98.6%
/ 4
 
1.1%
: 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 274
94.2%
] 17
 
5.8%
Open Punctuation
ValueCountFrequency (%)
( 274
94.2%
[ 17
 
5.8%
Space Separator
ValueCountFrequency (%)
1551
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5767
56.0%
Common 4409
42.8%
Latin 123
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
400
 
6.9%
329
 
5.7%
297
 
5.1%
282
 
4.9%
277
 
4.8%
262
 
4.5%
257
 
4.5%
257
 
4.5%
256
 
4.4%
256
 
4.4%
Other values (156) 2894
50.2%
Common
ValueCountFrequency (%)
1551
35.2%
1 550
 
12.5%
, 346
 
7.8%
) 274
 
6.2%
( 274
 
6.2%
2 245
 
5.6%
0 221
 
5.0%
4 151
 
3.4%
3 149
 
3.4%
8 130
 
2.9%
Other values (10) 518
 
11.7%
Latin
ValueCountFrequency (%)
B 59
48.0%
K 15
 
12.2%
S 15
 
12.2%
T 11
 
8.9%
I 10
 
8.1%
C 4
 
3.3%
A 4
 
3.3%
F 2
 
1.6%
b 1
 
0.8%
X 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5767
56.0%
ASCII 4532
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1551
34.2%
1 550
 
12.1%
, 346
 
7.6%
) 274
 
6.0%
( 274
 
6.0%
2 245
 
5.4%
0 221
 
4.9%
4 151
 
3.3%
3 149
 
3.3%
8 130
 
2.9%
Other values (21) 641
14.1%
Hangul
ValueCountFrequency (%)
400
 
6.9%
329
 
5.7%
297
 
5.1%
282
 
4.9%
277
 
4.8%
262
 
4.5%
257
 
4.5%
257
 
4.5%
256
 
4.4%
256
 
4.4%
Other values (156) 2894
50.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)29.5%
Missing211
Missing (%)45.4%
Infinite0
Infinite (%)0.0%
Mean8559.4016
Minimum8500
Maximum8654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-18T01:34:38.756822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8500
5-th percentile8501
Q18511
median8582
Q38592
95-th percentile8639
Maximum8654
Range154
Interquartile range (IQR)81

Descriptive statistics

Standard deviation47.106181
Coefficient of variation (CV)0.0055034432
Kurtosis-1.2808497
Mean8559.4016
Median Absolute Deviation (MAD)52
Skewness0.17656402
Sum2174088
Variance2218.9923
MonotonicityNot monotonic
2024-04-18T01:34:38.868556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8589 21
 
4.5%
8504 17
 
3.7%
8501 14
 
3.0%
8592 13
 
2.8%
8594 13
 
2.8%
8506 11
 
2.4%
8513 10
 
2.2%
8590 8
 
1.7%
8503 6
 
1.3%
8588 6
 
1.3%
Other values (65) 135
29.0%
(Missing) 211
45.4%
ValueCountFrequency (%)
8500 2
 
0.4%
8501 14
3.0%
8502 4
 
0.9%
8503 6
 
1.3%
8504 17
3.7%
8505 1
 
0.2%
8506 11
2.4%
8507 3
 
0.6%
8509 1
 
0.2%
8510 3
 
0.6%
ValueCountFrequency (%)
8654 2
 
0.4%
8652 5
1.1%
8649 3
0.6%
8644 1
 
0.2%
8639 4
0.9%
8638 2
 
0.4%
8637 1
 
0.2%
8635 2
 
0.4%
8634 1
 
0.2%
8632 2
 
0.4%
Distinct438
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-04-18T01:34:39.057178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length21
Mean length6.7311828
Min length2

Characters and Unicode

Total characters3130
Distinct characters426
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique417 ?
Unique (%)89.7%

Sample

1st row영진식품
2nd row한국맛김
3rd row영상산업(주)
4th row한빛농산
5th row세계식품
ValueCountFrequency (%)
주식회사 28
 
5.1%
영진식품 3
 
0.5%
엔와이푸드 3
 
0.5%
이레식품 3
 
0.5%
food 3
 
0.5%
2공장 3
 
0.5%
농업회사법인 3
 
0.5%
주)달라스 3
 
0.5%
주)본야록 3
 
0.5%
레드파이 3
 
0.5%
Other values (471) 496
90.0%
2024-04-18T01:34:39.349726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
 
5.3%
( 146
 
4.7%
) 146
 
4.7%
135
 
4.3%
103
 
3.3%
86
 
2.7%
84
 
2.7%
65
 
2.1%
61
 
1.9%
48
 
1.5%
Other values (416) 2091
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2603
83.2%
Open Punctuation 146
 
4.7%
Close Punctuation 146
 
4.7%
Space Separator 86
 
2.7%
Uppercase Letter 77
 
2.5%
Lowercase Letter 45
 
1.4%
Decimal Number 18
 
0.6%
Other Punctuation 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
165
 
6.3%
135
 
5.2%
103
 
4.0%
84
 
3.2%
65
 
2.5%
61
 
2.3%
48
 
1.8%
46
 
1.8%
44
 
1.7%
37
 
1.4%
Other values (369) 1815
69.7%
Uppercase Letter
ValueCountFrequency (%)
B 10
13.0%
O 9
11.7%
C 9
11.7%
F 9
11.7%
E 4
 
5.2%
M 4
 
5.2%
I 3
 
3.9%
K 3
 
3.9%
D 3
 
3.9%
S 3
 
3.9%
Other values (11) 20
26.0%
Lowercase Letter
ValueCountFrequency (%)
o 6
13.3%
t 5
11.1%
n 4
8.9%
s 4
8.9%
e 4
8.9%
r 4
8.9%
u 4
8.9%
a 3
6.7%
i 3
6.7%
g 2
 
4.4%
Other values (4) 6
13.3%
Decimal Number
ValueCountFrequency (%)
1 7
38.9%
2 4
22.2%
3 3
16.7%
0 2
 
11.1%
4 1
 
5.6%
5 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
& 7
77.8%
' 1
 
11.1%
? 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 146
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2601
83.1%
Common 405
 
12.9%
Latin 122
 
3.9%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
165
 
6.3%
135
 
5.2%
103
 
4.0%
84
 
3.2%
65
 
2.5%
61
 
2.3%
48
 
1.8%
46
 
1.8%
44
 
1.7%
37
 
1.4%
Other values (367) 1813
69.7%
Latin
ValueCountFrequency (%)
B 10
 
8.2%
O 9
 
7.4%
C 9
 
7.4%
F 9
 
7.4%
o 6
 
4.9%
t 5
 
4.1%
E 4
 
3.3%
n 4
 
3.3%
s 4
 
3.3%
e 4
 
3.3%
Other values (25) 58
47.5%
Common
ValueCountFrequency (%)
( 146
36.0%
) 146
36.0%
86
21.2%
1 7
 
1.7%
& 7
 
1.7%
2 4
 
1.0%
3 3
 
0.7%
0 2
 
0.5%
' 1
 
0.2%
4 1
 
0.2%
Other values (2) 2
 
0.5%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2601
83.1%
ASCII 527
 
16.8%
CJK 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
165
 
6.3%
135
 
5.2%
103
 
4.0%
84
 
3.2%
65
 
2.5%
61
 
2.3%
48
 
1.8%
46
 
1.8%
44
 
1.7%
37
 
1.4%
Other values (367) 1813
69.7%
ASCII
ValueCountFrequency (%)
( 146
27.7%
) 146
27.7%
86
16.3%
B 10
 
1.9%
O 9
 
1.7%
C 9
 
1.7%
F 9
 
1.7%
1 7
 
1.3%
& 7
 
1.3%
o 6
 
1.1%
Other values (37) 92
17.5%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct423
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1999-07-16 00:00:00
Maximum2024-04-11 16:26:32
2024-04-18T01:34:39.453567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:34:39.568328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
333 
U
132 

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 333
71.6%
U 132
 
28.4%

Length

2024-04-18T01:34:39.700356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:39.787850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 333
71.6%
u 132
 
28.4%
Distinct158
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-18T01:34:39.862354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:34:39.965043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식품제조가공업
333 
기타 식품제조가공업
131 
도시락제조업
 
1

Length

Max length10
Median length7
Mean length7.8430108
Min length6

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 333
71.6%
기타 식품제조가공업 131
 
28.2%
도시락제조업 1
 
0.2%

Length

2024-04-18T01:34:40.071117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:40.147772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 464
77.9%
기타 131
 
22.0%
도시락제조업 1
 
0.2%

좌표정보(X)
Real number (ℝ)

Distinct281
Distinct (%)60.7%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean190315.46
Minimum188830.03
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-18T01:34:40.230250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188830.03
5-th percentile189089.93
Q1189575.82
median190187.53
Q3191086.69
95-th percentile191663.57
Maximum192754.35
Range3924.316
Interquartile range (IQR)1510.872

Descriptive statistics

Standard deviation844.90338
Coefficient of variation (CV)0.004439489
Kurtosis-0.96263114
Mean190315.46
Median Absolute Deviation (MAD)663.0715
Skewness0.27531835
Sum88116056
Variance713861.72
MonotonicityNot monotonic
2024-04-18T01:34:40.336284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189575.815287955 14
 
3.0%
190081.372341474 11
 
2.4%
189369.53962474 11
 
2.4%
189127.981104583 9
 
1.9%
191226.287379467 8
 
1.7%
191433.007119534 7
 
1.5%
188968.189711073 7
 
1.5%
189089.927764903 6
 
1.3%
189450.60600488 6
 
1.3%
189561.360525634 6
 
1.3%
Other values (271) 378
81.3%
ValueCountFrequency (%)
188830.030176986 1
 
0.2%
188968.189711073 7
1.5%
188979.225789508 6
1.3%
188981.555267121 1
 
0.2%
188989.54677536 1
 
0.2%
189030.107416961 1
 
0.2%
189055.138252216 4
0.9%
189065.818334596 1
 
0.2%
189089.927764903 6
1.3%
189092.729912585 1
 
0.2%
ValueCountFrequency (%)
192754.34619252 1
0.2%
192343.982564036 1
0.2%
192140.313893951 1
0.2%
192121.520553079 1
0.2%
192110.050795719 2
0.4%
192019.006237946 1
0.2%
192015.491677364 1
0.2%
191979.00948806 1
0.2%
191919.012705941 1
0.2%
191895.615705345 1
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct281
Distinct (%)60.7%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean440774.88
Minimum436946.36
Maximum442585.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-18T01:34:40.443825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436946.36
5-th percentile437949.33
Q1440368.16
median441070.24
Q3441629.36
95-th percentile442364.56
Maximum442585.93
Range5639.5745
Interquartile range (IQR)1261.1998

Descriptive statistics

Standard deviation1236.1272
Coefficient of variation (CV)0.0028044411
Kurtosis0.39293341
Mean440774.88
Median Absolute Deviation (MAD)636.83286
Skewness-0.99543333
Sum2.0407877 × 108
Variance1528010.4
MonotonicityNot monotonic
2024-04-18T01:34:40.542904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441503.181731081 14
 
3.0%
441019.186737744 11
 
2.4%
441629.361414684 11
 
2.4%
442460.505542105 9
 
1.9%
437914.06299827 8
 
1.7%
437607.039565128 7
 
1.5%
442119.780901928 7
 
1.5%
442569.300676147 6
 
1.3%
441142.645065053 6
 
1.3%
440925.40762197 6
 
1.3%
Other values (271) 378
81.3%
ValueCountFrequency (%)
436946.358720615 1
 
0.2%
436997.075839023 1
 
0.2%
437099.172901614 1
 
0.2%
437546.055336785 1
 
0.2%
437562.242368734 1
 
0.2%
437607.039565128 7
1.5%
437680.1128998 2
 
0.4%
437777.824339474 1
 
0.2%
437816.239800826 1
 
0.2%
437914.06299827 8
1.7%
ValueCountFrequency (%)
442585.933234852 1
 
0.2%
442569.300676147 6
1.3%
442538.866901281 1
 
0.2%
442497.377672482 1
 
0.2%
442493.020182986 1
 
0.2%
442478.356256941 1
 
0.2%
442460.505542105 9
1.9%
442417.955057116 2
 
0.4%
442382.690694868 1
 
0.2%
442367.500287732 1
 
0.2%

위생업태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식품제조가공업
324 
기타 식품제조가공업
77 
<NA>
64 

Length

Max length10
Median length7
Mean length7.083871
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 324
69.7%
기타 식품제조가공업 77
 
16.6%
<NA> 64
 
13.8%

Length

2024-04-18T01:34:40.639986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:40.719005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 401
74.0%
기타 77
 
14.2%
na 64
 
11.8%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
410 
0
 
40
1
 
7
2
 
6
7
 
1

Length

Max length4
Median length4
Mean length3.6451613
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 410
88.2%
0 40
 
8.6%
1 7
 
1.5%
2 6
 
1.3%
7 1
 
0.2%
5 1
 
0.2%

Length

2024-04-18T01:34:40.800485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:40.886558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
88.2%
0 40
 
8.6%
1 7
 
1.5%
2 6
 
1.3%
7 1
 
0.2%
5 1
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
410 
0
48 
1
 
5
3
 
2

Length

Max length4
Median length4
Mean length3.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 410
88.2%
0 48
 
10.3%
1 5
 
1.1%
3 2
 
0.4%

Length

2024-04-18T01:34:40.974239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:41.058978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
88.2%
0 48
 
10.3%
1 5
 
1.1%
3 2
 
0.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
396 
기타
45 
주택가주변
 
22
학교정화(상대)
 
2

Length

Max length8
Median length4
Mean length3.8709677
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row기타
3rd row학교정화(상대)
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 396
85.2%
기타 45
 
9.7%
주택가주변 22
 
4.7%
학교정화(상대) 2
 
0.4%

Length

2024-04-18T01:34:41.393892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:41.468187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 396
85.2%
기타 45
 
9.7%
주택가주변 22
 
4.7%
학교정화(상대 2
 
0.4%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
396 
자율
 
39
기타
 
29
 
1

Length

Max length4
Median length4
Mean length3.7010753
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 396
85.2%
자율 39
 
8.4%
기타 29
 
6.2%
1
 
0.2%

Length

2024-04-18T01:34:41.550556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:41.624576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 396
85.2%
자율 39
 
8.4%
기타 29
 
6.2%
1
 
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
318 
상수도전용
147 

Length

Max length5
Median length4
Mean length4.316129
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 318
68.4%
상수도전용 147
31.6%

Length

2024-04-18T01:34:41.720023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:41.807655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 318
68.4%
상수도전용 147
31.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
17

Length

Max length4
Median length4
Mean length3.8903226
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> 448
96.3%
0 17
 
3.7%

Length

2024-04-18T01:34:41.883606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:41.956342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
96.3%
0 17
 
3.7%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
237 
<NA>
225 
1
 
1
2
 
1
3
 
1

Length

Max length4
Median length1
Mean length2.4516129
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 237
51.0%
<NA> 225
48.4%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%

Length

2024-04-18T01:34:42.031041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:42.108697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 237
51.0%
na 225
48.4%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
237 
<NA>
224 
2
 
3
3
 
1

Length

Max length4
Median length1
Mean length2.4451613
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 237
51.0%
<NA> 224
48.2%
2 3
 
0.6%
3 1
 
0.2%

Length

2024-04-18T01:34:42.197284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:42.273327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 237
51.0%
na 224
48.2%
2 3
 
0.6%
3 1
 
0.2%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
239 
<NA>
225 
3
 
1

Length

Max length4
Median length1
Mean length2.4516129
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 239
51.4%
<NA> 225
48.4%
3 1
 
0.2%

Length

2024-04-18T01:34:42.356739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:42.432340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 239
51.4%
na 225
48.4%
3 1
 
0.2%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.3%
Missing223
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean0.25206612
Minimum0
Maximum20
Zeros232
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-18T01:34:42.500347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6989428
Coefficient of variation (CV)6.740068
Kurtosis89.583536
Mean0.25206612
Median Absolute Deviation (MAD)0
Skewness8.9527081
Sum61
Variance2.8864065
MonotonicityNot monotonic
2024-04-18T01:34:42.582680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 232
49.9%
2 3
 
0.6%
3 2
 
0.4%
12 1
 
0.2%
20 1
 
0.2%
10 1
 
0.2%
6 1
 
0.2%
1 1
 
0.2%
(Missing) 223
48.0%
ValueCountFrequency (%)
0 232
49.9%
1 1
 
0.2%
2 3
 
0.6%
3 2
 
0.4%
6 1
 
0.2%
10 1
 
0.2%
12 1
 
0.2%
20 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
6 1
 
0.2%
3 2
 
0.4%
2 3
 
0.6%
1 1
 
0.2%
0 232
49.9%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
320 
자가
81 
임대
64 

Length

Max length4
Median length4
Mean length3.3763441
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> 320
68.8%
자가 81
 
17.4%
임대 64
 
13.8%

Length

2024-04-18T01:34:42.685945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:42.767099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 320
68.8%
자가 81
 
17.4%
임대 64
 
13.8%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
413 
0
50 
25000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.6946237
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
88.8%
0 50
 
10.8%
25000000 1
 
0.2%
10000000 1
 
0.2%

Length

2024-04-18T01:34:42.848768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:42.928827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
88.8%
0 50
 
10.8%
25000000 1
 
0.2%
10000000 1
 
0.2%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
413 
0
50 
1300000
 
1
200000
 
1

Length

Max length7
Median length4
Mean length3.688172
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 413
88.8%
0 50
 
10.8%
1300000 1
 
0.2%
200000 1
 
0.2%

Length

2024-04-18T01:34:43.011923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:34:43.109509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
88.8%
0 50
 
10.8%
1300000 1
 
0.2%
200000 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing64
Missing (%)13.8%
Memory size1.0 KiB
False
401 
(Missing)
64 
ValueCountFrequency (%)
False 401
86.2%
(Missing) 64
 
13.8%
2024-04-18T01:34:43.177158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct74
Distinct (%)18.5%
Missing64
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean15.269726
Minimum0
Maximum448.2
Zeros324
Zeros (%)69.7%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-18T01:34:43.261892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile98.46
Maximum448.2
Range448.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation50.286999
Coefficient of variation (CV)3.2932484
Kurtosis28.136511
Mean15.269726
Median Absolute Deviation (MAD)0
Skewness4.8562957
Sum6123.16
Variance2528.7823
MonotonicityNot monotonic
2024-04-18T01:34:43.364451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 324
69.7%
52.08 2
 
0.4%
21.07 2
 
0.4%
8.0 2
 
0.4%
156.26 2
 
0.4%
448.2 1
 
0.2%
9.9 1
 
0.2%
319.09 1
 
0.2%
8.96 1
 
0.2%
9.28 1
 
0.2%
Other values (64) 64
 
13.8%
(Missing) 64
 
13.8%
ValueCountFrequency (%)
0.0 324
69.7%
2.42 1
 
0.2%
3.3 1
 
0.2%
3.4 1
 
0.2%
3.6 1
 
0.2%
3.78 1
 
0.2%
6.08 1
 
0.2%
6.87 1
 
0.2%
8.0 2
 
0.4%
8.2 1
 
0.2%
ValueCountFrequency (%)
448.2 1
0.2%
368.02 1
0.2%
319.09 1
0.2%
283.25 1
0.2%
266.0 1
0.2%
252.14 1
0.2%
246.25 1
0.2%
175.54 1
0.2%
174.3 1
0.2%
167.34 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing465
Missing (%)100.0%
Memory size4.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031700003170000-106-1969-0026519691204<NA>3폐업2폐업20120208<NA><NA><NA>02 8676161548.56153801서울특별시 금천구 가산동 234-42번지 [사당길 11]<NA><NA>영진식품2008-05-07 11:03:24I2018-08-31 23:59:59.0식품제조가공업190521.187976441254.625991식품제조가공업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131700003170000-106-1982-0023019820614<NA>3폐업2폐업20040813<NA><NA><NA>02 8558442134.46153812서울특별시 금천구 독산동 289-3번지<NA><NA>한국맛김2004-07-06 00:00:00I2018-08-31 23:59:59.0식품제조가공업190807.871691440910.292313식품제조가공업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231700003170000-106-1985-0026419851227<NA>3폐업2폐업19970917<NA><NA><NA>02 8534408264.67153803서울특별시 금천구 가산동 664-0번지<NA><NA>영상산업(주)2002-01-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업189991.650798440695.614056식품제조가공업<NA><NA>학교정화(상대)기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331700003170000-106-1986-0024319861215<NA>3폐업2폐업20030219<NA><NA><NA>02 8664119174.20153813서울특별시 금천구 독산동 297-6번지<NA><NA>한빛농산2001-04-12 00:00:00I2018-08-31 23:59:59.0식품제조가공업190637.122653441212.744529식품제조가공업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431700003170000-106-1987-0025119870704<NA>3폐업2폐업20050414<NA><NA><NA>02 8028773161.34153829서울특별시 금천구 독산동 1006-185번지<NA><NA>세계식품2002-01-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업190434.661111440331.683029식품제조가공업<NA><NA>기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531700003170000-106-1989-0022519890728<NA>3폐업2폐업20000207<NA><NA><NA>02 896234584.70153841서울특별시 금천구 시흥동 219-2번지<NA><NA>일미외식산업(주)2002-01-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업192110.050796438972.444015식품제조가공업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631700003170000-106-1990-0023519900226<NA>1영업/정상1영업<NA><NA><NA><NA>02 858 5236160.17153800서울특별시 금천구 가산동 29-32번지 지하1층서울특별시 금천구 벚꽃로56길 66 (가산동,[순환샛길 58])8509J?A FOOD2019-03-11 13:21:20U2019-03-13 02:40:00.0기타 식품제조가공업189675.037841442367.500288기타 식품제조가공업<NA><NA>기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
731700003170000-106-1991-0022919910202<NA>3폐업2폐업19910202<NA><NA><NA>02 8948080927.40153829서울특별시 금천구 독산동 1003-32번지<NA><NA>(주)달라스2002-01-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업190253.060027440407.199599식품제조가공업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831700003170000-106-1991-0023919910202<NA>3폐업2폐업19980211<NA><NA><NA>02 8948080927.40153829서울특별시 금천구 독산동 1003-32번지<NA><NA>(주)달라스2002-01-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업190253.060027440407.199599식품제조가공업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931700003170000-106-1991-0024819910202<NA>3폐업2폐업19910202<NA><NA><NA>02 8948080927.40153829서울특별시 금천구 독산동 1003-32번지<NA><NA>(주)달라스2002-01-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업190253.060027440407.199599식품제조가공업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
45531700003170000-106-2023-000082023-08-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.44153-864서울특별시 금천구 시흥동 991-5서울특별시 금천구 시흥대로 189, 4층 401호 (시흥동)8635MC홀딩스2023-08-03 11:29:52I2022-12-08 00:05:00.0기타 식품제조가공업191231.71641438732.994399<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45631700003170000-106-2023-000092023-08-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>116.24153-803서울특별시 금천구 가산동 691 대륭테크노타운 20차서울특별시 금천구 가산디지털1로 5, 대륭테크노타운 20차 지하1층 B105호 (가산동)8594킹스베이커리2024-03-13 14:56:48U2023-12-02 23:06:00.0기타 식품제조가공업189920.528611440521.855249<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45731700003170000-106-2023-000102023-08-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>132.00153-802서울특별시 금천구 가산동 327-32 대륭테크노타운12차서울특별시 금천구 가산디지털2로 14, 대륭테크노타운12차 6층 603호 (가산동)8592주식회사 회성바이오2023-08-22 12:37:28I2022-12-07 22:04:00.0기타 식품제조가공업189686.475440870.092609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45831700003170000-106-2023-000112023-08-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>79.33153-802서울특별시 금천구 가산동 345-50 IT프리미어타워서울특별시 금천구 가산디지털1로 88, IT프리미어타워 5층 502-1호 (가산동)8590주식회사 연경당2023-08-28 09:40:21I2022-12-07 21:00:00.0기타 식품제조가공업189778.774505441302.111937<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45931700003170000-106-2023-000122023-09-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.36153-863서울특별시 금천구 시흥동 985 한영상가서울특별시 금천구 시흥대로39길 16, 한영상가 1층 9~10호 (시흥동)8638에이치 에프앤비(H F&B)2023-09-06 09:16:00I2022-12-09 00:08:00.0기타 식품제조가공업191266.732178438395.806834<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46031700003170000-106-2023-000132023-11-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.59153-803서울특별시 금천구 가산동 459-7서울특별시 금천구 가산디지털1로 205-27, 2층 207호 (가산동)8503디어푸르츠2024-03-05 11:43:01U2023-12-03 00:07:00.0기타 식품제조가공업189208.487614442298.78442<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46131700003170000-106-2023-000142023-12-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.85153-801서울특별시 금천구 가산동 60-73 벽산디지털밸리5차서울특별시 금천구 벚꽃로 244, 벽산디지털밸리5차 5층 512호 (가산동)8513클로버 에프엔비2023-12-22 14:17:02I2022-11-01 22:04:00.0기타 식품제조가공업189829.504143441618.071647<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46231700003170000-106-2024-000012024-01-05<NA>3폐업2폐업2024-02-02<NA><NA><NA><NA>842.37153-705서울특별시 금천구 가산동 533 롯데정보통신서울특별시 금천구 가산디지털2로 187, 롯데정보통신 1층(일부)호 (가산동)8500그린나래2024-02-02 09:19:25U2023-12-02 00:04:00.0기타 식품제조가공업188981.555267442497.377672<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46331700003170000-106-2024-000022024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>128.20153-803서울특별시 금천구 가산동 470-5 에이스테크노타워10차서울특별시 금천구 가산디지털1로 196, 에이스테크노타워10차 809호 (가산동)8502업셋(UPSET)2024-01-19 13:08:38I2023-11-30 22:01:00.0기타 식품제조가공업189417.708596442309.174988<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46431700003170000-106-2024-000032024-02-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>101.64153-803서울특별시 금천구 가산동 459-29 에이스 K1타워서울특별시 금천구 가산디지털2로 166, 에이스 K1타워 B105호 (가산동)8503주식회사 버쉘2024-02-19 12:05:53I2023-12-01 22:01:00.0기타 식품제조가공업189158.740846442283.977343<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>