Overview

Dataset statistics

Number of variables44
Number of observations466
Missing cells4317
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.8 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 (61.8%)Imbalance
등급구분명 is highly imbalanced (61.8%)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 466 (100.0%) missing valuesMissing
폐업일자 has 94 (20.2%) missing valuesMissing
휴업시작일자 has 466 (100.0%) missing valuesMissing
휴업종료일자 has 466 (100.0%) missing valuesMissing
재개업일자 has 466 (100.0%) missing valuesMissing
전화번호 has 153 (32.8%) missing valuesMissing
소재지면적 has 28 (6.0%) missing valuesMissing
도로명주소 has 209 (44.8%) missing valuesMissing
도로명우편번호 has 211 (45.3%) missing valuesMissing
공장생산직종업원수 has 224 (48.1%) missing valuesMissing
다중이용업소여부 has 65 (13.9%) missing valuesMissing
시설총규모 has 65 (13.9%) missing valuesMissing
전통업소지정번호 has 466 (100.0%) missing valuesMissing
전통업소주된음식 has 466 (100.0%) missing valuesMissing
홈페이지 has 466 (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 (49.8%) zerosZeros
시설총규모 has 324 (69.5%) zerosZeros

Reproduction

Analysis started2024-05-17 23:19:39.151090
Analysis finished2024-05-17 23:19:41.168097
Duration2.02 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
466 

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 466
100.0%

Length

2024-05-18T08:19:41.459733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:19:41.800289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 466
100.0%

관리번호
Text

UNIQUE 

Distinct466
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-18T08:19:42.315550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10252
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

Unique466 ?
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%
3170000-106-2016-00002 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%
3170000-106-2013-00008 1
 
0.2%
Other values (456) 456
97.9%
2024-05-18T08:19:43.225584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4515
44.0%
1 1452
 
14.2%
- 1398
 
13.6%
2 639
 
6.2%
3 592
 
5.8%
6 569
 
5.6%
7 546
 
5.3%
9 238
 
2.3%
4 109
 
1.1%
8 101
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8854
86.4%
Dash Punctuation 1398
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4515
51.0%
1 1452
 
16.4%
2 639
 
7.2%
3 592
 
6.7%
6 569
 
6.4%
7 546
 
6.2%
9 238
 
2.7%
4 109
 
1.2%
8 101
 
1.1%
5 93
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1398
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4515
44.0%
1 1452
 
14.2%
- 1398
 
13.6%
2 639
 
6.2%
3 592
 
5.8%
6 569
 
5.6%
7 546
 
5.3%
9 238
 
2.3%
4 109
 
1.1%
8 101
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4515
44.0%
1 1452
 
14.2%
- 1398
 
13.6%
2 639
 
6.2%
3 592
 
5.8%
6 569
 
5.6%
7 546
 
5.3%
9 238
 
2.3%
4 109
 
1.1%
8 101
 
1.0%
Distinct436
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1969-12-04 00:00:00
Maximum2024-05-10 00:00:00
2024-05-18T08:19:43.774006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:19:44.299329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing466
Missing (%)100.0%
Memory size4.2 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
372 
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 (%)
3 372
79.8%
1 94
 
20.2%

Length

2024-05-18T08:19:44.866004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:19:45.134410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 372
79.8%
1 94
 
20.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
372 
영업/정상
94 

Length

Max length5
Median length2
Mean length2.6051502
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 372
79.8%
영업/정상 94
 
20.2%

Length

2024-05-18T08:19:45.446791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:19:45.736423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 372
79.8%
영업/정상 94
 
20.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
372 
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 (%)
2 372
79.8%
1 94
 
20.2%

Length

2024-05-18T08:19:46.031280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:19:46.294848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 372
79.8%
1 94
 
20.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
372 
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 372
79.8%
영업 94
 
20.2%

Length

2024-05-18T08:19:46.741107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:19:47.155328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 372
79.8%
영업 94
 
20.2%

폐업일자
Date

MISSING 

Distinct339
Distinct (%)91.1%
Missing94
Missing (%)20.2%
Memory size3.8 KiB
Minimum1991-02-02 00:00:00
Maximum2024-05-07 00:00:00
2024-05-18T08:19:47.522157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:19:48.037864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing466
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing466
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing466
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct292
Distinct (%)93.3%
Missing153
Missing (%)32.8%
Memory size3.8 KiB
2024-05-18T08:19:48.903799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.134185
Min length2

Characters and Unicode

Total characters3172
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

Unique282 ?
Unique (%)90.1%

Sample

1st row02 8676161
2nd row02 8558442
3rd row02 8534408
4th row02 8664119
5th row02 8028773
ValueCountFrequency (%)
02 234
38.4%
070 15
 
2.5%
858 5
 
0.8%
804 3
 
0.5%
855 3
 
0.5%
8948080 3
 
0.5%
803 3
 
0.5%
868 3
 
0.5%
839 2
 
0.3%
851 2
 
0.3%
Other values (322) 336
55.2%
2024-05-18T08:19:50.165796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 584
18.4%
2 437
13.8%
8 407
12.8%
403
12.7%
3 215
 
6.8%
5 204
 
6.4%
9 191
 
6.0%
4 188
 
5.9%
7 186
 
5.9%
6 186
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2769
87.3%
Space Separator 403
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 584
21.1%
2 437
15.8%
8 407
14.7%
3 215
 
7.8%
5 204
 
7.4%
9 191
 
6.9%
4 188
 
6.8%
7 186
 
6.7%
6 186
 
6.7%
1 171
 
6.2%
Space Separator
ValueCountFrequency (%)
403
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 584
18.4%
2 437
13.8%
8 407
12.8%
403
12.7%
3 215
 
6.8%
5 204
 
6.4%
9 191
 
6.0%
4 188
 
5.9%
7 186
 
5.9%
6 186
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 584
18.4%
2 437
13.8%
8 407
12.8%
403
12.7%
3 215
 
6.8%
5 204
 
6.4%
9 191
 
6.0%
4 188
 
5.9%
7 186
 
5.9%
6 186
 
5.9%

소재지면적
Text

MISSING 

Distinct409
Distinct (%)93.4%
Missing28
Missing (%)6.0%
Memory size3.8 KiB
2024-05-18T08:19:51.325113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.4771689
Min length3

Characters and Unicode

Total characters2399
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

Unique385 ?
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%
7.83 2
 
0.5%
134.30 2
 
0.5%
328.50 2
 
0.5%
412.50 2
 
0.5%
Other values (399) 413
94.3%
2024-05-18T08:19:52.935738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 438
18.3%
0 292
12.2%
1 276
11.5%
2 244
10.2%
3 208
8.7%
4 183
7.6%
6 174
 
7.3%
7 156
 
6.5%
8 150
 
6.3%
5 143
 
6.0%
Other values (2) 135
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1960
81.7%
Other Punctuation 439
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 292
14.9%
1 276
14.1%
2 244
12.4%
3 208
10.6%
4 183
9.3%
6 174
8.9%
7 156
8.0%
8 150
7.7%
5 143
7.3%
9 134
6.8%
Other Punctuation
ValueCountFrequency (%)
. 438
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2399
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 438
18.3%
0 292
12.2%
1 276
11.5%
2 244
10.2%
3 208
8.7%
4 183
7.6%
6 174
 
7.3%
7 156
 
6.5%
8 150
 
6.3%
5 143
 
6.0%
Other values (2) 135
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 438
18.3%
0 292
12.2%
1 276
11.5%
2 244
10.2%
3 208
8.7%
4 183
7.6%
6 174
 
7.3%
7 156
 
6.5%
8 150
 
6.3%
5 143
 
6.0%
Other values (2) 135
 
5.6%
Distinct72
Distinct (%)15.5%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-05-18T08:19:53.968739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1010753
Min length6

Characters and Unicode

Total characters2837
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 86
18.5%
153801 51
 
11.0%
153802 42
 
9.0%
153813 34
 
7.3%
153829 17
 
3.7%
153-803 17
 
3.7%
153814 17
 
3.7%
153861 12
 
2.6%
153825 10
 
2.2%
153-802 10
 
2.2%
Other values (62) 169
36.3%
2024-05-18T08:19:55.320510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 650
22.9%
1 619
21.8%
5 513
18.1%
8 463
16.3%
0 255
 
9.0%
2 102
 
3.6%
6 77
 
2.7%
- 47
 
1.7%
7 43
 
1.5%
4 39
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2790
98.3%
Dash Punctuation 47
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 650
23.3%
1 619
22.2%
5 513
18.4%
8 463
16.6%
0 255
 
9.1%
2 102
 
3.7%
6 77
 
2.8%
7 43
 
1.5%
4 39
 
1.4%
9 29
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 650
22.9%
1 619
21.8%
5 513
18.1%
8 463
16.3%
0 255
 
9.0%
2 102
 
3.6%
6 77
 
2.7%
- 47
 
1.7%
7 43
 
1.5%
4 39
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 650
22.9%
1 619
21.8%
5 513
18.1%
8 463
16.3%
0 255
 
9.0%
2 102
 
3.6%
6 77
 
2.7%
- 47
 
1.7%
7 43
 
1.5%
4 39
 
1.4%
Distinct420
Distinct (%)90.3%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-05-18T08:19:55.924270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length29.434409
Min length18

Characters and Unicode

Total characters13687
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

Unique385 ?
Unique (%)82.8%

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 466
19.4%
서울특별시 465
19.3%
가산동 234
 
9.7%
독산동 144
 
6.0%
시흥동 87
 
3.6%
지하1층 18
 
0.7%
지상1층 18
 
0.7%
지상2층 15
 
0.6%
1층 13
 
0.5%
336-8번지 11
 
0.5%
Other values (654) 934
38.8%
2024-05-18T08:19:57.262198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2302
 
16.8%
1 566
 
4.1%
563
 
4.1%
503
 
3.7%
476
 
3.5%
470
 
3.4%
470
 
3.4%
468
 
3.4%
467
 
3.4%
466
 
3.4%
Other values (209) 6936
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7672
56.1%
Decimal Number 2864
 
20.9%
Space Separator 2302
 
16.8%
Dash Punctuation 446
 
3.3%
Open Punctuation 139
 
1.0%
Close 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 (%)
563
 
7.3%
503
 
6.6%
476
 
6.2%
470
 
6.1%
470
 
6.1%
468
 
6.1%
467
 
6.1%
466
 
6.1%
465
 
6.1%
465
 
6.1%
Other values (179) 2859
37.3%
Decimal Number
ValueCountFrequency (%)
1 566
19.8%
3 354
12.4%
2 336
11.7%
0 320
11.2%
4 283
9.9%
5 257
9.0%
9 235
8.2%
8 182
 
6.4%
6 174
 
6.1%
7 157
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 30
37.0%
T 10
 
12.3%
S 9
 
11.1%
K 9
 
11.1%
I 9
 
11.1%
C 6
 
7.4%
A 6
 
7.4%
V 1
 
1.2%
X 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 32
86.5%
/ 4
 
10.8%
: 1
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 73
52.5%
[ 66
47.5%
Close Punctuation
ValueCountFrequency (%)
) 73
52.5%
] 66
47.5%
Space Separator
ValueCountFrequency (%)
2302
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 446
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7672
56.1%
Common 5933
43.3%
Latin 82
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
563
 
7.3%
503
 
6.6%
476
 
6.2%
470
 
6.1%
470
 
6.1%
468
 
6.1%
467
 
6.1%
466
 
6.1%
465
 
6.1%
465
 
6.1%
Other values (179) 2859
37.3%
Common
ValueCountFrequency (%)
2302
38.8%
1 566
 
9.5%
- 446
 
7.5%
3 354
 
6.0%
2 336
 
5.7%
0 320
 
5.4%
4 283
 
4.8%
5 257
 
4.3%
9 235
 
4.0%
8 182
 
3.1%
Other values (10) 652
 
11.0%
Latin
ValueCountFrequency (%)
B 30
36.6%
T 10
 
12.2%
S 9
 
11.0%
K 9
 
11.0%
I 9
 
11.0%
C 6
 
7.3%
A 6
 
7.3%
V 1
 
1.2%
X 1
 
1.2%
c 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7672
56.1%
ASCII 6015
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2302
38.3%
1 566
 
9.4%
- 446
 
7.4%
3 354
 
5.9%
2 336
 
5.6%
0 320
 
5.3%
4 283
 
4.7%
5 257
 
4.3%
9 235
 
3.9%
8 182
 
3.0%
Other values (20) 734
 
12.2%
Hangul
ValueCountFrequency (%)
563
 
7.3%
503
 
6.6%
476
 
6.2%
470
 
6.1%
470
 
6.1%
468
 
6.1%
467
 
6.1%
466
 
6.1%
465
 
6.1%
465
 
6.1%
Other values (179) 2859
37.3%

도로명주소
Text

MISSING 

Distinct250
Distinct (%)97.3%
Missing209
Missing (%)44.8%
Memory size3.8 KiB
2024-05-18T08:19:58.014611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length53
Mean length40.175097
Min length24

Characters and Unicode

Total characters10325
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

Unique243 ?
Unique (%)94.6%

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 257
 
14.2%
금천구 257
 
14.2%
가산동 153
 
8.5%
가산디지털1로 63
 
3.5%
독산동 48
 
2.7%
가산디지털2로 39
 
2.2%
지하1층 26
 
1.4%
1층 24
 
1.3%
시흥동 24
 
1.3%
벚꽃로 20
 
1.1%
Other values (494) 897
49.6%
2024-05-18T08:19:59.294397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1552
 
15.0%
1 548
 
5.3%
403
 
3.9%
, 343
 
3.3%
330
 
3.2%
299
 
2.9%
283
 
2.7%
278
 
2.7%
( 275
 
2.7%
) 275
 
2.7%
Other values (187) 5739
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5796
56.1%
Decimal Number 1855
 
18.0%
Space Separator 1552
 
15.0%
Other Punctuation 348
 
3.4%
Open Punctuation 292
 
2.8%
Close Punctuation 292
 
2.8%
Uppercase Letter 123
 
1.2%
Dash Punctuation 57
 
0.6%
Math Symbol 9
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
403
 
7.0%
330
 
5.7%
299
 
5.2%
283
 
4.9%
278
 
4.8%
263
 
4.5%
258
 
4.5%
258
 
4.5%
257
 
4.4%
257
 
4.4%
Other values (156) 2910
50.2%
Decimal Number
ValueCountFrequency (%)
1 548
29.5%
2 245
13.2%
0 221
11.9%
4 150
 
8.1%
3 148
 
8.0%
8 129
 
7.0%
5 121
 
6.5%
6 117
 
6.3%
9 89
 
4.8%
7 87
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 60
48.8%
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%
X 1
 
0.8%
V 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 343
98.6%
/ 4
 
1.1%
: 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 275
94.2%
[ 17
 
5.8%
Close Punctuation
ValueCountFrequency (%)
) 275
94.2%
] 17
 
5.8%
Space Separator
ValueCountFrequency (%)
1552
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5796
56.1%
Common 4405
42.7%
Latin 124
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
403
 
7.0%
330
 
5.7%
299
 
5.2%
283
 
4.9%
278
 
4.8%
263
 
4.5%
258
 
4.5%
258
 
4.5%
257
 
4.4%
257
 
4.4%
Other values (156) 2910
50.2%
Common
ValueCountFrequency (%)
1552
35.2%
1 548
 
12.4%
, 343
 
7.8%
( 275
 
6.2%
) 275
 
6.2%
2 245
 
5.6%
0 221
 
5.0%
4 150
 
3.4%
3 148
 
3.4%
8 129
 
2.9%
Other values (10) 519
 
11.8%
Latin
ValueCountFrequency (%)
B 60
48.4%
K 15
 
12.1%
S 15
 
12.1%
T 11
 
8.9%
I 10
 
8.1%
C 4
 
3.2%
A 4
 
3.2%
F 2
 
1.6%
b 1
 
0.8%
X 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5796
56.1%
ASCII 4529
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1552
34.3%
1 548
 
12.1%
, 343
 
7.6%
( 275
 
6.1%
) 275
 
6.1%
2 245
 
5.4%
0 221
 
4.9%
4 150
 
3.3%
3 148
 
3.3%
8 129
 
2.8%
Other values (21) 643
14.2%
Hangul
ValueCountFrequency (%)
403
 
7.0%
330
 
5.7%
299
 
5.2%
283
 
4.9%
278
 
4.8%
263
 
4.5%
258
 
4.5%
258
 
4.5%
257
 
4.4%
257
 
4.4%
Other values (156) 2910
50.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)29.4%
Missing211
Missing (%)45.3%
Infinite0
Infinite (%)0.0%
Mean8558.8196
Minimum8500
Maximum8654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-18T08:19:59.712027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8500
5-th percentile8501
Q18510.5
median8576
Q38592
95-th percentile8639
Maximum8654
Range154
Interquartile range (IQR)81.5

Descriptive statistics

Standard deviation47.245451
Coefficient of variation (CV)0.0055200896
Kurtosis-1.2821571
Mean8558.8196
Median Absolute Deviation (MAD)50
Skewness0.19564534
Sum2182499
Variance2232.1327
MonotonicityNot monotonic
2024-05-18T08:20:00.168890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8589 21
 
4.5%
8504 17
 
3.6%
8501 15
 
3.2%
8594 13
 
2.8%
8592 12
 
2.6%
8506 11
 
2.4%
8513 10
 
2.1%
8590 8
 
1.7%
8503 6
 
1.3%
8588 6
 
1.3%
Other values (65) 136
29.2%
(Missing) 211
45.3%
ValueCountFrequency (%)
8500 2
 
0.4%
8501 15
3.2%
8502 5
 
1.1%
8503 6
 
1.3%
8504 17
3.6%
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%
Distinct439
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-18T08:20:00.949687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length21
Mean length6.7360515
Min length2

Characters and Unicode

Total characters3139
Distinct characters427
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

Unique418 ?
Unique (%)89.7%

Sample

1st row영진식품
2nd row한국맛김
3rd row영상산업(주)
4th row한빛농산
5th row세계식품
ValueCountFrequency (%)
주식회사 28
 
5.1%
영진식품 3
 
0.5%
주)달라스 3
 
0.5%
주)본야록 3
 
0.5%
이레식품 3
 
0.5%
다도원 3
 
0.5%
레드파이 3
 
0.5%
2공장 3
 
0.5%
엔와이푸드 3
 
0.5%
농업회사법인 3
 
0.5%
Other values (472) 497
90.0%
2024-05-18T08:20:02.160824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
 
5.3%
) 147
 
4.7%
( 147
 
4.7%
135
 
4.3%
103
 
3.3%
86
 
2.7%
85
 
2.7%
65
 
2.1%
62
 
2.0%
48
 
1.5%
Other values (417) 2095
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2610
83.1%
Close Punctuation 147
 
4.7%
Open Punctuation 147
 
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 (%)
166
 
6.4%
135
 
5.2%
103
 
3.9%
85
 
3.3%
65
 
2.5%
62
 
2.4%
48
 
1.8%
46
 
1.8%
44
 
1.7%
37
 
1.4%
Other values (370) 1819
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%
K 3
 
3.9%
I 3
 
3.9%
A 3
 
3.9%
D 3
 
3.9%
Other values (11) 20
26.0%
Lowercase Letter
ValueCountFrequency (%)
o 6
13.3%
t 5
11.1%
s 4
8.9%
n 4
8.9%
e 4
8.9%
r 4
8.9%
u 4
8.9%
i 3
6.7%
a 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%
Close Punctuation
ValueCountFrequency (%)
) 147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 147
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2608
83.1%
Common 407
 
13.0%
Latin 122
 
3.9%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
166
 
6.4%
135
 
5.2%
103
 
3.9%
85
 
3.3%
65
 
2.5%
62
 
2.4%
48
 
1.8%
46
 
1.8%
44
 
1.7%
37
 
1.4%
Other values (368) 1817
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%
s 4
 
3.3%
n 4
 
3.3%
e 4
 
3.3%
E 4
 
3.3%
Other values (25) 58
47.5%
Common
ValueCountFrequency (%)
) 147
36.1%
( 147
36.1%
86
21.1%
1 7
 
1.7%
& 7
 
1.7%
2 4
 
1.0%
3 3
 
0.7%
0 2
 
0.5%
4 1
 
0.2%
' 1
 
0.2%
Other values (2) 2
 
0.5%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2608
83.1%
ASCII 529
 
16.9%
CJK 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
166
 
6.4%
135
 
5.2%
103
 
3.9%
85
 
3.3%
65
 
2.5%
62
 
2.4%
48
 
1.8%
46
 
1.8%
44
 
1.7%
37
 
1.4%
Other values (368) 1817
69.7%
ASCII
ValueCountFrequency (%)
) 147
27.8%
( 147
27.8%
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
17.4%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct424
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1999-07-16 00:00:00
Maximum2024-05-14 13:16:56
2024-05-18T08:20:02.567934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:20:03.202511image/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
133 

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
71.5%
U 133
 
28.5%

Length

2024-05-18T08:20:03.691932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:04.039946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 333
71.5%
u 133
 
28.5%
Distinct160
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-18T08:20:04.488755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:20:04.998088image/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
132 
도시락제조업
 
1

Length

Max length10
Median length7
Mean length7.8476395
Min length6

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 333
71.5%
기타 식품제조가공업 132
 
28.3%
도시락제조업 1
 
0.2%

Length

2024-05-18T08:20:05.632574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:06.039897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 465
77.8%
기타 132
 
22.1%
도시락제조업 1
 
0.2%

좌표정보(X)
Real number (ℝ)

Distinct281
Distinct (%)60.6%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean190312.56
Minimum188830.03
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-18T08:20:06.413958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188830.03
5-th percentile189089.93
Q1189575.82
median190186.29
Q3191084.79
95-th percentile191663.57
Maximum192754.35
Range3924.316
Interquartile range (IQR)1508.9783

Descriptive statistics

Standard deviation845.99603
Coefficient of variation (CV)0.0044452979
Kurtosis-0.965957
Mean190312.56
Median Absolute Deviation (MAD)682.03379
Skewness0.27775404
Sum88305028
Variance715709.29
MonotonicityNot monotonic
2024-05-18T08:20:06.893590image/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) 379
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 (%)60.6%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean440781.08
Minimum436946.36
Maximum442585.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-18T08:20:07.505476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436946.36
5-th percentile437966.96
Q1440373.75
median441074.21
Q3441629.36
95-th percentile442380.41
Maximum442585.93
Range5639.5745
Interquartile range (IQR)1255.6114

Descriptive statistics

Standard deviation1239.2513
Coefficient of variation (CV)0.0028114893
Kurtosis0.38410367
Mean440781.08
Median Absolute Deviation (MAD)643.28184
Skewness-0.99116322
Sum2.0452242 × 108
Variance1535743.8
MonotonicityNot monotonic
2024-05-18T08:20:08.002677image/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) 379
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 2
 
0.4%
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>
65 

Length

Max length10
Median length7
Mean length7.0772532
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 324
69.5%
기타 식품제조가공업 77
 
16.5%
<NA> 65
 
13.9%

Length

2024-05-18T08:20:08.379772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:08.655491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 401
73.8%
기타 77
 
14.2%
na 65
 
12.0%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
411 
0
 
40
1
 
7
2
 
6
7
 
1

Length

Max length4
Median length4
Mean length3.6459227
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> 411
88.2%
0 40
 
8.6%
1 7
 
1.5%
2 6
 
1.3%
7 1
 
0.2%
5 1
 
0.2%

Length

2024-05-18T08:20:09.017646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:09.347585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 411
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>
411 
0
48 
1
 
5
3
 
2

Length

Max length4
Median length4
Mean length3.6459227
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> 411
88.2%
0 48
 
10.3%
1 5
 
1.1%
3 2
 
0.4%

Length

2024-05-18T08:20:09.734143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:10.097537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 411
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>
397 
기타
45 
주택가주변
 
22
학교정화(상대)
 
2

Length

Max length8
Median length4
Mean length3.8712446
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 397
85.2%
기타 45
 
9.7%
주택가주변 22
 
4.7%
학교정화(상대) 2
 
0.4%

Length

2024-05-18T08:20:10.430411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:10.800272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 397
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>
397 
자율
 
39
기타
 
29
 
1

Length

Max length4
Median length4
Mean length3.7017167
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 397
85.2%
자율 39
 
8.4%
기타 29
 
6.2%
1
 
0.2%

Length

2024-05-18T08:20:11.212379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:11.581271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 397
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>
319 
상수도전용
147 

Length

Max length5
Median length4
Mean length4.3154506
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 319
68.5%
상수도전용 147
31.5%

Length

2024-05-18T08:20:11.982131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:12.366120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 319
68.5%
상수도전용 147
31.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
449 
0
 
17

Length

Max length4
Median length4
Mean length3.8905579
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> 449
96.4%
0 17
 
3.6%

Length

2024-05-18T08:20:12.797576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:13.092194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 449
96.4%
0 17
 
3.6%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
237 
<NA>
226 
1
 
1
2
 
1
3
 
1

Length

Max length4
Median length1
Mean length2.4549356
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
50.9%
<NA> 226
48.5%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%

Length

2024-05-18T08:20:13.389253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:13.817529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 237
50.9%
na 226
48.5%
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>
225 
2
 
3
3
 
1

Length

Max length4
Median length1
Mean length2.4484979
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
50.9%
<NA> 225
48.3%
2 3
 
0.6%
3 1
 
0.2%

Length

2024-05-18T08:20:14.333046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:14.861136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 237
50.9%
na 225
48.3%
2 3
 
0.6%
3 1
 
0.2%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
239 
<NA>
226 
3
 
1

Length

Max length4
Median length1
Mean length2.4549356
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
51.3%
<NA> 226
48.5%
3 1
 
0.2%

Length

2024-05-18T08:20:15.204725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:15.615020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 239
51.3%
na 226
48.5%
3 1
 
0.2%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.3%
Missing224
Missing (%)48.1%
Infinite0
Infinite (%)0.0%
Mean0.25206612
Minimum0
Maximum20
Zeros232
Zeros (%)49.8%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-18T08:20:15.877364image/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
2024-05-18T08:20:16.346135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 232
49.8%
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) 224
48.1%
ValueCountFrequency (%)
0 232
49.8%
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
49.8%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
321 
자가
81 
임대
64 

Length

Max length4
Median length4
Mean length3.3776824
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> 321
68.9%
자가 81
 
17.4%
임대 64
 
13.7%

Length

2024-05-18T08:20:16.954703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:17.322180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 321
68.9%
자가 81
 
17.4%
임대 64
 
13.7%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
414 
0
50 
25000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.695279
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> 414
88.8%
0 50
 
10.7%
25000000 1
 
0.2%
10000000 1
 
0.2%

Length

2024-05-18T08:20:17.745839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:18.123424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 414
88.8%
0 50
 
10.7%
25000000 1
 
0.2%
10000000 1
 
0.2%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
414 
0
50 
1300000
 
1
200000
 
1

Length

Max length7
Median length4
Mean length3.6888412
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> 414
88.8%
0 50
 
10.7%
1300000 1
 
0.2%
200000 1
 
0.2%

Length

2024-05-18T08:20:18.696534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:19.022028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 414
88.8%
0 50
 
10.7%
1300000 1
 
0.2%
200000 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing65
Missing (%)13.9%
Memory size1.0 KiB
False
401 
(Missing)
65 
ValueCountFrequency (%)
False 401
86.1%
(Missing) 65
 
13.9%
2024-05-18T08:20:19.282591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct74
Distinct (%)18.5%
Missing65
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean15.269726
Minimum0
Maximum448.2
Zeros324
Zeros (%)69.5%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-18T08:20:19.648646image/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
2024-05-18T08:20:20.155423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 324
69.5%
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
 
13.7%
(Missing) 65
 
13.9%
ValueCountFrequency (%)
0.0 324
69.5%
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 

Missing466
Missing (%)100.0%
Memory size4.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing466
Missing (%)100.0%
Memory size4.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing466
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
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)8594킹스베이커리2024-05-14 13:16:56U2023-12-04 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>
46531700003170000-106-2024-000042024-05-10<NA>1영업/정상1영업<NA><NA><NA><NA>02 9602231741.24153-803서울특별시 금천구 가산동 481-4 벽산디지털밸리6차서울특별시 금천구 가산디지털1로 219, 벽산디지털밸리6차 B106~107호 (가산동)8501(주)메이크샐러드2024-05-10 16:04:34I2023-12-04 23:02:00.0기타 식품제조가공업189232.306428442478.356257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>