Overview

Dataset statistics

Number of variables44
Number of observations552
Missing cells6410
Missing cells (%)26.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory202.3 KiB
Average record size in memory375.2 B

Variable types

Categorical17
Text7
DateTime4
Unsupported7
Numeric8
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18273/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (56.2%)Imbalance
영업상태명 is highly imbalanced (56.2%)Imbalance
상세영업상태코드 is highly imbalanced (56.2%)Imbalance
상세영업상태명 is highly imbalanced (56.2%)Imbalance
여성종사자수 is highly imbalanced (74.2%)Imbalance
영업장주변구분명 is highly imbalanced (58.6%)Imbalance
등급구분명 is highly imbalanced (71.5%)Imbalance
총인원 is highly imbalanced (84.9%)Imbalance
인허가취소일자 has 552 (100.0%) missing valuesMissing
폐업일자 has 50 (9.1%) missing valuesMissing
휴업시작일자 has 552 (100.0%) missing valuesMissing
휴업종료일자 has 552 (100.0%) missing valuesMissing
재개업일자 has 552 (100.0%) missing valuesMissing
전화번호 has 142 (25.7%) missing valuesMissing
소재지면적 has 81 (14.7%) missing valuesMissing
도로명주소 has 282 (51.1%) missing valuesMissing
도로명우편번호 has 287 (52.0%) missing valuesMissing
좌표정보(X) has 8 (1.4%) missing valuesMissing
좌표정보(Y) has 8 (1.4%) missing valuesMissing
남성종사자수 has 486 (88.0%) missing valuesMissing
공장생산직종업원수 has 188 (34.1%) missing valuesMissing
보증액 has 473 (85.7%) missing valuesMissing
월세액 has 475 (86.1%) missing valuesMissing
다중이용업소여부 has 33 (6.0%) missing valuesMissing
시설총규모 has 33 (6.0%) missing valuesMissing
전통업소지정번호 has 552 (100.0%) missing valuesMissing
전통업소주된음식 has 552 (100.0%) missing valuesMissing
홈페이지 has 552 (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
남성종사자수 has 51 (9.2%) zerosZeros
공장생산직종업원수 has 345 (62.5%) zerosZeros
보증액 has 56 (10.1%) zerosZeros
월세액 has 57 (10.3%) zerosZeros
시설총규모 has 490 (88.8%) zerosZeros

Reproduction

Analysis started2024-04-29 19:41:02.490824
Analysis finished2024-04-29 19:41:03.601195
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3210000
552 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 552
100.0%

Length

2024-04-30T04:41:03.688619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:03.777191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 552
100.0%

관리번호
Text

UNIQUE 

Distinct552
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-04-30T04:41:03.932527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters12144
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

Unique552 ?
Unique (%)100.0%

Sample

1st row3210000-106-1970-01443
2nd row3210000-106-1981-00210
3rd row3210000-106-1984-00225
4th row3210000-106-1987-00226
5th row3210000-106-1987-00242
ValueCountFrequency (%)
3210000-106-1970-01443 1
 
0.2%
3210000-106-2012-00004 1
 
0.2%
3210000-106-2011-00035 1
 
0.2%
3210000-106-2012-00009 1
 
0.2%
3210000-106-2012-00008 1
 
0.2%
3210000-106-2012-00007 1
 
0.2%
3210000-106-2012-00006 1
 
0.2%
3210000-106-2012-00005 1
 
0.2%
3210000-106-2012-00011 1
 
0.2%
3210000-106-2012-00010 1
 
0.2%
Other values (542) 542
98.2%
2024-04-30T04:41:04.234940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5282
43.5%
1 1786
 
14.7%
- 1656
 
13.6%
2 1318
 
10.9%
3 717
 
5.9%
6 656
 
5.4%
9 237
 
2.0%
4 147
 
1.2%
8 144
 
1.2%
5 107
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10488
86.4%
Dash Punctuation 1656
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5282
50.4%
1 1786
 
17.0%
2 1318
 
12.6%
3 717
 
6.8%
6 656
 
6.3%
9 237
 
2.3%
4 147
 
1.4%
8 144
 
1.4%
5 107
 
1.0%
7 94
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12144
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5282
43.5%
1 1786
 
14.7%
- 1656
 
13.6%
2 1318
 
10.9%
3 717
 
5.9%
6 656
 
5.4%
9 237
 
2.0%
4 147
 
1.2%
8 144
 
1.2%
5 107
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5282
43.5%
1 1786
 
14.7%
- 1656
 
13.6%
2 1318
 
10.9%
3 717
 
5.9%
6 656
 
5.4%
9 237
 
2.0%
4 147
 
1.2%
8 144
 
1.2%
5 107
 
0.9%
Distinct508
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum1970-05-05 00:00:00
Maximum2024-03-29 00:00:00
2024-04-30T04:41:04.379253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:41:04.524336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3
502 
1
 
50

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 (%)
3 502
90.9%
1 50
 
9.1%

Length

2024-04-30T04:41:04.629996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:04.714378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 502
90.9%
1 50
 
9.1%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
폐업
502 
영업/정상
 
50

Length

Max length5
Median length2
Mean length2.2717391
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 502
90.9%
영업/정상 50
 
9.1%

Length

2024-04-30T04:41:04.830745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:04.935845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 502
90.9%
영업/정상 50
 
9.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2
502 
1
 
50

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 (%)
2 502
90.9%
1 50
 
9.1%

Length

2024-04-30T04:41:05.033029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:05.115203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 502
90.9%
1 50
 
9.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
폐업
502 
영업
 
50

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 502
90.9%
영업 50
 
9.1%

Length

2024-04-30T04:41:05.195716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:05.282730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 502
90.9%
영업 50
 
9.1%

폐업일자
Date

MISSING 

Distinct426
Distinct (%)84.9%
Missing50
Missing (%)9.1%
Memory size4.4 KiB
Minimum1993-11-02 00:00:00
Maximum2024-04-15 00:00:00
2024-04-30T04:41:05.393088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:41:05.521916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

전화번호
Text

MISSING 

Distinct389
Distinct (%)94.9%
Missing142
Missing (%)25.7%
Memory size4.4 KiB
2024-04-30T04:41:05.820832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.741463
Min length2

Characters and Unicode

Total characters4404
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

Unique374 ?
Unique (%)91.2%

Sample

1st row02 5670171
2nd row02 5933578
3rd row02 5911704
4th row02 0
5th row0205862126
ValueCountFrequency (%)
02 312
36.3%
070 26
 
3.0%
521 6
 
0.7%
586 5
 
0.6%
577 5
 
0.6%
596 5
 
0.6%
532 5
 
0.6%
585 5
 
0.6%
583 4
 
0.5%
522 3
 
0.3%
Other values (440) 484
56.3%
2024-04-30T04:41:06.210823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 703
16.0%
2 649
14.7%
627
14.2%
5 489
11.1%
7 347
7.9%
3 329
7.5%
8 274
 
6.2%
4 262
 
5.9%
1 257
 
5.8%
6 237
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3777
85.8%
Space Separator 627
 
14.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 703
18.6%
2 649
17.2%
5 489
12.9%
7 347
9.2%
3 329
8.7%
8 274
 
7.3%
4 262
 
6.9%
1 257
 
6.8%
6 237
 
6.3%
9 230
 
6.1%
Space Separator
ValueCountFrequency (%)
627
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4404
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 703
16.0%
2 649
14.7%
627
14.2%
5 489
11.1%
7 347
7.9%
3 329
7.5%
8 274
 
6.2%
4 262
 
5.9%
1 257
 
5.8%
6 237
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4404
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 703
16.0%
2 649
14.7%
627
14.2%
5 489
11.1%
7 347
7.9%
3 329
7.5%
8 274
 
6.2%
4 262
 
5.9%
1 257
 
5.8%
6 237
 
5.4%

소재지면적
Text

MISSING 

Distinct367
Distinct (%)77.9%
Missing81
Missing (%)14.7%
Memory size4.4 KiB
2024-04-30T04:41:06.558305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1698514
Min length3

Characters and Unicode

Total characters2435
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

Unique328 ?
Unique (%)69.6%

Sample

1st row5,395.00
2nd row.00
3rd row15.60
4th row12.95
5th row1,032.84
ValueCountFrequency (%)
00 17
 
3.6%
33.00 12
 
2.5%
30.00 8
 
1.7%
20.00 7
 
1.5%
10.00 6
 
1.3%
80.00 5
 
1.1%
12.00 4
 
0.8%
25.00 4
 
0.8%
24.00 4
 
0.8%
60.00 4
 
0.8%
Other values (357) 400
84.9%
2024-04-30T04:41:07.036041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 548
22.5%
. 471
19.3%
1 261
10.7%
2 198
 
8.1%
3 177
 
7.3%
6 147
 
6.0%
4 145
 
6.0%
5 138
 
5.7%
8 122
 
5.0%
9 120
 
4.9%
Other values (2) 108
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1961
80.5%
Other Punctuation 474
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 548
27.9%
1 261
13.3%
2 198
 
10.1%
3 177
 
9.0%
6 147
 
7.5%
4 145
 
7.4%
5 138
 
7.0%
8 122
 
6.2%
9 120
 
6.1%
7 105
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 471
99.4%
, 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 2435
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 548
22.5%
. 471
19.3%
1 261
10.7%
2 198
 
8.1%
3 177
 
7.3%
6 147
 
6.0%
4 145
 
6.0%
5 138
 
5.7%
8 122
 
5.0%
9 120
 
4.9%
Other values (2) 108
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 548
22.5%
. 471
19.3%
1 261
10.7%
2 198
 
8.1%
3 177
 
7.3%
6 147
 
6.0%
4 145
 
6.0%
5 138
 
5.7%
8 122
 
5.0%
9 120
 
4.9%
Other values (2) 108
 
4.4%
Distinct129
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-04-30T04:41:07.278872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0362319
Min length6

Characters and Unicode

Total characters3332
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

Unique39 ?
Unique (%)7.1%

Sample

1st row137857
2nd row137829
3rd row137030
4th row137040
5th row137871
ValueCountFrequency (%)
137894 25
 
4.5%
137896 17
 
3.1%
137829 16
 
2.9%
137832 14
 
2.5%
137806 13
 
2.4%
137898 12
 
2.2%
137899 12
 
2.2%
137886 12
 
2.2%
137895 11
 
2.0%
137838 11
 
2.0%
Other values (119) 409
74.1%
2024-04-30T04:41:07.633953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 668
20.0%
3 653
19.6%
1 633
19.0%
8 578
17.3%
9 236
 
7.1%
0 185
 
5.6%
6 109
 
3.3%
4 95
 
2.9%
2 79
 
2.4%
5 76
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3312
99.4%
Dash Punctuation 20
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 668
20.2%
3 653
19.7%
1 633
19.1%
8 578
17.5%
9 236
 
7.1%
0 185
 
5.6%
6 109
 
3.3%
4 95
 
2.9%
2 79
 
2.4%
5 76
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 668
20.0%
3 653
19.6%
1 633
19.0%
8 578
17.3%
9 236
 
7.1%
0 185
 
5.6%
6 109
 
3.3%
4 95
 
2.9%
2 79
 
2.4%
5 76
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 668
20.0%
3 653
19.6%
1 633
19.0%
8 578
17.3%
9 236
 
7.1%
0 185
 
5.6%
6 109
 
3.3%
4 95
 
2.9%
2 79
 
2.4%
5 76
 
2.3%
Distinct535
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-04-30T04:41:07.870969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length26.563406
Min length18

Characters and Unicode

Total characters14663
Distinct characters221
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique519 ?
Unique (%)94.0%

Sample

1st row서울특별시 서초구 서초동 1322-1번지
2nd row서울특별시 서초구 방배동 767-1번지
3rd row서울특별시 서초구 잠원동 132-15번지
4th row서울특별시 서초구 반포동 398-2번지
5th row서울특별시 서초구 서초동 1519-6번지
ValueCountFrequency (%)
서울특별시 552
20.2%
서초구 552
20.2%
방배동 143
 
5.2%
서초동 142
 
5.2%
양재동 140
 
5.1%
1층 98
 
3.6%
반포동 73
 
2.7%
지하1층 64
 
2.3%
잠원동 41
 
1.5%
2층 21
 
0.8%
Other values (720) 911
33.3%
2024-04-30T04:41:08.247993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2678
18.3%
1261
 
8.6%
1 808
 
5.5%
703
 
4.8%
600
 
4.1%
582
 
4.0%
560
 
3.8%
553
 
3.8%
552
 
3.8%
552
 
3.8%
Other values (211) 5814
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8369
57.1%
Decimal Number 2944
 
20.1%
Space Separator 2678
 
18.3%
Dash Punctuation 513
 
3.5%
Close Punctuation 53
 
0.4%
Open Punctuation 53
 
0.4%
Uppercase Letter 33
 
0.2%
Other Punctuation 19
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1261
15.1%
703
 
8.4%
600
 
7.2%
582
 
7.0%
560
 
6.7%
553
 
6.6%
552
 
6.6%
552
 
6.6%
552
 
6.6%
469
 
5.6%
Other values (184) 1985
23.7%
Decimal Number
ValueCountFrequency (%)
1 808
27.4%
2 346
11.8%
3 302
 
10.3%
5 241
 
8.2%
0 231
 
7.8%
4 230
 
7.8%
6 223
 
7.6%
7 206
 
7.0%
8 187
 
6.4%
9 170
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 15
45.5%
A 5
 
15.2%
C 3
 
9.1%
J 2
 
6.1%
M 2
 
6.1%
D 2
 
6.1%
I 1
 
3.0%
W 1
 
3.0%
H 1
 
3.0%
F 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 18
94.7%
/ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
2678
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 513
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8369
57.1%
Common 6261
42.7%
Latin 33
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1261
15.1%
703
 
8.4%
600
 
7.2%
582
 
7.0%
560
 
6.7%
553
 
6.6%
552
 
6.6%
552
 
6.6%
552
 
6.6%
469
 
5.6%
Other values (184) 1985
23.7%
Common
ValueCountFrequency (%)
2678
42.8%
1 808
 
12.9%
- 513
 
8.2%
2 346
 
5.5%
3 302
 
4.8%
5 241
 
3.8%
0 231
 
3.7%
4 230
 
3.7%
6 223
 
3.6%
7 206
 
3.3%
Other values (7) 483
 
7.7%
Latin
ValueCountFrequency (%)
B 15
45.5%
A 5
 
15.2%
C 3
 
9.1%
J 2
 
6.1%
M 2
 
6.1%
D 2
 
6.1%
I 1
 
3.0%
W 1
 
3.0%
H 1
 
3.0%
F 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8369
57.1%
ASCII 6294
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2678
42.5%
1 808
 
12.8%
- 513
 
8.2%
2 346
 
5.5%
3 302
 
4.8%
5 241
 
3.8%
0 231
 
3.7%
4 230
 
3.7%
6 223
 
3.5%
7 206
 
3.3%
Other values (17) 516
 
8.2%
Hangul
ValueCountFrequency (%)
1261
15.1%
703
 
8.4%
600
 
7.2%
582
 
7.0%
560
 
6.7%
553
 
6.6%
552
 
6.6%
552
 
6.6%
552
 
6.6%
469
 
5.6%
Other values (184) 1985
23.7%

도로명주소
Text

MISSING 

Distinct263
Distinct (%)97.4%
Missing282
Missing (%)51.1%
Memory size4.4 KiB
2024-04-30T04:41:08.490529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length46
Mean length31.259259
Min length22

Characters and Unicode

Total characters8440
Distinct characters189
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)94.8%

Sample

1st row서울특별시 서초구 동산로16길 20, 2층 (양재동)
2nd row서울특별시 서초구 방배중앙로13길 10 (방배동)
3rd row서울특별시 서초구 남부순환로339길 64-19 (서초동)
4th row서울특별시 서초구 언남12길 7, 1층 (양재동)
5th row서울특별시 서초구 동작대로 222, 목은빌딩 지하1층 (방배동)
ValueCountFrequency (%)
서울특별시 270
 
16.2%
서초구 270
 
16.2%
1층 84
 
5.0%
서초동 82
 
4.9%
방배동 70
 
4.2%
양재동 53
 
3.2%
지하1층 50
 
3.0%
반포동 40
 
2.4%
잠원동 24
 
1.4%
2층 17
 
1.0%
Other values (412) 709
42.5%
2024-04-30T04:41:08.853681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1400
 
16.6%
683
 
8.1%
1 418
 
5.0%
402
 
4.8%
298
 
3.5%
) 274
 
3.2%
( 274
 
3.2%
273
 
3.2%
271
 
3.2%
271
 
3.2%
Other values (179) 3876
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4881
57.8%
Space Separator 1400
 
16.6%
Decimal Number 1310
 
15.5%
Close Punctuation 274
 
3.2%
Open Punctuation 274
 
3.2%
Other Punctuation 236
 
2.8%
Dash Punctuation 49
 
0.6%
Uppercase Letter 15
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
683
14.0%
402
 
8.2%
298
 
6.1%
273
 
5.6%
271
 
5.6%
271
 
5.6%
270
 
5.5%
270
 
5.5%
257
 
5.3%
186
 
3.8%
Other values (156) 1700
34.8%
Decimal Number
ValueCountFrequency (%)
1 418
31.9%
2 189
14.4%
3 127
 
9.7%
5 116
 
8.9%
0 99
 
7.6%
4 90
 
6.9%
6 85
 
6.5%
7 79
 
6.0%
8 59
 
4.5%
9 48
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 8
53.3%
C 2
 
13.3%
F 1
 
6.7%
J 1
 
6.7%
W 1
 
6.7%
M 1
 
6.7%
I 1
 
6.7%
Space Separator
ValueCountFrequency (%)
1400
100.0%
Close Punctuation
ValueCountFrequency (%)
) 274
100.0%
Open Punctuation
ValueCountFrequency (%)
( 274
100.0%
Other Punctuation
ValueCountFrequency (%)
, 236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4881
57.8%
Common 3544
42.0%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
683
14.0%
402
 
8.2%
298
 
6.1%
273
 
5.6%
271
 
5.6%
271
 
5.6%
270
 
5.5%
270
 
5.5%
257
 
5.3%
186
 
3.8%
Other values (156) 1700
34.8%
Common
ValueCountFrequency (%)
1400
39.5%
1 418
 
11.8%
) 274
 
7.7%
( 274
 
7.7%
, 236
 
6.7%
2 189
 
5.3%
3 127
 
3.6%
5 116
 
3.3%
0 99
 
2.8%
4 90
 
2.5%
Other values (6) 321
 
9.1%
Latin
ValueCountFrequency (%)
B 8
53.3%
C 2
 
13.3%
F 1
 
6.7%
J 1
 
6.7%
W 1
 
6.7%
M 1
 
6.7%
I 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4881
57.8%
ASCII 3559
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1400
39.3%
1 418
 
11.7%
) 274
 
7.7%
( 274
 
7.7%
, 236
 
6.6%
2 189
 
5.3%
3 127
 
3.6%
5 116
 
3.3%
0 99
 
2.8%
4 90
 
2.5%
Other values (13) 336
 
9.4%
Hangul
ValueCountFrequency (%)
683
14.0%
402
 
8.2%
298
 
6.1%
273
 
5.6%
271
 
5.6%
271
 
5.6%
270
 
5.5%
270
 
5.5%
257
 
5.3%
186
 
3.8%
Other values (156) 1700
34.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct137
Distinct (%)51.7%
Missing287
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean6646.2189
Minimum6509
Maximum6791
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:08.973873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6509
5-th percentile6527.4
Q16571
median6643
Q36725
95-th percentile6780.6
Maximum6791
Range282
Interquartile range (IQR)154

Descriptive statistics

Standard deviation85.61881
Coefficient of variation (CV)0.012882334
Kurtosis-1.3229843
Mean6646.2189
Median Absolute Deviation (MAD)76
Skewness0.16045136
Sum1761248
Variance7330.5807
MonotonicityNot monotonic
2024-04-30T04:41:09.106909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6776 8
 
1.4%
6576 8
 
1.4%
6593 8
 
1.4%
6650 5
 
0.9%
6532 4
 
0.7%
6570 4
 
0.7%
6584 4
 
0.7%
6546 4
 
0.7%
6634 4
 
0.7%
6575 4
 
0.7%
Other values (127) 212
38.4%
(Missing) 287
52.0%
ValueCountFrequency (%)
6509 1
 
0.2%
6512 3
0.5%
6516 2
0.4%
6518 2
0.4%
6520 1
 
0.2%
6522 1
 
0.2%
6525 1
 
0.2%
6526 2
0.4%
6527 1
 
0.2%
6529 3
0.5%
ValueCountFrequency (%)
6791 2
 
0.4%
6789 2
 
0.4%
6786 2
 
0.4%
6785 3
 
0.5%
6784 1
 
0.2%
6781 4
0.7%
6779 2
 
0.4%
6778 3
 
0.5%
6777 2
 
0.4%
6776 8
1.4%
Distinct513
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-04-30T04:41:09.325756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length7.1666667
Min length2

Characters and Unicode

Total characters3956
Distinct characters502
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique483 ?
Unique (%)87.5%

Sample

1st row롯데칠성음료(주)
2nd row강남식품
3rd row낙원
4th row풀무원식품
5th row다복식품
ValueCountFrequency (%)
주식회사 18
 
2.6%
홍삼나라 6
 
0.9%
coffee 5
 
0.7%
고추랑 3
 
0.4%
한원푸드시스템(주 3
 
0.4%
아리랑 3
 
0.4%
우리떡 3
 
0.4%
주)놀부 3
 
0.4%
커피 3
 
0.4%
마노핀 3
 
0.4%
Other values (601) 640
92.8%
2024-04-30T04:41:09.652579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 187
 
4.7%
) 187
 
4.7%
167
 
4.2%
138
 
3.5%
94
 
2.4%
93
 
2.4%
91
 
2.3%
68
 
1.7%
63
 
1.6%
55
 
1.4%
Other values (492) 2813
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3013
76.2%
Uppercase Letter 240
 
6.1%
Open Punctuation 187
 
4.7%
Close Punctuation 187
 
4.7%
Lowercase Letter 164
 
4.1%
Space Separator 138
 
3.5%
Other Punctuation 16
 
0.4%
Decimal Number 9
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
167
 
5.5%
94
 
3.1%
93
 
3.1%
91
 
3.0%
68
 
2.3%
63
 
2.1%
55
 
1.8%
52
 
1.7%
50
 
1.7%
46
 
1.5%
Other values (433) 2234
74.1%
Uppercase Letter
ValueCountFrequency (%)
E 26
 
10.8%
C 26
 
10.8%
O 17
 
7.1%
R 16
 
6.7%
F 15
 
6.2%
N 14
 
5.8%
A 14
 
5.8%
T 13
 
5.4%
I 13
 
5.4%
S 12
 
5.0%
Other values (12) 74
30.8%
Lowercase Letter
ValueCountFrequency (%)
o 21
12.8%
e 21
12.8%
a 20
12.2%
f 15
9.1%
r 14
8.5%
c 12
 
7.3%
n 11
 
6.7%
d 6
 
3.7%
i 6
 
3.7%
l 6
 
3.7%
Other values (12) 32
19.5%
Decimal Number
ValueCountFrequency (%)
1 3
33.3%
2 2
22.2%
8 1
 
11.1%
0 1
 
11.1%
7 1
 
11.1%
9 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
& 6
37.5%
. 6
37.5%
' 2
 
12.5%
, 1
 
6.2%
? 1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 187
100.0%
Close Punctuation
ValueCountFrequency (%)
) 187
100.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3013
76.2%
Common 539
 
13.6%
Latin 404
 
10.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
167
 
5.5%
94
 
3.1%
93
 
3.1%
91
 
3.0%
68
 
2.3%
63
 
2.1%
55
 
1.8%
52
 
1.7%
50
 
1.7%
46
 
1.5%
Other values (433) 2234
74.1%
Latin
ValueCountFrequency (%)
E 26
 
6.4%
C 26
 
6.4%
o 21
 
5.2%
e 21
 
5.2%
a 20
 
5.0%
O 17
 
4.2%
R 16
 
4.0%
F 15
 
3.7%
f 15
 
3.7%
r 14
 
3.5%
Other values (34) 213
52.7%
Common
ValueCountFrequency (%)
( 187
34.7%
) 187
34.7%
138
25.6%
& 6
 
1.1%
. 6
 
1.1%
1 3
 
0.6%
- 2
 
0.4%
' 2
 
0.4%
2 2
 
0.4%
8 1
 
0.2%
Other values (5) 5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3013
76.2%
ASCII 943
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 187
19.8%
) 187
19.8%
138
14.6%
E 26
 
2.8%
C 26
 
2.8%
o 21
 
2.2%
e 21
 
2.2%
a 20
 
2.1%
O 17
 
1.8%
R 16
 
1.7%
Other values (49) 284
30.1%
Hangul
ValueCountFrequency (%)
167
 
5.5%
94
 
3.1%
93
 
3.1%
91
 
3.0%
68
 
2.3%
63
 
2.1%
55
 
1.8%
52
 
1.7%
50
 
1.7%
46
 
1.5%
Other values (433) 2234
74.1%
Distinct450
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum1999-10-04 00:00:00
Maximum2024-04-15 16:07:31
2024-04-30T04:41:09.774503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:41:10.058124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
I
450 
U
102 

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 450
81.5%
U 102
 
18.5%

Length

2024-04-30T04:41:10.178698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:10.269554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 450
81.5%
u 102
 
18.5%
Distinct107
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-30T04:41:10.362952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:41:10.472358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
식품제조가공업
456 
기타 식품제조가공업
96 

Length

Max length10
Median length7
Mean length7.5217391
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 456
82.6%
기타 식품제조가공업 96
 
17.4%

Length

2024-04-30T04:41:10.577440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:10.654420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 552
85.2%
기타 96
 
14.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct451
Distinct (%)82.9%
Missing8
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean201269.72
Minimum198394.43
Maximum204444.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:10.750607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198394.43
5-th percentile198592.57
Q1199538.06
median201310.1
Q3203046.47
95-th percentile203925.63
Maximum204444.42
Range6049.9851
Interquartile range (IQR)3508.4099

Descriptive statistics

Standard deviation1794.6517
Coefficient of variation (CV)0.0089166502
Kurtosis-1.2208574
Mean201269.72
Median Absolute Deviation (MAD)1754.5605
Skewness0.03348434
Sum1.0949073 × 108
Variance3220774.8
MonotonicityNot monotonic
2024-04-30T04:41:10.857154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198592.572389794 7
 
1.3%
200250.447804795 6
 
1.1%
199203.217542184 4
 
0.7%
203678.440399782 4
 
0.7%
201226.075930426 4
 
0.7%
200836.484603059 3
 
0.5%
199022.868453712 3
 
0.5%
201107.634736928 3
 
0.5%
202086.133719824 3
 
0.5%
202150.523779604 3
 
0.5%
Other values (441) 504
91.3%
(Missing) 8
 
1.4%
ValueCountFrequency (%)
198394.433265008 1
0.2%
198407.667634842 1
0.2%
198424.78286692 1
0.2%
198431.914365654 1
0.2%
198439.169954695 1
0.2%
198443.006869649 1
0.2%
198449.914939428 1
0.2%
198458.944611476 1
0.2%
198462.438803051 1
0.2%
198463.984448209 1
0.2%
ValueCountFrequency (%)
204444.418396759 1
0.2%
204361.663541489 1
0.2%
204352.426654986 1
0.2%
204309.899725102 1
0.2%
204249.890471433 1
0.2%
204243.707147236 1
0.2%
204225.831637531 1
0.2%
204224.33 1
0.2%
204190.996435039 1
0.2%
204185.987391403 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct451
Distinct (%)82.9%
Missing8
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean442884.47
Minimum439045.6
Maximum446331.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:10.968364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439045.6
5-th percentile440822.94
Q1441791.9
median442805.64
Q3443772.47
95-th percentile445452.19
Maximum446331.38
Range7285.784
Interquartile range (IQR)1980.5658

Descriptive statistics

Standard deviation1382.7203
Coefficient of variation (CV)0.003122079
Kurtosis-0.43412864
Mean442884.47
Median Absolute Deviation (MAD)981.12287
Skewness0.32472006
Sum2.4092915 × 108
Variance1911915.4
MonotonicityNot monotonic
2024-04-30T04:41:11.083116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443636.163371743 7
 
1.3%
444683.220506107 6
 
1.1%
442268.679255693 4
 
0.7%
441242.791786723 4
 
0.7%
446331.380046658 4
 
0.7%
444418.23261792 3
 
0.5%
443881.411090312 3
 
0.5%
443999.067092566 3
 
0.5%
444484.604437589 3
 
0.5%
440990.104205604 3
 
0.5%
Other values (441) 504
91.3%
(Missing) 8
 
1.4%
ValueCountFrequency (%)
439045.596025645 1
0.2%
440070.727589935 1
0.2%
440151.798837107 1
0.2%
440387.38641804 2
0.4%
440451.300800855 1
0.2%
440496.148197498 1
0.2%
440525.129901434 1
0.2%
440528.547862574 1
0.2%
440538.518514781 1
0.2%
440608.132795658 1
0.2%
ValueCountFrequency (%)
446331.380046658 4
0.7%
446102.588876 2
0.4%
445992.459343379 2
0.4%
445988.430075169 1
 
0.2%
445816.60469444 2
0.4%
445804.018502151 1
 
0.2%
445747.396057887 1
 
0.2%
445737.586115236 1
 
0.2%
445728.243918949 1
 
0.2%
445666.908243581 1
 
0.2%

위생업태명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
식품제조가공업
451 
기타 식품제조가공업
68 
<NA>
 
33

Length

Max length10
Median length7
Mean length7.1902174
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 451
81.7%
기타 식품제조가공업 68
 
12.3%
<NA> 33
 
6.0%

Length

2024-04-30T04:41:11.211511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:11.294829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 519
83.7%
기타 68
 
11.0%
na 33
 
5.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)9.1%
Missing486
Missing (%)88.0%
Infinite0
Infinite (%)0.0%
Mean0.54545455
Minimum0
Maximum5
Zeros51
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:11.369807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1526801
Coefficient of variation (CV)2.1132468
Kurtosis3.9313494
Mean0.54545455
Median Absolute Deviation (MAD)0
Skewness2.1543614
Sum36
Variance1.3286713
MonotonicityNot monotonic
2024-04-30T04:41:11.473058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 51
 
9.2%
3 5
 
0.9%
2 4
 
0.7%
1 4
 
0.7%
5 1
 
0.2%
4 1
 
0.2%
(Missing) 486
88.0%
ValueCountFrequency (%)
0 51
9.2%
1 4
 
0.7%
2 4
 
0.7%
3 5
 
0.9%
4 1
 
0.2%
5 1
 
0.2%
ValueCountFrequency (%)
5 1
 
0.2%
4 1
 
0.2%
3 5
 
0.9%
2 4
 
0.7%
1 4
 
0.7%
0 51
9.2%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
486 
0
51 
2
 
7
1
 
5
4
 
2

Length

Max length4
Median length4
Mean length3.6413043
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row2
3rd row1
4th row<NA>
5th row4

Common Values

ValueCountFrequency (%)
<NA> 486
88.0%
0 51
 
9.2%
2 7
 
1.3%
1 5
 
0.9%
4 2
 
0.4%
3 1
 
0.2%

Length

2024-04-30T04:41:11.610617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:11.706658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 486
88.0%
0 51
 
9.2%
2 7
 
1.3%
1 5
 
0.9%
4 2
 
0.4%
3 1
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
483 
기타
 
47
주택가주변
 
22

Length

Max length5
Median length4
Mean length3.8695652
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 483
87.5%
기타 47
 
8.5%
주택가주변 22
 
4.0%

Length

2024-04-30T04:41:11.798319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:11.887348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 483
87.5%
기타 47
 
8.5%
주택가주변 22
 
4.0%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
483 
기타
67 
우수
 
1
자율
 
1

Length

Max length4
Median length4
Mean length3.75
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 483
87.5%
기타 67
 
12.1%
우수 1
 
0.2%
자율 1
 
0.2%

Length

2024-04-30T04:41:11.982623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:12.068901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 483
87.5%
기타 67
 
12.1%
우수 1
 
0.2%
자율 1
 
0.2%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
396 
상수도전용
155 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.2826087
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 396
71.7%
상수도전용 155
 
28.1%
지하수전용 1
 
0.2%

Length

2024-04-30T04:41:12.162143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:12.240974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 396
71.7%
상수도전용 155
 
28.1%
지하수전용 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
540 
0
 
12

Length

Max length4
Median length4
Mean length3.9347826
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> 540
97.8%
0 12
 
2.2%

Length

2024-04-30T04:41:12.330652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:12.406830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 540
97.8%
0 12
 
2.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
0
357 
<NA>
195 

Length

Max length4
Median length1
Mean length2.0597826
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 357
64.7%
<NA> 195
35.3%

Length

2024-04-30T04:41:12.496948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:12.578683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 357
64.7%
na 195
35.3%
Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
0
354 
<NA>
192 
1
 
4
2
 
2

Length

Max length4
Median length1
Mean length2.0434783
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 354
64.1%
<NA> 192
34.8%
1 4
 
0.7%
2 2
 
0.4%

Length

2024-04-30T04:41:12.680835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:12.774986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 354
64.1%
na 192
34.8%
1 4
 
0.7%
2 2
 
0.4%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
0
357 
<NA>
194 
2
 
1

Length

Max length4
Median length1
Mean length2.0543478
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 357
64.7%
<NA> 194
35.1%
2 1
 
0.2%

Length

2024-04-30T04:41:12.863441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:12.950751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 357
64.7%
na 194
35.1%
2 1
 
0.2%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.9%
Missing188
Missing (%)34.1%
Infinite0
Infinite (%)0.0%
Mean0.10714286
Minimum0
Maximum7
Zeros345
Zeros (%)62.5%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:13.022271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.85
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.60489607
Coefficient of variation (CV)5.6456966
Kurtosis76.914112
Mean0.10714286
Median Absolute Deviation (MAD)0
Skewness8.1332385
Sum39
Variance0.36589925
MonotonicityNot monotonic
2024-04-30T04:41:13.121488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 345
62.5%
1 11
 
2.0%
2 4
 
0.7%
7 1
 
0.2%
3 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
(Missing) 188
34.1%
ValueCountFrequency (%)
0 345
62.5%
1 11
 
2.0%
2 4
 
0.7%
3 1
 
0.2%
4 1
 
0.2%
6 1
 
0.2%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
2 4
 
0.7%
1 11
 
2.0%
0 345
62.5%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
임대
253 
<NA>
212 
자가
87 

Length

Max length4
Median length2
Mean length2.7681159
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 (%)
임대 253
45.8%
<NA> 212
38.4%
자가 87
 
15.8%

Length

2024-04-30T04:41:13.237652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:41:13.352377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 253
45.8%
na 212
38.4%
자가 87
 
15.8%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)16.5%
Missing473
Missing (%)85.7%
Infinite0
Infinite (%)0.0%
Mean14088608
Minimum0
Maximum2 × 108
Zeros56
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:13.437060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310000000
95-th percentile73000000
Maximum2 × 108
Range2 × 108
Interquartile range (IQR)10000000

Descriptive statistics

Standard deviation33603720
Coefficient of variation (CV)2.3851697
Kurtosis14.067261
Mean14088608
Median Absolute Deviation (MAD)0
Skewness3.4838108
Sum1.113 × 109
Variance1.12921 × 1015
MonotonicityNot monotonic
2024-04-30T04:41:13.539066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 56
 
10.1%
30000000 4
 
0.7%
40000000 3
 
0.5%
10000000 3
 
0.5%
100000000 2
 
0.4%
20000000 2
 
0.4%
15000000 2
 
0.4%
70000000 2
 
0.4%
200000000 1
 
0.2%
28000000 1
 
0.2%
Other values (3) 3
 
0.5%
(Missing) 473
85.7%
ValueCountFrequency (%)
0 56
10.1%
5000000 1
 
0.2%
10000000 3
 
0.5%
15000000 2
 
0.4%
20000000 2
 
0.4%
28000000 1
 
0.2%
30000000 4
 
0.7%
40000000 3
 
0.5%
60000000 1
 
0.2%
70000000 2
 
0.4%
ValueCountFrequency (%)
200000000 1
 
0.2%
140000000 1
 
0.2%
100000000 2
0.4%
70000000 2
0.4%
60000000 1
 
0.2%
40000000 3
0.5%
30000000 4
0.7%
28000000 1
 
0.2%
20000000 2
0.4%
15000000 2
0.4%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)26.0%
Missing475
Missing (%)86.1%
Infinite0
Infinite (%)0.0%
Mean585584.42
Minimum0
Maximum7940000
Zeros57
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:13.651745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3240000
95-th percentile3000000
Maximum7940000
Range7940000
Interquartile range (IQR)240000

Descriptive statistics

Standard deviation1324949.3
Coefficient of variation (CV)2.2626103
Kurtosis12.807998
Mean585584.42
Median Absolute Deviation (MAD)0
Skewness3.202521
Sum45090000
Variance1.7554908 × 1012
MonotonicityNot monotonic
2024-04-30T04:41:13.748091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 57
 
10.3%
3000000 2
 
0.4%
2600000 1
 
0.2%
2700000 1
 
0.2%
1600000 1
 
0.2%
1000000 1
 
0.2%
1500000 1
 
0.2%
4100000 1
 
0.2%
1200000 1
 
0.2%
500000 1
 
0.2%
Other values (10) 10
 
1.8%
(Missing) 475
86.1%
ValueCountFrequency (%)
0 57
10.3%
240000 1
 
0.2%
500000 1
 
0.2%
700000 1
 
0.2%
1000000 1
 
0.2%
1100000 1
 
0.2%
1200000 1
 
0.2%
1350000 1
 
0.2%
1500000 1
 
0.2%
1600000 1
 
0.2%
ValueCountFrequency (%)
7940000 1
0.2%
4500000 1
0.2%
4100000 1
0.2%
3000000 2
0.4%
2700000 1
0.2%
2600000 1
0.2%
2500000 1
0.2%
2000000 1
0.2%
1800000 1
0.2%
1760000 1
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing33
Missing (%)6.0%
Memory size1.2 KiB
False
519 
(Missing)
 
33
ValueCountFrequency (%)
False 519
94.0%
(Missing) 33
 
6.0%
2024-04-30T04:41:13.844031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)5.8%
Missing33
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean2.5373988
Minimum0
Maximum180
Zeros490
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-30T04:41:13.939310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.4
Maximum180
Range180
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.711914
Coefficient of variation (CV)6.192134
Kurtosis82.21798
Mean2.5373988
Median Absolute Deviation (MAD)0
Skewness8.6065543
Sum1316.91
Variance246.86423
MonotonicityNot monotonic
2024-04-30T04:41:14.049904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 490
88.8%
30.0 1
 
0.2%
15.0 1
 
0.2%
180.0 1
 
0.2%
15.46 1
 
0.2%
20.0 1
 
0.2%
6.0 1
 
0.2%
1.73 1
 
0.2%
94.56 1
 
0.2%
52.8 1
 
0.2%
Other values (20) 20
 
3.6%
(Missing) 33
 
6.0%
ValueCountFrequency (%)
0.0 490
88.8%
1.73 1
 
0.2%
2.0 1
 
0.2%
6.0 1
 
0.2%
10.0 1
 
0.2%
12.0 1
 
0.2%
13.0 1
 
0.2%
13.12 1
 
0.2%
14.0 1
 
0.2%
15.0 1
 
0.2%
ValueCountFrequency (%)
180.0 1
0.2%
177.38 1
0.2%
138.4 1
0.2%
130.91 1
0.2%
94.56 1
0.2%
76.3 1
0.2%
52.8 1
0.2%
47.36 1
0.2%
46.6 1
0.2%
40.0 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing552
Missing (%)100.0%
Memory size5.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-106-1970-0144319700505<NA>3폐업2폐업20001229<NA><NA><NA>02 56701715,395.00137857서울특별시 서초구 서초동 1322-1번지<NA><NA>롯데칠성음료(주)2000-12-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업202004.369537443715.709197식품제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132100003210000-106-1981-0021019810819<NA>3폐업2폐업20020220<NA><NA><NA>02 5933578.00137829서울특별시 서초구 방배동 767-1번지<NA><NA>강남식품2002-07-05 00:00:00I2018-08-31 23:59:59.0식품제조가공업198592.57239443636.163372식품제조가공업22기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
232100003210000-106-1984-0022519840625<NA>3폐업2폐업19961015<NA><NA><NA>02 591170415.60137030서울특별시 서초구 잠원동 132-15번지<NA><NA>낙원2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332100003210000-106-1987-0022619870601<NA>3폐업2폐업19960819<NA><NA><NA>02 012.95137040서울특별시 서초구 반포동 398-2번지<NA><NA>풀무원식품2002-07-05 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
432100003210000-106-1987-0024219870303<NA>3폐업2폐업19950120<NA><NA><NA>02058621261,032.84137871서울특별시 서초구 서초동 1519-6번지<NA><NA>다복식품2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업200459.271068442546.887873식품제조가공업24기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532100003210000-106-1988-0019519881031<NA>3폐업2폐업19980316<NA><NA><NA>02 547054628.33137808서울특별시 서초구 반포동 703-2번지<NA><NA>영생흑염소2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업201587.645389445318.400304식품제조가공업11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632100003210000-106-1989-0021119890607<NA>3폐업2폐업20071226<NA><NA><NA>02 5348829.00137829서울특별시 서초구 방배동 767-1번지 남부시장<NA><NA>제일식품2004-05-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업198592.57239443636.163372식품제조가공업11기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
732100003210000-106-1989-0021719890418<NA>3폐업2폐업19980321<NA><NA><NA>02 585665926.00137887서울특별시 서초구 양재동 11-42번지<NA><NA>(주)희심2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업12기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832100003210000-106-1991-0024419910710<NA>3폐업2폐업19931102<NA><NA><NA>02 58409231,041.71137876서울특별시 서초구 서초동 1589-3번지<NA><NA>(주)부흥윈첼도우넛2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업201045.417717442539.95475식품제조가공업32기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932100003210000-106-1991-0024719910408<NA>3폐업2폐업20051104<NA><NA><NA>02 5639191162.22137896서울특별시 서초구 양재동 306-4번지<NA><NA>(주)고궁2004-05-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업203885.771426441283.306743식품제조가공업22주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
54232100003210000-106-2022-000022022-03-28<NA>3폐업2폐업2023-02-14<NA><NA><NA>02 532 372196.76137-802서울특별시 서초구 반포동 51-12 지하1층서울특별시 서초구 서초중앙로 215, 지하1층 (반포동)6593그린팜박스2023-02-14 09:56:40U2022-12-01 23:06:00.0기타 식품제조가공업200961.285922444290.367052<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54332100003210000-106-2022-000032022-04-28<NA>3폐업2폐업2023-07-20<NA><NA><NA><NA>66.00137-878서울특별시 서초구 서초동 1621-26 지하1층호서울특별시 서초구 서초중앙로6길 25, 지하1층 (서초동)6643브라이언스 로스터리2023-07-20 15:26:59U2022-12-06 22:02:00.0기타 식품제조가공업201433.037995442710.004774<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54432100003210000-106-2022-000042022-05-23<NA>1영업/정상1영업<NA><NA><NA><NA>070 42541920326.01137-885서울특별시 서초구 서초동 1716-6 기영빌딩, 2층서울특별시 서초구 서초대로 277, 기영빌딩 2층 (서초동)6596플레이팅키친(교대점)2024-04-04 08:23:20U2023-12-04 00:06:00.0기타 식품제조가공업200976.724028443493.629145<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54532100003210000-106-2022-000052022-10-12<NA>3폐업2폐업2023-08-03<NA><NA><NA><NA>28.45137-974서울특별시 서초구 방배동 3001-1 디오슈페리움2 B2F04호서울특별시 서초구 동작대로 108, B2F층 04호 (방배동, 디오슈페리움2)6568큰벌덕2023-08-03 10:31:31U2022-12-08 00:05:00.0기타 식품제조가공업198394.433265442651.558949<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54632100003210000-106-2023-000012023-08-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>90.13137-865서울특별시 서초구 서초동 1443-4서울특별시 서초구 효령로 316-1, 3층 (서초동)6721주식회사 천년식향2023-10-04 15:19:55U2022-10-31 00:06:00.0기타 식품제조가공업201602.866496442581.652272<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54732100003210000-106-2023-000022023-08-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.10137-808서울특별시 서초구 반포동 703-6서울특별시 서초구 주흥길 82, 1층 103호 (반포동)6534로스톨로지2023-08-21 17:56:53I2022-12-07 22:03:00.0기타 식품제조가공업201547.599086445279.178568<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54832100003210000-106-2023-000032023-12-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.00137-893서울특별시 서초구 양재동 219-1 파사디서울특별시 서초구 매헌로3길 2, 파사디 1층 (양재동)6772몽거2023-12-26 13:07:39I2022-11-01 22:08:00.0기타 식품제조가공업203000.92305440151.798837<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54932100003210000-106-2024-000012024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.00137-874서울특별시 서초구 서초동 1571-14 우성빌딩서울특별시 서초구 반포대로30길 70, 우성빌딩 (서초동)6645미니말레 뢰스터리2024-02-01 10:43:18I2023-12-02 00:03:00.0기타 식품제조가공업201020.72609443361.286772<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55032100003210000-106-2024-000022024-03-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>161.73137-903서울특별시 서초구 잠원동 27-1서울특별시 서초구 강남대로97길 7, 프로빌딩1 (잠원동)6526프로간장게장2024-03-11 13:16:24I2023-12-02 23:03:00.0기타 식품제조가공업201624.527919445816.604694<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55132100003210000-106-2024-000032024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.60137-829서울특별시 서초구 방배동 769-24서울특별시 서초구 방배중앙로 168 (방배동)6556루베르 로스터리(RUBER ROASTERY HAUS)2024-03-29 12:02:01I2023-12-02 21:01:00.0기타 식품제조가공업198723.66875443552.067631<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>