Overview

Dataset statistics

Number of variables44
Number of observations1646
Missing cells19013
Missing cells (%)26.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory604.5 KiB
Average record size in memory376.1 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18424/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (71.3%)Imbalance
등급구분명 is highly imbalanced (73.7%)Imbalance
총인원 is highly imbalanced (71.4%)Imbalance
본사종업원수 is highly imbalanced (71.2%)Imbalance
공장사무직종업원수 is highly imbalanced (71.2%)Imbalance
공장판매직종업원수 is highly imbalanced (71.2%)Imbalance
공장생산직종업원수 is highly imbalanced (71.2%)Imbalance
보증액 is highly imbalanced (71.2%)Imbalance
월세액 is highly imbalanced (71.2%)Imbalance
다중이용업소여부 is highly imbalanced (89.4%)Imbalance
인허가취소일자 has 1646 (100.0%) missing valuesMissing
폐업일자 has 460 (27.9%) missing valuesMissing
휴업시작일자 has 1646 (100.0%) missing valuesMissing
휴업종료일자 has 1646 (100.0%) missing valuesMissing
재개업일자 has 1646 (100.0%) missing valuesMissing
전화번호 has 966 (58.7%) missing valuesMissing
소재지면적 has 224 (13.6%) missing valuesMissing
도로명주소 has 153 (9.3%) missing valuesMissing
도로명우편번호 has 164 (10.0%) missing valuesMissing
남성종사자수 has 1362 (82.7%) missing valuesMissing
여성종사자수 has 1362 (82.7%) missing valuesMissing
건물소유구분명 has 1646 (100.0%) missing valuesMissing
다중이용업소여부 has 565 (34.3%) missing valuesMissing
시설총규모 has 565 (34.3%) missing valuesMissing
전통업소지정번호 has 1646 (100.0%) missing valuesMissing
전통업소주된음식 has 1646 (100.0%) missing valuesMissing
홈페이지 has 1646 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 32.87165802)Skewed
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
건물소유구분명 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 268 (16.3%) zerosZeros
여성종사자수 has 261 (15.9%) zerosZeros
시설총규모 has 51 (3.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:25:31.866655
Analysis finished2024-05-11 06:25:34.002382
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
3220000
1646 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 1646
100.0%

Length

2024-05-11T15:25:34.155152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:34.372059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 1646
100.0%

관리번호
Text

UNIQUE 

Distinct1646
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2024-05-11T15:25:34.738556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters36212
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

Unique1646 ?
Unique (%)100.0%

Sample

1st row3220000-121-1978-02821
2nd row3220000-121-1979-00001
3rd row3220000-121-1982-02460
4th row3220000-121-1983-02575
5th row3220000-121-1983-02837
ValueCountFrequency (%)
3220000-121-1978-02821 1
 
0.1%
3220000-121-2020-00016 1
 
0.1%
3220000-121-2020-00026 1
 
0.1%
3220000-121-2020-00025 1
 
0.1%
3220000-121-2020-00024 1
 
0.1%
3220000-121-2020-00023 1
 
0.1%
3220000-121-2020-00022 1
 
0.1%
3220000-121-2020-00021 1
 
0.1%
3220000-121-2020-00020 1
 
0.1%
3220000-121-2020-00019 1
 
0.1%
Other values (1636) 1636
99.4%
2024-05-11T15:25:35.282397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13433
37.1%
2 7814
21.6%
- 4938
 
13.6%
1 4875
 
13.5%
3 2314
 
6.4%
9 544
 
1.5%
4 506
 
1.4%
5 488
 
1.3%
6 463
 
1.3%
7 427
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31274
86.4%
Dash Punctuation 4938
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13433
43.0%
2 7814
25.0%
1 4875
 
15.6%
3 2314
 
7.4%
9 544
 
1.7%
4 506
 
1.6%
5 488
 
1.6%
6 463
 
1.5%
7 427
 
1.4%
8 410
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 4938
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13433
37.1%
2 7814
21.6%
- 4938
 
13.6%
1 4875
 
13.5%
3 2314
 
6.4%
9 544
 
1.5%
4 506
 
1.4%
5 488
 
1.3%
6 463
 
1.3%
7 427
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13433
37.1%
2 7814
21.6%
- 4938
 
13.6%
1 4875
 
13.5%
3 2314
 
6.4%
9 544
 
1.5%
4 506
 
1.4%
5 488
 
1.3%
6 463
 
1.3%
7 427
 
1.2%
Distinct1359
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
Minimum1978-11-16 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:25:35.517858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:35.723636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
3
1186 
1
460 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1186
72.1%
1 460
 
27.9%

Length

2024-05-11T15:25:35.950891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:36.164621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1186
72.1%
1 460
 
27.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
폐업
1186 
영업/정상
460 

Length

Max length5
Median length2
Mean length2.8383961
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1186
72.1%
영업/정상 460
 
27.9%

Length

2024-05-11T15:25:36.356648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:36.545569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1186
72.1%
영업/정상 460
 
27.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2
1186 
1
460 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1186
72.1%
1 460
 
27.9%

Length

2024-05-11T15:25:36.729786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:36.882035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1186
72.1%
1 460
 
27.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
폐업
1186 
영업
460 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1186
72.1%
영업 460
 
27.9%

Length

2024-05-11T15:25:37.121968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:37.820646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1186
72.1%
영업 460
 
27.9%

폐업일자
Date

MISSING 

Distinct909
Distinct (%)76.6%
Missing460
Missing (%)27.9%
Memory size13.0 KiB
Minimum2005-11-29 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T15:25:38.011450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:38.282862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

전화번호
Text

MISSING 

Distinct583
Distinct (%)85.7%
Missing966
Missing (%)58.7%
Memory size13.0 KiB
2024-05-11T15:25:38.757521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.845588
Min length2

Characters and Unicode

Total characters7375
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

Unique520 ?
Unique (%)76.5%

Sample

1st row02 5485892
2nd row02 5772728
3rd row0205422952
4th row0205571221
5th row02 5734718
ValueCountFrequency (%)
02 431
31.1%
070 42
 
3.0%
031 21
 
1.5%
525 10
 
0.7%
88609377 9
 
0.6%
545 9
 
0.6%
516 8
 
0.6%
511 7
 
0.5%
517 7
 
0.5%
34598000 6
 
0.4%
Other values (657) 838
60.4%
2024-05-11T15:25:39.397948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1214
16.5%
2 1064
14.4%
1016
13.8%
5 758
10.3%
4 558
7.6%
1 514
7.0%
7 500
6.8%
3 496
6.7%
6 488
6.6%
8 446
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6359
86.2%
Space Separator 1016
 
13.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1214
19.1%
2 1064
16.7%
5 758
11.9%
4 558
8.8%
1 514
8.1%
7 500
7.9%
3 496
7.8%
6 488
7.7%
8 446
 
7.0%
9 321
 
5.0%
Space Separator
ValueCountFrequency (%)
1016
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7375
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1214
16.5%
2 1064
14.4%
1016
13.8%
5 758
10.3%
4 558
7.6%
1 514
7.0%
7 500
6.8%
3 496
6.7%
6 488
6.6%
8 446
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7375
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1214
16.5%
2 1064
14.4%
1016
13.8%
5 758
10.3%
4 558
7.6%
1 514
7.0%
7 500
6.8%
3 496
6.7%
6 488
6.6%
8 446
 
6.0%

소재지면적
Text

MISSING 

Distinct866
Distinct (%)60.9%
Missing224
Missing (%)13.6%
Memory size13.0 KiB
2024-05-11T15:25:40.014574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.9444444
Min length3

Characters and Unicode

Total characters7031
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

Unique693 ?
Unique (%)48.7%

Sample

1st row68.09
2nd row70.09
3rd row48.65
4th row52.30
5th row66.24
ValueCountFrequency (%)
3.30 43
 
3.0%
6.60 31
 
2.2%
10.00 30
 
2.1%
00 18
 
1.3%
33.00 17
 
1.2%
9.90 17
 
1.2%
30.00 15
 
1.1%
6.00 14
 
1.0%
5.00 14
 
1.0%
16.50 12
 
0.8%
Other values (856) 1211
85.2%
2024-05-11T15:25:40.853458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1422
20.2%
0 1378
19.6%
1 649
9.2%
3 584
8.3%
2 577
8.2%
6 501
 
7.1%
5 485
 
6.9%
4 396
 
5.6%
8 377
 
5.4%
9 371
 
5.3%
Other values (2) 291
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5608
79.8%
Other Punctuation 1423
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1378
24.6%
1 649
11.6%
3 584
10.4%
2 577
10.3%
6 501
 
8.9%
5 485
 
8.6%
4 396
 
7.1%
8 377
 
6.7%
9 371
 
6.6%
7 290
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 1422
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 7031
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1422
20.2%
0 1378
19.6%
1 649
9.2%
3 584
8.3%
2 577
8.2%
6 501
 
7.1%
5 485
 
6.9%
4 396
 
5.6%
8 377
 
5.4%
9 371
 
5.3%
Other values (2) 291
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7031
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1422
20.2%
0 1378
19.6%
1 649
9.2%
3 584
8.3%
2 577
8.2%
6 501
 
7.1%
5 485
 
6.9%
4 396
 
5.6%
8 377
 
5.4%
9 371
 
5.3%
Other values (2) 291
 
4.1%
Distinct282
Distinct (%)17.2%
Missing4
Missing (%)0.2%
Memory size13.0 KiB
2024-05-11T15:25:41.311892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2466504
Min length6

Characters and Unicode

Total characters10257
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

Unique79 ?
Unique (%)4.8%

Sample

1st row135894
2nd row135838
3rd row135952
4th row135907
5th row135834
ValueCountFrequency (%)
135090 99
 
6.0%
135902 73
 
4.4%
135724 68
 
4.1%
135730 66
 
4.0%
135-902 66
 
4.0%
135-730 57
 
3.5%
135900 55
 
3.3%
135-724 46
 
2.8%
135998 29
 
1.8%
135906 29
 
1.8%
Other values (272) 1054
64.2%
2024-05-11T15:25:41.979536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1994
19.4%
5 1905
18.6%
1 1872
18.3%
9 978
9.5%
0 904
8.8%
8 789
 
7.7%
2 456
 
4.4%
7 432
 
4.2%
- 405
 
3.9%
4 327
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9852
96.1%
Dash Punctuation 405
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1994
20.2%
5 1905
19.3%
1 1872
19.0%
9 978
9.9%
0 904
9.2%
8 789
 
8.0%
2 456
 
4.6%
7 432
 
4.4%
4 327
 
3.3%
6 195
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 405
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10257
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1994
19.4%
5 1905
18.6%
1 1872
18.3%
9 978
9.5%
0 904
8.8%
8 789
 
7.7%
2 456
 
4.4%
7 432
 
4.2%
- 405
 
3.9%
4 327
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1994
19.4%
5 1905
18.6%
1 1872
18.3%
9 978
9.5%
0 904
8.8%
8 789
 
7.7%
2 456
 
4.4%
7 432
 
4.2%
- 405
 
3.9%
4 327
 
3.2%
Distinct1040
Distinct (%)63.3%
Missing4
Missing (%)0.2%
Memory size13.0 KiB
2024-05-11T15:25:42.413730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length25.507308
Min length16

Characters and Unicode

Total characters41883
Distinct characters312
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

Unique943 ?
Unique (%)57.4%

Sample

1st row서울특별시 강남구 신사동 614-7번지
2nd row서울특별시 강남구 대치동 626-0번지 청실상가117호
3rd row서울특별시 강남구 청담동 50-2번지
4th row서울특별시 강남구 역삼동 604-11
5th row서울특별시 강남구 대치동 66-0번지 쌍용종합상가 가동
ValueCountFrequency (%)
서울특별시 1642
20.8%
강남구 1642
20.8%
압구정동 364
 
4.6%
삼성동 334
 
4.2%
신사동 198
 
2.5%
역삼동 184
 
2.3%
대치동 166
 
2.1%
현대백화점 153
 
1.9%
지상1층 139
 
1.8%
갤러리아백화점 137
 
1.7%
Other values (1324) 2933
37.2%
2024-05-11T15:25:42.986237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7305
 
17.4%
2014
 
4.8%
1686
 
4.0%
1674
 
4.0%
1667
 
4.0%
1662
 
4.0%
1 1661
 
4.0%
1649
 
3.9%
1644
 
3.9%
1642
 
3.9%
Other values (302) 19279
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25938
61.9%
Decimal Number 7307
 
17.4%
Space Separator 7305
 
17.4%
Dash Punctuation 1097
 
2.6%
Uppercase Letter 136
 
0.3%
Other Punctuation 52
 
0.1%
Lowercase Letter 26
 
0.1%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2014
 
7.8%
1686
 
6.5%
1674
 
6.5%
1667
 
6.4%
1662
 
6.4%
1649
 
6.4%
1644
 
6.3%
1642
 
6.3%
1642
 
6.3%
1234
 
4.8%
Other values (250) 9424
36.3%
Uppercase Letter
ValueCountFrequency (%)
E 22
16.2%
B 20
14.7%
S 19
14.0%
T 13
9.6%
C 12
8.8%
A 6
 
4.4%
M 5
 
3.7%
O 5
 
3.7%
K 4
 
2.9%
G 4
 
2.9%
Other values (10) 26
19.1%
Lowercase Letter
ValueCountFrequency (%)
a 5
19.2%
n 4
15.4%
e 4
15.4%
l 3
11.5%
g 1
 
3.8%
i 1
 
3.8%
h 1
 
3.8%
s 1
 
3.8%
u 1
 
3.8%
o 1
 
3.8%
Other values (4) 4
15.4%
Decimal Number
ValueCountFrequency (%)
1 1661
22.7%
9 929
12.7%
4 921
12.6%
2 758
10.4%
5 711
9.7%
7 639
 
8.7%
6 503
 
6.9%
0 484
 
6.6%
3 396
 
5.4%
8 305
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 38
73.1%
. 13
 
25.0%
? 1
 
1.9%
Space Separator
ValueCountFrequency (%)
7305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1097
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25938
61.9%
Common 15783
37.7%
Latin 162
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2014
 
7.8%
1686
 
6.5%
1674
 
6.5%
1667
 
6.4%
1662
 
6.4%
1649
 
6.4%
1644
 
6.3%
1642
 
6.3%
1642
 
6.3%
1234
 
4.8%
Other values (250) 9424
36.3%
Latin
ValueCountFrequency (%)
E 22
13.6%
B 20
 
12.3%
S 19
 
11.7%
T 13
 
8.0%
C 12
 
7.4%
A 6
 
3.7%
M 5
 
3.1%
a 5
 
3.1%
O 5
 
3.1%
n 4
 
2.5%
Other values (24) 51
31.5%
Common
ValueCountFrequency (%)
7305
46.3%
1 1661
 
10.5%
- 1097
 
7.0%
9 929
 
5.9%
4 921
 
5.8%
2 758
 
4.8%
5 711
 
4.5%
7 639
 
4.0%
6 503
 
3.2%
0 484
 
3.1%
Other values (8) 775
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25938
61.9%
ASCII 15945
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7305
45.8%
1 1661
 
10.4%
- 1097
 
6.9%
9 929
 
5.8%
4 921
 
5.8%
2 758
 
4.8%
5 711
 
4.5%
7 639
 
4.0%
6 503
 
3.2%
0 484
 
3.0%
Other values (42) 937
 
5.9%
Hangul
ValueCountFrequency (%)
2014
 
7.8%
1686
 
6.5%
1674
 
6.5%
1667
 
6.4%
1662
 
6.4%
1649
 
6.4%
1644
 
6.3%
1642
 
6.3%
1642
 
6.3%
1234
 
4.8%
Other values (250) 9424
36.3%

도로명주소
Text

MISSING 

Distinct1055
Distinct (%)70.7%
Missing153
Missing (%)9.3%
Memory size13.0 KiB
2024-05-11T15:25:43.561484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length52
Mean length37.054253
Min length22

Characters and Unicode

Total characters55322
Distinct characters347
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

Unique993 ?
Unique (%)66.5%

Sample

1st row서울특별시 강남구 압구정로 212 (신사동)
2nd row서울특별시 강남구 남부순환로 2917 (대치동,청실상가117호)
3rd row서울특별시 강남구 봉은사로 150 (역삼동)
4th row서울특별시 강남구 역삼로 452 (대치동)
5th row서울특별시 강남구 언주로 317 (역삼동)
ValueCountFrequency (%)
서울특별시 1493
 
14.5%
강남구 1493
 
14.5%
지하1층 647
 
6.3%
압구정로 359
 
3.5%
압구정동 333
 
3.2%
지상1층 332
 
3.2%
삼성동 289
 
2.8%
테헤란로 217
 
2.1%
517 189
 
1.8%
현대백화점 188
 
1.8%
Other values (1314) 4746
46.1%
2024-05-11T15:25:44.267944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8801
 
15.9%
1 2982
 
5.4%
2287
 
4.1%
, 1870
 
3.4%
1681
 
3.0%
1636
 
3.0%
1588
 
2.9%
1524
 
2.8%
1512
 
2.7%
1506
 
2.7%
Other values (337) 29935
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33091
59.8%
Space Separator 8801
 
15.9%
Decimal Number 8012
 
14.5%
Other Punctuation 1882
 
3.4%
Open Punctuation 1502
 
2.7%
Close Punctuation 1502
 
2.7%
Uppercase Letter 358
 
0.6%
Dash Punctuation 95
 
0.2%
Lowercase Letter 73
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2287
 
6.9%
1681
 
5.1%
1636
 
4.9%
1588
 
4.8%
1524
 
4.6%
1512
 
4.6%
1506
 
4.6%
1495
 
4.5%
1495
 
4.5%
1493
 
4.5%
Other values (277) 16874
51.0%
Uppercase Letter
ValueCountFrequency (%)
B 64
17.9%
S 56
15.6%
E 53
14.8%
T 47
13.1%
W 35
9.8%
C 23
 
6.4%
A 12
 
3.4%
R 11
 
3.1%
D 8
 
2.2%
H 7
 
2.0%
Other values (13) 42
11.7%
Lowercase Letter
ValueCountFrequency (%)
e 12
16.4%
a 10
13.7%
s 8
11.0%
l 8
11.0%
w 7
9.6%
t 7
9.6%
n 5
6.8%
c 3
 
4.1%
i 3
 
4.1%
u 2
 
2.7%
Other values (8) 8
11.0%
Decimal Number
ValueCountFrequency (%)
1 2982
37.2%
3 885
 
11.0%
5 805
 
10.0%
2 773
 
9.6%
0 665
 
8.3%
4 562
 
7.0%
6 475
 
5.9%
7 450
 
5.6%
8 228
 
2.8%
9 187
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 1870
99.4%
. 10
 
0.5%
? 1
 
0.1%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8801
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1502
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1502
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33091
59.8%
Common 21800
39.4%
Latin 431
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2287
 
6.9%
1681
 
5.1%
1636
 
4.9%
1588
 
4.8%
1524
 
4.6%
1512
 
4.6%
1506
 
4.6%
1495
 
4.5%
1495
 
4.5%
1493
 
4.5%
Other values (277) 16874
51.0%
Latin
ValueCountFrequency (%)
B 64
14.8%
S 56
13.0%
E 53
12.3%
T 47
10.9%
W 35
 
8.1%
C 23
 
5.3%
A 12
 
2.8%
e 12
 
2.8%
R 11
 
2.6%
a 10
 
2.3%
Other values (31) 108
25.1%
Common
ValueCountFrequency (%)
8801
40.4%
1 2982
 
13.7%
, 1870
 
8.6%
( 1502
 
6.9%
) 1502
 
6.9%
3 885
 
4.1%
5 805
 
3.7%
2 773
 
3.5%
0 665
 
3.1%
4 562
 
2.6%
Other values (9) 1453
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33091
59.8%
ASCII 22231
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8801
39.6%
1 2982
 
13.4%
, 1870
 
8.4%
( 1502
 
6.8%
) 1502
 
6.8%
3 885
 
4.0%
5 805
 
3.6%
2 773
 
3.5%
0 665
 
3.0%
4 562
 
2.5%
Other values (50) 1884
 
8.5%
Hangul
ValueCountFrequency (%)
2287
 
6.9%
1681
 
5.1%
1636
 
4.9%
1588
 
4.8%
1524
 
4.6%
1512
 
4.6%
1506
 
4.6%
1495
 
4.5%
1495
 
4.5%
1493
 
4.5%
Other values (277) 16874
51.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct276
Distinct (%)18.6%
Missing164
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean6124.5
Minimum6000
Maximum6377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.6 KiB
2024-05-11T15:25:44.459741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000
5-th percentile6001
Q16017
median6122
Q36199.75
95-th percentile6318.9
Maximum6377
Range377
Interquartile range (IQR)182.75

Descriptive statistics

Standard deviation108.37191
Coefficient of variation (CV)0.017694817
Kurtosis-0.90337795
Mean6124.5
Median Absolute Deviation (MAD)96
Skewness0.47885742
Sum9076509
Variance11744.47
MonotonicityNot monotonic
2024-05-11T15:25:44.654486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6164 236
 
14.3%
6001 170
 
10.3%
6008 161
 
9.8%
6206 30
 
1.8%
6028 23
 
1.4%
6018 19
 
1.2%
6029 16
 
1.0%
6019 13
 
0.8%
6017 12
 
0.7%
6280 12
 
0.7%
Other values (266) 790
48.0%
(Missing) 164
 
10.0%
ValueCountFrequency (%)
6000 2
 
0.1%
6001 170
10.3%
6002 6
 
0.4%
6004 2
 
0.1%
6005 1
 
0.1%
6006 2
 
0.1%
6008 161
9.8%
6009 4
 
0.2%
6011 5
 
0.3%
6012 2
 
0.1%
ValueCountFrequency (%)
6377 1
 
0.1%
6376 2
 
0.1%
6374 3
0.2%
6373 3
0.2%
6372 1
 
0.1%
6370 3
0.2%
6369 4
0.2%
6367 6
0.4%
6366 1
 
0.1%
6365 2
 
0.1%
Distinct1323
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2024-05-11T15:25:44.963453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length9.0218712
Min length1

Characters and Unicode

Total characters14850
Distinct characters623
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

Unique1143 ?
Unique (%)69.4%

Sample

1st row크라운베이커리압구정
2nd row크라운베이커리 대치제일직영점
3rd row빵굼터
4th row삼정제과
5th row권상원과자점
ValueCountFrequency (%)
파리바게뜨 47
 
1.9%
뚜레쥬르 25
 
1.0%
압구정점 23
 
0.9%
베이커리 23
 
0.9%
주식회사 19
 
0.8%
던킨도너츠 18
 
0.7%
파리바게트 14
 
0.6%
카페 13
 
0.5%
대치점 12
 
0.5%
현대백화점 12
 
0.5%
Other values (1537) 2259
91.6%
2024-05-11T15:25:45.721671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
822
 
5.5%
532
 
3.6%
) 504
 
3.4%
( 504
 
3.4%
489
 
3.3%
443
 
3.0%
340
 
2.3%
301
 
2.0%
269
 
1.8%
248
 
1.7%
Other values (613) 10398
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11812
79.5%
Space Separator 822
 
5.5%
Lowercase Letter 646
 
4.4%
Close Punctuation 504
 
3.4%
Open Punctuation 504
 
3.4%
Uppercase Letter 431
 
2.9%
Decimal Number 100
 
0.7%
Other Punctuation 29
 
0.2%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
532
 
4.5%
489
 
4.1%
443
 
3.8%
340
 
2.9%
301
 
2.5%
269
 
2.3%
248
 
2.1%
234
 
2.0%
211
 
1.8%
184
 
1.6%
Other values (543) 8561
72.5%
Lowercase Letter
ValueCountFrequency (%)
e 90
13.9%
o 64
 
9.9%
a 58
 
9.0%
l 48
 
7.4%
r 47
 
7.3%
n 43
 
6.7%
i 43
 
6.7%
t 37
 
5.7%
u 29
 
4.5%
s 27
 
4.2%
Other values (14) 160
24.8%
Uppercase Letter
ValueCountFrequency (%)
A 48
 
11.1%
E 36
 
8.4%
B 36
 
8.4%
N 29
 
6.7%
O 27
 
6.3%
C 27
 
6.3%
T 26
 
6.0%
S 25
 
5.8%
P 23
 
5.3%
R 21
 
4.9%
Other values (14) 133
30.9%
Decimal Number
ValueCountFrequency (%)
2 21
21.0%
1 18
18.0%
3 13
13.0%
0 12
12.0%
4 11
11.0%
5 9
9.0%
7 7
 
7.0%
8 5
 
5.0%
9 3
 
3.0%
6 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 10
34.5%
? 7
24.1%
& 3
 
10.3%
! 3
 
10.3%
' 2
 
6.9%
/ 2
 
6.9%
@ 1
 
3.4%
, 1
 
3.4%
Space Separator
ValueCountFrequency (%)
822
100.0%
Close Punctuation
ValueCountFrequency (%)
) 504
100.0%
Open Punctuation
ValueCountFrequency (%)
( 504
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11812
79.5%
Common 1961
 
13.2%
Latin 1077
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
532
 
4.5%
489
 
4.1%
443
 
3.8%
340
 
2.9%
301
 
2.5%
269
 
2.3%
248
 
2.1%
234
 
2.0%
211
 
1.8%
184
 
1.6%
Other values (543) 8561
72.5%
Latin
ValueCountFrequency (%)
e 90
 
8.4%
o 64
 
5.9%
a 58
 
5.4%
l 48
 
4.5%
A 48
 
4.5%
r 47
 
4.4%
n 43
 
4.0%
i 43
 
4.0%
t 37
 
3.4%
E 36
 
3.3%
Other values (38) 563
52.3%
Common
ValueCountFrequency (%)
822
41.9%
) 504
25.7%
( 504
25.7%
2 21
 
1.1%
1 18
 
0.9%
3 13
 
0.7%
0 12
 
0.6%
4 11
 
0.6%
. 10
 
0.5%
5 9
 
0.5%
Other values (12) 37
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11812
79.5%
ASCII 3038
 
20.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
822
27.1%
) 504
16.6%
( 504
16.6%
e 90
 
3.0%
o 64
 
2.1%
a 58
 
1.9%
l 48
 
1.6%
A 48
 
1.6%
r 47
 
1.5%
n 43
 
1.4%
Other values (60) 810
26.7%
Hangul
ValueCountFrequency (%)
532
 
4.5%
489
 
4.1%
443
 
3.8%
340
 
2.9%
301
 
2.5%
269
 
2.3%
248
 
2.1%
234
 
2.0%
211
 
1.8%
184
 
1.6%
Other values (543) 8561
72.5%
Distinct1563
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
Minimum1999-04-29 00:00:00
Maximum2024-05-09 15:42:37
2024-05-11T15:25:46.075174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:46.467986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
I
871 
U
775 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 871
52.9%
U 775
47.1%

Length

2024-05-11T15:25:46.717556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:46.885335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 871
52.9%
u 775
47.1%
Distinct624
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:25:47.091283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:47.351564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
제과점영업
1646 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 1646
100.0%

Length

2024-05-11T15:25:47.626647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:47.876541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 1646
100.0%

좌표정보(X)
Real number (ℝ)

Distinct788
Distinct (%)48.1%
Missing8
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean203922.02
Minimum201543.96
Maximum210037.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.6 KiB
2024-05-11T15:25:48.121238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201543.96
5-th percentile202025.55
Q1202676.54
median203520.97
Q3205130.59
95-th percentile206245.56
Maximum210037.99
Range8494.0229
Interquartile range (IQR)2454.049

Descriptive statistics

Standard deviation1473.6191
Coefficient of variation (CV)0.0072263855
Kurtosis1.5812691
Mean203922.02
Median Absolute Deviation (MAD)1162.4622
Skewness0.99174067
Sum3.3402427 × 108
Variance2171553.3
MonotonicityNot monotonic
2024-05-11T15:25:48.371753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205210.358779172 192
 
11.7%
202358.505687227 175
 
10.6%
203470.848439305 164
 
10.0%
205130.591678902 40
 
2.4%
204669.543366778 26
 
1.6%
204749.304517964 15
 
0.9%
205707.089399978 11
 
0.7%
206279.206641169 9
 
0.5%
203319.729227626 9
 
0.5%
204213.643236507 8
 
0.5%
Other values (778) 989
60.1%
(Missing) 8
 
0.5%
ValueCountFrequency (%)
201543.962547061 1
 
0.1%
201588.001969935 1
 
0.1%
201620.446225572 1
 
0.1%
201658.416590861 1
 
0.1%
201664.929814711 1
 
0.1%
201667.786866215 3
0.2%
201708.994700757 1
 
0.1%
201715.387381606 2
0.1%
201753.303709664 1
 
0.1%
201753.375869612 2
0.1%
ValueCountFrequency (%)
210037.985481183 1
0.1%
210005.675529724 1
0.1%
209792.411872683 1
0.1%
209423.649311203 1
0.1%
209349.691167499 1
0.1%
209246.667934188 2
0.1%
209246.406810922 1
0.1%
209235.004361179 1
0.1%
209205.687910519 1
0.1%
209148.486125918 2
0.1%

좌표정보(Y)
Real number (ℝ)

Distinct788
Distinct (%)48.1%
Missing8
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean445434.06
Minimum439882.12
Maximum447864.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.6 KiB
2024-05-11T15:25:48.665910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439882.12
5-th percentile442530.03
Q1444154.92
median445403.89
Q3447105.59
95-th percentile447369.58
Maximum447864.76
Range7982.6454
Interquartile range (IQR)2950.6734

Descriptive statistics

Standard deviation1634.4907
Coefficient of variation (CV)0.0036694337
Kurtosis-0.5146486
Mean445434.06
Median Absolute Deviation (MAD)1457.0925
Skewness-0.5413537
Sum7.2962099 × 108
Variance2671560
MonotonicityNot monotonic
2024-05-11T15:25:49.006488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445154.42225208 192
 
11.7%
447232.955697694 175
 
10.6%
447369.579851952 164
 
10.0%
445590.096837802 40
 
2.4%
443873.621189048 26
 
1.6%
443058.194678364 15
 
0.9%
443914.194133105 11
 
0.7%
443733.802684109 9
 
0.5%
444338.162235023 9
 
0.5%
444113.028210915 8
 
0.5%
Other values (778) 989
60.1%
(Missing) 8
 
0.5%
ValueCountFrequency (%)
439882.118303183 1
0.1%
440112.987487173 1
0.1%
440158.402062979 1
0.1%
440208.558412381 1
0.1%
440517.958320304 1
0.1%
440518.696295713 1
0.1%
440973.932558753 1
0.1%
441014.810920055 1
0.1%
441086.596187726 1
0.1%
441108.499651602 1
0.1%
ValueCountFrequency (%)
447864.763737276 7
 
0.4%
447782.51322707 1
 
0.1%
447748.161018109 1
 
0.1%
447708.404153773 1
 
0.1%
447663.86257666 3
 
0.2%
447521.520319158 1
 
0.1%
447369.579851952 164
10.0%
447366.539357322 1
 
0.1%
447352.637685553 1
 
0.1%
447334.651098516 1
 
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
제과점영업
1081 
<NA>
565 

Length

Max length5
Median length5
Mean length4.6567436
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 1081
65.7%
<NA> 565
34.3%

Length

2024-05-11T15:25:49.286486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:49.527840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 1081
65.7%
na 565
34.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.1%
Missing1362
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.11267606
Minimum0
Maximum6
Zeros268
Zeros (%)16.3%
Negative0
Negative (%)0.0%
Memory size14.6 KiB
2024-05-11T15:25:49.745538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.57753701
Coefficient of variation (CV)5.125641
Kurtosis54.429874
Mean0.11267606
Median Absolute Deviation (MAD)0
Skewness6.8662447
Sum32
Variance0.333549
MonotonicityNot monotonic
2024-05-11T15:25:50.033469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 268
 
16.3%
1 9
 
0.5%
2 3
 
0.2%
4 2
 
0.1%
3 1
 
0.1%
6 1
 
0.1%
(Missing) 1362
82.7%
ValueCountFrequency (%)
0 268
16.3%
1 9
 
0.5%
2 3
 
0.2%
3 1
 
0.1%
4 2
 
0.1%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 2
 
0.1%
3 1
 
0.1%
2 3
 
0.2%
1 9
 
0.5%
0 268
16.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.1%
Missing1362
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.19366197
Minimum0
Maximum8
Zeros261
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size14.6 KiB
2024-05-11T15:25:50.378925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.85
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8621376
Coefficient of variation (CV)4.4517651
Kurtosis51.136719
Mean0.19366197
Median Absolute Deviation (MAD)0
Skewness6.5791769
Sum55
Variance0.74328124
MonotonicityNot monotonic
2024-05-11T15:25:50.746635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 261
 
15.9%
2 11
 
0.7%
1 8
 
0.5%
8 2
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
(Missing) 1362
82.7%
ValueCountFrequency (%)
0 261
15.9%
1 8
 
0.5%
2 11
 
0.7%
4 1
 
0.1%
5 1
 
0.1%
8 2
 
0.1%
ValueCountFrequency (%)
8 2
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
2 11
 
0.7%
1 8
 
0.5%
0 261
15.9%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1441 
기타
163 
주택가주변
 
20
아파트지역
 
19
유흥업소밀집지역
 
3

Length

Max length8
Median length4
Mean length3.8329283
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1441
87.5%
기타 163
 
9.9%
주택가주변 20
 
1.2%
아파트지역 19
 
1.2%
유흥업소밀집지역 3
 
0.2%

Length

2024-05-11T15:25:51.026939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:51.272393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1441
87.5%
기타 163
 
9.9%
주택가주변 20
 
1.2%
아파트지역 19
 
1.2%
유흥업소밀집지역 3
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1448 
자율
 
144
기타
 
33
 
11
지도
 
8

Length

Max length4
Median length4
Mean length3.7515188
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1448
88.0%
자율 144
 
8.7%
기타 33
 
2.0%
11
 
0.7%
지도 8
 
0.5%
2
 
0.1%

Length

2024-05-11T15:25:51.529311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:51.736818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1448
88.0%
자율 144
 
8.7%
기타 33
 
2.0%
11
 
0.7%
지도 8
 
0.5%
2
 
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1310 
상수도전용
336 

Length

Max length5
Median length4
Mean length4.2041312
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1310
79.6%
상수도전용 336
 
20.4%

Length

2024-05-11T15:25:51.975932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:52.182329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1310
79.6%
상수도전용 336
 
20.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1564 
0
 
82

Length

Max length4
Median length4
Mean length3.8505468
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> 1564
95.0%
0 82
 
5.0%

Length

2024-05-11T15:25:52.382740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:53.000431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1564
95.0%
0 82
 
5.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1563 
0
 
83

Length

Max length4
Median length4
Mean length3.8487242
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> 1563
95.0%
0 83
 
5.0%

Length

2024-05-11T15:25:53.220494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:53.452786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1563
95.0%
0 83
 
5.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1563 
0
 
83

Length

Max length4
Median length4
Mean length3.8487242
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> 1563
95.0%
0 83
 
5.0%

Length

2024-05-11T15:25:53.684366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:53.936633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1563
95.0%
0 83
 
5.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1563 
0
 
83

Length

Max length4
Median length4
Mean length3.8487242
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> 1563
95.0%
0 83
 
5.0%

Length

2024-05-11T15:25:54.181936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:54.436215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1563
95.0%
0 83
 
5.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1563 
0
 
83

Length

Max length4
Median length4
Mean length3.8487242
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> 1563
95.0%
0 83
 
5.0%

Length

2024-05-11T15:25:54.663704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:54.882442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1563
95.0%
0 83
 
5.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1563 
0
 
83

Length

Max length4
Median length4
Mean length3.8487242
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> 1563
95.0%
0 83
 
5.0%

Length

2024-05-11T15:25:55.123803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:55.328017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1563
95.0%
0 83
 
5.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1563 
0
 
83

Length

Max length4
Median length4
Mean length3.8487242
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> 1563
95.0%
0 83
 
5.0%

Length

2024-05-11T15:25:55.538933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:55.775051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1563
95.0%
0 83
 
5.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing565
Missing (%)34.3%
Memory size3.3 KiB
False
1066 
True
 
15
(Missing)
565 
ValueCountFrequency (%)
False 1066
64.8%
True 15
 
0.9%
(Missing) 565
34.3%
2024-05-11T15:25:55.941773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct644
Distinct (%)59.6%
Missing565
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean222.38507
Minimum0
Maximum184133
Zeros51
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size14.6 KiB
2024-05-11T15:25:56.132935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.2
Q19.91
median32.06
Q366
95-th percentile182.16
Maximum184133
Range184133
Interquartile range (IQR)56.09

Descriptive statistics

Standard deviation5599.2038
Coefficient of variation (CV)25.177966
Kurtosis1080.6967
Mean222.38507
Median Absolute Deviation (MAD)24.06
Skewness32.871658
Sum240398.26
Variance31351083
MonotonicityNot monotonic
2024-05-11T15:25:56.388416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 51
 
3.1%
3.3 40
 
2.4%
6.6 29
 
1.8%
10.0 24
 
1.5%
9.9 15
 
0.9%
5.0 13
 
0.8%
33.0 13
 
0.8%
6.0 13
 
0.8%
3.0 11
 
0.7%
16.5 10
 
0.6%
Other values (634) 862
52.4%
(Missing) 565
34.3%
ValueCountFrequency (%)
0.0 51
3.1%
1.06 1
 
0.1%
1.65 1
 
0.1%
2.0 1
 
0.1%
2.2 1
 
0.1%
2.4 1
 
0.1%
2.5 2
 
0.1%
2.7 2
 
0.1%
2.8 2
 
0.1%
3.0 11
 
0.7%
ValueCountFrequency (%)
184133.0 1
0.1%
889.34 1
0.1%
547.88 1
0.1%
395.61 1
0.1%
338.06 1
0.1%
331.3 1
0.1%
326.94 1
0.1%
325.48 1
0.1%
320.82 1
0.1%
315.05 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1646
Missing (%)100.0%
Memory size14.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032200003220000-121-1978-0282119781116<NA>3폐업2폐업20130315<NA><NA><NA>02 548589268.09135894서울특별시 강남구 신사동 614-7번지서울특별시 강남구 압구정로 212 (신사동)6022크라운베이커리압구정2012-06-11 17:50:23I2018-08-31 23:59:59.0제과점영업202622.614428447287.24829제과점영업12주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N68.09<NA><NA><NA>
132200003220000-121-1979-0000119790716<NA>3폐업2폐업20120612<NA><NA><NA>02 577272870.09135838서울특별시 강남구 대치동 626-0번지 청실상가117호서울특별시 강남구 남부순환로 2917 (대치동,청실상가117호)6280크라운베이커리 대치제일직영점2012-06-12 09:20:47I2018-08-31 23:59:59.0제과점영업205154.638097443439.981645제과점영업11아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N70.09<NA><NA><NA>
232200003220000-121-1982-0246019820210<NA>3폐업2폐업20070115<NA><NA><NA>020542295248.65135952서울특별시 강남구 청담동 50-2번지<NA><NA>빵굼터2002-04-08 00:00:00I2018-08-31 23:59:59.0제과점영업204359.310905446886.095685제과점영업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N48.65<NA><NA><NA>
332200003220000-121-1983-0257519830805<NA>1영업/정상1영업<NA><NA><NA><NA>020557122152.30135907서울특별시 강남구 역삼동 604-11서울특별시 강남구 봉은사로 150 (역삼동)6125삼정제과2021-04-22 14:42:11U2021-04-24 02:40:00.0제과점영업202699.226067444846.764226제과점영업02기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N52.3<NA><NA><NA>
432200003220000-121-1983-0283719830512<NA>3폐업2폐업20090724<NA><NA><NA>02 573471866.24135834서울특별시 강남구 대치동 66-0번지 쌍용종합상가 가동<NA><NA>권상원과자점2002-03-21 00:00:00I2018-08-31 23:59:59.0제과점영업206228.074633443988.38641제과점영업02주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N66.24<NA><NA><NA>
532200003220000-121-1984-0252919840127<NA>3폐업2폐업20071128<NA><NA><NA>02 451006334.80135994서울특별시 강남구 개포동 186-18번지<NA><NA>빵굼터2002-03-22 00:00:00I2018-08-31 23:59:59.0제과점영업206030.984146442979.926652제과점영업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N34.8<NA><NA><NA>
632200003220000-121-1984-0277819840927<NA>3폐업2폐업20220209<NA><NA><NA>02 553580644.92135841서울특별시 강남구 대치동 911-13서울특별시 강남구 역삼로 452 (대치동)6201빵굼터 착한빵집2022-02-09 13:21:57U2022-02-11 02:40:00.0제과점영업204941.049526444443.797815제과점영업11주택가주변상수도전용00000<NA>00N44.92<NA><NA><NA>
732200003220000-121-1985-2233319850521<NA>3폐업2폐업20060116<NA><NA><NA>02 557017276.22135925서울특별시 강남구 역삼동 752-52번지<NA><NA>프로방스2002-03-25 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업12주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N76.22<NA><NA><NA>
832200003220000-121-1985-2233419850320<NA>3폐업2폐업20141229<NA><NA><NA>02 540521226.91135928서울특별시 강남구 역삼동 779-5번지서울특별시 강남구 언주로 317 (역삼동)6226힐튼제과2010-03-15 16:37:42I2018-08-31 23:59:59.0제과점영업203942.743843443773.130888제과점영업02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.91<NA><NA><NA>
932200003220000-121-1985-2233519850118<NA>3폐업2폐업20090218<NA><NA><NA>02 553693332.34135857서울특별시 강남구 도곡동 543-5번지<NA><NA>부산뉴욕제과2001-08-02 00:00:00I2018-08-31 23:59:59.0제과점영업203682.487186443363.703553제과점영업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N32.34<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
163632200003220000-121-2024-000712024-04-29<NA>3폐업2폐업2024-05-07<NA><NA><NA><NA><NA>135-730서울특별시 강남구 삼성동 159-7 현대백화점서울특별시 강남구 테헤란로 517, 현대백화점 지하1층 (삼성동)6164데루베이커리(한시적)2024-05-08 04:15:10U2023-12-04 23:00:00.0제과점영업205210.358779445154.422252<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
163732200003220000-121-2024-000722024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>135-902서울특별시 강남구 압구정동 494 갤러리아백화점서울특별시 강남구 압구정로 343, 갤러리아백화점 WEST 지하1층 (압구정동)6008마이페이보릿쿠키(한시적)2024-04-29 13:00:50I2023-12-05 00:01:00.0제과점영업203470.848439447369.579852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
163832200003220000-121-2024-000732024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.92135-902서울특별시 강남구 압구정동 494 갤러리아백화점서울특별시 강남구 압구정로 343, 갤러리아백화점 명품관 WEST 지하1층 식품관 (압구정동)6008청킴제과2024-04-30 12:02:50I2023-12-05 00:02:00.0제과점영업203470.848439447369.579852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
163932200003220000-121-2024-000742024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>135-731서울특별시 강남구 삼성동 159 코엑스서울특별시 강남구 영동대로 513, 코엑스 D홀 (삼성동)6164카페큐(한시적)2024-04-30 12:50:55I2023-12-05 00:02:00.0제과점영업205130.591679445590.096838<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
164032200003220000-121-2024-000752024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>73.00135-911서울특별시 강남구 역삼동 647서울특별시 강남구 테헤란로13길 12, 지상1층 (역삼동)6133아방베이커리 역삼점2024-05-03 14:32:55I2023-12-05 00:05:00.0제과점영업202803.368626444252.631304<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
164132200003220000-121-2024-000762024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>135-730서울특별시 강남구 삼성동 159-7 현대백화점서울특별시 강남구 테헤란로 517, 현대백화점 지하1층 (삼성동)6164한라산쑥떡전문점 미당(한시적)2024-05-08 17:16:53I2023-12-04 23:00:00.0제과점영업205210.358779445154.422252<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
164232200003220000-121-2024-000772024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.00135-947서울특별시 강남구 일원동 717 삼성생명 일원역 빌딩서울특별시 강남구 일원로 115, 삼성생명 일원역 빌딩 지하1층 롯데프리이엄푸드마켓 일부호 (일원동)6355베이커리팩토리 일원점2024-05-09 10:14:30I2023-12-04 23:01:00.0제과점영업207399.551655442426.399301<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
164332200003220000-121-2024-000782024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>135-724서울특별시 강남구 압구정동 429 현대백화점본점서울특별시 강남구 압구정로 165, 현대백화점본점 지하1층 (압구정동)6001떡함지 서초점(한시적)2024-05-09 10:23:05I2023-12-04 23:01:00.0제과점영업202358.505687447232.955698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
164432200003220000-121-2024-000792024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>135-724서울특별시 강남구 압구정동 429 현대백화점본점서울특별시 강남구 압구정로 165, 지하1층 식품관 (압구정동)6001히히etc2024-05-09 10:51:05I2023-12-04 23:01:00.0제과점영업202358.505687447232.955698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
164532200003220000-121-2024-000802024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00135-902서울특별시 강남구 압구정동 494 갤러리아백화점서울특별시 강남구 압구정로 343, 갤러리아백화점 지하1층 (압구정동)6008리암스(한시적)2024-05-09 15:42:37I2023-12-04 23:01:00.0제과점영업203470.848439447369.579852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>