Overview

Dataset statistics

Number of variables44
Number of observations1131
Missing cells10740
Missing cells (%)21.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory415.4 KiB
Average record size in memory376.1 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18426/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
총인원 is highly imbalanced (80.1%)Imbalance
본사종업원수 is highly imbalanced (78.8%)Imbalance
공장사무직종업원수 is highly imbalanced (78.8%)Imbalance
공장판매직종업원수 is highly imbalanced (78.8%)Imbalance
공장생산직종업원수 is highly imbalanced (78.8%)Imbalance
보증액 is highly imbalanced (78.8%)Imbalance
월세액 is highly imbalanced (78.8%)Imbalance
다중이용업소여부 is highly imbalanced (97.9%)Imbalance
전통업소지정번호 is highly imbalanced (99.0%)Imbalance
인허가취소일자 has 1131 (100.0%) missing valuesMissing
폐업일자 has 170 (15.0%) missing valuesMissing
휴업시작일자 has 1131 (100.0%) missing valuesMissing
휴업종료일자 has 1131 (100.0%) missing valuesMissing
재개업일자 has 1131 (100.0%) missing valuesMissing
전화번호 has 332 (29.4%) missing valuesMissing
소재지면적 has 25 (2.2%) missing valuesMissing
도로명주소 has 709 (62.7%) missing valuesMissing
도로명우편번호 has 711 (62.9%) missing valuesMissing
좌표정보(X) has 71 (6.3%) missing valuesMissing
좌표정보(Y) has 71 (6.3%) missing valuesMissing
남성종사자수 has 444 (39.3%) missing valuesMissing
건물소유구분명 has 1131 (100.0%) missing valuesMissing
다중이용업소여부 has 145 (12.8%) missing valuesMissing
시설총규모 has 145 (12.8%) missing valuesMissing
전통업소주된음식 has 1131 (100.0%) missing valuesMissing
홈페이지 has 1131 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 29.32591965)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
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 457 (40.4%) zerosZeros
시설총규모 has 14 (1.2%) zerosZeros

Reproduction

Analysis started2024-05-11 06:06:08.349414
Analysis finished2024-05-11 06:06:09.934499
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
3240000
1131 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 1131
100.0%

Length

2024-05-11T15:06:10.048756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:10.293358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 1131
100.0%

관리번호
Text

UNIQUE 

Distinct1131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-11T15:06:10.648660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters24882
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

Unique1131 ?
Unique (%)100.0%

Sample

1st row3240000-121-1952-04848
2nd row3240000-121-1979-04931
3rd row3240000-121-1979-05083
4th row3240000-121-1980-04890
5th row3240000-121-1980-04952
ValueCountFrequency (%)
3240000-121-1952-04848 1
 
0.1%
3240000-121-2009-00012 1
 
0.1%
3240000-121-2009-00018 1
 
0.1%
3240000-121-2009-00017 1
 
0.1%
3240000-121-2009-00016 1
 
0.1%
3240000-121-2009-00015 1
 
0.1%
3240000-121-2009-00025 1
 
0.1%
3240000-121-2009-00013 1
 
0.1%
3240000-121-2009-00011 1
 
0.1%
3240000-121-2009-00020 1
 
0.1%
Other values (1121) 1121
99.1%
2024-05-11T15:06:11.124276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7988
32.1%
1 3640
14.6%
2 3422
13.8%
- 3393
13.6%
4 1864
 
7.5%
3 1484
 
6.0%
9 1312
 
5.3%
8 563
 
2.3%
7 416
 
1.7%
6 403
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21489
86.4%
Dash Punctuation 3393
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7988
37.2%
1 3640
16.9%
2 3422
15.9%
4 1864
 
8.7%
3 1484
 
6.9%
9 1312
 
6.1%
8 563
 
2.6%
7 416
 
1.9%
6 403
 
1.9%
5 397
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 3393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24882
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7988
32.1%
1 3640
14.6%
2 3422
13.8%
- 3393
13.6%
4 1864
 
7.5%
3 1484
 
6.0%
9 1312
 
5.3%
8 563
 
2.3%
7 416
 
1.7%
6 403
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7988
32.1%
1 3640
14.6%
2 3422
13.8%
- 3393
13.6%
4 1864
 
7.5%
3 1484
 
6.0%
9 1312
 
5.3%
8 563
 
2.3%
7 416
 
1.7%
6 403
 
1.6%
Distinct1022
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum1952-05-13 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:06:11.710304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:11.954356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
3
961 
1
170 

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 (%)
3 961
85.0%
1 170
 
15.0%

Length

2024-05-11T15:06:12.173816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:12.323421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 961
85.0%
1 170
 
15.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
폐업
961 
영업/정상
170 

Length

Max length5
Median length2
Mean length2.4509284
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 961
85.0%
영업/정상 170
 
15.0%

Length

2024-05-11T15:06:12.494069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:12.690608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 961
85.0%
영업/정상 170
 
15.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2
961 
1
170 

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 (%)
2 961
85.0%
1 170
 
15.0%

Length

2024-05-11T15:06:12.859531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:13.001155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 961
85.0%
1 170
 
15.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
폐업
961 
영업
170 

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 961
85.0%
영업 170
 
15.0%

Length

2024-05-11T15:06:13.162298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:13.311741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 961
85.0%
영업 170
 
15.0%

폐업일자
Date

MISSING 

Distinct754
Distinct (%)78.5%
Missing170
Missing (%)15.0%
Memory size9.0 KiB
Minimum1989-04-20 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T15:06:13.482660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:13.734105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB

전화번호
Text

MISSING 

Distinct589
Distinct (%)73.7%
Missing332
Missing (%)29.4%
Memory size9.0 KiB
2024-05-11T15:06:14.219687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.2403004
Min length2

Characters and Unicode

Total characters7383
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

Unique562 ?
Unique (%)70.3%

Sample

1st row02 4287033
2nd row02 4826175
3rd row0204863691
4th row0200000000
5th row02
ValueCountFrequency (%)
02 536
40.4%
0200000000 38
 
2.9%
4882233 17
 
1.3%
00000 12
 
0.9%
0201768800 11
 
0.8%
0 10
 
0.8%
070 9
 
0.7%
1768800 6
 
0.5%
470 5
 
0.4%
441 5
 
0.4%
Other values (617) 678
51.1%
2024-05-11T15:06:15.220604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1762
23.9%
2 1299
17.6%
4 902
12.2%
669
 
9.1%
8 592
 
8.0%
7 522
 
7.1%
3 370
 
5.0%
6 353
 
4.8%
1 327
 
4.4%
5 309
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6714
90.9%
Space Separator 669
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1762
26.2%
2 1299
19.3%
4 902
13.4%
8 592
 
8.8%
7 522
 
7.8%
3 370
 
5.5%
6 353
 
5.3%
1 327
 
4.9%
5 309
 
4.6%
9 278
 
4.1%
Space Separator
ValueCountFrequency (%)
669
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7383
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1762
23.9%
2 1299
17.6%
4 902
12.2%
669
 
9.1%
8 592
 
8.0%
7 522
 
7.1%
3 370
 
5.0%
6 353
 
4.8%
1 327
 
4.4%
5 309
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1762
23.9%
2 1299
17.6%
4 902
12.2%
669
 
9.1%
8 592
 
8.0%
7 522
 
7.1%
3 370
 
5.0%
6 353
 
4.8%
1 327
 
4.4%
5 309
 
4.2%

소재지면적
Text

MISSING 

Distinct749
Distinct (%)67.7%
Missing25
Missing (%)2.2%
Memory size9.0 KiB
2024-05-11T15:06:15.844778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9683544
Min length3

Characters and Unicode

Total characters5495
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

Unique602 ?
Unique (%)54.4%

Sample

1st row34.19
2nd row35.74
3rd row60.32
4th row29.18
5th row18.98
ValueCountFrequency (%)
26.40 21
 
1.9%
33.00 16
 
1.4%
6.60 16
 
1.4%
30.00 15
 
1.4%
29.70 12
 
1.1%
23.10 10
 
0.9%
26.00 9
 
0.8%
19.80 9
 
0.8%
24.00 8
 
0.7%
42.90 8
 
0.7%
Other values (739) 982
88.8%
2024-05-11T15:06:16.720000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1106
20.1%
0 949
17.3%
2 607
11.0%
3 453
8.2%
6 417
 
7.6%
1 412
 
7.5%
4 397
 
7.2%
5 327
 
6.0%
9 297
 
5.4%
8 286
 
5.2%
Other values (2) 244
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4387
79.8%
Other Punctuation 1108
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 949
21.6%
2 607
13.8%
3 453
10.3%
6 417
9.5%
1 412
9.4%
4 397
9.0%
5 327
 
7.5%
9 297
 
6.8%
8 286
 
6.5%
7 242
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 1106
99.8%
, 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 5495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1106
20.1%
0 949
17.3%
2 607
11.0%
3 453
8.2%
6 417
 
7.6%
1 412
 
7.5%
4 397
 
7.2%
5 327
 
6.0%
9 297
 
5.4%
8 286
 
5.2%
Other values (2) 244
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1106
20.1%
0 949
17.3%
2 607
11.0%
3 453
8.2%
6 417
 
7.6%
1 412
 
7.5%
4 397
 
7.2%
5 327
 
6.0%
9 297
 
5.4%
8 286
 
5.2%
Other values (2) 244
 
4.4%
Distinct133
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-11T15:06:17.161071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0813439
Min length6

Characters and Unicode

Total characters6878
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)2.7%

Sample

1st row134825
2nd row134848
3rd row134874
4th row134822
5th row134853
ValueCountFrequency (%)
134874 73
 
6.5%
134830 73
 
6.5%
134825 49
 
4.3%
134864 42
 
3.7%
134779 34
 
3.0%
134880 32
 
2.8%
134840 31
 
2.7%
134859 31
 
2.7%
134822 29
 
2.6%
134890 27
 
2.4%
Other values (123) 710
62.8%
2024-05-11T15:06:17.961906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1429
20.8%
1 1356
19.7%
3 1313
19.1%
8 1174
17.1%
7 388
 
5.6%
0 344
 
5.0%
5 207
 
3.0%
6 206
 
3.0%
2 203
 
3.0%
9 166
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6786
98.7%
Dash Punctuation 92
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1429
21.1%
1 1356
20.0%
3 1313
19.3%
8 1174
17.3%
7 388
 
5.7%
0 344
 
5.1%
5 207
 
3.1%
6 206
 
3.0%
2 203
 
3.0%
9 166
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6878
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1429
20.8%
1 1356
19.7%
3 1313
19.1%
8 1174
17.1%
7 388
 
5.6%
0 344
 
5.0%
5 207
 
3.0%
6 206
 
3.0%
2 203
 
3.0%
9 166
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1429
20.8%
1 1356
19.7%
3 1313
19.1%
8 1174
17.1%
7 388
 
5.6%
0 344
 
5.0%
5 207
 
3.0%
6 206
 
3.0%
2 203
 
3.0%
9 166
 
2.4%
Distinct933
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-11T15:06:18.461157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length24.504863
Min length14

Characters and Unicode

Total characters27715
Distinct characters230
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique836 ?
Unique (%)73.9%

Sample

1st row서울특별시 강동구 명일동 48번지 주양쇼핑19호(지1층)
2nd row서울특별시 강동구 성내동 271-2번지
3rd row서울특별시 강동구 천호동 455-20번지
4th row서울특별시 강동구 둔촌동 522-3번지 둔촌종합 114호
5th row서울특별시 강동구 암사동 414-2번지
ValueCountFrequency (%)
서울특별시 1131
22.0%
강동구 1131
22.0%
천호동 326
 
6.3%
성내동 203
 
4.0%
명일동 173
 
3.4%
길동 125
 
2.4%
암사동 118
 
2.3%
둔촌동 83
 
1.6%
고덕동 54
 
1.1%
455-8번지 50
 
1.0%
Other values (1100) 1743
33.9%
2024-05-11T15:06:19.228665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4929
17.8%
2351
 
8.5%
1159
 
4.2%
1140
 
4.1%
1133
 
4.1%
1133
 
4.1%
1132
 
4.1%
1131
 
4.1%
1131
 
4.1%
1 1044
 
3.8%
Other values (220) 11432
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16307
58.8%
Decimal Number 5306
 
19.1%
Space Separator 4929
 
17.8%
Dash Punctuation 989
 
3.6%
Close Punctuation 61
 
0.2%
Open Punctuation 61
 
0.2%
Other Punctuation 40
 
0.1%
Uppercase Letter 21
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2351
14.4%
1159
 
7.1%
1140
 
7.0%
1133
 
6.9%
1133
 
6.9%
1132
 
6.9%
1131
 
6.9%
1131
 
6.9%
976
 
6.0%
894
 
5.5%
Other values (193) 4127
25.3%
Decimal Number
ValueCountFrequency (%)
1 1044
19.7%
4 847
16.0%
2 694
13.1%
3 570
10.7%
5 546
10.3%
0 474
8.9%
7 301
 
5.7%
8 300
 
5.7%
6 267
 
5.0%
9 263
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 7
33.3%
A 4
19.0%
G 2
 
9.5%
S 2
 
9.5%
F 2
 
9.5%
E 1
 
4.8%
T 1
 
4.8%
J 1
 
4.8%
N 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 33
82.5%
. 6
 
15.0%
& 1
 
2.5%
Space Separator
ValueCountFrequency (%)
4929
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 989
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16307
58.8%
Common 11386
41.1%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2351
14.4%
1159
 
7.1%
1140
 
7.0%
1133
 
6.9%
1133
 
6.9%
1132
 
6.9%
1131
 
6.9%
1131
 
6.9%
976
 
6.0%
894
 
5.5%
Other values (193) 4127
25.3%
Common
ValueCountFrequency (%)
4929
43.3%
1 1044
 
9.2%
- 989
 
8.7%
4 847
 
7.4%
2 694
 
6.1%
3 570
 
5.0%
5 546
 
4.8%
0 474
 
4.2%
7 301
 
2.6%
8 300
 
2.6%
Other values (7) 692
 
6.1%
Latin
ValueCountFrequency (%)
B 7
31.8%
A 4
18.2%
G 2
 
9.1%
S 2
 
9.1%
F 2
 
9.1%
E 1
 
4.5%
T 1
 
4.5%
J 1
 
4.5%
N 1
 
4.5%
1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16305
58.8%
ASCII 11407
41.2%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4929
43.2%
1 1044
 
9.2%
- 989
 
8.7%
4 847
 
7.4%
2 694
 
6.1%
3 570
 
5.0%
5 546
 
4.8%
0 474
 
4.2%
7 301
 
2.6%
8 300
 
2.6%
Other values (16) 713
 
6.3%
Hangul
ValueCountFrequency (%)
2351
14.4%
1159
 
7.1%
1140
 
7.0%
1133
 
6.9%
1133
 
6.9%
1132
 
6.9%
1131
 
6.9%
1131
 
6.9%
976
 
6.0%
894
 
5.5%
Other values (191) 4125
25.3%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct378
Distinct (%)89.6%
Missing709
Missing (%)62.7%
Memory size9.0 KiB
2024-05-11T15:06:19.686976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length33.869668
Min length21

Characters and Unicode

Total characters14293
Distinct characters226
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique363 ?
Unique (%)86.0%

Sample

1st row서울특별시 강동구 고덕로62길 55 (명일동,주양쇼핑19호(지1층))
2nd row서울특별시 강동구 천호옛12길 57 (성내동)
3rd row서울특별시 강동구 명일로 375, 1층 27호 (명일동, 삼익2차쇼핑)
4th row서울특별시 강동구 고덕로 390 (상일동)
5th row서울특별시 강동구 진황도로 79 (길동)
ValueCountFrequency (%)
서울특별시 422
 
15.4%
강동구 422
 
15.4%
1층 166
 
6.1%
천호동 107
 
3.9%
천호대로 85
 
3.1%
성내동 71
 
2.6%
1005 53
 
1.9%
명일동 50
 
1.8%
암사동 42
 
1.5%
현대백화점 40
 
1.5%
Other values (587) 1283
46.8%
2024-05-11T15:06:20.462185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2320
 
16.2%
928
 
6.5%
1 816
 
5.7%
465
 
3.3%
455
 
3.2%
) 449
 
3.1%
( 449
 
3.1%
, 447
 
3.1%
429
 
3.0%
424
 
3.0%
Other values (216) 7111
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8088
56.6%
Decimal Number 2470
 
17.3%
Space Separator 2320
 
16.2%
Close Punctuation 449
 
3.1%
Open Punctuation 449
 
3.1%
Other Punctuation 448
 
3.1%
Uppercase Letter 35
 
0.2%
Dash Punctuation 28
 
0.2%
Math Symbol 5
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
928
 
11.5%
465
 
5.7%
455
 
5.6%
429
 
5.3%
424
 
5.2%
424
 
5.2%
423
 
5.2%
422
 
5.2%
414
 
5.1%
410
 
5.1%
Other values (188) 3294
40.7%
Decimal Number
ValueCountFrequency (%)
1 816
33.0%
0 384
15.5%
2 262
 
10.6%
5 207
 
8.4%
3 173
 
7.0%
7 147
 
6.0%
4 138
 
5.6%
6 133
 
5.4%
8 116
 
4.7%
9 94
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 21
60.0%
S 2
 
5.7%
A 2
 
5.7%
L 2
 
5.7%
F 2
 
5.7%
G 2
 
5.7%
J 1
 
2.9%
N 1
 
2.9%
T 1
 
2.9%
E 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 447
99.8%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2320
100.0%
Close Punctuation
ValueCountFrequency (%)
) 449
100.0%
Open Punctuation
ValueCountFrequency (%)
( 449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8088
56.6%
Common 6169
43.2%
Latin 36
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
928
 
11.5%
465
 
5.7%
455
 
5.6%
429
 
5.3%
424
 
5.2%
424
 
5.2%
423
 
5.2%
422
 
5.2%
414
 
5.1%
410
 
5.1%
Other values (188) 3294
40.7%
Common
ValueCountFrequency (%)
2320
37.6%
1 816
 
13.2%
) 449
 
7.3%
( 449
 
7.3%
, 447
 
7.2%
0 384
 
6.2%
2 262
 
4.2%
5 207
 
3.4%
3 173
 
2.8%
7 147
 
2.4%
Other values (7) 515
 
8.3%
Latin
ValueCountFrequency (%)
B 21
58.3%
S 2
 
5.6%
A 2
 
5.6%
L 2
 
5.6%
F 2
 
5.6%
G 2
 
5.6%
1
 
2.8%
J 1
 
2.8%
N 1
 
2.8%
T 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8086
56.6%
ASCII 6204
43.4%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2320
37.4%
1 816
 
13.2%
) 449
 
7.2%
( 449
 
7.2%
, 447
 
7.2%
0 384
 
6.2%
2 262
 
4.2%
5 207
 
3.3%
3 173
 
2.8%
7 147
 
2.4%
Other values (17) 550
 
8.9%
Hangul
ValueCountFrequency (%)
928
 
11.5%
465
 
5.8%
455
 
5.6%
429
 
5.3%
424
 
5.2%
424
 
5.2%
423
 
5.2%
422
 
5.2%
414
 
5.1%
410
 
5.1%
Other values (186) 3292
40.7%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct130
Distinct (%)31.0%
Missing711
Missing (%)62.9%
Infinite0
Infinite (%)0.0%
Mean5315.0905
Minimum5209
Maximum5415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-11T15:06:20.730229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5209
5-th percentile5227
Q15269
median5328
Q35352.25
95-th percentile5404
Maximum5415
Range206
Interquartile range (IQR)83.25

Descriptive statistics

Standard deviation54.361087
Coefficient of variation (CV)0.010227688
Kurtosis-1.0008143
Mean5315.0905
Median Absolute Deviation (MAD)47
Skewness-0.03023726
Sum2232338
Variance2955.1278
MonotonicityNot monotonic
2024-05-11T15:06:20.994584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5328 61
 
5.4%
5269 16
 
1.4%
5351 11
 
1.0%
5292 11
 
1.0%
5404 10
 
0.9%
5339 8
 
0.7%
5378 8
 
0.7%
5264 8
 
0.7%
5271 7
 
0.6%
5384 7
 
0.6%
Other values (120) 273
 
24.1%
(Missing) 711
62.9%
ValueCountFrequency (%)
5209 1
 
0.1%
5211 5
0.4%
5214 1
 
0.1%
5215 1
 
0.1%
5220 3
0.3%
5222 3
0.3%
5224 4
0.4%
5226 1
 
0.1%
5227 4
0.4%
5229 5
0.4%
ValueCountFrequency (%)
5415 2
 
0.2%
5412 1
 
0.1%
5408 4
 
0.4%
5407 2
 
0.2%
5406 1
 
0.1%
5405 4
 
0.4%
5404 10
0.9%
5403 3
 
0.3%
5402 3
 
0.3%
5399 3
 
0.3%
Distinct945
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-11T15:06:21.425024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length7.3642794
Min length1

Characters and Unicode

Total characters8329
Distinct characters511
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

Unique844 ?
Unique (%)74.6%

Sample

1st row케익하우스 이삭
2nd row밀라노베이커리
3rd row고려당분점
4th row윈첼도우넛
5th row문수남과자점
ValueCountFrequency (%)
파리바게뜨 29
 
2.1%
뚜레쥬르 24
 
1.7%
베이커리 23
 
1.6%
한시적영업 22
 
1.6%
천호점 17
 
1.2%
밀라노베이커리 9
 
0.6%
크라운베이커리 9
 
0.6%
이딸리앙베이커리 8
 
0.6%
명일점 8
 
0.6%
던킨도너츠 7
 
0.5%
Other values (1007) 1241
88.8%
2024-05-11T15:06:22.125111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
416
 
5.0%
386
 
4.6%
375
 
4.5%
268
 
3.2%
263
 
3.2%
228
 
2.7%
222
 
2.7%
175
 
2.1%
159
 
1.9%
( 136
 
1.6%
Other values (501) 5701
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7370
88.5%
Space Separator 268
 
3.2%
Uppercase Letter 185
 
2.2%
Lowercase Letter 179
 
2.1%
Open Punctuation 136
 
1.6%
Close Punctuation 134
 
1.6%
Decimal Number 42
 
0.5%
Other Punctuation 14
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
416
 
5.6%
386
 
5.2%
375
 
5.1%
263
 
3.6%
228
 
3.1%
222
 
3.0%
175
 
2.4%
159
 
2.2%
131
 
1.8%
107
 
1.5%
Other values (438) 4908
66.6%
Uppercase Letter
ValueCountFrequency (%)
E 24
13.0%
B 17
 
9.2%
A 16
 
8.6%
R 12
 
6.5%
S 12
 
6.5%
D 11
 
5.9%
N 10
 
5.4%
O 10
 
5.4%
L 9
 
4.9%
U 8
 
4.3%
Other values (14) 56
30.3%
Lowercase Letter
ValueCountFrequency (%)
e 30
16.8%
a 27
15.1%
r 16
8.9%
k 11
 
6.1%
t 11
 
6.1%
y 11
 
6.1%
i 10
 
5.6%
o 9
 
5.0%
n 9
 
5.0%
m 6
 
3.4%
Other values (11) 39
21.8%
Decimal Number
ValueCountFrequency (%)
1 12
28.6%
2 10
23.8%
3 7
16.7%
0 7
16.7%
7 2
 
4.8%
5 2
 
4.8%
9 1
 
2.4%
8 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
? 5
35.7%
& 3
21.4%
: 2
 
14.3%
. 2
 
14.3%
# 1
 
7.1%
' 1
 
7.1%
Space Separator
ValueCountFrequency (%)
268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7370
88.5%
Common 595
 
7.1%
Latin 364
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
416
 
5.6%
386
 
5.2%
375
 
5.1%
263
 
3.6%
228
 
3.1%
222
 
3.0%
175
 
2.4%
159
 
2.2%
131
 
1.8%
107
 
1.5%
Other values (438) 4908
66.6%
Latin
ValueCountFrequency (%)
e 30
 
8.2%
a 27
 
7.4%
E 24
 
6.6%
B 17
 
4.7%
A 16
 
4.4%
r 16
 
4.4%
R 12
 
3.3%
S 12
 
3.3%
k 11
 
3.0%
t 11
 
3.0%
Other values (35) 188
51.6%
Common
ValueCountFrequency (%)
268
45.0%
( 136
22.9%
) 134
22.5%
1 12
 
2.0%
2 10
 
1.7%
3 7
 
1.2%
0 7
 
1.2%
? 5
 
0.8%
& 3
 
0.5%
7 2
 
0.3%
Other values (8) 11
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7370
88.5%
ASCII 959
 
11.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
416
 
5.6%
386
 
5.2%
375
 
5.1%
263
 
3.6%
228
 
3.1%
222
 
3.0%
175
 
2.4%
159
 
2.2%
131
 
1.8%
107
 
1.5%
Other values (438) 4908
66.6%
ASCII
ValueCountFrequency (%)
268
27.9%
( 136
14.2%
) 134
14.0%
e 30
 
3.1%
a 27
 
2.8%
E 24
 
2.5%
B 17
 
1.8%
A 16
 
1.7%
r 16
 
1.7%
R 12
 
1.3%
Other values (53) 279
29.1%
Distinct721
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum1999-01-11 00:00:00
Maximum2024-05-09 09:27:56
2024-05-11T15:06:22.382022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:22.652766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
I
916 
U
215 

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 916
81.0%
U 215
 
19.0%

Length

2024-05-11T15:06:22.907208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:23.051673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 916
81.0%
u 215
 
19.0%
Distinct238
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:06:23.230239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:23.455009image/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 size9.0 KiB
제과점영업
1131 

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 1131
100.0%

Length

2024-05-11T15:06:23.661225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:23.805007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 1131
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct656
Distinct (%)61.9%
Missing71
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean212128.1
Minimum210566.88
Maximum216029.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-11T15:06:23.972852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210566.88
5-th percentile210929.92
Q1211222.48
median211904.54
Q3212707.79
95-th percentile214293.41
Maximum216029.39
Range5462.5124
Interquartile range (IQR)1485.3112

Descriptive statistics

Standard deviation1078.8991
Coefficient of variation (CV)0.0050860735
Kurtosis0.65706754
Mean212128.1
Median Absolute Deviation (MAD)740.45968
Skewness0.98584592
Sum2.2485579 × 108
Variance1164023.3
MonotonicityNot monotonic
2024-05-11T15:06:24.192424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210931.643485 55
 
4.9%
210929.919693661 32
 
2.8%
211025.924972294 24
 
2.1%
213700.877714971 18
 
1.6%
211979.520569314 12
 
1.1%
213048.692179757 10
 
0.9%
212334.69890736 9
 
0.8%
211912.282694478 7
 
0.6%
212845.87675862 6
 
0.5%
212676.162193508 6
 
0.5%
Other values (646) 881
77.9%
(Missing) 71
 
6.3%
ValueCountFrequency (%)
210566.875626134 2
0.2%
210630.209443525 1
0.1%
210666.544542252 1
0.1%
210669.722533894 1
0.1%
210692.588312686 2
0.2%
210708.395291121 1
0.1%
210719.904367879 2
0.2%
210732.609714299 1
0.1%
210733.127672305 2
0.2%
210742.934504221 1
0.1%
ValueCountFrequency (%)
216029.388021 1
0.1%
215784.2264 1
0.1%
215743.278884315 1
0.1%
215422.746119624 1
0.1%
215400.574803 1
0.1%
215384.844269 1
0.1%
215303.913311463 1
0.1%
215289.815449411 2
0.2%
215277.575586465 1
0.1%
215257.766510608 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct656
Distinct (%)61.9%
Missing71
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean448905.24
Minimum446462.9
Maximum452195.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-11T15:06:24.501785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446462.9
5-th percentile447197.27
Q1448249.96
median448721.09
Q3449814.24
95-th percentile450566.11
Maximum452195.59
Range5732.6861
Interquartile range (IQR)1564.2829

Descriptive statistics

Standard deviation1049.1412
Coefficient of variation (CV)0.0023371107
Kurtosis-0.61367478
Mean448905.24
Median Absolute Deviation (MAD)876.00744
Skewness0.071817754
Sum4.7583955 × 108
Variance1100697.3
MonotonicityNot monotonic
2024-05-11T15:06:24.740371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448522.079827 55
 
4.9%
448537.406728283 32
 
2.8%
448495.189151526 24
 
2.1%
450278.100930843 18
 
1.6%
446932.653730601 12
 
1.1%
450124.105734971 10
 
0.9%
447728.865137096 9
 
0.8%
447248.126116539 7
 
0.6%
449772.477083199 6
 
0.5%
449910.881572138 6
 
0.5%
Other values (646) 881
77.9%
(Missing) 71
 
6.3%
ValueCountFrequency (%)
446462.901761568 2
0.2%
446742.800284862 1
0.1%
446748.493341691 1
0.1%
446753.841167447 1
0.1%
446810.814080816 1
0.1%
446824.910976521 1
0.1%
446859.875435823 1
0.1%
446862.234226426 1
0.1%
446872.29983338 2
0.2%
446893.337244184 1
0.1%
ValueCountFrequency (%)
452195.587817951 1
0.1%
452189.755118282 1
0.1%
452130.329696 1
0.1%
451707.466249 1
0.1%
451519.404046335 2
0.2%
451505.007408289 1
0.1%
451457.0 1
0.1%
451402.228621793 1
0.1%
451319.018562 1
0.1%
451151.696609954 1
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
제과점영업
986 
<NA>
145 

Length

Max length5
Median length5
Mean length4.8717949
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 986
87.2%
<NA> 145
 
12.8%

Length

2024-05-11T15:06:25.307469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:25.490707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 986
87.2%
na 145
 
12.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.9%
Missing444
Missing (%)39.3%
Infinite0
Infinite (%)0.0%
Mean0.41921397
Minimum0
Maximum9
Zeros457
Zeros (%)40.4%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-11T15:06:25.639932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.72769693
Coefficient of variation (CV)1.7358604
Kurtosis29.771888
Mean0.41921397
Median Absolute Deviation (MAD)0
Skewness3.6290086
Sum288
Variance0.52954282
MonotonicityNot monotonic
2024-05-11T15:06:25.806888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 457
40.4%
1 189
16.7%
2 32
 
2.8%
3 6
 
0.5%
4 2
 
0.2%
9 1
 
0.1%
(Missing) 444
39.3%
ValueCountFrequency (%)
0 457
40.4%
1 189
16.7%
2 32
 
2.8%
3 6
 
0.5%
4 2
 
0.2%
9 1
 
0.1%
ValueCountFrequency (%)
9 1
 
0.1%
4 2
 
0.2%
3 6
 
0.5%
2 32
 
2.8%
1 189
16.7%
0 457
40.4%
Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
443 
0
406 
1
246 
2
 
30
3
 
5

Length

Max length4
Median length1
Mean length2.1750663
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 443
39.2%
0 406
35.9%
1 246
21.8%
2 30
 
2.7%
3 5
 
0.4%
9 1
 
0.1%

Length

2024-05-11T15:06:26.029179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:26.217895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 443
39.2%
0 406
35.9%
1 246
21.8%
2 30
 
2.7%
3 5
 
0.4%
9 1
 
0.1%
Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
526 
주택가주변
409 
아파트지역
75 
유흥업소밀집지역
60 
기타
59 
Other values (2)
 
2

Length

Max length8
Median length7
Mean length4.5419982
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 526
46.5%
주택가주변 409
36.2%
아파트지역 75
 
6.6%
유흥업소밀집지역 60
 
5.3%
기타 59
 
5.2%
학교정화(절대) 1
 
0.1%
결혼예식장주변 1
 
0.1%

Length

2024-05-11T15:06:26.406375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:26.570463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 526
46.5%
주택가주변 409
36.2%
아파트지역 75
 
6.6%
유흥업소밀집지역 60
 
5.3%
기타 59
 
5.2%
학교정화(절대 1
 
0.1%
결혼예식장주변 1
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
526 
기타
194 
자율
178 
지도
137 
91 
Other values (3)
 
5

Length

Max length4
Median length2
Mean length2.8479222
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 526
46.5%
기타 194
 
17.2%
자율 178
 
15.7%
지도 137
 
12.1%
91
 
8.0%
2
 
0.2%
우수 2
 
0.2%
관리 1
 
0.1%

Length

2024-05-11T15:06:26.851991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:27.044080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 526
46.5%
기타 194
 
17.2%
자율 178
 
15.7%
지도 137
 
12.1%
91
 
8.0%
2
 
0.2%
우수 2
 
0.2%
관리 1
 
0.1%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
상수도전용
616 
<NA>
513 
상수도(음용)지하수(주방용)겸용
 
1
지하수전용
 
1

Length

Max length17
Median length5
Mean length4.5570292
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 616
54.5%
<NA> 513
45.4%
상수도(음용)지하수(주방용)겸용 1
 
0.1%
지하수전용 1
 
0.1%

Length

2024-05-11T15:06:27.226738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:27.393479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 616
54.5%
na 513
45.4%
상수도(음용)지하수(주방용)겸용 1
 
0.1%
지하수전용 1
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1096 
0
 
35

Length

Max length4
Median length4
Mean length3.9071618
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> 1096
96.9%
0 35
 
3.1%

Length

2024-05-11T15:06:27.578820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:27.789214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1096
96.9%
0 35
 
3.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1093 
0
 
38

Length

Max length4
Median length4
Mean length3.8992042
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> 1093
96.6%
0 38
 
3.4%

Length

2024-05-11T15:06:27.960466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:28.140774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1093
96.6%
0 38
 
3.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1093 
0
 
38

Length

Max length4
Median length4
Mean length3.8992042
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> 1093
96.6%
0 38
 
3.4%

Length

2024-05-11T15:06:28.359308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:28.542871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1093
96.6%
0 38
 
3.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1093 
0
 
38

Length

Max length4
Median length4
Mean length3.8992042
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> 1093
96.6%
0 38
 
3.4%

Length

2024-05-11T15:06:28.749976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:28.994467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1093
96.6%
0 38
 
3.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1093 
0
 
38

Length

Max length4
Median length4
Mean length3.8992042
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> 1093
96.6%
0 38
 
3.4%

Length

2024-05-11T15:06:29.213680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:29.444988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1093
96.6%
0 38
 
3.4%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1093 
0
 
38

Length

Max length4
Median length4
Mean length3.8992042
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> 1093
96.6%
0 38
 
3.4%

Length

2024-05-11T15:06:29.628938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:29.784801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1093
96.6%
0 38
 
3.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1093 
0
 
38

Length

Max length4
Median length4
Mean length3.8992042
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> 1093
96.6%
0 38
 
3.4%

Length

2024-05-11T15:06:29.950952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:30.133143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1093
96.6%
0 38
 
3.4%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing145
Missing (%)12.8%
Memory size2.3 KiB
False
984 
True
 
2
(Missing)
145 
ValueCountFrequency (%)
False 984
87.0%
True 2
 
0.2%
(Missing) 145
 
12.8%
2024-05-11T15:06:30.295277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct683
Distinct (%)69.3%
Missing145
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean144.13084
Minimum0
Maximum85033.58
Zeros14
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-11T15:06:30.483319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.6
Q121.02
median29.03
Q343.03
95-th percentile90
Maximum85033.58
Range85033.58
Interquartile range (IQR)22.01

Descriptive statistics

Standard deviation2780.3667
Coefficient of variation (CV)19.290574
Kurtosis887.26366
Mean144.13084
Median Absolute Deviation (MAD)10.57
Skewness29.32592
Sum142113.01
Variance7730439.1
MonotonicityNot monotonic
2024-05-11T15:06:30.704640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 20
 
1.8%
6.6 15
 
1.3%
0.0 14
 
1.2%
29.7 12
 
1.1%
33.0 11
 
1.0%
30.0 10
 
0.9%
23.1 10
 
0.9%
42.9 8
 
0.7%
39.6 8
 
0.7%
26.0 8
 
0.7%
Other values (673) 870
76.9%
(Missing) 145
 
12.8%
ValueCountFrequency (%)
0.0 14
1.2%
1.26 1
 
0.1%
1.65 1
 
0.1%
2.04 1
 
0.1%
2.4 1
 
0.1%
2.52 1
 
0.1%
2.7 1
 
0.1%
3.3 4
 
0.4%
3.31 1
 
0.1%
3.51 1
 
0.1%
ValueCountFrequency (%)
85033.58 1
0.1%
20035.7 1
0.1%
572.66 1
0.1%
554.21 1
0.1%
429.75 1
0.1%
247.5 1
0.1%
245.22 1
0.1%
201.08 1
0.1%
157.0 1
0.1%
155.68 1
0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1130 
0
 
1

Length

Max length4
Median length4
Mean length3.9973475
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1130
99.9%
0 1
 
0.1%

Length

2024-05-11T15:06:30.903607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:31.055600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1130
99.9%
0 1
 
0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1131
Missing (%)100.0%
Memory size10.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-121-1952-0484819520513<NA>3폐업2폐업20170227<NA><NA><NA>02 428703334.19134825서울특별시 강동구 명일동 48번지 주양쇼핑19호(지1층)서울특별시 강동구 고덕로62길 55 (명일동,주양쇼핑19호(지1층))5269케익하우스 이삭2015-07-22 17:19:22I2018-08-31 23:59:59.0제과점영업213493.907175450038.84732제과점영업11아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N34.19<NA><NA><NA>
132400003240000-121-1979-0493119790901<NA>3폐업2폐업19970204<NA><NA><NA>02 482617535.74134848서울특별시 강동구 성내동 271-2번지<NA><NA>밀라노베이커리2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업211071.489376447715.668884제과점영업00주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N35.74<NA><NA><NA>
232400003240000-121-1979-0508319790419<NA>3폐업2폐업19951120<NA><NA><NA>020486369160.32134874서울특별시 강동구 천호동 455-20번지<NA><NA>고려당분점2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N60.32<NA><NA><NA>
332400003240000-121-1980-0489019800709<NA>3폐업2폐업20121206<NA><NA><NA>020000000029.18134822서울특별시 강동구 둔촌동 522-3번지 둔촌종합 114호<NA><NA>윈첼도우넛2008-01-24 10:21:13I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업21주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.18<NA><NA><NA>
432400003240000-121-1980-0495219800630<NA>3폐업2폐업20000304<NA><NA><NA>0218.98134853서울특별시 강동구 암사동 414-2번지<NA><NA>문수남과자점2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업212480.463676450472.374955제과점영업01아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N18.98<NA><NA><NA>
532400003240000-121-1980-0495419800910<NA>3폐업2폐업20000201<NA><NA><NA>0245.56134857서울특별시 강동구 암사동 463-0번지<NA><NA>독일제과2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업211338.526335450163.935831제과점영업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.56<NA><NA><NA>
632400003240000-121-1980-0508219801104<NA>3폐업2폐업20000616<NA><NA><NA>020000000080.28134840서울특별시 강동구 성내동 79-8번지<NA><NA>프린스제과2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N80.28<NA><NA><NA>
732400003240000-121-1980-0508719801008<NA>3폐업2폐업19920521<NA><NA><NA>0204761146130.64134859서울특별시 강동구 암사동 501-3번지<NA><NA>효성제과2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업211228.867878449776.322853제과점영업31주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N130.64<NA><NA><NA>
832400003240000-121-1980-0508819800329<NA>3폐업2폐업20080325<NA><NA><NA><NA>37.10134880서울특별시 강동구 길동 400-1번지<NA><NA>블루문 베이커리2002-07-25 00:00:00I2018-08-31 23:59:59.0제과점영업212589.271821448309.85989제과점영업00기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N37.1<NA><NA><NA>
932400003240000-121-1981-0474019811123<NA>3폐업2폐업20101019<NA><NA><NA>020176880021.50134818서울특별시 강동구 둔촌동 112-4번지 주공(상가) 나동 118호<NA><NA>김윤호베이커리2008-01-24 10:22:31I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업00아파트지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N21.5<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
112132400003240000-121-2024-000022024-01-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>132.00134-822서울특별시 강동구 둔촌동 436-3서울특별시 강동구 양재대로 1424, 지1층 B102호 (둔촌동)5362그레인 베이커리2024-01-25 10:54:05I2023-11-30 22:07:00.0제과점영업212191.260488447873.981033<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112232400003240000-121-2024-000032024-02-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00134-874서울특별시 강동구 천호동 457-47서울특별시 강동구 구천면로18길 28, 1층 (천호동)5248케키도리2024-02-19 13:03:36I2023-12-01 22:01:00.0제과점영업210756.118234448698.40758<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112332400003240000-121-2024-000042024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.00134-843서울특별시 강동구 성내동 386-55서울특별시 강동구 양재대로101길 57, 1층 101-2호 (성내동)5374알레그리아케이크(alegria cake)2024-03-19 13:25:24I2023-12-02 22:01:00.0제과점영업211827.517453447832.006145<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112432400003240000-121-2024-000052024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.01134-880서울특별시 강동구 길동 401-8서울특별시 강동구 양재대로112길 87, 102호 (길동)5350파파베이커리2024-04-01 13:52:49I2023-12-04 00:03:00.0제과점영업212714.726866448193.392189<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112532400003240000-121-2024-000062024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.78134-830서울특별시 강동구 명일동 327-1 센트로빌서울특별시 강동구 구천면로 428, 1층 115호 (명일동, 센트로빌)5292에따 베이커리(etat bakery)2024-04-15 15:37:02I2023-12-03 23:07:00.0제과점영업212845.876759449772.477083<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112632400003240000-121-2024-000072024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.09134-877서울특별시 강동구 암사동 511서울특별시 강동구 상암로 14, 108호 (암사동)5242러브포션2024-04-19 17:08:31I2023-12-03 22:01:00.0제과점영업211005.592616449849.48776<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112732400003240000-121-2024-000082024-04-23<NA>3폐업2폐업2024-04-25<NA><NA><NA><NA><NA>134-700서울특별시 강동구 성내동 540 강동구청서울특별시 강동구 성내로 25, 강동구청 별관 1층 (성내동)5397더샤르망베이커리 한시적영업2024-04-26 04:15:10U2023-12-03 22:08:00.0제과점영업210863.000371447545.992755<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112832400003240000-121-2024-000092024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00134-825서울특별시 강동구 명일동 48-12 동양타워서울특별시 강동구 동남로71길 38, 3층 305호 (명일동, 동양타워)5269도도베이크2024-04-26 09:31:09I2023-12-03 22:08:00.0제과점영업213545.011196449988.458107<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
112932400003240000-121-2024-000102024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.90134-877서울특별시 강동구 암사동 512-7 웰빙타워서울특별시 강동구 상암로4길 23, 웰빙타워 102호 (암사동)5242티도스룸2024-05-01 10:12:32I2023-12-05 00:04:00.0제과점영업211096.215937449690.76318<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
113032400003240000-121-2024-000112024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00134-827서울특별시 강동구 명일동 239-4서울특별시 강동구 동남로65길 46, 1층 102호 (명일동)5271미니테이블2024-05-09 09:27:56I2023-12-04 23:01:00.0제과점영업213482.812336449520.750715<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>