Overview

Dataset statistics

Number of variables44
Number of observations2513
Missing cells31425
Missing cells (%)28.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory927.8 KiB
Average record size in memory378.1 B

Variable types

Categorical18
Text7
DateTime4
Unsupported10
Numeric4
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
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-18080/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (60.6%)Imbalance
여성종사자수 is highly imbalanced (60.6%)Imbalance
급수시설구분명 is highly imbalanced (87.5%)Imbalance
총인원 is highly imbalanced (60.6%)Imbalance
본사종업원수 is highly imbalanced (55.2%)Imbalance
공장사무직종업원수 is highly imbalanced (55.3%)Imbalance
공장판매직종업원수 is highly imbalanced (60.6%)Imbalance
보증액 is highly imbalanced (82.1%)Imbalance
월세액 is highly imbalanced (82.1%)Imbalance
인허가취소일자 has 2513 (100.0%) missing valuesMissing
폐업일자 has 764 (30.4%) missing valuesMissing
휴업시작일자 has 2513 (100.0%) missing valuesMissing
휴업종료일자 has 2513 (100.0%) missing valuesMissing
재개업일자 has 2513 (100.0%) missing valuesMissing
전화번호 has 1505 (59.9%) missing valuesMissing
소재지면적 has 1442 (57.4%) missing valuesMissing
도로명주소 has 435 (17.3%) missing valuesMissing
도로명우편번호 has 473 (18.8%) missing valuesMissing
업태구분명 has 2513 (100.0%) missing valuesMissing
좌표정보(X) has 40 (1.6%) missing valuesMissing
좌표정보(Y) has 40 (1.6%) missing valuesMissing
영업장주변구분명 has 2513 (100.0%) missing valuesMissing
등급구분명 has 2513 (100.0%) missing valuesMissing
다중이용업소여부 has 775 (30.8%) missing valuesMissing
시설총규모 has 775 (30.8%) missing valuesMissing
전통업소지정번호 has 2513 (100.0%) missing valuesMissing
전통업소주된음식 has 2513 (100.0%) missing valuesMissing
홈페이지 has 2513 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 24.18703616)Skewed
시설총규모 is highly skewed (γ1 = 30.8161243)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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
시설총규모 has 1720 (68.4%) zerosZeros

Reproduction

Analysis started2024-05-11 03:53:07.629483
Analysis finished2024-05-11 03:53:10.347338
Duration2.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
3030000
2513 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 2513
100.0%

Length

2024-05-11T03:53:10.504923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:10.802887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 2513
100.0%

관리번호
Text

UNIQUE 

Distinct2513
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
2024-05-11T03:53:11.255544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters55286
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

Unique2513 ?
Unique (%)100.0%

Sample

1st row3030000-134-2002-00001
2nd row3030000-134-2004-00001
3rd row3030000-134-2004-00002
4th row3030000-134-2004-00004
5th row3030000-134-2004-00005
ValueCountFrequency (%)
3030000-134-2002-00001 1
 
< 0.1%
3030000-134-2020-00022 1
 
< 0.1%
3030000-134-2020-00031 1
 
< 0.1%
3030000-134-2020-00016 1
 
< 0.1%
3030000-134-2020-00017 1
 
< 0.1%
3030000-134-2020-00018 1
 
< 0.1%
3030000-134-2020-00019 1
 
< 0.1%
3030000-134-2020-00020 1
 
< 0.1%
3030000-134-2020-00021 1
 
< 0.1%
3030000-134-2020-00024 1
 
< 0.1%
Other values (2503) 2503
99.6%
2024-05-11T03:53:12.287935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23395
42.3%
3 8392
 
15.2%
- 7539
 
13.6%
1 5070
 
9.2%
2 4291
 
7.8%
4 3413
 
6.2%
9 660
 
1.2%
5 650
 
1.2%
7 632
 
1.1%
8 625
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47747
86.4%
Dash Punctuation 7539
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23395
49.0%
3 8392
 
17.6%
1 5070
 
10.6%
2 4291
 
9.0%
4 3413
 
7.1%
9 660
 
1.4%
5 650
 
1.4%
7 632
 
1.3%
8 625
 
1.3%
6 619
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 7539
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23395
42.3%
3 8392
 
15.2%
- 7539
 
13.6%
1 5070
 
9.2%
2 4291
 
7.8%
4 3413
 
6.2%
9 660
 
1.2%
5 650
 
1.2%
7 632
 
1.1%
8 625
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23395
42.3%
3 8392
 
15.2%
- 7539
 
13.6%
1 5070
 
9.2%
2 4291
 
7.8%
4 3413
 
6.2%
9 660
 
1.2%
5 650
 
1.2%
7 632
 
1.1%
8 625
 
1.1%
Distinct1808
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
Minimum2004-03-24 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T03:53:12.642904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:53:12.964121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
3
1749 
1
764 

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 1749
69.6%
1 764
30.4%

Length

2024-05-11T03:53:13.260311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:13.459898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1749
69.6%
1 764
30.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
폐업
1749 
영업/정상
764 

Length

Max length5
Median length2
Mean length2.9120573
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1749
69.6%
영업/정상 764
30.4%

Length

2024-05-11T03:53:13.817016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:14.139811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1749
69.6%
영업/정상 764
30.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
2
1749 
1
764 

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 1749
69.6%
1 764
30.4%

Length

2024-05-11T03:53:14.407552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:14.620515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1749
69.6%
1 764
30.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
폐업
1749 
영업
764 

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 1749
69.6%
영업 764
30.4%

Length

2024-05-11T03:53:14.925431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:15.215876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1749
69.6%
영업 764
30.4%

폐업일자
Date

MISSING 

Distinct1197
Distinct (%)68.4%
Missing764
Missing (%)30.4%
Memory size19.8 KiB
Minimum2004-07-21 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T03:53:15.536546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:53:15.980608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

전화번호
Text

MISSING 

Distinct979
Distinct (%)97.1%
Missing1505
Missing (%)59.9%
Memory size19.8 KiB
2024-05-11T03:53:16.606851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.50496
Min length7

Characters and Unicode

Total characters10589
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

Unique954 ?
Unique (%)94.6%

Sample

1st row02 22358754
2nd row0222941614
3rd row22421946
4th row4537032
5th row0222914104
ValueCountFrequency (%)
02 387
 
24.9%
070 46
 
3.0%
468 5
 
0.3%
466 5
 
0.3%
031 5
 
0.3%
462 4
 
0.3%
0232848112 4
 
0.3%
3325 3
 
0.2%
32848342 3
 
0.2%
22979988 3
 
0.2%
Other values (1049) 1091
70.1%
2024-05-11T03:53:17.634392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2266
21.4%
0 1818
17.2%
797
 
7.5%
4 795
 
7.5%
9 784
 
7.4%
1 720
 
6.8%
6 714
 
6.7%
8 705
 
6.7%
5 703
 
6.6%
7 682
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9792
92.5%
Space Separator 797
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2266
23.1%
0 1818
18.6%
4 795
 
8.1%
9 784
 
8.0%
1 720
 
7.4%
6 714
 
7.3%
8 705
 
7.2%
5 703
 
7.2%
7 682
 
7.0%
3 605
 
6.2%
Space Separator
ValueCountFrequency (%)
797
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10589
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2266
21.4%
0 1818
17.2%
797
 
7.5%
4 795
 
7.5%
9 784
 
7.4%
1 720
 
6.8%
6 714
 
6.7%
8 705
 
6.7%
5 703
 
6.6%
7 682
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10589
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2266
21.4%
0 1818
17.2%
797
 
7.5%
4 795
 
7.5%
9 784
 
7.4%
1 720
 
6.8%
6 714
 
6.7%
8 705
 
6.7%
5 703
 
6.6%
7 682
 
6.4%

소재지면적
Text

MISSING 

Distinct478
Distinct (%)44.6%
Missing1442
Missing (%)57.4%
Memory size19.8 KiB
2024-05-11T03:53:18.409152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.7152194
Min length3

Characters and Unicode

Total characters5050
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

Unique373 ?
Unique (%)34.8%

Sample

1st row53.76
2nd row5.76
3rd row37.15
4th row281.61
5th row15.12
ValueCountFrequency (%)
3.30 116
 
10.8%
3.00 41
 
3.8%
6.60 37
 
3.5%
00 32
 
3.0%
33.00 31
 
2.9%
10.00 24
 
2.2%
6.00 18
 
1.7%
9.90 17
 
1.6%
5.00 16
 
1.5%
15.00 16
 
1.5%
Other values (468) 723
67.5%
2024-05-11T03:53:19.639492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1420
28.1%
. 1071
21.2%
3 556
 
11.0%
1 387
 
7.7%
2 309
 
6.1%
6 273
 
5.4%
5 264
 
5.2%
4 229
 
4.5%
9 219
 
4.3%
8 174
 
3.4%
Other values (2) 148
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3978
78.8%
Other Punctuation 1072
 
21.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1420
35.7%
3 556
 
14.0%
1 387
 
9.7%
2 309
 
7.8%
6 273
 
6.9%
5 264
 
6.6%
4 229
 
5.8%
9 219
 
5.5%
8 174
 
4.4%
7 147
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 1071
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 5050
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1420
28.1%
. 1071
21.2%
3 556
 
11.0%
1 387
 
7.7%
2 309
 
6.1%
6 273
 
5.4%
5 264
 
5.2%
4 229
 
4.5%
9 219
 
4.3%
8 174
 
3.4%
Other values (2) 148
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1420
28.1%
. 1071
21.2%
3 556
 
11.0%
1 387
 
7.7%
2 309
 
6.1%
6 273
 
5.4%
5 264
 
5.2%
4 229
 
4.5%
9 219
 
4.3%
8 174
 
3.4%
Other values (2) 148
 
2.9%
Distinct209
Distinct (%)8.4%
Missing23
Missing (%)0.9%
Memory size19.8 KiB
2024-05-11T03:53:20.432019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2156627
Min length6

Characters and Unicode

Total characters15477
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

Unique41 ?
Unique (%)1.6%

Sample

1st row133880
2nd row133826
3rd row133854
4th row133851
5th row133833
ValueCountFrequency (%)
133834 106
 
4.3%
133070 91
 
3.7%
133832 73
 
2.9%
133809 62
 
2.5%
133822 62
 
2.5%
133835 61
 
2.4%
133882 56
 
2.2%
133823 47
 
1.9%
133-834 44
 
1.8%
133828 43
 
1.7%
Other values (199) 1845
74.1%
2024-05-11T03:53:21.717798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 5734
37.0%
1 2912
18.8%
8 2402
15.5%
0 909
 
5.9%
2 836
 
5.4%
7 588
 
3.8%
- 537
 
3.5%
5 491
 
3.2%
4 469
 
3.0%
6 311
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14940
96.5%
Dash Punctuation 537
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 5734
38.4%
1 2912
19.5%
8 2402
16.1%
0 909
 
6.1%
2 836
 
5.6%
7 588
 
3.9%
5 491
 
3.3%
4 469
 
3.1%
6 311
 
2.1%
9 288
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 537
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 5734
37.0%
1 2912
18.8%
8 2402
15.5%
0 909
 
5.9%
2 836
 
5.4%
7 588
 
3.8%
- 537
 
3.5%
5 491
 
3.2%
4 469
 
3.0%
6 311
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 5734
37.0%
1 2912
18.8%
8 2402
15.5%
0 909
 
5.9%
2 836
 
5.4%
7 588
 
3.8%
- 537
 
3.5%
5 491
 
3.2%
4 469
 
3.0%
6 311
 
2.0%
Distinct1326
Distinct (%)53.3%
Missing23
Missing (%)0.9%
Memory size19.8 KiB
2024-05-11T03:53:22.394456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length47
Mean length27.939759
Min length16

Characters and Unicode

Total characters69570
Distinct characters381
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique988 ?
Unique (%)39.7%

Sample

1st row서울특별시 성동구 홍익동 ***번지 이노피스 ***호
2nd row서울특별시 성동구 성수동*가 ***-*번지 (*층)
3rd row서울특별시 성동구 하왕십리동 ***-*번지 지상*층 동원빌딩***호
4th row서울특별시 성동구 용답동 ***-*번지 (*층)
5th row서울특별시 성동구 성수동*가 ***-**번지 (*층)
ValueCountFrequency (%)
서울특별시 2490
19.9%
성동구 2489
19.9%
번지 1296
10.3%
1188
9.5%
성수동*가 912
 
7.3%
행당동 350
 
2.8%
금호동*가 325
 
2.6%
지상*층 294
 
2.3%
278
 
2.2%
용답동 170
 
1.4%
Other values (798) 2745
21.9%
2024-05-11T03:53:23.506742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 13656
19.6%
11660
16.8%
5265
 
7.6%
3619
 
5.2%
2572
 
3.7%
2570
 
3.7%
2504
 
3.6%
2497
 
3.6%
2490
 
3.6%
2490
 
3.6%
Other values (371) 20247
29.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41236
59.3%
Other Punctuation 13743
 
19.8%
Space Separator 11660
 
16.8%
Dash Punctuation 1697
 
2.4%
Open Punctuation 320
 
0.5%
Close Punctuation 319
 
0.5%
Uppercase Letter 276
 
0.4%
Decimal Number 248
 
0.4%
Lowercase Letter 58
 
0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5265
 
12.8%
3619
 
8.8%
2572
 
6.2%
2570
 
6.2%
2504
 
6.1%
2497
 
6.1%
2490
 
6.0%
2490
 
6.0%
1816
 
4.4%
1357
 
3.3%
Other values (315) 14056
34.1%
Uppercase Letter
ValueCountFrequency (%)
K 38
13.8%
B 31
11.2%
T 28
10.1%
D 25
 
9.1%
S 19
 
6.9%
I 15
 
5.4%
C 15
 
5.4%
A 15
 
5.4%
E 12
 
4.3%
R 10
 
3.6%
Other values (14) 68
24.6%
Lowercase Letter
ValueCountFrequency (%)
e 16
27.6%
r 12
20.7%
w 10
17.2%
o 10
17.2%
l 2
 
3.4%
n 2
 
3.4%
t 2
 
3.4%
i 1
 
1.7%
z 1
 
1.7%
s 1
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 44
17.7%
2 39
15.7%
5 27
10.9%
3 27
10.9%
0 22
8.9%
7 22
8.9%
6 20
8.1%
8 20
8.1%
9 14
 
5.6%
4 13
 
5.2%
Other Punctuation
ValueCountFrequency (%)
* 13656
99.4%
@ 47
 
0.3%
, 37
 
0.3%
/ 3
 
< 0.1%
Letter Number
ValueCountFrequency (%)
3
60.0%
2
40.0%
Space Separator
ValueCountFrequency (%)
11660
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1697
100.0%
Open Punctuation
ValueCountFrequency (%)
( 320
100.0%
Close Punctuation
ValueCountFrequency (%)
) 319
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41236
59.3%
Common 27995
40.2%
Latin 339
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5265
 
12.8%
3619
 
8.8%
2572
 
6.2%
2570
 
6.2%
2504
 
6.1%
2497
 
6.1%
2490
 
6.0%
2490
 
6.0%
1816
 
4.4%
1357
 
3.3%
Other values (315) 14056
34.1%
Latin
ValueCountFrequency (%)
K 38
 
11.2%
B 31
 
9.1%
T 28
 
8.3%
D 25
 
7.4%
S 19
 
5.6%
e 16
 
4.7%
I 15
 
4.4%
C 15
 
4.4%
A 15
 
4.4%
r 12
 
3.5%
Other values (27) 125
36.9%
Common
ValueCountFrequency (%)
* 13656
48.8%
11660
41.7%
- 1697
 
6.1%
( 320
 
1.1%
) 319
 
1.1%
@ 47
 
0.2%
1 44
 
0.2%
2 39
 
0.1%
, 37
 
0.1%
5 27
 
0.1%
Other values (9) 149
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41236
59.3%
ASCII 28329
40.7%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 13656
48.2%
11660
41.2%
- 1697
 
6.0%
( 320
 
1.1%
) 319
 
1.1%
@ 47
 
0.2%
1 44
 
0.2%
2 39
 
0.1%
K 38
 
0.1%
, 37
 
0.1%
Other values (44) 472
 
1.7%
Hangul
ValueCountFrequency (%)
5265
 
12.8%
3619
 
8.8%
2572
 
6.2%
2570
 
6.2%
2504
 
6.1%
2497
 
6.1%
2490
 
6.0%
2490
 
6.0%
1816
 
4.4%
1357
 
3.3%
Other values (315) 14056
34.1%
Number Forms
ValueCountFrequency (%)
3
60.0%
2
40.0%

도로명주소
Text

MISSING 

Distinct1541
Distinct (%)74.2%
Missing435
Missing (%)17.3%
Memory size19.8 KiB
2024-05-11T03:53:24.148209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length53
Mean length38.399423
Min length22

Characters and Unicode

Total characters79794
Distinct characters360
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1299 ?
Unique (%)62.5%

Sample

1st row서울특별시 성동구 청계천로 *** (하왕십리동,지상*층 동원빌딩***호)
2nd row서울특별시 성동구 왕십리로 **-*, 지상*층 (성수동*가, ***-*)
3rd row서울특별시 성동구 뚝섬로 ***, *층,*층 (성수동*가)
4th row서울특별시 성동구 무학봉**길 * (하왕십리동,설악빌딩 *층)
5th row서울특별시 성동구 왕십리로 *** (상왕십리동,외*필지 노블리안 ***호)
ValueCountFrequency (%)
2211
14.8%
서울특별시 2078
13.9%
성동구 2076
13.9%
1160
 
7.7%
949
 
6.3%
성수동*가 731
 
4.9%
395
 
2.6%
행당동 268
 
1.8%
금호동*가 234
 
1.6%
지상*층 176
 
1.2%
Other values (972) 4696
31.4%
2024-05-11T03:53:25.729449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 14801
18.5%
12898
16.2%
4946
 
6.2%
3261
 
4.1%
, 2886
 
3.6%
2347
 
2.9%
) 2184
 
2.7%
( 2184
 
2.7%
2177
 
2.7%
2124
 
2.7%
Other values (350) 29986
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43587
54.6%
Other Punctuation 17698
22.2%
Space Separator 12898
 
16.2%
Close Punctuation 2184
 
2.7%
Open Punctuation 2184
 
2.7%
Dash Punctuation 475
 
0.6%
Decimal Number 397
 
0.5%
Uppercase Letter 333
 
0.4%
Lowercase Letter 27
 
< 0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4946
 
11.3%
3261
 
7.5%
2347
 
5.4%
2177
 
5.0%
2124
 
4.9%
2092
 
4.8%
2078
 
4.8%
2078
 
4.8%
1850
 
4.2%
1521
 
3.5%
Other values (298) 19113
43.9%
Uppercase Letter
ValueCountFrequency (%)
B 70
21.0%
A 45
13.5%
K 29
8.7%
T 23
 
6.9%
D 23
 
6.9%
R 17
 
5.1%
S 17
 
5.1%
C 16
 
4.8%
I 15
 
4.5%
E 13
 
3.9%
Other values (14) 65
19.5%
Decimal Number
ValueCountFrequency (%)
1 118
29.7%
2 68
17.1%
0 59
14.9%
3 54
13.6%
4 23
 
5.8%
5 18
 
4.5%
7 18
 
4.5%
6 17
 
4.3%
8 15
 
3.8%
9 7
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 6
22.2%
r 6
22.2%
w 6
22.2%
o 6
22.2%
s 2
 
7.4%
p 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
* 14801
83.6%
, 2886
 
16.3%
@ 6
 
< 0.1%
? 3
 
< 0.1%
/ 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
12898
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 475
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43587
54.6%
Common 35844
44.9%
Latin 363
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4946
 
11.3%
3261
 
7.5%
2347
 
5.4%
2177
 
5.0%
2124
 
4.9%
2092
 
4.8%
2078
 
4.8%
2078
 
4.8%
1850
 
4.2%
1521
 
3.5%
Other values (298) 19113
43.9%
Latin
ValueCountFrequency (%)
B 70
19.3%
A 45
12.4%
K 29
 
8.0%
T 23
 
6.3%
D 23
 
6.3%
R 17
 
4.7%
S 17
 
4.7%
C 16
 
4.4%
I 15
 
4.1%
E 13
 
3.6%
Other values (22) 95
26.2%
Common
ValueCountFrequency (%)
* 14801
41.3%
12898
36.0%
, 2886
 
8.1%
) 2184
 
6.1%
( 2184
 
6.1%
- 475
 
1.3%
1 118
 
0.3%
2 68
 
0.2%
0 59
 
0.2%
3 54
 
0.2%
Other values (10) 117
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43587
54.6%
ASCII 36204
45.4%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 14801
40.9%
12898
35.6%
, 2886
 
8.0%
) 2184
 
6.0%
( 2184
 
6.0%
- 475
 
1.3%
1 118
 
0.3%
B 70
 
0.2%
2 68
 
0.2%
0 59
 
0.2%
Other values (40) 461
 
1.3%
Hangul
ValueCountFrequency (%)
4946
 
11.3%
3261
 
7.5%
2347
 
5.4%
2177
 
5.0%
2124
 
4.9%
2092
 
4.8%
2078
 
4.8%
2078
 
4.8%
1850
 
4.2%
1521
 
3.5%
Other values (298) 19113
43.9%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct103
Distinct (%)5.0%
Missing473
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean4757.5103
Minimum4700
Maximum6959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.2 KiB
2024-05-11T03:53:26.392498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4700
5-th percentile4704
Q14721
median4762
Q34790
95-th percentile4805
Maximum6959
Range2259
Interquartile range (IQR)69

Descriptive statistics

Standard deviation60.013558
Coefficient of variation (CV)0.012614488
Kurtosis887.86985
Mean4757.5103
Median Absolute Deviation (MAD)32
Skewness24.187036
Sum9705321
Variance3601.6272
MonotonicityNot monotonic
2024-05-11T03:53:26.883663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4794 72
 
2.9%
4808 69
 
2.7%
4793 68
 
2.7%
4782 65
 
2.6%
4709 62
 
2.5%
4775 46
 
1.8%
4783 45
 
1.8%
4718 44
 
1.8%
4779 43
 
1.7%
4713 41
 
1.6%
Other values (93) 1485
59.1%
(Missing) 473
 
18.8%
ValueCountFrequency (%)
4700 30
1.2%
4701 40
1.6%
4702 21
 
0.8%
4703 7
 
0.3%
4704 13
 
0.5%
4705 11
 
0.4%
4706 6
 
0.2%
4707 28
1.1%
4708 12
 
0.5%
4709 62
2.5%
ValueCountFrequency (%)
6959 1
 
< 0.1%
4808 69
2.7%
4805 34
1.4%
4804 32
1.3%
4803 10
 
0.4%
4802 8
 
0.3%
4801 19
 
0.8%
4800 20
 
0.8%
4799 26
 
1.0%
4798 22
 
0.9%
Distinct2388
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
2024-05-11T03:53:27.562008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length7.1862316
Min length1

Characters and Unicode

Total characters18059
Distinct characters754
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2316 ?
Unique (%)92.2%

Sample

1st row(주)아이마코
2nd row청원테크
3rd row(주)팜모드
4th row덕양시스템
5th row주식회사 큐브넷
ValueCountFrequency (%)
주식회사 136
 
4.4%
한국암웨이 21
 
0.7%
세븐일레븐 19
 
0.6%
훼미리마트 18
 
0.6%
왕십리점 17
 
0.5%
gs25 16
 
0.5%
인셀덤 16
 
0.5%
주)하이리빙 16
 
0.5%
씨제이올리브영(주 12
 
0.4%
다이어트 10
 
0.3%
Other values (2577) 2816
90.9%
2024-05-11T03:53:28.930094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
720
 
4.0%
586
 
3.2%
536
 
3.0%
) 528
 
2.9%
( 526
 
2.9%
523
 
2.9%
381
 
2.1%
287
 
1.6%
279
 
1.5%
272
 
1.5%
Other values (744) 13421
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15091
83.6%
Space Separator 586
 
3.2%
Uppercase Letter 542
 
3.0%
Close Punctuation 528
 
2.9%
Open Punctuation 526
 
2.9%
Lowercase Letter 513
 
2.8%
Decimal Number 219
 
1.2%
Other Punctuation 44
 
0.2%
Dash Punctuation 8
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
720
 
4.8%
536
 
3.6%
523
 
3.5%
381
 
2.5%
287
 
1.9%
279
 
1.8%
272
 
1.8%
228
 
1.5%
187
 
1.2%
186
 
1.2%
Other values (671) 11492
76.2%
Uppercase Letter
ValueCountFrequency (%)
S 85
15.7%
G 65
 
12.0%
N 35
 
6.5%
O 33
 
6.1%
A 30
 
5.5%
T 28
 
5.2%
I 26
 
4.8%
J 23
 
4.2%
B 23
 
4.2%
E 22
 
4.1%
Other values (16) 172
31.7%
Lowercase Letter
ValueCountFrequency (%)
e 62
12.1%
o 46
 
9.0%
n 41
 
8.0%
a 41
 
8.0%
s 35
 
6.8%
i 34
 
6.6%
r 34
 
6.6%
t 32
 
6.2%
l 32
 
6.2%
h 20
 
3.9%
Other values (14) 136
26.5%
Decimal Number
ValueCountFrequency (%)
2 73
33.3%
5 59
26.9%
1 24
 
11.0%
4 22
 
10.0%
7 9
 
4.1%
6 8
 
3.7%
9 8
 
3.7%
3 7
 
3.2%
0 7
 
3.2%
8 2
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 18
40.9%
& 14
31.8%
? 6
 
13.6%
' 2
 
4.5%
/ 1
 
2.3%
# 1
 
2.3%
, 1
 
2.3%
1
 
2.3%
Space Separator
ValueCountFrequency (%)
586
100.0%
Close Punctuation
ValueCountFrequency (%)
) 528
100.0%
Open Punctuation
ValueCountFrequency (%)
( 526
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15087
83.5%
Common 1913
 
10.6%
Latin 1055
 
5.8%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
720
 
4.8%
536
 
3.6%
523
 
3.5%
381
 
2.5%
287
 
1.9%
279
 
1.8%
272
 
1.8%
228
 
1.5%
187
 
1.2%
186
 
1.2%
Other values (667) 11488
76.1%
Latin
ValueCountFrequency (%)
S 85
 
8.1%
G 65
 
6.2%
e 62
 
5.9%
o 46
 
4.4%
n 41
 
3.9%
a 41
 
3.9%
s 35
 
3.3%
N 35
 
3.3%
i 34
 
3.2%
r 34
 
3.2%
Other values (40) 577
54.7%
Common
ValueCountFrequency (%)
586
30.6%
) 528
27.6%
( 526
27.5%
2 73
 
3.8%
5 59
 
3.1%
1 24
 
1.3%
4 22
 
1.2%
. 18
 
0.9%
& 14
 
0.7%
7 9
 
0.5%
Other values (13) 54
 
2.8%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15087
83.5%
ASCII 2967
 
16.4%
CJK 4
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
720
 
4.8%
536
 
3.6%
523
 
3.5%
381
 
2.5%
287
 
1.9%
279
 
1.8%
272
 
1.8%
228
 
1.5%
187
 
1.2%
186
 
1.2%
Other values (667) 11488
76.1%
ASCII
ValueCountFrequency (%)
586
19.8%
) 528
17.8%
( 526
17.7%
S 85
 
2.9%
2 73
 
2.5%
G 65
 
2.2%
e 62
 
2.1%
5 59
 
2.0%
o 46
 
1.6%
n 41
 
1.4%
Other values (62) 896
30.2%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
None
ValueCountFrequency (%)
1
100.0%
Distinct2413
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
Minimum2004-03-24 00:00:00
Maximum2024-05-07 17:33:35
2024-05-11T03:53:29.358732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:53:29.811170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
I
1529 
U
984 

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 1529
60.8%
U 984
39.2%

Length

2024-05-11T03:53:30.287262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:30.625657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1529
60.8%
u 984
39.2%
Distinct856
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T03:53:30.976738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:53:31.652407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1164
Distinct (%)47.1%
Missing40
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean203539.78
Minimum194028.64
Maximum206299.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.2 KiB
2024-05-11T03:53:32.424486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194028.64
5-th percentile201383.02
Q1202400.07
median203608.52
Q3204718.25
95-th percentile205557.94
Maximum206299.73
Range12271.095
Interquartile range (IQR)2318.1791

Descriptive statistics

Standard deviation1338.1128
Coefficient of variation (CV)0.0065742077
Kurtosis-0.12669804
Mean203539.78
Median Absolute Deviation (MAD)1133.8316
Skewness-0.20784207
Sum5.0335387 × 108
Variance1790545.8
MonotonicityNot monotonic
2024-05-11T03:53:33.183213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202326.503044305 53
 
2.1%
202511.142930696 41
 
1.6%
204966.098616157 30
 
1.2%
202372.912023599 28
 
1.1%
202113.869605464 28
 
1.1%
204743.677915464 27
 
1.1%
204764.658079784 24
 
1.0%
205039.907145725 23
 
0.9%
202326.470897024 22
 
0.9%
203292.151898869 22
 
0.9%
Other values (1154) 2175
86.5%
(Missing) 40
 
1.6%
ValueCountFrequency (%)
194028.639907457 1
 
< 0.1%
200812.992681398 3
 
0.1%
200813.000885632 1
 
< 0.1%
200855.656010734 1
 
< 0.1%
200872.57005534 1
 
< 0.1%
200896.532906303 2
 
0.1%
200951.206580662 12
0.5%
200967.214079 1
 
< 0.1%
200967.537033206 3
 
0.1%
200971.081407511 2
 
0.1%
ValueCountFrequency (%)
206299.734441078 1
 
< 0.1%
206296.271795372 1
 
< 0.1%
206296.143802875 1
 
< 0.1%
206282.03007881 1
 
< 0.1%
206256.217606196 1
 
< 0.1%
206194.671177891 6
0.2%
206170.06980287 1
 
< 0.1%
206138.230276944 1
 
< 0.1%
206111.359005992 1
 
< 0.1%
206097.463443773 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1164
Distinct (%)47.1%
Missing40
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean450034.45
Minimum444301.34
Maximum452138.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.2 KiB
2024-05-11T03:53:33.948126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444301.34
5-th percentile448508.76
Q1449236.06
median449785.1
Q3450973.92
95-th percentile451686
Maximum452138.17
Range7836.8275
Interquartile range (IQR)1737.8622

Descriptive statistics

Standard deviation1016.5846
Coefficient of variation (CV)0.002258904
Kurtosis-0.75270682
Mean450034.45
Median Absolute Deviation (MAD)810.65342
Skewness0.13631449
Sum1.1129352 × 109
Variance1033444.3
MonotonicityNot monotonic
2024-05-11T03:53:34.691518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450625.58422744 53
 
2.1%
450401.303715561 41
 
1.6%
449159.452779834 30
 
1.2%
451536.680876573 28
 
1.1%
451897.581865192 28
 
1.1%
449357.9464135 27
 
1.1%
449437.628334972 24
 
1.0%
449216.223655036 23
 
0.9%
449954.683065141 22
 
0.9%
451267.730901002 22
 
0.9%
Other values (1154) 2175
86.5%
(Missing) 40
 
1.6%
ValueCountFrequency (%)
444301.343900875 1
< 0.1%
448032.759033613 2
0.1%
448121.687172695 2
0.1%
448129.748333703 1
< 0.1%
448131.986753243 1
< 0.1%
448178.209240365 1
< 0.1%
448178.459724944 1
< 0.1%
448179.869576203 1
< 0.1%
448229.126737125 1
< 0.1%
448229.168685688 1
< 0.1%
ValueCountFrequency (%)
452138.17136839 1
< 0.1%
452130.256229522 1
< 0.1%
452119.787390161 1
< 0.1%
452088.576728202 1
< 0.1%
452078.470105803 1
< 0.1%
452076.36180744 1
< 0.1%
452063.440192474 1
< 0.1%
452048.323797162 1
< 0.1%
452035.039804075 1
< 0.1%
452019.558572479 1
< 0.1%

위생업태명
Categorical

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
775 
영업장판매
737 
전자상거래(통신판매업)
491 
통신판매
240 
다단계판매
123 
Other values (5)
147 

Length

Max length14
Median length12
Mean length5.9470752
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row통신판매
2nd row영업장판매
3rd row영업장판매
4th row영업장판매
5th row영업장판매

Common Values

ValueCountFrequency (%)
<NA> 775
30.8%
영업장판매 737
29.3%
전자상거래(통신판매업) 491
19.5%
통신판매 240
 
9.6%
다단계판매 123
 
4.9%
방문판매 122
 
4.9%
도매업(유통) 9
 
0.4%
기타(복합 등) 7
 
0.3%
전화권유판매 5
 
0.2%
기타 건강기능식품일반판매업 4
 
0.2%

Length

2024-05-11T03:53:35.518671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:36.013807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 775
30.7%
영업장판매 737
29.2%
전자상거래(통신판매업 491
19.5%
통신판매 240
 
9.5%
다단계판매 123
 
4.9%
방문판매 122
 
4.8%
도매업(유통 9
 
0.4%
기타(복합 7
 
0.3%
7
 
0.3%
전화권유판매 5
 
0.2%
Other values (2) 8
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
2318 
0
 
195

Length

Max length4
Median length4
Mean length3.7672105
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> 2318
92.2%
0 195
 
7.8%

Length

2024-05-11T03:53:36.591005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:37.064848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2318
92.2%
0 195
 
7.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
2318 
0
 
195

Length

Max length4
Median length4
Mean length3.7672105
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> 2318
92.2%
0 195
 
7.8%

Length

2024-05-11T03:53:37.373561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:37.746580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2318
92.2%
0 195
 
7.8%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
2470 
상수도전용
 
43

Length

Max length5
Median length4
Mean length4.017111
Min length4

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> 2470
98.3%
상수도전용 43
 
1.7%

Length

2024-05-11T03:53:38.251032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:38.591175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2470
98.3%
상수도전용 43
 
1.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
2318 
0
 
195

Length

Max length4
Median length4
Mean length3.7672105
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> 2318
92.2%
0 195
 
7.8%

Length

2024-05-11T03:53:38.999087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:39.419602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2318
92.2%
0 195
 
7.8%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
1753 
0
757 
1
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.0927179
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1753
69.8%
0 757
30.1%
1 2
 
0.1%
2 1
 
< 0.1%

Length

2024-05-11T03:53:39.933715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:40.527262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1753
69.8%
0 757
30.1%
1 2
 
0.1%
2 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
1753 
0
758 
5
 
1
10
 
1

Length

Max length4
Median length4
Mean length3.0931158
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1753
69.8%
0 758
30.2%
5 1
 
< 0.1%
10 1
 
< 0.1%

Length

2024-05-11T03:53:40.912124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:41.273465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1753
69.8%
0 758
30.2%
5 1
 
< 0.1%
10 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
1751 
0
754 
1
 
4
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.0903303
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1751
69.7%
0 754
30.0%
1 4
 
0.2%
2 3
 
0.1%
3 1
 
< 0.1%

Length

2024-05-11T03:53:41.743733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:42.174128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1751
69.7%
0 754
30.0%
1 4
 
0.2%
2 3
 
0.1%
3 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
1754 
0
759 

Length

Max length4
Median length4
Mean length3.0939117
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1754
69.8%
0 759
30.2%

Length

2024-05-11T03:53:42.848497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:43.157236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1754
69.8%
0 759
30.2%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
1905 
자가
456 
임대
 
152

Length

Max length4
Median length4
Mean length3.5161162
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1905
75.8%
자가 456
 
18.1%
임대 152
 
6.0%

Length

2024-05-11T03:53:43.488272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:43.875675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1905
75.8%
자가 456
 
18.1%
임대 152
 
6.0%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
2310 
0
 
200
20000000
 
1
40000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.7660167
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2310
91.9%
0 200
 
8.0%
20000000 1
 
< 0.1%
40000000 1
 
< 0.1%
10000000 1
 
< 0.1%

Length

2024-05-11T03:53:44.309801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:44.653581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2310
91.9%
0 200
 
8.0%
20000000 1
 
< 0.1%
40000000 1
 
< 0.1%
10000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
<NA>
2310 
0
 
200
1250000
 
1
1500000
 
1
800000
 
1

Length

Max length7
Median length4
Mean length3.764425
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2310
91.9%
0 200
 
8.0%
1250000 1
 
< 0.1%
1500000 1
 
< 0.1%
800000 1
 
< 0.1%

Length

2024-05-11T03:53:45.045080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:53:45.443667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2310
91.9%
0 200
 
8.0%
1250000 1
 
< 0.1%
1500000 1
 
< 0.1%
800000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing775
Missing (%)30.8%
Memory size5.0 KiB
False
1738 
(Missing)
775 
ValueCountFrequency (%)
False 1738
69.2%
(Missing) 775
30.8%
2024-05-11T03:53:45.772882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct18
Distinct (%)1.0%
Missing775
Missing (%)30.8%
Infinite0
Infinite (%)0.0%
Mean0.72108746
Minimum0
Maximum497.99
Zeros1720
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size22.2 KiB
2024-05-11T03:53:46.124238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum497.99
Range497.99
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.44898
Coefficient of variation (CV)18.65097
Kurtosis1091.3038
Mean0.72108746
Median Absolute Deviation (MAD)0
Skewness30.816124
Sum1253.25
Variance180.87507
MonotonicityNot monotonic
2024-05-11T03:53:46.639259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 1720
68.4%
3.3 2
 
0.1%
119.0 1
 
< 0.1%
5.0 1
 
< 0.1%
12.0 1
 
< 0.1%
497.99 1
 
< 0.1%
60.0 1
 
< 0.1%
6.38 1
 
< 0.1%
100.0 1
 
< 0.1%
30.0 1
 
< 0.1%
Other values (8) 8
 
0.3%
(Missing) 775
30.8%
ValueCountFrequency (%)
0.0 1720
68.4%
3.3 2
 
0.1%
5.0 1
 
< 0.1%
6.38 1
 
< 0.1%
6.6 1
 
< 0.1%
6.8 1
 
< 0.1%
12.0 1
 
< 0.1%
19.8 1
 
< 0.1%
28.52 1
 
< 0.1%
30.0 1
 
< 0.1%
ValueCountFrequency (%)
497.99 1
< 0.1%
141.88 1
< 0.1%
119.0 1
< 0.1%
100.0 1
< 0.1%
99.0 1
< 0.1%
72.8 1
< 0.1%
60.0 1
< 0.1%
40.88 1
< 0.1%
30.0 1
< 0.1%
28.52 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2513
Missing (%)100.0%
Memory size22.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030300003030000-134-2002-0000120090414<NA>3폐업2폐업20091221<NA><NA><NA>02 22358754<NA>133880서울특별시 성동구 홍익동 ***번지 이노피스 ***호<NA><NA>(주)아이마코2009-04-14 17:25:56I2018-08-31 23:59:59.0<NA>202778.67869451468.504507통신판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130300003030000-134-2004-0000120040324<NA>3폐업2폐업20061023<NA><NA><NA><NA>53.76133826서울특별시 성동구 성수동*가 ***-*번지 (*층)<NA><NA>청원테크2004-03-24 00:00:00I2018-08-31 23:59:59.0<NA>205260.827744448399.94866영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230300003030000-134-2004-0000220040324<NA>3폐업2폐업20140320<NA><NA><NA>02229416145.76133854서울특별시 성동구 하왕십리동 ***-*번지 지상*층 동원빌딩***호서울특별시 성동구 청계천로 *** (하왕십리동,지상*층 동원빌딩***호)4702(주)팜모드2013-01-07 09:12:33I2018-08-31 23:59:59.0<NA>202376.541636451970.37998영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330300003030000-134-2004-0000420040324<NA>3폐업2폐업20071129<NA><NA><NA>2242194637.15133851서울특별시 성동구 용답동 ***-*번지 (*층)<NA><NA>덕양시스템2004-03-24 00:00:00I2018-08-31 23:59:59.0<NA>205945.32968450667.5581영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430300003030000-134-2004-0000520040324<NA>3폐업2폐업20041021<NA><NA><NA>4537032281.61133833서울특별시 성동구 성수동*가 ***-**번지 (*층)<NA><NA>주식회사 큐브넷2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>204623.140438449327.418298영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530300003030000-134-2004-0000620040324<NA>3폐업2폐업20050803<NA><NA><NA>022291410415.12133869서울특별시 성동구 행당동 ***-**번지 (지하*층)<NA><NA>미건의료기 성동점2004-03-24 00:00:00I2018-08-31 23:59:59.0<NA>202908.364516450755.032711영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630300003030000-134-2004-0000720040324<NA>3폐업2폐업20040721<NA><NA><NA>022298825958.10133809서울특별시 성동구 금호동*가 ****번지 (*층)<NA><NA>건강?2004-03-24 00:00:00I2018-08-31 23:59:59.0<NA>201552.141307449550.010988영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730300003030000-134-2004-0000820040409<NA>3폐업2폐업20181212<NA><NA><NA>02 497909526.25133821서울특별시 성동구 성수동*가 ***-*번지 (지상*층)서울특별시 성동구 왕십리로 **-*, 지상*층 (성수동*가, ***-*)4778중앙비타민2018-12-12 11:09:42U2018-12-14 02:40:00.0<NA>203904.832657449317.777058영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830300003030000-134-2004-0000920040409<NA>3폐업2폐업20050407<NA><NA><NA>2296758014.50133867서울특별시 성동구 행당동 ***-**번지 (지상*층)<NA><NA>솔고헬스케어2004-04-09 00:00:00I2018-08-31 23:59:59.0<NA>202812.091845450980.210853영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930300003030000-134-2004-0001020040412<NA>3폐업2폐업20110901<NA><NA><NA>022291200444.10133871서울특별시 성동구 행당동 **번지 한양대병원 동관*층 류마티즘연구소<NA><NA>임뮤노씽크2006-02-14 00:00:00I2018-08-31 23:59:59.0<NA>203684.127182450698.570811통신판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
250330300003030000-134-2024-000462024-03-29<NA>3폐업2폐업2024-04-14<NA><NA><NA>02 829 6600<NA>133-827서울특별시 성동구 성수동*가 ***-* (주)대명케미칼서울특별시 성동구 성수이로**길 ** (주)대명케미칼 나동 *층 (성수동*가)4784바이엘코리아주식회사2024-04-15 04:15:09U2023-12-03 23:07:00.0<NA>204965.130972448808.060834<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
250430300003030000-134-2024-000472024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-834서울특별시 성동구 성수동*가 ***-** 제이제이빌딩서울특별시 성동구 아차산로*길 **-*, 제이제이빌딩 *층 ***호 (성수동*가)4793핑크누들2024-04-01 11:13:50I2023-12-04 00:03:00.0<NA>204743.677915449357.946414<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
250530300003030000-134-2024-000482024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA>02 69568525<NA>133-924서울특별시 성동구 성수동*가 ***-****서울특별시 성동구 뚝섬로*길 **-*, *층 (성수동*가)4778이승필가정의학과의원2024-04-01 15:09:09I2023-12-04 00:03:00.0<NA>204125.775678449307.471708<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
250630300003030000-134-2024-000492024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-834서울특별시 성동구 성수동*가 ***-* 삼진빌딩서울특별시 성동구 아차산로 ***, 삼진빌딩 *층 ***호 (성수동*가)4794성수멜팅의원2024-04-04 09:40:57I2023-12-04 00:06:00.0<NA>204966.098616449159.45278<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
250730300003030000-134-2024-000502024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA>080 750 1800<NA>133-823서울특별시 성동구 성수동*가 ***-*** KD타워서울특별시 성동구 왕십리로 ***, KD타워 *층 ***호 (성수동*가)4766셀리노2024-04-18 09:37:45I2023-12-03 22:00:00.0<NA>203808.75878449612.381771<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
250830300003030000-134-2024-000512024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-866서울특별시 성동구 행당동 ***-*** 왕십리민자역사서울특별시 성동구 왕십리광장로 **, 왕십리민자역사 *층 OV-**, **호 (행당동)4750365다움의원2024-04-19 09:31:20I2023-12-03 22:01:00.0<NA>203321.56233451001.868688<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
250930300003030000-134-2024-000522024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-070서울특별시 성동구 행당동 *** 행당두산위브서울특별시 성동구 행당로*길 *, ***동 ****호 (행당동, 행당두산위브)4716건강메이드2024-04-22 12:16:13I2023-12-03 22:04:00.0<NA>202716.322136450492.834061<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
251030300003030000-134-2024-000532024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-851서울특별시 성동구 용답동 ***-*서울특별시 성동구 자동차시장*길 **, *층 ***호 (용답동)4808보들부들2024-04-24 14:04:08I2023-12-03 22:06:00.0<NA>205872.055412450720.690537<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
251130300003030000-134-2024-000542024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-100서울특별시 성동구 옥수동 *** 옥수 어울림서울특별시 성동구 독서당로**길 **, ***동 ***호 (옥수동, 옥수 어울림)4739(주)민커머스2024-04-25 11:17:33I2023-12-03 22:07:00.0<NA>201538.056127448894.755197<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
251230300003030000-134-2024-000552024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>133-853서울특별시 성동구 응봉동 ***-** 응봉노블레스빌라서울특별시 성동구 독서당로**길 **-*, *동 ***호 (응봉동, 응봉노블레스빌라)4719반상회2024-05-07 09:55:05I2023-12-05 00:09:00.0<NA>202581.84931450145.723776<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>