Overview

Dataset statistics

Number of variables29
Number of observations126
Missing cells862
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.8 KiB
Average record size in memory250.0 B

Variable types

Categorical10
Numeric7
DateTime4
Unsupported4
Text4

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),자산규모,부채총액,자본금,판매방식명
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18796/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (93.3%)Imbalance
휴업종료일자 is highly imbalanced (93.3%)Imbalance
재개업일자 is highly imbalanced (93.3%)Imbalance
인허가취소일자 has 126 (100.0%) missing valuesMissing
폐업일자 has 44 (34.9%) missing valuesMissing
전화번호 has 16 (12.7%) missing valuesMissing
소재지면적 has 126 (100.0%) missing valuesMissing
지번주소 has 24 (19.0%) missing valuesMissing
도로명주소 has 6 (4.8%) missing valuesMissing
도로명우편번호 has 74 (58.7%) missing valuesMissing
업태구분명 has 126 (100.0%) missing valuesMissing
좌표정보(X) has 4 (3.2%) missing valuesMissing
좌표정보(Y) has 4 (3.2%) missing valuesMissing
자산규모 has 62 (49.2%) missing valuesMissing
부채총액 has 62 (49.2%) missing valuesMissing
자본금 has 62 (49.2%) missing valuesMissing
판매방식명 has 126 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 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
판매방식명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자산규모 has 15 (11.9%) zerosZeros
부채총액 has 42 (33.3%) zerosZeros
자본금 has 12 (9.5%) zerosZeros

Reproduction

Analysis started2024-05-11 09:37:57.532612
Analysis finished2024-05-11 09:37:58.811414
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3190000
126 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 126
100.0%

Length

2024-05-11T09:37:59.146713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:37:59.466074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 126
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9975016 × 1018
Minimum2.0031901 × 1017
Maximum2.024319 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T09:38:00.174105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0031901 × 1017
5-th percentile2.007319 × 1018
Q12.007319 × 1018
median2.009319 × 1018
Q32.016319 × 1018
95-th percentile2.022319 × 1018
Maximum2.024319 × 1018
Range1.824 × 1018
Interquartile range (IQR)9.0000059 × 1015

Descriptive statistics

Standard deviation1.6147264 × 1017
Coefficient of variation (CV)0.080837306
Kurtosis125.72514
Mean1.9975016 × 1018
Median Absolute Deviation (MAD)2 × 1015
Skewness-11.20672
Sum-6.5692214 × 1018
Variance2.6073415 × 1034
MonotonicityStrictly increasing
2024-05-11T09:38:01.184481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200319009924200001 1
 
0.8%
2012319012824200007 1
 
0.8%
2016319015824200004 1
 
0.8%
2016319015824200002 1
 
0.8%
2016319015824200001 1
 
0.8%
2015319015824200006 1
 
0.8%
2015319015824200004 1
 
0.8%
2015319015824200003 1
 
0.8%
2015319015824200002 1
 
0.8%
2015319015824200001 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
200319009924200001 1
0.8%
2005319009924200001 1
0.8%
2006319009924200001 1
0.8%
2007319009924200001 1
0.8%
2007319009924200002 1
0.8%
2007319009924200003 1
0.8%
2007319009924200004 1
0.8%
2007319009924200005 1
0.8%
2007319009924200006 1
0.8%
2007319009924200007 1
0.8%
ValueCountFrequency (%)
2024319027124200001 1
0.8%
2023319027124200002 1
0.8%
2023319027124200001 1
0.8%
2022319027124200003 1
0.8%
2022319027124200002 1
0.8%
2022319027124200001 1
0.8%
2022319021624200003 1
0.8%
2022319021624200002 1
0.8%
2022319021624200001 1
0.8%
2021319021624200001 1
0.8%

인허가일자
Date

Distinct114
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2002-10-17 00:00:00
Maximum2024-01-08 00:00:00
2024-05-11T09:38:01.980188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:38:02.625359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing126
Missing (%)100.0%
Memory size1.2 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
4
54 
3
41 
1
28 
5
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4 54
42.9%
3 41
32.5%
1 28
22.2%
5 3
 
2.4%

Length

2024-05-11T09:38:03.079261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:03.411350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 54
42.9%
3 41
32.5%
1 28
22.2%
5 3
 
2.4%

영업상태명
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
취소/말소/만료/정지/중지
54 
폐업
41 
영업/정상
28 
제외/삭제/전출
 
3

Length

Max length14
Median length8
Mean length7.952381
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 54
42.9%
폐업 41
32.5%
영업/정상 28
22.2%
제외/삭제/전출 3
 
2.4%

Length

2024-05-11T09:38:03.895040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:04.349204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 54
42.9%
폐업 41
32.5%
영업/정상 28
22.2%
제외/삭제/전출 3
 
2.4%

상세영업상태코드
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
7
54 
3
41 
1
28 
5
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
7 54
42.9%
3 41
32.5%
1 28
22.2%
5 3
 
2.4%

Length

2024-05-11T09:38:04.870871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:05.221692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 54
42.9%
3 41
32.5%
1 28
22.2%
5 3
 
2.4%

상세영업상태명
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
직권말소
54 
폐업처리
41 
정상영업
28 
타시군구이관
 
3

Length

Max length6
Median length4
Mean length4.047619
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상영업
2nd row폐업처리
3rd row정상영업
4th row정상영업
5th row정상영업

Common Values

ValueCountFrequency (%)
직권말소 54
42.9%
폐업처리 41
32.5%
정상영업 28
22.2%
타시군구이관 3
 
2.4%

Length

2024-05-11T09:38:05.640949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:06.021124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직권말소 54
42.9%
폐업처리 41
32.5%
정상영업 28
22.2%
타시군구이관 3
 
2.4%

폐업일자
Date

MISSING 

Distinct47
Distinct (%)57.3%
Missing44
Missing (%)34.9%
Memory size1.1 KiB
Minimum2008-05-14 00:00:00
Maximum2023-10-19 00:00:00
2024-05-11T09:38:06.450134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:38:06.955122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
125 
20090114
 
1

Length

Max length8
Median length4
Mean length4.031746
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row<NA>
2nd row20090114
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 125
99.2%
20090114 1
 
0.8%

Length

2024-05-11T09:38:07.366455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:07.825410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
99.2%
20090114 1
 
0.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
125 
20100113
 
1

Length

Max length8
Median length4
Mean length4.031746
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row<NA>
2nd row20100113
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 125
99.2%
20100113 1
 
0.8%

Length

2024-05-11T09:38:08.335569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:08.731981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
99.2%
20100113 1
 
0.8%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
125 
20120424
 
1

Length

Max length8
Median length4
Mean length4.031746
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
99.2%
20120424 1
 
0.8%

Length

2024-05-11T09:38:09.191391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:09.635974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
99.2%
20120424 1
 
0.8%

전화번호
Text

MISSING 

Distinct97
Distinct (%)88.2%
Missing16
Missing (%)12.7%
Memory size1.1 KiB
2024-05-11T09:38:10.459157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12.5
Mean length9.6090909
Min length1

Characters and Unicode

Total characters1057
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)77.3%

Sample

1st row6266-6397
2nd row02
3rd row6266-6397
4th row6266-6397
5th row6069-8800
ValueCountFrequency (%)
6
 
5.1%
02 5
 
4.2%
6266-6397 3
 
2.5%
816-2287 2
 
1.7%
02-591-9902 2
 
1.7%
7170 2
 
1.7%
537 2
 
1.7%
6098-4151 2
 
1.7%
812-2656 2
 
1.7%
582-9004 2
 
1.7%
Other values (87) 90
76.3%
2024-05-11T09:38:11.901938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 159
15.0%
0 158
14.9%
2 140
13.2%
8 98
9.3%
6 87
8.2%
1 71
6.7%
5 71
6.7%
7 70
6.6%
3 67
6.3%
4 66
6.2%
Other values (2) 70
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 890
84.2%
Dash Punctuation 159
 
15.0%
Space Separator 8
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 158
17.8%
2 140
15.7%
8 98
11.0%
6 87
9.8%
1 71
8.0%
5 71
8.0%
7 70
7.9%
3 67
7.5%
4 66
7.4%
9 62
 
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1057
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 159
15.0%
0 158
14.9%
2 140
13.2%
8 98
9.3%
6 87
8.2%
1 71
6.7%
5 71
6.7%
7 70
6.6%
3 67
6.3%
4 66
6.2%
Other values (2) 70
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 159
15.0%
0 158
14.9%
2 140
13.2%
8 98
9.3%
6 87
8.2%
1 71
6.7%
5 71
6.7%
7 70
6.6%
3 67
6.3%
4 66
6.2%
Other values (2) 70
6.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing126
Missing (%)100.0%
Memory size1.2 KiB

소재지우편번호
Categorical

Distinct22
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
49 
156090
24 
156010
15 
156030
8 
156807
6 
Other values (17)
24 

Length

Max length7
Median length6
Mean length5.2301587
Min length4

Unique

Unique13 ?
Unique (%)10.3%

Sample

1st row156010
2nd row156051
3rd row156010
4th row156010
5th row156091

Common Values

ValueCountFrequency (%)
<NA> 49
38.9%
156090 24
19.0%
156010 15
 
11.9%
156030 8
 
6.3%
156807 6
 
4.8%
156050 4
 
3.2%
156080 3
 
2.4%
156091 2
 
1.6%
156811 2
 
1.6%
156810 1
 
0.8%
Other values (12) 12
 
9.5%

Length

2024-05-11T09:38:12.546700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 49
38.9%
156090 24
19.0%
156010 15
 
11.9%
156030 8
 
6.3%
156807 6
 
4.8%
156050 4
 
3.2%
156080 3
 
2.4%
156091 2
 
1.6%
156811 2
 
1.6%
156031 1
 
0.8%
Other values (12) 12
 
9.5%

지번주소
Text

MISSING 

Distinct71
Distinct (%)69.6%
Missing24
Missing (%)19.0%
Memory size1.1 KiB
2024-05-11T09:38:13.267297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length26.960784
Min length19

Characters and Unicode

Total characters2750
Distinct characters104
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)48.0%

Sample

1st row서울특별시 동작구 신대방동 ***번지 *호
2nd row서울특별시 동작구 노량진동 ***번지 우성아파트 ***동 ****호
3rd row서울특별시 동작구 신대방동 ***번지 *호
4th row서울특별시 동작구 신대방동 ***번지 *호
5th row서울특별시 동작구 사당동 ***번지 **호 서림빌딩 *층
ValueCountFrequency (%)
서울특별시 102
17.2%
동작구 100
16.9%
호 90
15.2%
번지 89
15.0%
층 45
7.6%
사당동 33
 
5.6%
신대방동 20
 
3.4%
대방동 15
 
2.5%
13
 
2.2%
상도동 13
 
2.2%
Other values (47) 72
12.2%
2024-05-11T09:38:14.348309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 558
20.3%
491
17.9%
동 216
 
7.9%
서 109
 
4.0%
작 106
 
3.9%
특 102
 
3.7%
별 102
 
3.7%
시 102
 
3.7%
구 102
 
3.7%
울 102
 
3.7%
Other values (94) 760
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1680
61.1%
Other Punctuation 559
 
20.3%
Space Separator 491
 
17.9%
Dash Punctuation 11
 
0.4%
Uppercase Letter 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 216
 
12.9%
서 109
 
6.5%
작 106
 
6.3%
특 102
 
6.1%
별 102
 
6.1%
시 102
 
6.1%
구 102
 
6.1%
울 102
 
6.1%
지 93
 
5.5%
호 91
 
5.4%
Other values (85) 555
33.0%
Uppercase Letter
ValueCountFrequency (%)
T 3
33.3%
K 3
33.3%
B 1
 
11.1%
P 1
 
11.1%
A 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 558
99.8%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1680
61.1%
Common 1061
38.6%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 216
 
12.9%
서 109
 
6.5%
작 106
 
6.3%
특 102
 
6.1%
별 102
 
6.1%
시 102
 
6.1%
구 102
 
6.1%
울 102
 
6.1%
지 93
 
5.5%
호 91
 
5.4%
Other values (85) 555
33.0%
Latin
ValueCountFrequency (%)
T 3
33.3%
K 3
33.3%
B 1
 
11.1%
P 1
 
11.1%
A 1
 
11.1%
Common
ValueCountFrequency (%)
* 558
52.6%
491
46.3%
- 11
 
1.0%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1680
61.1%
ASCII 1070
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 558
52.1%
491
45.9%
- 11
 
1.0%
T 3
 
0.3%
K 3
 
0.3%
B 1
 
0.1%
P 1
 
0.1%
A 1
 
0.1%
/ 1
 
0.1%
Hangul
ValueCountFrequency (%)
동 216
 
12.9%
서 109
 
6.5%
작 106
 
6.3%
특 102
 
6.1%
별 102
 
6.1%
시 102
 
6.1%
구 102
 
6.1%
울 102
 
6.1%
지 93
 
5.5%
호 91
 
5.4%
Other values (85) 555
33.0%

도로명주소
Text

MISSING 

Distinct99
Distinct (%)82.5%
Missing6
Missing (%)4.8%
Memory size1.1 KiB
2024-05-11T09:38:15.120048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length32.133333
Min length22

Characters and Unicode

Total characters3856
Distinct characters143
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)67.5%

Sample

1st row서울특별시 동작구 여의대방로 ** (신대방동)
2nd row서울특별시 동작구 만양로*길 **, ***동 ****호 (노량진동,우성아파트)
3rd row서울특별시 동작구 여의대방로 ** (신대방동)
4th row서울특별시 동작구 여의대방로 ** (신대방동)
5th row서울특별시 동작구 사당로 *** (사당동,서림빌딩 *층)
ValueCountFrequency (%)
서울특별시 120
16.5%
120
16.5%
동작구 119
16.3%
층 53
 
7.3%
호 27
 
3.7%
사당동 20
 
2.7%
대방동 17
 
2.3%
등용로*길 15
 
2.1%
신대방동 13
 
1.8%
상도로 12
 
1.6%
Other values (104) 212
29.1%
2024-05-11T09:38:16.245212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
608
15.8%
* 572
 
14.8%
동 292
 
7.6%
작 159
 
4.1%
서 124
 
3.2%
, 123
 
3.2%
시 123
 
3.2%
울 120
 
3.1%
) 120
 
3.1%
( 120
 
3.1%
Other values (133) 1495
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2279
59.1%
Other Punctuation 696
 
18.0%
Space Separator 608
 
15.8%
Close Punctuation 120
 
3.1%
Open Punctuation 120
 
3.1%
Uppercase Letter 22
 
0.6%
Dash Punctuation 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 292
 
12.8%
작 159
 
7.0%
서 124
 
5.4%
시 123
 
5.4%
울 120
 
5.3%
구 120
 
5.3%
별 120
 
5.3%
특 120
 
5.3%
로 115
 
5.0%
대 102
 
4.5%
Other values (121) 884
38.8%
Uppercase Letter
ValueCountFrequency (%)
T 9
40.9%
K 9
40.9%
B 2
 
9.1%
A 1
 
4.5%
P 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
* 572
82.2%
, 123
 
17.7%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
608
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2279
59.1%
Common 1555
40.3%
Latin 22
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 292
 
12.8%
작 159
 
7.0%
서 124
 
5.4%
시 123
 
5.4%
울 120
 
5.3%
구 120
 
5.3%
별 120
 
5.3%
특 120
 
5.3%
로 115
 
5.0%
대 102
 
4.5%
Other values (121) 884
38.8%
Common
ValueCountFrequency (%)
608
39.1%
* 572
36.8%
, 123
 
7.9%
) 120
 
7.7%
( 120
 
7.7%
- 11
 
0.7%
/ 1
 
0.1%
Latin
ValueCountFrequency (%)
T 9
40.9%
K 9
40.9%
B 2
 
9.1%
A 1
 
4.5%
P 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2279
59.1%
ASCII 1577
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
608
38.6%
* 572
36.3%
, 123
 
7.8%
) 120
 
7.6%
( 120
 
7.6%
- 11
 
0.7%
T 9
 
0.6%
K 9
 
0.6%
B 2
 
0.1%
A 1
 
0.1%
Other values (2) 2
 
0.1%
Hangul
ValueCountFrequency (%)
동 292
 
12.8%
작 159
 
7.0%
서 124
 
5.4%
시 123
 
5.4%
울 120
 
5.3%
구 120
 
5.3%
별 120
 
5.3%
특 120
 
5.3%
로 115
 
5.0%
대 102
 
4.5%
Other values (121) 884
38.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)71.2%
Missing74
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean47258.096
Minimum6913
Maximum156863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T09:38:16.715365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6913
5-th percentile6918.4
Q16932
median6997
Q3156022.75
95-th percentile156853.45
Maximum156863
Range149950
Interquartile range (IQR)149090.75

Descriptive statistics

Standard deviation67020.566
Coefficient of variation (CV)1.4181817
Kurtosis-0.8870186
Mean47258.096
Median Absolute Deviation (MAD)65
Skewness1.0717228
Sum2457421
Variance4.4917563 × 109
MonotonicityNot monotonic
2024-05-11T09:38:17.186080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
6932 8
 
6.3%
7025 3
 
2.4%
6913 2
 
1.6%
6997 2
 
1.6%
156854 2
 
1.6%
6922 2
 
1.6%
6994 2
 
1.6%
156826 2
 
1.6%
6914 1
 
0.8%
6927 1
 
0.8%
Other values (27) 27
 
21.4%
(Missing) 74
58.7%
ValueCountFrequency (%)
6913 2
 
1.6%
6914 1
 
0.8%
6922 2
 
1.6%
6927 1
 
0.8%
6932 8
6.3%
6936 1
 
0.8%
6938 1
 
0.8%
6950 1
 
0.8%
6953 1
 
0.8%
6954 1
 
0.8%
ValueCountFrequency (%)
156863 1
0.8%
156854 2
1.6%
156853 1
0.8%
156848 1
0.8%
156826 2
1.6%
156823 1
0.8%
156806 1
0.8%
156754 1
0.8%
156091 1
0.8%
156060 1
0.8%

사업장명
Text

Distinct118
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T09:38:17.750035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length13
Mean length7.8253968
Min length2

Characters and Unicode

Total characters986
Distinct characters214
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)88.1%

Sample

1st row하나로산업개발(주)
2nd rowAndy유성
3rd row하나로산업개발(주)
4th row하나로산업개발(주)
5th row하나로플래너(주)
ValueCountFrequency (%)
주식회사 19
 
11.7%
하나로산업개발(주 3
 
1.9%
주)태동아이티씨 2
 
1.2%
주 2
 
1.2%
영업센터 2
 
1.2%
현은텔레콤 2
 
1.2%
통신 2
 
1.2%
태양통신 2
 
1.2%
고려이앤씨 2
 
1.2%
유즈커뮤니케이션(주 2
 
1.2%
Other values (123) 124
76.5%
2024-05-11T09:38:18.807962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 66
 
6.7%
이 52
 
5.3%
( 46
 
4.7%
) 46
 
4.7%
36
 
3.7%
사 27
 
2.7%
회 24
 
2.4%
스 23
 
2.3%
식 23
 
2.3%
티 16
 
1.6%
Other values (204) 627
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 802
81.3%
Open Punctuation 46
 
4.7%
Close Punctuation 46
 
4.7%
Space Separator 36
 
3.7%
Lowercase Letter 24
 
2.4%
Uppercase Letter 23
 
2.3%
Other Punctuation 8
 
0.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 66
 
8.2%
이 52
 
6.5%
사 27
 
3.4%
회 24
 
3.0%
스 23
 
2.9%
식 23
 
2.9%
티 16
 
2.0%
신 15
 
1.9%
통 15
 
1.9%
케 14
 
1.7%
Other values (173) 527
65.7%
Uppercase Letter
ValueCountFrequency (%)
T 4
17.4%
M 3
13.0%
A 3
13.0%
E 2
8.7%
G 2
8.7%
S 2
8.7%
L 1
 
4.3%
P 1
 
4.3%
K 1
 
4.3%
F 1
 
4.3%
Other values (3) 3
13.0%
Lowercase Letter
ValueCountFrequency (%)
e 7
29.2%
l 4
16.7%
n 2
 
8.3%
d 2
 
8.3%
o 2
 
8.3%
c 2
 
8.3%
b 1
 
4.2%
a 1
 
4.2%
t 1
 
4.2%
h 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
& 3
37.5%
, 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 802
81.3%
Common 137
 
13.9%
Latin 47
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 66
 
8.2%
이 52
 
6.5%
사 27
 
3.4%
회 24
 
3.0%
스 23
 
2.9%
식 23
 
2.9%
티 16
 
2.0%
신 15
 
1.9%
통 15
 
1.9%
케 14
 
1.7%
Other values (173) 527
65.7%
Latin
ValueCountFrequency (%)
e 7
14.9%
l 4
 
8.5%
T 4
 
8.5%
M 3
 
6.4%
A 3
 
6.4%
E 2
 
4.3%
n 2
 
4.3%
d 2
 
4.3%
o 2
 
4.3%
G 2
 
4.3%
Other values (14) 16
34.0%
Common
ValueCountFrequency (%)
( 46
33.6%
) 46
33.6%
36
26.3%
. 4
 
2.9%
& 3
 
2.2%
, 1
 
0.7%
- 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 802
81.3%
ASCII 184
 
18.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 66
 
8.2%
이 52
 
6.5%
사 27
 
3.4%
회 24
 
3.0%
스 23
 
2.9%
식 23
 
2.9%
티 16
 
2.0%
신 15
 
1.9%
통 15
 
1.9%
케 14
 
1.7%
Other values (173) 527
65.7%
ASCII
ValueCountFrequency (%)
( 46
25.0%
) 46
25.0%
36
19.6%
e 7
 
3.8%
. 4
 
2.2%
l 4
 
2.2%
T 4
 
2.2%
M 3
 
1.6%
A 3
 
1.6%
& 3
 
1.6%
Other values (21) 28
15.2%

최종수정일자
Date

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2007-07-27 18:48:54
Maximum2024-02-15 14:33:54
2024-05-11T09:38:19.486481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:38:19.988853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
I
103 
U
23 

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 103
81.7%
U 23
 
18.3%

Length

2024-05-11T09:38:20.503775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:20.799797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 103
81.7%
u 23
 
18.3%

데이터갱신일자
Date

Distinct26
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-01 23:07:00
2024-05-11T09:38:21.073745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:38:21.409099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing126
Missing (%)100.0%
Memory size1.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct86
Distinct (%)70.5%
Missing4
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean195295.1
Minimum191691.68
Maximum198585.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T09:38:21.812881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191691.68
5-th percentile191775.77
Q1193626.34
median194605.62
Q3198091.9
95-th percentile198297.97
Maximum198585.88
Range6894.1978
Interquartile range (IQR)4465.5675

Descriptive statistics

Standard deviation2276.2371
Coefficient of variation (CV)0.011655372
Kurtosis-1.4133026
Mean195295.1
Median Absolute Deviation (MAD)1884.3548
Skewness0.14379958
Sum23826002
Variance5181255.2
MonotonicityNot monotonic
2024-05-11T09:38:22.346013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194125.60814847 15
 
11.9%
192415.904489299 6
 
4.8%
191691.678396263 3
 
2.4%
193176.63667583 3
 
2.4%
194835.762213041 2
 
1.6%
193639.332709567 2
 
1.6%
191773.113359066 2
 
1.6%
198228.66750094 2
 
1.6%
195159.843317658 2
 
1.6%
194577.984495846 2
 
1.6%
Other values (76) 83
65.9%
(Missing) 4
 
3.2%
ValueCountFrequency (%)
191691.678396263 3
2.4%
191693.61312206 1
 
0.8%
191753.03973638 1
 
0.8%
191773.113359066 2
 
1.6%
191826.307710005 1
 
0.8%
191839.288564199 1
 
0.8%
192135.310595358 1
 
0.8%
192283.757727143 1
 
0.8%
192415.904489299 6
4.8%
193026.631879921 1
 
0.8%
ValueCountFrequency (%)
198585.876201782 2
1.6%
198366.228688108 2
1.6%
198332.497687081 1
0.8%
198320.630192629 1
0.8%
198298.187118645 1
0.8%
198293.812256567 1
0.8%
198275.378711558 1
0.8%
198261.938633463 1
0.8%
198259.59417762 1
0.8%
198255.761425267 1
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct86
Distinct (%)70.5%
Missing4
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean443777.28
Minimum441616.77
Maximum445979.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T09:38:22.916366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441616.77
5-th percentile441697.05
Q1442640.07
median443794.77
Q3445008.15
95-th percentile445617.48
Maximum445979.99
Range4363.2246
Interquartile range (IQR)2368.0753

Descriptive statistics

Standard deviation1331.9755
Coefficient of variation (CV)0.0030014504
Kurtosis-1.3306535
Mean443777.28
Median Absolute Deviation (MAD)1197.0413
Skewness-0.056129129
Sum54140828
Variance1774158.7
MonotonicityNot monotonic
2024-05-11T09:38:23.448264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445475.841471441 15
 
11.9%
443794.771249905 6
 
4.8%
442818.113681285 3
 
2.4%
443379.17134595 3
 
2.4%
444759.157628603 2
 
1.6%
445637.87823237 2
 
1.6%
443070.113294018 2
 
1.6%
442211.135016155 2
 
1.6%
445611.486175435 2
 
1.6%
444921.064676825 2
 
1.6%
Other values (76) 83
65.9%
(Missing) 4
 
3.2%
ValueCountFrequency (%)
441616.77006268 1
0.8%
441657.21421139 1
0.8%
441659.149738346 1
0.8%
441672.922415486 1
0.8%
441690.921865632 2
1.6%
441694.55231525 1
0.8%
441744.549947645 1
0.8%
441808.553923544 1
0.8%
441839.878978481 1
0.8%
441849.20877159 2
1.6%
ValueCountFrequency (%)
445979.994671 1
 
0.8%
445692.62623807 1
 
0.8%
445637.87823237 2
 
1.6%
445633.047209129 1
 
0.8%
445619.199346052 1
 
0.8%
445617.796618445 1
 
0.8%
445611.486175435 2
 
1.6%
445610.919894144 1
 
0.8%
445503.566841864 1
 
0.8%
445475.841471441 15
11.9%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)46.9%
Missing62
Missing (%)49.2%
Infinite0
Infinite (%)0.0%
Mean7.2831818 × 108
Minimum0
Maximum9.6751424 × 109
Zeros15
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T09:38:24.005798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1875000
median50000000
Q31.9440669 × 108
95-th percentile7.0390058 × 109
Maximum9.6751424 × 109
Range9.6751424 × 109
Interquartile range (IQR)1.9353169 × 108

Descriptive statistics

Standard deviation2.0468964 × 109
Coefficient of variation (CV)2.8104425
Kurtosis11.024372
Mean7.2831818 × 108
Median Absolute Deviation (MAD)50000000
Skewness3.4460635
Sum4.6612364 × 1010
Variance4.1897847 × 1018
MonotonicityNot monotonic
2024-05-11T09:38:24.489109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 15
 
11.9%
50000000 10
 
7.9%
10000000 5
 
4.0%
150000000 4
 
3.2%
200000000 3
 
2.4%
7873038799 3
 
2.4%
192542250 1
 
0.8%
2250699069 1
 
0.8%
364485440 1
 
0.8%
174110501 1
 
0.8%
Other values (20) 20
 
15.9%
(Missing) 62
49.2%
ValueCountFrequency (%)
0 15
11.9%
500000 1
 
0.8%
1000000 1
 
0.8%
9500000 1
 
0.8%
10000000 5
 
4.0%
15000000 1
 
0.8%
22868787 1
 
0.8%
25000000 1
 
0.8%
48780675 1
 
0.8%
50000000 10
7.9%
ValueCountFrequency (%)
9675142409 1
 
0.8%
7873038799 3
2.4%
2312818698 1
 
0.8%
2250699069 1
 
0.8%
1900000000 1
 
0.8%
1458674508 1
 
0.8%
1132990011 1
 
0.8%
481000000 1
 
0.8%
364485440 1
 
0.8%
300000000 1
 
0.8%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)31.2%
Missing62
Missing (%)49.2%
Infinite0
Infinite (%)0.0%
Mean6.2949749 × 108
Minimum0
Maximum9.737 × 109
Zeros42
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T09:38:25.014922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.1099663 × 108
95-th percentile3.3583443 × 109
Maximum9.737 × 109
Range9.737 × 109
Interquartile range (IQR)1.1099663 × 108

Descriptive statistics

Standard deviation1.8818501 × 109
Coefficient of variation (CV)2.9894481
Kurtosis15.909569
Mean6.2949749 × 108
Median Absolute Deviation (MAD)0
Skewness3.889623
Sum4.028784 × 1010
Variance3.5413598 × 1018
MonotonicityNot monotonic
2024-05-11T09:38:25.451098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 42
33.3%
3358344276 3
 
2.4%
14000000 2
 
1.6%
1380181641 1
 
0.8%
6391880 1
 
0.8%
486390016 1
 
0.8%
137624427 1
 
0.8%
9737000000 1
 
0.8%
140599686 1
 
0.8%
2778600 1
 
0.8%
Other values (10) 10
 
7.9%
(Missing) 62
49.2%
ValueCountFrequency (%)
0 42
33.3%
867585 1
 
0.8%
2778600 1
 
0.8%
6391880 1
 
0.8%
14000000 2
 
1.6%
102120699 1
 
0.8%
137624427 1
 
0.8%
140000000 1
 
0.8%
140599686 1
 
0.8%
161419480 1
 
0.8%
ValueCountFrequency (%)
9737000000 1
 
0.8%
9573409444 1
 
0.8%
4534945446 1
 
0.8%
3358344276 3
2.4%
1972597182 1
 
0.8%
1380181641 1
 
0.8%
1100000000 1
 
0.8%
486390016 1
 
0.8%
447626062 1
 
0.8%
260854670 1
 
0.8%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)42.2%
Missing62
Missing (%)49.2%
Infinite0
Infinite (%)0.0%
Mean3.4683644 × 108
Minimum-8.4404194 × 109
Maximum9.256 × 109
Zeros12
Zeros (%)9.5%
Negative2
Negative (%)1.6%
Memory size1.2 KiB
2024-05-11T09:38:25.922151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8.4404194 × 109
5-th percentile0
Q14000000
median50000000
Q32 × 108
95-th percentile3.5 × 109
Maximum9.256 × 109
Range1.7696419 × 1010
Interquartile range (IQR)1.96 × 108

Descriptive statistics

Standard deviation1.8219981 × 109
Coefficient of variation (CV)5.2531912
Kurtosis17.221572
Mean3.4683644 × 108
Median Absolute Deviation (MAD)50000000
Skewness0.52361604
Sum2.2197532 × 1010
Variance3.3196772 × 1018
MonotonicityNot monotonic
2024-05-11T09:38:26.433453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 12
 
9.5%
50000000 12
 
9.5%
10000000 7
 
5.6%
300000000 4
 
3.2%
150000000 3
 
2.4%
200000000 3
 
2.4%
3500000000 3
 
2.4%
278101887 1
 
0.8%
25000000 1
 
0.8%
-121904584 1
 
0.8%
Other values (17) 17
 
13.5%
(Missing) 62
49.2%
ValueCountFrequency (%)
-8440419433 1
 
0.8%
-121904584 1
 
0.8%
0 12
9.5%
500000 1
 
0.8%
1000000 1
 
0.8%
5000000 1
 
0.8%
10000000 7
5.6%
25000000 1
 
0.8%
25908488 1
 
0.8%
30000000 1
 
0.8%
ValueCountFrequency (%)
9256000000 1
 
0.8%
4500000000 1
 
0.8%
3500000000 3
2.4%
1011048446 1
 
0.8%
932637057 1
 
0.8%
400000000 1
 
0.8%
350000000 1
 
0.8%
300000000 4
3.2%
278101887 1
 
0.8%
222172437 1
 
0.8%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing126
Missing (%)100.0%
Memory size1.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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63190000200731900992420000420070605<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-7014-1000<NA>156010서울특별시 동작구 신대방동 ***번지 ***동 ***호서울특별시 동작구 신대방*가길 **, ***동 ***호 (신대방동)<NA>유즈커뮤니케이션(주)2007-08-07 18:41:57I2018-08-31 23:59:59.0<NA>191691.678396442818.11368110000000010000000<NA>
73190000200731900992420000520070516<NA>1영업/정상1정상영업<NA><NA><NA><NA>6298-4102<NA>156010서울특별시 동작구 신대방동 ***번지 **호 한컴빌딩 *층서울특별시 동작구 보라매로*길 ** (신대방동,한컴빌딩 *층)<NA>(주)피앤하이컴2007-08-07 18:45:11I2018-08-31 23:59:59.0<NA>193167.049947443326.060409000<NA>
83190000200731900992420000620070507<NA>1영업/정상1정상영업<NA><NA><NA><NA>582-9004<NA>156090서울특별시 동작구 사당동 ****번지 *호서울특별시 동작구 동작대로*길 ** (사당동)<NA>(주)거송아이앤디2007-08-07 18:48:18I2018-08-31 23:59:59.0<NA>198229.647422441690.921866000<NA>
93190000200731900992420000720070403<NA>1영업/정상1정상영업<NA><NA><NA><NA>816-2287<NA>156807서울특별시 동작구 대방동 **번지 **호 KT동작지사 ***호서울특별시 동작구 등용로*길 ***, ***호 (대방동,KT동작지사)<NA>(주)지엠씨와이네트워크2007-08-07 18:51:14I2018-08-31 23:59:59.0<NA>194125.608148445475.84147150000000050000000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
1163190000202131902162420000120210403<NA>3폐업3폐업처리20210920<NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 *** 숭실대학교서울특별시 동작구 상도로 ***, 숭실대학교 창신관 ***호 (상도동)6978주식회사 디노스튜디오2021-09-15 14:09:42U2021-09-17 02:40:00.0<NA>196147.389254443795.142709364485440486390016-121904584<NA>
1173190000202231902162420000120220411<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1566-0296<NA><NA>서울특별시 동작구 대방동 ***-** 산맥빌딩서울특별시 동작구 상도로 **, 산맥빌딩 *층 (대방동)7055(주)한국투자컨설팅2022-04-11 17:45:12I2021-12-03 23:03:00.0<NA>193235.337318444156.155372<NA><NA><NA><NA>
1183190000202231902162420000220150710<NA>3폐업3폐업처리20220823<NA><NA><NA>02-2039-3950<NA><NA>서울특별시 동작구 노량진동 **-* 제이와이빌딩서울특별시 동작구 장승배기로**길 *-*, 제이와이빌딩 ***호 (노량진동)6922(주)해티스2022-08-24 10:36:43I2021-12-07 22:06:00.0<NA>194741.164875445619.199346<NA><NA><NA><NA>
1193190000202231902162420000320220921<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 신대방동 *** 아파트서울특별시 동작구 보라매로 **, ***동 ***호 (신대방동, 아파트)7060알고리즘 통신2022-09-21 16:20:18I2021-12-08 22:03:00.0<NA>193498.73008443833.932922<NA><NA><NA><NA>
1203190000202231902712420000120190118<NA>1영업/정상1정상영업<NA><NA><NA><NA>031-892-2638<NA><NA>서울특별시 동작구 사당동 ****-**서울특별시 동작구 동작대로*길 **, *층 ***호 (사당동)7025아이티코리아2022-11-09 17:51:28U2021-10-31 23:01:00.0<NA>198100.14877441672.922415<NA><NA><NA><NA>
1213190000202231902712420000220221115<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6081-8955<NA><NA>서울특별시 동작구 노량진동 ***-**서울특별시 동작구 등용로**길 **-*, *층 ***-*호 (노량진동)6927시케이컴퍼니2022-11-15 14:12:13I2021-10-31 23:07:00.0<NA>194196.354194445617.796618<NA><NA><NA><NA>
122319000020223190271242000032022-11-16<NA>5제외/삭제/전출5타시군구이관2023-10-19<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 ***-*서울특별시 동작구 만양로**길 **, 지하 *층 (노량진동)6914스마트 퍼밍2023-10-19 11:10:20U2022-10-30 22:01:00.0<NA>195116.060334445503.566842<NA><NA><NA><NA>
123319000020233190271242000012018-12-06<NA>5제외/삭제/전출5타시군구이관2023-09-04<NA><NA><NA>032-664-8282<NA><NA>서울특별시 동작구 사당동 ****-**서울특별시 동작구 동작대로 **, 사임당화장품빌딩 *층 (사당동)7015주식회사 메이드홀딩스2023-09-04 09:17:05U2022-12-09 00:06:00.0<NA>198275.378712441839.878978<NA><NA><NA><NA>
124319000020233190271242000022023-04-17<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 - 816 - 7026<NA><NA>서울특별시 동작구 상도동 ***-*서울특별시 동작구 장승배기로 *-*, 지층 (상도동)6967에스엔피(S&P)2023-06-28 11:33:27U2022-12-05 21:00:00.0<NA>194936.776663444154.877105<NA><NA><NA><NA>
125319000020243190271242000012024-01-08<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 ***-** 마루서울특별시 동작구 상도로**바길 **, 마루 *층 (상도동)6950오투폰2024-01-08 20:26:49I2023-11-30 23:00:00.0<NA>194094.53266444672.981431<NA><NA><NA><NA>