Overview

Dataset statistics

Number of variables26
Number of observations891
Missing cells7152
Missing cells (%)30.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory189.8 KiB
Average record size in memory218.1 B

Variable types

Categorical7
Numeric3
DateTime6
Unsupported4
Text6

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),영업내용
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-17845/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 is highly imbalanced (98.7%)Imbalance
인허가취소일자 has 891 (100.0%) missing valuesMissing
폐업일자 has 380 (42.6%) missing valuesMissing
휴업시작일자 has 880 (98.8%) missing valuesMissing
휴업종료일자 has 880 (98.8%) missing valuesMissing
전화번호 has 305 (34.2%) missing valuesMissing
소재지면적 has 891 (100.0%) missing valuesMissing
소재지우편번호 has 891 (100.0%) missing valuesMissing
도로명주소 has 68 (7.6%) missing valuesMissing
도로명우편번호 has 657 (73.7%) missing valuesMissing
업태구분명 has 891 (100.0%) missing valuesMissing
좌표정보(X) has 41 (4.6%) missing valuesMissing
좌표정보(Y) has 41 (4.6%) missing valuesMissing
영업내용 has 332 (37.3%) missing valuesMissing
관리번호 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
소재지우편번호 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

Reproduction

Analysis started2024-04-06 12:09:38.513717
Analysis finished2024-04-06 12:09:40.049529
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3180000
891 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 891
100.0%

Length

2024-04-06T21:09:40.528640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:40.702025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 891
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct891
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0053573 × 1018
Minimum1.991318 × 1018
Maximum2.024318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-06T21:09:40.958255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.991318 × 1018
5-th percentile1.996818 × 1018
Q12.001318 × 1018
median2.001318 × 1018
Q32.009318 × 1018
95-th percentile2.020318 × 1018
Maximum2.024318 × 1018
Range3.3000013 × 1016
Interquartile range (IQR)8.0000144 × 1015

Descriptive statistics

Standard deviation6.7856172 × 1015
Coefficient of variation (CV)0.0033837448
Kurtosis0.24231904
Mean2.0053573 × 1018
Median Absolute Deviation (MAD)2 × 1015
Skewness0.9851582
Sum-2.5608287 × 1018
Variance4.6044601 × 1031
MonotonicityStrictly increasing
2024-04-06T21:09:41.244016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1991318008508500017 1
 
0.1%
2006318008508200004 1
 
0.1%
2005318008508200024 1
 
0.1%
2005318008508200025 1
 
0.1%
2005318008508200026 1
 
0.1%
2005318008508200027 1
 
0.1%
2005318008508200028 1
 
0.1%
2005318008508200029 1
 
0.1%
2006318008508100010 1
 
0.1%
2006318008508100020 1
 
0.1%
Other values (881) 881
98.9%
ValueCountFrequency (%)
1991318008508500017 1
0.1%
1991318008508500047 1
0.1%
1991318008508500055 1
0.1%
1991318008508500123 1
0.1%
1992318008508500070 1
0.1%
1992318008508500129 1
0.1%
1993318008508500053 1
0.1%
1993318008508500202 1
0.1%
1993318008508500207 1
0.1%
1993318008508500221 1
0.1%
ValueCountFrequency (%)
2024318021808500002 1
0.1%
2024318021808500001 1
0.1%
2023318021808500013 1
0.1%
2023318021808500012 1
0.1%
2023318021808500011 1
0.1%
2023318021808500010 1
0.1%
2023318021808500009 1
0.1%
2023318021808500008 1
0.1%
2023318021808500007 1
0.1%
2023318021808500006 1
0.1%

인허가일자
Date

Distinct705
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum1991-07-24 00:00:00
Maximum2024-02-23 00:00:00
2024-04-06T21:09:41.526905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:09:41.771869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing891
Missing (%)100.0%
Memory size8.0 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3
549 
1
228 
4
110 
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row4
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 549
61.6%
1 228
25.6%
4 110
 
12.3%
2 4
 
0.4%

Length

2024-04-06T21:09:42.002461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:42.226048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 549
61.6%
1 228
25.6%
4 110
 
12.3%
2 4
 
0.4%

영업상태명
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
폐업
549 
영업/정상
228 
취소/말소/만료/정지/중지
110 
휴업
 
4

Length

Max length14
Median length2
Mean length4.2491582
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row취소/말소/만료/정지/중지
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 549
61.6%
영업/정상 228
25.6%
취소/말소/만료/정지/중지 110
 
12.3%
휴업 4
 
0.4%

Length

2024-04-06T21:09:42.498307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:42.721794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 549
61.6%
영업/정상 228
25.6%
취소/말소/만료/정지/중지 110
 
12.3%
휴업 4
 
0.4%

상세영업상태코드
Categorical

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
40
549 
20
155 
70
110 
10
 
31
01
 
28
Other values (3)
 
18

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40
2nd row40
3rd row70
4th row40
5th row40

Common Values

ValueCountFrequency (%)
40 549
61.6%
20 155
 
17.4%
70 110
 
12.3%
10 31
 
3.5%
01 28
 
3.1%
% 9
 
1.0%
99 5
 
0.6%
30 4
 
0.4%

Length

2024-04-06T21:09:42.957701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:43.178602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 549
61.6%
20 155
 
17.4%
70 110
 
12.3%
10 31
 
3.5%
01 28
 
3.1%
9
 
1.0%
99 5
 
0.6%
30 4
 
0.4%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
폐업
549 
정상
155 
취소
110 
<NA>
 
42
설립신청
 
31

Length

Max length4
Median length2
Mean length2.1638608
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 549
61.6%
정상 155
 
17.4%
취소 110
 
12.3%
<NA> 42
 
4.7%
설립신청 31
 
3.5%
휴업 4
 
0.4%

Length

2024-04-06T21:09:43.424865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:43.801687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 549
61.6%
정상 155
 
17.4%
취소 110
 
12.3%
na 42
 
4.7%
설립신청 31
 
3.5%
휴업 4
 
0.4%

폐업일자
Date

MISSING 

Distinct362
Distinct (%)70.8%
Missing380
Missing (%)42.6%
Memory size7.1 KiB
Minimum1998-04-13 00:00:00
Maximum2023-12-20 00:00:00
2024-04-06T21:09:44.062157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:09:44.398046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct11
Distinct (%)100.0%
Missing880
Missing (%)98.8%
Memory size7.1 KiB
Minimum2003-05-22 00:00:00
Maximum2024-03-21 00:00:00
2024-04-06T21:09:44.653898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:09:44.885875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

휴업종료일자
Date

MISSING 

Distinct11
Distinct (%)100.0%
Missing880
Missing (%)98.8%
Memory size7.1 KiB
Minimum2004-06-30 00:00:00
Maximum2027-03-31 00:00:00
2024-04-06T21:09:45.123338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:09:45.350291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
890 
20191204
 
1

Length

Max length8
Median length4
Mean length4.0044893
Min length4

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> 890
99.9%
20191204 1
 
0.1%

Length

2024-04-06T21:09:45.633223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:45.882450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 890
99.9%
20191204 1
 
0.1%

전화번호
Text

MISSING 

Distinct568
Distinct (%)96.9%
Missing305
Missing (%)34.2%
Memory size7.1 KiB
2024-04-06T21:09:46.370662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.831058
Min length7

Characters and Unicode

Total characters5175
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

Unique551 ?
Unique (%)94.0%

Sample

1st row02 780 8622
2nd row02 782 8311
3rd row02 843 7013
4th row02 780 4088
5th row02 844 0011
ValueCountFrequency (%)
02 173
 
20.9%
782 4
 
0.5%
786 4
 
0.5%
8352871 3
 
0.4%
02780 3
 
0.4%
868 3
 
0.4%
831 3
 
0.4%
761 3
 
0.4%
780 3
 
0.4%
8463274 2
 
0.2%
Other values (601) 628
75.8%
2024-04-06T21:09:47.116472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 762
14.7%
0 654
12.6%
3 529
10.2%
7 529
10.2%
8 519
10.0%
6 501
9.7%
4 380
7.3%
1 365
7.1%
5 355
6.9%
348
6.7%
Other values (2) 233
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4825
93.2%
Space Separator 348
 
6.7%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 762
15.8%
0 654
13.6%
3 529
11.0%
7 529
11.0%
8 519
10.8%
6 501
10.4%
4 380
7.9%
1 365
7.6%
5 355
7.4%
9 231
 
4.8%
Space Separator
ValueCountFrequency (%)
348
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 762
14.7%
0 654
12.6%
3 529
10.2%
7 529
10.2%
8 519
10.0%
6 501
9.7%
4 380
7.3%
1 365
7.1%
5 355
6.9%
348
6.7%
Other values (2) 233
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 762
14.7%
0 654
12.6%
3 529
10.2%
7 529
10.2%
8 519
10.0%
6 501
9.7%
4 380
7.3%
1 365
7.1%
5 355
6.9%
348
6.7%
Other values (2) 233
 
4.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing891
Missing (%)100.0%
Memory size8.0 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing891
Missing (%)100.0%
Memory size8.0 KiB

지번주소
Text

Distinct483
Distinct (%)54.5%
Missing4
Missing (%)0.4%
Memory size7.1 KiB
2024-04-06T21:09:47.503065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length27.005637
Min length18

Characters and Unicode

Total characters23954
Distinct characters278
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique374 ?
Unique (%)42.2%

Sample

1st row서울특별시 영등포구 여의도동 **-**번지 ***호
2nd row서울특별시 영등포구 대림동 ***-*번지
3rd row서울특별시 영등포구 여의도동 **-** 대산빌딩 ****호
4th row서울특별시 영등포구 여의도동 **-**번지 원정빌딩 ***호
5th row서울특별시 영등포구 당산동*가 **-**번지
ValueCountFrequency (%)
서울특별시 884
20.8%
영등포구 872
20.5%
번지 543
12.8%
383
9.0%
여의도동 223
 
5.2%
호 186
 
4.4%
신길동 120
 
2.8%
대림동 118
 
2.8%
당산동*가 110
 
2.6%
영등포동*가 107
 
2.5%
Other values (320) 706
16.6%
2024-04-06T21:09:48.161925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 4646
19.4%
3924
16.4%
영 1003
 
4.2%
포 998
 
4.2%
등 994
 
4.1%
동 923
 
3.9%
서 908
 
3.8%
시 901
 
3.8%
구 889
 
3.7%
울 885
 
3.7%
Other values (268) 7883
32.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14544
60.7%
Other Punctuation 4665
 
19.5%
Space Separator 3924
 
16.4%
Dash Punctuation 718
 
3.0%
Uppercase Letter 66
 
0.3%
Decimal Number 15
 
0.1%
Lowercase Letter 11
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 1003
 
6.9%
포 998
 
6.9%
등 994
 
6.8%
동 923
 
6.3%
서 908
 
6.2%
시 901
 
6.2%
구 889
 
6.1%
울 885
 
6.1%
별 884
 
6.1%
특 884
 
6.1%
Other values (227) 5275
36.3%
Uppercase Letter
ValueCountFrequency (%)
B 16
24.2%
C 6
 
9.1%
A 6
 
9.1%
D 6
 
9.1%
M 5
 
7.6%
K 3
 
4.5%
I 3
 
4.5%
T 3
 
4.5%
G 3
 
4.5%
F 2
 
3.0%
Other values (9) 13
19.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
c 3
27.3%
b 1
 
9.1%
k 1
 
9.1%
t 1
 
9.1%
r 1
 
9.1%
n 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 6
40.0%
9 2
 
13.3%
4 2
 
13.3%
3 2
 
13.3%
2 2
 
13.3%
0 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 4646
99.6%
, 10
 
0.2%
/ 5
 
0.1%
. 4
 
0.1%
Space Separator
ValueCountFrequency (%)
3924
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 718
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14544
60.7%
Common 9332
39.0%
Latin 78
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 1003
 
6.9%
포 998
 
6.9%
등 994
 
6.8%
동 923
 
6.3%
서 908
 
6.2%
시 901
 
6.2%
구 889
 
6.1%
울 885
 
6.1%
별 884
 
6.1%
특 884
 
6.1%
Other values (227) 5275
36.3%
Latin
ValueCountFrequency (%)
B 16
20.5%
C 6
 
7.7%
A 6
 
7.7%
D 6
 
7.7%
M 5
 
6.4%
K 3
 
3.8%
I 3
 
3.8%
e 3
 
3.8%
c 3
 
3.8%
T 3
 
3.8%
Other values (17) 24
30.8%
Common
ValueCountFrequency (%)
* 4646
49.8%
3924
42.0%
- 718
 
7.7%
, 10
 
0.1%
1 6
 
0.1%
) 5
 
0.1%
( 5
 
0.1%
/ 5
 
0.1%
. 4
 
< 0.1%
9 2
 
< 0.1%
Other values (4) 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14544
60.7%
ASCII 9409
39.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 4646
49.4%
3924
41.7%
- 718
 
7.6%
B 16
 
0.2%
, 10
 
0.1%
C 6
 
0.1%
A 6
 
0.1%
1 6
 
0.1%
D 6
 
0.1%
) 5
 
0.1%
Other values (30) 66
 
0.7%
Hangul
ValueCountFrequency (%)
영 1003
 
6.9%
포 998
 
6.9%
등 994
 
6.8%
동 923
 
6.3%
서 908
 
6.2%
시 901
 
6.2%
구 889
 
6.1%
울 885
 
6.1%
별 884
 
6.1%
특 884
 
6.1%
Other values (227) 5275
36.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct628
Distinct (%)76.3%
Missing68
Missing (%)7.6%
Memory size7.1 KiB
2024-04-06T21:09:48.669563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length32.55407
Min length22

Characters and Unicode

Total characters26792
Distinct characters289
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique519 ?
Unique (%)63.1%

Sample

1st row서울특별시 영등포구 여의대방로**길 *, ***호 (여의도동)
2nd row서울특별시 영등포구 대림로 *** (대림동)
3rd row서울특별시 영등포구 국회대로**길 **, ****호 (여의도동,대산빌딩)
4th row서울특별시 영등포구 국회대로**길 **, ***호 (여의도동,원정빌딩)
5th row서울특별시 영등포구 양평로 ** (당산동*가)
ValueCountFrequency (%)
859
18.6%
서울특별시 821
17.8%
영등포구 815
17.6%
호 187
 
4.0%
신길동 94
 
2.0%
대림동 92
 
2.0%
여의도동 89
 
1.9%
층 88
 
1.9%
양평동*가 81
 
1.8%
영등포동*가 78
 
1.7%
Other values (435) 1418
30.7%
2024-04-06T21:09:49.744106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4191
 
15.6%
* 4103
 
15.3%
영 1049
 
3.9%
포 989
 
3.7%
등 985
 
3.7%
동 867
 
3.2%
서 858
 
3.2%
시 842
 
3.1%
로 829
 
3.1%
) 826
 
3.1%
Other values (279) 11253
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16142
60.2%
Other Punctuation 4590
 
17.1%
Space Separator 4191
 
15.6%
Close Punctuation 826
 
3.1%
Open Punctuation 826
 
3.1%
Dash Punctuation 121
 
0.5%
Uppercase Letter 66
 
0.2%
Decimal Number 17
 
0.1%
Lowercase Letter 12
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 1049
 
6.5%
포 989
 
6.1%
등 985
 
6.1%
동 867
 
5.4%
서 858
 
5.3%
시 842
 
5.2%
로 829
 
5.1%
구 824
 
5.1%
울 823
 
5.1%
특 821
 
5.1%
Other values (235) 7255
44.9%
Uppercase Letter
ValueCountFrequency (%)
B 13
19.7%
A 7
10.6%
C 6
9.1%
D 5
 
7.6%
K 5
 
7.6%
M 5
 
7.6%
I 3
 
4.5%
G 3
 
4.5%
T 3
 
4.5%
L 2
 
3.0%
Other values (10) 14
21.2%
Decimal Number
ValueCountFrequency (%)
1 4
23.5%
4 4
23.5%
2 3
17.6%
0 2
11.8%
8 1
 
5.9%
9 1
 
5.9%
3 1
 
5.9%
7 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
c 3
25.0%
e 3
25.0%
n 2
16.7%
r 1
 
8.3%
t 1
 
8.3%
k 1
 
8.3%
b 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
* 4103
89.4%
, 479
 
10.4%
/ 4
 
0.1%
. 4
 
0.1%
Space Separator
ValueCountFrequency (%)
4191
100.0%
Close Punctuation
ValueCountFrequency (%)
) 826
100.0%
Open Punctuation
ValueCountFrequency (%)
( 826
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16142
60.2%
Common 10571
39.5%
Latin 79
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 1049
 
6.5%
포 989
 
6.1%
등 985
 
6.1%
동 867
 
5.4%
서 858
 
5.3%
시 842
 
5.2%
로 829
 
5.1%
구 824
 
5.1%
울 823
 
5.1%
특 821
 
5.1%
Other values (235) 7255
44.9%
Latin
ValueCountFrequency (%)
B 13
16.5%
A 7
 
8.9%
C 6
 
7.6%
D 5
 
6.3%
K 5
 
6.3%
M 5
 
6.3%
I 3
 
3.8%
c 3
 
3.8%
G 3
 
3.8%
T 3
 
3.8%
Other values (18) 26
32.9%
Common
ValueCountFrequency (%)
4191
39.6%
* 4103
38.8%
) 826
 
7.8%
( 826
 
7.8%
, 479
 
4.5%
- 121
 
1.1%
/ 4
 
< 0.1%
1 4
 
< 0.1%
. 4
 
< 0.1%
4 4
 
< 0.1%
Other values (6) 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16142
60.2%
ASCII 10649
39.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4191
39.4%
* 4103
38.5%
) 826
 
7.8%
( 826
 
7.8%
, 479
 
4.5%
- 121
 
1.1%
B 13
 
0.1%
A 7
 
0.1%
C 6
 
0.1%
D 5
 
< 0.1%
Other values (33) 72
 
0.7%
Hangul
ValueCountFrequency (%)
영 1049
 
6.5%
포 989
 
6.1%
등 985
 
6.1%
동 867
 
5.4%
서 858
 
5.3%
시 842
 
5.2%
로 829
 
5.1%
구 824
 
5.1%
울 823
 
5.1%
특 821
 
5.1%
Other values (235) 7255
44.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct131
Distinct (%)56.0%
Missing657
Missing (%)73.7%
Memory size7.1 KiB
2024-04-06T21:09:50.323558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3846154
Min length5

Characters and Unicode

Total characters1260
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

Unique78 ?
Unique (%)33.3%

Sample

1st row07371
2nd row07251
3rd row07292
4th row07291
5th row07350
ValueCountFrequency (%)
07238 9
 
3.8%
07206 7
 
3.0%
07251 5
 
2.1%
07333 5
 
2.1%
07272 5
 
2.1%
07261 4
 
1.7%
07395 4
 
1.7%
07299 4
 
1.7%
07320 4
 
1.7%
150103 4
 
1.7%
Other values (121) 183
78.2%
2024-04-06T21:09:51.162316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 321
25.5%
7 201
16.0%
2 158
12.5%
5 124
 
9.8%
1 121
 
9.6%
3 109
 
8.7%
8 70
 
5.6%
4 49
 
3.9%
6 47
 
3.7%
9 37
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1237
98.2%
Dash Punctuation 23
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 321
25.9%
7 201
16.2%
2 158
12.8%
5 124
 
10.0%
1 121
 
9.8%
3 109
 
8.8%
8 70
 
5.7%
4 49
 
4.0%
6 47
 
3.8%
9 37
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 321
25.5%
7 201
16.0%
2 158
12.5%
5 124
 
9.8%
1 121
 
9.6%
3 109
 
8.7%
8 70
 
5.6%
4 49
 
3.9%
6 47
 
3.7%
9 37
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 321
25.5%
7 201
16.0%
2 158
12.5%
5 124
 
9.8%
1 121
 
9.6%
3 109
 
8.7%
8 70
 
5.6%
4 49
 
3.9%
6 47
 
3.7%
9 37
 
2.9%

사업장명
Text

Distinct842
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-04-06T21:09:51.752568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length6.0718294
Min length2

Characters and Unicode

Total characters5410
Distinct characters398
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

Unique800 ?
Unique (%)89.8%

Sample

1st row(주)대종사
2nd row(주)거명기획
3rd row(주)대산
4th row대륙기획
5th row고려광고
ValueCountFrequency (%)
주식회사 30
 
3.1%
월드기획 4
 
0.4%
나래기획 3
 
0.3%
포듐 3
 
0.3%
미래광고 3
 
0.3%
하나기획 3
 
0.3%
서울기획 3
 
0.3%
동방기획 2
 
0.2%
미도공사 2
 
0.2%
가람디자인 2
 
0.2%
Other values (859) 898
94.2%
2024-04-06T21:09:52.503897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 323
 
6.0%
) 280
 
5.2%
( 264
 
4.9%
기 200
 
3.7%
획 159
 
2.9%
드 137
 
2.5%
이 135
 
2.5%
광 130
 
2.4%
고 122
 
2.3%
인 122
 
2.3%
Other values (388) 3538
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4690
86.7%
Close Punctuation 280
 
5.2%
Open Punctuation 264
 
4.9%
Uppercase Letter 80
 
1.5%
Space Separator 62
 
1.1%
Other Punctuation 13
 
0.2%
Lowercase Letter 10
 
0.2%
Decimal Number 9
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 323
 
6.9%
기 200
 
4.3%
획 159
 
3.4%
드 137
 
2.9%
이 135
 
2.9%
광 130
 
2.8%
고 122
 
2.6%
인 122
 
2.6%
애 109
 
2.3%
디 103
 
2.2%
Other values (350) 3150
67.2%
Uppercase Letter
ValueCountFrequency (%)
C 11
13.8%
I 10
12.5%
N 8
10.0%
M 6
 
7.5%
G 6
 
7.5%
S 6
 
7.5%
T 5
 
6.2%
R 5
 
6.2%
A 4
 
5.0%
E 4
 
5.0%
Other values (7) 15
18.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
t 2
20.0%
i 1
10.0%
n 1
10.0%
a 1
10.0%
r 1
10.0%
c 1
10.0%
d 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 3
33.3%
2 3
33.3%
3 1
 
11.1%
4 1
 
11.1%
5 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 8
61.5%
& 2
 
15.4%
, 2
 
15.4%
＆ 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 280
100.0%
Open Punctuation
ValueCountFrequency (%)
( 264
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4690
86.7%
Common 630
 
11.6%
Latin 90
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 323
 
6.9%
기 200
 
4.3%
획 159
 
3.4%
드 137
 
2.9%
이 135
 
2.9%
광 130
 
2.8%
고 122
 
2.6%
인 122
 
2.6%
애 109
 
2.3%
디 103
 
2.2%
Other values (350) 3150
67.2%
Latin
ValueCountFrequency (%)
C 11
12.2%
I 10
 
11.1%
N 8
 
8.9%
M 6
 
6.7%
G 6
 
6.7%
S 6
 
6.7%
T 5
 
5.6%
R 5
 
5.6%
A 4
 
4.4%
E 4
 
4.4%
Other values (15) 25
27.8%
Common
ValueCountFrequency (%)
) 280
44.4%
( 264
41.9%
62
 
9.8%
. 8
 
1.3%
1 3
 
0.5%
2 3
 
0.5%
& 2
 
0.3%
, 2
 
0.3%
- 2
 
0.3%
3 1
 
0.2%
Other values (3) 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4688
86.7%
ASCII 719
 
13.3%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 323
 
6.9%
기 200
 
4.3%
획 159
 
3.4%
드 137
 
2.9%
이 135
 
2.9%
광 130
 
2.8%
고 122
 
2.6%
인 122
 
2.6%
애 109
 
2.3%
디 103
 
2.2%
Other values (349) 3148
67.2%
ASCII
ValueCountFrequency (%)
) 280
38.9%
( 264
36.7%
62
 
8.6%
C 11
 
1.5%
I 10
 
1.4%
. 8
 
1.1%
N 8
 
1.1%
M 6
 
0.8%
G 6
 
0.8%
S 6
 
0.8%
Other values (27) 58
 
8.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정일자
Date

Distinct811
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum1991-07-24 00:00:00
Maximum2024-03-28 16:37:55
2024-04-06T21:09:52.767065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:09:53.035826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
I
500 
U
391 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 500
56.1%
U 391
43.9%

Length

2024-04-06T21:09:53.248965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:09:53.424708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 500
56.1%
u 391
43.9%

데이터갱신일자
Date

Distinct101
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-06T21:09:53.645178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:09:53.954412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing891
Missing (%)100.0%
Memory size8.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct578
Distinct (%)68.0%
Missing41
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean191809.14
Minimum181539.51
Maximum203919.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-06T21:09:54.222102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum181539.51
5-th percentile190161.57
Q1190878.43
median191553.21
Q3192880.95
95-th percentile193787.76
Maximum203919.5
Range22379.988
Interquartile range (IQR)2002.5119

Descriptive statistics

Standard deviation1420.213
Coefficient of variation (CV)0.007404303
Kurtosis12.884957
Mean191809.14
Median Absolute Deviation (MAD)862.48602
Skewness1.07139
Sum1.6303777 × 108
Variance2017004.9
MonotonicityNot monotonic
2024-04-06T21:09:54.847898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193282.654266684 12
 
1.3%
193469.554731741 9
 
1.0%
190828.268143013 8
 
0.9%
192934.679988733 7
 
0.8%
190372.127120283 7
 
0.8%
192969.820840993 7
 
0.8%
191031.927735122 7
 
0.8%
194530.535390096 6
 
0.7%
194561.746032498 6
 
0.7%
190996.357288859 6
 
0.7%
Other values (568) 775
87.0%
(Missing) 41
 
4.6%
ValueCountFrequency (%)
181539.508264155 1
0.1%
185653.303294561 1
0.1%
186071.676915153 1
0.1%
189567.256144053 1
0.1%
189653.829218246 1
0.1%
189674.216564428 2
0.2%
189689.859838034 1
0.1%
189700.355755718 1
0.1%
189723.750290155 1
0.1%
189734.544016734 2
0.2%
ValueCountFrequency (%)
203919.495860998 1
 
0.1%
201635.68062994 1
 
0.1%
199550.320164815 1
 
0.1%
199037.541694145 1
 
0.1%
196078.108047045 1
 
0.1%
194632.526367463 1
 
0.1%
194561.746032498 6
0.7%
194530.535390096 6
0.7%
194370.32715363 1
 
0.1%
194028.635844427 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct578
Distinct (%)68.0%
Missing41
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean446159.09
Minimum433767.57
Maximum450635.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-06T21:09:55.120336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum433767.57
5-th percentile443450.2
Q1445202.64
median446496.68
Q3447231.56
95-th percentile448223.83
Maximum450635.25
Range16867.687
Interquartile range (IQR)2028.9139

Descriptive statistics

Standard deviation1560.9658
Coefficient of variation (CV)0.0034986753
Kurtosis4.6519509
Mean446159.09
Median Absolute Deviation (MAD)922.96694
Skewness-1.1331745
Sum3.7923523 × 108
Variance2436614.3
MonotonicityNot monotonic
2024-04-06T21:09:55.395307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447611.552045596 12
 
1.3%
446508.068667777 9
 
1.0%
445548.79737092 8
 
0.9%
447522.605711768 7
 
0.8%
448218.446478138 7
 
0.8%
447419.648688406 7
 
0.8%
443665.206911515 7
 
0.8%
446306.787198089 6
 
0.7%
446364.318286465 6
 
0.7%
445841.377603245 6
 
0.7%
Other values (568) 775
87.0%
(Missing) 41
 
4.6%
ValueCountFrequency (%)
433767.565586245 1
 
0.1%
438041.497247854 1
 
0.1%
441822.713782044 1
 
0.1%
442621.787911877 1
 
0.1%
442756.531513655 1
 
0.1%
442835.171044815 1
 
0.1%
442859.720767624 1
 
0.1%
442905.116903156 2
0.2%
442905.413546796 3
0.3%
442916.550661673 1
 
0.1%
ValueCountFrequency (%)
450635.252086817 1
0.1%
450165.231476195 1
0.1%
450153.525269193 1
0.1%
449674.170276314 1
0.1%
449133.635570461 1
0.1%
449015.382667848 1
0.1%
448896.727242794 1
0.1%
448883.184967604 1
0.1%
448871.733893544 2
0.2%
448656.726986041 1
0.1%

영업내용
Text

MISSING 

Distinct130
Distinct (%)23.3%
Missing332
Missing (%)37.3%
Memory size7.1 KiB
2024-04-06T21:09:55.714643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length5
Mean length6.7942755
Min length2

Characters and Unicode

Total characters3798
Distinct characters150
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 (%)19.9%

Sample

1st row옥외광고업
2nd row옥외광고업
3rd row옥외광고업
4th row옥외광고업
5th row옥외광고업
ValueCountFrequency (%)
옥외광고업 378
46.7%
및 56
 
6.9%
제작 52
 
6.4%
대행 33
 
4.1%
옥외광고물 28
 
3.5%
광고물제작 23
 
2.8%
광고물 19
 
2.3%
옥외광고 13
 
1.6%
광고대행 12
 
1.5%
간판 10
 
1.2%
Other values (132) 185
22.9%
2024-04-06T21:09:56.267683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 560
14.7%
고 558
14.7%
옥 456
12.0%
외 456
12.0%
업 417
11.0%
253
 
6.7%
제 129
 
3.4%
작 114
 
3.0%
물 109
 
2.9%
대 73
 
1.9%
Other values (140) 673
17.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3413
89.9%
Space Separator 253
 
6.7%
Other Punctuation 80
 
2.1%
Decimal Number 21
 
0.6%
Open Punctuation 9
 
0.2%
Close Punctuation 9
 
0.2%
Uppercase Letter 8
 
0.2%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 560
16.4%
고 558
16.3%
옥 456
13.4%
외 456
13.4%
업 417
12.2%
제 129
 
3.8%
작 114
 
3.3%
물 109
 
3.2%
대 73
 
2.1%
행 71
 
2.1%
Other values (118) 470
13.8%
Decimal Number
ValueCountFrequency (%)
1 5
23.8%
2 5
23.8%
0 4
19.0%
8 2
 
9.5%
7 2
 
9.5%
6 1
 
4.8%
9 1
 
4.8%
3 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 54
67.5%
. 14
 
17.5%
/ 9
 
11.2%
: 1
 
1.2%
? 1
 
1.2%
; 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
L 3
37.5%
E 2
25.0%
D 2
25.0%
A 1
 
12.5%
Space Separator
ValueCountFrequency (%)
253
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3413
89.9%
Common 377
 
9.9%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 560
16.4%
고 558
16.3%
옥 456
13.4%
외 456
13.4%
업 417
12.2%
제 129
 
3.8%
작 114
 
3.3%
물 109
 
3.2%
대 73
 
2.1%
행 71
 
2.1%
Other values (118) 470
13.8%
Common
ValueCountFrequency (%)
253
67.1%
, 54
 
14.3%
. 14
 
3.7%
/ 9
 
2.4%
( 9
 
2.4%
) 9
 
2.4%
1 5
 
1.3%
- 5
 
1.3%
2 5
 
1.3%
0 4
 
1.1%
Other values (8) 10
 
2.7%
Latin
ValueCountFrequency (%)
L 3
37.5%
E 2
25.0%
D 2
25.0%
A 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3413
89.9%
ASCII 385
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 560
16.4%
고 558
16.3%
옥 456
13.4%
외 456
13.4%
업 417
12.2%
제 129
 
3.8%
작 114
 
3.3%
물 109
 
3.2%
대 73
 
2.1%
행 71
 
2.1%
Other values (118) 470
13.8%
ASCII
ValueCountFrequency (%)
253
65.7%
, 54
 
14.0%
. 14
 
3.6%
/ 9
 
2.3%
( 9
 
2.3%
) 9
 
2.3%
1 5
 
1.3%
- 5
 
1.3%
2 5
 
1.3%
0 4
 
1.0%
Other values (12) 18
 
4.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
03180000199131800850850001719910724<NA>3폐업40폐업20131209<NA><NA><NA>02 780 8622<NA><NA>서울특별시 영등포구 여의도동 **-**번지 ***호서울특별시 영등포구 여의대방로**길 *, ***호 (여의도동)<NA>(주)대종사2013-12-10 11:04:12I2018-08-31 23:59:59.0<NA>193787.76227446371.610691옥외광고업
13180000199131800850850004719910724<NA>3폐업40폐업19991213<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 ***-*번지서울특별시 영등포구 대림로 *** (대림동)<NA>(주)거명기획2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>190946.718498443932.700621옥외광고업
2318000019913180085085000551991-07-24<NA>4취소/말소/만료/정지/중지70취소<NA><NA><NA><NA>02 782 8311<NA><NA>서울특별시 영등포구 여의도동 **-** 대산빌딩 ****호서울특별시 영등포구 국회대로**길 **, ****호 (여의도동,대산빌딩)<NA>(주)대산2023-05-19 18:29:18U2022-12-04 22:01:00.0<NA>192852.010701447460.202083<NA>
33180000199131800850850012319911129<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 **-**번지 원정빌딩 ***호서울특별시 영등포구 국회대로**길 **, ***호 (여의도동,원정빌딩)<NA>대륙기획2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>192636.733285447145.450292옥외광고업
43180000199231800850850007019920417<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동*가 **-**번지서울특별시 영등포구 양평로 ** (당산동*가)<NA>고려광고2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>191510.61802447776.853735옥외광고업
53180000199231800850850012919920520<NA>3폐업40폐업19981117<NA><NA><NA>02 843 7013<NA><NA>서울특별시 영등포구 신길동 ***-**번지서울특별시 영등포구 도신로**길 * (신길동)<NA>태광기획2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>192361.825127445525.515554옥외광고업
63180000199331800850850005319930210<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 신길동 **-**번지서울특별시 영등포구 영등포로 *** (신길동)<NA>한국종합광고2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>192946.280189445685.944519옥외광고업
73180000199331800850850020219930414<NA>3폐업40폐업20001025<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 신길동 ***-*번지서울특별시 영등포구 가마산로**나길 ** (신길동)<NA>한양광고2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>191661.068483444967.853668옥외광고업
83180000199331800850850020719930525<NA>3폐업40폐업19990802<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 ***-*번지서울특별시 영등포구 대림로**길 ** (대림동)<NA>명작광고디자인2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>190988.207756443448.641062옥외광고업
93180000199331800850850022119930827<NA>3폐업40폐업20000316<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 ***-*번지서울특별시 영등포구 대림로**가길 ** (대림동)<NA>일손기획2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA>190985.176384443755.745846옥외광고업
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
881318000020233180218085000062023-05-03<NA>1영업/정상20정상<NA><NA><NA><NA>0237704812<NA><NA>서울특별시 영등포구 여의도동 **-* 엔에이치농협캐피탈빌딩서울특별시 영등포구 국제금융로*길 **-*, 엔에이치농협캐피탈빌딩 *층 (여의도동)07332(주)지앤비시스템2024-01-25 14:18:24U2023-11-30 22:07:00.0<NA>193598.53644446357.770653<NA>
882318000020233180218085000072023-05-08<NA>1영업/정상20정상<NA><NA><NA><NA>0263323042<NA><NA>서울특별시 영등포구 여의도동 **-* 삼보빌딩 ***호서울특별시 영등포구 국회대로**길 *, 삼보빌딩 ***호 (여의도동)07238주식회사 단아커뮤니케이션2023-10-20 10:39:16U2022-10-30 22:02:00.0<NA>192974.136279447585.389405<NA>
883318000020233180218085000082023-06-01<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동*가 *-* MG신용정보빌딩서울특별시 영등포구 영등포로 ***, MG신용정보빌딩 (당산동*가)07292엠지신용정보 주식회사2023-10-20 10:38:34U2022-10-30 22:02:00.0<NA>191030.288738446482.271251<NA>
884318000020233180218085000092023-07-04<NA>1영업/정상20정상<NA><NA><NA><NA>025853036<NA><NA>서울특별시 영등포구 영등포동*가 **-** 우성빌딩서울특별시 영등포구 버드나루로 **, 우성빌딩 *층 (영등포동*가)07247(주)엔쓰컴퍼니2023-10-20 10:37:24U2022-10-30 22:02:00.0<NA>191918.689235446964.793381<NA>
885318000020233180218085000102023-07-05<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 ***-** 가람빌딩서울특별시 영등포구 도림로 ***, 가람빌딩 *층 (대림동)07422대명광고2023-10-20 10:36:30U2022-10-30 22:02:00.0<NA>191227.895848443717.344225<NA>
886318000020233180218085000111999-02-05<NA>1영업/정상20정상<NA><NA><NA><NA>02 8370035<NA><NA>서울특별시 영등포구 대림동 ***-*서울특별시 영등포구 대림로**가길 *, *층 (대림동)07414좋은디자인2023-10-20 10:10:05U2022-10-30 22:02:00.0<NA>190740.377309443718.868442<NA>
887318000020233180218085000122023-07-24<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 **-** 가든빌딩 ***호서울특별시 영등포구 국회대로**길 **, 가든빌딩 ***호 (여의도동)07238(주)이엠비즈2023-10-20 09:54:33U2022-10-30 22:02:00.0<NA>192969.820841447419.648688<NA>
888318000020233180218085000132023-12-26<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동*가 **서울특별시 영등포구 선유로**길 ** (양평동*가)07210지에스엠비즈 주식회사2024-01-03 17:21:29U2023-12-01 00:05:00.0<NA>190539.090154447911.03148<NA>
889318000020243180218085000012024-01-03<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동*가 **-**서울특별시 영등포구 선유동*로 *-*, *층 (당산동*가)07263디에스에이디(DS Ad)2024-01-11 17:39:04U2023-11-30 23:03:00.0<NA>190363.607136446697.649231<NA>
890318000020243180218085000022024-02-16<NA>1영업/정상20정상<NA><NA><NA><NA>0220554097<NA><NA>서울특별시 영등포구 여의도동 **-* 에프케이아이타워서울특별시 영등포구 여의대로 **, 에프케이아이타워 **층 (여의도동)07320주식회사 위블링2024-02-20 13:23:07U2023-12-01 22:02:00.0<NA>192880.946054446664.787384<NA>