Overview

Dataset statistics

Number of variables26
Number of observations293
Missing cells1855
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory63.1 KiB
Average record size in memory220.5 B

Variable types

Categorical8
Numeric4
DateTime5
Unsupported4
Text5

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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-17846/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 has constant value ""Constant
영업내용 has a high cardinality: 51 distinct valuesHigh cardinality
영업상태코드 is highly imbalanced (59.7%)Imbalance
영업상태명 is highly imbalanced (59.7%)Imbalance
상세영업상태명 is highly imbalanced (69.3%)Imbalance
휴업시작일자 is highly imbalanced (95.1%)Imbalance
휴업종료일자 is highly imbalanced (95.1%)Imbalance
영업내용 is highly imbalanced (57.0%)Imbalance
인허가취소일자 has 293 (100.0%) missing valuesMissing
폐업일자 has 66 (22.5%) missing valuesMissing
재개업일자 has 292 (99.7%) missing valuesMissing
전화번호 has 50 (17.1%) missing valuesMissing
소재지면적 has 293 (100.0%) missing valuesMissing
소재지우편번호 has 293 (100.0%) missing valuesMissing
지번주소 has 7 (2.4%) missing valuesMissing
도로명주소 has 30 (10.2%) missing valuesMissing
도로명우편번호 has 192 (65.5%) missing valuesMissing
업태구분명 has 293 (100.0%) missing valuesMissing
좌표정보(X) has 23 (7.8%) missing valuesMissing
좌표정보(Y) has 23 (7.8%) 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 started2024-05-11 06:59:37.739409
Analysis finished2024-05-11 06:59:38.660632
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3190000
293 

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 293
100.0%

Length

2024-05-11T15:59:38.777682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:38.935704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 293
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct293
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0013531 × 1018
Minimum1.992319 × 1018
Maximum2.024319 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:59:39.098907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.992319 × 1018
5-th percentile1.992319 × 1018
Q11.994319 × 1018
median2.000319 × 1018
Q32.005319 × 1018
95-th percentile2.018319 × 1018
Maximum2.024319 × 1018
Range3.2000019 × 1016
Interquartile range (IQR)1.1 × 1016

Descriptive statistics

Standard deviation8.074497 × 1015
Coefficient of variation (CV)0.0040345189
Kurtosis-0.016559695
Mean2.0013531 × 1018
Median Absolute Deviation (MAD)6 × 1015
Skewness0.83575487
Sum-3.8993408 × 1018
Variance6.5197502 × 1031
MonotonicityStrictly increasing
2024-05-11T15:59:39.373240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1992319007508500006 1
 
0.3%
2003319007508500193 1
 
0.3%
2004319007508500210 1
 
0.3%
2004319007508500209 1
 
0.3%
2004319007508500208 1
 
0.3%
2004319007508500207 1
 
0.3%
2004319007508500206 1
 
0.3%
2004319007508500205 1
 
0.3%
2004319007508500203 1
 
0.3%
2004319007508500202 1
 
0.3%
Other values (283) 283
96.6%
ValueCountFrequency (%)
1992319007508500006 1
0.3%
1992319007508500007 1
0.3%
1992319007508500008 1
0.3%
1992319007508500009 1
0.3%
1992319007508500010 1
0.3%
1992319007508500011 1
0.3%
1992319007508500012 1
0.3%
1992319007508500013 1
0.3%
1992319007508500014 1
0.3%
1992319007508500015 1
0.3%
ValueCountFrequency (%)
2024319026708500001 1
0.3%
2023319026708500001 1
0.3%
2022319026708500001 1
0.3%
2021319021008500003 1
0.3%
2021319021008500002 1
0.3%
2021319021008500001 1
0.3%
2020319021008500005 1
0.3%
2020319021008500004 1
0.3%
2020319021008500003 1
0.3%
2020319021008500002 1
0.3%

인허가일자
Date

Distinct231
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1992-02-24 00:00:00
Maximum2023-09-22 00:00:00
2024-05-11T15:59:39.739494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:59:39.969632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3
232 
1
58 
4
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
3 232
79.2%
1 58
 
19.8%
4 2
 
0.7%
2 1
 
0.3%

Length

2024-05-11T15:59:40.190595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:40.366523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 232
79.2%
1 58
 
19.8%
4 2
 
0.7%
2 1
 
0.3%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
232 
영업/정상
58 
취소/말소/만료/정지/중지
 
2
휴업
 
1

Length

Max length14
Median length2
Mean length2.6757679
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 232
79.2%
영업/정상 58
 
19.8%
취소/말소/만료/정지/중지 2
 
0.7%
휴업 1
 
0.3%

Length

2024-05-11T15:59:40.586865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:40.810465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 232
79.2%
영업/정상 58
 
19.8%
취소/말소/만료/정지/중지 2
 
0.7%
휴업 1
 
0.3%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.324232
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:59:40.972033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20
Q140
median40
Q340
95-th percentile40
Maximum90
Range89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.0065041
Coefficient of variation (CV)0.24794754
Kurtosis5.2212647
Mean36.324232
Median Absolute Deviation (MAD)0
Skewness-0.34834185
Sum10643
Variance81.117116
MonotonicityNot monotonic
2024-05-11T15:59:41.123574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
40 232
79.2%
20 56
 
19.1%
30 1
 
0.3%
1 1
 
0.3%
50 1
 
0.3%
90 1
 
0.3%
72 1
 
0.3%
ValueCountFrequency (%)
1 1
 
0.3%
20 56
 
19.1%
30 1
 
0.3%
40 232
79.2%
50 1
 
0.3%
72 1
 
0.3%
90 1
 
0.3%
ValueCountFrequency (%)
90 1
 
0.3%
72 1
 
0.3%
50 1
 
0.3%
40 232
79.2%
30 1
 
0.3%
20 56
 
19.1%
1 1
 
0.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
232 
정상
56 
휴업
 
1
<NA>
 
1
영업정지
 
1
Other values (2)
 
2

Length

Max length8
Median length2
Mean length2.0409556
Min length2

Unique

Unique5 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 232
79.2%
정상 56
 
19.1%
휴업 1
 
0.3%
<NA> 1
 
0.3%
영업정지 1
 
0.3%
등록신청 1
 
0.3%
신청취소(반려) 1
 
0.3%

Length

2024-05-11T15:59:41.333373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:41.528308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 232
79.2%
정상 56
 
19.1%
휴업 1
 
0.3%
na 1
 
0.3%
영업정지 1
 
0.3%
등록신청 1
 
0.3%
신청취소(반려 1
 
0.3%

폐업일자
Date

MISSING 

Distinct126
Distinct (%)55.5%
Missing66
Missing (%)22.5%
Memory size2.4 KiB
Minimum1993-06-09 00:00:00
Maximum2024-03-11 00:00:00
2024-05-11T15:59:41.754893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:59:41.996078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
20151118
 
1
20181212
 
1
20060608
 
1

Length

Max length8
Median length4
Mean length4.0409556
Min length4

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
99.0%
20151118 1
 
0.3%
20181212 1
 
0.3%
20060608 1
 
0.3%

Length

2024-05-11T15:59:42.232696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:42.455131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
99.0%
20151118 1
 
0.3%
20181212 1
 
0.3%
20060608 1
 
0.3%

휴업종료일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
20161117
 
1
20251212
 
1
20061207
 
1

Length

Max length8
Median length4
Mean length4.0409556
Min length4

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
99.0%
20161117 1
 
0.3%
20251212 1
 
0.3%
20061207 1
 
0.3%

Length

2024-05-11T15:59:42.658032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:42.857558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
99.0%
20161117 1
 
0.3%
20251212 1
 
0.3%
20061207 1
 
0.3%

재개업일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing292
Missing (%)99.7%
Memory size2.4 KiB
Minimum2008-03-14 00:00:00
Maximum2008-03-14 00:00:00
2024-05-11T15:59:43.073848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:59:43.242811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

전화번호
Text

MISSING 

Distinct237
Distinct (%)97.5%
Missing50
Missing (%)17.1%
Memory size2.4 KiB
2024-05-11T15:59:43.828952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.757202
Min length7

Characters and Unicode

Total characters2857
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

Unique231 ?
Unique (%)95.1%

Sample

1st row02 815 3594
2nd row02 523 2935
3rd row02 792 4173
4th row02 34776341
5th row02 851 5098
ValueCountFrequency (%)
02 228
33.4%
822 16
 
2.3%
814 12
 
1.8%
817 12
 
1.8%
821 10
 
1.5%
815 10
 
1.5%
824 10
 
1.5%
813 10
 
1.5%
826 9
 
1.3%
522 8
 
1.2%
Other values (282) 357
52.3%
2024-05-11T15:59:44.648393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
667
23.3%
2 474
16.6%
0 352
12.3%
8 261
 
9.1%
5 226
 
7.9%
1 184
 
6.4%
4 155
 
5.4%
6 148
 
5.2%
3 145
 
5.1%
9 123
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2190
76.7%
Space Separator 667
 
23.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 474
21.6%
0 352
16.1%
8 261
11.9%
5 226
10.3%
1 184
 
8.4%
4 155
 
7.1%
6 148
 
6.8%
3 145
 
6.6%
9 123
 
5.6%
7 122
 
5.6%
Space Separator
ValueCountFrequency (%)
667
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2857
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
667
23.3%
2 474
16.6%
0 352
12.3%
8 261
 
9.1%
5 226
 
7.9%
1 184
 
6.4%
4 155
 
5.4%
6 148
 
5.2%
3 145
 
5.1%
9 123
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
667
23.3%
2 474
16.6%
0 352
12.3%
8 261
 
9.1%
5 226
 
7.9%
1 184
 
6.4%
4 155
 
5.4%
6 148
 
5.2%
3 145
 
5.1%
9 123
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

지번주소
Text

MISSING 

Distinct126
Distinct (%)44.1%
Missing7
Missing (%)2.4%
Memory size2.4 KiB
2024-05-11T15:59:45.012947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length26.926573
Min length9

Characters and Unicode

Total characters7701
Distinct characters100
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

Unique84 ?
Unique (%)29.4%

Sample

1st row서울특별시 동작구 노량진동 **-**번지 *통*반
2nd row서울특별시 동작구 사당동 ***-**번지 *통*반
3rd row서울특별시 동작구 신대방동 ***-*번지 *통*반
4th row서울특별시 동작구 사당동 ***-**
5th row서울특별시 동작구 신대방동 ***-**번지 *통*반
ValueCountFrequency (%)
서울특별시 285
20.2%
동작구 282
20.0%
번지 251
17.8%
통*반 182
12.9%
사당동 104
 
7.4%
상도동 57
 
4.0%
대방동 36
 
2.6%
36
 
2.6%
신대방동 35
 
2.5%
층 34
 
2.4%
Other values (44) 109
 
7.7%
2024-05-11T15:59:45.790395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1798
23.3%
1382
17.9%
동 577
 
7.5%
서 286
 
3.7%
특 285
 
3.7%
별 285
 
3.7%
시 285
 
3.7%
구 285
 
3.7%
울 285
 
3.7%
작 282
 
3.7%
Other values (90) 1951
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4241
55.1%
Other Punctuation 1798
23.3%
Space Separator 1382
 
17.9%
Dash Punctuation 276
 
3.6%
Uppercase Letter 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 577
13.6%
서 286
 
6.7%
특 285
 
6.7%
별 285
 
6.7%
시 285
 
6.7%
구 285
 
6.7%
울 285
 
6.7%
작 282
 
6.6%
지 256
 
6.0%
번 251
 
5.9%
Other values (84) 1164
27.4%
Other Punctuation
ValueCountFrequency (%)
* 1798
100.0%
Space Separator
ValueCountFrequency (%)
1382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4241
55.1%
Common 3458
44.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 577
13.6%
서 286
 
6.7%
특 285
 
6.7%
별 285
 
6.7%
시 285
 
6.7%
구 285
 
6.7%
울 285
 
6.7%
작 282
 
6.6%
지 256
 
6.0%
번 251
 
5.9%
Other values (84) 1164
27.4%
Common
ValueCountFrequency (%)
* 1798
52.0%
1382
40.0%
- 276
 
8.0%
( 1
 
< 0.1%
) 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4241
55.1%
ASCII 3460
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1798
52.0%
1382
39.9%
- 276
 
8.0%
B 2
 
0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
동 577
13.6%
서 286
 
6.7%
특 285
 
6.7%
별 285
 
6.7%
시 285
 
6.7%
구 285
 
6.7%
울 285
 
6.7%
작 282
 
6.6%
지 256
 
6.0%
번 251
 
5.9%
Other values (84) 1164
27.4%

도로명주소
Text

MISSING 

Distinct172
Distinct (%)65.4%
Missing30
Missing (%)10.2%
Memory size2.4 KiB
2024-05-11T15:59:46.145820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length27.897338
Min length22

Characters and Unicode

Total characters7337
Distinct characters128
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

Unique138 ?
Unique (%)52.5%

Sample

1st row서울특별시 동작구 노량진로 *** (노량진동)
2nd row서울특별시 동작구 보라매로 ** (신대방동)
3rd row서울특별시 동작구 사당로**길 *, *층 ***호 (사당동)
4th row서울특별시 동작구 대림로 ** (신대방동)
5th row서울특별시 동작구 사당로**마길 * (사당동)
ValueCountFrequency (%)
265
18.5%
서울특별시 263
18.3%
동작구 262
18.3%
사당동 94
 
6.6%
층 55
 
3.8%
상도동 47
 
3.3%
대방동 34
 
2.4%
신대방동 32
 
2.2%
상도로 27
 
1.9%
호 23
 
1.6%
Other values (109) 332
23.2%
2024-05-11T15:59:46.759836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1329
18.1%
* 1054
14.4%
동 577
 
7.9%
작 293
 
4.0%
서 268
 
3.7%
시 265
 
3.6%
) 264
 
3.6%
( 264
 
3.6%
특 263
 
3.6%
별 263
 
3.6%
Other values (118) 2497
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4284
58.4%
Space Separator 1329
 
18.1%
Other Punctuation 1152
 
15.7%
Close Punctuation 264
 
3.6%
Open Punctuation 264
 
3.6%
Dash Punctuation 41
 
0.6%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 577
13.5%
작 293
 
6.8%
서 268
 
6.3%
시 265
 
6.2%
특 263
 
6.1%
별 263
 
6.1%
구 263
 
6.1%
울 263
 
6.1%
로 245
 
5.7%
사 162
 
3.8%
Other values (111) 1422
33.2%
Other Punctuation
ValueCountFrequency (%)
* 1054
91.5%
, 98
 
8.5%
Space Separator
ValueCountFrequency (%)
1329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4284
58.4%
Common 3050
41.6%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 577
13.5%
작 293
 
6.8%
서 268
 
6.3%
시 265
 
6.2%
특 263
 
6.1%
별 263
 
6.1%
구 263
 
6.1%
울 263
 
6.1%
로 245
 
5.7%
사 162
 
3.8%
Other values (111) 1422
33.2%
Common
ValueCountFrequency (%)
1329
43.6%
* 1054
34.6%
) 264
 
8.7%
( 264
 
8.7%
, 98
 
3.2%
- 41
 
1.3%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4284
58.4%
ASCII 3053
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1329
43.5%
* 1054
34.5%
) 264
 
8.6%
( 264
 
8.6%
, 98
 
3.2%
- 41
 
1.3%
B 3
 
0.1%
Hangul
ValueCountFrequency (%)
동 577
13.5%
작 293
 
6.8%
서 268
 
6.3%
시 265
 
6.2%
특 263
 
6.1%
별 263
 
6.1%
구 263
 
6.1%
울 263
 
6.1%
로 245
 
5.7%
사 162
 
3.8%
Other values (111) 1422
33.2%

도로명우편번호
Text

MISSING 

Distinct73
Distinct (%)72.3%
Missing192
Missing (%)65.5%
Memory size2.4 KiB
2024-05-11T15:59:47.184081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.6039604
Min length5

Characters and Unicode

Total characters566
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

Unique56 ?
Unique (%)55.4%

Sample

1st row07012
2nd row06935
3rd row156811
4th row156839
5th row156804
ValueCountFrequency (%)
156807 5
 
5.0%
156827 4
 
4.0%
156824 4
 
4.0%
07012 3
 
3.0%
06950 3
 
3.0%
07069 3
 
3.0%
156811 3
 
3.0%
07014 2
 
2.0%
156839 2
 
2.0%
07030 2
 
2.0%
Other values (63) 70
69.3%
2024-05-11T15:59:47.993881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 103
18.2%
6 96
17.0%
1 88
15.5%
5 71
12.5%
8 58
10.2%
7 42
7.4%
9 35
 
6.2%
3 25
 
4.4%
2 22
 
3.9%
4 20
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 560
98.9%
Dash Punctuation 6
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 103
18.4%
6 96
17.1%
1 88
15.7%
5 71
12.7%
8 58
10.4%
7 42
7.5%
9 35
 
6.2%
3 25
 
4.5%
2 22
 
3.9%
4 20
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 566
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 103
18.2%
6 96
17.0%
1 88
15.5%
5 71
12.5%
8 58
10.2%
7 42
7.4%
9 35
 
6.2%
3 25
 
4.4%
2 22
 
3.9%
4 20
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 103
18.2%
6 96
17.0%
1 88
15.5%
5 71
12.5%
8 58
10.2%
7 42
7.4%
9 35
 
6.2%
3 25
 
4.4%
2 22
 
3.9%
4 20
 
3.5%

사업장명
Text

Distinct287
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T15:59:48.551721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.3822526
Min length2

Characters and Unicode

Total characters1577
Distinct characters267
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)96.6%

Sample

1st row진양광고
2nd row광고기획
3rd row삼일실업
4th row간판대흥
5th row한길광고기획
ValueCountFrequency (%)
현대광고 4
 
1.3%
주식회사 4
 
1.3%
디자인 3
 
0.9%
광고기획 3
 
0.9%
쏘드시스템 3
 
0.9%
광고 2
 
0.6%
형제기획 2
 
0.6%
초록광고기획 2
 
0.6%
수창 1
 
0.3%
우리간판 1
 
0.3%
Other values (292) 292
92.1%
2024-05-11T15:59:49.308859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 76
 
4.8%
고 72
 
4.6%
기 70
 
4.4%
획 62
 
3.9%
주 53
 
3.4%
인 50
 
3.2%
( 46
 
2.9%
) 46
 
2.9%
드 43
 
2.7%
디 41
 
2.6%
Other values (257) 1018
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1424
90.3%
Open Punctuation 46
 
2.9%
Close Punctuation 46
 
2.9%
Space Separator 24
 
1.5%
Uppercase Letter 22
 
1.4%
Lowercase Letter 7
 
0.4%
Decimal Number 4
 
0.3%
Other Punctuation 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 76
 
5.3%
고 72
 
5.1%
기 70
 
4.9%
획 62
 
4.4%
주 53
 
3.7%
인 50
 
3.5%
드 43
 
3.0%
디 41
 
2.9%
이 34
 
2.4%
자 34
 
2.4%
Other values (232) 889
62.4%
Uppercase Letter
ValueCountFrequency (%)
S 3
13.6%
M 3
13.6%
G 3
13.6%
C 2
9.1%
K 2
9.1%
E 2
9.1%
P 2
9.1%
A 1
 
4.5%
T 1
 
4.5%
N 1
 
4.5%
Other values (2) 2
9.1%
Lowercase Letter
ValueCountFrequency (%)
c 3
42.9%
r 1
 
14.3%
f 1
 
14.3%
v 1
 
14.3%
t 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1424
90.3%
Common 124
 
7.9%
Latin 29
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 76
 
5.3%
고 72
 
5.1%
기 70
 
4.9%
획 62
 
4.4%
주 53
 
3.7%
인 50
 
3.5%
드 43
 
3.0%
디 41
 
2.9%
이 34
 
2.4%
자 34
 
2.4%
Other values (232) 889
62.4%
Latin
ValueCountFrequency (%)
S 3
10.3%
M 3
10.3%
G 3
10.3%
c 3
10.3%
C 2
 
6.9%
K 2
 
6.9%
E 2
 
6.9%
P 2
 
6.9%
A 1
 
3.4%
T 1
 
3.4%
Other values (7) 7
24.1%
Common
ValueCountFrequency (%)
( 46
37.1%
) 46
37.1%
24
19.4%
1 2
 
1.6%
2 2
 
1.6%
. 2
 
1.6%
- 1
 
0.8%
& 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1424
90.3%
ASCII 153
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 76
 
5.3%
고 72
 
5.1%
기 70
 
4.9%
획 62
 
4.4%
주 53
 
3.7%
인 50
 
3.5%
드 43
 
3.0%
디 41
 
2.9%
이 34
 
2.4%
자 34
 
2.4%
Other values (232) 889
62.4%
ASCII
ValueCountFrequency (%)
( 46
30.1%
) 46
30.1%
24
15.7%
S 3
 
2.0%
M 3
 
2.0%
G 3
 
2.0%
c 3
 
2.0%
1 2
 
1.3%
2 2
 
1.3%
C 2
 
1.3%
Other values (15) 19
12.4%

최종수정일자
Date

Distinct137
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2000-08-11 00:00:00
Maximum2024-03-13 13:27:40
2024-05-11T15:59:49.549650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:59:49.806380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
I
253 
U
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 253
86.3%
U 40
 
13.7%

Length

2024-05-11T15:59:50.128315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:59:50.307665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 253
86.3%
u 40
 
13.7%

데이터갱신일자
Date

Distinct46
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 23:06:00
2024-05-11T15:59:50.497265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:59:50.739915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct245
Distinct (%)90.7%
Missing23
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean195518.95
Minimum186615.06
Maximum198323.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:59:50.986357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum186615.06
5-th percentile191923.55
Q1193935.67
median195364.83
Q3197676.38
95-th percentile198226.55
Maximum198323.32
Range11708.255
Interquartile range (IQR)3740.7093

Descriptive statistics

Standard deviation2143.9408
Coefficient of variation (CV)0.010965386
Kurtosis-0.38504944
Mean195518.95
Median Absolute Deviation (MAD)1869.5569
Skewness-0.38221826
Sum52790118
Variance4596482.1
MonotonicityNot monotonic
2024-05-11T15:59:51.597107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193564.452792314 4
 
1.4%
194088.898893195 4
 
1.4%
197186.050752132 2
 
0.7%
197747.09857026 2
 
0.7%
198217.275056369 2
 
0.7%
196609.160226225 2
 
0.7%
195935.458394901 2
 
0.7%
193972.121419392 2
 
0.7%
191958.16953273 2
 
0.7%
191748.253117587 2
 
0.7%
Other values (235) 246
84.0%
(Missing) 23
 
7.8%
ValueCountFrequency (%)
186615.060983644 1
0.3%
191206.667833783 1
0.3%
191218.603640354 1
0.3%
191704.477106486 1
0.3%
191748.253117587 2
0.7%
191787.677056618 1
0.3%
191818.173735701 1
0.3%
191841.985106362 1
0.3%
191844.373149353 1
0.3%
191856.280274493 1
0.3%
ValueCountFrequency (%)
198323.315884585 1
0.3%
198310.468541102 1
0.3%
198304.080681975 1
0.3%
198277.424839965 1
0.3%
198277.137574688 1
0.3%
198261.860491377 1
0.3%
198260.606422072 2
0.7%
198242.263168525 2
0.7%
198240.435377395 1
0.3%
198235.364889058 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct245
Distinct (%)90.7%
Missing23
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean443652.33
Minimum441541.55
Maximum450133.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:59:51.814635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441541.55
5-th percentile441679.44
Q1442435.48
median443927.68
Q3444665.53
95-th percentile445609.89
Maximum450133.94
Range8592.3815
Interquartile range (IQR)2230.0551

Descriptive statistics

Standard deviation1353.5478
Coefficient of variation (CV)0.0030509201
Kurtosis0.33262731
Mean443652.33
Median Absolute Deviation (MAD)1257.2981
Skewness0.36991465
Sum1.1978613 × 108
Variance1832091.7
MonotonicityNot monotonic
2024-05-11T15:59:52.057429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445609.889238394 4
 
1.4%
444804.136599742 4
 
1.4%
442605.071529068 2
 
0.7%
441609.191214767 2
 
0.7%
442185.69520758 2
 
0.7%
445244.753264746 2
 
0.7%
445583.752273666 2
 
0.7%
444283.903816913 2
 
0.7%
442754.754162376 2
 
0.7%
442967.417508527 2
 
0.7%
Other values (235) 246
84.0%
(Missing) 23
 
7.8%
ValueCountFrequency (%)
441541.554552654 2
0.7%
441543.537610587 1
0.3%
441595.660481209 1
0.3%
441607.91944008 1
0.3%
441609.191214767 2
0.7%
441621.408468674 1
0.3%
441633.951360171 1
0.3%
441660.055575466 1
0.3%
441663.546703748 2
0.7%
441671.438697802 1
0.3%
ValueCountFrequency (%)
450133.936019244 1
0.3%
445868.076456773 1
0.3%
445737.024248612 1
0.3%
445639.392259045 1
0.3%
445637.957918936 2
0.7%
445633.90103038 1
0.3%
445631.450029526 1
0.3%
445628.940499705 1
0.3%
445610.919894144 1
0.3%
445610.160717686 1
0.3%

영업내용
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
옥외광고물 제작
202 
<NA>
 
19
간판제작
 
5
옥외광고업
 
5
옥외광고물 제작
 
4
Other values (46)
58 

Length

Max length29
Median length8
Mean length8.1501706
Min length2

Unique

Unique38 ?
Unique (%)13.0%

Sample

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

Common Values

ValueCountFrequency (%)
옥외광고물 제작 202
68.9%
<NA> 19
 
6.5%
간판제작 5
 
1.7%
옥외광고업 5
 
1.7%
옥외광고물 제작 4
 
1.4%
광고물 제작 4
 
1.4%
옥외광고물 제작 및 대행 3
 
1.0%
광고물제작,대행 3
 
1.0%
광고물제작 2
 
0.7%
현수막 및 간판제작 2
 
0.7%
Other values (41) 44
 
15.0%

Length

2024-05-11T15:59:52.314383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제작 221
38.0%
옥외광고물 213
36.7%
na 19
 
3.3%
및 17
 
2.9%
광고물 14
 
2.4%
대행 9
 
1.5%
광고물제작 8
 
1.4%
간판제작 8
 
1.4%
간판 8
 
1.4%
광고대행 6
 
1.0%
Other values (39) 58
 
10.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
03190000199231900750850000619920224<NA>3폐업40폐업20041220<NA><NA><NA>02 815 3594<NA><NA>서울특별시 동작구 노량진동 **-**번지 *통*반서울특별시 동작구 노량진로 *** (노량진동)<NA>진양광고2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>194776.600151445737.024249옥외광고물 제작
13190000199231900750850000719920224<NA>3폐업40폐업19930714<NA><NA><NA>02 523 2935<NA><NA>서울특별시 동작구 사당동 ***-**번지 *통*반<NA><NA>광고기획2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>197787.735507442264.121236옥외광고물 제작
23190000199231900750850000819920313<NA>3폐업40폐업19930716<NA><NA><NA>02 792 4173<NA><NA>서울특별시 동작구 신대방동 ***-*번지 *통*반서울특별시 동작구 보라매로 ** (신대방동)<NA>삼일실업2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>193582.973797443921.190735옥외광고물 제작
3319000019923190075085000091992-03-23<NA>3폐업40폐업2023-03-13<NA><NA><NA>02 34776341<NA><NA>서울특별시 동작구 사당동 ***-**서울특별시 동작구 사당로**길 *, *층 ***호 (사당동)07012간판대흥2023-03-13 17:35:15U2022-12-02 23:05:00.0<NA>197692.364579442214.493054<NA>
43190000199231900750850001019920327<NA>3폐업40폐업19941130<NA><NA><NA>02 851 5098<NA><NA>서울특별시 동작구 신대방동 ***-**번지 *통*반서울특별시 동작구 대림로 ** (신대방동)<NA>한길광고기획2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>191932.053919442799.937388옥외광고물 제작
53190000199231900750850001119920515<NA>3폐업40폐업19950329<NA><NA><NA>02 522 8900<NA><NA>서울특별시 동작구 사당동 ***-*번지 *통*반서울특별시 동작구 사당로**마길 * (사당동)<NA>삼진광고2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>197453.688731442161.758263옥외광고물 제작
63190000199231900750850001219920530<NA>3폐업40폐업19951220<NA><NA><NA>02 536 5039<NA><NA>서울특별시 동작구 사당동 ***-*번지 *통*반서울특별시 동작구 사당로 *** (사당동)<NA>마창열2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>197208.353448442631.503033옥외광고물 제작
73190000199231900750850001319920530<NA>3폐업40폐업20030322<NA><NA><NA>02 824 6610<NA><NA>서울특별시 동작구 사당동 ***-**번지 *통*반서울특별시 동작구 사당로*길 ** (사당동)<NA>해성기획2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>197085.051575442313.214019옥외광고물 제작
83190000199231900750850001419920817<NA>3폐업40폐업19951220<NA><NA><NA>02 813 4616<NA><NA>서울특별시 동작구 상도동 ***-*번지 *통*반<NA><NA>탑토탈기획2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA><NA><NA>옥외광고물 제작
93190000199231900750850001519920817<NA>3폐업40폐업19970327<NA><NA><NA>02 814 3512<NA><NA>서울특별시 동작구 상도동 ***-*번지 *통*반서울특별시 동작구 상도로**길 **-* (상도동)<NA>유창광고2008-03-04 15:06:22I2018-08-31 23:59:59.0<NA>194292.584824444638.296081옥외광고물 제작
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
2833190000202031902100850000220200204<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 대방동 ***-**번지 미리내빌라 ***호서울특별시 동작구 대방동길 **, ***호 (대방동, 미리내빌라)06954마루2020-02-04 20:41:53I2020-02-06 00:23:24.0<NA>193549.758554444415.867649간판조립시공
2843190000202031902100850000320200409<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 신대방*길 **, 쇠누피빌딩 *층 (신대방동)07069상상싸인2020-04-10 10:07:31I2020-04-12 00:23:22.0<NA>191748.253118442967.417509간판 제작 설치, 인테리어
2853190000202031902100850000420200508<NA>3폐업40폐업20210426<NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 *** 상도현대아파트 ***동 ****호서울특별시 동작구 사당로*길 *-**, ***동 ****층 (상도동, 상도현대아파트)07027처리기획2021-04-26 08:27:57U2021-04-28 02:40:00.0<NA>196340.877681443534.584336광고대행업
2863190000202031902100850000520201207<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 사당동 ****-**서울특별시 동작구 사당로**길 ** (사당동)07014하람디자인(ESC)2020-12-08 10:14:54I2020-12-10 00:23:07.0<NA>198226.551796442140.633802인쇄, 옥외광고물,상품중개업, 무역, 기획, 광고대행
2873190000202131902100850000120210412<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 사당동 ***-**서울특별시 동작구 사당로*차길 ** (사당동)07030익스디자인2021-04-12 16:22:41I2021-04-14 00:22:57.0<NA>196927.162547442779.131245옥외광고물 제작 대행
2883190000202131902100850000220210707<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도로**길 **, 태원 ***호 (상도동)06949주식회사 밸류디엔씨2021-07-07 13:27:26I2021-07-09 00:22:53.0<NA>194267.456436444664.132384광고물 및 간판 제조업
2893190000202131902100850000320081215<NA>1영업/정상20정상<NA><NA><NA><NA>025371134<NA><NA>서울특별시 동작구 사당동 ***-**서울특별시 동작구 사당로*아길 *, *층 (사당동)07029이글디자인2021-10-22 14:13:57U2021-10-24 02:40:00.0<NA>196791.841841443096.852562간판, 천막, 앵글, 철구조물
290319000020223190267085000012023-07-03<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 ***-** 대왕주택서울특별시 동작구 양녕로**길 **, 대왕주택 *층 (상도동)07037형제기획2023-07-04 09:19:36U2022-12-07 00:06:00.0<NA>194973.725455443970.159765<NA>
291319000020233190267085000012023-05-02<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 *** 힐스테이트 상도 센트럴파크서울특별시 동작구 상도로 ***-*, 상가*동 ***호 (상도동, 힐스테이트 상도 센트럴파크)07039윤일기획(주)2023-05-02 15:31:10I2022-12-05 00:04:00.0<NA>195585.914046443690.595413<NA>
292319000020243190267085000012014-08-18<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 대방동 **-**서울특별시 동작구 등용로 **-* (대방동)06933행복나눔애드2024-01-04 14:52:54I2023-12-01 00:06:00.0<NA>193953.101694445155.322907<NA>