Overview

Dataset statistics

Number of variables26
Number of observations753
Missing cells5634
Missing cells (%)28.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory161.2 KiB
Average record size in memory219.2 B

Variable types

Categorical7
Numeric3
DateTime5
Unsupported4
Text7

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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-17840/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (58.5%)Imbalance
영업상태명 is highly imbalanced (58.5%)Imbalance
상세영업상태코드 is highly imbalanced (58.5%)Imbalance
상세영업상태명 is highly imbalanced (58.5%)Imbalance
재개업일자 is highly imbalanced (98.5%)Imbalance
인허가취소일자 has 753 (100.0%) missing valuesMissing
폐업일자 has 165 (21.9%) missing valuesMissing
휴업시작일자 has 740 (98.3%) missing valuesMissing
휴업종료일자 has 740 (98.3%) missing valuesMissing
전화번호 has 139 (18.5%) missing valuesMissing
소재지면적 has 753 (100.0%) missing valuesMissing
소재지우편번호 has 753 (100.0%) missing valuesMissing
지번주소 has 12 (1.6%) missing valuesMissing
도로명주소 has 96 (12.7%) missing valuesMissing
도로명우편번호 has 511 (67.9%) missing valuesMissing
업태구분명 has 753 (100.0%) missing valuesMissing
좌표정보(X) has 76 (10.1%) missing valuesMissing
좌표정보(Y) has 76 (10.1%) missing valuesMissing
영업내용 has 67 (8.9%) 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 10:28:29.464991
Analysis finished2024-04-06 10:28:31.019304
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3130000
753 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 753
100.0%

Length

2024-04-06T19:28:31.144408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:31.332980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 753
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct753
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0027088 × 1018
Minimum1.900313 × 1018
Maximum2.024313 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-06T19:28:31.515923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.900313 × 1018
5-th percentile1.992913 × 1018
Q11.999313 × 1018
median2.004313 × 1018
Q32.011313 × 1018
95-th percentile2.020713 × 1018
Maximum2.024313 × 1018
Range1.2400001 × 1017
Interquartile range (IQR)1.2000001 × 1016

Descriptive statistics

Standard deviation2.0124086 × 1016
Coefficient of variation (CV)0.010048434
Kurtosis18.650515
Mean2.0027088 × 1018
Median Absolute Deviation (MAD)5.0000003 × 1015
Skewness-4.1065802
Sum-4.593314 × 1018
Variance4.0497885 × 1032
MonotonicityStrictly increasing
2024-04-06T19:28:31.776665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1900313013408500020 1
 
0.1%
2008313013708500685 1
 
0.1%
2008313013708500011 1
 
0.1%
2008313013708500013 1
 
0.1%
2008313013708500014 1
 
0.1%
2008313013708500015 1
 
0.1%
2008313013708500016 1
 
0.1%
2008313013708500017 1
 
0.1%
2008313013708500018 1
 
0.1%
2008313013708500019 1
 
0.1%
Other values (743) 743
98.7%
ValueCountFrequency (%)
1900313013408500020 1
0.1%
1900313013408500027 1
0.1%
1900313013408500030 1
0.1%
1900313013408500032 1
0.1%
1900313013408500037 1
0.1%
1900313013408500047 1
0.1%
1900313013408500053 1
0.1%
1900313013408500054 1
0.1%
1900313013408500057 1
0.1%
1900313013408500066 1
0.1%
ValueCountFrequency (%)
2024313026808500004 1
0.1%
2024313026808500003 1
0.1%
2024313026808500002 1
0.1%
2024313026808500001 1
0.1%
2023313026808500008 1
0.1%
2023313026808500007 1
0.1%
2023313026808500006 1
0.1%
2023313026808500005 1
0.1%
2023313026808500004 1
0.1%
2023313026808500003 1
0.1%

인허가일자
Date

Distinct600
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum1900-01-01 00:00:00
Maximum2024-04-01 00:00:00
2024-04-06T19:28:31.985046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:28:32.194131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing753
Missing (%)100.0%
Memory size6.7 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3
595 
1
146 
2
 
11
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row3
2nd row1
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 595
79.0%
1 146
 
19.4%
2 11
 
1.5%
4 1
 
0.1%

Length

2024-04-06T19:28:32.440962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:32.638462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 595
79.0%
1 146
 
19.4%
2 11
 
1.5%
4 1
 
0.1%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
폐업
595 
영업/정상
146 
휴업
 
11
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length2.5976096
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 595
79.0%
영업/정상 146
 
19.4%
휴업 11
 
1.5%
취소/말소/만료/정지/중지 1
 
0.1%

Length

2024-04-06T19:28:32.901438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:33.093982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 595
79.0%
영업/정상 146
 
19.4%
휴업 11
 
1.5%
취소/말소/만료/정지/중지 1
 
0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
40
595 
20
146 
30
 
11
70
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row40
2nd row20
3rd row30
4th row40
5th row20

Common Values

ValueCountFrequency (%)
40 595
79.0%
20 146
 
19.4%
30 11
 
1.5%
70 1
 
0.1%

Length

2024-04-06T19:28:33.291169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:33.463799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 595
79.0%
20 146
 
19.4%
30 11
 
1.5%
70 1
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
폐업
595 
정상
146 
휴업
 
11
취소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 595
79.0%
정상 146
 
19.4%
휴업 11
 
1.5%
취소 1
 
0.1%

Length

2024-04-06T19:28:33.647167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:33.833268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 595
79.0%
정상 146
 
19.4%
휴업 11
 
1.5%
취소 1
 
0.1%

폐업일자
Date

MISSING 

Distinct395
Distinct (%)67.2%
Missing165
Missing (%)21.9%
Memory size6.0 KiB
Minimum1995-09-30 00:00:00
Maximum2024-02-22 00:00:00
2024-04-06T19:28:34.070035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:28:34.284446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct12
Distinct (%)92.3%
Missing740
Missing (%)98.3%
Memory size6.0 KiB
Minimum1999-10-01 00:00:00
Maximum2022-05-31 00:00:00
2024-04-06T19:28:34.422187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:28:34.580560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

휴업종료일자
Text

MISSING 

Distinct12
Distinct (%)92.3%
Missing740
Missing (%)98.3%
Memory size6.0 KiB
2024-04-06T19:28:34.811976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1538462
Min length8

Characters and Unicode

Total characters106
Distinct characters9
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

Unique11 ?
Unique (%)84.6%

Sample

1st row20030630
2nd row20081231
3rd row20081231
4th row20021231
5th row20000630
ValueCountFrequency (%)
20081231 2
15.4%
20030630 1
7.7%
20021231 1
7.7%
20000630 1
7.7%
20020515 1
7.7%
20100630 1
7.7%
20090630 1
7.7%
20211231 1
7.7%
20111231 1
7.7%
29991231 1
7.7%
Other values (2) 2
15.4%
2024-04-06T19:28:35.357099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32
30.2%
2 25
23.6%
1 19
17.9%
3 14
13.2%
6 4
 
3.8%
9 4
 
3.8%
8 3
 
2.8%
5 3
 
2.8%
- 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
98.1%
Dash Punctuation 2
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32
30.8%
2 25
24.0%
1 19
18.3%
3 14
13.5%
6 4
 
3.8%
9 4
 
3.8%
8 3
 
2.9%
5 3
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32
30.2%
2 25
23.6%
1 19
17.9%
3 14
13.2%
6 4
 
3.8%
9 4
 
3.8%
8 3
 
2.8%
5 3
 
2.8%
- 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32
30.2%
2 25
23.6%
1 19
17.9%
3 14
13.2%
6 4
 
3.8%
9 4
 
3.8%
8 3
 
2.8%
5 3
 
2.8%
- 2
 
1.9%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
752 
20140826
 
1

Length

Max length8
Median length4
Mean length4.0053121
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> 752
99.9%
20140826 1
 
0.1%

Length

2024-04-06T19:28:35.614200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:35.822598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 752
99.9%
20140826 1
 
0.1%

전화번호
Text

MISSING 

Distinct553
Distinct (%)90.1%
Missing139
Missing (%)18.5%
Memory size6.0 KiB
2024-04-06T19:28:36.242216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.013029
Min length2

Characters and Unicode

Total characters6148
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

Unique532 ?
Unique (%)86.6%

Sample

1st row3344723
2nd row02-335-5433
3rd row02-332-5411
4th row02-338-4567
5th row02-000-0000
ValueCountFrequency (%)
02 60
 
8.4%
02-000-0000 37
 
5.2%
324 3
 
0.4%
704 3
 
0.4%
02-325-7882 2
 
0.3%
322 2
 
0.3%
338 2
 
0.3%
751 2
 
0.3%
333 2
 
0.3%
02-3143-1210 2
 
0.3%
Other values (581) 601
83.9%
2024-04-06T19:28:36.958536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1129
18.4%
2 953
15.5%
3 862
14.0%
- 679
11.0%
1 501
8.1%
7 472
7.7%
4 343
 
5.6%
6 314
 
5.1%
5 293
 
4.8%
8 242
 
3.9%
Other values (2) 360
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5334
86.8%
Dash Punctuation 679
 
11.0%
Space Separator 135
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1129
21.2%
2 953
17.9%
3 862
16.2%
1 501
9.4%
7 472
8.8%
4 343
 
6.4%
6 314
 
5.9%
5 293
 
5.5%
8 242
 
4.5%
9 225
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 679
100.0%
Space Separator
ValueCountFrequency (%)
135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1129
18.4%
2 953
15.5%
3 862
14.0%
- 679
11.0%
1 501
8.1%
7 472
7.7%
4 343
 
5.6%
6 314
 
5.1%
5 293
 
4.8%
8 242
 
3.9%
Other values (2) 360
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1129
18.4%
2 953
15.5%
3 862
14.0%
- 679
11.0%
1 501
8.1%
7 472
7.7%
4 343
 
5.6%
6 314
 
5.1%
5 293
 
4.8%
8 242
 
3.9%
Other values (2) 360
 
5.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing753
Missing (%)100.0%
Memory size6.7 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing753
Missing (%)100.0%
Memory size6.7 KiB

지번주소
Text

MISSING 

Distinct471
Distinct (%)63.6%
Missing12
Missing (%)1.6%
Memory size6.0 KiB
2024-04-06T19:28:37.352741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length45
Mean length29.021592
Min length17

Characters and Unicode

Total characters21505
Distinct characters237
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

Unique380 ?
Unique (%)51.3%

Sample

1st row서울특별시 마포구 아현동 ***-** *통*반 .
2nd row서울특별시 마포구 망원동 ***-*번지
3rd row서울특별시 마포구 ***-*번지 *통*반 .
4th row서울특별시 마포구 서교동 ***-**번지 *통*반 .
5th row서울특별시 마포구 연남동 ***-**
ValueCountFrequency (%)
서울특별시 741
17.9%
마포구 736
17.7%
번지 620
14.9%
통*반 417
10.0%
397
9.6%
서교동 163
 
3.9%
호 116
 
2.8%
층 113
 
2.7%
성산동 62
 
1.5%
동교동 59
 
1.4%
Other values (260) 726
17.5%
2024-04-06T19:28:38.334655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 4721
22.0%
4069
18.9%
서 917
 
4.3%
동 806
 
3.7%
마 770
 
3.6%
포 766
 
3.6%
구 758
 
3.5%
시 744
 
3.5%
울 742
 
3.5%
특 741
 
3.4%
Other values (227) 6471
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11640
54.1%
Other Punctuation 4999
23.2%
Space Separator 4069
 
18.9%
Dash Punctuation 692
 
3.2%
Uppercase Letter 78
 
0.4%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Decimal Number 8
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 917
 
7.9%
동 806
 
6.9%
마 770
 
6.6%
포 766
 
6.6%
구 758
 
6.5%
시 744
 
6.4%
울 742
 
6.4%
특 741
 
6.4%
별 741
 
6.4%
지 650
 
5.6%
Other values (198) 4005
34.4%
Uppercase Letter
ValueCountFrequency (%)
B 14
17.9%
D 10
12.8%
C 10
12.8%
M 9
11.5%
K 5
 
6.4%
S 5
 
6.4%
A 4
 
5.1%
L 4
 
5.1%
P 4
 
5.1%
G 4
 
5.1%
Other values (5) 9
11.5%
Decimal Number
ValueCountFrequency (%)
6 2
25.0%
9 2
25.0%
1 2
25.0%
3 1
12.5%
0 1
12.5%
Other Punctuation
ValueCountFrequency (%)
* 4721
94.4%
. 273
 
5.5%
, 4
 
0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4069
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 692
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11640
54.1%
Common 9787
45.5%
Latin 78
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 917
 
7.9%
동 806
 
6.9%
마 770
 
6.6%
포 766
 
6.6%
구 758
 
6.5%
시 744
 
6.4%
울 742
 
6.4%
특 741
 
6.4%
별 741
 
6.4%
지 650
 
5.6%
Other values (198) 4005
34.4%
Latin
ValueCountFrequency (%)
B 14
17.9%
D 10
12.8%
C 10
12.8%
M 9
11.5%
K 5
 
6.4%
S 5
 
6.4%
A 4
 
5.1%
L 4
 
5.1%
P 4
 
5.1%
G 4
 
5.1%
Other values (5) 9
11.5%
Common
ValueCountFrequency (%)
* 4721
48.2%
4069
41.6%
- 692
 
7.1%
. 273
 
2.8%
( 9
 
0.1%
) 9
 
0.1%
, 4
 
< 0.1%
6 2
 
< 0.1%
9 2
 
< 0.1%
1 2
 
< 0.1%
Other values (4) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11640
54.1%
ASCII 9865
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 4721
47.9%
4069
41.2%
- 692
 
7.0%
. 273
 
2.8%
B 14
 
0.1%
D 10
 
0.1%
C 10
 
0.1%
( 9
 
0.1%
) 9
 
0.1%
M 9
 
0.1%
Other values (19) 49
 
0.5%
Hangul
ValueCountFrequency (%)
서 917
 
7.9%
동 806
 
6.9%
마 770
 
6.6%
포 766
 
6.6%
구 758
 
6.5%
시 744
 
6.4%
울 742
 
6.4%
특 741
 
6.4%
별 741
 
6.4%
지 650
 
5.6%
Other values (198) 4005
34.4%

도로명주소
Text

MISSING 

Distinct571
Distinct (%)86.9%
Missing96
Missing (%)12.7%
Memory size6.0 KiB
2024-04-06T19:28:38.821340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length44
Mean length30.672755
Min length21

Characters and Unicode

Total characters20152
Distinct characters261
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

Unique514 ?
Unique (%)78.2%

Sample

1st row서울특별시 마포구 마포대로 *** (아현동,.)
2nd row서울특별시 마포구 동교로 **, *층 (망원동)
3rd row서울특별시 마포구 잔다리로 ** (서교동,.)
4th row서울특별시 마포구 동교로**길 **, 지하*층 (연남동)
5th row서울특별시 마포구 홍익로*길 ** (서교동,.)
ValueCountFrequency (%)
660
17.6%
서울특별시 657
17.5%
마포구 654
17.5%
호 149
 
4.0%
층 134
 
3.6%
서교동 110
 
2.9%
성산동 51
 
1.4%
마포대로 51
 
1.4%
동교로 47
 
1.3%
동교동 44
 
1.2%
Other values (400) 1190
31.8%
2024-04-06T19:28:39.557348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3370
16.7%
* 2844
 
14.1%
서 840
 
4.2%
동 826
 
4.1%
포 762
 
3.8%
마 759
 
3.8%
구 675
 
3.3%
울 668
 
3.3%
) 667
 
3.3%
( 667
 
3.3%
Other values (251) 8074
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11570
57.4%
Other Punctuation 3703
 
18.4%
Space Separator 3370
 
16.7%
Close Punctuation 667
 
3.3%
Open Punctuation 667
 
3.3%
Dash Punctuation 92
 
0.5%
Uppercase Letter 73
 
0.4%
Decimal Number 9
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 840
 
7.3%
동 826
 
7.1%
포 762
 
6.6%
마 759
 
6.6%
구 675
 
5.8%
울 668
 
5.8%
시 661
 
5.7%
별 659
 
5.7%
특 657
 
5.7%
로 642
 
5.5%
Other values (223) 4421
38.2%
Uppercase Letter
ValueCountFrequency (%)
B 12
16.4%
D 9
12.3%
M 8
11.0%
C 7
9.6%
A 6
8.2%
L 6
8.2%
G 5
6.8%
K 4
 
5.5%
P 4
 
5.5%
I 3
 
4.1%
Other values (5) 9
12.3%
Decimal Number
ValueCountFrequency (%)
0 3
33.3%
1 3
33.3%
7 1
 
11.1%
9 1
 
11.1%
2 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 2844
76.8%
, 659
 
17.8%
. 200
 
5.4%
Space Separator
ValueCountFrequency (%)
3370
100.0%
Close Punctuation
ValueCountFrequency (%)
) 667
100.0%
Open Punctuation
ValueCountFrequency (%)
( 667
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11570
57.4%
Common 8509
42.2%
Latin 73
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 840
 
7.3%
동 826
 
7.1%
포 762
 
6.6%
마 759
 
6.6%
구 675
 
5.8%
울 668
 
5.8%
시 661
 
5.7%
별 659
 
5.7%
특 657
 
5.7%
로 642
 
5.5%
Other values (223) 4421
38.2%
Latin
ValueCountFrequency (%)
B 12
16.4%
D 9
12.3%
M 8
11.0%
C 7
9.6%
A 6
8.2%
L 6
8.2%
G 5
6.8%
K 4
 
5.5%
P 4
 
5.5%
I 3
 
4.1%
Other values (5) 9
12.3%
Common
ValueCountFrequency (%)
3370
39.6%
* 2844
33.4%
) 667
 
7.8%
( 667
 
7.8%
, 659
 
7.7%
. 200
 
2.4%
- 92
 
1.1%
0 3
 
< 0.1%
1 3
 
< 0.1%
7 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11570
57.4%
ASCII 8582
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3370
39.3%
* 2844
33.1%
) 667
 
7.8%
( 667
 
7.8%
, 659
 
7.7%
. 200
 
2.3%
- 92
 
1.1%
B 12
 
0.1%
D 9
 
0.1%
M 8
 
0.1%
Other values (18) 54
 
0.6%
Hangul
ValueCountFrequency (%)
서 840
 
7.3%
동 826
 
7.1%
포 762
 
6.6%
마 759
 
6.6%
구 675
 
5.8%
울 668
 
5.8%
시 661
 
5.7%
별 659
 
5.7%
특 657
 
5.7%
로 642
 
5.5%
Other values (223) 4421
38.2%

도로명우편번호
Text

MISSING 

Distinct151
Distinct (%)62.4%
Missing511
Missing (%)67.9%
Memory size6.0 KiB
2024-04-06T19:28:40.085087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3347107
Min length5

Characters and Unicode

Total characters1291
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

Unique93 ?
Unique (%)38.4%

Sample

1st row04018
2nd row03984
3rd row121803
4th row04074
5th row121868
ValueCountFrequency (%)
03909 8
 
3.3%
04157 5
 
2.1%
04030 4
 
1.7%
121840 4
 
1.7%
121849 4
 
1.7%
121251 3
 
1.2%
121894 3
 
1.2%
121842 3
 
1.2%
04046 3
 
1.2%
03994 3
 
1.2%
Other values (141) 202
83.5%
2024-04-06T19:28:40.876324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 287
22.2%
1 231
17.9%
4 158
12.2%
2 136
10.5%
9 131
10.1%
3 111
 
8.6%
8 106
 
8.2%
7 45
 
3.5%
5 43
 
3.3%
6 41
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1289
99.8%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 287
22.3%
1 231
17.9%
4 158
12.3%
2 136
10.6%
9 131
10.2%
3 111
 
8.6%
8 106
 
8.2%
7 45
 
3.5%
5 43
 
3.3%
6 41
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 287
22.2%
1 231
17.9%
4 158
12.2%
2 136
10.5%
9 131
10.1%
3 111
 
8.6%
8 106
 
8.2%
7 45
 
3.5%
5 43
 
3.3%
6 41
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 287
22.2%
1 231
17.9%
4 158
12.2%
2 136
10.5%
9 131
10.1%
3 111
 
8.6%
8 106
 
8.2%
7 45
 
3.5%
5 43
 
3.3%
6 41
 
3.2%

사업장명
Text

Distinct709
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-04-06T19:28:41.330466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.6918991
Min length2

Characters and Unicode

Total characters5039
Distinct characters393
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique670 ?
Unique (%)89.0%

Sample

1st row창미사
2nd row현대공사
3rd row(주)대보애드
4th row오상기획
5th row대성네온공사
ValueCountFrequency (%)
주식회사 50
 
6.0%
업체명무 6
 
0.7%
주)시스테크비즈 3
 
0.4%
디자인 3
 
0.4%
트리앤 3
 
0.4%
스튜디오 3
 
0.4%
건인애드 2
 
0.2%
맥경광고산업(주 2
 
0.2%
주)정양기획 2
 
0.2%
주)덕산애드 2
 
0.2%
Other values (728) 760
90.9%
2024-04-06T19:28:42.048899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 377
 
7.5%
( 320
 
6.4%
) 320
 
6.4%
인 153
 
3.0%
이 150
 
3.0%
디 149
 
3.0%
스 139
 
2.8%
드 124
 
2.5%
기 118
 
2.3%
획 107
 
2.1%
Other values (383) 3082
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4257
84.5%
Open Punctuation 320
 
6.4%
Close Punctuation 320
 
6.4%
Space Separator 86
 
1.7%
Uppercase Letter 27
 
0.5%
Lowercase Letter 11
 
0.2%
Decimal Number 9
 
0.2%
Dash Punctuation 5
 
0.1%
Other Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 377
 
8.9%
인 153
 
3.6%
이 150
 
3.5%
디 149
 
3.5%
스 139
 
3.3%
드 124
 
2.9%
기 118
 
2.8%
획 107
 
2.5%
광 104
 
2.4%
애 97
 
2.3%
Other values (348) 2739
64.3%
Uppercase Letter
ValueCountFrequency (%)
S 4
14.8%
C 3
11.1%
E 2
 
7.4%
P 2
 
7.4%
D 2
 
7.4%
T 2
 
7.4%
L 2
 
7.4%
I 2
 
7.4%
N 2
 
7.4%
G 1
 
3.7%
Other values (5) 5
18.5%
Lowercase Letter
ValueCountFrequency (%)
i 2
18.2%
g 2
18.2%
n 2
18.2%
a 1
9.1%
b 1
9.1%
c 1
9.1%
o 1
9.1%
m 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
1 3
33.3%
4 1
 
11.1%
0 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
* 1
33.3%
, 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 320
100.0%
Close Punctuation
ValueCountFrequency (%)
) 320
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4257
84.5%
Common 744
 
14.8%
Latin 38
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 377
 
8.9%
인 153
 
3.6%
이 150
 
3.5%
디 149
 
3.5%
스 139
 
3.3%
드 124
 
2.9%
기 118
 
2.8%
획 107
 
2.5%
광 104
 
2.4%
애 97
 
2.3%
Other values (348) 2739
64.3%
Latin
ValueCountFrequency (%)
S 4
 
10.5%
C 3
 
7.9%
i 2
 
5.3%
E 2
 
5.3%
P 2
 
5.3%
g 2
 
5.3%
n 2
 
5.3%
D 2
 
5.3%
T 2
 
5.3%
L 2
 
5.3%
Other values (13) 15
39.5%
Common
ValueCountFrequency (%)
( 320
43.0%
) 320
43.0%
86
 
11.6%
- 5
 
0.7%
2 4
 
0.5%
1 3
 
0.4%
4 1
 
0.1%
+ 1
 
0.1%
0 1
 
0.1%
. 1
 
0.1%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4257
84.5%
ASCII 782
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 377
 
8.9%
인 153
 
3.6%
이 150
 
3.5%
디 149
 
3.5%
스 139
 
3.3%
드 124
 
2.9%
기 118
 
2.8%
획 107
 
2.5%
광 104
 
2.4%
애 97
 
2.3%
Other values (348) 2739
64.3%
ASCII
ValueCountFrequency (%)
( 320
40.9%
) 320
40.9%
86
 
11.0%
- 5
 
0.6%
S 4
 
0.5%
2 4
 
0.5%
1 3
 
0.4%
C 3
 
0.4%
i 2
 
0.3%
E 2
 
0.3%
Other values (25) 33
 
4.2%

최종수정일자
Date

Distinct511
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2007-12-03 16:27:30
Maximum2024-04-01 13:43:57
2024-04-06T19:28:42.293597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:28:42.562832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
I
617 
U
136 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 617
81.9%
U 136
 
18.1%

Length

2024-04-06T19:28:42.759196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:28:42.923316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 617
81.9%
u 136
 
18.1%

데이터갱신일자
Date

Distinct143
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-04-06T19:28:43.091775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:28:43.325594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing753
Missing (%)100.0%
Memory size6.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct523
Distinct (%)77.3%
Missing76
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean193286.5
Minimum187952.56
Maximum204197.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-06T19:28:43.575938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum187952.56
5-th percentile190733.61
Q1192372.58
median192948.08
Q3194439.42
95-th percentile195829.15
Maximum204197.39
Range16244.835
Interquartile range (IQR)2066.8379

Descriptive statistics

Standard deviation1546.7846
Coefficient of variation (CV)0.0080025486
Kurtosis3.0635491
Mean193286.5
Median Absolute Deviation (MAD)884.98824
Skewness0.6039306
Sum1.3085496 × 108
Variance2392542.6
MonotonicityNot monotonic
2024-04-06T19:28:43.820620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194974.587674037 6
 
0.8%
192937.426138742 6
 
0.8%
195703.425296812 6
 
0.8%
195324.793653981 5
 
0.7%
192527.265934192 5
 
0.7%
195019.399817378 5
 
0.7%
195748.06444032 5
 
0.7%
192862.116757044 4
 
0.5%
193286.152946388 4
 
0.5%
194100.139582446 4
 
0.5%
Other values (513) 627
83.3%
(Missing) 76
 
10.1%
ValueCountFrequency (%)
187952.560027898 1
 
0.1%
189369.53962474 1
 
0.1%
189409.319972063 1
 
0.1%
189624.641758403 1
 
0.1%
189855.433985731 3
0.4%
190075.380363452 1
 
0.1%
190125.564768858 1
 
0.1%
190204.923593825 2
0.3%
190221.187884898 4
0.5%
190250.875091908 1
 
0.1%
ValueCountFrequency (%)
204197.395 1
0.1%
197497.808380954 1
0.1%
196564.298958022 1
0.1%
196385.734339392 1
0.1%
196379.695803334 1
0.1%
196293.231026739 1
0.1%
196281.310352227 1
0.1%
196274.957998502 1
0.1%
196230.192860905 1
0.1%
196229.115581681 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct523
Distinct (%)77.3%
Missing76
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean450123.75
Minimum441629.36
Maximum453872.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-06T19:28:44.039733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441629.36
5-th percentile448642.4
Q1449460.09
median450130.32
Q3450596.15
95-th percentile452449.13
Maximum453872.43
Range12243.064
Interquartile range (IQR)1136.0639

Descriptive statistics

Standard deviation1073.5756
Coefficient of variation (CV)0.0023850677
Kurtosis7.2977235
Mean450123.75
Median Absolute Deviation (MAD)575.83158
Skewness-0.20087842
Sum3.0473378 × 108
Variance1152564.6
MonotonicityNot monotonic
2024-04-06T19:28:44.274014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448229.063825491 6
 
0.8%
450226.210530626 6
 
0.8%
449330.800717721 6
 
0.8%
448885.430093289 5
 
0.7%
450204.469476329 5
 
0.7%
448407.752664604 5
 
0.7%
449145.578789461 5
 
0.7%
449741.693030785 4
 
0.5%
449527.466294041 4
 
0.5%
450068.310095071 4
 
0.5%
Other values (513) 627
83.3%
(Missing) 76
 
10.1%
ValueCountFrequency (%)
441629.361414684 1
 
0.1%
444564.045 1
 
0.1%
447510.956185518 1
 
0.1%
448229.063825491 6
0.8%
448332.967337527 1
 
0.1%
448396.329449757 1
 
0.1%
448407.752664604 5
0.7%
448411.703822551 1
 
0.1%
448459.488112945 1
 
0.1%
448476.859046692 2
 
0.3%
ValueCountFrequency (%)
453872.42578746 1
 
0.1%
453614.583448105 3
0.4%
453459.525588653 1
 
0.1%
453345.947683972 1
 
0.1%
453112.077787463 1
 
0.1%
453090.149821248 1
 
0.1%
453017.867202928 1
 
0.1%
452930.266219352 1
 
0.1%
452911.904225602 2
0.3%
452814.165393934 1
 
0.1%

영업내용
Text

MISSING 

Distinct158
Distinct (%)23.0%
Missing67
Missing (%)8.9%
Memory size6.0 KiB
2024-04-06T19:28:44.775774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length5
Mean length7.1428571
Min length3

Characters and Unicode

Total characters4900
Distinct characters94
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)17.5%

Sample

1st row간판및광고물제조
2nd row옥외광고물
3rd row옥외광고물
4th row옥외광고물
5th row옥외광고물
ValueCountFrequency (%)
옥외광고물 370
37.3%
광고대행 94
 
9.5%
및 75
 
7.6%
제작 55
 
5.5%
광고물제작 49
 
4.9%
광고물 22
 
2.2%
간판제조 21
 
2.1%
등 18
 
1.8%
간판 17
 
1.7%
광고물제조 14
 
1.4%
Other values (120) 257
25.9%
2024-04-06T19:28:45.470896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 767
15.7%
고 761
15.5%
물 567
11.6%
외 470
9.6%
옥 467
9.5%
309
 
6.3%
제 249
 
5.1%
작 172
 
3.5%
대 149
 
3.0%
행 148
 
3.0%
Other values (84) 841
17.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4420
90.2%
Space Separator 309
 
6.3%
Other Punctuation 68
 
1.4%
Close Punctuation 48
 
1.0%
Open Punctuation 48
 
1.0%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 767
17.4%
고 761
17.2%
물 567
12.8%
외 470
10.6%
옥 467
10.6%
제 249
 
5.6%
작 172
 
3.9%
대 149
 
3.4%
행 148
 
3.3%
및 104
 
2.4%
Other values (73) 566
12.8%
Uppercase Letter
ValueCountFrequency (%)
S 1
14.3%
D 1
14.3%
I 1
14.3%
G 1
14.3%
N 1
14.3%
L 1
14.3%
E 1
14.3%
Space Separator
ValueCountFrequency (%)
309
100.0%
Other Punctuation
ValueCountFrequency (%)
, 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4420
90.2%
Common 473
 
9.7%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 767
17.4%
고 761
17.2%
물 567
12.8%
외 470
10.6%
옥 467
10.6%
제 249
 
5.6%
작 172
 
3.9%
대 149
 
3.4%
행 148
 
3.3%
및 104
 
2.4%
Other values (73) 566
12.8%
Latin
ValueCountFrequency (%)
S 1
14.3%
D 1
14.3%
I 1
14.3%
G 1
14.3%
N 1
14.3%
L 1
14.3%
E 1
14.3%
Common
ValueCountFrequency (%)
309
65.3%
, 68
 
14.4%
) 48
 
10.1%
( 48
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4420
90.2%
ASCII 480
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 767
17.4%
고 761
17.2%
물 567
12.8%
외 470
10.6%
옥 467
10.6%
제 249
 
5.6%
작 172
 
3.9%
대 149
 
3.4%
행 148
 
3.3%
및 104
 
2.4%
Other values (73) 566
12.8%
ASCII
ValueCountFrequency (%)
309
64.4%
, 68
 
14.2%
) 48
 
10.0%
( 48
 
10.0%
S 1
 
0.2%
D 1
 
0.2%
I 1
 
0.2%
G 1
 
0.2%
N 1
 
0.2%
L 1
 
0.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
0313000019003130134085000202023-05-22<NA>3폐업40폐업2023-05-22<NA><NA><NA><NA><NA><NA>서울특별시 마포구 아현동 ***-** *통*반 .서울특별시 마포구 마포대로 *** (아현동,.)<NA>창미사2023-05-22 10:44:41U2022-12-04 22:04:00.0<NA>196123.351315450104.723189<NA>
13130000190031301340850002720160615<NA>1영업/정상20정상<NA><NA><NA><NA>3344723<NA><NA>서울특별시 마포구 망원동 ***-*번지서울특별시 마포구 동교로 **, *층 (망원동)04018현대공사2016-06-15 16:17:58I2018-08-31 23:59:59.0<NA>192067.852696450218.8781간판및광고물제조
23130000190031301340850003019000101<NA>2휴업30휴업<NA>2003010120030630<NA>02-335-5433<NA><NA>서울특별시 마포구 ***-*번지 *통*반 .<NA><NA>(주)대보애드2007-12-03 16:27:30I2018-08-31 23:59:59.0<NA><NA><NA>옥외광고물
33130000190031301340850003219000101<NA>3폐업40폐업20050622<NA><NA><NA>02-332-5411<NA><NA>서울특별시 마포구 서교동 ***-**번지 *통*반 .서울특별시 마포구 잔다리로 ** (서교동,.)<NA>오상기획2007-12-03 16:27:30I2018-08-31 23:59:59.0<NA>192544.226045450251.557355옥외광고물
43130000190031301340850003719000101<NA>1영업/정상20정상<NA><NA><NA><NA>02-338-4567<NA><NA>서울특별시 마포구 연남동 ***-**서울특별시 마포구 동교로**길 **, 지하*층 (연남동)03984대성네온공사2021-06-24 11:32:52U2021-06-26 02:40:00.0<NA>193069.03966451200.332306옥외광고물
53130000190031301340850004719000101<NA>3폐업40폐업20040309<NA><NA><NA>02-000-0000<NA><NA>서울특별시 마포구 ***-*번지 *통*반 거성빌딩 ****호<NA><NA>(주)파나아트2007-12-03 16:27:30I2018-08-31 23:59:59.0<NA><NA><NA>옥외광고물
63130000190031301340850005320051231<NA>3폐업40폐업20051231<NA><NA><NA>02-336-0851<NA><NA>서울특별시 마포구 서교동 ***-*번지 *통*반 .서울특별시 마포구 홍익로*길 ** (서교동,.)<NA>(주)에스콤2010-03-03 09:14:10I2018-08-31 23:59:59.0<NA>193000.440895450209.598801옥외광고물
73130000190031301340850005419950930<NA>3폐업40폐업19950930<NA><NA><NA>02-702-4475<NA><NA>서울특별시 마포구 신수동 **-***번지 *통*반 .서울특별시 마포구 백범로 ** (신수동,.)<NA>대신기업2010-03-03 09:00:44I2018-08-31 23:59:59.0<NA>194424.86237449836.6894옥외광고물
83130000190031301340850005719000101<NA>3폐업40폐업20150623<NA><NA><NA>02-323-7761<NA><NA>서울특별시 마포구 서교동 ***-**번지 *통*반 . ***동 **호서울특별시 마포구 동교로 **, ***동 **호 (서교동,.)<NA>(주)홍우기획2015-06-23 13:08:26I2018-08-31 23:59:59.0<NA>192240.048644450229.636071옥외광고물
93130000190031301340850006619000101<NA>3폐업40폐업20150515<NA><NA><NA>7045817<NA><NA>서울특별시 마포구 공덕동 ***-**번지 *통*반 .서울특별시 마포구 마포대로 *** (공덕동,.)<NA>대성광고2015-05-15 16:05:54I2018-08-31 23:59:59.0<NA>195967.719264449825.655955간판제조
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
743313000020233130268085000032023-05-25<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 **** 케이지아이티센터서울특별시 마포구 월드컵북로 ***, 케이지아이티센터 ****호 (상암동)03925(주)컵아이앤엠2023-05-25 10:05:45I2022-12-04 22:07:00.0<NA>190125.564769453090.149821<NA>
744313000020233130268085000042023-06-05<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 연남동 ***-**서울특별시 마포구 성미산로**길 **-* (연남동)03979주식회사 프럼에이2023-06-05 13:25:45I2022-12-06 00:08:00.0<NA>192953.847128451411.247078<NA>
745313000020233130268085000052023-06-19<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 동교동 ***-** 해로빌서울특별시 마포구 와우산로**길 **-*, 해로빌 A동 ***호 (동교동)04057사인그라피 스튜디오2023-06-19 15:11:56I2022-12-05 22:01:00.0<NA>193912.235254450338.006177<NA>
746313000020233130268085000062023-07-10<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 염리동 ***-* 마포 한국빌딩서울특별시 마포구 독막로 ***, 마포 한국빌딩 *층 (염리동)04151(주)한네트2023-07-10 11:49:57I2022-12-06 23:03:00.0<NA>195048.36846449214.083651<NA>
747313000020233130268085000072023-07-26<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 동교동 ***-*서울특별시 마포구 신촌로*길 **, *층 (동교동)04056(주)이즈솔루션2023-07-27 09:25:20I2022-12-06 22:09:00.0<NA>193596.863534450569.421142<NA>
748313000020233130268085000082023-11-13<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 ***-**서울특별시 마포구 월드컵북로 **, *층 (서교동)03999애드케이2023-11-13 10:52:34I2022-10-31 23:05:00.0<NA>192633.988797450702.533715<NA>
749313000020243130268085000012024-01-09<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 **** 누리꿈스퀘어서울특별시 마포구 월드컵북로 ***, 누리꿈스퀘어 ****호 (상암동)03925(주)팝스라인2024-01-09 09:53:43I2023-11-30 23:01:00.0<NA>190250.875092453017.867203<NA>
750313000020243130268085000022024-01-17<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 **** 디디엠씨(DDMC)서울특별시 마포구 매봉산로 **, 디디엠씨(DDMC) ****, ****호 (상암동)03926(주)덱스터스튜디오2024-01-17 11:02:07I2023-11-30 23:09:00.0<NA>190471.090858452911.904226<NA>
751313000020243130268085000032024-02-17<NA>1영업/정상20정상<NA><NA><NA><NA>07073733212<NA><NA>서울특별시 마포구 상암동 ****-* 드림타워 *층서울특별시 마포구 월드컵북로**길 **, 드림타워 *층 (상암동)03923주식회사 엘지헬로비전2024-02-19 12:51:20I2023-12-01 22:01:00.0<NA>190075.380363453345.947684<NA>
752313000020243130268085000042024-02-28<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 월드컵북로 **, *층 (서교동)03999주식회사 에드케이2024-02-29 16:13:24I2023-12-03 00:02:00.0<NA>192633.988797450702.533715<NA>