Overview

Dataset statistics

Number of variables34
Number of observations37
Missing cells349
Missing cells (%)27.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory295.6 B

Variable types

Categorical15
Text5
DateTime2
Unsupported8
Numeric4

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),문화체육업종명,공사립구분명,보험가입여부코드,지도자수,건축물동수,건축물연면적,회원모집총인원,세부업종명,법인명
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19695/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
도로명우편번호 is highly imbalanced (56.3%)Imbalance
데이터갱신일자 is highly imbalanced (51.3%)Imbalance
지도자수 is highly imbalanced (59.4%)Imbalance
회원모집총인원 is highly imbalanced (69.7%)Imbalance
인허가취소일자 has 37 (100.0%) missing valuesMissing
폐업일자 has 7 (18.9%) missing valuesMissing
휴업시작일자 has 37 (100.0%) missing valuesMissing
휴업종료일자 has 37 (100.0%) missing valuesMissing
재개업일자 has 37 (100.0%) missing valuesMissing
전화번호 has 8 (21.6%) missing valuesMissing
소재지면적 has 37 (100.0%) missing valuesMissing
도로명주소 has 5 (13.5%) missing valuesMissing
업태구분명 has 37 (100.0%) missing valuesMissing
좌표정보(X) has 4 (10.8%) missing valuesMissing
좌표정보(Y) has 4 (10.8%) missing valuesMissing
건축물연면적 has 25 (67.6%) missing valuesMissing
세부업종명 has 37 (100.0%) missing valuesMissing
법인명 has 37 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 has 6 (16.2%) zerosZeros

Reproduction

Analysis started2024-05-10 23:54:40.580122
Analysis finished2024-05-10 23:54:41.250986
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
3180000
37 

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 37
100.0%

Length

2024-05-10T23:54:41.456389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:41.772386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 37
100.0%

관리번호
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-05-10T23:54:42.164165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters740
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st rowCDFH3301111993000001
2nd rowCDFH3301111994000001
3rd rowCDFH3301111994000003
4th rowCDFH3301111995000002
5th rowCDFH3301111995000003
ValueCountFrequency (%)
cdfh3301111993000001 1
 
2.7%
cdfh3301111999000009 1
 
2.7%
cdfh3301112000000002 1
 
2.7%
cdfh3301112000000003 1
 
2.7%
cdfh3301112000000004 1
 
2.7%
cdfh3301112000000005 1
 
2.7%
cdfh3301112001000001 1
 
2.7%
cdfh3301112001000002 1
 
2.7%
cdfh3301112002000001 1
 
2.7%
cdfh3301112003000001 1
 
2.7%
Other values (27) 27
73.0%
2024-05-10T23:54:42.931204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 258
34.9%
1 153
20.7%
3 81
 
10.9%
9 51
 
6.9%
C 37
 
5.0%
D 37
 
5.0%
F 37
 
5.0%
H 37
 
5.0%
2 27
 
3.6%
8 7
 
0.9%
Other values (4) 15
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 592
80.0%
Uppercase Letter 148
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 258
43.6%
1 153
25.8%
3 81
 
13.7%
9 51
 
8.6%
2 27
 
4.6%
8 7
 
1.2%
4 5
 
0.8%
5 5
 
0.8%
7 3
 
0.5%
6 2
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
C 37
25.0%
D 37
25.0%
F 37
25.0%
H 37
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 592
80.0%
Latin 148
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 258
43.6%
1 153
25.8%
3 81
 
13.7%
9 51
 
8.6%
2 27
 
4.6%
8 7
 
1.2%
4 5
 
0.8%
5 5
 
0.8%
7 3
 
0.5%
6 2
 
0.3%
Latin
ValueCountFrequency (%)
C 37
25.0%
D 37
25.0%
F 37
25.0%
H 37
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 258
34.9%
1 153
20.7%
3 81
 
10.9%
9 51
 
6.9%
C 37
 
5.0%
D 37
 
5.0%
F 37
 
5.0%
H 37
 
5.0%
2 27
 
3.6%
8 7
 
0.9%
Other values (4) 15
 
2.0%

인허가일자
Date

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
Minimum1993-02-01 00:00:00
Maximum2021-04-12 00:00:00
2024-05-10T23:54:43.183803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:54:43.526603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
3
26 
1
7 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row4
5th row3

Common Values

ValueCountFrequency (%)
3 26
70.3%
1 7
 
18.9%
4 4
 
10.8%

Length

2024-05-10T23:54:43.893317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:44.136928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 26
70.3%
1 7
 
18.9%
4 4
 
10.8%

영업상태명
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
폐업
26 
영업/정상
7 
취소/말소/만료/정지/중지
4 

Length

Max length14
Median length2
Mean length3.8648649
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 26
70.3%
영업/정상 7
 
18.9%
취소/말소/만료/정지/중지 4
 
10.8%

Length

2024-05-10T23:54:44.511200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:44.844860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 26
70.3%
영업/정상 7
 
18.9%
취소/말소/만료/정지/중지 4
 
10.8%

상세영업상태코드
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
3
26 
13
7 
35
4 

Length

Max length2
Median length1
Mean length1.2972973
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row13
4th row35
5th row3

Common Values

ValueCountFrequency (%)
3 26
70.3%
13 7
 
18.9%
35 4
 
10.8%

Length

2024-05-10T23:54:45.205722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:45.531578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 26
70.3%
13 7
 
18.9%
35 4
 
10.8%

상세영업상태명
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
폐업
26 
영업중
7 
직권말소
4 

Length

Max length4
Median length2
Mean length2.4054054
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 26
70.3%
영업중 7
 
18.9%
직권말소 4
 
10.8%

Length

2024-05-10T23:54:45.763036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:45.972570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 26
70.3%
영업중 7
 
18.9%
직권말소 4
 
10.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)93.3%
Missing7
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean20105672
Minimum20000128
Maximum20220120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-05-10T23:54:46.225226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000128
5-th percentile20035713
Q120053373
median20090417
Q320160356
95-th percentile20210547
Maximum20220120
Range219992
Interquartile range (IQR)106983.25

Descriptive statistics

Standard deviation60826.466
Coefficient of variation (CV)0.0030253386
Kurtosis-0.82855068
Mean20105672
Median Absolute Deviation (MAD)39462
Skewness0.49143677
Sum6.0317017 × 108
Variance3.699859 × 109
MonotonicityNot monotonic
2024-05-10T23:54:46.555359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20090417 3
 
8.1%
20201005 1
 
2.7%
20170620 1
 
2.7%
20210830 1
 
2.7%
20120514 1
 
2.7%
20071112 1
 
2.7%
20051108 1
 
2.7%
20080327 1
 
2.7%
20130329 1
 
2.7%
20031202 1
 
2.7%
Other values (18) 18
48.6%
(Missing) 7
 
18.9%
ValueCountFrequency (%)
20000128 1
2.7%
20031202 1
2.7%
20041227 1
2.7%
20050329 1
2.7%
20050802 1
2.7%
20051108 1
2.7%
20051122 1
2.7%
20051124 1
2.7%
20060120 1
2.7%
20060208 1
2.7%
ValueCountFrequency (%)
20220120 1
2.7%
20210830 1
2.7%
20210201 1
2.7%
20201005 1
2.7%
20180503 1
2.7%
20171114 1
2.7%
20170620 1
2.7%
20170201 1
2.7%
20130822 1
2.7%
20130329 1
2.7%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing8
Missing (%)21.6%
Memory size428.0 B
2024-05-10T23:54:46.900422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.7241379
Min length8

Characters and Unicode

Total characters253
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

Unique29 ?
Unique (%)100.0%

Sample

1st row784-0619
2nd row2675-1300
3rd row2636-5223
4th row835-7766
5th row678-2319
ValueCountFrequency (%)
784-0619 1
 
3.4%
675-7668 1
 
3.4%
2634-1617 1
 
3.4%
812-7277 1
 
3.4%
2672-8050 1
 
3.4%
2679-8899 1
 
3.4%
02-2672-6008 1
 
3.4%
899-3932 1
 
3.4%
831-7679 1
 
3.4%
678-3646 1
 
3.4%
Other values (19) 19
65.5%
2024-05-10T23:54:47.669915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 44
17.4%
7 37
14.6%
- 32
12.6%
2 28
11.1%
8 21
8.3%
3 18
7.1%
5 18
7.1%
0 16
 
6.3%
1 15
 
5.9%
4 12
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 221
87.4%
Dash Punctuation 32
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 44
19.9%
7 37
16.7%
2 28
12.7%
8 21
9.5%
3 18
8.1%
5 18
8.1%
0 16
 
7.2%
1 15
 
6.8%
4 12
 
5.4%
9 12
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 253
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 44
17.4%
7 37
14.6%
- 32
12.6%
2 28
11.1%
8 21
8.3%
3 18
7.1%
5 18
7.1%
0 16
 
6.3%
1 15
 
5.9%
4 12
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 44
17.4%
7 37
14.6%
- 32
12.6%
2 28
11.1%
8 21
8.3%
3 18
7.1%
5 18
7.1%
0 16
 
6.3%
1 15
 
5.9%
4 12
 
4.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

소재지우편번호
Categorical

Distinct15
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
150033
11 
<NA>
5 
150903
5 
150035
3 
150837
2 
Other values (10)
11 

Length

Max length7
Median length6
Mean length5.8108108
Min length4

Unique

Unique9 ?
Unique (%)24.3%

Sample

1st row150890
2nd row150033
3rd row150-890
4th row150035
5th row150839

Common Values

ValueCountFrequency (%)
150033 11
29.7%
<NA> 5
13.5%
150903 5
13.5%
150035 3
 
8.1%
150837 2
 
5.4%
150031 2
 
5.4%
150890 1
 
2.7%
150-890 1
 
2.7%
150839 1
 
2.7%
150092 1
 
2.7%
Other values (5) 5
13.5%

Length

2024-05-10T23:54:48.104351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
150033 11
29.7%
na 5
13.5%
150903 5
13.5%
150035 3
 
8.1%
150837 2
 
5.4%
150031 2
 
5.4%
150890 1
 
2.7%
150-890 1
 
2.7%
150839 1
 
2.7%
150092 1
 
2.7%
Other values (5) 5
13.5%

지번주소
Text

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-05-10T23:54:48.582211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length26
Min length20

Characters and Unicode

Total characters962
Distinct characters52
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

Unique34 ?
Unique (%)91.9%

Sample

1st row서울특별시 영등포구 여의도동 44-32번지 엘리트B/D903
2nd row서울특별시 영등포구 영등포동3가 12-22번지 4층
3rd row서울특별시 영등포구 여의도동 44-14 경도빌딩 501,502호
4th row서울특별시 영등포구 영등포동5가 27-4번지
5th row서울특별시 영등포구 신길동 96-15번지
ValueCountFrequency (%)
서울특별시 37
22.7%
영등포구 37
22.7%
영등포동3가 12
 
7.4%
영등포동5가 7
 
4.3%
영등포동2가 6
 
3.7%
332-7번지 4
 
2.5%
신길동 3
 
1.8%
영등포동1가 2
 
1.2%
지하1층 2
 
1.2%
영등포동7가 2
 
1.2%
Other values (47) 51
31.3%
2024-05-10T23:54:49.255321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
16.4%
영 68
 
7.1%
등 67
 
7.0%
포 67
 
7.0%
3 40
 
4.2%
서 37
 
3.8%
특 37
 
3.8%
별 37
 
3.8%
시 37
 
3.8%
구 37
 
3.8%
Other values (42) 377
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 597
62.1%
Decimal Number 169
 
17.6%
Space Separator 158
 
16.4%
Dash Punctuation 32
 
3.3%
Other Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 68
11.4%
등 67
11.2%
포 67
11.2%
서 37
 
6.2%
특 37
 
6.2%
별 37
 
6.2%
시 37
 
6.2%
구 37
 
6.2%
동 37
 
6.2%
울 37
 
6.2%
Other values (24) 136
22.8%
Decimal Number
ValueCountFrequency (%)
3 40
23.7%
2 33
19.5%
1 27
16.0%
5 17
10.1%
7 15
 
8.9%
6 13
 
7.7%
4 10
 
5.9%
0 7
 
4.1%
9 4
 
2.4%
8 3
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
, 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 597
62.1%
Common 363
37.7%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 68
11.4%
등 67
11.2%
포 67
11.2%
서 37
 
6.2%
특 37
 
6.2%
별 37
 
6.2%
시 37
 
6.2%
구 37
 
6.2%
동 37
 
6.2%
울 37
 
6.2%
Other values (24) 136
22.8%
Common
ValueCountFrequency (%)
158
43.5%
3 40
 
11.0%
2 33
 
9.1%
- 32
 
8.8%
1 27
 
7.4%
5 17
 
4.7%
7 15
 
4.1%
6 13
 
3.6%
4 10
 
2.8%
0 7
 
1.9%
Other values (6) 11
 
3.0%
Latin
ValueCountFrequency (%)
B 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 597
62.1%
ASCII 365
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
158
43.3%
3 40
 
11.0%
2 33
 
9.0%
- 32
 
8.8%
1 27
 
7.4%
5 17
 
4.7%
7 15
 
4.1%
6 13
 
3.6%
4 10
 
2.7%
0 7
 
1.9%
Other values (8) 13
 
3.6%
Hangul
ValueCountFrequency (%)
영 68
11.4%
등 67
11.2%
포 67
11.2%
서 37
 
6.2%
특 37
 
6.2%
별 37
 
6.2%
시 37
 
6.2%
구 37
 
6.2%
동 37
 
6.2%
울 37
 
6.2%
Other values (24) 136
22.8%

도로명주소
Text

MISSING 

Distinct29
Distinct (%)90.6%
Missing5
Missing (%)13.5%
Memory size428.0 B
2024-05-10T23:54:49.709967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length31.5625
Min length26

Characters and Unicode

Total characters1010
Distinct characters58
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

Unique26 ?
Unique (%)81.2%

Sample

1st row서울특별시 영등포구 여의대방로65길 12 (여의도동,엘리트B/D903)
2nd row서울특별시 영등포구 영중로4길 38 (영등포동3가,4층)
3rd row서울특별시 영등포구 여의대방로 383, 501,502호 (여의도동,경도빌딩)
4th row서울특별시 영등포구 영등포로 382-1 (신길동)
5th row서울특별시 영등포구 영중로10길 43 (영등포동3가)
ValueCountFrequency (%)
서울특별시 32
19.3%
영등포구 32
19.3%
영등포로 16
 
9.6%
영등포동3가 8
 
4.8%
영등포동5가 4
 
2.4%
249-1 4
 
2.4%
영등포동2가 4
 
2.4%
영중로 4
 
2.4%
영중로10길 3
 
1.8%
신길동 3
 
1.8%
Other values (50) 56
33.7%
2024-05-10T23:54:50.661768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
 
15.3%
영 85
 
8.4%
등 75
 
7.4%
포 75
 
7.4%
2 36
 
3.6%
서 32
 
3.2%
울 32
 
3.2%
) 32
 
3.2%
동 32
 
3.2%
( 32
 
3.2%
Other values (48) 424
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 600
59.4%
Decimal Number 158
 
15.6%
Space Separator 155
 
15.3%
Close Punctuation 32
 
3.2%
Open Punctuation 32
 
3.2%
Other Punctuation 18
 
1.8%
Dash Punctuation 13
 
1.3%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 85
14.2%
등 75
12.5%
포 75
12.5%
서 32
 
5.3%
울 32
 
5.3%
동 32
 
5.3%
로 32
 
5.3%
별 32
 
5.3%
구 32
 
5.3%
시 32
 
5.3%
Other values (30) 141
23.5%
Decimal Number
ValueCountFrequency (%)
2 36
22.8%
3 32
20.3%
1 27
17.1%
5 16
10.1%
4 11
 
7.0%
8 9
 
5.7%
9 8
 
5.1%
0 8
 
5.1%
6 7
 
4.4%
7 4
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 17
94.4%
/ 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 600
59.4%
Common 408
40.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 85
14.2%
등 75
12.5%
포 75
12.5%
서 32
 
5.3%
울 32
 
5.3%
동 32
 
5.3%
로 32
 
5.3%
별 32
 
5.3%
구 32
 
5.3%
시 32
 
5.3%
Other values (30) 141
23.5%
Common
ValueCountFrequency (%)
155
38.0%
2 36
 
8.8%
) 32
 
7.8%
( 32
 
7.8%
3 32
 
7.8%
1 27
 
6.6%
, 17
 
4.2%
5 16
 
3.9%
- 13
 
3.2%
4 11
 
2.7%
Other values (6) 37
 
9.1%
Latin
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 600
59.4%
ASCII 410
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
37.8%
2 36
 
8.8%
) 32
 
7.8%
( 32
 
7.8%
3 32
 
7.8%
1 27
 
6.6%
, 17
 
4.1%
5 16
 
3.9%
- 13
 
3.2%
4 11
 
2.7%
Other values (8) 39
 
9.5%
Hangul
ValueCountFrequency (%)
영 85
14.2%
등 75
12.5%
포 75
12.5%
서 32
 
5.3%
울 32
 
5.3%
동 32
 
5.3%
로 32
 
5.3%
별 32
 
5.3%
구 32
 
5.3%
시 32
 
5.3%
Other values (30) 141
23.5%

도로명우편번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
<NA>
30 
7250
4 
7302
 
1
7252
 
1
7303
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique3 ?
Unique (%)8.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
81.1%
7250 4
 
10.8%
7302 1
 
2.7%
7252 1
 
2.7%
7303 1
 
2.7%

Length

2024-05-10T23:54:51.082208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:51.419399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
81.1%
7250 4
 
10.8%
7302 1
 
2.7%
7252 1
 
2.7%
7303 1
 
2.7%

사업장명
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-05-10T23:54:51.890467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.1891892
Min length2

Characters and Unicode

Total characters192
Distinct characters80
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)94.6%

Sample

1st row여의도
2nd row명문
3rd row써니박 라틴댄스 아카데미
4th row제일
5th row명현이네
ValueCountFrequency (%)
중앙 2
 
4.5%
베스트리듬댄스 1
 
2.3%
월드댄스스포츠학원 1
 
2.3%
예성 1
 
2.3%
청록 1
 
2.3%
유나 1
 
2.3%
코리아나무도학원 1
 
2.3%
한빛무도학원 1
 
2.3%
남경 1
 
2.3%
로타리무도학원 1
 
2.3%
Other values (33) 33
75.0%
2024-05-10T23:54:52.840645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 22
 
11.5%
댄 11
 
5.7%
학 10
 
5.2%
원 10
 
5.2%
도 8
 
4.2%
포 8
 
4.2%
츠 8
 
4.2%
무 7
 
3.6%
7
 
3.6%
리 6
 
3.1%
Other values (70) 95
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183
95.3%
Space Separator 7
 
3.6%
Decimal Number 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 22
 
12.0%
댄 11
 
6.0%
학 10
 
5.5%
원 10
 
5.5%
도 8
 
4.4%
포 8
 
4.4%
츠 8
 
4.4%
무 7
 
3.8%
리 6
 
3.3%
명 3
 
1.6%
Other values (68) 90
49.2%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
5 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 183
95.3%
Common 9
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 22
 
12.0%
댄 11
 
6.0%
학 10
 
5.5%
원 10
 
5.5%
도 8
 
4.4%
포 8
 
4.4%
츠 8
 
4.4%
무 7
 
3.8%
리 6
 
3.3%
명 3
 
1.6%
Other values (68) 90
49.2%
Common
ValueCountFrequency (%)
7
77.8%
5 2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183
95.3%
ASCII 9
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 22
 
12.0%
댄 11
 
6.0%
학 10
 
5.5%
원 10
 
5.5%
도 8
 
4.4%
포 8
 
4.4%
츠 8
 
4.4%
무 7
 
3.8%
리 6
 
3.3%
명 3
 
1.6%
Other values (68) 90
49.2%
ASCII
ValueCountFrequency (%)
7
77.8%
5 2
 
22.2%

최종수정일자
Date

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
Minimum2003-04-18 15:28:04
Maximum2024-02-14 11:08:18
2024-05-10T23:54:53.228437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:54:53.641674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
I
28 
U
9 

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 28
75.7%
U 9
 
24.3%

Length

2024-05-10T23:54:54.032107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:54.374490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 28
75.7%
u 9
 
24.3%

데이터갱신일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size428.0 B
2018-08-31 23:59:59.0
28 
2023-12-01 23:06:00.0
5 
2021-02-03 02:40:00.0
 
1
2022-01-22 02:40:00.0
 
1
2020-10-07 02:40:00.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique4 ?
Unique (%)10.8%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2023-12-01 23:06:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 28
75.7%
2023-12-01 23:06:00.0 5
 
13.5%
2021-02-03 02:40:00.0 1
 
2.7%
2022-01-22 02:40:00.0 1
 
2.7%
2020-10-07 02:40:00.0 1
 
2.7%
2021-09-01 02:40:00.0 1
 
2.7%

Length

2024-05-10T23:54:54.887101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:55.371813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 28
37.8%
23:59:59.0 28
37.8%
2023-12-01 5
 
6.8%
23:06:00.0 5
 
6.8%
02:40:00.0 4
 
5.4%
2021-02-03 1
 
1.4%
2022-01-22 1
 
1.4%
2020-10-07 1
 
1.4%
2021-09-01 1
 
1.4%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)84.8%
Missing4
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean191975.65
Minimum190410.67
Maximum193870.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-05-10T23:54:55.875813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190410.67
5-th percentile191348.73
Q1191663.09
median191874.7
Q3192015.56
95-th percentile193323.51
Maximum193870.81
Range3460.1383
Interquartile range (IQR)352.47811

Descriptive statistics

Standard deviation670.12515
Coefficient of variation (CV)0.0034906778
Kurtosis2.7921131
Mean191975.65
Median Absolute Deviation (MAD)141.80336
Skewness1.172564
Sum6335196.5
Variance449067.71
MonotonicityNot monotonic
2024-05-10T23:54:56.480696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
191908.634244893 4
 
10.8%
191732.892900792 2
 
5.4%
192015.563167244 2
 
5.4%
191917.561920888 1
 
2.7%
191784.794564879 1
 
2.7%
191546.509628902 1
 
2.7%
191476.429288795 1
 
2.7%
193023.082601626 1
 
2.7%
191853.391777102 1
 
2.7%
191769.314678876 1
 
2.7%
Other values (18) 18
48.6%
(Missing) 4
 
10.8%
ValueCountFrequency (%)
190410.674585518 1
2.7%
191157.184455732 1
2.7%
191476.429288795 1
2.7%
191540.1178181 1
2.7%
191546.509628902 1
2.7%
191573.154456698 1
2.7%
191626.989430711 1
2.7%
191661.036153797 1
2.7%
191663.085056707 1
2.7%
191723.182919733 1
2.7%
ValueCountFrequency (%)
193870.812916718 1
2.7%
193745.64337296 1
2.7%
193042.092915795 1
2.7%
193023.082601626 1
2.7%
192902.256553057 1
2.7%
192038.23560773 1
2.7%
192016.315942134 1
2.7%
192015.563167244 2
5.4%
192006.229698115 1
2.7%
191982.613337632 1
2.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)84.8%
Missing4
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean446320.94
Minimum445539.74
Maximum448006.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-05-10T23:54:57.569895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445539.74
5-th percentile445710.09
Q1446222.79
median446339.26
Q3446380.25
95-th percentile446844.35
Maximum448006.55
Range2466.8031
Interquartile range (IQR)157.46303

Descriptive statistics

Standard deviation410.19204
Coefficient of variation (CV)0.00091905175
Kurtosis8.7761114
Mean446320.94
Median Absolute Deviation (MAD)73.975086
Skewness1.9170365
Sum14728591
Variance168257.51
MonotonicityNot monotonic
2024-05-10T23:54:58.093489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
446341.469456035 4
 
10.8%
446390.542846428 2
 
5.4%
446265.282454703 2
 
5.4%
446339.257541108 1
 
2.7%
446222.791601545 1
 
2.7%
446519.577188055 1
 
2.7%
446466.247657464 1
 
2.7%
445717.452325145 1
 
2.7%
446182.129014848 1
 
2.7%
446310.154682683 1
 
2.7%
Other values (18) 18
48.6%
(Missing) 4
 
10.8%
ValueCountFrequency (%)
445539.743961617 1
2.7%
445699.051714344 1
2.7%
445717.452325145 1
2.7%
445717.999672415 1
2.7%
446140.25090082 1
2.7%
446145.18900308 1
2.7%
446182.129014848 1
2.7%
446211.81231008 1
2.7%
446222.791601545 1
2.7%
446227.4563182 1
2.7%
ValueCountFrequency (%)
448006.547069614 1
2.7%
446959.492413252 1
2.7%
446767.583022901 1
2.7%
446519.577188055 1
2.7%
446466.247657464 1
2.7%
446400.902615722 1
2.7%
446390.542846428 2
5.4%
446380.254633325 1
2.7%
446370.303360468 1
2.7%
446352.494864804 1
2.7%

문화체육업종명
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
무도학원업
32 
<NA>
5 

Length

Max length5
Median length5
Mean length4.8648649
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무도학원업 32
86.5%
<NA> 5
 
13.5%

Length

2024-05-10T23:54:58.803602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:54:59.316748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무도학원업 32
86.5%
na 5
 
13.5%

공사립구분명
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
사립
32 
<NA>
5 

Length

Max length4
Median length2
Mean length2.2702703
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 32
86.5%
<NA> 5
 
13.5%

Length

2024-05-10T23:55:00.013120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:55:00.606477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 32
86.5%
na 5
 
13.5%

보험가입여부코드
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
<NA>
19 
0
18 

Length

Max length4
Median length4
Mean length2.5405405
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
51.4%
0 18
48.6%

Length

2024-05-10T23:55:01.251197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:55:01.698666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
51.4%
0 18
48.6%

지도자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
<NA>
34 
0
 
3

Length

Max length4
Median length4
Mean length3.7567568
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 34
91.9%
0 3
 
8.1%

Length

2024-05-10T23:55:02.117497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:55:02.531649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
91.9%
0 3
 
8.1%

건축물동수
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
<NA>
29 
0
7 
1
 
1

Length

Max length4
Median length4
Mean length3.3513514
Min length1

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 29
78.4%
0 7
 
18.9%
1 1
 
2.7%

Length

2024-05-10T23:55:02.938869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:55:03.340012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
78.4%
0 7
 
18.9%
1 1
 
2.7%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)50.0%
Missing25
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean413.60833
Minimum0
Maximum1018.21
Zeros6
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-05-10T23:55:03.704547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median341.81
Q3832.75
95-th percentile950.5215
Maximum1018.21
Range1018.21
Interquartile range (IQR)832.75

Descriptive statistics

Standard deviation440.10423
Coefficient of variation (CV)1.0640604
Kurtosis-2.1985801
Mean413.60833
Median Absolute Deviation (MAD)341.81
Skewness0.12640162
Sum4963.3
Variance193691.74
MonotonicityNot monotonic
2024-05-10T23:55:04.194376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 6
 
16.2%
832.75 2
 
5.4%
895.14 1
 
2.7%
1018.21 1
 
2.7%
683.62 1
 
2.7%
700.83 1
 
2.7%
(Missing) 25
67.6%
ValueCountFrequency (%)
0.0 6
16.2%
683.62 1
 
2.7%
700.83 1
 
2.7%
832.75 2
 
5.4%
895.14 1
 
2.7%
1018.21 1
 
2.7%
ValueCountFrequency (%)
1018.21 1
 
2.7%
895.14 1
 
2.7%
832.75 2
 
5.4%
700.83 1
 
2.7%
683.62 1
 
2.7%
0.0 6
16.2%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
<NA>
35 
0
 
2

Length

Max length4
Median length4
Mean length3.8378378
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 35
94.6%
0 2
 
5.4%

Length

2024-05-10T23:55:04.825099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:55:05.508941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
94.6%
0 2
 
5.4%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03180000CDFH330111199300000119930201<NA>3폐업3폐업20000128<NA><NA><NA>784-0619<NA>150890서울특별시 영등포구 여의도동 44-32번지 엘리트B/D903서울특별시 영등포구 여의대방로65길 12 (여의도동,엘리트B/D903)<NA>여의도2003-04-18 15:28:04I2018-08-31 23:59:59.0<NA>193745.643373446380.254633무도학원업사립<NA>000.0<NA><NA><NA>
13180000CDFH330111199400000119940127<NA>3폐업3폐업20130822<NA><NA><NA>2675-1300<NA>150033서울특별시 영등포구 영등포동3가 12-22번지 4층서울특별시 영등포구 영중로4길 38 (영등포동3가,4층)<NA>명문2013-08-22 21:48:30I2018-08-31 23:59:59.0<NA>192006.229698446211.81231무도학원업사립0<NA><NA><NA><NA><NA><NA>
23180000CDFH33011119940000031994-04-21<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>150-890서울특별시 영등포구 여의도동 44-14 경도빌딩 501,502호서울특별시 영등포구 여의대방로 383, 501,502호 (여의도동,경도빌딩)<NA>써니박 라틴댄스 아카데미2024-02-14 11:08:18U2023-12-01 23:06:00.0<NA>193870.812917446351.974201<NA><NA><NA><NA><NA><NA><NA><NA><NA>
33180000CDFH330111199500000219951214<NA>4취소/말소/만료/정지/중지35직권말소20090417<NA><NA><NA>2636-5223<NA>150035서울특별시 영등포구 영등포동5가 27-4번지<NA><NA>제일2009-07-16 14:40:40I2018-08-31 23:59:59.0<NA><NA><NA>무도학원업사립<NA><NA><NA><NA><NA><NA><NA>
43180000CDFH330111199500000319951130<NA>3폐업3폐업20060208<NA><NA><NA>835-7766<NA>150839서울특별시 영등포구 신길동 96-15번지서울특별시 영등포구 영등포로 382-1 (신길동)<NA>명현이네2006-02-10 16:48:53I2018-08-31 23:59:59.0<NA>192902.256553445699.051714무도학원업사립0<NA><NA><NA><NA><NA><NA>
53180000CDFH330111199600000119961115<NA>3폐업3폐업20051122<NA><NA><NA>678-2319<NA>150033서울특별시 영등포구 영등포동3가 2-3번지서울특별시 영등포구 영중로10길 43 (영등포동3가)<NA>두리두리2005-11-24 14:36:58I2018-08-31 23:59:59.0<NA>191982.613338446255.109043무도학원업사립0<NA><NA><NA><NA><NA><NA>
63180000CDFH330111199700000119970808<NA>4취소/말소/만료/정지/중지35직권말소20090417<NA><NA><NA>651-7224<NA>150092서울특별시 영등포구 문래동2가 29-1번지<NA><NA>문래2009-07-16 14:41:18I2018-08-31 23:59:59.0<NA>190410.674586445539.743962무도학원업사립<NA><NA>00.0<NA><NA><NA>
73180000CDFH330111199700000219970521<NA>3폐업3폐업20171114<NA><NA><NA>2637-2149<NA>150037서울특별시 영등포구 영등포동7가 41번지 지하1층서울특별시 영등포구 영중로 76-1 (영등포동7가,지하1층)<NA>5호선 스포츠댄스2017-11-14 10:41:30I2018-08-31 23:59:59.0<NA>191573.154457446767.583023무도학원업사립<NA><NA><NA>895.14<NA><NA><NA>
83180000CDFH33011119980000011998-11-25<NA>1영업/정상13영업중<NA><NA><NA><NA>2671-1568<NA>150-037서울특별시 영등포구 영등포동7가 70-4 지하1층서울특별시 영등포구 영중로 95-1 (영등포동7가,지하1층)<NA>와 스포츠댄스학원2024-02-14 10:59:56U2023-12-01 23:06:00.0<NA>191540.117818446959.492413<NA><NA><NA><NA><NA><NA><NA><NA><NA>
93180000CDFH330111199800000319981008<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3667-4877<NA>150035서울특별시 영등포구 영등포동5가 18번지 (영신상가 2층)<NA><NA>영신2017-11-13 18:02:25I2018-08-31 23:59:59.0<NA><NA><NA>무도학원업사립<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
273180000CDFH330111200200000120020329<NA>3폐업3폐업20080327<NA><NA><NA>899-3932<NA>150837서울특별시 영등포구 신길동 66-13번지서울특별시 영등포구 영등포로 393 (신길동)<NA>월드댄스스포츠학원2008-03-27 10:59:53I2018-08-31 23:59:59.0<NA>193023.082602445717.452325무도학원업사립0<NA><NA><NA><NA><NA><NA>
283180000CDFH330111200300000120030916<NA>3폐업3폐업20051108<NA><NA><NA><NA><NA>150036서울특별시 영등포구 영등포동6가 1-15번지서울특별시 영등포구 영중로 43 (영등포동6가)<NA>로타리무도학원2005-11-09 15:48:17I2018-08-31 23:59:59.0<NA>191476.429289446466.247657무도학원업사립0<NA><NA><NA><NA><NA><NA>
293180000CDFH330111200500000120050805<NA>3폐업3폐업20071112<NA><NA><NA>02-2672-6008<NA>150903서울특별시 영등포구 영등포동2가 332-7번지서울특별시 영등포구 영등포로 249-1 (영등포동2가)<NA>유나무도학원2007-11-12 17:47:33I2018-08-31 23:59:59.0<NA>191908.634245446341.469456무도학원업사립0<NA>1832.75<NA><NA><NA>
303180000CDFH330111200800000120080729<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동5가 27-6번지서울특별시 영등포구 영중로 52-1, 지하1층 (영등포동5가)7250세븐댄스스포츠2017-11-20 17:53:04I2018-08-31 23:59:59.0<NA>191546.509629446519.577188무도학원업사립<NA><NA><NA>683.62<NA><NA><NA>
313180000CDFH330111200800000220081231<NA>3폐업3폐업20120514<NA><NA><NA>2679-8899<NA>150903서울특별시 영등포구 영등포동2가 332-7번지 3층서울특별시 영등포구 영등포로 249-1 (영등포동2가,3층)<NA>최호범 댄스학원2012-06-04 13:39:44I2018-08-31 23:59:59.0<NA>191908.634245446341.469456무도학원업사립<NA><NA><NA>832.75<NA><NA><NA>
323180000CDFH330111200900000120090202<NA>3폐업3폐업20210830<NA><NA><NA>2672-8050<NA>150033서울특별시 영등포구 영등포동3가 26 3층서울특별시 영등포구 영중로8길 20 (영등포동3가,3층)<NA>좋은날2021-08-30 13:45:02U2021-09-01 02:40:00.0<NA>191784.794565446222.791602무도학원업사립000700.830<NA><NA>
333180000CDFH33011120100000012010-03-10<NA>1영업/정상13영업중<NA><NA><NA><NA>812-7277<NA>150-903서울특별시 영등포구 영등포동2가 332-2 3층층서울특별시 영등포구 영등포로 251 (영등포동2가,3층층)<NA>동작무도학원2024-02-14 11:05:14U2023-12-01 23:06:00.0<NA>191917.561921446339.257541<NA><NA><NA><NA><NA><NA><NA><NA><NA>
343180000CDFH330111201200000120120607<NA>3폐업3폐업20170620<NA><NA><NA><NA><NA>150903서울특별시 영등포구 영등포동2가 332-7번지서울특별시 영등포구 영등포로 249-1 (영등포동2가)7252이사베리오 댄스스포츠2017-06-21 13:58:16I2018-08-31 23:59:59.0<NA>191908.634245446341.469456무도학원업사립<NA><NA><NA><NA><NA><NA><NA>
353180000CDFH33011120180000022018-09-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동3가 2-7서울특별시 영등포구 영등포로 262 (영등포동3가)7303베스트리듬댄스 무도학원2024-02-14 11:04:55U2023-12-01 23:06:00.0<NA>192015.563167446265.282455<NA><NA><NA><NA><NA><NA><NA><NA><NA>
363180000CDFH33011120210000012021-04-12<NA>1영업/정상13영업중<NA><NA><NA><NA>02-703-4679<NA><NA>서울특별시 영등포구 영등포동5가 6-3서울특별시 영등포구 영등포로 231-1, 3층 (영등포동5가)7250이동석댄스스포츠스쿨2024-02-14 11:04:42U2023-12-01 23:06:00.0<NA>191732.892901446390.542846<NA><NA><NA><NA><NA><NA><NA><NA><NA>