Overview

Dataset statistics

Number of variables34
Number of observations57
Missing cells579
Missing cells (%)29.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.3 KiB
Average record size in memory292.3 B

Variable types

Categorical14
Text6
DateTime4
Unsupported7
Numeric3

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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-19828/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (57.9%)Imbalance
회원모집총인원 is highly imbalanced (87.3%)Imbalance
인허가취소일자 has 57 (100.0%) missing valuesMissing
폐업일자 has 34 (59.6%) missing valuesMissing
휴업시작일자 has 57 (100.0%) missing valuesMissing
휴업종료일자 has 57 (100.0%) missing valuesMissing
재개업일자 has 57 (100.0%) missing valuesMissing
전화번호 has 42 (73.7%) missing valuesMissing
소재지면적 has 57 (100.0%) missing valuesMissing
소재지우편번호 has 15 (26.3%) missing valuesMissing
지번주소 has 1 (1.8%) missing valuesMissing
도로명주소 has 37 (64.9%) missing valuesMissing
도로명우편번호 has 37 (64.9%) missing valuesMissing
좌표정보(X) has 7 (12.3%) missing valuesMissing
좌표정보(Y) has 7 (12.3%) missing valuesMissing
세부업종명 has 57 (100.0%) missing valuesMissing
법인명 has 57 (100.0%) missing valuesMissing
관리번호 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
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

Reproduction

Analysis started2024-05-11 05:22:41.245566
Analysis finished2024-05-11 05:22:41.742270
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
3010000
57 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 57
100.0%

Length

2024-05-11T14:22:41.837003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:41.965753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 57
100.0%

관리번호
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-05-11T14:22:42.190962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1140
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

Unique57 ?
Unique (%)100.0%

Sample

1st rowCDFH3301021989000001
2nd rowCDFH3301021989000002
3rd rowCDFH3301021989000003
4th rowCDFH3301021989000004
5th rowCDFH3301021990000001
ValueCountFrequency (%)
cdfh3301021989000001 1
 
1.8%
cdfh3301022004000003 1
 
1.8%
cdfh3301022005000001 1
 
1.8%
cdfh3301022005000002 1
 
1.8%
cdfh3301022005000003 1
 
1.8%
cdfh3301022005000004 1
 
1.8%
cdfh3301022005000005 1
 
1.8%
cdfh3301022006000002 1
 
1.8%
cdfh3301022006000004 1
 
1.8%
cdfh3301022007000001 1
 
1.8%
Other values (47) 47
82.5%
2024-05-11T14:22:42.681674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 464
40.7%
3 128
 
11.2%
1 113
 
9.9%
2 111
 
9.7%
C 57
 
5.0%
D 57
 
5.0%
F 57
 
5.0%
H 57
 
5.0%
9 51
 
4.5%
4 16
 
1.4%
Other values (4) 29
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 912
80.0%
Uppercase Letter 228
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 464
50.9%
3 128
 
14.0%
1 113
 
12.4%
2 111
 
12.2%
9 51
 
5.6%
4 16
 
1.8%
8 14
 
1.5%
5 8
 
0.9%
6 4
 
0.4%
7 3
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
C 57
25.0%
D 57
25.0%
F 57
25.0%
H 57
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 912
80.0%
Latin 228
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 464
50.9%
3 128
 
14.0%
1 113
 
12.4%
2 111
 
12.2%
9 51
 
5.6%
4 16
 
1.8%
8 14
 
1.5%
5 8
 
0.9%
6 4
 
0.4%
7 3
 
0.3%
Latin
ValueCountFrequency (%)
C 57
25.0%
D 57
25.0%
F 57
25.0%
H 57
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 464
40.7%
3 128
 
11.2%
1 113
 
9.9%
2 111
 
9.7%
C 57
 
5.0%
D 57
 
5.0%
F 57
 
5.0%
H 57
 
5.0%
9 51
 
4.5%
4 16
 
1.4%
Other values (4) 29
 
2.5%

인허가일자
Date

Distinct52
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum1989-12-16 00:00:00
Maximum2024-02-02 00:00:00
2024-05-11T14:22:42.873838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:43.060806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
1
34 
3
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 34
59.6%
3 23
40.4%

Length

2024-05-11T14:22:43.196978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:43.303331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 34
59.6%
3 23
40.4%

영업상태명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
영업/정상
34 
폐업
23 

Length

Max length5
Median length5
Mean length3.7894737
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 34
59.6%
폐업 23
40.4%

Length

2024-05-11T14:22:43.435191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:43.615950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 34
59.6%
폐업 23
40.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
13
34 
3
23 

Length

Max length2
Median length2
Mean length1.5964912
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 34
59.6%
3 23
40.4%

Length

2024-05-11T14:22:43.748127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:44.192601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 34
59.6%
3 23
40.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
영업중
34 
폐업
23 

Length

Max length3
Median length3
Mean length2.5964912
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 34
59.6%
폐업 23
40.4%

Length

2024-05-11T14:22:44.333986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:44.459776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 34
59.6%
폐업 23
40.4%

폐업일자
Date

MISSING 

Distinct19
Distinct (%)82.6%
Missing34
Missing (%)59.6%
Memory size588.0 B
Minimum1994-12-06 00:00:00
Maximum2023-08-31 00:00:00
2024-05-11T14:22:44.580982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:44.706865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

전화번호
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing42
Missing (%)73.7%
Memory size588.0 B
2024-05-11T14:22:44.870774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.9333333
Min length8

Characters and Unicode

Total characters149
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

Unique15 ?
Unique (%)100.0%

Sample

1st row2232-3555
2nd row2273-8927
3rd row2256-3311
4th row02-2237-8852
5th row2235-4132
ValueCountFrequency (%)
2232-3555 1
 
6.7%
2273-8927 1
 
6.7%
2256-3311 1
 
6.7%
02-2237-8852 1
 
6.7%
2235-4132 1
 
6.7%
2252-7333 1
 
6.7%
2264-4595 1
 
6.7%
2237-5800 1
 
6.7%
2233-0678 1
 
6.7%
364-7989 1
 
6.7%
Other values (5) 5
33.3%
2024-05-11T14:22:45.220385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 42
28.2%
3 21
14.1%
- 20
13.4%
5 16
 
10.7%
0 11
 
7.4%
7 8
 
5.4%
8 8
 
5.4%
1 7
 
4.7%
6 6
 
4.0%
9 5
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 129
86.6%
Dash Punctuation 20
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 42
32.6%
3 21
16.3%
5 16
 
12.4%
0 11
 
8.5%
7 8
 
6.2%
8 8
 
6.2%
1 7
 
5.4%
6 6
 
4.7%
9 5
 
3.9%
4 5
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 149
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 42
28.2%
3 21
14.1%
- 20
13.4%
5 16
 
10.7%
0 11
 
7.4%
7 8
 
5.4%
8 8
 
5.4%
1 7
 
4.7%
6 6
 
4.0%
9 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 42
28.2%
3 21
14.1%
- 20
13.4%
5 16
 
10.7%
0 11
 
7.4%
7 8
 
5.4%
8 8
 
5.4%
1 7
 
4.7%
6 6
 
4.0%
9 5
 
3.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

소재지우편번호
Text

MISSING 

Distinct32
Distinct (%)76.2%
Missing15
Missing (%)26.3%
Memory size588.0 B
2024-05-11T14:22:45.426504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0238095
Min length6

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

Unique27 ?
Unique (%)64.3%

Sample

1st row100858
2nd row100871
3rd row100834
4th row100879
5th row100011
ValueCountFrequency (%)
100450 5
 
11.9%
100824 4
 
9.5%
100834 2
 
4.8%
100868 2
 
4.8%
100826 2
 
4.8%
100032 1
 
2.4%
100455 1
 
2.4%
100456 1
 
2.4%
100859 1
 
2.4%
100781 1
 
2.4%
Other values (22) 22
52.4%
2024-05-11T14:22:45.814334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96
37.9%
1 50
19.8%
8 32
 
12.6%
4 18
 
7.1%
5 15
 
5.9%
2 13
 
5.1%
6 8
 
3.2%
9 7
 
2.8%
7 7
 
2.8%
3 6
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
99.6%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96
38.1%
1 50
19.8%
8 32
 
12.7%
4 18
 
7.1%
5 15
 
6.0%
2 13
 
5.2%
6 8
 
3.2%
9 7
 
2.8%
7 7
 
2.8%
3 6
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 253
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 96
37.9%
1 50
19.8%
8 32
 
12.6%
4 18
 
7.1%
5 15
 
5.9%
2 13
 
5.1%
6 8
 
3.2%
9 7
 
2.8%
7 7
 
2.8%
3 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96
37.9%
1 50
19.8%
8 32
 
12.6%
4 18
 
7.1%
5 15
 
5.9%
2 13
 
5.1%
6 8
 
3.2%
9 7
 
2.8%
7 7
 
2.8%
3 6
 
2.4%

지번주소
Text

MISSING 

Distinct53
Distinct (%)94.6%
Missing1
Missing (%)1.8%
Memory size588.0 B
2024-05-11T14:22:46.109310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length23.339286
Min length16

Characters and Unicode

Total characters1307
Distinct characters76
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

Unique50 ?
Unique (%)89.3%

Sample

1st row서울특별시 중구 중림동 129-15번지
2nd row서울특별시 중구 황학동 2488번지
3rd row서울특별시 중구 신당동 386-10번지
4th row서울특별시 중구 흥인동 25-1번지
5th row서울특별시 중구 충무로1가 51-7번지
ValueCountFrequency (%)
서울특별시 56
22.5%
중구 56
22.5%
신당동 38
15.3%
황학동 6
 
2.4%
370-24번지 2
 
0.8%
태양빌딩 2
 
0.8%
62-95번지 2
 
0.8%
묵정동 2
 
0.8%
3층 2
 
0.8%
저동2가 2
 
0.8%
Other values (76) 81
32.5%
2024-05-11T14:22:46.634818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
18.2%
중 59
 
4.5%
서 56
 
4.3%
울 56
 
4.3%
특 56
 
4.3%
별 56
 
4.3%
시 56
 
4.3%
구 56
 
4.3%
동 56
 
4.3%
지 48
 
3.7%
Other values (66) 570
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 750
57.4%
Decimal Number 266
 
20.4%
Space Separator 238
 
18.2%
Dash Punctuation 46
 
3.5%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 59
 
7.9%
서 56
 
7.5%
울 56
 
7.5%
특 56
 
7.5%
별 56
 
7.5%
시 56
 
7.5%
구 56
 
7.5%
동 56
 
7.5%
지 48
 
6.4%
번 45
 
6.0%
Other values (51) 206
27.5%
Decimal Number
ValueCountFrequency (%)
2 45
16.9%
3 41
15.4%
4 36
13.5%
1 36
13.5%
0 27
10.2%
5 22
8.3%
7 20
7.5%
8 17
 
6.4%
9 12
 
4.5%
6 10
 
3.8%
Space Separator
ValueCountFrequency (%)
238
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 750
57.4%
Common 556
42.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 59
 
7.9%
서 56
 
7.5%
울 56
 
7.5%
특 56
 
7.5%
별 56
 
7.5%
시 56
 
7.5%
구 56
 
7.5%
동 56
 
7.5%
지 48
 
6.4%
번 45
 
6.0%
Other values (51) 206
27.5%
Common
ValueCountFrequency (%)
238
42.8%
- 46
 
8.3%
2 45
 
8.1%
3 41
 
7.4%
4 36
 
6.5%
1 36
 
6.5%
0 27
 
4.9%
5 22
 
4.0%
7 20
 
3.6%
8 17
 
3.1%
Other values (4) 28
 
5.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 750
57.4%
ASCII 557
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
238
42.7%
- 46
 
8.3%
2 45
 
8.1%
3 41
 
7.4%
4 36
 
6.5%
1 36
 
6.5%
0 27
 
4.8%
5 22
 
3.9%
7 20
 
3.6%
8 17
 
3.1%
Other values (5) 29
 
5.2%
Hangul
ValueCountFrequency (%)
중 59
 
7.9%
서 56
 
7.5%
울 56
 
7.5%
특 56
 
7.5%
별 56
 
7.5%
시 56
 
7.5%
구 56
 
7.5%
동 56
 
7.5%
지 48
 
6.4%
번 45
 
6.0%
Other values (51) 206
27.5%

도로명주소
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing37
Missing (%)64.9%
Memory size588.0 B
2024-05-11T14:22:46.907022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length27.55
Min length22

Characters and Unicode

Total characters551
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)90.0%

Sample

1st row서울특별시 중구 다산로28길 40 (신당동)
2nd row서울특별시 중구 퇴계로87길 29, 지하1, 2층 (황학동)
3rd row서울특별시 중구 퇴계로 377 (신당동)
4th row서울특별시 중구 퇴계로 377 (신당동)
5th row서울특별시 중구 동호로12길 98, 103호 (신당동)
ValueCountFrequency (%)
서울특별시 20
16.9%
중구 20
16.9%
신당동 16
 
13.6%
다산로 6
 
5.1%
퇴계로 4
 
3.4%
지하1층 2
 
1.7%
150 2
 
1.7%
태양빌딩 2
 
1.7%
황학동 2
 
1.7%
2층 2
 
1.7%
Other values (39) 42
35.6%
2024-05-11T14:22:47.402464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
 
17.8%
동 23
 
4.2%
서 20
 
3.6%
구 20
 
3.6%
) 20
 
3.6%
( 20
 
3.6%
로 20
 
3.6%
울 20
 
3.6%
중 20
 
3.6%
시 20
 
3.6%
Other values (48) 270
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 314
57.0%
Space Separator 98
 
17.8%
Decimal Number 83
 
15.1%
Close Punctuation 20
 
3.6%
Open Punctuation 20
 
3.6%
Other Punctuation 14
 
2.5%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
 
7.3%
서 20
 
6.4%
구 20
 
6.4%
로 20
 
6.4%
울 20
 
6.4%
중 20
 
6.4%
시 20
 
6.4%
별 20
 
6.4%
특 20
 
6.4%
당 16
 
5.1%
Other values (33) 115
36.6%
Decimal Number
ValueCountFrequency (%)
2 16
19.3%
1 16
19.3%
3 10
12.0%
8 10
12.0%
7 8
9.6%
0 6
 
7.2%
5 5
 
6.0%
4 5
 
6.0%
9 5
 
6.0%
6 2
 
2.4%
Space Separator
ValueCountFrequency (%)
98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 314
57.0%
Common 237
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
 
7.3%
서 20
 
6.4%
구 20
 
6.4%
로 20
 
6.4%
울 20
 
6.4%
중 20
 
6.4%
시 20
 
6.4%
별 20
 
6.4%
특 20
 
6.4%
당 16
 
5.1%
Other values (33) 115
36.6%
Common
ValueCountFrequency (%)
98
41.4%
) 20
 
8.4%
( 20
 
8.4%
2 16
 
6.8%
1 16
 
6.8%
, 14
 
5.9%
3 10
 
4.2%
8 10
 
4.2%
7 8
 
3.4%
0 6
 
2.5%
Other values (5) 19
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 314
57.0%
ASCII 237
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
41.4%
) 20
 
8.4%
( 20
 
8.4%
2 16
 
6.8%
1 16
 
6.8%
, 14
 
5.9%
3 10
 
4.2%
8 10
 
4.2%
7 8
 
3.4%
0 6
 
2.5%
Other values (5) 19
 
8.0%
Hangul
ValueCountFrequency (%)
동 23
 
7.3%
서 20
 
6.4%
구 20
 
6.4%
로 20
 
6.4%
울 20
 
6.4%
중 20
 
6.4%
시 20
 
6.4%
별 20
 
6.4%
특 20
 
6.4%
당 16
 
5.1%
Other values (33) 115
36.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)85.0%
Missing37
Missing (%)64.9%
Infinite0
Infinite (%)0.0%
Mean14172.85
Minimum4552
Maximum100454
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:22:47.592858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4552
5-th percentile4565.3
Q14577.5
median4589.5
Q34599.5
95-th percentile100452.1
Maximum100454
Range95902
Interquartile range (IQR)22

Descriptive statistics

Standard deviation29507.193
Coefficient of variation (CV)2.081952
Kurtosis7.0370314
Mean14172.85
Median Absolute Deviation (MAD)12.5
Skewness2.8879375
Sum283457
Variance8.7067443 × 108
MonotonicityNot monotonic
2024-05-11T14:22:47.776563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
4566 2
 
3.5%
4590 2
 
3.5%
4576 2
 
3.5%
4584 1
 
1.8%
4589 1
 
1.8%
4619 1
 
1.8%
4552 1
 
1.8%
4607 1
 
1.8%
4583 1
 
1.8%
100454 1
 
1.8%
Other values (7) 7
 
12.3%
(Missing) 37
64.9%
ValueCountFrequency (%)
4552 1
1.8%
4566 2
3.5%
4576 2
3.5%
4578 1
1.8%
4579 1
1.8%
4583 1
1.8%
4584 1
1.8%
4589 1
1.8%
4590 2
3.5%
4595 1
1.8%
ValueCountFrequency (%)
100454 1
1.8%
100452 1
1.8%
4619 1
1.8%
4608 1
1.8%
4607 1
1.8%
4597 1
1.8%
4596 1
1.8%
4595 1
1.8%
4590 2
3.5%
4589 1
1.8%

사업장명
Text

Distinct52
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-05-11T14:22:48.162107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.0350877
Min length3

Characters and Unicode

Total characters401
Distinct characters123
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)82.5%

Sample

1st row숭무관
2nd row한화쿵후
3rd row화랑체육관
4th row청죽관
5th row한국요가회
ValueCountFrequency (%)
태권도 5
 
5.7%
태권도장 4
 
4.5%
용인대 3
 
3.4%
체육관 2
 
2.3%
장충체육관 2
 
2.3%
lta 2
 
2.3%
복싱클럽 2
 
2.3%
아리랑 2
 
2.3%
한국체육관 2
 
2.3%
천하무적 2
 
2.3%
Other values (60) 62
70.5%
2024-05-11T14:22:48.789096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
7.7%
관 29
 
7.2%
육 24
 
6.0%
도 24
 
6.0%
체 23
 
5.7%
태 21
 
5.2%
권 21
 
5.2%
한 11
 
2.7%
장 8
 
2.0%
무 7
 
1.7%
Other values (113) 202
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
86.8%
Space Separator 31
 
7.7%
Uppercase Letter 22
 
5.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 29
 
8.3%
육 24
 
6.9%
도 24
 
6.9%
체 23
 
6.6%
태 21
 
6.0%
권 21
 
6.0%
한 11
 
3.2%
장 8
 
2.3%
무 7
 
2.0%
복 6
 
1.7%
Other values (102) 174
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 5
22.7%
A 5
22.7%
M 3
13.6%
V 2
 
9.1%
L 2
 
9.1%
O 1
 
4.5%
R 1
 
4.5%
S 1
 
4.5%
D 1
 
4.5%
F 1
 
4.5%
Space Separator
ValueCountFrequency (%)
31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
86.8%
Common 31
 
7.7%
Latin 22
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 29
 
8.3%
육 24
 
6.9%
도 24
 
6.9%
체 23
 
6.6%
태 21
 
6.0%
권 21
 
6.0%
한 11
 
3.2%
장 8
 
2.3%
무 7
 
2.0%
복 6
 
1.7%
Other values (102) 174
50.0%
Latin
ValueCountFrequency (%)
T 5
22.7%
A 5
22.7%
M 3
13.6%
V 2
 
9.1%
L 2
 
9.1%
O 1
 
4.5%
R 1
 
4.5%
S 1
 
4.5%
D 1
 
4.5%
F 1
 
4.5%
Common
ValueCountFrequency (%)
31
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 347
86.5%
ASCII 53
 
13.2%
Compat Jamo 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
58.5%
T 5
 
9.4%
A 5
 
9.4%
M 3
 
5.7%
V 2
 
3.8%
L 2
 
3.8%
O 1
 
1.9%
R 1
 
1.9%
S 1
 
1.9%
D 1
 
1.9%
Hangul
ValueCountFrequency (%)
관 29
 
8.4%
육 24
 
6.9%
도 24
 
6.9%
체 23
 
6.6%
태 21
 
6.1%
권 21
 
6.1%
한 11
 
3.2%
장 8
 
2.3%
무 7
 
2.0%
복 6
 
1.7%
Other values (101) 173
49.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

최종수정일자
Date

Distinct41
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2003-02-11 17:52:00
Maximum2024-03-26 14:32:02
2024-05-11T14:22:48.996454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:49.206228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
I
46 
U
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 46
80.7%
U 11
 
19.3%

Length

2024-05-11T14:22:49.424465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:49.602342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 46
80.7%
u 11
 
19.3%

데이터갱신일자
Date

Distinct16
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:08:00
2024-05-11T14:22:49.762059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:49.938432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
48 
태권도
5 
권투
 
3
레슬링
 
1

Length

Max length4
Median length4
Mean length3.7894737
Min length2

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 48
84.2%
태권도 5
 
8.8%
권투 3
 
5.3%
레슬링 1
 
1.8%

Length

2024-05-11T14:22:50.165344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:50.345643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 48
84.2%
태권도 5
 
8.8%
권투 3
 
5.3%
레슬링 1
 
1.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)86.0%
Missing7
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean200813.52
Minimum196546.98
Maximum201972.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:22:50.521805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196546.98
5-th percentile198009.72
Q1200750.46
median201098.3
Q3201553.29
95-th percentile201852.93
Maximum201972.72
Range5425.7454
Interquartile range (IQR)802.8331

Descriptive statistics

Standard deviation1204.4913
Coefficient of variation (CV)0.0059980586
Kurtosis5.457898
Mean200813.52
Median Absolute Deviation (MAD)419.13245
Skewness-2.3008066
Sum10040676
Variance1450799.2
MonotonicityNot monotonic
2024-05-11T14:22:50.733051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
200750.455125653 3
 
5.3%
201783.815945902 2
 
3.5%
201852.931048042 2
 
3.5%
200999.416248308 2
 
3.5%
201121.850377708 2
 
3.5%
201651.672204443 2
 
3.5%
200731.129475046 1
 
1.8%
200893.965676785 1
 
1.8%
201100.771582794 1
 
1.8%
200009.852223599 1
 
1.8%
Other values (33) 33
57.9%
(Missing) 7
 
12.3%
ValueCountFrequency (%)
196546.97612053 1
1.8%
196839.497862957 1
1.8%
197180.290658626 1
1.8%
199023.464538991 1
1.8%
199083.229260527 1
1.8%
199587.700169739 1
1.8%
200009.852223599 1
1.8%
200130.485133167 1
1.8%
200428.077024911 1
1.8%
200446.244902305 1
1.8%
ValueCountFrequency (%)
201972.72150882 1
1.8%
201901.862341835 1
1.8%
201852.931048042 2
3.5%
201783.815945902 2
3.5%
201762.765771009 1
1.8%
201726.806519228 1
1.8%
201722.054412826 1
1.8%
201651.672204443 2
3.5%
201641.363400185 1
1.8%
201560.489823964 1
1.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)86.0%
Missing7
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean450883.75
Minimum449638.82
Maximum451861.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:22:50.943445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449638.82
5-th percentile449805.94
Q1450532.8
median450978.99
Q3451361.01
95-th percentile451612.3
Maximum451861.6
Range2222.7721
Interquartile range (IQR)828.21296

Descriptive statistics

Standard deviation563.17122
Coefficient of variation (CV)0.0012490386
Kurtosis-0.3695911
Mean450883.75
Median Absolute Deviation (MAD)416.47339
Skewness-0.54453466
Sum22544187
Variance317161.82
MonotonicityNot monotonic
2024-05-11T14:22:51.135056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
449638.824308081 3
 
5.3%
451612.300460601 2
 
3.5%
450855.26449377 2
 
3.5%
450518.940817637 2
 
3.5%
451441.450973059 2
 
3.5%
450978.98774701 2
 
3.5%
450622.173017614 1
 
1.8%
450010.190882608 1
 
1.8%
450721.049824391 1
 
1.8%
451140.907519006 1
 
1.8%
Other values (33) 33
57.9%
(Missing) 7
 
12.3%
ValueCountFrequency (%)
449638.824308081 3
5.3%
450010.190882608 1
 
1.8%
450014.367000389 1
 
1.8%
450139.377659972 1
 
1.8%
450181.755632626 1
 
1.8%
450218.977052913 1
 
1.8%
450277.600241968 1
 
1.8%
450410.638502556 1
 
1.8%
450499.726296957 1
 
1.8%
450518.940817637 2
3.5%
ValueCountFrequency (%)
451861.596377979 1
1.8%
451675.382346995 1
1.8%
451612.300460601 2
3.5%
451528.702353228 1
1.8%
451491.976739206 1
1.8%
451464.168767791 1
1.8%
451462.316640157 1
1.8%
451442.823563911 1
1.8%
451441.450973059 2
3.5%
451407.30606508 1
1.8%

문화체육업종명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
체육도장업
48 
<NA>
9 

Length

Max length5
Median length5
Mean length4.8421053
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 48
84.2%
<NA> 9
 
15.8%

Length

2024-05-11T14:22:51.334440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:51.496010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 48
84.2%
na 9
 
15.8%

공사립구분명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
사립
48 
<NA>
9 

Length

Max length4
Median length2
Mean length2.3157895
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 48
84.2%
<NA> 9
 
15.8%

Length

2024-05-11T14:22:51.666587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:51.825904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 48
84.2%
na 9
 
15.8%

보험가입여부코드
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
44 
0
13 

Length

Max length4
Median length4
Mean length3.3157895
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> 44
77.2%
0 13
 
22.8%

Length

2024-05-11T14:22:51.986104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:52.131698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
77.2%
0 13
 
22.8%

지도자수
Categorical

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
31 
0
20 
1
6 

Length

Max length4
Median length4
Mean length2.6315789
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 31
54.4%
0 20
35.1%
1 6
 
10.5%

Length

2024-05-11T14:22:52.298007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:52.472553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
54.4%
0 20
35.1%
1 6
 
10.5%

건축물동수
Categorical

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
29 
0
23 
1
4 
2
 
1

Length

Max length4
Median length4
Mean length2.5263158
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 29
50.9%
0 23
40.4%
1 4
 
7.0%
2 1
 
1.8%

Length

2024-05-11T14:22:52.654824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:52.796973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
50.9%
0 23
40.4%
1 4
 
7.0%
2 1
 
1.8%

건축물연면적
Categorical

Distinct6
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
31 
0.0
22 
1236.21
 
1
1010.0
 
1
70.34
 
1

Length

Max length7
Median length4
Mean length3.7368421
Min length3

Unique

Unique4 ?
Unique (%)7.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
<NA> 31
54.4%
0.0 22
38.6%
1236.21 1
 
1.8%
1010.0 1
 
1.8%
70.34 1
 
1.8%
223.0 1
 
1.8%

Length

2024-05-11T14:22:52.944871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:53.136139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
54.4%
0.0 22
38.6%
1236.21 1
 
1.8%
1010.0 1
 
1.8%
70.34 1
 
1.8%
223.0 1
 
1.8%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
56 
0
 
1

Length

Max length4
Median length4
Mean length3.9473684
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 56
98.2%
0 1
 
1.8%

Length

2024-05-11T14:22:53.338703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:53.490085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
98.2%
0 1
 
1.8%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03010000CDFH330102198900000119891216<NA>3폐업3폐업19950401<NA><NA><NA><NA><NA>100858서울특별시 중구 중림동 129-15번지<NA><NA>숭무관2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>197180.290659450574.359292체육도장업사립<NA>000.0<NA><NA><NA>
13010000CDFH330102198900000219891220<NA>3폐업3폐업19970617<NA><NA><NA><NA><NA>100871서울특별시 중구 황학동 2488번지<NA><NA>한화쿵후2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>201972.721509451464.168768체육도장업사립<NA>000.0<NA><NA><NA>
23010000CDFH330102198900000319891229<NA>3폐업3폐업19981211<NA><NA><NA><NA><NA>100834서울특별시 중구 신당동 386-10번지<NA><NA>화랑체육관2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>201044.951267450902.940228체육도장업사립<NA>000.0<NA><NA><NA>
33010000CDFH330102198900000419891229<NA>3폐업3폐업19941206<NA><NA><NA><NA><NA>100879서울특별시 중구 흥인동 25-1번지<NA><NA>청죽관2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>201503.174618451491.976739체육도장업사립<NA>000.0<NA><NA><NA>
43010000CDFH330102199000000119900714<NA>3폐업3폐업19950401<NA><NA><NA><NA><NA>100011서울특별시 중구 충무로1가 51-7번지<NA><NA>한국요가회2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA><NA><NA>체육도장업사립<NA>000.0<NA><NA><NA>
53010000CDFH330102199000000319900725<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>100816서울특별시 중구 신당동 62-95번지<NA><NA>한영체육관2004-08-25 11:58:32I2018-08-31 23:59:59.0<NA>201651.672204450978.987747체육도장업사립0<NA><NA><NA><NA><NA><NA>
63010000CDFH330102199000000419900725<NA>3폐업3폐업20000529<NA><NA><NA><NA><NA>100868서울특별시 중구 황학동 141-0번지<NA><NA>신유경체육관2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>201531.683433451861.596378체육도장업사립<NA>000.0<NA><NA><NA>
73010000CDFH330102199000000519900725<NA>3폐업3폐업19960117<NA><NA><NA><NA><NA>100400서울특별시 중구 쌍림동 235-2번지<NA><NA>장충체육관2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>200428.077025451218.740245체육도장업사립<NA>000.0<NA><NA><NA>
83010000CDFH330102199000000619900818<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>100454서울특별시 중구 신당동 321-27번지서울특별시 중구 다산로28길 40 (신당동)100454VTA 청구수련관2015-01-12 15:30:37I2018-08-31 23:59:59.0<NA>201291.179588450745.848527체육도장업사립<NA><NA><NA><NA><NA><NA><NA>
93010000CDFH330102199000000719900725<NA>3폐업3폐업20171010<NA><NA><NA><NA><NA><NA>서울특별시 중구 황학동 594번지서울특별시 중구 퇴계로87길 29, 지하1, 2층 (황학동)4576흑룡 체육관2017-10-10 13:56:08I2018-08-31 23:59:59.0태권도201783.815946451612.300461체육도장업사립<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
473010000CDFH33010220120000022012-11-28<NA>3폐업3폐업2023-08-31<NA><NA><NA><NA><NA><NA>서울특별시 중구 신당동 844 남산타운서울특별시 중구 다산로 32, 203호 (신당동, 남산타운)4595남산타운 한국태권도장2023-08-31 15:13:25U2022-12-09 00:02:00.0<NA>200750.455126449638.824308<NA><NA><NA><NA><NA><NA><NA><NA><NA>
483010000CDFH330102201300000120130625<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>100450서울특별시 중구 신당동 140-10번지서울특별시 중구 퇴계로 438-1 (신당동)4578박창환 복싱클럽2013-06-25 09:00:33I2018-08-31 23:59:59.0<NA>201726.806519451462.31664체육도장업사립<NA><NA><NA><NA><NA><NA><NA>
493010000CDFH330102201600000120160205<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2235-1282<NA><NA>서울특별시 중구 신당동 52-11번지 3층서울특별시 중구 퇴계로88길 63 (신당동)4584SD 복싱짐2016-02-05 15:02:57I2018-08-31 23:59:59.0권투201641.3634451210.115521체육도장업사립<NA><NA><NA><NA><NA><NA><NA>
503010000CDFH330102201800000120181109<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2236-1009<NA><NA>서울특별시 중구 신당동 52-74번지 대림빌딩서울특별시 중구 퇴계로88다길 23, 대림빌딩 지하1층 (신당동)4583천하무적 태권도2018-11-09 10:06:36I2018-11-11 02:38:42.0태권도201722.054413451122.730678체육도장업사립<NA><NA><NA><NA><NA><NA><NA>
513010000CDFH330102201900000120190115<NA>3폐업3폐업20220620<NA><NA><NA>02-2231-5547<NA><NA>서울특별시 중구 황학동 594서울특별시 중구 퇴계로87길 29, 지하 1층 (황학동)4576VMT 비젼2022-06-20 13:31:00U2021-12-05 22:02:00.0태권도201783.815946451612.300461<NA><NA><NA><NA><NA><NA><NA><NA><NA>
523010000CDFH330102201900000220191218<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2236-1282<NA><NA>서울특별시 중구 신당동 370-24번지 태양빌딩서울특별시 중구 다산로 150, 태양빌딩 지하1층 (신당동)4590한국체육관2019-12-18 14:11:45I2019-12-20 00:23:35.0권투200999.416248450518.940818체육도장업사립<NA>1<NA>223.0<NA><NA><NA>
533010000CDFH330102202100000120211125<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 중구 신당동 377-58서울특별시 중구 동호로 224 (신당동)4607월티즌 도지엄 태권도장2021-12-17 09:22:55U2021-12-19 02:40:00.0태권도200731.129475450622.173018체육도장업사립<NA>000.00<NA><NA>
543010000CDFH330102202200000120220804<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 중구 저동2가 73-4 저동빌딩서울특별시 중구 마른내로 18, 지하2층 (저동2가)4552히트앤핏 을지로2022-08-04 14:24:05I2021-12-08 00:07:00.0권투199023.464539451381.374079<NA><NA><NA><NA><NA><NA><NA><NA><NA>
553010000CDFH33010220230000012023-10-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 중구 묵정동 27-17서울특별시 중구 퇴계로 262-1, 3층 (묵정동)4619오케이 태권도장2023-10-05 18:01:09I2022-10-31 00:07:00.0태권도200009.852224451140.907519<NA><NA><NA><NA><NA><NA><NA><NA><NA>
563010000CDFH33010220240000012024-02-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 중구 신당동 333-203 제일정형외과서울특별시 중구 다산로 172, 제일정형외과 5층 (신당동)4589ART OF MMA2024-02-02 15:00:49I2023-12-02 00:04:00.0레슬링201100.771583450721.049824<NA><NA><NA><NA><NA><NA><NA><NA><NA>