Overview

Dataset statistics

Number of variables34
Number of observations75
Missing cells758
Missing cells (%)29.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.4 KiB
Average record size in memory291.8 B

Variable types

Numeric5
Text6
DateTime4
Unsupported8
Categorical11

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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16134/S/1/datasetView.do

Alerts

문화체육업종명 is highly imbalanced (55.3%)Imbalance
공사립구분명 is highly imbalanced (55.3%)Imbalance
회원모집총인원 is highly imbalanced (82.3%)Imbalance
인허가취소일자 has 75 (100.0%) missing valuesMissing
폐업일자 has 11 (14.7%) missing valuesMissing
휴업시작일자 has 75 (100.0%) missing valuesMissing
휴업종료일자 has 75 (100.0%) missing valuesMissing
재개업일자 has 75 (100.0%) missing valuesMissing
전화번호 has 33 (44.0%) missing valuesMissing
소재지면적 has 75 (100.0%) missing valuesMissing
소재지우편번호 has 14 (18.7%) missing valuesMissing
도로명주소 has 7 (9.3%) missing valuesMissing
도로명우편번호 has 54 (72.0%) missing valuesMissing
업태구분명 has 75 (100.0%) missing valuesMissing
좌표정보(X) has 3 (4.0%) missing valuesMissing
좌표정보(Y) has 3 (4.0%) missing valuesMissing
건축물연면적 has 33 (44.0%) missing valuesMissing
세부업종명 has 75 (100.0%) missing valuesMissing
법인명 has 75 (100.0%) missing valuesMissing
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 32 (42.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:04:02.891334
Analysis finished2024-05-11 06:04:03.756690
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct17
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3113200
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-05-11T15:04:03.835428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3007000
Q13050000
median3100000
Q33150000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)100000

Descriptive statistics

Standard deviation70541.535
Coefficient of variation (CV)0.022658851
Kurtosis-1.0491605
Mean3113200
Median Absolute Deviation (MAD)50000
Skewness0.22934473
Sum2.3349 × 108
Variance4.9761081 × 109
MonotonicityNot monotonic
2024-05-11T15:04:04.011953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3050000 18
24.0%
3150000 13
17.3%
3200000 7
 
9.3%
3090000 7
 
9.3%
3130000 5
 
6.7%
3240000 5
 
6.7%
3000000 4
 
5.3%
3060000 3
 
4.0%
3010000 3
 
4.0%
3080000 2
 
2.7%
Other values (7) 8
10.7%
ValueCountFrequency (%)
3000000 4
 
5.3%
3010000 3
 
4.0%
3050000 18
24.0%
3060000 3
 
4.0%
3080000 2
 
2.7%
3090000 7
 
9.3%
3100000 1
 
1.3%
3110000 1
 
1.3%
3130000 5
 
6.7%
3150000 13
17.3%
ValueCountFrequency (%)
3240000 5
 
6.7%
3230000 1
 
1.3%
3220000 2
 
2.7%
3200000 7
9.3%
3180000 1
 
1.3%
3170000 1
 
1.3%
3160000 1
 
1.3%
3150000 13
17.3%
3130000 5
 
6.7%
3110000 1
 
1.3%

관리번호
Text

Distinct41
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-05-11T15:04:04.315382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1500
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

Unique26 ?
Unique (%)34.7%

Sample

1st rowCDFH3301102006000001
2nd rowCDFH3301102000000001
3rd rowCDFH3301102020000002
4th rowCDFH3301102000000002
5th rowCDFH3301102022000001
ValueCountFrequency (%)
cdfh3301101999000001 7
 
9.3%
cdfh3301102000000001 7
 
9.3%
cdfh3301102001000001 4
 
5.3%
cdfh3301102002000001 4
 
5.3%
cdfh3301102006000001 3
 
4.0%
cdfh3301101998000002 3
 
4.0%
cdfh3301102005000001 3
 
4.0%
cdfh3301102020000001 3
 
4.0%
cdfh3301102000000002 3
 
4.0%
cdfh3301102019000001 2
 
2.7%
Other values (31) 36
48.0%
2024-05-11T15:04:04.825003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 627
41.8%
1 245
 
16.3%
3 155
 
10.3%
2 84
 
5.6%
C 75
 
5.0%
D 75
 
5.0%
F 75
 
5.0%
H 75
 
5.0%
9 62
 
4.1%
8 7
 
0.5%
Other values (4) 20
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1200
80.0%
Uppercase Letter 300
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 627
52.2%
1 245
 
20.4%
3 155
 
12.9%
2 84
 
7.0%
9 62
 
5.2%
8 7
 
0.6%
6 6
 
0.5%
4 6
 
0.5%
5 5
 
0.4%
7 3
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
C 75
25.0%
D 75
25.0%
F 75
25.0%
H 75
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1200
80.0%
Latin 300
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 627
52.2%
1 245
 
20.4%
3 155
 
12.9%
2 84
 
7.0%
9 62
 
5.2%
8 7
 
0.6%
6 6
 
0.5%
4 6
 
0.5%
5 5
 
0.4%
7 3
 
0.2%
Latin
ValueCountFrequency (%)
C 75
25.0%
D 75
25.0%
F 75
25.0%
H 75
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 627
41.8%
1 245
 
16.3%
3 155
 
10.3%
2 84
 
5.6%
C 75
 
5.0%
D 75
 
5.0%
F 75
 
5.0%
H 75
 
5.0%
9 62
 
4.1%
8 7
 
0.5%
Other values (4) 20
 
1.3%

인허가일자
Date

Distinct73
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
Minimum1991-09-25 00:00:00
Maximum2022-10-04 00:00:00
2024-05-11T15:04:05.013186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.200035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
3
61 
1
11 
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 61
81.3%
1 11
 
14.7%
4 3
 
4.0%

Length

2024-05-11T15:04:05.367333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:05.536690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
81.3%
1 11
 
14.7%
4 3
 
4.0%

영업상태명
Categorical

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
폐업
61 
영업/정상
11 
취소/말소/만료/정지/중지
 
3

Length

Max length14
Median length2
Mean length2.92
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
81.3%
영업/정상 11
 
14.7%
취소/말소/만료/정지/중지 3
 
4.0%

Length

2024-05-11T15:04:05.719543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:05.869247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
81.3%
영업/정상 11
 
14.7%
취소/말소/만료/정지/중지 3
 
4.0%

상세영업상태코드
Categorical

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
3
61 
13
11 
35
 
3

Length

Max length2
Median length1
Mean length1.1866667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 61
81.3%
13 11
 
14.7%
35 3
 
4.0%

Length

2024-05-11T15:04:06.026950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:06.180655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
81.3%
13 11
 
14.7%
35 3
 
4.0%

상세영업상태명
Categorical

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
폐업
61 
영업중
11 
직권말소
 
3

Length

Max length4
Median length2
Mean length2.2266667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
81.3%
영업중 11
 
14.7%
직권말소 3
 
4.0%

Length

2024-05-11T15:04:06.364105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:06.550965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
81.3%
영업중 11
 
14.7%
직권말소 3
 
4.0%

폐업일자
Date

MISSING 

Distinct60
Distinct (%)93.8%
Missing11
Missing (%)14.7%
Memory size732.0 B
Minimum1993-01-30 00:00:00
Maximum2023-07-28 00:00:00
2024-05-11T15:04:06.710744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:06.909821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

전화번호
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing33
Missing (%)44.0%
Memory size732.0 B
2024-05-11T15:04:07.206637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.6666667
Min length8

Characters and Unicode

Total characters364
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

Unique42 ?
Unique (%)100.0%

Sample

1st row2285-6560
2nd row02-888-7400
3rd row543-7887
4th row02-858-0436
5th row02-3394-5888
ValueCountFrequency (%)
02-324-2301 1
 
2.4%
2285-6560 1
 
2.4%
978-6266 1
 
2.4%
2246-8204 1
 
2.4%
2215-8858 1
 
2.4%
715-2393 1
 
2.4%
325-0550 1
 
2.4%
336-9226 1
 
2.4%
698-9036 1
 
2.4%
2605-1188 1
 
2.4%
Other values (32) 32
76.2%
2024-05-11T15:04:07.678130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 47
12.9%
2 46
12.6%
6 41
11.3%
8 41
11.3%
0 39
10.7%
9 32
8.8%
3 28
7.7%
4 28
7.7%
5 25
6.9%
1 21
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 317
87.1%
Dash Punctuation 47
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 46
14.5%
6 41
12.9%
8 41
12.9%
0 39
12.3%
9 32
10.1%
3 28
8.8%
4 28
8.8%
5 25
7.9%
1 21
6.6%
7 16
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 47
12.9%
2 46
12.6%
6 41
11.3%
8 41
11.3%
0 39
10.7%
9 32
8.8%
3 28
7.7%
4 28
7.7%
5 25
6.9%
1 21
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 47
12.9%
2 46
12.6%
6 41
11.3%
8 41
11.3%
0 39
10.7%
9 32
8.8%
3 28
7.7%
4 28
7.7%
5 25
6.9%
1 21
5.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

소재지우편번호
Text

MISSING 

Distinct42
Distinct (%)68.9%
Missing14
Missing (%)18.7%
Memory size732.0 B
2024-05-11T15:04:08.002813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0327869
Min length6

Characters and Unicode

Total characters368
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

Unique32 ?
Unique (%)52.5%

Sample

1st row100-851
2nd row132-908
3rd row135887
4th row130867
5th row131848
ValueCountFrequency (%)
130805 6
 
9.8%
157909 5
 
8.2%
130870 3
 
4.9%
157910 3
 
4.9%
130846 2
 
3.3%
110829 2
 
3.3%
151902 2
 
3.3%
131848 2
 
3.3%
132899 2
 
3.3%
157866 2
 
3.3%
Other values (32) 32
52.5%
2024-05-11T15:04:08.443513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 86
23.4%
0 57
15.5%
8 55
14.9%
3 35
9.5%
5 35
9.5%
9 28
 
7.6%
7 23
 
6.2%
2 20
 
5.4%
4 15
 
4.1%
6 12
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 366
99.5%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 86
23.5%
0 57
15.6%
8 55
15.0%
3 35
9.6%
5 35
9.6%
9 28
 
7.7%
7 23
 
6.3%
2 20
 
5.5%
4 15
 
4.1%
6 12
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 368
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 86
23.4%
0 57
15.5%
8 55
14.9%
3 35
9.5%
5 35
9.5%
9 28
 
7.6%
7 23
 
6.2%
2 20
 
5.4%
4 15
 
4.1%
6 12
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 86
23.4%
0 57
15.5%
8 55
14.9%
3 35
9.5%
5 35
9.5%
9 28
 
7.6%
7 23
 
6.2%
2 20
 
5.4%
4 15
 
4.1%
6 12
 
3.3%

지번주소
Text

Distinct73
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-05-11T15:04:08.934156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length24.373333
Min length14

Characters and Unicode

Total characters1828
Distinct characters114
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

Unique71 ?
Unique (%)94.7%

Sample

1st row서울특별시 중구 을지로6가 18-131 7층
2nd row서울특별시 도봉구 창동 333-1 청백빌딩 지하1층
3rd row서울특별시 도봉구 창동 10
4th row서울특별시 도봉구 창동 4
5th row서울특별시 관악구 남현동 1062-15
ValueCountFrequency (%)
서울특별시 75
22.1%
동대문구 18
 
5.3%
화곡동 13
 
3.8%
강서구 13
 
3.8%
답십리동 9
 
2.6%
관악구 7
 
2.1%
도봉구 7
 
2.1%
창동 7
 
2.1%
3층 7
 
2.1%
2층 5
 
1.5%
Other values (135) 179
52.6%
2024-05-11T15:04:09.462515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
333
18.2%
동 100
 
5.5%
서 91
 
5.0%
1 77
 
4.2%
구 77
 
4.2%
울 75
 
4.1%
시 75
 
4.1%
별 75
 
4.1%
특 75
 
4.1%
지 74
 
4.0%
Other values (104) 776
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1070
58.5%
Decimal Number 343
 
18.8%
Space Separator 333
 
18.2%
Dash Punctuation 65
 
3.6%
Close Punctuation 8
 
0.4%
Open Punctuation 8
 
0.4%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 100
 
9.3%
서 91
 
8.5%
구 77
 
7.2%
울 75
 
7.0%
시 75
 
7.0%
별 75
 
7.0%
특 75
 
7.0%
지 74
 
6.9%
번 63
 
5.9%
층 24
 
2.2%
Other values (89) 341
31.9%
Decimal Number
ValueCountFrequency (%)
1 77
22.4%
2 50
14.6%
3 42
12.2%
4 39
11.4%
9 35
10.2%
0 27
 
7.9%
6 26
 
7.6%
5 25
 
7.3%
7 13
 
3.8%
8 9
 
2.6%
Space Separator
ValueCountFrequency (%)
333
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1070
58.5%
Common 757
41.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 100
 
9.3%
서 91
 
8.5%
구 77
 
7.2%
울 75
 
7.0%
시 75
 
7.0%
별 75
 
7.0%
특 75
 
7.0%
지 74
 
6.9%
번 63
 
5.9%
층 24
 
2.2%
Other values (89) 341
31.9%
Common
ValueCountFrequency (%)
333
44.0%
1 77
 
10.2%
- 65
 
8.6%
2 50
 
6.6%
3 42
 
5.5%
4 39
 
5.2%
9 35
 
4.6%
0 27
 
3.6%
6 26
 
3.4%
5 25
 
3.3%
Other values (4) 38
 
5.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1070
58.5%
ASCII 758
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
333
43.9%
1 77
 
10.2%
- 65
 
8.6%
2 50
 
6.6%
3 42
 
5.5%
4 39
 
5.1%
9 35
 
4.6%
0 27
 
3.6%
6 26
 
3.4%
5 25
 
3.3%
Other values (5) 39
 
5.1%
Hangul
ValueCountFrequency (%)
동 100
 
9.3%
서 91
 
8.5%
구 77
 
7.2%
울 75
 
7.0%
시 75
 
7.0%
별 75
 
7.0%
특 75
 
7.0%
지 74
 
6.9%
번 63
 
5.9%
층 24
 
2.2%
Other values (89) 341
31.9%

도로명주소
Text

MISSING 

Distinct67
Distinct (%)98.5%
Missing7
Missing (%)9.3%
Memory size732.0 B
2024-05-11T15:04:09.832622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35.5
Mean length28.367647
Min length22

Characters and Unicode

Total characters1929
Distinct characters137
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

Unique66 ?
Unique (%)97.1%

Sample

1st row서울특별시 도봉구 노해로65길 7-12 (창동,청백빌딩 지하1층)
2nd row서울특별시 도봉구 노해로69길 15-15, 지하2층 1호 (창동)
3rd row서울특별시 도봉구 마들로11가길 13 (창동)
4th row서울특별시 관악구 남현1길 58, 5층 (남현동)
5th row서울특별시 금천구 범안로 1209, 협진식품빌딩 8층 (독산동)
ValueCountFrequency (%)
서울특별시 68
 
18.5%
동대문구 18
 
4.9%
강서구 13
 
3.5%
화곡동 12
 
3.3%
도봉구 7
 
1.9%
관악구 6
 
1.6%
천호대로 5
 
1.4%
창동 5
 
1.4%
답십리동 5
 
1.4%
5 4
 
1.1%
Other values (165) 225
61.1%
2024-05-11T15:04:10.369871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
340
 
17.6%
동 94
 
4.9%
서 89
 
4.6%
( 75
 
3.9%
) 75
 
3.9%
로 72
 
3.7%
구 71
 
3.7%
시 70
 
3.6%
별 68
 
3.5%
특 68
 
3.5%
Other values (127) 907
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1146
59.4%
Space Separator 340
 
17.6%
Decimal Number 252
 
13.1%
Open Punctuation 75
 
3.9%
Close Punctuation 75
 
3.9%
Other Punctuation 34
 
1.8%
Dash Punctuation 6
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 94
 
8.2%
서 89
 
7.8%
로 72
 
6.3%
구 71
 
6.2%
시 70
 
6.1%
별 68
 
5.9%
특 68
 
5.9%
울 68
 
5.9%
대 30
 
2.6%
층 29
 
2.5%
Other values (111) 487
42.5%
Decimal Number
ValueCountFrequency (%)
1 53
21.0%
2 40
15.9%
3 35
13.9%
5 31
12.3%
6 20
 
7.9%
8 19
 
7.5%
4 14
 
5.6%
7 14
 
5.6%
0 13
 
5.2%
9 13
 
5.2%
Space Separator
ValueCountFrequency (%)
340
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Other Punctuation
ValueCountFrequency (%)
, 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1146
59.4%
Common 782
40.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 94
 
8.2%
서 89
 
7.8%
로 72
 
6.3%
구 71
 
6.2%
시 70
 
6.1%
별 68
 
5.9%
특 68
 
5.9%
울 68
 
5.9%
대 30
 
2.6%
층 29
 
2.5%
Other values (111) 487
42.5%
Common
ValueCountFrequency (%)
340
43.5%
( 75
 
9.6%
) 75
 
9.6%
1 53
 
6.8%
2 40
 
5.1%
3 35
 
4.5%
, 34
 
4.3%
5 31
 
4.0%
6 20
 
2.6%
8 19
 
2.4%
Other values (5) 60
 
7.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1146
59.4%
ASCII 783
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
340
43.4%
( 75
 
9.6%
) 75
 
9.6%
1 53
 
6.8%
2 40
 
5.1%
3 35
 
4.5%
, 34
 
4.3%
5 31
 
4.0%
6 20
 
2.6%
8 19
 
2.4%
Other values (6) 61
 
7.8%
Hangul
ValueCountFrequency (%)
동 94
 
8.2%
서 89
 
7.8%
로 72
 
6.3%
구 71
 
6.2%
시 70
 
6.1%
별 68
 
5.9%
특 68
 
5.9%
울 68
 
5.9%
대 30
 
2.6%
층 29
 
2.5%
Other values (111) 487
42.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)71.4%
Missing54
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean16036.762
Minimum1063
Maximum138861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-05-11T15:04:10.510140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1063
5-th percentile1220
Q11414
median2622
Q35355
95-th percentile131858
Maximum138861
Range137798
Interquartile range (IQR)3941

Descriptive statistics

Standard deviation39760.686
Coefficient of variation (CV)2.4793463
Kurtosis7.5203057
Mean16036.762
Median Absolute Deviation (MAD)1208
Skewness2.9582218
Sum336772
Variance1.5809121 × 109
MonotonicityNot monotonic
2024-05-11T15:04:10.651466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1414 4
 
5.3%
2622 4
 
5.3%
8806 1
 
1.3%
8585 1
 
1.3%
8787 1
 
1.3%
3397 1
 
1.3%
1063 1
 
1.3%
2033 1
 
1.3%
1220 1
 
1.3%
3980 1
 
1.3%
Other values (5) 5
 
6.7%
(Missing) 54
72.0%
ValueCountFrequency (%)
1063 1
 
1.3%
1220 1
 
1.3%
1414 4
5.3%
2033 1
 
1.3%
2622 4
5.3%
2645 1
 
1.3%
3397 1
 
1.3%
3980 1
 
1.3%
4038 1
 
1.3%
5355 1
 
1.3%
ValueCountFrequency (%)
138861 1
1.3%
131858 1
1.3%
8806 1
1.3%
8787 1
1.3%
8585 1
1.3%
5355 1
1.3%
4038 1
1.3%
3980 1
1.3%
3397 1
1.3%
2645 1
1.3%

사업장명
Text

Distinct69
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-05-11T15:04:10.930041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.5733333
Min length2

Characters and Unicode

Total characters418
Distinct characters120
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)85.3%

Sample

1st row남남무도장
2nd row신세계무도장
3rd row창동 무도장
4th row동양 무도장
5th row5번출구무도장
ValueCountFrequency (%)
무도장 8
 
9.2%
태양무도장 3
 
3.4%
공단 2
 
2.3%
제일무도장 2
 
2.3%
동양 2
 
2.3%
한강무도학원 2
 
2.3%
무도학원 2
 
2.3%
동양무도장 1
 
1.1%
일번지 1
 
1.1%
장안무도클럽 1
 
1.1%
Other values (63) 63
72.4%
2024-05-11T15:04:11.399508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 64
 
15.3%
무 61
 
14.6%
장 44
 
10.5%
학 20
 
4.8%
원 20
 
4.8%
12
 
2.9%
동 9
 
2.2%
양 7
 
1.7%
남 6
 
1.4%
강 6
 
1.4%
Other values (110) 169
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 395
94.5%
Space Separator 12
 
2.9%
Decimal Number 6
 
1.4%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 64
16.2%
무 61
 
15.4%
장 44
 
11.1%
학 20
 
5.1%
원 20
 
5.1%
동 9
 
2.3%
양 7
 
1.8%
남 6
 
1.5%
강 6
 
1.5%
제 5
 
1.3%
Other values (103) 153
38.7%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
5 1
 
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 395
94.5%
Common 23
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 64
16.2%
무 61
 
15.4%
장 44
 
11.1%
학 20
 
5.1%
원 20
 
5.1%
동 9
 
2.3%
양 7
 
1.8%
남 6
 
1.5%
강 6
 
1.5%
제 5
 
1.3%
Other values (103) 153
38.7%
Common
ValueCountFrequency (%)
12
52.2%
2 3
 
13.0%
0 2
 
8.7%
( 2
 
8.7%
) 2
 
8.7%
5 1
 
4.3%
. 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 395
94.5%
ASCII 23
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 64
16.2%
무 61
 
15.4%
장 44
 
11.1%
학 20
 
5.1%
원 20
 
5.1%
동 9
 
2.3%
양 7
 
1.8%
남 6
 
1.5%
강 6
 
1.5%
제 5
 
1.3%
Other values (103) 153
38.7%
ASCII
ValueCountFrequency (%)
12
52.2%
2 3
 
13.0%
0 2
 
8.7%
( 2
 
8.7%
) 2
 
8.7%
5 1
 
4.3%
. 1
 
4.3%

최종수정일자
Date

Distinct57
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
Minimum2003-02-06 10:45:13
Maximum2023-07-31 13:45:09
2024-05-11T15:04:11.576684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:11.740749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
I
61 
U
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 61
81.3%
U 14
 
18.7%

Length

2024-05-11T15:04:11.890668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:12.005013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 61
81.3%
u 14
 
18.7%

데이터갱신일자
Date

Distinct19
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
Minimum2018-08-31 23:59:59
Maximum2022-12-08 00:02:00
2024-05-11T15:04:12.112855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:12.240471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)86.1%
Missing3
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean199165.23
Minimum185684.89
Maximum212143.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-05-11T15:04:12.415884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185684.89
5-th percentile186327.12
Q1192673.21
median202112.45
Q3204802.88
95-th percentile209286.89
Maximum212143.78
Range26458.884
Interquartile range (IQR)12129.67

Descriptive statistics

Standard deviation7863.9772
Coefficient of variation (CV)0.03948469
Kurtosis-1.036467
Mean199165.23
Median Absolute Deviation (MAD)3903.2979
Skewness-0.50843178
Sum14339896
Variance61842137
MonotonicityNot monotonic
2024-05-11T15:04:12.567188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204802.884455346 3
 
4.0%
206774.874230196 2
 
2.7%
203803.484634588 2
 
2.7%
204814.685158893 2
 
2.7%
186434.920963544 2
 
2.7%
191376.602183978 2
 
2.7%
201882.733697042 2
 
2.7%
205018.506913318 2
 
2.7%
198209.153690741 2
 
2.7%
203757.008715438 1
 
1.3%
Other values (52) 52
69.3%
(Missing) 3
 
4.0%
ValueCountFrequency (%)
185684.894440424 1
1.3%
185863.097607353 1
1.3%
186011.813821434 1
1.3%
186292.945737558 1
1.3%
186355.084186229 1
1.3%
186357.622061194 1
1.3%
186371.657681233 1
1.3%
186392.833320338 1
1.3%
186434.920963544 2
2.7%
186490.193484856 1
1.3%
ValueCountFrequency (%)
212143.778930005 1
1.3%
212111.336830711 1
1.3%
211185.18354777 1
1.3%
211122.336085013 1
1.3%
207785.163886948 1
1.3%
206944.177669765 1
1.3%
206774.874230196 2
2.7%
206162.986259812 1
1.3%
205851.797111459 1
1.3%
205711.263315761 1
1.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)86.1%
Missing3
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean450884.71
Minimum440515.67
Maximum461377.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-05-11T15:04:12.715060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440515.67
5-th percentile441830.25
Q1447512.78
median451311.02
Q3452963.4
95-th percentile461163.31
Maximum461377.82
Range20862.154
Interquartile range (IQR)5450.6241

Descriptive statistics

Standard deviation5416.4966
Coefficient of variation (CV)0.012013041
Kurtosis-0.16416637
Mean450884.71
Median Absolute Deviation (MAD)3256.9722
Skewness0.25220831
Sum32463699
Variance29338436
MonotonicityNot monotonic
2024-05-11T15:04:12.864560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451543.494717439 3
 
4.0%
457011.632629502 2
 
2.7%
453084.117645319 2
 
2.7%
451460.510691169 2
 
2.7%
447405.536849132 2
 
2.7%
442456.748277117 2
 
2.7%
452327.866797265 2
 
2.7%
451331.654449855 2
 
2.7%
441502.542951079 2
 
2.7%
452923.162315716 1
 
1.3%
Other values (52) 52
69.3%
(Missing) 3
 
4.0%
ValueCountFrequency (%)
440515.66903538 1
1.3%
440705.811600324 1
1.3%
441502.542951079 2
2.7%
442098.372819317 1
1.3%
442105.342411703 1
1.3%
442456.748277117 2
2.7%
444585.129994846 1
1.3%
445158.311972517 1
1.3%
445484.879944005 1
1.3%
446086.819081927 1
1.3%
ValueCountFrequency (%)
461377.823143433 1
1.3%
461278.391079956 1
1.3%
461173.522951977 1
1.3%
461163.779496304 1
1.3%
461162.92 1
1.3%
461159.384486912 1
1.3%
461157.210858518 1
1.3%
461040.287040565 1
1.3%
459520.705724947 1
1.3%
457011.632629502 2
2.7%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
무도장업
68 
<NA>
7 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무도장업 68
90.7%
<NA> 7
 
9.3%

Length

2024-05-11T15:04:13.006050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:13.124521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무도장업 68
90.7%
na 7
 
9.3%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
사립
68 
<NA>
7 

Length

Max length4
Median length2
Mean length2.1866667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 68
90.7%
<NA> 7
 
9.3%

Length

2024-05-11T15:04:13.559325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:13.676700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 68
90.7%
na 7
 
9.3%

보험가입여부코드
Categorical

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
56 
0
13 
Y
6 

Length

Max length4
Median length4
Mean length3.24
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> 56
74.7%
0 13
 
17.3%
Y 6
 
8.0%

Length

2024-05-11T15:04:13.800470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:13.920514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
74.7%
0 13
 
17.3%
y 6
 
8.0%

지도자수
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
46 
0
29 

Length

Max length4
Median length4
Mean length2.84
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> 46
61.3%
0 29
38.7%

Length

2024-05-11T15:04:14.066778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:14.189010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
61.3%
0 29
38.7%

건축물동수
Categorical

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
38 
0
34 
1
 
3

Length

Max length4
Median length4
Mean length2.52
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> 38
50.7%
0 34
45.3%
1 3
 
4.0%

Length

2024-05-11T15:04:14.335815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:14.484470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
50.7%
0 34
45.3%
1 3
 
4.0%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)26.2%
Missing33
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean1222.2824
Minimum0
Maximum17882.76
Zeros32
Zeros (%)42.7%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-05-11T15:04:14.646833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4726.681
Maximum17882.76
Range17882.76
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3443.252
Coefficient of variation (CV)2.8170675
Kurtosis15.521637
Mean1222.2824
Median Absolute Deviation (MAD)0
Skewness3.8143409
Sum51335.86
Variance11855984
MonotonicityNot monotonic
2024-05-11T15:04:14.846568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 32
42.7%
4729.74 1
 
1.3%
17882.76 1
 
1.3%
366.92 1
 
1.3%
2589.43 1
 
1.3%
4668.56 1
 
1.3%
2695.72 1
 
1.3%
2837.88 1
 
1.3%
2720.0 1
 
1.3%
12456.89 1
 
1.3%
(Missing) 33
44.0%
ValueCountFrequency (%)
0.0 32
42.7%
366.92 1
 
1.3%
387.96 1
 
1.3%
2589.43 1
 
1.3%
2695.72 1
 
1.3%
2720.0 1
 
1.3%
2837.88 1
 
1.3%
4668.56 1
 
1.3%
4729.74 1
 
1.3%
12456.89 1
 
1.3%
ValueCountFrequency (%)
17882.76 1
1.3%
12456.89 1
1.3%
4729.74 1
1.3%
4668.56 1
1.3%
2837.88 1
1.3%
2720.0 1
1.3%
2695.72 1
1.3%
2589.43 1
1.3%
387.96 1
1.3%
366.92 1
1.3%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
73 
0
 
2

Length

Max length4
Median length4
Mean length3.92
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> 73
97.3%
0 2
 
2.7%

Length

2024-05-11T15:04:15.001146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:15.141973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 73
97.3%
0 2
 
2.7%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03010000CDFH33011020060000012006-08-25<NA>4취소/말소/만료/정지/중지35직권말소2023-07-28<NA><NA><NA>2285-6560<NA>100-851서울특별시 중구 을지로6가 18-131 7층<NA><NA>남남무도장2023-07-31 13:45:09U2022-12-08 00:02:00.0<NA>200492.764852451583.836506<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13090000CDFH33011020000000012000-01-07<NA>3폐업3폐업2011-01-11<NA><NA><NA><NA><NA>132-908서울특별시 도봉구 창동 333-1 청백빌딩 지하1층서울특별시 도봉구 노해로65길 7-12 (창동,청백빌딩 지하1층)<NA>신세계무도장2023-06-22 18:04:38U2022-12-05 22:04:00.0<NA>203974.826952461040.287041<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23090000CDFH33011020200000022020-05-21<NA>3폐업3폐업2023-05-30<NA><NA><NA><NA><NA><NA>서울특별시 도봉구 창동 10서울특별시 도봉구 노해로69길 15-15, 지하2층 1호 (창동)1414창동 무도장2023-05-30 18:18:11U2022-12-06 00:01:00.0<NA>204335.057042461157.210859<NA><NA><NA><NA><NA><NA><NA><NA><NA>
33090000CDFH33011020000000022000-07-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 도봉구 창동 4서울특별시 도봉구 마들로11가길 13 (창동)1414동양 무도장2023-02-22 14:13:35U2022-12-01 22:04:00.0<NA>204272.935757461173.522952<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43200000CDFH330110202200000120221004<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 남현동 1062-15서울특별시 관악구 남현1길 58, 5층 (남현동)88065번출구무도장2022-10-04 14:13:37I2021-10-31 00:06:00.0<NA>198209.153691441502.542951<NA><NA><NA><NA><NA><NA><NA><NA><NA>
53170000CDFH330110202000000120200714<NA>3폐업3폐업20220921<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 293-5 협진식품빌딩서울특별시 금천구 범안로 1209, 협진식품빌딩 8층 (독산동)8585청화2022-09-21 16:49:36U2021-12-08 22:03:00.0<NA>190771.59559440515.669035<NA><NA><NA><NA><NA><NA><NA><NA><NA>
63200000CDFH330110202000000120200610<NA>3폐업3폐업20220915<NA><NA><NA>02-888-7400<NA><NA>서울특별시 관악구 봉천동 869-12서울특별시 관악구 남부순환로 1812-2, 지하2층 (봉천동)8787스타무도장2022-09-15 17:04:50U2021-12-08 23:07:00.0<NA>195647.366394442105.342412<NA><NA><NA><NA><NA><NA><NA><NA><NA>
73050000CDFH330110202100000120211109<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 961-9서울특별시 동대문구 고미술로 99, 지하층 4,41호 (답십리동)2622제니아 무도장2021-11-09 12:14:30I2021-11-11 00:22:54.0<NA>205018.506913451331.65445무도장업사립<NA>000.00<NA><NA>
83110000CDFH330110202100000120210217<NA>3폐업3폐업20210901<NA><NA><NA><NA><NA><NA>서울특별시 은평구 대조동 14-20 3층서울특별시 은평구 불광로 28, 3층 (대조동)3397궁전 무도장2021-09-02 09:25:01U2021-09-04 02:40:00.0<NA>193671.151836456443.282712무도장업사립<NA>004729.740<NA><NA>
93220000CDFH330110199900000119991204<NA>3폐업3폐업20210311<NA><NA><NA>543-7887<NA>135887서울특별시 강남구 신사동 502-12서울특별시 강남구 강남대로 620 (신사동)<NA>강남무도장(2)2021-03-11 19:36:58U2021-03-13 02:40:00.0<NA>201666.745077446101.563566무도장업사립<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
653150000CDFH330110199900000219991215<NA>3폐업3폐업20021111<NA><NA><NA>659-7896<NA>157866서울특별시 강서구 화곡동 24-39번지서울특별시 강서구 화곡로44길 2 (화곡동)<NA>명성무도학원2003-04-18 11:50:37I2018-08-31 23:59:59.0<NA>186392.83332449547.522251무도장업사립<NA>000.0<NA><NA><NA>
663150000CDFH330110199200000119921119<NA>3폐업3폐업19941201<NA><NA><NA>691-7937<NA>157909서울특별시 강서구 화곡동 905-9번지서울특별시 강서구 강서로5나길 32 (화곡동)<NA>강서무도학원2003-04-18 11:50:37I2018-08-31 23:59:59.0<NA>186355.084186447404.18978무도장업사립<NA>000.0<NA><NA><NA>
673240000CDFH330110200100000120010425<NA>3폐업3폐업20020517<NA><NA><NA>485-2994<NA>134822서울특별시 강동구 둔촌동 453-1번지<NA><NA>성심무도장2003-04-11 10:24:39I2018-08-31 23:59:59.0<NA><NA><NA>무도장업사립<NA>000.0<NA><NA><NA>
683100000CDFH330110199900000119990312<NA>3폐업3폐업20000831<NA><NA><NA><NA><NA>139942서울특별시 노원구 상계동 712번지 남성빌딩 3층서울특별시 노원구 동일로 1413 (상계동,남성빌딩 3층)<NA>미도무도장2003-02-21 10:29:10I2018-08-31 23:59:59.0<NA>205226.636813461377.823143무도장업사립<NA>000.0<NA><NA><NA>
693010000CDFH330110200000000120001013<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>100440서울특별시 중구 황학동 2941-0번지<NA><NA>태양2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA><NA><NA>무도장업사립<NA>000.0<NA><NA><NA>
703010000CDFH330110200000000220001013<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>100868서울특별시 중구 황학동 73-1번지 미도빌딩9층<NA><NA>미도무도학원2003-02-11 17:52:00I2018-08-31 23:59:59.0<NA>201637.855135451945.755421무도장업사립<NA>000.0<NA><NA><NA>
713000000CDFH330110200000000120000110<NA>3폐업3폐업20000228<NA><NA><NA><NA><NA>110840서울특별시 종로구 창신동 292-0번지서울특별시 종로구 종로 335 (창신동)<NA>동대문무도장2003-02-07 09:11:15I2018-08-31 23:59:59.0<NA>201238.696068452317.865597무도장업사립<NA>000.0<NA><NA><NA>
723200000CDFH330110199900000119990212<NA>3폐업3폐업19990915<NA><NA><NA><NA><NA>151856서울특별시 관악구 신림동 144-10번지<NA><NA>한일무도장2003-02-06 10:45:13I2018-08-31 23:59:59.0<NA>195316.77642440705.8116무도장업사립<NA>000.0<NA><NA><NA>
733200000CDFH330110199800000119980304<NA>3폐업3폐업20000906<NA><NA><NA><NA><NA>151800서울특별시 관악구 남현동 1062-15번지서울특별시 관악구 남현1길 58 (남현동)<NA>남태령2003-02-06 10:45:13I2018-08-31 23:59:59.0<NA>198209.153691441502.542951무도장업사립<NA>000.0<NA><NA><NA>
743200000CDFH330110199800000219981017<NA>3폐업3폐업20000828<NA><NA><NA><NA><NA>151902서울특별시 관악구 신림동 1643번지서울특별시 관악구 시흥대로 578 (신림동)<NA>공단2003-02-06 10:45:13I2018-08-31 23:59:59.0<NA>191376.602184442456.748277무도장업사립<NA>000.0<NA><NA><NA>