Overview

Dataset statistics

Number of variables34
Number of observations91
Missing cells642
Missing cells (%)20.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.8 KiB
Average record size in memory290.5 B

Variable types

Categorical13
Text6
DateTime6
Unsupported3
Numeric6

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),의료유사업종별명,종업원수,자격증소유자수,보조종업원수,시설관리자수,기타종업원수,병상수,욕실면적,총면적
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-16380/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
자격증소유자수 is highly imbalanced (74.0%)Imbalance
보조종업원수 is highly imbalanced (74.0%)Imbalance
시설관리자수 is highly imbalanced (74.0%)Imbalance
기타종업원수 is highly imbalanced (74.0%)Imbalance
욕실면적 is highly imbalanced (75.2%)Imbalance
인허가취소일자 has 91 (100.0%) missing valuesMissing
폐업일자 has 30 (33.0%) missing valuesMissing
휴업시작일자 has 79 (86.8%) missing valuesMissing
휴업종료일자 has 79 (86.8%) missing valuesMissing
재개업일자 has 91 (100.0%) missing valuesMissing
전화번호 has 8 (8.8%) missing valuesMissing
소재지면적 has 91 (100.0%) missing valuesMissing
소재지우편번호 has 40 (44.0%) missing valuesMissing
도로명주소 has 3 (3.3%) missing valuesMissing
도로명우편번호 has 35 (38.5%) missing valuesMissing
좌표정보(X) has 1 (1.1%) missing valuesMissing
좌표정보(Y) has 1 (1.1%) missing valuesMissing
종업원수 has 27 (29.7%) missing valuesMissing
병상수 has 41 (45.1%) missing valuesMissing
총면적 has 25 (27.5%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
지번주소 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
병상수 has 1 (1.1%) zerosZeros

Reproduction

Analysis started2024-05-11 05:56:04.489849
Analysis finished2024-05-11 05:56:05.361869
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
3220000
91 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 91
100.0%

Length

2024-05-11T14:56:05.504855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:05.679327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 91
100.0%

관리번호
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-05-11T14:56:06.012658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2275
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

Unique91 ?
Unique (%)100.0%

Sample

1st rowPHMB419843220033042400001
2nd rowPHMB419893220033042400001
3rd rowPHMB419903220033042400001
4th rowPHMB419913220033042400001
5th rowPHMB419933220033042400001
ValueCountFrequency (%)
phmb419843220033042400001 1
 
1.1%
phmb420063220033042400008 1
 
1.1%
phmb420113220033042400004 1
 
1.1%
phmb420113220033042400003 1
 
1.1%
phmb420113220033042400002 1
 
1.1%
phmb420113220033042400001 1
 
1.1%
phmb420103220033042400003 1
 
1.1%
phmb420103220033042400002 1
 
1.1%
phmb420103220033042400001 1
 
1.1%
phmb420093220033042400004 1
 
1.1%
Other values (81) 81
89.0%
2024-05-11T14:56:06.561670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 778
34.2%
2 379
16.7%
4 298
 
13.1%
3 295
 
13.0%
P 91
 
4.0%
H 91
 
4.0%
M 91
 
4.0%
B 91
 
4.0%
1 72
 
3.2%
9 23
 
1.0%
Other values (4) 66
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1911
84.0%
Uppercase Letter 364
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 778
40.7%
2 379
19.8%
4 298
 
15.6%
3 295
 
15.4%
1 72
 
3.8%
9 23
 
1.2%
5 21
 
1.1%
6 18
 
0.9%
7 17
 
0.9%
8 10
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
P 91
25.0%
H 91
25.0%
M 91
25.0%
B 91
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1911
84.0%
Latin 364
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 778
40.7%
2 379
19.8%
4 298
 
15.6%
3 295
 
15.4%
1 72
 
3.8%
9 23
 
1.2%
5 21
 
1.1%
6 18
 
0.9%
7 17
 
0.9%
8 10
 
0.5%
Latin
ValueCountFrequency (%)
P 91
25.0%
H 91
25.0%
M 91
25.0%
B 91
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 778
34.2%
2 379
16.7%
4 298
 
13.1%
3 295
 
13.0%
P 91
 
4.0%
H 91
 
4.0%
M 91
 
4.0%
B 91
 
4.0%
1 72
 
3.2%
9 23
 
1.0%
Other values (4) 66
 
2.9%

인허가일자
Date

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
Minimum1984-06-26 00:00:00
Maximum2024-01-23 00:00:00
2024-05-11T14:56:06.835312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:07.112977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
3
63 
1
26 
2
 
2

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 (%)
3 63
69.2%
1 26
28.6%
2 2
 
2.2%

Length

2024-05-11T14:56:07.315719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:07.488401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 63
69.2%
1 26
28.6%
2 2
 
2.2%

영업상태명
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
폐업
63 
영업/정상
26 
휴업
 
2

Length

Max length5
Median length2
Mean length2.8571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 63
69.2%
영업/정상 26
28.6%
휴업 2
 
2.2%

Length

2024-05-11T14:56:07.652415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:07.788633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 63
69.2%
영업/정상 26
28.6%
휴업 2
 
2.2%

상세영업상태코드
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
3
63 
13
26 
2
 
2

Length

Max length2
Median length1
Mean length1.2857143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 63
69.2%
13 26
28.6%
2 2
 
2.2%

Length

2024-05-11T14:56:07.964024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:08.129828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 63
69.2%
13 26
28.6%
2 2
 
2.2%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
폐업
63 
영업중
26 
휴업
 
2

Length

Max length3
Median length2
Mean length2.2857143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 63
69.2%
영업중 26
28.6%
휴업 2
 
2.2%

Length

2024-05-11T14:56:08.320984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:08.499402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 63
69.2%
영업중 26
28.6%
휴업 2
 
2.2%

폐업일자
Date

MISSING 

Distinct61
Distinct (%)100.0%
Missing30
Missing (%)33.0%
Memory size860.0 B
Minimum2009-04-28 00:00:00
Maximum2024-03-29 00:00:00
2024-05-11T14:56:08.708276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:08.949241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct12
Distinct (%)100.0%
Missing79
Missing (%)86.8%
Memory size860.0 B
Minimum2011-12-08 00:00:00
Maximum2024-01-01 00:00:00
2024-05-11T14:56:09.175322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:09.372701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

휴업종료일자
Date

MISSING 

Distinct12
Distinct (%)100.0%
Missing79
Missing (%)86.8%
Memory size860.0 B
Minimum2012-06-30 00:00:00
Maximum2024-09-20 00:00:00
2024-05-11T14:56:09.546299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:09.753314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

전화번호
Text

MISSING 

Distinct80
Distinct (%)96.4%
Missing8
Missing (%)8.8%
Memory size860.0 B
2024-05-11T14:56:10.230324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.7710843
Min length8

Characters and Unicode

Total characters728
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)92.8%

Sample

1st row546-3356
2nd row02-545-8574
3rd row562-3040
4th row554-3070
5th row548-4391
ValueCountFrequency (%)
549-5888 2
 
2.4%
539-4323 2
 
2.4%
562-9922 2
 
2.4%
02-459-7575 1
 
1.2%
568-7582 1
 
1.2%
564-5644 1
 
1.2%
543-8575 1
 
1.2%
554-8575 1
 
1.2%
508-0025 1
 
1.2%
02-538-1491 1
 
1.2%
Other values (70) 70
84.3%
2024-05-11T14:56:11.111252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 156
21.4%
- 100
13.7%
6 62
 
8.5%
0 62
 
8.5%
4 60
 
8.2%
1 60
 
8.2%
2 55
 
7.6%
3 50
 
6.9%
8 45
 
6.2%
7 39
 
5.4%
Other values (3) 39
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 625
85.9%
Dash Punctuation 100
 
13.7%
Math Symbol 2
 
0.3%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 156
25.0%
6 62
 
9.9%
0 62
 
9.9%
4 60
 
9.6%
1 60
 
9.6%
2 55
 
8.8%
3 50
 
8.0%
8 45
 
7.2%
7 39
 
6.2%
9 36
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 728
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 156
21.4%
- 100
13.7%
6 62
 
8.5%
0 62
 
8.5%
4 60
 
8.2%
1 60
 
8.2%
2 55
 
7.6%
3 50
 
6.9%
8 45
 
6.2%
7 39
 
5.4%
Other values (3) 39
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 156
21.4%
- 100
13.7%
6 62
 
8.5%
0 62
 
8.5%
4 60
 
8.2%
1 60
 
8.2%
2 55
 
7.6%
3 50
 
6.9%
8 45
 
6.2%
7 39
 
5.4%
Other values (3) 39
 
5.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

소재지우편번호
Text

MISSING 

Distinct34
Distinct (%)66.7%
Missing40
Missing (%)44.0%
Memory size860.0 B
2024-05-11T14:56:11.465910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0784314
Min length6

Characters and Unicode

Total characters310
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

Unique28 ?
Unique (%)54.9%

Sample

1st row135870
2nd row135-819
3rd row135915
4th row135080
5th row135892
ValueCountFrequency (%)
135080 8
 
15.7%
135090 6
 
11.8%
135915 3
 
5.9%
135945 2
 
3.9%
135010 2
 
3.9%
135092 2
 
3.9%
135502 1
 
2.0%
135-924 1
 
2.0%
135920 1
 
2.0%
135280 1
 
2.0%
Other values (24) 24
47.1%
2024-05-11T14:56:12.019892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 63
20.3%
5 61
19.7%
3 58
18.7%
0 42
13.5%
8 26
8.4%
9 26
8.4%
2 11
 
3.5%
4 8
 
2.6%
7 7
 
2.3%
- 4
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306
98.7%
Dash Punctuation 4
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 63
20.6%
5 61
19.9%
3 58
19.0%
0 42
13.7%
8 26
8.5%
9 26
8.5%
2 11
 
3.6%
4 8
 
2.6%
7 7
 
2.3%
6 4
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 63
20.3%
5 61
19.7%
3 58
18.7%
0 42
13.5%
8 26
8.4%
9 26
8.4%
2 11
 
3.5%
4 8
 
2.6%
7 7
 
2.3%
- 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 63
20.3%
5 61
19.7%
3 58
18.7%
0 42
13.5%
8 26
8.4%
9 26
8.4%
2 11
 
3.5%
4 8
 
2.6%
7 7
 
2.3%
- 4
 
1.3%

지번주소
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-05-11T14:56:12.618045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length25.494505
Min length18

Characters and Unicode

Total characters2320
Distinct characters83
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)100.0%

Sample

1st row서울특별시 강남구 삼성동 65번지 5호
2nd row서울특별시 강남구 논현2동 97번지 16호
3rd row서울특별시 강남구 역삼동 678번지 29호
4th row서울특별시 강남구 역삼동 688번지 3호
5th row서울특별시 강남구 신사동 586번지
ValueCountFrequency (%)
서울특별시 90
 
17.9%
강남구 90
 
17.9%
역삼동 30
 
6.0%
삼성동 13
 
2.6%
논현동 10
 
2.0%
143번지 8
 
1.6%
대치동 7
 
1.4%
16호 6
 
1.2%
신사동 6
 
1.2%
11호 6
 
1.2%
Other values (152) 236
47.0%
2024-05-11T14:56:13.532243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
413
 
17.8%
1 106
 
4.6%
호 94
 
4.1%
지 93
 
4.0%
동 92
 
4.0%
구 91
 
3.9%
서 90
 
3.9%
울 90
 
3.9%
남 90
 
3.9%
강 90
 
3.9%
Other values (73) 1071
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1374
59.2%
Decimal Number 505
 
21.8%
Space Separator 413
 
17.8%
Other Punctuation 12
 
0.5%
Math Symbol 8
 
0.3%
Dash Punctuation 4
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 94
 
6.8%
지 93
 
6.8%
동 92
 
6.7%
구 91
 
6.6%
서 90
 
6.6%
울 90
 
6.6%
남 90
 
6.6%
강 90
 
6.6%
시 90
 
6.6%
별 90
 
6.6%
Other values (57) 464
33.8%
Decimal Number
ValueCountFrequency (%)
1 106
21.0%
2 80
15.8%
6 59
11.7%
3 48
9.5%
8 43
8.5%
7 42
 
8.3%
4 37
 
7.3%
5 32
 
6.3%
0 32
 
6.3%
9 26
 
5.1%
Space Separator
ValueCountFrequency (%)
413
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1374
59.2%
Common 946
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 94
 
6.8%
지 93
 
6.8%
동 92
 
6.7%
구 91
 
6.6%
서 90
 
6.6%
울 90
 
6.6%
남 90
 
6.6%
강 90
 
6.6%
시 90
 
6.6%
별 90
 
6.6%
Other values (57) 464
33.8%
Common
ValueCountFrequency (%)
413
43.7%
1 106
 
11.2%
2 80
 
8.5%
6 59
 
6.2%
3 48
 
5.1%
8 43
 
4.5%
7 42
 
4.4%
4 37
 
3.9%
5 32
 
3.4%
0 32
 
3.4%
Other values (6) 54
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1374
59.2%
ASCII 946
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
413
43.7%
1 106
 
11.2%
2 80
 
8.5%
6 59
 
6.2%
3 48
 
5.1%
8 43
 
4.5%
7 42
 
4.4%
4 37
 
3.9%
5 32
 
3.4%
0 32
 
3.4%
Other values (6) 54
 
5.7%
Hangul
ValueCountFrequency (%)
호 94
 
6.8%
지 93
 
6.8%
동 92
 
6.7%
구 91
 
6.6%
서 90
 
6.6%
울 90
 
6.6%
남 90
 
6.6%
강 90
 
6.6%
시 90
 
6.6%
별 90
 
6.6%
Other values (57) 464
33.8%

도로명주소
Text

MISSING 

Distinct86
Distinct (%)97.7%
Missing3
Missing (%)3.3%
Memory size860.0 B
2024-05-11T14:56:14.002752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length30.454545
Min length23

Characters and Unicode

Total characters2680
Distinct characters100
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)95.5%

Sample

1st row서울특별시 강남구 삼성로 634 (삼성동)
2nd row서울특별시 강남구 언주로148길 13 (논현동)
3rd row서울특별시 강남구 테헤란로33길 5 (역삼동)
4th row서울특별시 강남구 언주로 554 (역삼동)
5th row서울특별시 강남구 논현로 819 (신사동)
ValueCountFrequency (%)
서울특별시 88
 
17.1%
강남구 88
 
17.1%
역삼동 35
 
6.8%
삼성동 14
 
2.7%
논현동 11
 
2.1%
대치동 9
 
1.8%
7 6
 
1.2%
테헤란로77길 6
 
1.2%
2층 6
 
1.2%
개포동 5
 
1.0%
Other values (173) 246
47.9%
2024-05-11T14:56:14.580487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
426
 
15.9%
동 99
 
3.7%
1 96
 
3.6%
구 93
 
3.5%
남 92
 
3.4%
강 91
 
3.4%
( 89
 
3.3%
) 89
 
3.3%
로 88
 
3.3%
울 88
 
3.3%
Other values (90) 1429
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1520
56.7%
Decimal Number 455
 
17.0%
Space Separator 426
 
15.9%
Open Punctuation 89
 
3.3%
Close Punctuation 89
 
3.3%
Other Punctuation 72
 
2.7%
Dash Punctuation 17
 
0.6%
Math Symbol 12
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 99
 
6.5%
구 93
 
6.1%
남 92
 
6.1%
강 91
 
6.0%
로 88
 
5.8%
울 88
 
5.8%
서 88
 
5.8%
특 88
 
5.8%
시 88
 
5.8%
별 88
 
5.8%
Other values (74) 617
40.6%
Decimal Number
ValueCountFrequency (%)
1 96
21.1%
2 70
15.4%
3 67
14.7%
0 47
10.3%
8 33
 
7.3%
5 33
 
7.3%
7 31
 
6.8%
4 30
 
6.6%
6 27
 
5.9%
9 21
 
4.6%
Space Separator
ValueCountFrequency (%)
426
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1520
56.7%
Common 1160
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 99
 
6.5%
구 93
 
6.1%
남 92
 
6.1%
강 91
 
6.0%
로 88
 
5.8%
울 88
 
5.8%
서 88
 
5.8%
특 88
 
5.8%
시 88
 
5.8%
별 88
 
5.8%
Other values (74) 617
40.6%
Common
ValueCountFrequency (%)
426
36.7%
1 96
 
8.3%
( 89
 
7.7%
) 89
 
7.7%
, 72
 
6.2%
2 70
 
6.0%
3 67
 
5.8%
0 47
 
4.1%
8 33
 
2.8%
5 33
 
2.8%
Other values (6) 138
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1520
56.7%
ASCII 1160
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
426
36.7%
1 96
 
8.3%
( 89
 
7.7%
) 89
 
7.7%
, 72
 
6.2%
2 70
 
6.0%
3 67
 
5.8%
0 47
 
4.1%
8 33
 
2.8%
5 33
 
2.8%
Other values (6) 138
 
11.9%
Hangul
ValueCountFrequency (%)
동 99
 
6.5%
구 93
 
6.1%
남 92
 
6.1%
강 91
 
6.0%
로 88
 
5.8%
울 88
 
5.8%
서 88
 
5.8%
특 88
 
5.8%
시 88
 
5.8%
별 88
 
5.8%
Other values (74) 617
40.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)82.1%
Missing35
Missing (%)38.5%
Infinite0
Infinite (%)0.0%
Mean17769.089
Minimum6023
Maximum135920
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T14:56:14.835164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6023
5-th percentile6047.25
Q16139.75
median6199.5
Q36260.75
95-th percentile135897.75
Maximum135920
Range129897
Interquartile range (IQR)121

Descriptive statistics

Standard deviation37324.327
Coefficient of variation (CV)2.10052
Kurtosis7.0139964
Mean17769.089
Median Absolute Deviation (MAD)61
Skewness2.9605007
Sum995069
Variance1.3931054 × 109
MonotonicityNot monotonic
2024-05-11T14:56:15.091441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
6329 3
 
3.3%
6159 3
 
3.3%
6335 2
 
2.2%
6343 2
 
2.2%
6141 2
 
2.2%
6023 2
 
2.2%
6110 2
 
2.2%
6211 2
 
2.2%
6030 1
 
1.1%
6236 1
 
1.1%
Other values (36) 36
39.6%
(Missing) 35
38.5%
ValueCountFrequency (%)
6023 2
2.2%
6030 1
1.1%
6053 1
1.1%
6054 1
1.1%
6060 1
1.1%
6084 1
1.1%
6099 1
1.1%
6101 1
1.1%
6104 1
1.1%
6110 2
2.2%
ValueCountFrequency (%)
135920 1
 
1.1%
135917 1
 
1.1%
135915 1
 
1.1%
135892 1
 
1.1%
135876 1
 
1.1%
6343 2
2.2%
6339 1
 
1.1%
6335 2
2.2%
6329 3
3.3%
6284 1
 
1.1%

사업장명
Text

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-05-11T14:56:15.467951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.967033
Min length1

Characters and Unicode

Total characters634
Distinct characters145
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

Unique83 ?
Unique (%)91.2%

Sample

1st row수안보안마시술소
2nd row보그안마시술소
3rd row마카오
4th row도깨비안마시술소
5th row리얼안마시술소
ValueCountFrequency (%)
수안보안마시술소 2
 
2.2%
드림안마시술소 2
 
2.2%
퀸안마시술소 2
 
2.2%
혜무안마시술소 2
 
2.2%
꼭지안마시술소 1
 
1.1%
강남건강안마센터 1
 
1.1%
어머니약손안마원 1
 
1.1%
평강안마원 1
 
1.1%
자전거안마시술소 1
 
1.1%
마이다스안마원 1
 
1.1%
Other values (79) 79
84.9%
2024-05-11T14:56:16.415004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 86
 
13.6%
안 86
 
13.6%
술 54
 
8.5%
시 53
 
8.4%
소 53
 
8.4%
원 27
 
4.3%
지 11
 
1.7%
스 10
 
1.6%
강 9
 
1.4%
이 8
 
1.3%
Other values (135) 237
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
99.4%
Space Separator 2
 
0.3%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 86
 
13.7%
안 86
 
13.7%
술 54
 
8.6%
시 53
 
8.4%
소 53
 
8.4%
원 27
 
4.3%
지 11
 
1.7%
스 10
 
1.6%
강 9
 
1.4%
이 8
 
1.3%
Other values (132) 233
37.0%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
5 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
99.4%
Common 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 86
 
13.7%
안 86
 
13.7%
술 54
 
8.6%
시 53
 
8.4%
소 53
 
8.4%
원 27
 
4.3%
지 11
 
1.7%
스 10
 
1.6%
강 9
 
1.4%
이 8
 
1.3%
Other values (132) 233
37.0%
Common
ValueCountFrequency (%)
2
50.0%
6 1
25.0%
5 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
99.4%
ASCII 4
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 86
 
13.7%
안 86
 
13.7%
술 54
 
8.6%
시 53
 
8.4%
소 53
 
8.4%
원 27
 
4.3%
지 11
 
1.7%
스 10
 
1.6%
강 9
 
1.4%
이 8
 
1.3%
Other values (132) 233
37.0%
ASCII
ValueCountFrequency (%)
2
50.0%
6 1
25.0%
5 1
25.0%

최종수정일자
Date

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
Minimum2009-04-28 14:54:20
Maximum2024-05-03 07:55:16
2024-05-11T14:56:16.623451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:16.858629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
I
53 
U
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 53
58.2%
U 38
41.8%

Length

2024-05-11T14:56:17.082113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:17.274043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 53
58.2%
u 38
41.8%

데이터갱신일자
Date

Distinct40
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T14:56:17.446993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:17.650694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

업태구분명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
안마시술소
60 
안마원
31 

Length

Max length5
Median length5
Mean length4.3186813
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마시술소 60
65.9%
안마원 31
34.1%

Length

2024-05-11T14:56:17.885645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:18.069484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마시술소 60
65.9%
안마원 31
34.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)94.4%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean203892.66
Minimum201948.52
Maximum207432.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T14:56:18.264214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201948.52
5-th percentile202248.74
Q1203024.99
median203557.2
Q3204638.82
95-th percentile206309.14
Maximum207432.49
Range5483.9794
Interquartile range (IQR)1613.8368

Descriptive statistics

Standard deviation1235.4277
Coefficient of variation (CV)0.0060592063
Kurtosis0.73510057
Mean203892.66
Median Absolute Deviation (MAD)817.27866
Skewness0.93043507
Sum18350339
Variance1526281.5
MonotonicityNot monotonic
2024-05-11T14:56:18.529412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205430.675401509 3
 
3.3%
203421.695229095 2
 
2.2%
203451.550821003 2
 
2.2%
205884.374131265 2
 
2.2%
204507.725 1
 
1.1%
202622.614427913 1
 
1.1%
206618.425209149 1
 
1.1%
205707.089399978 1
 
1.1%
203552.516735999 1
 
1.1%
203675.905036013 1
 
1.1%
Other values (75) 75
82.4%
ValueCountFrequency (%)
201948.515562104 1
1.1%
202015.916578891 1
1.1%
202040.298872506 1
1.1%
202066.694352243 1
1.1%
202220.14 1
1.1%
202283.685456409 1
1.1%
202393.79868862 1
1.1%
202540.123155393 1
1.1%
202556.030346964 1
1.1%
202557.470516797 1
1.1%
ValueCountFrequency (%)
207432.495 1
 
1.1%
207367.992495204 1
 
1.1%
207356.154197928 1
 
1.1%
206618.425209149 1
 
1.1%
206581.787067095 1
 
1.1%
205975.914211031 1
 
1.1%
205884.374131265 2
2.2%
205707.089399978 1
 
1.1%
205430.675401509 3
3.3%
205239.155558835 1
 
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)94.4%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean444772.23
Minimum442584.25
Maximum447366.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T14:56:18.785042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442584.25
5-th percentile443108.38
Q1444296.94
median444791.87
Q3445097.79
95-th percentile446556.88
Maximum447366.54
Range4782.2899
Interquartile range (IQR)800.84816

Descriptive statistics

Standard deviation998.88493
Coefficient of variation (CV)0.0022458347
Kurtosis0.36380181
Mean444772.23
Median Absolute Deviation (MAD)480.00772
Skewness0.36084009
Sum40029501
Variance997771.11
MonotonicityNot monotonic
2024-05-11T14:56:19.075587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445034.546016578 3
 
3.3%
444309.674219389 2
 
2.2%
444529.420299492 2
 
2.2%
442955.266910236 2
 
2.2%
446043.48 1
 
1.1%
447287.248289595 1
 
1.1%
443390.560639694 1
 
1.1%
443914.194133105 1
 
1.1%
445969.499275396 1
 
1.1%
445926.119732235 1
 
1.1%
Other values (75) 75
82.4%
ValueCountFrequency (%)
442584.249412167 1
1.1%
442955.266910236 2
2.2%
443009.613343501 1
1.1%
443088.103774528 1
1.1%
443133.151522752 1
1.1%
443348.921370947 1
1.1%
443349.655 1
1.1%
443351.145 1
1.1%
443390.560639694 1
1.1%
443526.235146442 1
1.1%
ValueCountFrequency (%)
447366.539357322 1
1.1%
447287.248289595 1
1.1%
447239.218593207 1
1.1%
446973.178181631 1
1.1%
446598.273574037 1
1.1%
446506.287266234 1
1.1%
446179.775774667 1
1.1%
446122.702025921 1
1.1%
446107.548064976 1
1.1%
446043.48 1
1.1%

의료유사업종별명
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
안마시술소
43 
<NA>
25 
안마원
23 

Length

Max length5
Median length4
Mean length4.2197802
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마시술소 43
47.3%
<NA> 25
27.5%
안마원 23
25.3%

Length

2024-05-11T14:56:19.332667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:19.559180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마시술소 43
47.3%
na 25
27.5%
안마원 23
25.3%

종업원수
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)17.2%
Missing27
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean3.59375
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T14:56:19.761596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile7.85
Maximum13
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.7063638
Coefficient of variation (CV)0.75307513
Kurtosis2.2099554
Mean3.59375
Median Absolute Deviation (MAD)2
Skewness1.3545037
Sum230
Variance7.3244048
MonotonicityNot monotonic
2024-05-11T14:56:19.953779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 19
20.9%
2 9
 
9.9%
4 9
 
9.9%
6 7
 
7.7%
3 7
 
7.7%
5 6
 
6.6%
7 3
 
3.3%
13 1
 
1.1%
10 1
 
1.1%
8 1
 
1.1%
(Missing) 27
29.7%
ValueCountFrequency (%)
1 19
20.9%
2 9
9.9%
3 7
 
7.7%
4 9
9.9%
5 6
 
6.6%
6 7
 
7.7%
7 3
 
3.3%
8 1
 
1.1%
10 1
 
1.1%
12 1
 
1.1%
ValueCountFrequency (%)
13 1
 
1.1%
12 1
 
1.1%
10 1
 
1.1%
8 1
 
1.1%
7 3
 
3.3%
6 7
7.7%
5 6
6.6%
4 9
9.9%
3 7
7.7%
2 9
9.9%

자격증소유자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
<NA>
87 
0
 
4

Length

Max length4
Median length4
Mean length3.8681319
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> 87
95.6%
0 4
 
4.4%

Length

2024-05-11T14:56:20.150047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:20.390200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 87
95.6%
0 4
 
4.4%

보조종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
<NA>
87 
0
 
4

Length

Max length4
Median length4
Mean length3.8681319
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> 87
95.6%
0 4
 
4.4%

Length

2024-05-11T14:56:20.650164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:20.822129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 87
95.6%
0 4
 
4.4%

시설관리자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
<NA>
87 
0
 
4

Length

Max length4
Median length4
Mean length3.8681319
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> 87
95.6%
0 4
 
4.4%

Length

2024-05-11T14:56:21.004659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:21.159585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 87
95.6%
0 4
 
4.4%

기타종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
<NA>
87 
0
 
4

Length

Max length4
Median length4
Mean length3.8681319
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> 87
95.6%
0 4
 
4.4%

Length

2024-05-11T14:56:21.330010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:21.506148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 87
95.6%
0 4
 
4.4%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)52.0%
Missing41
Missing (%)45.1%
Infinite0
Infinite (%)0.0%
Mean18.68
Minimum0
Maximum39
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T14:56:21.662519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q111.5
median20
Q325.75
95-th percentile35
Maximum39
Range39
Interquartile range (IQR)14.25

Descriptive statistics

Standard deviation10.20092
Coefficient of variation (CV)0.54608781
Kurtosis-0.62189509
Mean18.68
Median Absolute Deviation (MAD)7
Skewness-0.20109926
Sum934
Variance104.05878
MonotonicityNot monotonic
2024-05-11T14:56:21.923424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
27 4
 
4.4%
1 4
 
4.4%
18 4
 
4.4%
24 4
 
4.4%
20 3
 
3.3%
9 3
 
3.3%
17 3
 
3.3%
21 2
 
2.2%
35 2
 
2.2%
15 2
 
2.2%
Other values (16) 19
20.9%
(Missing) 41
45.1%
ValueCountFrequency (%)
0 1
 
1.1%
1 4
4.4%
2 1
 
1.1%
5 1
 
1.1%
7 2
2.2%
9 3
3.3%
11 1
 
1.1%
13 1
 
1.1%
14 1
 
1.1%
15 2
2.2%
ValueCountFrequency (%)
39 1
 
1.1%
36 1
 
1.1%
35 2
2.2%
34 1
 
1.1%
29 1
 
1.1%
28 2
2.2%
27 4
4.4%
26 1
 
1.1%
25 2
2.2%
24 4
4.4%

욕실면적
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
<NA>
85 
0.0
 
5
44.53
 
1

Length

Max length5
Median length4
Mean length3.956044
Min length3

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
93.4%
0.0 5
 
5.5%
44.53 1
 
1.1%

Length

2024-05-11T14:56:22.160253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:22.343906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
93.4%
0.0 5
 
5.5%
44.53 1
 
1.1%

총면적
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)95.5%
Missing25
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean460.61636
Minimum16.69
Maximum827.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T14:56:22.544488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.69
5-th percentile42.7875
Q195.85
median537.99
Q3787.98
95-th percentile822.6975
Maximum827.43
Range810.74
Interquartile range (IQR)692.13

Descriptive statistics

Standard deviation320.02233
Coefficient of variation (CV)0.69476979
Kurtosis-1.7549388
Mean460.61636
Median Absolute Deviation (MAD)270.485
Skewness-0.16606053
Sum30400.68
Variance102414.29
MonotonicityNot monotonic
2024-05-11T14:56:22.832472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
787.98 3
 
3.3%
279.0 2
 
2.2%
41.65 1
 
1.1%
94.07 1
 
1.1%
758.36 1
 
1.1%
101.19 1
 
1.1%
115.0 1
 
1.1%
46.2 1
 
1.1%
60.6 1
 
1.1%
69.3 1
 
1.1%
Other values (53) 53
58.2%
(Missing) 25
27.5%
ValueCountFrequency (%)
16.69 1
1.1%
23.14 1
1.1%
33.05 1
1.1%
41.65 1
1.1%
46.2 1
1.1%
47.55 1
1.1%
49.05 1
1.1%
52.05 1
1.1%
60.6 1
1.1%
62.4 1
1.1%
ValueCountFrequency (%)
827.43 1
1.1%
825.91 1
1.1%
825.24 1
1.1%
823.2 1
1.1%
821.19 1
1.1%
819.69 1
1.1%
814.18 1
1.1%
811.17 1
1.1%
810.7 1
1.1%
806.25 1
1.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03220000PHMB41984322003304240000119840626<NA>3폐업3폐업20161212<NA><NA><NA>546-3356<NA>135870서울특별시 강남구 삼성동 65번지 5호서울특별시 강남구 삼성로 634 (삼성동)6084수안보안마시술소2016-12-12 15:36:51I2018-08-31 23:59:59.0안마시술소204507.725446043.48안마시술소6<NA><NA><NA><NA>18<NA>421.54
13220000PHMB4198932200330424000011989-05-31<NA>3폐업3폐업2023-12-122022-12-012023-12-31<NA>02-545-8574<NA>135-819서울특별시 강남구 논현2동 97번지 16호서울특별시 강남구 언주로148길 13 (논현동)6054보그안마시술소2023-12-12 10:10:41U2022-11-01 23:04:00.0안마시술소203080.57851446506.287266<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23220000PHMB41990322003304240000119900613<NA>3폐업3폐업20100219<NA><NA><NA>562-3040<NA>135915서울특별시 강남구 역삼동 678번지 29호서울특별시 강남구 테헤란로33길 5 (역삼동)<NA>마카오2010-03-19 13:25:38I2018-08-31 23:59:59.0안마시술소203412.589875444440.380089안마시술소6<NA><NA><NA><NA>29<NA>797.86
33220000PHMB41991322003304240000119911101<NA>3폐업3폐업201404072013120720140531<NA>554-3070<NA>135080서울특별시 강남구 역삼동 688번지 3호서울특별시 강남구 언주로 554 (역삼동)<NA>도깨비안마시술소2014-04-07 14:07:36I2018-08-31 23:59:59.0안마시술소203486.753586445031.745297안마시술소2<NA><NA><NA><NA>7<NA>311.22
43220000PHMB41993322003304240000119930713<NA>3폐업3폐업20120727<NA><NA><NA>548-4391<NA>135892서울특별시 강남구 신사동 586번지서울특별시 강남구 논현로 819 (신사동)135892리얼안마시술소2012-07-27 13:34:13I2018-08-31 23:59:59.0안마시술소202393.798689446598.273574안마시술소2<NA><NA><NA><NA>18<NA>372.68
53220000PHMB41993322003304240000219931101<NA>1영업/정상13영업중<NA><NA><NA><NA>539-7787<NA><NA>서울특별시 강남구 역삼동 707번지 11호서울특별시 강남구 테헤란로48길 6 (역삼동)6211리라안마시술소2021-08-18 17:41:20U2021-08-20 02:40:00.0안마시술소203976.752413444516.494313안마시술소50000200.0757.6
63220000PHMB41997322003304240000119970328<NA>3폐업3폐업20110325<NA><NA><NA>562-9922<NA>135846서울특별시 강남구 대치2동 945번지 11호 (지하1층)서울특별시 강남구 테헤란로98길 14 (대치동,(지하1층))<NA>천천안마시술소2012-01-25 14:11:40I2018-08-31 23:59:59.0안마시술소205430.675402445034.546017안마시술소6<NA><NA><NA><NA>2344.53787.98
73220000PHMB41997322003304240000219971230<NA>3폐업3폐업201308012013040920131008<NA>562-3389<NA>135090서울특별시 강남구 삼성동 143번지 21호서울특별시 강남구 테헤란로77길 11-15 (삼성동)<NA>우등생안마시술소2013-08-01 16:50:09I2018-08-31 23:59:59.0안마시술소204640.74444948.985안마시술소4<NA><NA><NA><NA>20<NA>734.4
83220000PHMB41998322003304240000119980428<NA>1영업/정상13영업중<NA><NA><NA><NA>553-7156<NA><NA>서울특별시 강남구 역삼동 707-16서울특별시 강남구 언주로86길 27, 1층일부, 2~5층 (역삼동)6211블루문타임안마시술소2022-01-11 17:34:53U2022-01-13 02:40:00.0안마시술소203943.797786444481.642794안마시술소130000390.0825.24
93220000PHMB42000322003304240000120000105<NA>3폐업3폐업20111031<NA><NA><NA>557-4828<NA>135080서울특별시 강남구 역삼동 689번지 7호서울특별시 강남구 언주로 530 (역삼동)135917에이플러스안마시술소2012-01-25 14:13:35I2018-08-31 23:59:59.0안마시술소203599.250677444863.862847안마시술소4<NA><NA><NA><NA>15<NA>497.42
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
813220000PHMB42017322003304240000120170628<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 신사동 576번지 1호서울특별시 강남구 압구정로28길 22-11, 3층 301호 (신사동)6030청홍안마원2017-06-28 14:41:30I2018-08-31 23:59:59.0안마원202283.685456446973.178182안마원1<NA><NA><NA><NA><NA><NA>23.14
823220000PHMB4201732200330424000022017-07-27<NA>3폐업3폐업2023-05-31<NA><NA><NA>02-2052-1681<NA><NA>서울특별시 강남구 역삼동 823번지 48호서울특별시 강남구 테헤란로10길 7, 1~3층 (역삼동)6234스타안마시술소2023-06-05 13:15:25U2022-12-06 00:08:00.0안마시술소202805.26692444046.288355<NA><NA><NA><NA><NA><NA><NA><NA><NA>
833220000PHMB4201732200330424000032017-10-16<NA>2휴업2휴업<NA>2022-12-142024-09-20<NA><NA><NA><NA>서울특별시 강남구 삼성동 143번지 8호 지하1층서울특별시 강남구 테헤란로77길 17, 지하1층 (삼성동, 승광빌딩)6159테티스안마시술소2024-03-13 14:19:20U2023-12-02 23:05:00.0안마시술소204718.327234445034.184824<NA><NA><NA><NA><NA><NA><NA><NA><NA>
843220000PHMB42017322003304240000420171212<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3432-8852<NA><NA>서울특별시 강남구 역삼동 781번지 37호 202호서울특별시 강남구 논현로66길 13, 202호 (역삼동)6228하나안마원2017-12-12 17:47:57I2018-08-31 23:59:59.0안마원203587.554948443570.987995안마원1<NA><NA><NA><NA><NA><NA>52.05
853220000PHMB42017322003304240000520171213<NA>3폐업3폐업20180921<NA><NA><NA>02-516-8575<NA><NA>서울특별시 강남구 논현동 122번지 3호 3층서울특별시 강남구 학동로6길 8, 3층 (논현동)6110바른손건강안마원2018-09-21 11:31:28U2018-09-21 23:59:59.0안마원202015.916579445439.081444안마원1<NA><NA><NA><NA><NA><NA>149.73
863220000PHMB42017322003304240000620171226<NA>1영업/정상13영업중<NA><NA><NA><NA>02-517-1033<NA><NA>서울특별시 강남구 논현동 122번지 11호 205호서울특별시 강남구 학동로6길 12, 205호 (논현동)6110우리건강안마원2020-08-19 09:29:27U2020-08-21 02:40:00.0안마원202040.298873445406.382381안마원1<NA><NA><NA><NA><NA><NA>33.05
873220000PHMB4201832200330424000012018-04-26<NA>3폐업3폐업2023-11-30<NA><NA><NA><NA><NA><NA>서울특별시 강남구 개포동 186번지 16호 현대빌딩 401호서울특별시 강남구 개포로 510, 현대빌딩 401호 (개포동)6329서울보건안마원2023-11-28 13:50:14U2022-10-31 21:00:00.0안마원205975.914211443009.613344<NA><NA><NA><NA><NA><NA><NA><NA><NA>
883220000PHMB42018322003304240000220180605<NA>3폐업3폐업20180807<NA><NA><NA>02-459-7575<NA><NA>서울특별시 강남구 개포동 186번지 12호 삼성빌딩 303호서울특별시 강남구 개포로82길 7, 삼성빌딩 3층 303호 (개포동)6329정체안마원2018-08-07 16:53:29I2018-08-31 23:59:59.0안마원205884.374131442955.26691안마원1<NA><NA><NA><NA><NA><NA>133.75
893220000PHMB42018322003304240000320181130<NA>3폐업3폐업20200812<NA><NA><NA>02-761-6026<NA><NA>서울특별시 강남구 신사동 620번지 압구정스퀘어서울특별시 강남구 압구정로34길 11, 압구정스퀘어 지하1층 103호 (신사동)6023압구정안마원2020-08-12 17:38:20U2020-08-14 02:40:00.0안마원202666.717098447239.218593안마원1<NA><NA><NA><NA><NA><NA>73.36
903220000PHMB4202432200330424000012024-01-23<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 755 한솔필리아 210호서울특별시 강남구 역삼로 310, 한솔필리아 2층 10호 (역삼동)6217용인안마지압원강남점2024-01-24 14:14:24I2023-11-30 22:07:00.0안마원204213.643237444113.028211<NA><NA><NA><NA><NA><NA><NA><NA><NA>