Overview

Dataset statistics

Number of variables34
Number of observations35
Missing cells173
Missing cells (%)14.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory294.8 B

Variable types

Categorical17
Text6
DateTime3
Unsupported3
Numeric5

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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-16378/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (81.3%)Imbalance
휴업종료일자 is highly imbalanced (81.3%)Imbalance
인허가취소일자 has 35 (100.0%) missing valuesMissing
폐업일자 has 12 (34.3%) missing valuesMissing
재개업일자 has 35 (100.0%) missing valuesMissing
전화번호 has 7 (20.0%) missing valuesMissing
소재지면적 has 35 (100.0%) missing valuesMissing
소재지우편번호 has 10 (28.6%) missing valuesMissing
지번주소 has 1 (2.9%) missing valuesMissing
도로명우편번호 has 16 (45.7%) missing valuesMissing
병상수 has 19 (54.3%) missing valuesMissing
총면적 has 3 (8.6%) missing valuesMissing
관리번호 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 4 (11.4%) zerosZeros

Reproduction

Analysis started2024-05-11 07:05:22.596022
Analysis finished2024-05-11 07:05:23.160611
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
3200000
35 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 35
100.0%

Length

2024-05-11T16:05:23.268850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:23.696668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 35
100.0%

관리번호
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-05-11T16:05:23.940757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters875
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

Unique35 ?
Unique (%)100.0%

Sample

1st rowPHMB419983200033042400001
2nd rowPHMB420013200033042400001
3rd rowPHMB420033200033042400001
4th rowPHMB420033200033042400002
5th rowPHMB420053200033042400001
ValueCountFrequency (%)
phmb419983200033042400001 1
 
2.9%
phmb420113200033042400003 1
 
2.9%
phmb420123200033042400002 1
 
2.9%
phmb420133200033042400001 1
 
2.9%
phmb420133200033042400002 1
 
2.9%
phmb420133200033042400003 1
 
2.9%
phmb420133200033042400004 1
 
2.9%
phmb420143200033042400001 1
 
2.9%
phmb420123200033042400001 1
 
2.9%
phmb420143200033042400002 1
 
2.9%
Other values (25) 25
71.4%
2024-05-11T16:05:24.460207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 330
37.7%
2 118
 
13.5%
3 116
 
13.3%
4 109
 
12.5%
1 40
 
4.6%
P 35
 
4.0%
H 35
 
4.0%
M 35
 
4.0%
B 35
 
4.0%
9 6
 
0.7%
Other values (4) 16
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 735
84.0%
Uppercase Letter 140
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 330
44.9%
2 118
 
16.1%
3 116
 
15.8%
4 109
 
14.8%
1 40
 
5.4%
9 6
 
0.8%
7 6
 
0.8%
8 4
 
0.5%
5 3
 
0.4%
6 3
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
P 35
25.0%
H 35
25.0%
M 35
25.0%
B 35
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 735
84.0%
Latin 140
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 330
44.9%
2 118
 
16.1%
3 116
 
15.8%
4 109
 
14.8%
1 40
 
5.4%
9 6
 
0.8%
7 6
 
0.8%
8 4
 
0.5%
5 3
 
0.4%
6 3
 
0.4%
Latin
ValueCountFrequency (%)
P 35
25.0%
H 35
25.0%
M 35
25.0%
B 35
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 330
37.7%
2 118
 
13.5%
3 116
 
13.3%
4 109
 
12.5%
1 40
 
4.6%
P 35
 
4.0%
H 35
 
4.0%
M 35
 
4.0%
B 35
 
4.0%
9 6
 
0.7%
Other values (4) 16
 
1.8%

인허가일자
Date

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum1998-02-02 00:00:00
Maximum2020-12-28 00:00:00
2024-05-11T16:05:24.690336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:05:24.887192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
3
23 
1
12 

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 23
65.7%
1 12
34.3%

Length

2024-05-11T16:05:25.076915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:25.224395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 23
65.7%
1 12
34.3%

영업상태명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
폐업
23 
영업/정상
12 

Length

Max length5
Median length2
Mean length3.0285714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 23
65.7%
영업/정상 12
34.3%

Length

2024-05-11T16:05:25.389796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:25.535322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 23
65.7%
영업/정상 12
34.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
3
23 
13
12 

Length

Max length2
Median length1
Mean length1.3428571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 23
65.7%
13 12
34.3%

Length

2024-05-11T16:05:25.679603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:25.808791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 23
65.7%
13 12
34.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
폐업
23 
영업중
12 

Length

Max length3
Median length2
Mean length2.3428571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 23
65.7%
영업중 12
34.3%

Length

2024-05-11T16:05:25.968044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:26.100680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 23
65.7%
영업중 12
34.3%

폐업일자
Date

MISSING 

Distinct22
Distinct (%)95.7%
Missing12
Missing (%)34.3%
Memory size412.0 B
Minimum2009-03-31 00:00:00
Maximum2023-02-06 00:00:00
2024-05-11T16:05:26.221740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:05:26.366604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
34 
20100625
 
1

Length

Max length8
Median length4
Mean length4.1142857
Min length4

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 34
97.1%
20100625 1
 
2.9%

Length

2024-05-11T16:05:26.614213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:26.802067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
97.1%
20100625 1
 
2.9%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
34 
20110624
 
1

Length

Max length8
Median length4
Mean length4.1142857
Min length4

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 34
97.1%
20110624 1
 
2.9%

Length

2024-05-11T16:05:27.006745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:27.160842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
97.1%
20110624 1
 
2.9%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

전화번호
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing7
Missing (%)20.0%
Memory size412.0 B
2024-05-11T16:05:27.415974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length9
Min length8

Characters and Unicode

Total characters252
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 (%)100.0%

Sample

1st row855-0235
2nd row871-0046
3rd row838-0223
4th row888-0729
5th row852-5588
ValueCountFrequency (%)
865-7572 1
 
3.6%
871-0046 1
 
3.6%
873-2879 1
 
3.6%
070-8861-1515 1
 
3.6%
02-889-7577 1
 
3.6%
02-878-1275 1
 
3.6%
02-6494-1119 1
 
3.6%
883-1803 1
 
3.6%
1577-7416 1
 
3.6%
875-2789 1
 
3.6%
Other values (18) 18
64.3%
2024-05-11T16:05:27.844099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 52
20.6%
- 35
13.9%
7 28
11.1%
5 24
9.5%
3 24
9.5%
2 22
8.7%
6 16
 
6.3%
0 16
 
6.3%
1 15
 
6.0%
9 11
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 217
86.1%
Dash Punctuation 35
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 52
24.0%
7 28
12.9%
5 24
11.1%
3 24
11.1%
2 22
10.1%
6 16
 
7.4%
0 16
 
7.4%
1 15
 
6.9%
9 11
 
5.1%
4 9
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 52
20.6%
- 35
13.9%
7 28
11.1%
5 24
9.5%
3 24
9.5%
2 22
8.7%
6 16
 
6.3%
0 16
 
6.3%
1 15
 
6.0%
9 11
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 52
20.6%
- 35
13.9%
7 28
11.1%
5 24
9.5%
3 24
9.5%
2 22
8.7%
6 16
 
6.3%
0 16
 
6.3%
1 15
 
6.0%
9 11
 
4.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

소재지우편번호
Text

MISSING 

Distinct23
Distinct (%)92.0%
Missing10
Missing (%)28.6%
Memory size412.0 B
2024-05-11T16:05:28.095646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.08
Min length6

Characters and Unicode

Total characters152
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

Unique22 ?
Unique (%)88.0%

Sample

1st row151903
2nd row151892
3rd row151891
4th row151887
5th row151016
ValueCountFrequency (%)
151843 3
 
12.0%
151015 1
 
4.0%
151903 1
 
4.0%
151-018 1
 
4.0%
151830 1
 
4.0%
151899 1
 
4.0%
151810 1
 
4.0%
151895 1
 
4.0%
151870 1
 
4.0%
151874 1
 
4.0%
Other values (13) 13
52.0%
2024-05-11T16:05:28.445048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 59
38.8%
5 28
18.4%
8 19
 
12.5%
0 16
 
10.5%
9 8
 
5.3%
7 6
 
3.9%
3 5
 
3.3%
4 4
 
2.6%
2 3
 
2.0%
6 2
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
98.7%
Dash Punctuation 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 59
39.3%
5 28
18.7%
8 19
 
12.7%
0 16
 
10.7%
9 8
 
5.3%
7 6
 
4.0%
3 5
 
3.3%
4 4
 
2.7%
2 3
 
2.0%
6 2
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 59
38.8%
5 28
18.4%
8 19
 
12.5%
0 16
 
10.5%
9 8
 
5.3%
7 6
 
3.9%
3 5
 
3.3%
4 4
 
2.6%
2 3
 
2.0%
6 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 59
38.8%
5 28
18.4%
8 19
 
12.5%
0 16
 
10.5%
9 8
 
5.3%
7 6
 
3.9%
3 5
 
3.3%
4 4
 
2.6%
2 3
 
2.0%
6 2
 
1.3%

지번주소
Text

MISSING 

Distinct33
Distinct (%)97.1%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-05-11T16:05:28.764890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length24.441176
Min length19

Characters and Unicode

Total characters831
Distinct characters57
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

Unique32 ?
Unique (%)94.1%

Sample

1st row서울특별시 관악구 조원동 1655번지 17호 2~4층
2nd row서울특별시 관악구 신림동 1421번지 22호
3rd row서울특별시 관악구 신림동 1425번지 4호
4th row서울특별시 관악구 미성동 1474번지 14호
5th row서울특별시 관악구 삼성동 304번지 25호
ValueCountFrequency (%)
서울특별시 34
19.1%
관악구 34
19.1%
봉천동 8
 
4.5%
신림동 7
 
3.9%
조원동 4
 
2.2%
은천동 4
 
2.2%
2층 3
 
1.7%
15호 3
 
1.7%
4호 3
 
1.7%
남현동 2
 
1.1%
Other values (64) 76
42.7%
2024-05-11T16:05:29.356351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
 
17.3%
1 41
 
4.9%
서 35
 
4.2%
호 35
 
4.2%
특 34
 
4.1%
별 34
 
4.1%
시 34
 
4.1%
관 34
 
4.1%
악 34
 
4.1%
구 34
 
4.1%
Other values (47) 372
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 492
59.2%
Decimal Number 190
 
22.9%
Space Separator 144
 
17.3%
Math Symbol 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 35
 
7.1%
호 35
 
7.1%
특 34
 
6.9%
별 34
 
6.9%
시 34
 
6.9%
관 34
 
6.9%
악 34
 
6.9%
구 34
 
6.9%
울 34
 
6.9%
동 34
 
6.9%
Other values (31) 150
30.5%
Decimal Number
ValueCountFrequency (%)
1 41
21.6%
2 27
14.2%
6 24
12.6%
4 21
11.1%
5 20
10.5%
3 15
 
7.9%
9 12
 
6.3%
7 11
 
5.8%
0 10
 
5.3%
8 9
 
4.7%
Space Separator
ValueCountFrequency (%)
144
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 492
59.2%
Common 339
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 35
 
7.1%
호 35
 
7.1%
특 34
 
6.9%
별 34
 
6.9%
시 34
 
6.9%
관 34
 
6.9%
악 34
 
6.9%
구 34
 
6.9%
울 34
 
6.9%
동 34
 
6.9%
Other values (31) 150
30.5%
Common
ValueCountFrequency (%)
144
42.5%
1 41
 
12.1%
2 27
 
8.0%
6 24
 
7.1%
4 21
 
6.2%
5 20
 
5.9%
3 15
 
4.4%
9 12
 
3.5%
7 11
 
3.2%
0 10
 
2.9%
Other values (6) 14
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 492
59.2%
ASCII 339
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
42.5%
1 41
 
12.1%
2 27
 
8.0%
6 24
 
7.1%
4 21
 
6.2%
5 20
 
5.9%
3 15
 
4.4%
9 12
 
3.5%
7 11
 
3.2%
0 10
 
2.9%
Other values (6) 14
 
4.1%
Hangul
ValueCountFrequency (%)
서 35
 
7.1%
호 35
 
7.1%
특 34
 
6.9%
별 34
 
6.9%
시 34
 
6.9%
관 34
 
6.9%
악 34
 
6.9%
구 34
 
6.9%
울 34
 
6.9%
동 34
 
6.9%
Other values (31) 150
30.5%

도로명주소
Text

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-05-11T16:05:29.698873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31
Mean length27.485714
Min length16

Characters and Unicode

Total characters962
Distinct characters67
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st row서울특별시 관악구 시흥대로 558-1 (신림동,2~4층)
2nd row서울특별시 관악구 신림로64길 29 (신림동)
3rd row서울특별시 관악구 봉천로12길 28 (신림동)
4th row서울특별시 관악구 남부순환로 1464 (신림동)
5th row서울특별시 관악구 호암로 535 (신림동)
ValueCountFrequency (%)
서울특별시 35
18.3%
관악구 34
17.8%
신림동 15
 
7.9%
봉천동 12
 
6.3%
남부순환로 8
 
4.2%
3층 4
 
2.1%
시흥대로 4
 
2.1%
신림로 3
 
1.6%
2층 3
 
1.6%
봉천로 3
 
1.6%
Other values (63) 70
36.6%
2024-05-11T16:05:30.138198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
 
16.2%
시 39
 
4.1%
관 39
 
4.1%
악 37
 
3.8%
서 35
 
3.6%
) 35
 
3.6%
( 35
 
3.6%
울 35
 
3.6%
별 35
 
3.6%
특 35
 
3.6%
Other values (57) 481
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
57.8%
Space Separator 156
 
16.2%
Decimal Number 151
 
15.7%
Close Punctuation 35
 
3.6%
Open Punctuation 35
 
3.6%
Other Punctuation 21
 
2.2%
Dash Punctuation 4
 
0.4%
Math Symbol 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 39
 
7.0%
관 39
 
7.0%
악 37
 
6.7%
서 35
 
6.3%
울 35
 
6.3%
별 35
 
6.3%
특 35
 
6.3%
구 34
 
6.1%
동 34
 
6.1%
로 33
 
5.9%
Other values (39) 200
36.0%
Decimal Number
ValueCountFrequency (%)
1 28
18.5%
3 26
17.2%
4 19
12.6%
2 18
11.9%
5 14
9.3%
6 14
9.3%
8 9
 
6.0%
0 8
 
5.3%
9 8
 
5.3%
7 7
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
57.8%
Common 404
42.0%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 39
 
7.0%
관 39
 
7.0%
악 37
 
6.7%
서 35
 
6.3%
울 35
 
6.3%
별 35
 
6.3%
특 35
 
6.3%
구 34
 
6.1%
동 34
 
6.1%
로 33
 
5.9%
Other values (39) 200
36.0%
Common
ValueCountFrequency (%)
156
38.6%
) 35
 
8.7%
( 35
 
8.7%
1 28
 
6.9%
3 26
 
6.4%
, 21
 
5.2%
4 19
 
4.7%
2 18
 
4.5%
5 14
 
3.5%
6 14
 
3.5%
Other values (6) 38
 
9.4%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
57.8%
ASCII 406
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
38.4%
) 35
 
8.6%
( 35
 
8.6%
1 28
 
6.9%
3 26
 
6.4%
, 21
 
5.2%
4 19
 
4.7%
2 18
 
4.4%
5 14
 
3.4%
6 14
 
3.4%
Other values (8) 40
 
9.9%
Hangul
ValueCountFrequency (%)
시 39
 
7.0%
관 39
 
7.0%
악 37
 
6.7%
서 35
 
6.3%
울 35
 
6.3%
별 35
 
6.3%
특 35
 
6.3%
구 34
 
6.1%
동 34
 
6.1%
로 33
 
5.9%
Other values (39) 200
36.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)78.9%
Missing16
Missing (%)45.7%
Infinite0
Infinite (%)0.0%
Mean31367.684
Minimum8737
Maximum151902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T16:05:30.262365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8737
5-th percentile8737
Q18755.5
median8777
Q38801
95-th percentile151892.1
Maximum151902
Range143165
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation53616.725
Coefficient of variation (CV)1.7092982
Kurtosis2.409925
Mean31367.684
Median Absolute Deviation (MAD)24
Skewness2.0412054
Sum595986
Variance2.8747532 × 109
MonotonicityNot monotonic
2024-05-11T16:05:30.387283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
8737 3
 
8.6%
8757 2
 
5.7%
8801 2
 
5.7%
151891 1
 
2.9%
8767 1
 
2.9%
151902 1
 
2.9%
151870 1
 
2.9%
8812 1
 
2.9%
8773 1
 
2.9%
8784 1
 
2.9%
Other values (5) 5
 
14.3%
(Missing) 16
45.7%
ValueCountFrequency (%)
8737 3
8.6%
8753 1
 
2.9%
8754 1
 
2.9%
8757 2
5.7%
8767 1
 
2.9%
8773 1
 
2.9%
8777 1
 
2.9%
8784 1
 
2.9%
8787 1
 
2.9%
8789 1
 
2.9%
ValueCountFrequency (%)
151902 1
2.9%
151891 1
2.9%
151870 1
2.9%
8812 1
2.9%
8801 2
5.7%
8789 1
2.9%
8787 1
2.9%
8784 1
2.9%
8777 1
2.9%
8773 1
2.9%

사업장명
Text

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-05-11T16:05:30.659716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length6.4
Min length4

Characters and Unicode

Total characters224
Distinct characters78
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)88.6%

Sample

1st row샤인안마시술소
2nd row청화안마시술소
3rd row씨티안마시술소
4th row스파안마시술소
5th row라파안마원
ValueCountFrequency (%)
굿모닝안마원 2
 
5.6%
정체안마원 2
 
5.6%
다온건강안마원 1
 
2.8%
중앙건강안마원 1
 
2.8%
낙성건강안마원 1
 
2.8%
생기팔팔안마원 1
 
2.8%
김해숙힐링안마원 1
 
2.8%
보라매안마원 1
 
2.8%
윤앤안마원 1
 
2.8%
관악보건안마원 1
 
2.8%
Other values (24) 24
66.7%
2024-05-11T16:05:31.036998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 35
15.6%
마 35
15.6%
원 26
 
11.6%
시 10
 
4.5%
술 10
 
4.5%
소 10
 
4.5%
강 4
 
1.8%
건 4
 
1.8%
스 3
 
1.3%
정 3
 
1.3%
Other values (68) 84
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 221
98.7%
Uppercase Letter 2
 
0.9%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 35
15.8%
마 35
15.8%
원 26
 
11.8%
시 10
 
4.5%
술 10
 
4.5%
소 10
 
4.5%
강 4
 
1.8%
건 4
 
1.8%
스 3
 
1.4%
정 3
 
1.4%
Other values (65) 81
36.7%
Uppercase Letter
ValueCountFrequency (%)
Y 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 221
98.7%
Latin 2
 
0.9%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 35
15.8%
마 35
15.8%
원 26
 
11.8%
시 10
 
4.5%
술 10
 
4.5%
소 10
 
4.5%
강 4
 
1.8%
건 4
 
1.8%
스 3
 
1.4%
정 3
 
1.4%
Other values (65) 81
36.7%
Latin
ValueCountFrequency (%)
Y 1
50.0%
G 1
50.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 221
98.7%
ASCII 3
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 35
15.8%
마 35
15.8%
원 26
 
11.8%
시 10
 
4.5%
술 10
 
4.5%
소 10
 
4.5%
강 4
 
1.8%
건 4
 
1.8%
스 3
 
1.4%
정 3
 
1.4%
Other values (65) 81
36.7%
ASCII
ValueCountFrequency (%)
1
33.3%
Y 1
33.3%
G 1
33.3%

최종수정일자
Date

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2009-03-31 15:05:29
Maximum2023-11-13 11:44:21
2024-05-11T16:05:31.158139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:05:31.322088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
I
25 
U
10 

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 25
71.4%
U 10
 
28.6%

Length

2024-05-11T16:05:31.483046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:31.591314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 25
71.4%
u 10
 
28.6%

데이터갱신일자
Categorical

Distinct9
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
2018-08-31 23:59:59.0
24 
2021-07-10 02:40:00.0
3 
2021-07-09 02:40:00.0
 
2
2018-10-20 02:35:52.0
 
1
2022-10-31 23:05:00.0
 
1
Other values (4)
4 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique6 ?
Unique (%)17.1%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 24
68.6%
2021-07-10 02:40:00.0 3
 
8.6%
2021-07-09 02:40:00.0 2
 
5.7%
2018-10-20 02:35:52.0 1
 
2.9%
2022-10-31 23:05:00.0 1
 
2.9%
2022-11-01 00:03:00.0 1
 
2.9%
2022-12-02 00:09:00.0 1
 
2.9%
2021-12-16 02:40:00.0 1
 
2.9%
2021-01-02 00:23:15.0 1
 
2.9%

Length

2024-05-11T16:05:31.703131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:31.847911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 24
34.3%
23:59:59.0 24
34.3%
02:40:00.0 6
 
8.6%
2021-07-10 3
 
4.3%
2021-07-09 2
 
2.9%
2018-10-20 1
 
1.4%
02:35:52.0 1
 
1.4%
2022-10-31 1
 
1.4%
23:05:00.0 1
 
1.4%
2022-11-01 1
 
1.4%
Other values (6) 6
 
8.6%

업태구분명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
안마원
25 
안마시술소
10 

Length

Max length5
Median length3
Mean length3.5714286
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 25
71.4%
안마시술소 10
 
28.6%

Length

2024-05-11T16:05:32.011847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:32.139376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 25
71.4%
안마시술소 10
 
28.6%

좌표정보(X)
Real number (ℝ)

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194298.26
Minimum191259.6
Maximum198209.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T16:05:32.254838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191259.6
5-th percentile191332.36
Q1193228.11
median193859.62
Q3195808.91
95-th percentile197245.87
Maximum198209.15
Range6949.5513
Interquartile range (IQR)2580.7977

Descriptive statistics

Standard deviation1856.3183
Coefficient of variation (CV)0.0095539623
Kurtosis-0.42770208
Mean194298.26
Median Absolute Deviation (MAD)1360.2012
Skewness0.18744147
Sum6800439.2
Variance3445917.6
MonotonicityNot monotonic
2024-05-11T16:05:32.398862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
195928.118731948 2
 
5.7%
191259.60234678 1
 
2.9%
193773.070404044 1
 
2.9%
194120.792650529 1
 
2.9%
196191.740648852 1
 
2.9%
192876.282505416 1
 
2.9%
193445.061683369 1
 
2.9%
194912.547175192 1
 
2.9%
193671.180923103 1
 
2.9%
194582.286653215 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
191259.60234678 1
2.9%
191288.170481488 1
2.9%
191351.294437084 1
2.9%
191358.477626236 1
2.9%
192185.353391213 1
2.9%
192222.526606453 1
2.9%
192267.416974047 1
2.9%
192876.282505416 1
2.9%
193011.162392195 1
2.9%
193445.061683369 1
2.9%
ValueCountFrequency (%)
198209.153690741 1
2.9%
198178.329676125 1
2.9%
196846.248376248 1
2.9%
196683.467110525 1
2.9%
196191.740648852 1
2.9%
196069.172603877 1
2.9%
195998.790182399 1
2.9%
195928.118731948 2
5.7%
195689.700662469 1
2.9%
195219.819865573 1
2.9%

좌표정보(Y)
Real number (ℝ)

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442228.74
Minimum440356.26
Maximum443094.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T16:05:32.554321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440356.26
5-th percentile441325.13
Q1442146.86
median442316.16
Q3442558.2
95-th percentile442818.69
Maximum443094.67
Range2738.4148
Interquartile range (IQR)411.34288

Descriptive statistics

Standard deviation537.90822
Coefficient of variation (CV)0.0012163575
Kurtosis3.6376638
Mean442228.74
Median Absolute Deviation (MAD)237.36424
Skewness-1.6095598
Sum15478006
Variance289345.25
MonotonicityNot monotonic
2024-05-11T16:05:32.680698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
442168.066143108 2
 
5.7%
442292.524001058 1
 
2.9%
442270.419248856 1
 
2.9%
440993.064165952 1
 
2.9%
442676.422203462 1
 
2.9%
442270.308263218 1
 
2.9%
443094.673567102 1
 
2.9%
442169.547273536 1
 
2.9%
442608.256980594 1
 
2.9%
442380.092460125 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
440356.258778085 1
2.9%
440993.064165952 1
2.9%
441467.43770264 1
2.9%
441502.542951079 1
2.9%
441616.720856604 1
2.9%
441709.675836661 1
2.9%
441971.086567335 1
2.9%
442020.136028105 1
2.9%
442125.650465587 1
2.9%
442168.066143108 2
5.7%
ValueCountFrequency (%)
443094.673567102 1
2.9%
442848.981553096 1
2.9%
442805.707905711 1
2.9%
442739.354185215 1
2.9%
442679.355472555 1
2.9%
442676.422203462 1
2.9%
442633.112320542 1
2.9%
442608.256980594 1
2.9%
442562.87358396 1
2.9%
442553.528776558 1
2.9%

의료유사업종별명
Categorical

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
안마원
24 
안마시술소
8 
<NA>
3 

Length

Max length5
Median length3
Mean length3.5428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 24
68.6%
안마시술소 8
 
22.9%
<NA> 3
 
8.6%

Length

2024-05-11T16:05:32.826977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:32.941730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 24
68.6%
안마시술소 8
 
22.9%
na 3
 
8.6%

종업원수
Categorical

Distinct6
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
1
14 
2
10 
<NA>
5 
4
3 
0
2 

Length

Max length4
Median length1
Mean length1.4285714
Min length1

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row2
2nd row2
3rd row1
4th row4
5th row2

Common Values

ValueCountFrequency (%)
1 14
40.0%
2 10
28.6%
<NA> 5
 
14.3%
4 3
 
8.6%
0 2
 
5.7%
5 1
 
2.9%

Length

2024-05-11T16:05:33.097897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:33.233914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 14
40.0%
2 10
28.6%
na 5
 
14.3%
4 3
 
8.6%
0 2
 
5.7%
5 1
 
2.9%

자격증소유자수
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
29 
0
6 

Length

Max length4
Median length4
Mean length3.4857143
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> 29
82.9%
0 6
 
17.1%

Length

2024-05-11T16:05:33.389496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:33.528421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
82.9%
0 6
 
17.1%

보조종업원수
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
29 
0
6 

Length

Max length4
Median length4
Mean length3.4857143
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> 29
82.9%
0 6
 
17.1%

Length

2024-05-11T16:05:33.679561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:33.822178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
82.9%
0 6
 
17.1%

시설관리자수
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
29 
0
6 

Length

Max length4
Median length4
Mean length3.4857143
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> 29
82.9%
0 6
 
17.1%

Length

2024-05-11T16:05:33.966593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:34.094119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
82.9%
0 6
 
17.1%

기타종업원수
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
29 
0
6 

Length

Max length4
Median length4
Mean length3.4857143
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> 29
82.9%
0 6
 
17.1%

Length

2024-05-11T16:05:34.235771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:34.624496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
82.9%
0 6
 
17.1%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)56.2%
Missing19
Missing (%)54.3%
Infinite0
Infinite (%)0.0%
Mean5.5
Minimum0
Maximum21
Zeros4
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T16:05:34.733730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median2.5
Q35.5
95-th percentile20.25
Maximum21
Range21
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation7.2387844
Coefficient of variation (CV)1.3161426
Kurtosis0.8088635
Mean5.5
Median Absolute Deviation (MAD)2.5
Skewness1.4661119
Sum88
Variance52.4
MonotonicityNot monotonic
2024-05-11T16:05:34.842761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 4
 
11.4%
1 3
 
8.6%
5 3
 
8.6%
21 1
 
2.9%
20 1
 
2.9%
17 1
 
2.9%
7 1
 
2.9%
2 1
 
2.9%
3 1
 
2.9%
(Missing) 19
54.3%
ValueCountFrequency (%)
0 4
11.4%
1 3
8.6%
2 1
 
2.9%
3 1
 
2.9%
5 3
8.6%
7 1
 
2.9%
17 1
 
2.9%
20 1
 
2.9%
21 1
 
2.9%
ValueCountFrequency (%)
21 1
 
2.9%
20 1
 
2.9%
17 1
 
2.9%
7 1
 
2.9%
5 3
8.6%
3 1
 
2.9%
2 1
 
2.9%
1 3
8.6%
0 4
11.4%

욕실면적
Categorical

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
25 
0.0
7 
42.51
 
1
300.0
 
1
27.0
 
1

Length

Max length5
Median length4
Mean length3.8571429
Min length3

Unique

Unique3 ?
Unique (%)8.6%

Sample

1st row<NA>
2nd row42.51
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
71.4%
0.0 7
 
20.0%
42.51 1
 
2.9%
300.0 1
 
2.9%
27.0 1
 
2.9%

Length

2024-05-11T16:05:34.990957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:05:35.128495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
71.4%
0.0 7
 
20.0%
42.51 1
 
2.9%
300.0 1
 
2.9%
27.0 1
 
2.9%

총면적
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)96.9%
Missing3
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean183.33219
Minimum24.32
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T16:05:35.298589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.32
5-th percentile38.435
Q159.96
median71.75
Q3250.1125
95-th percentile524.3
Maximum1000
Range975.68
Interquartile range (IQR)190.1525

Descriptive statistics

Standard deviation217.32458
Coefficient of variation (CV)1.1854142
Kurtosis5.3284477
Mean183.33219
Median Absolute Deviation (MAD)25.85
Skewness2.1582496
Sum5866.63
Variance47229.972
MonotonicityNot monotonic
2024-05-11T16:05:35.493929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
48.38 2
 
5.7%
424.44 1
 
2.9%
59.84 1
 
2.9%
64.8 1
 
2.9%
153.8 1
 
2.9%
68.0 1
 
2.9%
86.66 1
 
2.9%
72.5 1
 
2.9%
48.1 1
 
2.9%
50.0 1
 
2.9%
Other values (21) 21
60.0%
(Missing) 3
 
8.6%
ValueCountFrequency (%)
24.32 1
2.9%
32.0 1
2.9%
43.7 1
2.9%
48.1 1
2.9%
48.38 2
5.7%
50.0 1
2.9%
59.84 1
2.9%
60.0 1
2.9%
61.04 1
2.9%
61.2 1
2.9%
ValueCountFrequency (%)
1000.0 1
2.9%
554.0 1
2.9%
500.0 1
2.9%
454.0 1
2.9%
424.44 1
2.9%
421.0 1
2.9%
371.0 1
2.9%
314.98 1
2.9%
228.49 1
2.9%
153.8 1
2.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03200000PHMB41998320003304240000119980202<NA>3폐업3폐업20150302<NA><NA><NA>855-0235<NA>151903서울특별시 관악구 조원동 1655번지 17호 2~4층서울특별시 관악구 시흥대로 558-1 (신림동,2~4층)<NA>샤인안마시술소2015-03-02 17:05:16I2018-08-31 23:59:59.0안마시술소191259.602347442292.524001안마시술소2<NA><NA><NA><NA>21<NA>454.0
13200000PHMB42001320003304240000120010608<NA>3폐업3폐업20100323<NA><NA><NA><NA><NA>151892서울특별시 관악구 신림동 1421번지 22호서울특별시 관악구 신림로64길 29 (신림동)<NA>청화안마시술소2010-03-23 15:37:14I2018-08-31 23:59:59.0안마시술소193859.618675442562.873584안마시술소2<NA><NA><NA><NA>2042.51424.44
23200000PHMB42003320003304240000120030519<NA>3폐업3폐업20110426<NA><NA><NA>871-0046<NA>151891서울특별시 관악구 신림동 1425번지 4호서울특별시 관악구 봉천로12길 28 (신림동)151891씨티안마시술소2011-04-26 09:55:11I2018-08-31 23:59:59.0안마시술소193694.633577442805.707906안마시술소1<NA><NA><NA><NA>1<NA>421.0
33200000PHMB42003320003304240000220030519<NA>3폐업3폐업20101228<NA><NA><NA>838-0223<NA>151887서울특별시 관악구 미성동 1474번지 14호서울특별시 관악구 남부순환로 1464 (신림동)<NA>스파안마시술소2010-12-28 10:14:59I2018-08-31 23:59:59.0안마시술소192267.416974442125.650466안마시술소4<NA><NA><NA><NA>17<NA>314.98
43200000PHMB42005320003304240000120051025<NA>3폐업3폐업20091208<NA><NA><NA><NA><NA>151016서울특별시 관악구 삼성동 304번지 25호서울특별시 관악구 호암로 535 (신림동)<NA>라파안마원2009-12-08 16:37:59I2018-08-31 23:59:59.0안마원193852.999512440356.258778안마원2<NA><NA><NA><NA><NA><NA>115.0
53200000PHMB42006320003304240000120060316<NA>1영업/정상13영업중<NA><NA><NA><NA>888-0729<NA>151843서울특별시 관악구 은천동 931번지 7호 2,3층서울특별시 관악구 남부순환로 1717 (봉천동)8757실로암장애인근로사업장안마원2021-07-08 16:49:36U2021-07-10 02:40:00.0안마원194725.323011442316.164532안마원1000010.0228.49
63200000PHMB42006320003304240000220061004<NA>3폐업3폐업20181018<NA><NA><NA>852-5588<NA>151876서울특별시 관악구 신림동 539번지 6호서울특별시 관악구 조원로16가길 34 (신림동)8767강흥수안마원2018-10-18 13:35:19U2018-10-20 02:35:52.0안마원192185.353391442296.332761안마원<NA><NA><NA><NA><NA><NA><NA>77.0
73200000PHMB42007320003304240000120070308<NA>3폐업3폐업20090403<NA><NA><NA>873-9633<NA>151827서울특별시 관악구 은천동 908번지 66호서울특별시 관악구 양녕로1길 48 (봉천동)<NA>웰빙안마원2009-04-03 14:55:43I2018-08-31 23:59:59.0안마원194964.540666442402.066634안마원1<NA><NA><NA><NA><NA><NA>71.0
83200000PHMB4200732000330424000022007-05-17<NA>1영업/정상13영업중<NA><NA><NA><NA>587-1351<NA>151-080서울특별시 관악구 남현동 1062번지 15호서울특별시 관악구 남현1길 58 (남현동)<NA>용안마시술소2023-11-13 11:44:21U2022-10-31 23:05:00.0안마시술소198209.153691441502.542951<NA><NA><NA><NA><NA><NA><NA><NA><NA>
93200000PHMB42007320003304240000320070814<NA>3폐업3폐업201103212010062520110624<NA><NA><NA>151018서울특별시 관악구 조원동 1655번지 8호서울특별시 관악구 시흥대로 566 (신림동)<NA>칸안마시술소2011-03-21 13:44:29I2018-08-31 23:59:59.0안마시술소191288.170481442343.821507안마시술소2<NA><NA><NA><NA>7<NA>554.0
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
253200000PHMB42014320003304240000120140602<NA>3폐업3폐업20170704<NA><NA><NA>1577-7416<NA><NA><NA>서울특별시 관악구 남부순환로208길 10, 3층 (봉천동)8784굿모닝안마원2017-07-05 09:44:48I2018-08-31 23:59:59.0안마원194912.547175442169.547274안마원1<NA><NA><NA><NA><NA><NA>50.0
263200000PHMB42014320003304240000220140819<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>151711서울특별시 관악구 신림동 86번지 3호서울특별시 관악구 신림로 318, 6층 (신림동)8777윤앤안마원2021-07-07 17:52:22U2021-07-09 02:40:00.0안마원193773.070404442270.419249안마원0000000.048.1
273200000PHMB42015320003304240000120150819<NA>3폐업3폐업20171106<NA><NA><NA>883-1803<NA><NA>서울특별시 관악구 신림동 1432번지 76호서울특별시 관악구 신림로 344, 3층 303호 (신림동, SK허브그린)8754다온건강안마원2017-11-06 17:09:10I2018-08-31 23:59:59.0안마원193671.180923442608.256981안마원1<NA><NA><NA><NA>0<NA>72.5
283200000PHMB42015320003304240000220151021<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6494-1119<NA><NA>서울특별시 관악구 봉천동 1686번지 21호 호전크리닉스타워서울특별시 관악구 남부순환로 1925, 호전크리닉스타워 301호 (봉천동)8801관악보건안마원2021-07-07 17:49:48U2021-07-09 02:40:00.0안마원196683.467111441709.675837안마원4000000.086.66
293200000PHMB42016320003304240000120160622<NA>3폐업3폐업20160908<NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1601번지 22호서울특별시 관악구 남부순환로 1852, 4층 (봉천동)8789명진안마원2016-09-09 09:12:52I2018-08-31 23:59:59.0안마원195998.790182441971.086567안마원1<NA><NA><NA><NA><NA><NA>68.0
303200000PHMB42017320003304240000120170120<NA>1영업/정상13영업중<NA><NA><NA><NA>02-878-1275<NA><NA>서울특별시 관악구 봉천동 862번지 10호서울특별시 관악구 관악로15길 6, 4층 (봉천동)8787바른손길안마원2017-02-01 11:48:29I2018-08-31 23:59:59.0안마원195689.700662442020.136028안마원<NA><NA><NA><NA><NA><NA><NA>153.8
313200000PHMB4201732000330424000022017-02-08<NA>3폐업3폐업2023-02-06<NA><NA><NA>02-889-7577<NA><NA>서울특별시 관악구 신림동 1417번지 15호서울특별시 관악구 신림로68길 29, 2층 (신림동)8753오 안마원2023-02-07 17:56:08U2022-12-02 00:09:00.0안마원193827.523355442739.354185<NA><NA><NA><NA><NA><NA><NA><NA><NA>
323200000PHMB42017320003304240000320171208<NA>1영업/정상13영업중<NA><NA><NA><NA>070-8861-1515<NA><NA>서울특별시 관악구 봉천동 1688번지 125호서울특별시 관악구 남부순환로 1943, 2층 (봉천동)8801YG힐링안마원2017-12-13 10:56:22I2018-08-31 23:59:59.0안마원196846.248376441616.720857안마원1<NA><NA><NA><NA><NA><NA>64.8
333200000PHMB42018320003304240000120181109<NA>3폐업3폐업20211005<NA><NA><NA>02-6408-8868<NA><NA>서울특별시 관악구 봉천동 1667번지 30호서울특별시 관악구 봉천로 493, 3층 (봉천동)8737정체안마원2021-12-14 18:00:28U2021-12-16 02:40:00.0안마원195928.118732442168.066143안마원1000020.048.38
343200000PHMB42020320003304240000120201228<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 36-14서울특별시 관악구 관악로 234, 2층 (봉천동)8737찐지압안마원2020-12-31 14:39:41I2021-01-02 00:23:15.0안마원196069.172604442529.733049안마원1<NA><NA><NA><NA>3<NA>59.84