Overview

Dataset statistics

Number of variables34
Number of observations24
Missing cells117
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory297.5 B

Variable types

Categorical15
Text6
DateTime3
Unsupported3
Numeric7

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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-16371/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (62.9%)Imbalance
휴업종료일자 is highly imbalanced (62.9%)Imbalance
자격증소유자수 is highly imbalanced (75.0%)Imbalance
보조종업원수 is highly imbalanced (75.0%)Imbalance
시설관리자수 is highly imbalanced (75.0%)Imbalance
기타종업원수 is highly imbalanced (75.0%)Imbalance
인허가취소일자 has 24 (100.0%) missing valuesMissing
폐업일자 has 10 (41.7%) missing valuesMissing
재개업일자 has 24 (100.0%) missing valuesMissing
전화번호 has 2 (8.3%) missing valuesMissing
소재지면적 has 24 (100.0%) missing valuesMissing
소재지우편번호 has 8 (33.3%) missing valuesMissing
도로명주소 has 1 (4.2%) missing valuesMissing
도로명우편번호 has 6 (25.0%) missing valuesMissing
종업원수 has 5 (20.8%) missing valuesMissing
병상수 has 9 (37.5%) missing valuesMissing
총면적 has 4 (16.7%) missing valuesMissing
관리번호 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
종업원수 has 3 (12.5%) zerosZeros
병상수 has 1 (4.2%) zerosZeros

Reproduction

Analysis started2024-05-11 00:51:35.835690
Analysis finished2024-05-11 00:51:36.654852
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
3130000
24 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 24
100.0%

Length

2024-05-11T00:51:36.850015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:37.143525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 24
100.0%

관리번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-05-11T00:51:37.710432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters600
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

Unique24 ?
Unique (%)100.0%

Sample

1st rowPHMB419923130033042400001
2nd rowPHMB419963130033042400001
3rd rowPHMB419963130033042400002
4th rowPHMB419963130033042400003
5th rowPHMB420003130033042400001
ValueCountFrequency (%)
phmb419923130033042400001 1
 
4.2%
phmb419963130033042400001 1
 
4.2%
phmb420183130033042400001 1
 
4.2%
phmb420173130033042400001 1
 
4.2%
phmb420163130033042400001 1
 
4.2%
phmb420153130033042400002 1
 
4.2%
phmb420153130033042400001 1
 
4.2%
phmb420143130033042400002 1
 
4.2%
phmb420143130033042400001 1
 
4.2%
phmb420133130033042400002 1
 
4.2%
Other values (14) 14
58.3%
2024-05-11T00:51:38.883768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 198
33.0%
3 100
16.7%
4 75
 
12.5%
1 59
 
9.8%
2 54
 
9.0%
P 24
 
4.0%
H 24
 
4.0%
M 24
 
4.0%
B 24
 
4.0%
9 9
 
1.5%
Other values (4) 9
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
84.0%
Uppercase Letter 96
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 198
39.3%
3 100
19.8%
4 75
 
14.9%
1 59
 
11.7%
2 54
 
10.7%
9 9
 
1.8%
6 5
 
1.0%
5 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
P 24
25.0%
H 24
25.0%
M 24
25.0%
B 24
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 504
84.0%
Latin 96
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 198
39.3%
3 100
19.8%
4 75
 
14.9%
1 59
 
11.7%
2 54
 
10.7%
9 9
 
1.8%
6 5
 
1.0%
5 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
Latin
ValueCountFrequency (%)
P 24
25.0%
H 24
25.0%
M 24
25.0%
B 24
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 198
33.0%
3 100
16.7%
4 75
 
12.5%
1 59
 
9.8%
2 54
 
9.0%
P 24
 
4.0%
H 24
 
4.0%
M 24
 
4.0%
B 24
 
4.0%
9 9
 
1.5%
Other values (4) 9
 
1.5%

인허가일자
Date

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum1992-03-18 00:00:00
Maximum2022-09-21 00:00:00
2024-05-11T00:51:39.521007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:51:40.138724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
3
13 
1
10 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
3 13
54.2%
1 10
41.7%
4 1
 
4.2%

Length

2024-05-11T00:51:40.678615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:40.974970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 13
54.2%
1 10
41.7%
4 1
 
4.2%

영업상태명
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
폐업
13 
영업/정상
10 
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length3.75
Min length2

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 13
54.2%
영업/정상 10
41.7%
취소/말소/만료/정지/중지 1
 
4.2%

Length

2024-05-11T00:51:41.323433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:41.650652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 13
54.2%
영업/정상 10
41.7%
취소/말소/만료/정지/중지 1
 
4.2%

상세영업상태코드
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
3
13 
13
10 
24
 
1

Length

Max length2
Median length1
Mean length1.4583333
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row3
2nd row24
3rd row3
4th row13
5th row3

Common Values

ValueCountFrequency (%)
3 13
54.2%
13 10
41.7%
24 1
 
4.2%

Length

2024-05-11T00:51:42.027734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:42.357780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 13
54.2%
13 10
41.7%
24 1
 
4.2%

상세영업상태명
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
폐업
13 
영업중
10 
직권폐업
 
1

Length

Max length4
Median length2
Mean length2.5
Min length2

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 13
54.2%
영업중 10
41.7%
직권폐업 1
 
4.2%

Length

2024-05-11T00:51:42.737540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:43.096917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 13
54.2%
영업중 10
41.7%
직권폐업 1
 
4.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)100.0%
Missing10
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean20139850
Minimum20090610
Maximum20220713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:51:43.425748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090610
5-th percentile20096786
Q120103257
median20120767
Q320168162
95-th percentile20214149
Maximum20220713
Range130103
Interquartile range (IQR)64904.75

Descriptive statistics

Standard deviation44120.27
Coefficient of variation (CV)0.0021906951
Kurtosis-0.91361445
Mean20139850
Median Absolute Deviation (MAD)25250.5
Skewness0.70114007
Sum2.8195789 × 108
Variance1.9465982 × 109
MonotonicityNot monotonic
2024-05-11T00:51:43.880563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20100909 1
 
4.2%
20220713 1
 
4.2%
20100218 1
 
4.2%
20110721 1
 
4.2%
20100111 1
 
4.2%
20210614 1
 
4.2%
20090610 1
 
4.2%
20110302 1
 
4.2%
20190117 1
 
4.2%
20111018 1
 
4.2%
Other values (4) 4
 
16.7%
(Missing) 10
41.7%
ValueCountFrequency (%)
20090610 1
4.2%
20100111 1
4.2%
20100218 1
4.2%
20100909 1
4.2%
20110302 1
4.2%
20110721 1
4.2%
20111018 1
4.2%
20130516 1
4.2%
20150612 1
4.2%
20160824 1
4.2%
ValueCountFrequency (%)
20220713 1
4.2%
20210614 1
4.2%
20190117 1
4.2%
20170608 1
4.2%
20160824 1
4.2%
20150612 1
4.2%
20130516 1
4.2%
20111018 1
4.2%
20110721 1
4.2%
20110302 1
4.2%

휴업시작일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
21 
20100422
 
1
20090220
 
1
20181001
 
1

Length

Max length8
Median length4
Mean length4.5
Min length4

Unique

Unique3 ?
Unique (%)12.5%

Sample

1st row20100422
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 21
87.5%
20100422 1
 
4.2%
20090220 1
 
4.2%
20181001 1
 
4.2%

Length

2024-05-11T00:51:44.403486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:44.963782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
87.5%
20100422 1
 
4.2%
20090220 1
 
4.2%
20181001 1
 
4.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
21 
20110131
 
1
20090930
 
1
20190930
 
1

Length

Max length8
Median length4
Mean length4.5
Min length4

Unique

Unique3 ?
Unique (%)12.5%

Sample

1st row20110131
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 21
87.5%
20110131 1
 
4.2%
20090930 1
 
4.2%
20190930 1
 
4.2%

Length

2024-05-11T00:51:45.366393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:45.788425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
87.5%
20110131 1
 
4.2%
20090930 1
 
4.2%
20190930 1
 
4.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

전화번호
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing2
Missing (%)8.3%
Memory size324.0 B
2024-05-11T00:51:46.221982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.6363636
Min length8

Characters and Unicode

Total characters212
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

Unique20 ?
Unique (%)90.9%

Sample

1st row701-5541
2nd row02-702-3266
3rd row02-701-5541
4th row02-322-2258
5th row02-718-6454
ValueCountFrequency (%)
333-8821 2
 
9.1%
711-7575 1
 
4.5%
701-5541 1
 
4.5%
332-2809 1
 
4.5%
1670-3175 1
 
4.5%
365-2225 1
 
4.5%
02-703-7959 1
 
4.5%
02-2275-0675 1
 
4.5%
335-1009 1
 
4.5%
719-2234 1
 
4.5%
Other values (11) 11
50.0%
2024-05-11T00:51:47.136805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 35
16.5%
- 33
15.6%
3 28
13.2%
7 21
9.9%
0 20
9.4%
5 20
9.4%
1 18
8.5%
8 13
 
6.1%
6 10
 
4.7%
9 8
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 179
84.4%
Dash Punctuation 33
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 35
19.6%
3 28
15.6%
7 21
11.7%
0 20
11.2%
5 20
11.2%
1 18
10.1%
8 13
 
7.3%
6 10
 
5.6%
9 8
 
4.5%
4 6
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 35
16.5%
- 33
15.6%
3 28
13.2%
7 21
9.9%
0 20
9.4%
5 20
9.4%
1 18
8.5%
8 13
 
6.1%
6 10
 
4.7%
9 8
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 35
16.5%
- 33
15.6%
3 28
13.2%
7 21
9.9%
0 20
9.4%
5 20
9.4%
1 18
8.5%
8 13
 
6.1%
6 10
 
4.7%
9 8
 
3.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

소재지우편번호
Text

MISSING 

Distinct12
Distinct (%)75.0%
Missing8
Missing (%)33.3%
Memory size324.0 B
2024-05-11T00:51:47.568068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0625
Min length6

Characters and Unicode

Total characters97
Distinct characters10
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

Unique8 ?
Unique (%)50.0%

Sample

1st row121100
2nd row121100
3rd row121020
4th row121-210
5th row121040
ValueCountFrequency (%)
121100 2
12.5%
121040 2
12.5%
121838 2
12.5%
121030 2
12.5%
121020 1
6.2%
121-210 1
6.2%
121845 1
6.2%
121210 1
6.2%
121869 1
6.2%
121809 1
6.2%
Other values (2) 2
12.5%
2024-05-11T00:51:48.382231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 37
38.1%
2 19
19.6%
0 19
19.6%
8 9
 
9.3%
3 4
 
4.1%
4 3
 
3.1%
5 2
 
2.1%
9 2
 
2.1%
- 1
 
1.0%
6 1
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
99.0%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
38.5%
2 19
19.8%
0 19
19.8%
8 9
 
9.4%
3 4
 
4.2%
4 3
 
3.1%
5 2
 
2.1%
9 2
 
2.1%
6 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37
38.1%
2 19
19.6%
0 19
19.6%
8 9
 
9.3%
3 4
 
4.1%
4 3
 
3.1%
5 2
 
2.1%
9 2
 
2.1%
- 1
 
1.0%
6 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37
38.1%
2 19
19.6%
0 19
19.6%
8 9
 
9.3%
3 4
 
4.1%
4 3
 
3.1%
5 2
 
2.1%
9 2
 
2.1%
- 1
 
1.0%
6 1
 
1.0%

지번주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-05-11T00:51:48.964785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27.5
Mean length25.708333
Min length19

Characters and Unicode

Total characters617
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row서울특별시 마포구 노고산동 106번지 43호
2nd row서울특별시 마포구 노고산동 106번지 52호
3rd row서울특별시 마포구 공덕동 237번지 8호
4th row서울특별시 마포구 서교동 354번지 12호
5th row서울특별시 마포구 도화동 183번지 15호 2층
ValueCountFrequency (%)
서울특별시 24
17.9%
마포구 24
17.9%
2층 6
 
4.5%
서교동 5
 
3.7%
8호 3
 
2.2%
연남동 3
 
2.2%
1층 3
 
2.2%
354번지 3
 
2.2%
도화동 3
 
2.2%
신공덕동 3
 
2.2%
Other values (50) 57
42.5%
2024-05-11T00:51:50.287282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
 
17.8%
서 30
 
4.9%
시 25
 
4.1%
동 24
 
3.9%
특 24
 
3.9%
별 24
 
3.9%
마 24
 
3.9%
포 24
 
3.9%
구 24
 
3.9%
울 24
 
3.9%
Other values (49) 284
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 360
58.3%
Decimal Number 129
 
20.9%
Space Separator 110
 
17.8%
Open Punctuation 7
 
1.1%
Close Punctuation 7
 
1.1%
Other Punctuation 3
 
0.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 30
 
8.3%
시 25
 
6.9%
동 24
 
6.7%
특 24
 
6.7%
별 24
 
6.7%
마 24
 
6.7%
포 24
 
6.7%
구 24
 
6.7%
울 24
 
6.7%
지 22
 
6.1%
Other values (34) 115
31.9%
Decimal Number
ValueCountFrequency (%)
2 23
17.8%
1 23
17.8%
4 16
12.4%
3 16
12.4%
5 14
10.9%
8 10
7.8%
6 10
7.8%
0 9
 
7.0%
7 4
 
3.1%
9 4
 
3.1%
Space Separator
ValueCountFrequency (%)
110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 360
58.3%
Common 257
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 30
 
8.3%
시 25
 
6.9%
동 24
 
6.7%
특 24
 
6.7%
별 24
 
6.7%
마 24
 
6.7%
포 24
 
6.7%
구 24
 
6.7%
울 24
 
6.7%
지 22
 
6.1%
Other values (34) 115
31.9%
Common
ValueCountFrequency (%)
110
42.8%
2 23
 
8.9%
1 23
 
8.9%
4 16
 
6.2%
3 16
 
6.2%
5 14
 
5.4%
8 10
 
3.9%
6 10
 
3.9%
0 9
 
3.5%
( 7
 
2.7%
Other values (5) 19
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 360
58.3%
ASCII 257
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
42.8%
2 23
 
8.9%
1 23
 
8.9%
4 16
 
6.2%
3 16
 
6.2%
5 14
 
5.4%
8 10
 
3.9%
6 10
 
3.9%
0 9
 
3.5%
( 7
 
2.7%
Other values (5) 19
 
7.4%
Hangul
ValueCountFrequency (%)
서 30
 
8.3%
시 25
 
6.9%
동 24
 
6.7%
특 24
 
6.7%
별 24
 
6.7%
마 24
 
6.7%
포 24
 
6.7%
구 24
 
6.7%
울 24
 
6.7%
지 22
 
6.1%
Other values (34) 115
31.9%

도로명주소
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing1
Missing (%)4.2%
Memory size324.0 B
2024-05-11T00:51:50.978633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length33
Mean length28.826087
Min length23

Characters and Unicode

Total characters663
Distinct characters81
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

Unique23 ?
Unique (%)100.0%

Sample

1st row서울특별시 마포구 서강로18길 15 (노고산동)
2nd row서울특별시 마포구 백범로4길 12 (노고산동)
3rd row서울특별시 마포구 마포대로 156 (공덕동)
4th row서울특별시 마포구 양화로 118 (서교동)
5th row서울특별시 마포구 새창로 16 (도화동,2층)
ValueCountFrequency (%)
서울특별시 23
 
17.2%
마포구 23
 
17.2%
2층 8
 
6.0%
서교동 4
 
3.0%
양화로 4
 
3.0%
신공덕동 3
 
2.2%
8 2
 
1.5%
월드컵북로 2
 
1.5%
연남동 2
 
1.5%
도화동 2
 
1.5%
Other values (55) 61
45.5%
2024-05-11T00:51:52.252638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
 
16.7%
서 31
 
4.7%
2 26
 
3.9%
시 25
 
3.8%
마 25
 
3.8%
포 25
 
3.8%
) 25
 
3.8%
( 25
 
3.8%
동 24
 
3.6%
특 23
 
3.5%
Other values (71) 323
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
58.8%
Space Separator 111
 
16.7%
Decimal Number 89
 
13.4%
Close Punctuation 25
 
3.8%
Open Punctuation 25
 
3.8%
Other Punctuation 20
 
3.0%
Dash Punctuation 2
 
0.3%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 31
 
7.9%
시 25
 
6.4%
마 25
 
6.4%
포 25
 
6.4%
동 24
 
6.2%
특 23
 
5.9%
별 23
 
5.9%
구 23
 
5.9%
울 23
 
5.9%
로 20
 
5.1%
Other values (55) 148
37.9%
Decimal Number
ValueCountFrequency (%)
2 26
29.2%
1 23
25.8%
3 7
 
7.9%
5 7
 
7.9%
8 7
 
7.9%
7 5
 
5.6%
0 4
 
4.5%
6 4
 
4.5%
4 4
 
4.5%
9 2
 
2.2%
Space Separator
ValueCountFrequency (%)
111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
58.8%
Common 272
41.0%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 31
 
7.9%
시 25
 
6.4%
마 25
 
6.4%
포 25
 
6.4%
동 24
 
6.2%
특 23
 
5.9%
별 23
 
5.9%
구 23
 
5.9%
울 23
 
5.9%
로 20
 
5.1%
Other values (55) 148
37.9%
Common
ValueCountFrequency (%)
111
40.8%
2 26
 
9.6%
) 25
 
9.2%
( 25
 
9.2%
1 23
 
8.5%
, 20
 
7.4%
3 7
 
2.6%
5 7
 
2.6%
8 7
 
2.6%
7 5
 
1.8%
Other values (5) 16
 
5.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
58.8%
ASCII 273
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
40.7%
2 26
 
9.5%
) 25
 
9.2%
( 25
 
9.2%
1 23
 
8.4%
, 20
 
7.3%
3 7
 
2.6%
5 7
 
2.6%
8 7
 
2.6%
7 5
 
1.8%
Other values (6) 17
 
6.2%
Hangul
ValueCountFrequency (%)
서 31
 
7.9%
시 25
 
6.4%
마 25
 
6.4%
포 25
 
6.4%
동 24
 
6.2%
특 23
 
5.9%
별 23
 
5.9%
구 23
 
5.9%
울 23
 
5.9%
로 20
 
5.1%
Other values (55) 148
37.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)88.9%
Missing6
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean23694.611
Minimum3946
Maximum121865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:51:52.779992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3946
5-th percentile3946.85
Q14032.75
median4070
Q34185.5
95-th percentile121812.3
Maximum121865
Range117919
Interquartile range (IQR)152.75

Descriptive statistics

Standard deviation45156.995
Coefficient of variation (CV)1.9057918
Kurtosis2.039975
Mean23694.611
Median Absolute Deviation (MAD)85.5
Skewness1.9557487
Sum426503
Variance2.0391542 × 109
MonotonicityNot monotonic
2024-05-11T00:51:53.233283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4038 2
 
8.3%
121803 2
 
8.3%
4172 1
 
4.2%
3986 1
 
4.2%
4025 1
 
4.2%
4071 1
 
4.2%
4157 1
 
4.2%
4044 1
 
4.2%
4109 1
 
4.2%
4190 1
 
4.2%
Other values (6) 6
25.0%
(Missing) 6
25.0%
ValueCountFrequency (%)
3946 1
4.2%
3947 1
4.2%
3986 1
4.2%
4025 1
4.2%
4031 1
4.2%
4038 2
8.3%
4044 1
4.2%
4069 1
4.2%
4071 1
4.2%
4109 1
4.2%
ValueCountFrequency (%)
121865 1
4.2%
121803 2
8.3%
4209 1
4.2%
4190 1
4.2%
4172 1
4.2%
4157 1
4.2%
4109 1
4.2%
4071 1
4.2%
4069 1
4.2%
4044 1
4.2%

사업장명
Text

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-05-11T00:51:53.785596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.4166667
Min length5

Characters and Unicode

Total characters178
Distinct characters63
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)83.3%

Sample

1st row상상안마시술소
2nd row엔젤안마시술소
3rd row나이스안마시술소
4th row상상안마시술소
5th row대원안마원
ValueCountFrequency (%)
상상안마시술소 2
 
8.3%
여광안마원 2
 
8.3%
약손척추건강안마원 1
 
4.2%
맑은손안마원 1
 
4.2%
참손길안마원 1
 
4.2%
수안마힐링센터안마원 1
 
4.2%
바른마사지마마안마원 1
 
4.2%
키프러스안마원 1
 
4.2%
ojs치유안마원 1
 
4.2%
밀알안마원 1
 
4.2%
Other values (12) 12
50.0%
2024-05-11T00:51:54.700592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 30
16.9%
안 25
 
14.0%
원 17
 
9.6%
시 8
 
4.5%
술 8
 
4.5%
소 8
 
4.5%
손 5
 
2.8%
상 4
 
2.2%
지 4
 
2.2%
스 3
 
1.7%
Other values (53) 66
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
98.3%
Uppercase Letter 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 30
17.1%
안 25
 
14.3%
원 17
 
9.7%
시 8
 
4.6%
술 8
 
4.6%
소 8
 
4.6%
손 5
 
2.9%
상 4
 
2.3%
지 4
 
2.3%
스 3
 
1.7%
Other values (50) 63
36.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
33.3%
S 1
33.3%
O 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
98.3%
Latin 3
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 30
17.1%
안 25
 
14.3%
원 17
 
9.7%
시 8
 
4.6%
술 8
 
4.6%
소 8
 
4.6%
손 5
 
2.9%
상 4
 
2.3%
지 4
 
2.3%
스 3
 
1.7%
Other values (50) 63
36.0%
Latin
ValueCountFrequency (%)
J 1
33.3%
S 1
33.3%
O 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
98.3%
ASCII 3
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 30
17.1%
안 25
 
14.3%
원 17
 
9.7%
시 8
 
4.6%
술 8
 
4.6%
소 8
 
4.6%
손 5
 
2.9%
상 4
 
2.3%
지 4
 
2.3%
스 3
 
1.7%
Other values (50) 63
36.0%
ASCII
ValueCountFrequency (%)
J 1
33.3%
S 1
33.3%
O 1
33.3%

최종수정일자
Date

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2009-06-10 11:53:17
Maximum2023-12-28 17:34:36
2024-05-11T00:51:55.083909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:51:55.495434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

데이터갱신구분
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
I
12 
U
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 12
50.0%
U 12
50.0%

Length

2024-05-11T00:51:55.887254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:56.190886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 12
50.0%
u 12
50.0%

데이터갱신일자
Date

Distinct12
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2018-08-31 23:59:59
Maximum2022-12-05 22:09:00
2024-05-11T00:51:56.482040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:51:56.901698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

업태구분명
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
안마원
16 
안마시술소
8 

Length

Max length5
Median length3
Mean length3.6666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 16
66.7%
안마시술소 8
33.3%

Length

2024-05-11T00:51:57.317508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:57.661952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 16
66.7%
안마시술소 8
33.3%

좌표정보(X)
Real number (ℝ)

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193950.51
Minimum191837.77
Maximum196105.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:51:58.007720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191837.77
5-th percentile191924.28
Q1192826.92
median193480.34
Q3195413.26
95-th percentile196004.33
Maximum196105.24
Range4267.4684
Interquartile range (IQR)2586.3394

Descriptive statistics

Standard deviation1513.3964
Coefficient of variation (CV)0.007803003
Kurtosis-1.60997
Mean193950.51
Median Absolute Deviation (MAD)1271.3198
Skewness0.18200518
Sum4654812.3
Variance2290368.8
MonotonicityNot monotonic
2024-05-11T00:51:58.400577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
192912.154802425 2
 
8.3%
194261.110714031 1
 
4.2%
195914.923352729 1
 
4.2%
192665.991384091 1
 
4.2%
192085.129733942 1
 
4.2%
192332.918156777 1
 
4.2%
195322.033365468 1
 
4.2%
192513.424097452 1
 
4.2%
195331.300013874 1
 
4.2%
196105.23515064 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
191837.766772128 1
4.2%
191895.890184857 1
4.2%
192085.129733942 1
4.2%
192332.918156777 1
4.2%
192513.424097452 1
4.2%
192665.991384091 1
4.2%
192880.563694394 1
4.2%
192912.154802425 2
8.3%
192922.43605265 1
4.2%
193086.171639658 1
4.2%
ValueCountFrequency (%)
196105.23515064 1
4.2%
196010.78484327 1
4.2%
195967.719264 1
4.2%
195914.923352729 1
4.2%
195800.599942295 1
4.2%
195659.139970782 1
4.2%
195331.300013874 1
4.2%
195322.033365468 1
4.2%
195120.319425726 1
4.2%
194313.827747207 1
4.2%

좌표정보(Y)
Real number (ℝ)

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449954.33
Minimum448440.24
Maximum451762.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:51:58.792907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448440.24
5-th percentile448878.3
Q1449314.79
median449952.54
Q3450247.65
95-th percentile451557.82
Maximum451762.03
Range3321.7941
Interquartile range (IQR)932.85855

Descriptive statistics

Standard deviation860.55148
Coefficient of variation (CV)0.0019125307
Kurtosis-0.18204912
Mean449954.33
Median Absolute Deviation (MAD)543.53488
Skewness0.41765004
Sum10798904
Variance740548.85
MonotonicityNot monotonic
2024-05-11T00:51:59.173335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
450205.198838492 2
 
8.3%
450119.412610839 1
 
4.2%
449189.54568232 1
 
4.2%
450740.174633182 1
 
4.2%
449814.144425494 1
 
4.2%
449461.477885688 1
 
4.2%
448969.110547126 1
 
4.2%
449835.228830529 1
 
4.2%
448440.238743443 1
 
4.2%
448981.224199565 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
448440.238743443 1
4.2%
448862.272845142 1
4.2%
448969.110547126 1
4.2%
448981.224199565 1
4.2%
449069.861416806 1
4.2%
449189.54568232 1
4.2%
449356.535303765 1
4.2%
449461.477885688 1
4.2%
449568.977982811 1
4.2%
449814.144425494 1
4.2%
ValueCountFrequency (%)
451762.032886314 1
4.2%
451648.739175972 1
4.2%
451042.613331402 1
4.2%
450993.844393427 1
4.2%
450740.174633182 1
4.2%
450354.860685834 1
4.2%
450211.908368102 1
4.2%
450205.198838492 2
8.3%
450175.878676492 1
4.2%
450119.412610839 1
4.2%

의료유사업종별명
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
안마원
14 
안마시술소
6 
<NA>
4 

Length

Max length5
Median length3
Mean length3.6666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 14
58.3%
안마시술소 6
25.0%
<NA> 4
 
16.7%

Length

2024-05-11T00:51:59.774313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:52:00.145085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 14
58.3%
안마시술소 6
25.0%
na 4
 
16.7%

종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)31.6%
Missing5
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean1.7894737
Minimum0
Maximum9
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:52:00.432426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile5.4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.09706
Coefficient of variation (CV)1.1718865
Kurtosis7.8474188
Mean1.7894737
Median Absolute Deviation (MAD)1
Skewness2.613506
Sum34
Variance4.3976608
MonotonicityNot monotonic
2024-05-11T00:52:00.765470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 9
37.5%
2 4
16.7%
0 3
 
12.5%
9 1
 
4.2%
5 1
 
4.2%
3 1
 
4.2%
(Missing) 5
20.8%
ValueCountFrequency (%)
0 3
 
12.5%
1 9
37.5%
2 4
16.7%
3 1
 
4.2%
5 1
 
4.2%
9 1
 
4.2%
ValueCountFrequency (%)
9 1
 
4.2%
5 1
 
4.2%
3 1
 
4.2%
2 4
16.7%
1 9
37.5%
0 3
 
12.5%

자격증소유자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
23 
0
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
95.8%
0 1
 
4.2%

Length

2024-05-11T00:52:01.112268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:52:01.409934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
95.8%
0 1
 
4.2%

보조종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
23 
0
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
95.8%
0 1
 
4.2%

Length

2024-05-11T00:52:01.739368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:52:02.057844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
95.8%
0 1
 
4.2%

시설관리자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
23 
0
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
95.8%
0 1
 
4.2%

Length

2024-05-11T00:52:02.408562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:52:02.731179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
95.8%
0 1
 
4.2%

기타종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
23 
0
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
95.8%
0 1
 
4.2%

Length

2024-05-11T00:52:03.130021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:52:03.452190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
95.8%
0 1
 
4.2%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)60.0%
Missing9
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean6.7333333
Minimum0
Maximum27
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:52:03.745792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q11
median1
Q39.5
95-th percentile22.8
Maximum27
Range27
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation8.6970165
Coefficient of variation (CV)1.2916361
Kurtosis0.77727992
Mean6.7333333
Median Absolute Deviation (MAD)1
Skewness1.3790975
Sum101
Variance75.638095
MonotonicityNot monotonic
2024-05-11T00:52:04.155772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 7
29.2%
21 1
 
4.2%
27 1
 
4.2%
8 1
 
4.2%
18 1
 
4.2%
7 1
 
4.2%
11 1
 
4.2%
0 1
 
4.2%
2 1
 
4.2%
(Missing) 9
37.5%
ValueCountFrequency (%)
0 1
 
4.2%
1 7
29.2%
2 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
11 1
 
4.2%
18 1
 
4.2%
21 1
 
4.2%
27 1
 
4.2%
ValueCountFrequency (%)
27 1
 
4.2%
21 1
 
4.2%
18 1
 
4.2%
11 1
 
4.2%
8 1
 
4.2%
7 1
 
4.2%
2 1
 
4.2%
1 7
29.2%
0 1
 
4.2%

욕실면적
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
19 
0
5 

Length

Max length4
Median length4
Mean length3.375
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> 19
79.2%
0 5
 
20.8%

Length

2024-05-11T00:52:04.644550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:52:04.942586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
79.2%
0 5
 
20.8%

총면적
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing4
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean152.175
Minimum10.97
Maximum517.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-05-11T00:52:05.229980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.97
5-th percentile24.6215
Q148.7875
median85.56
Q3234.4075
95-th percentile515.2375
Maximum517.66
Range506.69
Interquartile range (IQR)185.62

Descriptive statistics

Standard deviation154.87547
Coefficient of variation (CV)1.0177458
Kurtosis1.2668712
Mean152.175
Median Absolute Deviation (MAD)46.19
Skewness1.4601568
Sum3043.5
Variance23986.411
MonotonicityNot monotonic
2024-05-11T00:52:05.605718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
83.78 1
 
4.2%
51.05 1
 
4.2%
123.58 1
 
4.2%
58.18 1
 
4.2%
118.59 1
 
4.2%
124.14 1
 
4.2%
54.93 1
 
4.2%
10.97 1
 
4.2%
87.34 1
 
4.2%
334.0 1
 
4.2%
Other values (10) 10
41.7%
(Missing) 4
 
16.7%
ValueCountFrequency (%)
10.97 1
4.2%
25.34 1
4.2%
34.04 1
4.2%
36.74 1
4.2%
42.0 1
4.2%
51.05 1
4.2%
54.93 1
4.2%
58.18 1
4.2%
60.3 1
4.2%
83.78 1
4.2%
ValueCountFrequency (%)
517.66 1
4.2%
515.11 1
4.2%
334.0 1
4.2%
279.0 1
4.2%
261.31 1
4.2%
225.44 1
4.2%
124.14 1
4.2%
123.58 1
4.2%
118.59 1
4.2%
87.34 1
4.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03130000PHMB41992313003304240000119920318<NA>3폐업3폐업201009092010042220110131<NA>701-5541<NA>121100서울특별시 마포구 노고산동 106번지 43호서울특별시 마포구 서강로18길 15 (노고산동)<NA>상상안마시술소2010-09-09 17:33:51I2018-08-31 23:59:59.0안마시술소194261.110714450119.412611안마시술소2<NA><NA><NA><NA>21<NA>334.0
13130000PHMB41996313003304240000119960626<NA>4취소/말소/만료/정지/중지24직권폐업20220713<NA><NA><NA>02-702-3266<NA>121100서울특별시 마포구 노고산동 106번지 52호서울특별시 마포구 백범로4길 12 (노고산동)4109엔젤안마시술소2022-07-15 15:24:57U2021-12-06 23:07:00.0안마시술소194313.827747450069.854126<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23130000PHMB41996313003304240000219960626<NA>3폐업3폐업20100218<NA><NA><NA>02-701-5541<NA>121020서울특별시 마포구 공덕동 237번지 8호서울특별시 마포구 마포대로 156 (공덕동)121803나이스안마시술소2010-02-18 17:16:16I2018-08-31 23:59:59.0안마시술소195967.719264449825.655955안마시술소9<NA><NA><NA><NA>27<NA>517.66
33130000PHMB4199631300330424000031996-12-03<NA>1영업/정상13영업중<NA><NA><NA><NA>02-322-2258<NA>121-210서울특별시 마포구 서교동 354번지 12호서울특별시 마포구 양화로 118 (서교동)4038상상안마시술소2023-12-28 17:34:36U2022-11-01 21:00:00.0안마시술소192880.563694450175.878676<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43130000PHMB42000313003304240000120000325<NA>3폐업3폐업20110721<NA><NA><NA>02-718-6454<NA>121040서울특별시 마포구 도화동 183번지 15호 2층서울특별시 마포구 새창로 16 (도화동,2층)<NA>대원안마원2011-07-21 11:58:42I2018-08-31 23:59:59.0안마원195659.139971448862.272845안마원1<NA><NA><NA><NA>1<NA>36.74
53130000PHMB42000313003304240000220000808<NA>1영업/정상13영업중<NA><NA><NA><NA>02-372-4126<NA>121845서울특별시 마포구 성산2동 200번지 81호서울특별시 마포구 월드컵북로27길 10 (성산동)3947성산안마원2011-12-28 17:50:05I2018-08-31 23:59:59.0안마원191895.890185451648.739176안마원1<NA><NA><NA><NA>1<NA>25.34
63130000PHMB42004313003304240000120040831<NA>3폐업3폐업20100111<NA><NA><NA>02-337-7822<NA>121210서울특별시 마포구 서교동 354번지 8호 3층서울특별시 마포구 양화로 122 (서교동,3층)<NA>폭스안마시술소2010-01-11 17:14:34I2018-08-31 23:59:59.0안마시술소192912.154802450205.198838안마시술소2<NA><NA><NA><NA>8<NA>261.31
73130000PHMB42006313003304240000120060327<NA>3폐업3폐업20210614<NA><NA><NA>02-335-5633<NA>121838서울특별시 마포구 서교동 351번지 19호 (2, 3, 4층)서울특별시 마포구 월드컵북로1길 6, 2,3,4층 (서교동)4031서교안마시술소2021-06-15 09:29:41U2021-06-17 02:40:00.0안마시술소192922.436053450354.860686안마시술소5<NA><NA><NA><NA>18<NA>515.11
83130000PHMB42009313003304240000120020529<NA>3폐업3폐업200906102009022020090930<NA>3211-8989<NA>121030서울특별시 마포구 신공덕동 26번지 4호서울특별시 마포구 만리재로 20-9 (신공덕동)<NA>마포안마시술소2009-06-10 11:53:17I2018-08-31 23:59:59.0안마시술소195800.599942449069.861417안마시술소3<NA><NA><NA><NA>7<NA>225.44
93130000PHMB42010313003304240000120100111<NA>3폐업3폐업20110302<NA><NA><NA>333-8821<NA>121869서울특별시 마포구 연남동 566번지 64호 (1층)서울특별시 마포구 연남로 17 (연남동,(1층))<NA>여광안마원2011-03-02 17:18:31I2018-08-31 23:59:59.0안마원193086.17164450993.844393안마원1<NA><NA><NA><NA>1<NA>34.04
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
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