Overview

Dataset statistics

Number of variables34
Number of observations21
Missing cells97
Missing cells (%)13.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory298.3 B

Variable types

Categorical16
Text6
DateTime3
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-16368/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (65.4%)Imbalance
휴업종료일자 is highly imbalanced (65.4%)Imbalance
자격증소유자수 is highly imbalanced (54.6%)Imbalance
보조종업원수 is highly imbalanced (54.6%)Imbalance
시설관리자수 is highly imbalanced (54.6%)Imbalance
기타종업원수 is highly imbalanced (54.6%)Imbalance
인허가취소일자 has 21 (100.0%) missing valuesMissing
폐업일자 has 6 (28.6%) missing valuesMissing
재개업일자 has 21 (100.0%) missing valuesMissing
전화번호 has 1 (4.8%) missing valuesMissing
소재지면적 has 21 (100.0%) missing valuesMissing
소재지우편번호 has 9 (42.9%) missing valuesMissing
지번주소 has 1 (4.8%) missing valuesMissing
도로명우편번호 has 4 (19.0%) missing valuesMissing
병상수 has 10 (47.6%) missing valuesMissing
총면적 has 3 (14.3%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
도로명주소 has unique valuesUnique
사업장명 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 2 (9.5%) zerosZeros

Reproduction

Analysis started2024-05-11 00:29:52.231686
Analysis finished2024-05-11 00:29:52.929591
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
3100000
21 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 21
100.0%

Length

2024-05-11T00:29:53.111761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:29:53.418237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 21
100.0%

관리번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-05-11T00:29:53.789344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters525
Distinct characters13
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

Unique21 ?
Unique (%)100.0%

Sample

1st rowPHMB420013100034042400001
2nd rowPHMB420033100034042400001
3rd rowPHMB420033100034042400002
4th rowPHMB420043100034042400001
5th rowPHMB420073100034042400001
ValueCountFrequency (%)
phmb420013100034042400001 1
 
4.8%
phmb420133100034042400001 1
 
4.8%
phmb420213100034042400002 1
 
4.8%
phmb420213100034042400001 1
 
4.8%
phmb420183100034042400001 1
 
4.8%
phmb420173100034042400001 1
 
4.8%
phmb420163100034042400004 1
 
4.8%
phmb420163100034042400003 1
 
4.8%
phmb420163100034042400002 1
 
4.8%
phmb420163100034042400001 1
 
4.8%
Other values (11) 11
52.4%
2024-05-11T00:29:54.880028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 196
37.3%
4 86
16.4%
2 53
 
10.1%
1 49
 
9.3%
3 48
 
9.1%
P 21
 
4.0%
H 21
 
4.0%
M 21
 
4.0%
B 21
 
4.0%
6 4
 
0.8%
Other values (3) 5
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 441
84.0%
Uppercase Letter 84
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 196
44.4%
4 86
19.5%
2 53
 
12.0%
1 49
 
11.1%
3 48
 
10.9%
6 4
 
0.9%
7 2
 
0.5%
9 2
 
0.5%
8 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
P 21
25.0%
H 21
25.0%
M 21
25.0%
B 21
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
84.0%
Latin 84
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 196
44.4%
4 86
19.5%
2 53
 
12.0%
1 49
 
11.1%
3 48
 
10.9%
6 4
 
0.9%
7 2
 
0.5%
9 2
 
0.5%
8 1
 
0.2%
Latin
ValueCountFrequency (%)
P 21
25.0%
H 21
25.0%
M 21
25.0%
B 21
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 196
37.3%
4 86
16.4%
2 53
 
10.1%
1 49
 
9.3%
3 48
 
9.1%
P 21
 
4.0%
H 21
 
4.0%
M 21
 
4.0%
B 21
 
4.0%
6 4
 
0.8%
Other values (3) 5
 
1.0%

인허가일자
Date

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2001-02-19 00:00:00
Maximum2021-08-26 00:00:00
2024-05-11T00:29:55.281083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:29:55.739667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
3
15 
1
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 15
71.4%
1 6
 
28.6%

Length

2024-05-11T00:29:56.165156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:29:56.513599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 15
71.4%
1 6
 
28.6%

영업상태명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
폐업
15 
영업/정상
6 

Length

Max length5
Median length2
Mean length2.8571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row영업/정상
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 15
71.4%
영업/정상 6
 
28.6%

Length

2024-05-11T00:29:57.063659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:29:57.460939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 15
71.4%
영업/정상 6
 
28.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
3
15 
13
6 

Length

Max length2
Median length1
Mean length1.2857143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 15
71.4%
13 6
 
28.6%

Length

2024-05-11T00:29:57.863193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:29:58.214726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 15
71.4%
13 6
 
28.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
폐업
15 
영업중
6 

Length

Max length3
Median length2
Mean length2.2857143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 15
71.4%
영업중 6
 
28.6%

Length

2024-05-11T00:29:58.520100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:29:58.841595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 15
71.4%
영업중 6
 
28.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)93.3%
Missing6
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean20147367
Minimum20090828
Maximum20191202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T00:29:59.350230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090828
5-th percentile20090894
Q120120614
median20141114
Q320190710
95-th percentile20191008
Maximum20191202
Range100374
Interquartile range (IQR)70096.5

Descriptive statistics

Standard deviation38378.568
Coefficient of variation (CV)0.0019048925
Kurtosis-1.4664207
Mean20147367
Median Absolute Deviation (MAD)40785
Skewness-0.14413236
Sum3.022105 × 108
Variance1.4729145 × 109
MonotonicityNot monotonic
2024-05-11T00:29:59.762859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20190925 2
 
9.5%
20090828 1
 
4.8%
20090922 1
 
4.8%
20140127 1
 
4.8%
20100329 1
 
4.8%
20110810 1
 
4.8%
20130430 1
 
4.8%
20141114 1
 
4.8%
20130417 1
 
4.8%
20190607 1
 
4.8%
Other values (4) 4
19.0%
(Missing) 6
28.6%
ValueCountFrequency (%)
20090828 1
4.8%
20090922 1
4.8%
20100329 1
4.8%
20110810 1
4.8%
20130417 1
4.8%
20130430 1
4.8%
20140127 1
4.8%
20141114 1
4.8%
20150429 1
4.8%
20170620 1
4.8%
ValueCountFrequency (%)
20191202 1
4.8%
20190925 2
9.5%
20190813 1
4.8%
20190607 1
4.8%
20170620 1
4.8%
20150429 1
4.8%
20141114 1
4.8%
20140127 1
4.8%
20130430 1
4.8%
20130417 1
4.8%

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
19 
20100317
 
1
20190627
 
1

Length

Max length8
Median length4
Mean length4.3809524
Min length4

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
90.5%
20100317 1
 
4.8%
20190627 1
 
4.8%

Length

2024-05-11T00:30:00.216722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:00.600005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
90.5%
20100317 1
 
4.8%
20190627 1
 
4.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
19 
20100608
 
1
20191031
 
1

Length

Max length8
Median length4
Mean length4.3809524
Min length4

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
90.5%
20100608 1
 
4.8%
20191031 1
 
4.8%

Length

2024-05-11T00:30:01.034114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:01.460156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
90.5%
20100608 1
 
4.8%
20191031 1
 
4.8%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

전화번호
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2024-05-11T00:30:02.129714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.5
Min length8

Characters and Unicode

Total characters190
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 (%)100.0%

Sample

1st row932-8587
2nd row939-1295
3rd row02-932-0880
4th row939-6266
5th row939-0072
ValueCountFrequency (%)
932-8587 1
 
5.0%
939-1295 1
 
5.0%
02-932-6700 1
 
5.0%
070-7717-7575 1
 
5.0%
02-975-9975 1
 
5.0%
02-989-5614 1
 
5.0%
02-931-9890 1
 
5.0%
02-939-0507 1
 
5.0%
931-5550 1
 
5.0%
02-976-7580 1
 
5.0%
Other values (10) 10
50.0%
2024-05-11T00:30:03.205040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 29
15.3%
9 28
14.7%
0 24
12.6%
5 21
11.1%
7 21
11.1%
2 20
10.5%
3 15
7.9%
8 13
6.8%
6 9
 
4.7%
1 7
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161
84.7%
Dash Punctuation 29
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 28
17.4%
0 24
14.9%
5 21
13.0%
7 21
13.0%
2 20
12.4%
3 15
9.3%
8 13
8.1%
6 9
 
5.6%
1 7
 
4.3%
4 3
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 29
15.3%
9 28
14.7%
0 24
12.6%
5 21
11.1%
7 21
11.1%
2 20
10.5%
3 15
7.9%
8 13
6.8%
6 9
 
4.7%
1 7
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 29
15.3%
9 28
14.7%
0 24
12.6%
5 21
11.1%
7 21
11.1%
2 20
10.5%
3 15
7.9%
8 13
6.8%
6 9
 
4.7%
1 7
 
3.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

소재지우편번호
Text

MISSING 

Distinct8
Distinct (%)66.7%
Missing9
Missing (%)42.9%
Memory size300.0 B
2024-05-11T00:30:03.612789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0833333
Min length6

Characters and Unicode

Total characters73
Distinct characters9
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

Unique6 ?
Unique (%)50.0%

Sample

1st row139832
2nd row139830
3rd row139942
4th row139-202
5th row139814
ValueCountFrequency (%)
139832 4
33.3%
139942 2
16.7%
139830 1
 
8.3%
139-202 1
 
8.3%
139814 1
 
8.3%
139846 1
 
8.3%
139818 1
 
8.3%
139822 1
 
8.3%
2024-05-11T00:30:04.568428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 17
23.3%
1 14
19.2%
9 14
19.2%
8 10
13.7%
2 10
13.7%
4 4
 
5.5%
0 2
 
2.7%
- 1
 
1.4%
6 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
98.6%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 17
23.6%
1 14
19.4%
9 14
19.4%
8 10
13.9%
2 10
13.9%
4 4
 
5.6%
0 2
 
2.8%
6 1
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 17
23.3%
1 14
19.2%
9 14
19.2%
8 10
13.7%
2 10
13.7%
4 4
 
5.5%
0 2
 
2.7%
- 1
 
1.4%
6 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 17
23.3%
1 14
19.2%
9 14
19.2%
8 10
13.7%
2 10
13.7%
4 4
 
5.5%
0 2
 
2.7%
- 1
 
1.4%
6 1
 
1.4%

지번주소
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2024-05-11T00:30:05.199297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33.5
Mean length28.35
Min length22

Characters and Unicode

Total characters567
Distinct characters47
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

Unique20 ?
Unique (%)100.0%

Sample

1st row서울특별시 노원구 상계동 726번지 1호 일신상가 402호
2nd row서울특별시 노원구 상계6.7동 733번지 4층,5층
3rd row서울특별시 노원구 상계6.7동 711번지 13호 삼양빌딩 2,3층
4th row서울특별시 노원구 상계동 326번지 2호 3층, 4층
5th row서울특별시 노원구 상계3.4동 173번지 1호 복합상가 108동 2동 28호
ValueCountFrequency (%)
서울특별시 20
16.8%
노원구 20
16.8%
상계동 7
 
5.9%
상계6.7동 6
 
5.0%
3층 4
 
3.4%
1호 4
 
3.4%
공릉동 3
 
2.5%
749번지 3
 
2.5%
8호 3
 
2.5%
13호 2
 
1.7%
Other values (43) 47
39.5%
2024-05-11T00:30:06.299610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
 
17.5%
동 23
 
4.1%
7 22
 
3.9%
3 21
 
3.7%
원 20
 
3.5%
호 20
 
3.5%
구 20
 
3.5%
서 20
 
3.5%
노 20
 
3.5%
시 20
 
3.5%
Other values (37) 282
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
55.9%
Decimal Number 133
23.5%
Space Separator 99
 
17.5%
Other Punctuation 11
 
1.9%
Dash Punctuation 3
 
0.5%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
 
7.3%
원 20
 
6.3%
호 20
 
6.3%
구 20
 
6.3%
서 20
 
6.3%
노 20
 
6.3%
시 20
 
6.3%
별 20
 
6.3%
특 20
 
6.3%
울 20
 
6.3%
Other values (21) 114
36.0%
Decimal Number
ValueCountFrequency (%)
7 22
16.5%
3 21
15.8%
1 17
12.8%
6 15
11.3%
4 14
10.5%
2 13
9.8%
8 10
7.5%
9 9
6.8%
0 8
 
6.0%
5 4
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 7
63.6%
, 4
36.4%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
55.9%
Common 250
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
 
7.3%
원 20
 
6.3%
호 20
 
6.3%
구 20
 
6.3%
서 20
 
6.3%
노 20
 
6.3%
시 20
 
6.3%
별 20
 
6.3%
특 20
 
6.3%
울 20
 
6.3%
Other values (21) 114
36.0%
Common
ValueCountFrequency (%)
99
39.6%
7 22
 
8.8%
3 21
 
8.4%
1 17
 
6.8%
6 15
 
6.0%
4 14
 
5.6%
2 13
 
5.2%
8 10
 
4.0%
9 9
 
3.6%
0 8
 
3.2%
Other values (6) 22
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
55.9%
ASCII 250
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
39.6%
7 22
 
8.8%
3 21
 
8.4%
1 17
 
6.8%
6 15
 
6.0%
4 14
 
5.6%
2 13
 
5.2%
8 10
 
4.0%
9 9
 
3.6%
0 8
 
3.2%
Other values (6) 22
 
8.8%
Hangul
ValueCountFrequency (%)
동 23
 
7.3%
원 20
 
6.3%
호 20
 
6.3%
구 20
 
6.3%
서 20
 
6.3%
노 20
 
6.3%
시 20
 
6.3%
별 20
 
6.3%
특 20
 
6.3%
울 20
 
6.3%
Other values (21) 114
36.0%

도로명주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-05-11T00:30:06.997620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length33.809524
Min length24

Characters and Unicode

Total characters710
Distinct characters60
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

Unique21 ?
Unique (%)100.0%

Sample

1st row서울특별시 노원구 동일로218길 17 (상계동, 일신상가 402호)
2nd row서울특별시 노원구 동일로217가길 17 (상계동,4층,5층)
3rd row서울특별시 노원구 동일로 1417 (상계동,삼양빌딩 2,3층)
4th row서울특별시 노원구 노해로83길 10-11, 3층, 4층 (상계동)
5th row서울특별시 노원구 한글비석로 396 (상계동, 108동 2동 28호)
ValueCountFrequency (%)
서울특별시 21
 
15.1%
노원구 21
 
15.1%
상계동 13
 
9.4%
동일로 9
 
6.5%
5층 4
 
2.9%
3층 4
 
2.9%
2층 3
 
2.2%
1350 3
 
2.2%
공릉동 3
 
2.2%
1343 2
 
1.4%
Other values (53) 56
40.3%
2024-05-11T00:30:08.074701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
16.6%
동 39
 
5.5%
1 29
 
4.1%
, 26
 
3.7%
노 23
 
3.2%
3 22
 
3.1%
) 22
 
3.1%
상 22
 
3.1%
( 22
 
3.1%
서 21
 
3.0%
Other values (50) 366
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 386
54.4%
Decimal Number 133
 
18.7%
Space Separator 118
 
16.6%
Other Punctuation 26
 
3.7%
Close Punctuation 22
 
3.1%
Open Punctuation 22
 
3.1%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 39
 
10.1%
노 23
 
6.0%
상 22
 
5.7%
서 21
 
5.4%
울 21
 
5.4%
계 21
 
5.4%
특 21
 
5.4%
별 21
 
5.4%
구 21
 
5.4%
원 21
 
5.4%
Other values (35) 155
40.2%
Decimal Number
ValueCountFrequency (%)
1 29
21.8%
3 22
16.5%
2 15
11.3%
5 14
10.5%
4 14
10.5%
0 13
9.8%
7 8
 
6.0%
8 8
 
6.0%
9 6
 
4.5%
6 4
 
3.0%
Space Separator
ValueCountFrequency (%)
118
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 386
54.4%
Common 324
45.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 39
 
10.1%
노 23
 
6.0%
상 22
 
5.7%
서 21
 
5.4%
울 21
 
5.4%
계 21
 
5.4%
특 21
 
5.4%
별 21
 
5.4%
구 21
 
5.4%
원 21
 
5.4%
Other values (35) 155
40.2%
Common
ValueCountFrequency (%)
118
36.4%
1 29
 
9.0%
, 26
 
8.0%
3 22
 
6.8%
) 22
 
6.8%
( 22
 
6.8%
2 15
 
4.6%
5 14
 
4.3%
4 14
 
4.3%
0 13
 
4.0%
Other values (5) 29
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 386
54.4%
ASCII 324
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
36.4%
1 29
 
9.0%
, 26
 
8.0%
3 22
 
6.8%
) 22
 
6.8%
( 22
 
6.8%
2 15
 
4.6%
5 14
 
4.3%
4 14
 
4.3%
0 13
 
4.0%
Other values (5) 29
 
9.0%
Hangul
ValueCountFrequency (%)
동 39
 
10.1%
노 23
 
6.0%
상 22
 
5.7%
서 21
 
5.4%
울 21
 
5.4%
계 21
 
5.4%
특 21
 
5.4%
별 21
 
5.4%
구 21
 
5.4%
원 21
 
5.4%
Other values (35) 155
40.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)82.4%
Missing4
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean42370.706
Minimum1674
Maximum139846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T00:30:08.547297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1674
5-th percentile1682
Q11751
median1769
Q3139814
95-th percentile139834.8
Maximum139846
Range138172
Interquartile range (IQR)138063

Descriptive statistics

Standard deviation64844.794
Coefficient of variation (CV)1.5304157
Kurtosis-1.1657151
Mean42370.706
Median Absolute Deviation (MAD)79
Skewness0.99360702
Sum720302
Variance4.2048473 × 109
MonotonicityNot monotonic
2024-05-11T00:30:08.982349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1751 2
9.5%
139832 2
9.5%
1767 2
9.5%
1695 1
 
4.8%
139814 1
 
4.8%
139846 1
 
4.8%
139818 1
 
4.8%
1674 1
 
4.8%
1848 1
 
4.8%
1684 1
 
4.8%
Other values (4) 4
19.0%
(Missing) 4
19.0%
ValueCountFrequency (%)
1674 1
4.8%
1684 1
4.8%
1695 1
4.8%
1751 2
9.5%
1756 1
4.8%
1767 2
9.5%
1769 1
4.8%
1845 1
4.8%
1848 1
4.8%
1853 1
4.8%
ValueCountFrequency (%)
139846 1
4.8%
139832 2
9.5%
139818 1
4.8%
139814 1
4.8%
1853 1
4.8%
1848 1
4.8%
1845 1
4.8%
1769 1
4.8%
1767 2
9.5%
1756 1
4.8%

사업장명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-05-11T00:30:09.542903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length7.9047619
Min length6

Characters and Unicode

Total characters166
Distinct characters63
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row웰빙지압안마원
2nd row갤러리안마시술소
3rd row프린스안마시술소
4th row노원안마시술소
5th row미래건강안마원
ValueCountFrequency (%)
웰빙지압안마원 1
 
4.8%
노원지압건강안마원 1
 
4.8%
백지압안마원 1
 
4.8%
조은지압안마원 1
 
4.8%
김동일지압안마원 1
 
4.8%
바른몸약손지압안마원 1
 
4.8%
한기쁨안마원 1
 
4.8%
우거리물리안마원 1
 
4.8%
건강드림안마원 1
 
4.8%
약손지압안마원 1
 
4.8%
Other values (11) 11
52.4%
2024-05-11T00:30:10.512886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 22
 
13.3%
안 21
 
12.7%
원 19
 
11.4%
지 10
 
6.0%
압 10
 
6.0%
손 4
 
2.4%
시 4
 
2.4%
술 4
 
2.4%
소 4
 
2.4%
약 4
 
2.4%
Other values (53) 64
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
97.0%
Uppercase Letter 3
 
1.8%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 22
 
13.7%
안 21
 
13.0%
원 19
 
11.8%
지 10
 
6.2%
압 10
 
6.2%
손 4
 
2.5%
시 4
 
2.5%
술 4
 
2.5%
소 4
 
2.5%
약 4
 
2.5%
Other values (48) 59
36.6%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
M 1
33.3%
T 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
97.0%
Latin 3
 
1.8%
Common 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 22
 
13.7%
안 21
 
13.0%
원 19
 
11.8%
지 10
 
6.2%
압 10
 
6.2%
손 4
 
2.5%
시 4
 
2.5%
술 4
 
2.5%
소 4
 
2.5%
약 4
 
2.5%
Other values (48) 59
36.6%
Latin
ValueCountFrequency (%)
O 1
33.3%
M 1
33.3%
T 1
33.3%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
97.0%
ASCII 5
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 22
 
13.7%
안 21
 
13.0%
원 19
 
11.8%
지 10
 
6.2%
압 10
 
6.2%
손 4
 
2.5%
시 4
 
2.5%
술 4
 
2.5%
소 4
 
2.5%
약 4
 
2.5%
Other values (48) 59
36.6%
ASCII
ValueCountFrequency (%)
O 1
20.0%
( 1
20.0%
M 1
20.0%
T 1
20.0%
) 1
20.0%

최종수정일자
Date

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2009-09-03 10:18:37
Maximum2023-06-16 17:32:30
2024-05-11T00:30:10.903419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:30:11.384262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

데이터갱신구분
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
I
11 
U
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 11
52.4%
U 10
47.6%

Length

2024-05-11T00:30:11.770187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:12.183210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 11
52.4%
u 10
47.6%

데이터갱신일자
Date

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2018-08-31 23:59:59
Maximum2022-12-06 00:03:00
2024-05-11T00:30:12.588992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:30:12.932829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

업태구분명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
안마원
17 
안마시술소
4 

Length

Max length5
Median length3
Mean length3.3809524
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 17
81.0%
안마시술소 4
 
19.0%

Length

2024-05-11T00:30:13.395708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:13.756204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 17
81.0%
안마시술소 4
 
19.0%

좌표정보(X)
Real number (ℝ)

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205615.64
Minimum205005.11
Maximum206658.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T00:30:14.047584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205005.11
5-th percentile205171.82
Q1205309.76
median205438
Q3205957.77
95-th percentile206623.08
Maximum206658.81
Range1653.7063
Interquartile range (IQR)648.00922

Descriptive statistics

Standard deviation486.98625
Coefficient of variation (CV)0.0023684299
Kurtosis0.03504976
Mean205615.64
Median Absolute Deviation (MAD)216.45691
Skewness1.0799345
Sum4317928.5
Variance237155.6
MonotonicityNot monotonic
2024-05-11T00:30:14.436182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
205437.99609028 3
14.3%
205221.539176675 2
 
9.5%
205400.87065435 2
 
9.5%
205394.112077124 1
 
4.8%
205439.320706497 1
 
4.8%
205396.51658775 1
 
4.8%
206658.814079746 1
 
4.8%
206197.858524454 1
 
4.8%
205309.755822239 1
 
4.8%
206016.659874902 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
205005.107760722 1
 
4.8%
205171.819268997 1
 
4.8%
205186.433291674 1
 
4.8%
205221.539176675 2
9.5%
205309.755822239 1
 
4.8%
205394.112077124 1
 
4.8%
205396.51658775 1
 
4.8%
205400.87065435 2
9.5%
205437.99609028 3
14.3%
205439.320706497 1
 
4.8%
ValueCountFrequency (%)
206658.814079746 1
 
4.8%
206623.082268808 1
 
4.8%
206356.052509483 1
 
4.8%
206197.858524454 1
 
4.8%
206016.659874902 1
 
4.8%
205957.765044419 1
 
4.8%
205656.401792504 1
 
4.8%
205439.320706497 1
 
4.8%
205437.99609028 3
14.3%
205400.87065435 2
9.5%

좌표정보(Y)
Real number (ℝ)

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean460631.95
Minimum457692.97
Maximum462756.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T00:30:14.861153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457692.97
5-th percentile457710.08
Q1460681.68
median460932.28
Q3461414.22
95-th percentile462123.01
Maximum462756.33
Range5063.3648
Interquartile range (IQR)732.53979

Descriptive statistics

Standard deviation1487.19
Coefficient of variation (CV)0.0032285863
Kurtosis0.3067574
Mean460631.95
Median Absolute Deviation (MAD)481.93576
Skewness-1.1325757
Sum9673271
Variance2211734.1
MonotonicityNot monotonic
2024-05-11T00:30:15.319211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
460765.486012553 3
14.3%
461414.218921501 2
 
9.5%
460681.679132551 2
 
9.5%
461283.511494133 1
 
4.8%
461335.356566932 1
 
4.8%
460932.283160478 1
 
4.8%
457822.100649643 1
 
4.8%
458210.615094447 1
 
4.8%
460429.879161878 1
 
4.8%
461794.576281039 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
457692.96795699 1
 
4.8%
457710.084732661 1
 
4.8%
457822.100649643 1
 
4.8%
458210.615094447 1
 
4.8%
460429.879161878 1
 
4.8%
460681.679132551 2
9.5%
460765.486012553 3
14.3%
460932.283160478 1
 
4.8%
461220.88706693 1
 
4.8%
461283.511494133 1
 
4.8%
ValueCountFrequency (%)
462756.332743137 1
4.8%
462123.008334776 1
4.8%
461957.248131884 1
4.8%
461794.576281039 1
4.8%
461513.856224424 1
4.8%
461414.218921501 2
9.5%
461335.356566932 1
4.8%
461283.511494133 1
4.8%
461220.88706693 1
4.8%
460932.283160478 1
4.8%

의료유사업종별명
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
안마원
15 
안마시술소
3 
<NA>
3 

Length

Max length5
Median length3
Mean length3.4285714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 15
71.4%
안마시술소 3
 
14.3%
<NA> 3
 
14.3%

Length

2024-05-11T00:30:15.739740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:16.108004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 15
71.4%
안마시술소 3
 
14.3%
na 3
 
14.3%

종업원수
Categorical

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
1
11 
<NA>
5 
2
2 
3
2 
5
 
1

Length

Max length4
Median length1
Mean length1.7142857
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row1
2nd row2
3rd row5
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
1 11
52.4%
<NA> 5
23.8%
2 2
 
9.5%
3 2
 
9.5%
5 1
 
4.8%

Length

2024-05-11T00:30:16.614787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:17.228477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 11
52.4%
na 5
23.8%
2 2
 
9.5%
3 2
 
9.5%
5 1
 
4.8%

자격증소유자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
19 
0
2 

Length

Max length4
Median length4
Mean length3.7142857
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
90.5%
0 2
 
9.5%

Length

2024-05-11T00:30:17.761841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:18.236235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
90.5%
0 2
 
9.5%

보조종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
19 
0
2 

Length

Max length4
Median length4
Mean length3.7142857
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
90.5%
0 2
 
9.5%

Length

2024-05-11T00:30:18.835236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:19.394219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
90.5%
0 2
 
9.5%

시설관리자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
19 
0
2 

Length

Max length4
Median length4
Mean length3.7142857
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
90.5%
0 2
 
9.5%

Length

2024-05-11T00:30:20.081246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:20.657696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
90.5%
0 2
 
9.5%

기타종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
19 
0
2 

Length

Max length4
Median length4
Mean length3.7142857
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
90.5%
0 2
 
9.5%

Length

2024-05-11T00:30:21.187960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:21.590266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
90.5%
0 2
 
9.5%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)63.6%
Missing10
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean4.0909091
Minimum0
Maximum16
Zeros2
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T00:30:21.822815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median3
Q35
95-th percentile12
Maximum16
Range16
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation4.6142073
Coefficient of variation (CV)1.1279173
Kurtosis4.3435812
Mean4.0909091
Median Absolute Deviation (MAD)2
Skewness1.9444518
Sum45
Variance21.290909
MonotonicityNot monotonic
2024-05-11T00:30:22.233147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 2
 
9.5%
0 2
 
9.5%
2 2
 
9.5%
5 2
 
9.5%
1 1
 
4.8%
8 1
 
4.8%
16 1
 
4.8%
(Missing) 10
47.6%
ValueCountFrequency (%)
0 2
9.5%
1 1
4.8%
2 2
9.5%
3 2
9.5%
5 2
9.5%
8 1
4.8%
16 1
4.8%
ValueCountFrequency (%)
16 1
4.8%
8 1
4.8%
5 2
9.5%
3 2
9.5%
2 2
9.5%
1 1
4.8%
0 2
9.5%

욕실면적
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
16 
0.0
4 
20.65
 
1

Length

Max length5
Median length4
Mean length3.8571429
Min length3

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 16
76.2%
0.0 4
 
19.0%
20.65 1
 
4.8%

Length

2024-05-11T00:30:22.876603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:30:23.356756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
76.2%
0.0 4
 
19.0%
20.65 1
 
4.8%

총면적
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)94.4%
Missing3
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean103.26667
Minimum15.78
Maximum455.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T00:30:23.674509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.78
5-th percentile23.243
Q137.83
median49.33
Q387.725
95-th percentile415.3715
Maximum455.84
Range440.06
Interquartile range (IQR)49.895

Descriptive statistics

Standard deviation128.6638
Coefficient of variation (CV)1.2459374
Kurtosis3.8859348
Mean103.26667
Median Absolute Deviation (MAD)19.3
Skewness2.1832586
Sum1858.8
Variance16554.373
MonotonicityNot monotonic
2024-05-11T00:30:24.016421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
37.83 2
 
9.5%
50.0 1
 
4.8%
48.66 1
 
4.8%
124.16 1
 
4.8%
51.4 1
 
4.8%
64.84 1
 
4.8%
15.78 1
 
4.8%
24.56 1
 
4.8%
89.1 1
 
4.8%
217.68 1
 
4.8%
Other values (7) 7
33.3%
(Missing) 3
14.3%
ValueCountFrequency (%)
15.78 1
4.8%
24.56 1
4.8%
26.24 1
4.8%
37.38 1
4.8%
37.83 2
9.5%
39.47 1
4.8%
46.2 1
4.8%
48.66 1
4.8%
50.0 1
4.8%
51.4 1
4.8%
ValueCountFrequency (%)
455.84 1
4.8%
408.23 1
4.8%
217.68 1
4.8%
124.16 1
4.8%
89.1 1
4.8%
83.6 1
4.8%
64.84 1
4.8%
51.4 1
4.8%
50.0 1
4.8%
48.66 1
4.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03100000PHMB42001310003404240000120010219<NA>3폐업3폐업20190925<NA><NA><NA>932-8587<NA>139832서울특별시 노원구 상계동 726번지 1호 일신상가 402호서울특별시 노원구 동일로218길 17 (상계동, 일신상가 402호)1751웰빙지압안마원2019-09-25 10:12:17U2019-09-27 02:40:00.0안마원205394.112077461283.511494안마원1<NA><NA><NA><NA><NA><NA>89.1
13100000PHMB42003310003404240000120031222<NA>3폐업3폐업20090828<NA><NA><NA>939-1295<NA>139830서울특별시 노원구 상계6.7동 733번지 4층,5층서울특별시 노원구 동일로217가길 17 (상계동,4층,5층)<NA>갤러리안마시술소2009-09-03 10:18:37I2018-08-31 23:59:59.0안마시술소205171.819269461220.887067안마시술소2<NA><NA><NA><NA>1<NA>217.68
23100000PHMB42003310003404240000220031230<NA>3폐업3폐업20090922<NA><NA><NA><NA><NA>139942서울특별시 노원구 상계6.7동 711번지 13호 삼양빌딩 2,3층서울특별시 노원구 동일로 1417 (상계동,삼양빌딩 2,3층)<NA>프린스안마시술소2009-09-22 11:41:40I2018-08-31 23:59:59.0안마시술소205221.539177461414.218922안마시술소5<NA><NA><NA><NA>8<NA>455.84
33100000PHMB4200431000340424000012004-06-18<NA>1영업/정상13영업중<NA><NA><NA><NA>02-932-0880<NA>139-202서울특별시 노원구 상계동 326번지 2호 3층, 4층서울특별시 노원구 노해로83길 10-11, 3층, 4층 (상계동)1695노원안마시술소2023-06-16 17:32:30U2022-12-05 23:08:00.0안마시술소205656.401793461513.856224<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43100000PHMB42007310003404240000120071128<NA>3폐업3폐업20140127<NA><NA><NA>939-6266<NA>139814서울특별시 노원구 상계3.4동 173번지 1호 복합상가 108동 2동 28호서울특별시 노원구 한글비석로 396 (상계동, 108동 2동 28호)139814미래건강안마원2014-01-27 15:46:01I2018-08-31 23:59:59.0안마원206356.052509462123.008335안마원1<NA><NA><NA><NA><NA><NA>46.2
53100000PHMB42009310003404240000120091007<NA>3폐업3폐업201003292010031720100608<NA>939-0072<NA>139942서울특별시 노원구 상계6.7동 711번지 13호 (2층, 3층)서울특별시 노원구 동일로 1417 (상계동,(2층, 3층))<NA>핑크안마시술소2010-03-29 11:49:47I2018-08-31 23:59:59.0안마시술소205221.539177461414.218922안마시술소3<NA><NA><NA><NA>1620.65408.23
63100000PHMB42009310003404240000220091113<NA>3폐업3폐업20110810<NA><NA><NA>584-5456<NA>139832서울특별시 노원구 상계6.7동 749번지 8호 3층서울특별시 노원구 동일로 1350 (상계동,3층)<NA>약손경락지압안마원2011-08-10 14:09:29I2018-08-31 23:59:59.0안마원205437.99609460765.486013안마원1<NA><NA><NA><NA>3<NA>37.83
73100000PHMB42011310003404240000120111116<NA>3폐업3폐업20130430<NA><NA><NA>935-1275<NA>139832서울특별시 노원구 상계6.7동 749번지 8호 302호서울특별시 노원구 동일로 1350, 3층 2호 (상계동)139832오엠티(OMT)경락지압안마원2013-04-30 11:43:22I2018-08-31 23:59:59.0안마원205437.99609460765.486013안마원1<NA><NA><NA><NA><NA><NA>37.38
83100000PHMB42012310003404240000120120110<NA>3폐업3폐업20141114<NA><NA><NA>2092-0015<NA>139846서울특별시 노원구 월계1동 409번지 10호 5층서울특별시 노원구 광운로 48, 5층 (월계동)139846월계수안마원2014-12-24 18:05:58I2018-08-31 23:59:59.0안마원205186.433292457710.084733안마원1<NA><NA><NA><NA><NA><NA>83.6
93100000PHMB42012310003404240000220120112<NA>3폐업3폐업20130417<NA><NA><NA>938-7388<NA>139818서울특별시 노원구 상계2동 389번지 374호 (1층)서울특별시 노원구 상계로9가길 53, 1층 (상계동)139818나무그늘지압안마원2013-04-17 17:13:42I2018-08-31 23:59:59.0안마원205957.765044461957.248132안마원1<NA><NA><NA><NA><NA><NA>26.24
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
113100000PHMB42013310003404240000120130617<NA>3폐업3폐업20150429<NA><NA><NA>936-7575<NA>139832서울특별시 노원구 상계6.7동 749번지 8호 삼양빌딩 3층 302호서울특별시 노원구 동일로 1350, 3층 302호 (상계동, 삼양빌딩)139832노원지압건강안마원2015-04-29 13:08:19I2018-08-31 23:59:59.0안마원205437.99609460765.486013안마원2<NA><NA><NA><NA>2<NA>37.83
123100000PHMB42016310003404240000120160314<NA>3폐업3폐업20170620<NA><NA><NA>02-976-7580<NA><NA>서울특별시 노원구 공릉동 584번지 14호서울특별시 노원구 동일로178길 19-6, 2층 (공릉동)1848약손지압안마원2017-06-20 10:41:59I2018-08-31 23:59:59.0안마원206623.082269457692.967957안마원1<NA><NA><NA><NA><NA><NA>50.0
133100000PHMB4201631000340424000022016-04-01<NA>1영업/정상13영업중<NA><NA><NA><NA>931-5550<NA><NA>서울특별시 노원구 상계동 724-1 길빌딩서울특별시 노원구 노해로 490, 길빌딩 5층 504호 (상계동)1751건강드림안마원2023-05-30 17:47:58U2022-12-06 00:01:00.0안마원205439.320706461335.356567<NA><NA><NA><NA><NA><NA><NA><NA><NA>
143100000PHMB42016310003404240000320160404<NA>1영업/정상13영업중<NA><NA><NA><NA>02-939-0507<NA><NA>서울특별시 노원구 상계동 389번지 489호서울특별시 노원구 상계로23길 7 (상계동)1684우거리물리안마원2021-08-04 11:13:31U2021-08-06 02:40:00.0안마원206016.659875461794.576281안마원1000050.024.56
153100000PHMB42016310003404240000420160429<NA>3폐업3폐업20191202<NA><NA><NA>02-931-9890<NA><NA>서울특별시 노원구 상계동 766번지 1호서울특별시 노원구 덕릉로 459-14, 106호 (상계동, 상계미도우편취급소)1769한기쁨안마원2019-12-02 15:23:34U2019-12-04 02:40:00.0안마원205309.755822460429.879162안마원<NA><NA><NA><NA><NA>3<NA>15.78
163100000PHMB42017310003404240000120170926<NA>3폐업3폐업20190925<NA><NA><NA>02-989-5614<NA><NA>서울특별시 노원구 상계동 763번지 7호서울특별시 노원구 동일로 1343, 5층 3호 (상계동, 동일프라자빌딩)1767바른몸약손지압안마원2019-09-25 17:39:40U2019-09-27 02:40:00.0안마원205400.870654460681.679133안마원1<NA><NA><NA><NA><NA><NA>64.84
173100000PHMB42018310003404240000120180412<NA>3폐업3폐업201908132019062720191031<NA>02-975-9975<NA><NA>서울특별시 노원구 공릉동 380번지 37호서울특별시 노원구 동일로191가길 25, 2층 (공릉동)1853김동일지압안마원2019-08-13 13:21:39U2019-08-15 02:40:00.0안마원206197.858524458210.615094안마원<NA><NA><NA><NA><NA>2<NA>51.4
183100000PHMB42021310003404240000120210303<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7717-7575<NA><NA>서울특별시 노원구 공릉동 566-20 공릉상가서울특별시 노원구 동일로180길 37, 공릉상가 2층 201호 (공릉동)1845조은지압안마원2021-03-05 13:36:21I2021-03-07 00:23:00.0안마원206658.81408457822.10065안마원3<NA><NA><NA><NA>50.0124.16
193100000PHMB4202131000340424000022021-06-04<NA>1영업/정상13영업중<NA><NA><NA><NA>02-932-6700<NA><NA>서울특별시 노원구 상계동 763-7 동일프라자빌딩서울특별시 노원구 동일로 1343, 동일프라자빌딩 304호 (상계동)1767백지압안마원2023-06-01 10:09:49U2022-12-06 00:03:00.0안마원205400.870654460681.679133<NA><NA><NA><NA><NA><NA><NA><NA><NA>
203100000PHMB42021310003404240000320210826<NA>1영업/정상13영업중<NA><NA><NA><NA>02-932-7577<NA><NA><NA>서울특별시 노원구 동일로 1368, 롯데프라자빌딩 5층 1호 (상계동)1756한국정통안마원2021-10-18 17:30:15U2021-10-20 02:40:00.0안마원205396.516588460932.28316안마원1000000.048.66