Overview

Dataset statistics

Number of variables34
Number of observations42
Missing cells276
Missing cells (%)19.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory293.1 B

Variable types

Categorical14
Text6
DateTime5
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-16363/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
자격증소유자수 is highly imbalanced (83.8%)Imbalance
보조종업원수 is highly imbalanced (83.8%)Imbalance
시설관리자수 is highly imbalanced (83.8%)Imbalance
기타종업원수 is highly imbalanced (83.8%)Imbalance
욕실면적 is highly imbalanced (72.4%)Imbalance
인허가취소일자 has 42 (100.0%) missing valuesMissing
폐업일자 has 12 (28.6%) missing valuesMissing
휴업시작일자 has 38 (90.5%) missing valuesMissing
휴업종료일자 has 38 (90.5%) missing valuesMissing
재개업일자 has 42 (100.0%) missing valuesMissing
전화번호 has 8 (19.0%) missing valuesMissing
소재지면적 has 42 (100.0%) missing valuesMissing
소재지우편번호 has 8 (19.0%) missing valuesMissing
도로명우편번호 has 24 (57.1%) missing valuesMissing
좌표정보(X) has 1 (2.4%) missing valuesMissing
좌표정보(Y) has 1 (2.4%) missing valuesMissing
병상수 has 13 (31.0%) missing valuesMissing
총면적 has 7 (16.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
병상수 has 1 (2.4%) zerosZeros

Reproduction

Analysis started2024-05-11 05:13:19.698061
Analysis finished2024-05-11 05:13:20.485238
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
3050000
42 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 42
100.0%

Length

2024-05-11T05:13:20.655929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:20.927166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 42
100.0%

관리번호
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-05-11T05:13:21.386857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1050
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

Unique42 ?
Unique (%)100.0%

Sample

1st rowPHMB419823050034042400001
2nd rowPHMB419933050034042400001
3rd rowPHMB419933050034042400002
4th rowPHMB419933050034042400003
5th rowPHMB419963050034042400001
ValueCountFrequency (%)
phmb419823050034042400001 1
 
2.4%
phmb420123050034042400001 1
 
2.4%
phmb420203050034042400002 1
 
2.4%
phmb420063050034042400001 1
 
2.4%
phmb420073050034042400002 1
 
2.4%
phmb420083050034042400001 1
 
2.4%
phmb420093050034042400001 1
 
2.4%
phmb420093050034042400002 1
 
2.4%
phmb420103050034042400001 1
 
2.4%
phmb420103050034042400002 1
 
2.4%
Other values (32) 32
76.2%
2024-05-11T05:13:22.179332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 398
37.9%
4 181
17.2%
3 99
 
9.4%
2 97
 
9.2%
5 49
 
4.7%
P 42
 
4.0%
H 42
 
4.0%
M 42
 
4.0%
B 42
 
4.0%
1 35
 
3.3%
Other values (4) 23
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 882
84.0%
Uppercase Letter 168
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 398
45.1%
4 181
20.5%
3 99
 
11.2%
2 97
 
11.0%
5 49
 
5.6%
1 35
 
4.0%
9 13
 
1.5%
8 4
 
0.5%
6 4
 
0.5%
7 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
P 42
25.0%
H 42
25.0%
M 42
25.0%
B 42
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 882
84.0%
Latin 168
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 398
45.1%
4 181
20.5%
3 99
 
11.2%
2 97
 
11.0%
5 49
 
5.6%
1 35
 
4.0%
9 13
 
1.5%
8 4
 
0.5%
6 4
 
0.5%
7 2
 
0.2%
Latin
ValueCountFrequency (%)
P 42
25.0%
H 42
25.0%
M 42
25.0%
B 42
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 398
37.9%
4 181
17.2%
3 99
 
9.4%
2 97
 
9.2%
5 49
 
4.7%
P 42
 
4.0%
H 42
 
4.0%
M 42
 
4.0%
B 42
 
4.0%
1 35
 
3.3%
Other values (4) 23
 
2.2%

인허가일자
Date

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum1982-11-13 00:00:00
Maximum2024-01-02 00:00:00
2024-05-11T05:13:22.626213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:13:23.195313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

영업상태코드
Categorical

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
3
29 
1
11 
4
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
3 29
69.0%
1 11
 
26.2%
4 1
 
2.4%
2 1
 
2.4%

Length

2024-05-11T05:13:23.818372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:24.356169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 29
69.0%
1 11
 
26.2%
4 1
 
2.4%
2 1
 
2.4%

영업상태명
Categorical

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
폐업
29 
영업/정상
11 
취소/말소/만료/정지/중지
 
1
휴업
 
1

Length

Max length14
Median length2
Mean length3.0714286
Min length2

Unique

Unique2 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 29
69.0%
영업/정상 11
 
26.2%
취소/말소/만료/정지/중지 1
 
2.4%
휴업 1
 
2.4%

Length

2024-05-11T05:13:24.754050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:25.377520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 29
69.0%
영업/정상 11
 
26.2%
취소/말소/만료/정지/중지 1
 
2.4%
휴업 1
 
2.4%

상세영업상태코드
Categorical

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
3
29 
13
11 
24
 
1
2
 
1

Length

Max length2
Median length1
Mean length1.2857143
Min length1

Unique

Unique2 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
3 29
69.0%
13 11
 
26.2%
24 1
 
2.4%
2 1
 
2.4%

Length

2024-05-11T05:13:26.207851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:27.159870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 29
69.0%
13 11
 
26.2%
24 1
 
2.4%
2 1
 
2.4%

상세영업상태명
Categorical

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
폐업
29 
영업중
11 
직권폐업
 
1
휴업
 
1

Length

Max length4
Median length2
Mean length2.3095238
Min length2

Unique

Unique2 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 29
69.0%
영업중 11
 
26.2%
직권폐업 1
 
2.4%
휴업 1
 
2.4%

Length

2024-05-11T05:13:27.959120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:28.488996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 29
69.0%
영업중 11
 
26.2%
직권폐업 1
 
2.4%
휴업 1
 
2.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)100.0%
Missing12
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean20093299
Minimum20040531
Maximum20221116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T05:13:29.181010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040531
5-th percentile20050736
Q120070174
median20075614
Q320105485
95-th percentile20192904
Maximum20221116
Range180585
Interquartile range (IQR)35310.75

Descriptive statistics

Standard deviation44986.78
Coefficient of variation (CV)0.0022388947
Kurtosis2.2344649
Mean20093299
Median Absolute Deviation (MAD)15050
Skewness1.6344745
Sum6.0279896 × 108
Variance2.0238103 × 109
MonotonicityNot monotonic
2024-05-11T05:13:29.727086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20070427 1
 
2.4%
20221116 1
 
2.4%
20210721 1
 
2.4%
20160518 1
 
2.4%
20171128 1
 
2.4%
20131129 1
 
2.4%
20120605 1
 
2.4%
20110309 1
 
2.4%
20091008 1
 
2.4%
20070806 1
 
2.4%
Other values (20) 20
47.6%
(Missing) 12
28.6%
ValueCountFrequency (%)
20040531 1
2.4%
20050516 1
2.4%
20051004 1
2.4%
20060123 1
2.4%
20060525 1
2.4%
20061004 1
2.4%
20061129 1
2.4%
20070129 1
2.4%
20070309 1
2.4%
20070326 1
2.4%
ValueCountFrequency (%)
20221116 1
2.4%
20210721 1
2.4%
20171128 1
2.4%
20160518 1
2.4%
20131129 1
2.4%
20120605 1
2.4%
20111124 1
2.4%
20110309 1
2.4%
20091012 1
2.4%
20091008 1
2.4%

휴업시작일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing38
Missing (%)90.5%
Memory size468.0 B
Minimum2009-08-11 00:00:00
Maximum2023-10-13 00:00:00
2024-05-11T05:13:30.195817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:13:30.554856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

휴업종료일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing38
Missing (%)90.5%
Memory size468.0 B
Minimum2010-02-11 00:00:00
Maximum2025-10-12 00:00:00
2024-05-11T05:13:30.895702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:13:31.228987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

전화번호
Text

MISSING 

Distinct32
Distinct (%)94.1%
Missing8
Missing (%)19.0%
Memory size468.0 B
2024-05-11T05:13:31.789512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.8235294
Min length8

Characters and Unicode

Total characters300
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

Unique30 ?
Unique (%)88.2%

Sample

1st row2242-6011
2nd row2215-8344
3rd row2212-9388
4th row2245-8909
5th row2246-0840
ValueCountFrequency (%)
2215-8344 2
 
5.9%
969-1475 2
 
5.9%
961-8100 1
 
2.9%
02-3394-7001 1
 
2.9%
963-1066 1
 
2.9%
921-0696 1
 
2.9%
422-1226 1
 
2.9%
2244-6855 1
 
2.9%
953-5050 1
 
2.9%
2244-9519 1
 
2.9%
Other values (22) 22
64.7%
2024-05-11T05:13:32.893398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 63
21.0%
- 35
11.7%
9 32
10.7%
4 30
10.0%
1 27
9.0%
0 26
8.7%
6 22
 
7.3%
5 20
 
6.7%
3 19
 
6.3%
8 13
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 265
88.3%
Dash Punctuation 35
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 63
23.8%
9 32
12.1%
4 30
11.3%
1 27
10.2%
0 26
9.8%
6 22
 
8.3%
5 20
 
7.5%
3 19
 
7.2%
8 13
 
4.9%
7 13
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 63
21.0%
- 35
11.7%
9 32
10.7%
4 30
10.0%
1 27
9.0%
0 26
8.7%
6 22
 
7.3%
5 20
 
6.7%
3 19
 
6.3%
8 13
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 63
21.0%
- 35
11.7%
9 32
10.7%
4 30
10.0%
1 27
9.0%
0 26
8.7%
6 22
 
7.3%
5 20
 
6.7%
3 19
 
6.3%
8 13
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

소재지우편번호
Text

MISSING 

Distinct17
Distinct (%)50.0%
Missing8
Missing (%)19.0%
Memory size468.0 B
2024-05-11T05:13:33.389252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0588235
Min length6

Characters and Unicode

Total characters206
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

Unique12 ?
Unique (%)35.3%

Sample

1st row130805
2nd row130100
3rd row130100
4th row130100
5th row130090
ValueCountFrequency (%)
130100 14
41.2%
130010 2
 
5.9%
130030 2
 
5.9%
130864 2
 
5.9%
130090 2
 
5.9%
130110 1
 
2.9%
130805 1
 
2.9%
130809 1
 
2.9%
130801 1
 
2.9%
130867 1
 
2.9%
Other values (7) 7
20.6%
2024-05-11T05:13:34.231370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 82
39.8%
1 56
27.2%
3 37
18.0%
8 11
 
5.3%
6 6
 
2.9%
7 4
 
1.9%
9 3
 
1.5%
4 3
 
1.5%
- 2
 
1.0%
5 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204
99.0%
Dash Punctuation 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82
40.2%
1 56
27.5%
3 37
18.1%
8 11
 
5.4%
6 6
 
2.9%
7 4
 
2.0%
9 3
 
1.5%
4 3
 
1.5%
5 1
 
0.5%
2 1
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 206
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 82
39.8%
1 56
27.2%
3 37
18.0%
8 11
 
5.3%
6 6
 
2.9%
7 4
 
1.9%
9 3
 
1.5%
4 3
 
1.5%
- 2
 
1.0%
5 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 82
39.8%
1 56
27.2%
3 37
18.0%
8 11
 
5.3%
6 6
 
2.9%
7 4
 
1.9%
9 3
 
1.5%
4 3
 
1.5%
- 2
 
1.0%
5 1
 
0.5%

지번주소
Text

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-05-11T05:13:34.955063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length37
Mean length30.261905
Min length21

Characters and Unicode

Total characters1271
Distinct characters73
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

Unique40 ?
Unique (%)95.2%

Sample

1st row서울특별시 동대문구 답십리1동 488번지 327호 3층
2nd row서울특별시 동대문구 장안동 372번지 1호
3rd row서울특별시 동대문구 장안동 345번지 10호 (지하1,지상1,2,3층)
4th row서울특별시 동대문구 장안동 372번지 3호 (지하1,지상3,4층)
5th row서울특별시 동대문구 휘경동 317번지 53호
ValueCountFrequency (%)
서울특별시 42
 
16.8%
동대문구 42
 
16.8%
장안동 14
 
5.6%
제기동 8
 
3.2%
1호 6
 
2.4%
2층 5
 
2.0%
용두동 5
 
2.0%
2호 5
 
2.0%
청량리동 4
 
1.6%
답십리동 4
 
1.6%
Other values (90) 115
46.0%
2024-05-11T05:13:36.210889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
16.4%
동 86
 
6.8%
지 54
 
4.2%
1 48
 
3.8%
호 43
 
3.4%
대 43
 
3.4%
서 43
 
3.4%
문 43
 
3.4%
시 42
 
3.3%
별 42
 
3.3%
Other values (63) 619
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 732
57.6%
Decimal Number 263
 
20.7%
Space Separator 208
 
16.4%
Other Punctuation 28
 
2.2%
Open Punctuation 18
 
1.4%
Close Punctuation 18
 
1.4%
Uppercase Letter 2
 
0.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 86
 
11.7%
지 54
 
7.4%
호 43
 
5.9%
대 43
 
5.9%
서 43
 
5.9%
문 43
 
5.9%
시 42
 
5.7%
별 42
 
5.7%
구 42
 
5.7%
울 42
 
5.7%
Other values (47) 252
34.4%
Decimal Number
ValueCountFrequency (%)
1 48
18.3%
2 42
16.0%
3 41
15.6%
4 28
10.6%
7 26
9.9%
6 21
8.0%
5 19
 
7.2%
9 16
 
6.1%
8 12
 
4.6%
0 10
 
3.8%
Space Separator
ValueCountFrequency (%)
208
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 732
57.6%
Common 537
42.3%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 86
 
11.7%
지 54
 
7.4%
호 43
 
5.9%
대 43
 
5.9%
서 43
 
5.9%
문 43
 
5.9%
시 42
 
5.7%
별 42
 
5.7%
구 42
 
5.7%
울 42
 
5.7%
Other values (47) 252
34.4%
Common
ValueCountFrequency (%)
208
38.7%
1 48
 
8.9%
2 42
 
7.8%
3 41
 
7.6%
4 28
 
5.2%
, 28
 
5.2%
7 26
 
4.8%
6 21
 
3.9%
5 19
 
3.5%
( 18
 
3.4%
Other values (5) 58
 
10.8%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 732
57.6%
ASCII 539
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
38.6%
1 48
 
8.9%
2 42
 
7.8%
3 41
 
7.6%
4 28
 
5.2%
, 28
 
5.2%
7 26
 
4.8%
6 21
 
3.9%
5 19
 
3.5%
( 18
 
3.3%
Other values (6) 60
 
11.1%
Hangul
ValueCountFrequency (%)
동 86
 
11.7%
지 54
 
7.4%
호 43
 
5.9%
대 43
 
5.9%
서 43
 
5.9%
문 43
 
5.9%
시 42
 
5.7%
별 42
 
5.7%
구 42
 
5.7%
울 42
 
5.7%
Other values (47) 252
34.4%

도로명주소
Text

Distinct39
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-05-11T05:13:36.889460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length32.142857
Min length23

Characters and Unicode

Total characters1350
Distinct characters78
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

Unique37 ?
Unique (%)88.1%

Sample

1st row서울특별시 동대문구 전농로 12, 3층 (답십리동)
2nd row서울특별시 동대문구 장한로 115 (장안동)
3rd row서울특별시 동대문구 장한로26가길 31 (장안동,(지하1,지상1,2,3층))
4th row서울특별시 동대문구 장한로 111-1 (장안동,(지하1,지상3,4층))
5th row서울특별시 동대문구 망우로 34 (휘경동)
ValueCountFrequency (%)
서울특별시 42
 
18.1%
동대문구 42
 
18.1%
장한로 11
 
4.7%
제기동 6
 
2.6%
2층 6
 
2.6%
왕산로 5
 
2.2%
고산자로 4
 
1.7%
용두동 4
 
1.7%
답십리동 3
 
1.3%
장안동,장한로 3
 
1.3%
Other values (90) 106
45.7%
2024-05-11T05:13:38.136009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190
 
14.1%
동 88
 
6.5%
( 60
 
4.4%
) 60
 
4.4%
, 56
 
4.1%
2 50
 
3.7%
로 48
 
3.6%
1 47
 
3.5%
대 45
 
3.3%
시 44
 
3.3%
Other values (68) 662
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 771
57.1%
Decimal Number 205
 
15.2%
Space Separator 190
 
14.1%
Open Punctuation 60
 
4.4%
Close Punctuation 60
 
4.4%
Other Punctuation 56
 
4.1%
Dash Punctuation 5
 
0.4%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 88
 
11.4%
로 48
 
6.2%
대 45
 
5.8%
시 44
 
5.7%
문 44
 
5.7%
울 42
 
5.4%
서 42
 
5.4%
구 42
 
5.4%
특 42
 
5.4%
별 42
 
5.4%
Other values (51) 292
37.9%
Decimal Number
ValueCountFrequency (%)
2 50
24.4%
1 47
22.9%
3 26
12.7%
4 23
11.2%
0 12
 
5.9%
5 12
 
5.9%
8 10
 
4.9%
9 9
 
4.4%
7 8
 
3.9%
6 8
 
3.9%
Space Separator
ValueCountFrequency (%)
190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 771
57.1%
Common 577
42.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 88
 
11.4%
로 48
 
6.2%
대 45
 
5.8%
시 44
 
5.7%
문 44
 
5.7%
울 42
 
5.4%
서 42
 
5.4%
구 42
 
5.4%
특 42
 
5.4%
별 42
 
5.4%
Other values (51) 292
37.9%
Common
ValueCountFrequency (%)
190
32.9%
( 60
 
10.4%
) 60
 
10.4%
, 56
 
9.7%
2 50
 
8.7%
1 47
 
8.1%
3 26
 
4.5%
4 23
 
4.0%
0 12
 
2.1%
5 12
 
2.1%
Other values (6) 41
 
7.1%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 771
57.1%
ASCII 579
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190
32.8%
( 60
 
10.4%
) 60
 
10.4%
, 56
 
9.7%
2 50
 
8.6%
1 47
 
8.1%
3 26
 
4.5%
4 23
 
4.0%
0 12
 
2.1%
5 12
 
2.1%
Other values (7) 43
 
7.4%
Hangul
ValueCountFrequency (%)
동 88
 
11.4%
로 48
 
6.2%
대 45
 
5.8%
시 44
 
5.7%
문 44
 
5.7%
울 42
 
5.4%
서 42
 
5.4%
구 42
 
5.4%
특 42
 
5.4%
별 42
 
5.4%
Other values (51) 292
37.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)83.3%
Missing24
Missing (%)57.1%
Infinite0
Infinite (%)0.0%
Mean31063.778
Minimum2436
Maximum130842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T05:13:38.672301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2436
5-th percentile2480.2
Q12561
median2570.5
Q32621.75
95-th percentile130840.3
Maximum130842
Range128406
Interquartile range (IQR)60.75

Descriptive statistics

Standard deviation54871.144
Coefficient of variation (CV)1.7664028
Kurtosis0.13660456
Mean31063.778
Median Absolute Deviation (MAD)16
Skewness1.460986
Sum559148
Variance3.0108424 × 109
MonotonicityNot monotonic
2024-05-11T05:13:39.106992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2570 3
 
7.1%
2560 2
 
4.8%
2621 1
 
2.4%
130840 1
 
2.4%
130842 1
 
2.4%
2586 1
 
2.4%
130805 1
 
2.4%
130817 1
 
2.4%
2436 1
 
2.4%
2554 1
 
2.4%
Other values (5) 5
 
11.9%
(Missing) 24
57.1%
ValueCountFrequency (%)
2436 1
 
2.4%
2488 1
 
2.4%
2554 1
 
2.4%
2560 2
4.8%
2564 1
 
2.4%
2570 3
7.1%
2571 1
 
2.4%
2572 1
 
2.4%
2586 1
 
2.4%
2621 1
 
2.4%
ValueCountFrequency (%)
130842 1
 
2.4%
130840 1
 
2.4%
130817 1
 
2.4%
130805 1
 
2.4%
2622 1
 
2.4%
2621 1
 
2.4%
2586 1
 
2.4%
2572 1
 
2.4%
2571 1
 
2.4%
2570 3
7.1%

사업장명
Text

Distinct36
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-05-11T05:13:39.718648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.2857143
Min length5

Characters and Unicode

Total characters306
Distinct characters90
Distinct categories5 ?
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 (%)73.8%

Sample

1st row쌍마안마시술소
2nd row동부안마시술소
3rd row백운안마시술소
4th row추카추카안마시술소
5th row비너스안마시술소
ValueCountFrequency (%)
비너스안마시술소 3
 
7.0%
임금지압안마원 2
 
4.7%
궁전안마시술소 2
 
4.7%
무병장수안마원 2
 
4.7%
지호안마원 2
 
4.7%
탤런트안마시술소 1
 
2.3%
참좋은지압안마원 1
 
2.3%
김기태안마원 1
 
2.3%
명품체질지압안마원 1
 
2.3%
약손지압안마원 1
 
2.3%
Other values (27) 27
62.8%
2024-05-11T05:13:40.803661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 42
13.7%
안 40
 
13.1%
시 26
 
8.5%
술 25
 
8.2%
소 25
 
8.2%
원 18
 
5.9%
지 11
 
3.6%
압 8
 
2.6%
비 4
 
1.3%
스 4
 
1.3%
Other values (80) 103
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
98.0%
Uppercase Letter 3
 
1.0%
Space Separator 1
 
0.3%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 42
14.0%
안 40
13.3%
시 26
 
8.7%
술 25
 
8.3%
소 25
 
8.3%
원 18
 
6.0%
지 11
 
3.7%
압 8
 
2.7%
비 4
 
1.3%
스 4
 
1.3%
Other values (74) 97
32.3%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
T 1
33.3%
P 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
98.0%
Common 3
 
1.0%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 42
14.0%
안 40
13.3%
시 26
 
8.7%
술 25
 
8.3%
소 25
 
8.3%
원 18
 
6.0%
지 11
 
3.7%
압 8
 
2.7%
비 4
 
1.3%
스 4
 
1.3%
Other values (74) 97
32.3%
Common
ValueCountFrequency (%)
1
33.3%
) 1
33.3%
( 1
33.3%
Latin
ValueCountFrequency (%)
O 1
33.3%
T 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
98.0%
ASCII 6
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 42
14.0%
안 40
13.3%
시 26
 
8.7%
술 25
 
8.3%
소 25
 
8.3%
원 18
 
6.0%
지 11
 
3.7%
압 8
 
2.7%
비 4
 
1.3%
스 4
 
1.3%
Other values (74) 97
32.3%
ASCII
ValueCountFrequency (%)
1
16.7%
O 1
16.7%
) 1
16.7%
T 1
16.7%
( 1
16.7%
P 1
16.7%

최종수정일자
Date

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2009-01-07 10:17:58
Maximum2024-04-02 13:58:05
2024-05-11T05:13:41.343962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:13:41.954495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
I
34 
U
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 34
81.0%
U 8
 
19.0%

Length

2024-05-11T05:13:42.483512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:42.948221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 34
81.0%
u 8
 
19.0%

데이터갱신일자
Date

Distinct11
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:04:00
2024-05-11T05:13:43.260999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:13:43.803800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

업태구분명
Categorical

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
안마시술소
25 
안마원
17 

Length

Max length5
Median length5
Mean length4.1904762
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마시술소 25
59.5%
안마원 17
40.5%

Length

2024-05-11T05:13:44.274278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:44.674150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마시술소 25
59.5%
안마원 17
40.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)85.4%
Missing1
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean204644.08
Minimum201997.95
Maximum206279.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T05:13:45.022467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201997.95
5-th percentile203244.19
Q1203451.44
median204884.45
Q3206076.9
95-th percentile206246.15
Maximum206279.69
Range4281.7393
Interquartile range (IQR)2625.4626

Descriptive statistics

Standard deviation1279.9331
Coefficient of variation (CV)0.0062544351
Kurtosis-1.1297782
Mean204644.08
Median Absolute Deviation (MAD)1269.8743
Skewness-0.21549451
Sum8390407.4
Variance1638228.9
MonotonicityNot monotonic
2024-05-11T05:13:45.437634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
203303.260023977 3
 
7.1%
206158.609154575 2
 
4.8%
204974.427135263 2
 
4.8%
206076.898359221 2
 
4.8%
203451.43573121 2
 
4.8%
205450.919680774 1
 
2.4%
204662.341213164 1
 
2.4%
201997.95066552 1
 
2.4%
203614.577614527 1
 
2.4%
204089.817117361 1
 
2.4%
Other values (25) 25
59.5%
ValueCountFrequency (%)
201997.95066552 1
 
2.4%
202015.405337661 1
 
2.4%
203244.194730719 1
 
2.4%
203264.091526218 1
 
2.4%
203303.260023977 3
7.1%
203358.086492638 1
 
2.4%
203360.831597984 1
 
2.4%
203451.43573121 2
4.8%
203515.178762769 1
 
2.4%
203534.238993913 1
 
2.4%
ValueCountFrequency (%)
206279.689993328 1
2.4%
206249.026456633 1
2.4%
206246.145219342 1
2.4%
206239.099846845 1
2.4%
206166.994766177 1
2.4%
206158.609154575 2
4.8%
206144.348296014 1
2.4%
206097.029464604 1
2.4%
206076.898359221 2
4.8%
205865.688377736 1
2.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)85.4%
Missing1
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean452537.43
Minimum451110.25
Maximum454258.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T05:13:46.289659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451110.25
5-th percentile451193.92
Q1451914.78
median452611.4
Q3453148.89
95-th percentile454008.04
Maximum454258.22
Range3147.9729
Interquartile range (IQR)1234.1131

Descriptive statistics

Standard deviation854.08178
Coefficient of variation (CV)0.0018873174
Kurtosis-0.85696768
Mean452537.43
Median Absolute Deviation (MAD)596.33328
Skewness0.070076364
Sum18554035
Variance729455.69
MonotonicityNot monotonic
2024-05-11T05:13:46.774818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
453148.892643354 3
 
7.1%
452075.431032307 2
 
4.8%
454008.040992673 2
 
4.8%
451784.733600414 2
 
4.8%
452611.401341474 2
 
4.8%
454258.218194207 1
 
2.4%
451605.260722901 1
 
2.4%
452772.273114985 1
 
2.4%
453106.963628925 1
 
2.4%
453314.135663101 1
 
2.4%
Other values (25) 25
59.5%
ValueCountFrequency (%)
451110.245309908 1
2.4%
451139.60744767 1
2.4%
451193.91719632 1
2.4%
451249.571870528 1
2.4%
451290.385714542 1
2.4%
451529.148204191 1
2.4%
451605.260722901 1
2.4%
451784.733600414 2
4.8%
451827.438245305 1
2.4%
451914.779527497 1
2.4%
ValueCountFrequency (%)
454258.218194207 1
 
2.4%
454008.040992673 2
4.8%
453852.661963297 1
 
2.4%
453459.013903349 1
 
2.4%
453415.795068163 1
 
2.4%
453314.135663101 1
 
2.4%
453280.132707797 1
 
2.4%
453207.734619347 1
 
2.4%
453148.892643354 3
7.1%
453106.963628925 1
 
2.4%

의료유사업종별명
Categorical

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
안마시술소
22 
안마원
13 
<NA>
7 

Length

Max length5
Median length5
Mean length4.2142857
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마시술소 22
52.4%
안마원 13
31.0%
<NA> 7
 
16.7%

Length

2024-05-11T05:13:47.339041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:47.753934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마시술소 22
52.4%
안마원 13
31.0%
na 7
 
16.7%

종업원수
Categorical

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
2
25 
<NA>
10 
1
5 
0
 
2

Length

Max length4
Median length1
Mean length1.7142857
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 25
59.5%
<NA> 10
 
23.8%
1 5
 
11.9%
0 2
 
4.8%

Length

2024-05-11T05:13:48.154667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:48.526230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 25
59.5%
na 10
 
23.8%
1 5
 
11.9%
0 2
 
4.8%

자격증소유자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
41 
0
 
1

Length

Max length4
Median length4
Mean length3.9285714
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 41
97.6%
0 1
 
2.4%

Length

2024-05-11T05:13:49.033775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:49.432714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 41
97.6%
0 1
 
2.4%

보조종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
41 
0
 
1

Length

Max length4
Median length4
Mean length3.9285714
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 41
97.6%
0 1
 
2.4%

Length

2024-05-11T05:13:49.935577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:50.360654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 41
97.6%
0 1
 
2.4%

시설관리자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
41 
0
 
1

Length

Max length4
Median length4
Mean length3.9285714
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 41
97.6%
0 1
 
2.4%

Length

2024-05-11T05:13:50.875489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:51.292814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 41
97.6%
0 1
 
2.4%

기타종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
41 
0
 
1

Length

Max length4
Median length4
Mean length3.9285714
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 41
97.6%
0 1
 
2.4%

Length

2024-05-11T05:13:51.742131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:52.155924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 41
97.6%
0 1
 
2.4%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)58.6%
Missing13
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean12.37931
Minimum0
Maximum28
Zeros1
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T05:13:52.563219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median14
Q318
95-th percentile24.6
Maximum28
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.4194239
Coefficient of variation (CV)0.6801206
Kurtosis-1.1733328
Mean12.37931
Median Absolute Deviation (MAD)7
Skewness-0.014215889
Sum359
Variance70.8867
MonotonicityNot monotonic
2024-05-11T05:13:53.168380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 4
 
9.5%
4 3
 
7.1%
11 3
 
7.1%
18 3
 
7.1%
14 3
 
7.1%
21 2
 
4.8%
22 1
 
2.4%
16 1
 
2.4%
25 1
 
2.4%
28 1
 
2.4%
Other values (7) 7
16.7%
(Missing) 13
31.0%
ValueCountFrequency (%)
0 1
 
2.4%
1 4
9.5%
2 1
 
2.4%
4 3
7.1%
7 1
 
2.4%
11 3
7.1%
13 1
 
2.4%
14 3
7.1%
15 1
 
2.4%
16 1
 
2.4%
ValueCountFrequency (%)
28 1
 
2.4%
25 1
 
2.4%
24 1
 
2.4%
22 1
 
2.4%
21 2
4.8%
20 1
 
2.4%
18 3
7.1%
16 1
 
2.4%
15 1
 
2.4%
14 3
7.1%

욕실면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
40 
0
 
2

Length

Max length4
Median length4
Mean length3.8571429
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> 40
95.2%
0 2
 
4.8%

Length

2024-05-11T05:13:53.660918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:13:54.016663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
95.2%
0 2
 
4.8%

총면적
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)100.0%
Missing7
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean2118.2903
Minimum9
Maximum62649
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T05:13:54.458850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile14.02
Q168.9
median242.58
Q3681.605
95-th percentile824.601
Maximum62649
Range62640
Interquartile range (IQR)612.705

Descriptive statistics

Standard deviation10536.783
Coefficient of variation (CV)4.974192
Kurtosis34.937747
Mean2118.2903
Median Absolute Deviation (MAD)210.82
Skewness5.9084169
Sum74140.16
Variance1.1102379 × 108
MonotonicityNot monotonic
2024-05-11T05:13:54.940919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
694.85 1
 
2.4%
808.46 1
 
2.4%
588.49 1
 
2.4%
31.76 1
 
2.4%
71.82 1
 
2.4%
77.35 1
 
2.4%
9.4 1
 
2.4%
95.0 1
 
2.4%
95.04 1
 
2.4%
120.33 1
 
2.4%
Other values (25) 25
59.5%
(Missing) 7
 
16.7%
ValueCountFrequency (%)
9.0 1
2.4%
9.4 1
2.4%
16.0 1
2.4%
31.76 1
2.4%
49.58 1
2.4%
51.83 1
2.4%
52.0 1
2.4%
56.64 1
2.4%
65.98 1
2.4%
71.82 1
2.4%
ValueCountFrequency (%)
62649.0 1
2.4%
829.97 1
2.4%
822.3 1
2.4%
808.46 1
2.4%
790.52 1
2.4%
778.0 1
2.4%
707.26 1
2.4%
702.24 1
2.4%
694.85 1
2.4%
668.36 1
2.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03050000PHMB41982305003404240000119821113<NA>1영업/정상13영업중<NA><NA><NA><NA>2242-6011<NA>130805서울특별시 동대문구 답십리1동 488번지 327호 3층서울특별시 동대문구 전농로 12, 3층 (답십리동)2621쌍마안마시술소2022-03-31 18:02:38U2021-12-04 00:02:00.0안마시술소204884.451934451529.148204<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13050000PHMB41993305003404240000119930820<NA>3폐업3폐업20040531<NA><NA><NA>2215-8344<NA>130100서울특별시 동대문구 장안동 372번지 1호서울특별시 동대문구 장한로 115 (장안동)<NA>동부안마시술소2009-01-07 10:17:58I2018-08-31 23:59:59.0안마시술소206158.609155452075.431032안마시술소2<NA><NA><NA><NA>11<NA>111.0
23050000PHMB41993305003404240000219931004<NA>3폐업3폐업20070511<NA><NA><NA>2212-9388<NA>130100서울특별시 동대문구 장안동 345번지 10호 (지하1,지상1,2,3층)서울특별시 동대문구 장한로26가길 31 (장안동,(지하1,지상1,2,3층))130840백운안마시술소2009-01-07 10:21:27I2018-08-31 23:59:59.0안마시술소206249.026457451997.891788안마시술소2<NA><NA><NA><NA>28<NA>694.85
33050000PHMB41993305003404240000319931222<NA>3폐업3폐업20070419<NA><NA><NA>2245-8909<NA>130100서울특별시 동대문구 장안동 372번지 3호 (지하1,지상3,4층)서울특별시 동대문구 장한로 111-1 (장안동,(지하1,지상3,4층))130842추카추카안마시술소2009-01-07 10:24:46I2018-08-31 23:59:59.0안마시술소206144.348296452047.885951안마시술소2<NA><NA><NA><NA>14<NA>458.62
43050000PHMB41996305003404240000119960619<NA>3폐업3폐업20060525<NA><NA><NA>2246-0840<NA>130090서울특별시 동대문구 휘경동 317번지 53호서울특별시 동대문구 망우로 34 (휘경동)<NA>비너스안마시술소2009-01-07 10:27:09I2018-08-31 23:59:59.0안마시술소204974.427135454008.040993안마시술소2<NA><NA><NA><NA>18<NA>62649.0
53050000PHMB41998305003404240000219980416<NA>3폐업3폐업20080421<NA><NA><NA>969-0117<NA>130010서울특별시 동대문구 청량리동 235번지 6호 (지하11,12호)서울특별시 동대문구 왕산로 239 (청량리동,(지하11,12호))<NA>진주안마시술소2009-01-07 10:30:03I2018-08-31 23:59:59.0안마시술소204190.108783453415.795068안마시술소2<NA><NA><NA><NA>11<NA>137.7
63050000PHMB42001305003404240000120010130<NA>3폐업3폐업20050516<NA><NA><NA>32952332<NA>130010서울특별시 동대문구 청량리동 486번지 (1층)서울특별시 동대문구 제기로 93 (청량리동,(1층))<NA>남수침시술소2009-01-07 10:38:04I2018-08-31 23:59:59.0안마시술소203773.909766453852.661963안마시술소2<NA><NA><NA><NA>1<NA>52.0
73050000PHMB4200230500340424000012002-07-15<NA>1영업/정상13영업중<NA><NA><NA><NA>2234-7194<NA>130-814서울특별시 동대문구 신설동 117번지 13호 외 1필지, 2층서울특별시 동대문구 난계로 244, 2층 (신설동)2586흥일안마시술소2024-04-02 13:58:05U2023-12-04 00:04:00.0안마시술소202015.405338452340.246199<NA><NA><NA><NA><NA><NA><NA><NA><NA>
83050000PHMB42002305003404240000220020722<NA>3폐업3폐업20061004<NA><NA><NA>965-7382<NA>130060서울특별시 동대문구 제기동 1109번지 8호 (2층)서울특별시 동대문구 약령중앙로4길 7-1 (제기동,(2층))<NA>최태암침구시술소2009-01-07 10:40:36I2018-08-31 23:59:59.0안마시술소203244.194731453074.68013안마시술소2<NA><NA><NA><NA>1<NA>16.0
93050000PHMB42003305003404240000120030410<NA>3폐업3폐업20060123<NA><NA><NA>2243-9977<NA>130030서울특별시 동대문구 답십리동 952번지 18호 (7,8층)서울특별시 동대문구 천호대로 343 (답십리동,(7,8층))<NA>쵸이스안마시술소2009-01-07 10:42:52I2018-08-31 23:59:59.0안마시술소205045.366491451249.571871안마시술소2<NA><NA><NA><NA>21<NA>609.88
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
323050000PHMB42013305003404240000220131008<NA>3폐업3폐업20171128<NA><NA><NA>02-3394-7001<NA>130801서울특별시 동대문구 답십리동 99번지 20호서울특별시 동대문구 전농로 105 (답십리동)<NA>오성지압안마원2017-11-28 12:58:34I2018-08-31 23:59:59.0안마원204991.517304452449.878146안마원0<NA><NA><NA><NA>40120.33
333050000PHMB42013305003404240000320131114<NA>1영업/정상13영업중<NA><NA><NA><NA>961-8100<NA><NA>서울특별시 동대문구 전농동 597번지 38호 2층서울특별시 동대문구 왕산로 228, 2층 (전농동)2554청량리명안마원2017-11-22 10:42:55I2018-08-31 23:59:59.0안마원204149.452746453280.132708안마원<NA><NA><NA><NA><NA>7<NA>125.29
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353050000PHMB42014305003404240000220141229<NA>3폐업3폐업20210721<NA><NA><NA><NA><NA>130809서울특별시 동대문구 답십리동 961번지 2호서울특별시 동대문구 고미술로 100 (답십리동)2622약손지압안마원2021-07-21 13:41:24U2021-07-23 02:40:00.0안마원204999.40152451290.385715안마원000000051.83
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373050000PHMB42015305003404240000320150902<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 제기동 1109번지 6호서울특별시 동대문구 약령중앙로4길 9, 2층 (제기동)2570김기태안마원2015-09-02 09:58:11I2018-08-31 23:59:59.0안마원203264.091526453073.831727안마원<NA><NA><NA><NA><NA><NA><NA>49.58
383050000PHMB42016305003404240000120161014<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 청량리동 50번지 18호 202호서울특별시 동대문구 왕산로 247-1, 202호 (청량리동)2488참좋은지압안마원2016-10-14 13:37:18I2018-08-31 23:59:59.0안마원204257.27418453459.013903안마원2<NA><NA><NA><NA>4<NA>56.64
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403050000PHMB42020305003404240000220200227<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 제기동 992번지 3호서울특별시 동대문구 경동시장로 11, 2층 (제기동)2571신동만안마원2020-02-27 15:40:48I2020-02-29 00:23:35.0안마원203515.178763453068.681339안마원1<NA><NA><NA><NA>1<NA>65.98
413050000PHMB4202430500340424000012024-01-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-963-1066<NA><NA>서울특별시 동대문구 용두동 39-944서울특별시 동대문구 고산자로30길 28, 2층 (용두동)2564임금지압안마원2024-01-02 17:04:07I2023-12-01 00:04:00.0안마원203451.435731452611.401341<NA><NA><NA><NA><NA><NA><NA><NA><NA>