Overview

Dataset statistics

Number of variables34
Number of observations22
Missing cells153
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory298.0 B

Variable types

Categorical14
Text5
DateTime4
Unsupported5
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-16372/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
자격증소유자수 is highly imbalanced (73.3%)Imbalance
보조종업원수 is highly imbalanced (73.3%)Imbalance
시설관리자수 is highly imbalanced (73.3%)Imbalance
기타종업원수 is highly imbalanced (73.3%)Imbalance
인허가취소일자 has 22 (100.0%) missing valuesMissing
폐업일자 has 11 (50.0%) missing valuesMissing
휴업시작일자 has 22 (100.0%) missing valuesMissing
휴업종료일자 has 22 (100.0%) missing valuesMissing
재개업일자 has 22 (100.0%) missing valuesMissing
전화번호 has 2 (9.1%) missing valuesMissing
소재지면적 has 22 (100.0%) missing valuesMissing
소재지우편번호 has 11 (50.0%) missing valuesMissing
도로명주소 has 2 (9.1%) missing valuesMissing
도로명우편번호 has 2 (9.1%) missing valuesMissing
병상수 has 8 (36.4%) missing valuesMissing
총면적 has 7 (31.8%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
지번주소 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 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

Reproduction

Analysis started2024-04-17 21:01:40.748703
Analysis finished2024-04-17 21:01:41.073943
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
3140000
22 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 22
100.0%

Length

2024-04-18T06:01:41.122924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:41.211589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 22
100.0%

관리번호
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-18T06:01:41.351647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters550
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

Unique22 ?
Unique (%)100.0%

Sample

1st rowPHMB419903140033042400001
2nd rowPHMB419983140033042400001
3rd rowPHMB420023140033042400001
4th rowPHMB420073140033042400001
5th rowPHMB420083140033042400001
ValueCountFrequency (%)
phmb419903140033042400001 1
 
4.5%
phmb419983140033042400001 1
 
4.5%
phmb420193140033042400002 1
 
4.5%
phmb420193140033042400001 1
 
4.5%
phmb420183140033042400001 1
 
4.5%
phmb420173140033042400003 1
 
4.5%
phmb420173140033042400002 1
 
4.5%
phmb420173140033042400001 1
 
4.5%
phmb420163140033042400003 1
 
4.5%
phmb420163140033042400002 1
 
4.5%
Other values (12) 12
54.5%
2024-04-18T06:01:41.604926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 179
32.5%
4 89
16.2%
3 69
 
12.5%
1 56
 
10.2%
2 50
 
9.1%
P 22
 
4.0%
H 22
 
4.0%
M 22
 
4.0%
B 22
 
4.0%
9 7
 
1.3%
Other values (4) 12
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 462
84.0%
Uppercase Letter 88
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 179
38.7%
4 89
19.3%
3 69
 
14.9%
1 56
 
12.1%
2 50
 
10.8%
9 7
 
1.5%
7 4
 
0.9%
8 3
 
0.6%
6 3
 
0.6%
5 2
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
P 22
25.0%
H 22
25.0%
M 22
25.0%
B 22
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 462
84.0%
Latin 88
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 179
38.7%
4 89
19.3%
3 69
 
14.9%
1 56
 
12.1%
2 50
 
10.8%
9 7
 
1.5%
7 4
 
0.9%
8 3
 
0.6%
6 3
 
0.6%
5 2
 
0.4%
Latin
ValueCountFrequency (%)
P 22
25.0%
H 22
25.0%
M 22
25.0%
B 22
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 179
32.5%
4 89
16.2%
3 69
 
12.5%
1 56
 
10.2%
2 50
 
9.1%
P 22
 
4.0%
H 22
 
4.0%
M 22
 
4.0%
B 22
 
4.0%
9 7
 
1.3%
Other values (4) 12
 
2.2%

인허가일자
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum1990-03-24 00:00:00
Maximum2023-04-07 00:00:00
2024-04-18T06:01:41.710006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:41.797728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
3
11 
1
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 11
50.0%
1 11
50.0%

Length

2024-04-18T06:01:41.881786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:41.953952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 11
50.0%
1 11
50.0%

영업상태명
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
폐업
11 
영업/정상
11 

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 11
50.0%
영업/정상 11
50.0%

Length

2024-04-18T06:01:42.036840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:42.127085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 11
50.0%
영업/정상 11
50.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
3
11 
13
11 

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 11
50.0%
13 11
50.0%

Length

2024-04-18T06:01:42.216678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:42.294836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 11
50.0%
13 11
50.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
폐업
11 
영업중
11 

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 11
50.0%
영업중 11
50.0%

Length

2024-04-18T06:01:42.374805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:42.449449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 11
50.0%
영업중 11
50.0%

폐업일자
Date

MISSING 

Distinct11
Distinct (%)100.0%
Missing11
Missing (%)50.0%
Memory size308.0 B
Minimum2009-05-06 00:00:00
Maximum2024-03-24 00:00:00
2024-04-18T06:01:42.513753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:42.591923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

전화번호
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-04-18T06:01:42.743033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length10.5
Min length9

Characters and Unicode

Total characters210
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 row02-2643-4546
2nd row2699-4999
3rd row2696-8843
4th row2645-7975
5th row2655-2200
ValueCountFrequency (%)
2699-4999 1
 
5.0%
2696-8843 1
 
5.0%
2606-7781 1
 
5.0%
02-2694-1114 1
 
5.0%
02-6339-8275 1
 
5.0%
02-2699-1217 1
 
5.0%
02-2601-7737 1
 
5.0%
02-2644-8789 1
 
5.0%
2690-3707 1
 
5.0%
02-2696-8280 1
 
5.0%
Other values (10) 10
50.0%
2024-04-18T06:01:42.984811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 36
17.1%
6 32
15.2%
- 30
14.3%
9 23
11.0%
0 19
9.0%
7 16
7.6%
4 15
7.1%
8 12
 
5.7%
5 12
 
5.7%
1 8
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
85.7%
Dash Punctuation 30
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 36
20.0%
6 32
17.8%
9 23
12.8%
0 19
10.6%
7 16
8.9%
4 15
8.3%
8 12
 
6.7%
5 12
 
6.7%
1 8
 
4.4%
3 7
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 36
17.1%
6 32
15.2%
- 30
14.3%
9 23
11.0%
0 19
9.0%
7 16
7.6%
4 15
7.1%
8 12
 
5.7%
5 12
 
5.7%
1 8
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 36
17.1%
6 32
15.2%
- 30
14.3%
9 23
11.0%
0 19
9.0%
7 16
7.6%
4 15
7.1%
8 12
 
5.7%
5 12
 
5.7%
1 8
 
3.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)90.9%
Missing11
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean158693.91
Minimum158070
Maximum158863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T06:01:43.076744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum158070
5-th percentile158072
Q1158759
median158857
Q3158860
95-th percentile158862
Maximum158863
Range793
Interquartile range (IQR)101

Descriptive statistics

Standard deviation310.75536
Coefficient of variation (CV)0.0019582059
Kurtosis1.8120512
Mean158693.91
Median Absolute Deviation (MAD)6
Skewness-1.8350751
Sum1745633
Variance96568.891
MonotonicityNot monotonic
2024-04-18T06:01:43.162910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
158860 2
 
9.1%
158070 1
 
4.5%
158074 1
 
4.5%
158861 1
 
4.5%
158811 1
 
4.5%
158857 1
 
4.5%
158859 1
 
4.5%
158712 1
 
4.5%
158806 1
 
4.5%
158863 1
 
4.5%
(Missing) 11
50.0%
ValueCountFrequency (%)
158070 1
4.5%
158074 1
4.5%
158712 1
4.5%
158806 1
4.5%
158811 1
4.5%
158857 1
4.5%
158859 1
4.5%
158860 2
9.1%
158861 1
4.5%
158863 1
4.5%
ValueCountFrequency (%)
158863 1
4.5%
158861 1
4.5%
158860 2
9.1%
158859 1
4.5%
158857 1
4.5%
158811 1
4.5%
158806 1
4.5%
158712 1
4.5%
158074 1
4.5%
158070 1
4.5%

지번주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-18T06:01:43.327126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32.5
Mean length27.590909
Min length21

Characters and Unicode

Total characters607
Distinct characters49
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

Unique22 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목동 404번지 114호 1,2,3,4층
2nd row서울특별시 양천구 신정동 902번지 18호 (오목로146)
3rd row서울특별시 양천구 신정동 972번지 5호 (신정중앙길13)
4th row서울특별시 양천구 신정1동 1026번지 2호 201호
5th row서울특별시 양천구 목3동 609번지 17호 3층
ValueCountFrequency (%)
서울특별시 22
16.9%
양천구 22
16.9%
신정동 8
 
6.2%
목동 6
 
4.6%
신정4동 4
 
3.1%
3층 4
 
3.1%
2호 3
 
2.3%
6호 3
 
2.3%
11호 2
 
1.5%
2층 2
 
1.5%
Other values (44) 54
41.5%
2024-04-18T06:01:43.637942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
17.8%
1 32
 
5.3%
동 26
 
4.3%
호 24
 
4.0%
지 23
 
3.8%
서 22
 
3.6%
특 22
 
3.6%
별 22
 
3.6%
시 22
 
3.6%
양 22
 
3.6%
Other values (39) 284
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 346
57.0%
Decimal Number 145
23.9%
Space Separator 108
 
17.8%
Other Punctuation 3
 
0.5%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
 
7.5%
호 24
 
6.9%
지 23
 
6.6%
서 22
 
6.4%
특 22
 
6.4%
별 22
 
6.4%
시 22
 
6.4%
양 22
 
6.4%
천 22
 
6.4%
구 22
 
6.4%
Other values (24) 119
34.4%
Decimal Number
ValueCountFrequency (%)
1 32
22.1%
4 20
13.8%
2 19
13.1%
0 15
10.3%
9 15
10.3%
5 12
 
8.3%
6 11
 
7.6%
3 10
 
6.9%
7 6
 
4.1%
8 5
 
3.4%
Space Separator
ValueCountFrequency (%)
108
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
57.0%
Common 261
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
 
7.5%
호 24
 
6.9%
지 23
 
6.6%
서 22
 
6.4%
특 22
 
6.4%
별 22
 
6.4%
시 22
 
6.4%
양 22
 
6.4%
천 22
 
6.4%
구 22
 
6.4%
Other values (24) 119
34.4%
Common
ValueCountFrequency (%)
108
41.4%
1 32
 
12.3%
4 20
 
7.7%
2 19
 
7.3%
0 15
 
5.7%
9 15
 
5.7%
5 12
 
4.6%
6 11
 
4.2%
3 10
 
3.8%
7 6
 
2.3%
Other values (5) 13
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 346
57.0%
ASCII 261
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
41.4%
1 32
 
12.3%
4 20
 
7.7%
2 19
 
7.3%
0 15
 
5.7%
9 15
 
5.7%
5 12
 
4.6%
6 11
 
4.2%
3 10
 
3.8%
7 6
 
2.3%
Other values (5) 13
 
5.0%
Hangul
ValueCountFrequency (%)
동 26
 
7.5%
호 24
 
6.9%
지 23
 
6.6%
서 22
 
6.4%
특 22
 
6.4%
별 22
 
6.4%
시 22
 
6.4%
양 22
 
6.4%
천 22
 
6.4%
구 22
 
6.4%
Other values (24) 119
34.4%

도로명주소
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-04-18T06:01:43.805099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length34.5
Mean length29.6
Min length25

Characters and Unicode

Total characters592
Distinct characters51
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

Unique18 ?
Unique (%)90.0%

Sample

1st row서울특별시 양천구 신목로 96, 1,2,3,4층 (목동)
2nd row서울특별시 양천구 신월로 340, 2층 201호 (신정동)
3rd row서울특별시 양천구 목동중앙북로7길 13, 3층 (목동)
4th row서울특별시 양천구 오목로 217, 5층 (신정동)
5th row서울특별시 양천구 오목로24길 17-1 (신정동)
ValueCountFrequency (%)
서울특별시 20
16.3%
양천구 20
16.3%
신정동 11
 
8.9%
목동 7
 
5.7%
3층 5
 
4.1%
2층 3
 
2.4%
5층 2
 
1.6%
월정로 2
 
1.6%
4층 2
 
1.6%
신목로 2
 
1.6%
Other values (39) 49
39.8%
2024-04-18T06:01:44.099863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
 
17.4%
동 29
 
4.9%
, 23
 
3.9%
서 20
 
3.4%
구 20
 
3.4%
) 20
 
3.4%
울 20
 
3.4%
로 20
 
3.4%
목 20
 
3.4%
천 20
 
3.4%
Other values (41) 297
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 334
56.4%
Space Separator 103
 
17.4%
Decimal Number 89
 
15.0%
Other Punctuation 23
 
3.9%
Close Punctuation 20
 
3.4%
Open Punctuation 20
 
3.4%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
 
8.7%
서 20
 
6.0%
구 20
 
6.0%
울 20
 
6.0%
로 20
 
6.0%
목 20
 
6.0%
천 20
 
6.0%
양 20
 
6.0%
시 20
 
6.0%
별 20
 
6.0%
Other values (26) 125
37.4%
Decimal Number
ValueCountFrequency (%)
2 18
20.2%
3 17
19.1%
1 14
15.7%
4 11
12.4%
7 9
10.1%
5 7
 
7.9%
0 6
 
6.7%
8 3
 
3.4%
9 3
 
3.4%
6 1
 
1.1%
Space Separator
ValueCountFrequency (%)
103
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 334
56.4%
Common 258
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
 
8.7%
서 20
 
6.0%
구 20
 
6.0%
울 20
 
6.0%
로 20
 
6.0%
목 20
 
6.0%
천 20
 
6.0%
양 20
 
6.0%
시 20
 
6.0%
별 20
 
6.0%
Other values (26) 125
37.4%
Common
ValueCountFrequency (%)
103
39.9%
, 23
 
8.9%
) 20
 
7.8%
( 20
 
7.8%
2 18
 
7.0%
3 17
 
6.6%
1 14
 
5.4%
4 11
 
4.3%
7 9
 
3.5%
5 7
 
2.7%
Other values (5) 16
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 334
56.4%
ASCII 258
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
103
39.9%
, 23
 
8.9%
) 20
 
7.8%
( 20
 
7.8%
2 18
 
7.0%
3 17
 
6.6%
1 14
 
5.4%
4 11
 
4.3%
7 9
 
3.5%
5 7
 
2.7%
Other values (5) 16
 
6.2%
Hangul
ValueCountFrequency (%)
동 29
 
8.7%
서 20
 
6.0%
구 20
 
6.0%
울 20
 
6.0%
로 20
 
6.0%
목 20
 
6.0%
천 20
 
6.0%
양 20
 
6.0%
시 20
 
6.0%
별 20
 
6.0%
Other values (26) 125
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)75.0%
Missing2
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean15549.25
Minimum7930
Maximum158861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T06:01:44.189282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7930
5-th percentile7944.25
Q17991
median8022
Q38027.25
95-th percentile15616.2
Maximum158861
Range150931
Interquartile range (IQR)36.25

Descriptive statistics

Standard deviation33732.113
Coefficient of variation (CV)2.1693723
Kurtosis19.999926
Mean15549.25
Median Absolute Deviation (MAD)17
Skewness4.4721241
Sum310985
Variance1.1378554 × 109
MonotonicityNot monotonic
2024-04-18T06:01:44.624341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
8022 3
13.6%
8007 2
 
9.1%
8027 2
 
9.1%
8005 2
 
9.1%
158861 1
 
4.5%
7946 1
 
4.5%
7945 1
 
4.5%
8026 1
 
4.5%
8073 1
 
4.5%
8077 1
 
4.5%
Other values (5) 5
22.7%
(Missing) 2
 
9.1%
ValueCountFrequency (%)
7930 1
 
4.5%
7945 1
 
4.5%
7946 1
 
4.5%
7948 1
 
4.5%
7949 1
 
4.5%
8005 2
9.1%
8007 2
9.1%
8022 3
13.6%
8026 1
 
4.5%
8027 2
9.1%
ValueCountFrequency (%)
158861 1
 
4.5%
8077 1
 
4.5%
8073 1
 
4.5%
8058 1
 
4.5%
8028 1
 
4.5%
8027 2
9.1%
8026 1
 
4.5%
8022 3
13.6%
8007 2
9.1%
8005 2
9.1%

사업장명
Text

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-18T06:01:44.766785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.5454545
Min length5

Characters and Unicode

Total characters144
Distinct characters51
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

Unique18 ?
Unique (%)81.8%

Sample

1st row스타안마시술소
2nd row홍안마시술소
3rd row으뜸안마시술소
4th row라파안마원
5th row약손365안마원
ValueCountFrequency (%)
라파안마원 2
 
9.1%
홍안마시술소 2
 
9.1%
스타안마시술소 1
 
4.5%
건강안마원 1
 
4.5%
서울보건안마원 1
 
4.5%
예손지압안마원 1
 
4.5%
목동건강안마원 1
 
4.5%
약손힐링원 1
 
4.5%
바른체형안마원 1
 
4.5%
담손정통지압안마원 1
 
4.5%
Other values (10) 10
45.5%
2024-04-18T06:01:45.017482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 21
 
14.6%
마 21
 
14.6%
원 17
 
11.8%
손 6
 
4.2%
압 5
 
3.5%
지 5
 
3.5%
시 4
 
2.8%
술 4
 
2.8%
소 4
 
2.8%
약 3
 
2.1%
Other values (41) 54
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141
97.9%
Decimal Number 3
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 21
14.9%
마 21
14.9%
원 17
 
12.1%
손 6
 
4.3%
압 5
 
3.5%
지 5
 
3.5%
시 4
 
2.8%
술 4
 
2.8%
소 4
 
2.8%
약 3
 
2.1%
Other values (38) 51
36.2%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
6 1
33.3%
5 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 141
97.9%
Common 3
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 21
14.9%
마 21
14.9%
원 17
 
12.1%
손 6
 
4.3%
압 5
 
3.5%
지 5
 
3.5%
시 4
 
2.8%
술 4
 
2.8%
소 4
 
2.8%
약 3
 
2.1%
Other values (38) 51
36.2%
Common
ValueCountFrequency (%)
3 1
33.3%
6 1
33.3%
5 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 141
97.9%
ASCII 3
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 21
14.9%
마 21
14.9%
원 17
 
12.1%
손 6
 
4.3%
압 5
 
3.5%
지 5
 
3.5%
시 4
 
2.8%
술 4
 
2.8%
소 4
 
2.8%
약 3
 
2.1%
Other values (38) 51
36.2%
ASCII
ValueCountFrequency (%)
3 1
33.3%
6 1
33.3%
5 1
33.3%

최종수정일자
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2009-05-06 17:36:08
Maximum2024-03-29 09:11:26
2024-04-18T06:01:45.112399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:45.194765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

데이터갱신구분
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
U
11 
I
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 11
50.0%
I 11
50.0%

Length

2024-04-18T06:01:45.281851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:45.354102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 11
50.0%
i 11
50.0%

데이터갱신일자
Date

Distinct12
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 21:01:00
2024-04-18T06:01:45.418920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:45.497595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

업태구분명
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
안마원
18 
안마시술소
4 

Length

Max length5
Median length3
Mean length3.3636364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 18
81.8%
안마시술소 4
 
18.2%

Length

2024-04-18T06:01:45.600725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:45.689093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 18
81.8%
안마시술소 4
 
18.2%

좌표정보(X)
Real number (ℝ)

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187642.88
Minimum186017.91
Maximum188919.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T06:01:45.761568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum186017.91
5-th percentile186133.81
Q1186994.47
median187703.8
Q3188196.26
95-th percentile188894.83
Maximum188919.01
Range2901.1087
Interquartile range (IQR)1201.7854

Descriptive statistics

Standard deviation845.98068
Coefficient of variation (CV)0.0045084615
Kurtosis-0.66511831
Mean187642.88
Median Absolute Deviation (MAD)704.92078
Skewness-0.20465255
Sum4128143.3
Variance715683.32
MonotonicityNot monotonic
2024-04-18T06:01:45.847349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
187703.798483792 2
 
9.1%
187953.650617003 2
 
9.1%
188723.665205598 2
 
9.1%
188903.833845019 1
 
4.5%
188492.612851826 1
 
4.5%
186096.765 1
 
4.5%
187501.829710537 1
 
4.5%
188198.09157556 1
 
4.5%
186017.905175899 1
 
4.5%
186837.668843828 1
 
4.5%
Other values (9) 9
40.9%
ValueCountFrequency (%)
186017.905175899 1
4.5%
186096.765 1
4.5%
186837.668843828 1
4.5%
186895.562184078 1
4.5%
186911.699121807 1
4.5%
186990.07041522 1
4.5%
187007.685 1
4.5%
187138.667234162 1
4.5%
187456.022118034 1
4.5%
187501.829710537 1
4.5%
ValueCountFrequency (%)
188919.01389015 1
4.5%
188903.833845019 1
4.5%
188723.665205598 2
9.1%
188492.612851826 1
4.5%
188198.09157556 1
4.5%
188190.763185816 1
4.5%
187953.650617003 2
9.1%
187822.906666898 1
4.5%
187703.798483792 2
9.1%
187501.829710537 1
4.5%

좌표정보(Y)
Real number (ℝ)

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447101.52
Minimum446135.93
Maximum449626.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T06:01:45.933780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446135.93
5-th percentile446194.28
Q1446632.4
median446777.46
Q3447023.08
95-th percentile449405.32
Maximum449626.38
Range3490.4451
Interquartile range (IQR)390.67881

Descriptive statistics

Standard deviation984.3743
Coefficient of variation (CV)0.0022016796
Kurtosis2.8621667
Mean447101.52
Median Absolute Deviation (MAD)162.59078
Skewness1.990405
Sum9836233.3
Variance968992.75
MonotonicityNot monotonic
2024-04-18T06:01:46.022091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
447098.469487983 2
 
9.1%
446905.045859132 2
 
9.1%
446911.177956532 2
 
9.1%
446768.351143323 1
 
4.5%
449286.462626536 1
 
4.5%
446640.425 1
 
4.5%
446706.89898076 1
 
4.5%
449411.580893629 1
 
4.5%
446733.286497942 1
 
4.5%
446526.106210474 1
 
4.5%
Other values (9) 9
40.9%
ValueCountFrequency (%)
446135.935 1
4.5%
446176.810389121 1
4.5%
446526.106210474 1
4.5%
446582.864576114 1
4.5%
446600.005086593 1
4.5%
446629.723609796 1
4.5%
446640.425 1
4.5%
446706.89898076 1
4.5%
446732.182570285 1
4.5%
446733.286497942 1
4.5%
ValueCountFrequency (%)
449626.380102558 1
4.5%
449411.580893629 1
4.5%
449286.462626536 1
4.5%
447098.469487983 2
9.1%
447060.377699409 1
4.5%
446911.177956532 2
9.1%
446905.045859132 2
9.1%
446786.559111612 1
4.5%
446768.351143323 1
4.5%
446733.286497942 1
4.5%

의료유사업종별명
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
안마원
12 
<NA>
7 
안마시술소
3 

Length

Max length5
Median length3
Mean length3.5909091
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 12
54.5%
<NA> 7
31.8%
안마시술소 3
 
13.6%

Length

2024-04-18T06:01:46.126329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:46.213080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 12
54.5%
na 7
31.8%
안마시술소 3
 
13.6%

종업원수
Categorical

Distinct6
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
11 
2
4 
1
4 
11
 
1
4
 
1

Length

Max length4
Median length3
Mean length2.5454545
Min length1

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row<NA>
2nd row11
3rd row2
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 11
50.0%
2 4
 
18.2%
1 4
 
18.2%
11 1
 
4.5%
4 1
 
4.5%
0 1
 
4.5%

Length

2024-04-18T06:01:46.308063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:46.412598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 11
50.0%
2 4
 
18.2%
1 4
 
18.2%
11 1
 
4.5%
4 1
 
4.5%
0 1
 
4.5%

자격증소유자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
0
 
1

Length

Max length4
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
0 1
 
4.5%

Length

2024-04-18T06:01:46.507053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:46.585206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
0 1
 
4.5%

보조종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
0
 
1

Length

Max length4
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
0 1
 
4.5%

Length

2024-04-18T06:01:46.677932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:46.758025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
0 1
 
4.5%

시설관리자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
0
 
1

Length

Max length4
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
0 1
 
4.5%

Length

2024-04-18T06:01:46.836662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:46.938054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
0 1
 
4.5%

기타종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
0
 
1

Length

Max length4
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
0 1
 
4.5%

Length

2024-04-18T06:01:47.032852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:47.110023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
0 1
 
4.5%

병상수
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)50.0%
Missing8
Missing (%)36.4%
Infinite0
Infinite (%)0.0%
Mean6.0714286
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T06:01:47.173752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q36.75
95-th percentile15
Maximum15
Range14
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation5.0606215
Coefficient of variation (CV)0.83351413
Kurtosis-0.30828578
Mean6.0714286
Median Absolute Deviation (MAD)2
Skewness0.99412585
Sum85
Variance25.60989
MonotonicityNot monotonic
2024-04-18T06:01:47.249318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
6 3
 
13.6%
1 3
 
13.6%
3 3
 
13.6%
15 2
 
9.1%
14 1
 
4.5%
7 1
 
4.5%
4 1
 
4.5%
(Missing) 8
36.4%
ValueCountFrequency (%)
1 3
13.6%
3 3
13.6%
4 1
 
4.5%
6 3
13.6%
7 1
 
4.5%
14 1
 
4.5%
15 2
9.1%
ValueCountFrequency (%)
15 2
9.1%
14 1
 
4.5%
7 1
 
4.5%
6 3
13.6%
4 1
 
4.5%
3 3
13.6%
1 3
13.6%

욕실면적
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
0
3 
48
 
1

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row48
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
0 3
 
13.6%
48 1
 
4.5%

Length

2024-04-18T06:01:47.350052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:47.434572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
0 3
 
13.6%
48 1
 
4.5%

총면적
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)86.7%
Missing7
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean152.032
Minimum22.82
Maximum465.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T06:01:47.506612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.82
5-th percentile30.968
Q169.18
median92.15
Q3143.275
95-th percentile413.188
Maximum465.45
Range442.63
Interquartile range (IQR)74.095

Descriptive statistics

Standard deviation141.75254
Coefficient of variation (CV)0.93238619
Kurtosis0.81748001
Mean152.032
Median Absolute Deviation (MAD)33.42
Skewness1.484687
Sum2280.48
Variance20093.782
MonotonicityNot monotonic
2024-04-18T06:01:47.580245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
390.79 2
 
9.1%
92.15 2
 
9.1%
465.45 1
 
4.5%
112.3 1
 
4.5%
59.48 1
 
4.5%
34.46 1
 
4.5%
160.98 1
 
4.5%
58.0 1
 
4.5%
78.88 1
 
4.5%
22.82 1
 
4.5%
Other values (3) 3
13.6%
(Missing) 7
31.8%
ValueCountFrequency (%)
22.82 1
4.5%
34.46 1
4.5%
58.0 1
4.5%
59.48 1
4.5%
78.88 1
4.5%
82.6 1
4.5%
92.15 2
9.1%
112.3 1
4.5%
114.06 1
4.5%
125.57 1
4.5%
ValueCountFrequency (%)
465.45 1
4.5%
390.79 2
9.1%
160.98 1
4.5%
125.57 1
4.5%
114.06 1
4.5%
112.3 1
4.5%
92.15 2
9.1%
82.6 1
4.5%
78.88 1
4.5%
59.48 1
4.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03140000PHMB4199031400330424000011990-03-24<NA>3폐업3폐업2024-03-24<NA><NA><NA>02-2643-4546<NA><NA>서울특별시 양천구 목동 404번지 114호 1,2,3,4층서울특별시 양천구 신목로 96, 1,2,3,4층 (목동)8007스타안마시술소2024-03-29 09:11:26U2023-12-02 21:01:00.0안마시술소188903.833845446768.351143<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13140000PHMB41998314003304240000119980925<NA>3폐업3폐업20091102<NA><NA><NA>2699-4999<NA>158070서울특별시 양천구 신정동 902번지 18호 (오목로146)<NA><NA>홍안마시술소2009-11-02 14:19:29I2018-08-31 23:59:59.0안마시술소187703.798484447098.469488안마시술소11<NA><NA><NA><NA>1548390.79
23140000PHMB42002314003304240000120021223<NA>3폐업3폐업20090506<NA><NA><NA>2696-8843<NA>158074서울특별시 양천구 신정동 972번지 5호 (신정중앙길13)<NA><NA>으뜸안마시술소2009-05-06 17:36:08I2018-08-31 23:59:59.0안마시술소186911.699122446582.864576안마시술소2<NA><NA><NA><NA>14<NA>465.45
33140000PHMB42007314003304240000120070820<NA>3폐업3폐업20131212<NA><NA><NA>2645-7975<NA>158861서울특별시 양천구 신정1동 1026번지 2호 201호서울특별시 양천구 신월로 340, 2층 201호 (신정동)158861라파안마원2013-12-12 15:21:16I2018-08-31 23:59:59.0안마원187456.022118446600.005087안마원2<NA><NA><NA><NA>6<NA>112.3
43140000PHMB42008314003304240000120080328<NA>1영업/정상13영업중<NA><NA><NA><NA>2655-2200<NA>158811서울특별시 양천구 목3동 609번지 17호 3층서울특별시 양천구 목동중앙북로7길 13, 3층 (목동)7946약손365안마원2022-12-23 10:58:39U2021-11-01 22:05:00.0안마원188190.763186449626.380103<NA><NA><NA><NA><NA><NA><NA><NA><NA>
53140000PHMB42009314003304240000120091103<NA>3폐업3폐업20201021<NA><NA><NA>02-2699-4999<NA>158857서울특별시 양천구 신정4동 902번지 18호 5층서울특별시 양천구 오목로 217, 5층 (신정동)7945홍안마시술소2020-10-21 15:17:40U2020-10-23 02:40:00.0안마시술소187703.798484447098.469488안마시술소4<NA><NA><NA><NA>15<NA>390.79
63140000PHMB42011314003304240000120111010<NA>1영업/정상13영업중<NA><NA><NA><NA>2608-9032<NA>158859서울특별시 양천구 신정4동 970번지 13호 1층서울특별시 양천구 오목로24길 17-1 (신정동)8026정주안마원2022-12-14 14:53:34U2021-11-01 23:07:00.0안마원186895.562184446732.18257<NA><NA><NA><NA><NA><NA><NA><NA><NA>
73140000PHMB42011314003304240000220111215<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2668-6556<NA>158860서울특별시 양천구 신정4동 992번지 1호 3층서울특별시 양천구 오목로 232, 3층 (신정동)8022정통안마원2022-12-14 14:51:32U2021-11-01 23:07:00.0안마원187822.906667447060.377699<NA><NA><NA><NA><NA><NA><NA><NA><NA>
83140000PHMB42012314003304240000120120312<NA>1영업/정상13영업중<NA><NA><NA><NA>2695-6666<NA>158860서울특별시 양천구 신정4동 976번지 6호서울특별시 양천구 신월로 309-1 (신정동)8027새아침안마원2015-06-22 10:40:25I2018-08-31 23:59:59.0안마원187138.667234446629.72361안마원1<NA><NA><NA><NA>6<NA>59.48
93140000PHMB42014314003304240000120140311<NA>1영업/정상13영업중<NA><NA><NA><NA>2647-7975<NA>158712서울특별시 양천구 신정동 1182번지 11호 5층 507호서울특별시 양천구 중앙로 237, 5층 507호 (신정동)8073라파안마원2014-03-12 09:53:37I2018-08-31 23:59:59.0안마원186990.070415446176.810389안마원1<NA><NA><NA><NA>1<NA>34.46
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
123140000PHMB42016314003304240000120160113<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2696-8280<NA><NA>서울특별시 양천구 신정동 1190번지 16호 2층서울특별시 양천구 중앙로45길 8-30 (신정동, 2층)8058양천안마지압원2016-01-13 10:34:43I2018-08-31 23:59:59.0안마원186837.668844446526.10621안마원<NA><NA><NA><NA><NA>3<NA>78.88
133140000PHMB42016314003304240000220160128<NA>3폐업3폐업20221226<NA><NA><NA>2690-3707<NA><NA>서울특별시 양천구 신월동 444번지 22호 지층서울특별시 양천구 월정로 33 (신월동, 지층)7930건강안마원2022-12-29 12:12:24U2021-11-01 21:01:00.0안마원186017.905176446733.286498<NA><NA><NA><NA><NA><NA><NA><NA><NA>
143140000PHMB42016314003304240000320161213<NA>3폐업3폐업20180711<NA><NA><NA>02-2644-8789<NA><NA>서울특별시 양천구 목동 405번지 216호 3층서울특별시 양천구 오목로54길 2, 3층 (목동)8005맑은손지압안마센터2018-08-02 13:30:37I2018-08-31 23:59:59.0안마원188723.665206446911.177957안마원1<NA><NA><NA><NA>3<NA>92.15
153140000PHMB42017314003304240000120170113<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 956번지 목동롯데캐슬위너상가동 지하114호서울특별시 양천구 목동중앙북로 38, 지하114호 (목동, 목동롯데캐슬위너상가동)7949담손정통지압안마원2017-01-13 14:22:55I2018-08-31 23:59:59.0안마원188198.091576449411.580894안마원<NA><NA><NA><NA><NA>1<NA>22.82
163140000PHMB42017314003304240000220170427<NA>3폐업3폐업20190401<NA><NA><NA>02-2601-7737<NA><NA>서울특별시 양천구 신정동 995번지 6호 정동프라자 402호서울특별시 양천구 목동로 177, 402호 (신정동, 정동프라자)8022바른체형안마원2019-04-01 13:52:05U2019-04-03 02:40:00.0안마원187953.650617446905.045859안마원<NA><NA><NA><NA><NA>6<NA>114.06
173140000PHMB42017314003304240000320170803<NA>3폐업3폐업20190311<NA><NA><NA>02-2699-1217<NA><NA>서울특별시 양천구 신정동 980번지 11호 2층서울특별시 양천구 은행정로 31, 2층 (신정동)8027약손힐링원2019-03-11 12:58:07U2019-03-13 02:40:00.0안마원187501.829711446706.898981안마원<NA><NA><NA><NA><NA>4<NA>125.57
183140000PHMB42018314003304240000120180803<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 405번지 216호서울특별시 양천구 오목로54길 2, 3층 (목동)8005목동건강안마원2018-08-17 18:45:36I2018-08-31 23:59:59.0안마원188723.665206446911.177957안마원0<NA><NA><NA><NA>1092.15
193140000PHMB42019314003304240000120190207<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6339-8275<NA><NA>서울특별시 양천구 신월동 513번지 2호서울특별시 양천구 월정로 22, 지층 (신월동)8028예손지압안마원2019-02-07 13:33:34I2019-02-09 02:21:15.0안마원186096.765446640.425안마원2<NA><NA><NA><NA><NA>082.6
203140000PHMB4201931400330424000022019-04-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2694-1114<NA><NA>서울특별시 양천구 신정동 995번지 6호 정동프라자서울특별시 양천구 목동로 177, 정동프라자 4층 (신정동)8022서울보건안마원2023-11-29 18:14:29U2022-11-02 00:01:00.0안마원187953.650617446905.045859<NA><NA><NA><NA><NA><NA><NA><NA><NA>
213140000PHMB4202331400330424000012023-04-07<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2651-9468<NA><NA>서울특별시 양천구 목동 505-2 1층서울특별시 양천구 목동중앙북로12길 24, 1층 (목동)7948바로고침안마원2023-04-25 15:23:05U2022-12-03 22:08:00.0안마원188492.612852449286.462627<NA><NA><NA><NA><NA><NA><NA><NA><NA>