Overview

Dataset statistics

Number of variables47
Number of observations725
Missing cells7593
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory286.9 KiB
Average record size in memory405.2 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric9
Boolean2

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),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-17947/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.1%)Imbalance
위생업태명 is highly imbalanced (74.4%)Imbalance
사용끝지하층 is highly imbalanced (56.7%)Imbalance
건물소유구분명 is highly imbalanced (62.3%)Imbalance
여성종사자수 is highly imbalanced (78.5%)Imbalance
남성종사자수 is highly imbalanced (78.9%)Imbalance
인허가취소일자 has 725 (100.0%) missing valuesMissing
폐업일자 has 107 (14.8%) missing valuesMissing
휴업시작일자 has 725 (100.0%) missing valuesMissing
휴업종료일자 has 725 (100.0%) missing valuesMissing
재개업일자 has 725 (100.0%) missing valuesMissing
전화번호 has 129 (17.8%) missing valuesMissing
도로명주소 has 497 (68.6%) missing valuesMissing
도로명우편번호 has 498 (68.7%) missing valuesMissing
좌표정보(X) has 55 (7.6%) missing valuesMissing
좌표정보(Y) has 55 (7.6%) missing valuesMissing
건물지상층수 has 125 (17.2%) missing valuesMissing
건물지하층수 has 166 (22.9%) missing valuesMissing
사용시작지상층 has 249 (34.3%) missing valuesMissing
사용끝지상층 has 474 (65.4%) missing valuesMissing
발한실여부 has 61 (8.4%) missing valuesMissing
좌석수 has 55 (7.6%) missing valuesMissing
조건부허가신고사유 has 725 (100.0%) missing valuesMissing
조건부허가시작일자 has 725 (100.0%) missing valuesMissing
조건부허가종료일자 has 725 (100.0%) missing valuesMissing
다중이용업소여부 has 47 (6.5%) missing valuesMissing
관리번호 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
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 24 (3.3%) zerosZeros
건물지상층수 has 265 (36.6%) zerosZeros
건물지하층수 has 287 (39.6%) zerosZeros
사용시작지상층 has 238 (32.8%) zerosZeros
사용끝지상층 has 11 (1.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:42:25.899739
Analysis finished2024-05-11 06:42:27.182479
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
3200000
725 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3200000 725
100.0%

Length

2024-05-11T15:42:27.365745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:27.541252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 725
100.0%

관리번호
Text

UNIQUE 

Distinct725
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2024-05-11T15:42:27.851251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters15950
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

Unique725 ?
Unique (%)100.0%

Sample

1st row3200000-203-1968-01986
2nd row3200000-203-1968-01989
3rd row3200000-203-1968-01996
4th row3200000-203-1968-01997
5th row3200000-203-1969-00546
ValueCountFrequency (%)
3200000-203-1968-01986 1
 
0.1%
3200000-203-2000-02346 1
 
0.1%
3200000-203-2001-02142 1
 
0.1%
3200000-203-2001-02145 1
 
0.1%
3200000-203-2001-02177 1
 
0.1%
3200000-203-2001-02179 1
 
0.1%
3200000-203-2001-02234 1
 
0.1%
3200000-203-2001-02257 1
 
0.1%
3200000-203-2001-02380 1
 
0.1%
3200000-203-2001-02420 1
 
0.1%
Other values (715) 715
98.6%
2024-05-11T15:42:28.406992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6520
40.9%
2 2296
 
14.4%
- 2175
 
13.6%
3 1678
 
10.5%
1 1066
 
6.7%
9 865
 
5.4%
8 443
 
2.8%
7 317
 
2.0%
4 205
 
1.3%
5 195
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13775
86.4%
Dash Punctuation 2175
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6520
47.3%
2 2296
 
16.7%
3 1678
 
12.2%
1 1066
 
7.7%
9 865
 
6.3%
8 443
 
3.2%
7 317
 
2.3%
4 205
 
1.5%
5 195
 
1.4%
6 190
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15950
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6520
40.9%
2 2296
 
14.4%
- 2175
 
13.6%
3 1678
 
10.5%
1 1066
 
6.7%
9 865
 
5.4%
8 443
 
2.8%
7 317
 
2.0%
4 205
 
1.3%
5 195
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15950
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6520
40.9%
2 2296
 
14.4%
- 2175
 
13.6%
3 1678
 
10.5%
1 1066
 
6.7%
9 865
 
5.4%
8 443
 
2.8%
7 317
 
2.0%
4 205
 
1.3%
5 195
 
1.2%

인허가일자
Date

Distinct670
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum1968-07-01 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T15:42:28.636660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:28.912807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
3
618 
1
107 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 618
85.2%
1 107
 
14.8%

Length

2024-05-11T15:42:29.228555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:29.446297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 618
85.2%
1 107
 
14.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
폐업
618 
영업/정상
107 

Length

Max length5
Median length2
Mean length2.4427586
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 618
85.2%
영업/정상 107
 
14.8%

Length

2024-05-11T15:42:29.687444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:29.884610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 618
85.2%
영업/정상 107
 
14.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2
618 
1
107 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 618
85.2%
1 107
 
14.8%

Length

2024-05-11T15:42:30.079987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:30.255609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 618
85.2%
1 107
 
14.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
폐업
618 
영업
107 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 618
85.2%
영업 107
 
14.8%

Length

2024-05-11T15:42:30.437367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:30.640559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 618
85.2%
영업 107
 
14.8%

폐업일자
Date

MISSING 

Distinct525
Distinct (%)85.0%
Missing107
Missing (%)14.8%
Memory size5.8 KiB
Minimum1992-01-17 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:42:31.176274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:31.426438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

전화번호
Text

MISSING 

Distinct444
Distinct (%)74.5%
Missing129
Missing (%)17.8%
Memory size5.8 KiB
2024-05-11T15:42:31.904894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.7936242
Min length2

Characters and Unicode

Total characters5837
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

Unique407 ?
Unique (%)68.3%

Sample

1st row02 8570617
2nd row0208850743
3rd row02 00000
4th row02 00000
5th row02 8897576
ValueCountFrequency (%)
02 497
45.3%
00000 58
 
5.3%
0200000000 36
 
3.3%
0 18
 
1.6%
8574963 3
 
0.3%
8845362 3
 
0.3%
8857080 3
 
0.3%
5863927 2
 
0.2%
8792123 2
 
0.2%
8305365 2
 
0.2%
Other values (442) 474
43.2%
2024-05-11T15:42:32.447925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1436
24.6%
8 892
15.3%
2 854
14.6%
666
11.4%
7 375
 
6.4%
5 332
 
5.7%
3 303
 
5.2%
6 279
 
4.8%
1 234
 
4.0%
4 233
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5171
88.6%
Space Separator 666
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1436
27.8%
8 892
17.3%
2 854
16.5%
7 375
 
7.3%
5 332
 
6.4%
3 303
 
5.9%
6 279
 
5.4%
1 234
 
4.5%
4 233
 
4.5%
9 233
 
4.5%
Space Separator
ValueCountFrequency (%)
666
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1436
24.6%
8 892
15.3%
2 854
14.6%
666
11.4%
7 375
 
6.4%
5 332
 
5.7%
3 303
 
5.2%
6 279
 
4.8%
1 234
 
4.0%
4 233
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1436
24.6%
8 892
15.3%
2 854
14.6%
666
11.4%
7 375
 
6.4%
5 332
 
5.7%
3 303
 
5.2%
6 279
 
4.8%
1 234
 
4.0%
4 233
 
4.0%

소재지면적
Real number (ℝ)

ZEROS 

Distinct489
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.561007
Minimum0
Maximum396
Zeros24
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:32.664768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.6
Q112.42
median19.04
Q330.78
95-th percentile94.754
Maximum396
Range396
Interquartile range (IQR)18.36

Descriptive statistics

Standard deviation33.021819
Coefficient of variation (CV)1.1170736
Kurtosis30.115482
Mean29.561007
Median Absolute Deviation (MAD)8.14
Skewness4.1983825
Sum21431.73
Variance1090.4405
MonotonicityNot monotonic
2024-05-11T15:42:32.881663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
 
3.3%
9.9 16
 
2.2%
6.6 12
 
1.7%
20.0 11
 
1.5%
23.1 10
 
1.4%
16.5 9
 
1.2%
26.4 8
 
1.1%
19.8 7
 
1.0%
13.2 7
 
1.0%
33.0 7
 
1.0%
Other values (479) 614
84.7%
ValueCountFrequency (%)
0.0 24
3.3%
3.3 1
 
0.1%
3.5 1
 
0.1%
3.9 1
 
0.1%
4.2 1
 
0.1%
4.31 1
 
0.1%
4.5 1
 
0.1%
4.95 1
 
0.1%
5.0 3
 
0.4%
5.5 1
 
0.1%
ValueCountFrequency (%)
396.0 1
0.1%
280.0 1
0.1%
264.0 1
0.1%
175.2 1
0.1%
165.0 1
0.1%
155.0 1
0.1%
147.6 1
0.1%
143.21 1
0.1%
142.03 1
0.1%
138.38 1
0.1%

소재지우편번호
Text

Distinct123
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2024-05-11T15:42:33.313267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0372414
Min length6

Characters and Unicode

Total characters4377
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

Unique26 ?
Unique (%)3.6%

Sample

1st row151869
2nd row151862
3rd row151050
4th row151050
5th row151830
ValueCountFrequency (%)
151892 26
 
3.6%
151836 25
 
3.4%
151903 22
 
3.0%
151891 20
 
2.8%
151015 20
 
2.8%
151800 20
 
2.8%
151050 18
 
2.5%
151849 18
 
2.5%
151876 17
 
2.3%
151890 16
 
2.2%
Other values (113) 523
72.1%
2024-05-11T15:42:33.914003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1588
36.3%
5 864
19.7%
8 707
16.2%
0 283
 
6.5%
9 236
 
5.4%
3 175
 
4.0%
4 162
 
3.7%
2 126
 
2.9%
6 105
 
2.4%
7 104
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4350
99.4%
Dash Punctuation 27
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1588
36.5%
5 864
19.9%
8 707
16.3%
0 283
 
6.5%
9 236
 
5.4%
3 175
 
4.0%
4 162
 
3.7%
2 126
 
2.9%
6 105
 
2.4%
7 104
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1588
36.3%
5 864
19.7%
8 707
16.2%
0 283
 
6.5%
9 236
 
5.4%
3 175
 
4.0%
4 162
 
3.7%
2 126
 
2.9%
6 105
 
2.4%
7 104
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1588
36.3%
5 864
19.7%
8 707
16.2%
0 283
 
6.5%
9 236
 
5.4%
3 175
 
4.0%
4 162
 
3.7%
2 126
 
2.9%
6 105
 
2.4%
7 104
 
2.4%

지번주소
Text

Distinct640
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2024-05-11T15:42:34.292440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length23.474483
Min length19

Characters and Unicode

Total characters17019
Distinct characters132
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

Unique571 ?
Unique (%)78.8%

Sample

1st row서울특별시 관악구 신림동 1594-1
2nd row서울특별시 관악구 신림동 354-0번지
3rd row서울특별시 관악구 봉천동 94-1번지
4th row서울특별시 관악구 봉천동 81-0번지
5th row서울특별시 관악구 봉천동 706-4번지
ValueCountFrequency (%)
서울특별시 725
23.8%
관악구 725
23.8%
신림동 382
12.6%
봉천동 317
 
10.4%
남현동 26
 
0.9%
1층 18
 
0.6%
산 12
 
0.4%
지하1층 10
 
0.3%
1679-7번지 7
 
0.2%
2층 5
 
0.2%
Other values (688) 815
26.8%
2024-05-11T15:42:34.866800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2987
17.6%
1 856
 
5.0%
동 739
 
4.3%
서 729
 
4.3%
시 728
 
4.3%
관 728
 
4.3%
악 727
 
4.3%
울 727
 
4.3%
별 726
 
4.3%
특 726
 
4.3%
Other values (122) 7346
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9614
56.5%
Decimal Number 3681
 
21.6%
Space Separator 2987
 
17.6%
Dash Punctuation 706
 
4.1%
Uppercase Letter 16
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 739
 
7.7%
서 729
 
7.6%
시 728
 
7.6%
관 728
 
7.6%
악 727
 
7.6%
울 727
 
7.6%
별 726
 
7.6%
특 726
 
7.6%
구 725
 
7.5%
지 639
 
6.6%
Other values (97) 2420
25.2%
Decimal Number
ValueCountFrequency (%)
1 856
23.3%
6 424
11.5%
2 378
10.3%
4 361
9.8%
3 344
9.3%
5 330
 
9.0%
0 280
 
7.6%
9 249
 
6.8%
8 240
 
6.5%
7 219
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 5
31.2%
A 4
25.0%
E 1
 
6.2%
S 1
 
6.2%
U 1
 
6.2%
O 1
 
6.2%
H 1
 
6.2%
J 1
 
6.2%
K 1
 
6.2%
Space Separator
ValueCountFrequency (%)
2987
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 706
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9614
56.5%
Common 7389
43.4%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 739
 
7.7%
서 729
 
7.6%
시 728
 
7.6%
관 728
 
7.6%
악 727
 
7.6%
울 727
 
7.6%
별 726
 
7.6%
특 726
 
7.6%
구 725
 
7.5%
지 639
 
6.6%
Other values (97) 2420
25.2%
Common
ValueCountFrequency (%)
2987
40.4%
1 856
 
11.6%
- 706
 
9.6%
6 424
 
5.7%
2 378
 
5.1%
4 361
 
4.9%
3 344
 
4.7%
5 330
 
4.5%
0 280
 
3.8%
9 249
 
3.4%
Other values (6) 474
 
6.4%
Latin
ValueCountFrequency (%)
B 5
31.2%
A 4
25.0%
E 1
 
6.2%
S 1
 
6.2%
U 1
 
6.2%
O 1
 
6.2%
H 1
 
6.2%
J 1
 
6.2%
K 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9614
56.5%
ASCII 7405
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2987
40.3%
1 856
 
11.6%
- 706
 
9.5%
6 424
 
5.7%
2 378
 
5.1%
4 361
 
4.9%
3 344
 
4.6%
5 330
 
4.5%
0 280
 
3.8%
9 249
 
3.4%
Other values (15) 490
 
6.6%
Hangul
ValueCountFrequency (%)
동 739
 
7.7%
서 729
 
7.6%
시 728
 
7.6%
관 728
 
7.6%
악 727
 
7.6%
울 727
 
7.6%
별 726
 
7.6%
특 726
 
7.6%
구 725
 
7.5%
지 639
 
6.6%
Other values (97) 2420
25.2%

도로명주소
Text

MISSING 

Distinct219
Distinct (%)96.1%
Missing497
Missing (%)68.6%
Memory size5.8 KiB
2024-05-11T15:42:35.268611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length27.855263
Min length21

Characters and Unicode

Total characters6351
Distinct characters146
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

Unique212 ?
Unique (%)93.0%

Sample

1st row서울특별시 관악구 신원로3다길 1, 1층 (신림동)
2nd row서울특별시 관악구 당곡길 49 (봉천동)
3rd row서울특별시 관악구 원신길 156 (신림동)
4th row서울특별시 관악구 난우길 32 (신림동)
5th row서울특별시 관악구 중앙1가길 10 (봉천동)
ValueCountFrequency (%)
서울특별시 228
17.8%
관악구 228
17.8%
신림동 103
 
8.0%
봉천동 101
 
7.9%
1층 60
 
4.7%
남부순환로 11
 
0.9%
남현동 9
 
0.7%
난곡로 8
 
0.6%
쑥고개로 8
 
0.6%
101호 8
 
0.6%
Other values (322) 520
40.5%
2024-05-11T15:42:36.008003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1056
 
16.6%
1 287
 
4.5%
관 248
 
3.9%
악 245
 
3.9%
동 242
 
3.8%
서 232
 
3.7%
) 232
 
3.7%
시 232
 
3.7%
( 232
 
3.7%
울 230
 
3.6%
Other values (136) 3115
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3735
58.8%
Space Separator 1056
 
16.6%
Decimal Number 926
 
14.6%
Close Punctuation 232
 
3.7%
Open Punctuation 232
 
3.7%
Other Punctuation 120
 
1.9%
Dash Punctuation 33
 
0.5%
Uppercase Letter 16
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 248
 
6.6%
악 245
 
6.6%
동 242
 
6.5%
서 232
 
6.2%
시 232
 
6.2%
울 230
 
6.2%
구 230
 
6.2%
특 229
 
6.1%
별 229
 
6.1%
길 162
 
4.3%
Other values (110) 1456
39.0%
Decimal Number
ValueCountFrequency (%)
1 287
31.0%
2 142
15.3%
3 93
 
10.0%
4 80
 
8.6%
5 72
 
7.8%
0 61
 
6.6%
6 56
 
6.0%
7 54
 
5.8%
9 43
 
4.6%
8 38
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 5
31.2%
O 2
 
12.5%
A 2
 
12.5%
E 1
 
6.2%
S 1
 
6.2%
U 1
 
6.2%
H 1
 
6.2%
J 1
 
6.2%
K 1
 
6.2%
R 1
 
6.2%
Space Separator
ValueCountFrequency (%)
1056
100.0%
Close Punctuation
ValueCountFrequency (%)
) 232
100.0%
Open Punctuation
ValueCountFrequency (%)
( 232
100.0%
Other Punctuation
ValueCountFrequency (%)
, 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3735
58.8%
Common 2600
40.9%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 248
 
6.6%
악 245
 
6.6%
동 242
 
6.5%
서 232
 
6.2%
시 232
 
6.2%
울 230
 
6.2%
구 230
 
6.2%
특 229
 
6.1%
별 229
 
6.1%
길 162
 
4.3%
Other values (110) 1456
39.0%
Common
ValueCountFrequency (%)
1056
40.6%
1 287
 
11.0%
) 232
 
8.9%
( 232
 
8.9%
2 142
 
5.5%
, 120
 
4.6%
3 93
 
3.6%
4 80
 
3.1%
5 72
 
2.8%
0 61
 
2.3%
Other values (6) 225
 
8.7%
Latin
ValueCountFrequency (%)
B 5
31.2%
O 2
 
12.5%
A 2
 
12.5%
E 1
 
6.2%
S 1
 
6.2%
U 1
 
6.2%
H 1
 
6.2%
J 1
 
6.2%
K 1
 
6.2%
R 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3735
58.8%
ASCII 2616
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1056
40.4%
1 287
 
11.0%
) 232
 
8.9%
( 232
 
8.9%
2 142
 
5.4%
, 120
 
4.6%
3 93
 
3.6%
4 80
 
3.1%
5 72
 
2.8%
0 61
 
2.3%
Other values (16) 241
 
9.2%
Hangul
ValueCountFrequency (%)
관 248
 
6.6%
악 245
 
6.6%
동 242
 
6.5%
서 232
 
6.2%
시 232
 
6.2%
울 230
 
6.2%
구 230
 
6.2%
특 229
 
6.1%
별 229
 
6.1%
길 162
 
4.3%
Other values (110) 1456
39.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct103
Distinct (%)45.4%
Missing498
Missing (%)68.7%
Infinite0
Infinite (%)0.0%
Mean8778.467
Minimum8700
Maximum8865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:36.269444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8700
5-th percentile8707
Q18744
median8774
Q38806
95-th percentile8856.7
Maximum8865
Range165
Interquartile range (IQR)62

Descriptive statistics

Standard deviation45.156488
Coefficient of variation (CV)0.0051440062
Kurtosis-0.84193318
Mean8778.467
Median Absolute Deviation (MAD)32
Skewness0.30424728
Sum1992712
Variance2039.1084
MonotonicityNot monotonic
2024-05-11T15:42:36.536690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8846 9
 
1.2%
8784 7
 
1.0%
8729 6
 
0.8%
8742 5
 
0.7%
8707 5
 
0.7%
8806 5
 
0.7%
8787 5
 
0.7%
8705 5
 
0.7%
8786 5
 
0.7%
8774 5
 
0.7%
Other values (93) 170
 
23.4%
(Missing) 498
68.7%
ValueCountFrequency (%)
8700 1
 
0.1%
8702 2
 
0.3%
8704 1
 
0.1%
8705 5
0.7%
8707 5
0.7%
8708 1
 
0.1%
8711 1
 
0.1%
8713 1
 
0.1%
8716 2
 
0.3%
8719 1
 
0.1%
ValueCountFrequency (%)
8865 1
 
0.1%
8864 2
0.3%
8863 1
 
0.1%
8862 1
 
0.1%
8859 2
0.3%
8858 3
0.4%
8857 2
0.3%
8856 2
0.3%
8854 3
0.4%
8853 3
0.4%

사업장명
Text

Distinct548
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2024-05-11T15:42:37.113238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length2
Mean length3.6303448
Min length1

Characters and Unicode

Total characters2632
Distinct characters350
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

Unique450 ?
Unique (%)62.1%

Sample

1st row대광
2nd row청용
3rd row강남
4th row봉천
5th row협동
ValueCountFrequency (%)
현대 12
 
1.5%
이용원 8
 
1.0%
태양 8
 
1.0%
우성 7
 
0.9%
우정 7
 
0.9%
바버샵 7
 
0.9%
대성 6
 
0.8%
대중 5
 
0.6%
평화 5
 
0.6%
삼성 5
 
0.6%
Other values (570) 716
91.1%
2024-05-11T15:42:37.878027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 125
 
4.7%
원 100
 
3.8%
용 82
 
3.1%
성 81
 
3.1%
대 72
 
2.7%
탕 66
 
2.5%
) 63
 
2.4%
( 63
 
2.4%
61
 
2.3%
우 59
 
2.2%
Other values (340) 1860
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2267
86.1%
Lowercase Letter 81
 
3.1%
Uppercase Letter 69
 
2.6%
Close Punctuation 63
 
2.4%
Open Punctuation 63
 
2.4%
Space Separator 61
 
2.3%
Decimal Number 21
 
0.8%
Other Punctuation 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 125
 
5.5%
원 100
 
4.4%
용 82
 
3.6%
성 81
 
3.6%
대 72
 
3.2%
탕 66
 
2.9%
우 59
 
2.6%
신 42
 
1.9%
화 41
 
1.8%
일 37
 
1.6%
Other values (291) 1562
68.9%
Lowercase Letter
ValueCountFrequency (%)
r 13
16.0%
e 10
12.3%
h 8
9.9%
o 7
8.6%
a 6
 
7.4%
s 6
 
7.4%
t 4
 
4.9%
i 4
 
4.9%
p 3
 
3.7%
l 3
 
3.7%
Other values (11) 17
21.0%
Uppercase Letter
ValueCountFrequency (%)
B 11
15.9%
O 10
14.5%
R 8
11.6%
S 7
10.1%
E 4
 
5.8%
N 4
 
5.8%
A 4
 
5.8%
T 3
 
4.3%
H 3
 
4.3%
P 3
 
4.3%
Other values (6) 12
17.4%
Decimal Number
ValueCountFrequency (%)
4 7
33.3%
2 6
28.6%
8 3
14.3%
5 2
 
9.5%
0 2
 
9.5%
1 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
' 2
28.6%
? 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Space Separator
ValueCountFrequency (%)
61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2267
86.1%
Common 215
 
8.2%
Latin 150
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 125
 
5.5%
원 100
 
4.4%
용 82
 
3.6%
성 81
 
3.6%
대 72
 
3.2%
탕 66
 
2.9%
우 59
 
2.6%
신 42
 
1.9%
화 41
 
1.8%
일 37
 
1.6%
Other values (291) 1562
68.9%
Latin
ValueCountFrequency (%)
r 13
 
8.7%
B 11
 
7.3%
e 10
 
6.7%
O 10
 
6.7%
R 8
 
5.3%
h 8
 
5.3%
S 7
 
4.7%
o 7
 
4.7%
a 6
 
4.0%
s 6
 
4.0%
Other values (27) 64
42.7%
Common
ValueCountFrequency (%)
) 63
29.3%
( 63
29.3%
61
28.4%
4 7
 
3.3%
2 6
 
2.8%
. 4
 
1.9%
8 3
 
1.4%
' 2
 
0.9%
5 2
 
0.9%
0 2
 
0.9%
Other values (2) 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2267
86.1%
ASCII 365
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 125
 
5.5%
원 100
 
4.4%
용 82
 
3.6%
성 81
 
3.6%
대 72
 
3.2%
탕 66
 
2.9%
우 59
 
2.6%
신 42
 
1.9%
화 41
 
1.8%
일 37
 
1.6%
Other values (291) 1562
68.9%
ASCII
ValueCountFrequency (%)
) 63
17.3%
( 63
17.3%
61
16.7%
r 13
 
3.6%
B 11
 
3.0%
e 10
 
2.7%
O 10
 
2.7%
R 8
 
2.2%
h 8
 
2.2%
S 7
 
1.9%
Other values (39) 111
30.4%

최종수정일자
Date

Distinct428
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum1999-01-12 00:00:00
Maximum2024-05-02 09:09:59
2024-05-11T15:42:38.089759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:38.323539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
I
591 
U
134 

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 591
81.5%
U 134
 
18.5%

Length

2024-05-11T15:42:38.587925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:38.771147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 591
81.5%
u 134
 
18.5%

데이터갱신일자
Date

Distinct102
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T15:42:38.948363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:39.150176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
일반이용업
720 
이용업 기타
 
5

Length

Max length6
Median length5
Mean length5.0068966
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 720
99.3%
이용업 기타 5
 
0.7%

Length

2024-05-11T15:42:39.339969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:39.477137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 720
98.6%
이용업 5
 
0.7%
기타 5
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct550
Distinct (%)82.1%
Missing55
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean194370.19
Minimum191106.44
Maximum198297.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:39.631642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191106.44
5-th percentile191797.89
Q1193247.43
median194240.68
Q3195628.86
95-th percentile196996.12
Maximum198297.24
Range7190.8011
Interquartile range (IQR)2381.433

Descriptive statistics

Standard deviation1617.0733
Coefficient of variation (CV)0.0083195543
Kurtosis-0.49967122
Mean194370.19
Median Absolute Deviation (MAD)1275.6504
Skewness0.19769532
Sum1.3022803 × 108
Variance2614926.1
MonotonicityNot monotonic
2024-05-11T15:42:39.861144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198097.13526738 7
 
1.0%
196387.83963757 7
 
1.0%
195572.774825165 5
 
0.7%
195444.735051198 5
 
0.7%
193555.127667196 4
 
0.6%
193721.863991816 4
 
0.6%
191326.542622821 4
 
0.6%
193596.72315537 3
 
0.4%
194996.559172999 3
 
0.4%
191182.000480527 3
 
0.4%
Other values (540) 625
86.2%
(Missing) 55
 
7.6%
ValueCountFrequency (%)
191106.438915286 1
 
0.1%
191182.000480527 3
0.4%
191185.163772161 2
0.3%
191191.448323925 1
 
0.1%
191206.518253355 1
 
0.1%
191215.879312952 1
 
0.1%
191244.186952943 1
 
0.1%
191259.918585504 1
 
0.1%
191278.82541331 1
 
0.1%
191326.542622821 4
0.6%
ValueCountFrequency (%)
198297.240031378 1
 
0.1%
198284.078546351 1
 
0.1%
198278.438025281 1
 
0.1%
198266.765199796 2
 
0.3%
198264.099355157 2
 
0.3%
198258.813290653 1
 
0.1%
198219.957648914 1
 
0.1%
198097.13526738 7
1.0%
198006.674977451 1
 
0.1%
197974.59786506 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct550
Distinct (%)82.1%
Missing55
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean442020.98
Minimum439023.17
Maximum443647.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:40.066196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440574.13
Q1441567.25
median442171.5
Q3442551.59
95-th percentile442917.5
Maximum443647.02
Range4623.8557
Interquartile range (IQR)984.34212

Descriptive statistics

Standard deviation721.73597
Coefficient of variation (CV)0.0016328093
Kurtosis0.75480552
Mean442020.98
Median Absolute Deviation (MAD)431.16704
Skewness-0.89517492
Sum2.9615405 × 108
Variance520902.81
MonotonicityNot monotonic
2024-05-11T15:42:40.256769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441468.017877057 7
 
1.0%
441884.686807457 7
 
1.0%
441942.462369482 5
 
0.7%
442859.116608526 5
 
0.7%
442912.064489952 4
 
0.6%
440545.946420334 4
 
0.6%
442358.444307642 4
 
0.6%
442551.937602292 3
 
0.4%
442398.514693671 3
 
0.4%
442181.791890078 3
 
0.4%
Other values (540) 625
86.2%
(Missing) 55
 
7.6%
ValueCountFrequency (%)
439023.167125842 2
0.3%
439771.908015585 2
0.3%
439787.715563055 1
0.1%
440005.119086228 1
0.1%
440040.309820942 2
0.3%
440048.493191723 1
0.1%
440049.785934878 1
0.1%
440088.672588608 1
0.1%
440135.811928744 1
0.1%
440268.066602308 1
0.1%
ValueCountFrequency (%)
443647.022828539 1
0.1%
443341.379446435 1
0.1%
443284.530613553 1
0.1%
443231.666283907 2
0.3%
443222.125800199 1
0.1%
443199.528183519 1
0.1%
443183.34691341 1
0.1%
443179.96522589 2
0.3%
443176.735306808 1
0.1%
443171.872144536 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
일반이용업
673 
<NA>
 
47
이용업 기타
 
5

Length

Max length6
Median length5
Mean length4.942069
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 673
92.8%
<NA> 47
 
6.5%
이용업 기타 5
 
0.7%

Length

2024-05-11T15:42:40.485564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:40.640847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 673
92.2%
na 47
 
6.4%
이용업 5
 
0.7%
기타 5
 
0.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)2.8%
Missing125
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean2.0666667
Minimum0
Maximum20
Zeros265
Zeros (%)36.6%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:40.819347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile6
Maximum20
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5897362
Coefficient of variation (CV)1.2530981
Kurtosis8.5750557
Mean2.0666667
Median Absolute Deviation (MAD)2
Skewness2.1980921
Sum1240
Variance6.7067334
MonotonicityNot monotonic
2024-05-11T15:42:41.032366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 265
36.6%
2 93
 
12.8%
3 84
 
11.6%
4 63
 
8.7%
5 32
 
4.4%
1 19
 
2.6%
6 17
 
2.3%
7 8
 
1.1%
8 6
 
0.8%
10 4
 
0.6%
Other values (7) 9
 
1.2%
(Missing) 125
17.2%
ValueCountFrequency (%)
0 265
36.6%
1 19
 
2.6%
2 93
 
12.8%
3 84
 
11.6%
4 63
 
8.7%
5 32
 
4.4%
6 17
 
2.3%
7 8
 
1.1%
8 6
 
0.8%
9 1
 
0.1%
ValueCountFrequency (%)
20 1
 
0.1%
18 1
 
0.1%
15 2
 
0.3%
14 1
 
0.1%
12 1
 
0.1%
11 2
 
0.3%
10 4
0.6%
9 1
 
0.1%
8 6
0.8%
7 8
1.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.3%
Missing166
Missing (%)22.9%
Infinite0
Infinite (%)0.0%
Mean0.56887299
Minimum0
Maximum6
Zeros287
Zeros (%)39.6%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:41.217684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.73701227
Coefficient of variation (CV)1.2955656
Kurtosis11.445407
Mean0.56887299
Median Absolute Deviation (MAD)0
Skewness2.4431529
Sum318
Variance0.54318708
MonotonicityNot monotonic
2024-05-11T15:42:41.358687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 287
39.6%
1 248
34.2%
2 12
 
1.7%
3 6
 
0.8%
4 3
 
0.4%
5 2
 
0.3%
6 1
 
0.1%
(Missing) 166
22.9%
ValueCountFrequency (%)
0 287
39.6%
1 248
34.2%
2 12
 
1.7%
3 6
 
0.8%
4 3
 
0.4%
5 2
 
0.3%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
5 2
 
0.3%
4 3
 
0.4%
3 6
 
0.8%
2 12
 
1.7%
1 248
34.2%
0 287
39.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.7%
Missing249
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean0.74159664
Minimum0
Maximum7
Zeros238
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:41.819434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.96159559
Coefficient of variation (CV)1.2966558
Kurtosis6.1213035
Mean0.74159664
Median Absolute Deviation (MAD)0.5
Skewness1.9061997
Sum353
Variance0.92466608
MonotonicityNot monotonic
2024-05-11T15:42:41.960584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 238
32.8%
1 160
22.1%
2 53
 
7.3%
3 19
 
2.6%
4 3
 
0.4%
7 1
 
0.1%
5 1
 
0.1%
6 1
 
0.1%
(Missing) 249
34.3%
ValueCountFrequency (%)
0 238
32.8%
1 160
22.1%
2 53
 
7.3%
3 19
 
2.6%
4 3
 
0.4%
5 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 3
 
0.4%
3 19
 
2.6%
2 53
 
7.3%
1 160
22.1%
0 238
32.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.2%
Missing474
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean1.4223108
Minimum0
Maximum7
Zeros11
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:42.094924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.91046155
Coefficient of variation (CV)0.64012843
Kurtosis8.4184599
Mean1.4223108
Median Absolute Deviation (MAD)0
Skewness2.2681444
Sum357
Variance0.82894024
MonotonicityNot monotonic
2024-05-11T15:42:42.251192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 162
 
22.3%
2 52
 
7.2%
3 19
 
2.6%
0 11
 
1.5%
4 4
 
0.6%
7 1
 
0.1%
5 1
 
0.1%
6 1
 
0.1%
(Missing) 474
65.4%
ValueCountFrequency (%)
0 11
 
1.5%
1 162
22.3%
2 52
 
7.2%
3 19
 
2.6%
4 4
 
0.6%
5 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 4
 
0.6%
3 19
 
2.6%
2 52
 
7.2%
1 162
22.3%
0 11
 
1.5%

사용시작지하층
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
335 
0
255 
1
128 
2
 
5
3
 
2

Length

Max length4
Median length1
Mean length2.3862069
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 335
46.2%
0 255
35.2%
1 128
 
17.7%
2 5
 
0.7%
3 2
 
0.3%

Length

2024-05-11T15:42:42.405337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:42.568511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 335
46.2%
0 255
35.2%
1 128
 
17.7%
2 5
 
0.7%
3 2
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
557 
1
131 
0
 
29
2
 
6
3
 
2

Length

Max length4
Median length4
Mean length3.3048276
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> 557
76.8%
1 131
 
18.1%
0 29
 
4.0%
2 6
 
0.8%
3 2
 
0.3%

Length

2024-05-11T15:42:42.753084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:42.921499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 557
76.8%
1 131
 
18.1%
0 29
 
4.0%
2 6
 
0.8%
3 2
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
376 
0
349 

Length

Max length4
Median length4
Mean length2.5558621
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 376
51.9%
0 349
48.1%

Length

2024-05-11T15:42:43.129391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:43.308919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
51.9%
0 349
48.1%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
376 
0
349 

Length

Max length4
Median length4
Mean length2.5558621
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 376
51.9%
0 349
48.1%

Length

2024-05-11T15:42:43.432213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:43.569142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
51.9%
0 349
48.1%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
376 
0
349 

Length

Max length4
Median length4
Mean length2.5558621
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 376
51.9%
0 349
48.1%

Length

2024-05-11T15:42:43.716613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:43.847631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
51.9%
0 349
48.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing61
Missing (%)8.4%
Memory size1.5 KiB
False
664 
(Missing)
 
61
ValueCountFrequency (%)
False 664
91.6%
(Missing) 61
 
8.4%
2024-05-11T15:42:43.963556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)2.2%
Missing55
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean3.8164179
Minimum0
Maximum16
Zeros5
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T15:42:44.095094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median3
Q35
95-th percentile8
Maximum16
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3480486
Coefficient of variation (CV)0.61524935
Kurtosis3.1781138
Mean3.8164179
Median Absolute Deviation (MAD)1
Skewness1.5778744
Sum2557
Variance5.5133324
MonotonicityNot monotonic
2024-05-11T15:42:44.269564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 197
27.2%
3 190
26.2%
4 71
 
9.8%
5 47
 
6.5%
7 41
 
5.7%
8 32
 
4.4%
6 31
 
4.3%
1 25
 
3.4%
9 17
 
2.3%
10 6
 
0.8%
Other values (5) 13
 
1.8%
(Missing) 55
 
7.6%
ValueCountFrequency (%)
0 5
 
0.7%
1 25
 
3.4%
2 197
27.2%
3 190
26.2%
4 71
 
9.8%
5 47
 
6.5%
6 31
 
4.3%
7 41
 
5.7%
8 32
 
4.4%
9 17
 
2.3%
ValueCountFrequency (%)
16 1
 
0.1%
15 3
 
0.4%
13 1
 
0.1%
11 3
 
0.4%
10 6
 
0.8%
9 17
 
2.3%
8 32
4.4%
7 41
5.7%
6 31
4.3%
5 47
6.5%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)100.0%
Memory size6.5 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
629 
임대
92 
자가
 
4

Length

Max length4
Median length4
Mean length3.7351724
Min length2

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> 629
86.8%
임대 92
 
12.7%
자가 4
 
0.6%

Length

2024-05-11T15:42:44.475700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:44.621849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 629
86.8%
임대 92
 
12.7%
자가 4
 
0.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
603 
0
122 

Length

Max length4
Median length4
Mean length3.4951724
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> 603
83.2%
0 122
 
16.8%

Length

2024-05-11T15:42:44.770043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:44.919493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 603
83.2%
0 122
 
16.8%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
682 
0
 
41
1
 
2

Length

Max length4
Median length4
Mean length3.822069
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> 682
94.1%
0 41
 
5.7%
1 2
 
0.3%

Length

2024-05-11T15:42:45.071783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:45.292629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 682
94.1%
0 41
 
5.7%
1 2
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
682 
0
 
42
1
 
1

Length

Max length4
Median length4
Mean length3.822069
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 682
94.1%
0 42
 
5.8%
1 1
 
0.1%

Length

2024-05-11T15:42:45.548202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:45.751858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 682
94.1%
0 42
 
5.8%
1 1
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
623 
0
102 

Length

Max length4
Median length4
Mean length3.577931
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> 623
85.9%
0 102
 
14.1%

Length

2024-05-11T15:42:45.945017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:46.142826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 623
85.9%
0 102
 
14.1%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
<NA>
626 
0
99 

Length

Max length4
Median length4
Mean length3.5903448
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> 626
86.3%
0 99
 
13.7%

Length

2024-05-11T15:42:46.348843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:46.525311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 626
86.3%
0 99
 
13.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing47
Missing (%)6.5%
Memory size1.5 KiB
False
678 
(Missing)
 
47
ValueCountFrequency (%)
False 678
93.5%
(Missing) 47
 
6.5%
2024-05-11T15:42:46.640966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032000003200000-203-1968-0198619681029<NA>1영업/정상1영업<NA><NA><NA><NA>02 857061728.0151869서울특별시 관악구 신림동 1594-1서울특별시 관악구 신원로3다길 1, 1층 (신림동)8774대광2021-10-05 09:56:11U2021-10-07 02:40:00.0일반이용업193429.807164442246.272981일반이용업2111<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132000003200000-203-1968-0198919680701<NA>3폐업2폐업20030326<NA><NA><NA>020885074313.05151862서울특별시 관악구 신림동 354-0번지<NA><NA>청용2003-03-26 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232000003200000-203-1968-0199619681029<NA>3폐업2폐업19950111<NA><NA><NA>02 0000017.29151050서울특별시 관악구 봉천동 94-1번지<NA><NA>강남2001-09-29 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332000003200000-203-1968-0199719681028<NA>3폐업2폐업19951202<NA><NA><NA>02 0000013.77151050서울특별시 관악구 봉천동 81-0번지<NA><NA>봉천2001-09-29 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432000003200000-203-1969-0054619690314<NA>1영업/정상1영업<NA><NA><NA><NA>02 889757626.9151830서울특별시 관악구 봉천동 706-4번지서울특별시 관악구 당곡길 49 (봉천동)8722협동2013-07-16 11:55:00I2018-08-31 23:59:59.0일반이용업193569.59297443222.1258일반이용업1111<NA><NA><NA><NA><NA>N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532000003200000-203-1969-0197319690425<NA>3폐업2폐업20040510<NA><NA><NA>02 885792521.24151849서울특별시 관악구 봉천동 1674-8번지<NA><NA>현대2003-09-02 00:00:00I2018-08-31 23:59:59.0일반이용업196257.273818441950.481384일반이용업2<NA>11<NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632000003200000-203-1969-0199419690823<NA>3폐업2폐업20030326<NA><NA><NA>020867157312.01151909서울특별시 관악구 신림동 산 97-0번지<NA><NA>호남2003-03-26 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732000003200000-203-1969-0200319690417<NA>3폐업2폐업20080513<NA><NA><NA>02 886717710.56151843서울특별시 관악구 봉천동 950-1번지<NA><NA>봉일2003-09-02 00:00:00I2018-08-31 23:59:59.0일반이용업194519.533254442557.775786일반이용업2<NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832000003200000-203-1969-0204619690505<NA>3폐업2폐업20221012<NA><NA><NA><NA>10.56151861서울특별시 관악구 신림동 808-143서울특별시 관악구 원신길 156 (신림동)8848현대2022-10-12 15:46:58U2021-10-30 23:04:00.0일반이용업193757.445266440490.932005<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
932000003200000-203-1970-0190719700506<NA>3폐업2폐업19960723<NA><NA><NA>02 0000013.77151813서울특별시 관악구 봉천동 101-0번지<NA><NA>청파2001-09-29 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
71532000003200000-203-2022-0000720220928<NA>3폐업2폐업20221221<NA><NA><NA>05071359582828.62151891서울특별시 관악구 신림동 1430-2 한일하이빌 101호서울특별시 관악구 신림로71길 7, 1층 101호 (신림동, 한일하이빌)8707바버샵 엉클부스 신림점2022-12-21 09:30:55U2021-11-01 22:03:00.0일반이용업193555.127667442912.06449<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
71632000003200000-203-2022-000082022-12-22<NA>3폐업2폐업2024-02-26<NA><NA><NA>05071359582828.62151-891서울특별시 관악구 신림동 1430-2 한일하이빌서울특별시 관악구 신림로71길 7, 1층 101호 (신림동, 한일하이빌)8707바버샵 엉클부스2024-02-26 11:25:59U2023-12-01 22:08:00.0일반이용업193555.127667442912.06449<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
71732000003200000-203-2023-0000120230125<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.45151892서울특별시 관악구 신림동 1462-41서울특별시 관악구 신림동길 41, 101호 (신림동)8759BROOKS 브룩스2023-01-25 17:32:36I2022-11-30 22:07:00.0일반이용업193221.296786442712.90475<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
71832000003200000-203-2023-000022023-02-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.29151-895서울특별시 관악구 신림동 1536 세목서울특별시 관악구 호암로24길 52, 세목 6층 603호 (신림동)8813엉클맨즈뷰티케어2023-02-13 17:38:04I2022-12-01 23:05:00.0일반이용업194269.061941440798.364864<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
71932000003200000-203-2023-000032023-06-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.1151-840서울특별시 관악구 봉천동 908-63 다솜HOUSE서울특별시 관악구 봉천로33길 18, 다솜HOUSE 1층 (봉천동)8752편안머리2023-06-26 14:33:14I2022-12-05 22:08:00.0일반이용업194964.033808442423.10074<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
72032000003200000-203-2023-000042023-08-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.91151-835서울특별시 관악구 봉천동 1601-1서울특별시 관악구 남부순환로 1840, 2층 R04호 (봉천동)8788맨라이즈바버샵 with 맨즈헤어2023-12-08 14:02:40U2022-11-01 23:00:00.0일반이용업195888.1921442019.999682<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
72132000003200000-203-2023-000052023-09-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0151-830서울특별시 관악구 봉천동 698-32서울특별시 관악구 보라매로2길 11, 1층 (봉천동)8722대성남성컷전문2023-09-07 10:33:14I2022-12-09 00:09:00.0일반이용업193624.500797443101.985288<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
72232000003200000-203-2024-000012024-01-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.5151-823서울특별시 관악구 봉천동 888-25서울특별시 관악구 양녕로 32-1, 1층 (봉천동)8747SUPER MANS(슈퍼맨즈)2024-01-24 16:08:58I2023-11-30 22:06:00.0일반이용업195236.115754442529.232624<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
72332000003200000-203-2024-000022024-03-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.9151-903서울특별시 관악구 신림동 1666-35서울특별시 관악구 시흥대로158가길 25, 1층 (신림동)876845바버샵2024-03-28 11:21:22I2023-12-02 21:00:00.0일반이용업191106.438915442028.921461<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
72432000003200000-203-2024-000032024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.14151-873서울특별시 관악구 신림동 514-4서울특별시 관악구 조원로 115-1, 1층 (신림동)8705넘버원 남성컷트전문점2024-04-25 15:59:36I2023-12-03 22:07:00.0일반이용업192429.922331442558.786427<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>