Overview

Dataset statistics

Number of variables47
Number of observations9174
Missing cells111806
Missing cells (%)25.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 MiB
Average record size in memory404.0 B

Variable types

Categorical17
Text7
DateTime4
Unsupported7
Numeric10
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-17924/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
사용시작지하층 is highly imbalanced (60.1%)Imbalance
사용끝지하층 is highly imbalanced (72.9%)Imbalance
발한실여부 is highly imbalanced (99.2%)Imbalance
건물소유구분명 is highly imbalanced (57.5%)Imbalance
남성종사자수 is highly imbalanced (57.9%)Imbalance
다중이용업소여부 is highly imbalanced (98.6%)Imbalance
인허가취소일자 has 9174 (100.0%) missing valuesMissing
폐업일자 has 2951 (32.2%) missing valuesMissing
휴업시작일자 has 9174 (100.0%) missing valuesMissing
휴업종료일자 has 9174 (100.0%) missing valuesMissing
재개업일자 has 9174 (100.0%) missing valuesMissing
전화번호 has 4616 (50.3%) missing valuesMissing
도로명주소 has 2585 (28.2%) missing valuesMissing
도로명우편번호 has 2630 (28.7%) missing valuesMissing
좌표정보(X) has 106 (1.2%) missing valuesMissing
좌표정보(Y) has 106 (1.2%) missing valuesMissing
건물지상층수 has 2675 (29.2%) missing valuesMissing
건물지하층수 has 2954 (32.2%) missing valuesMissing
사용시작지상층 has 5695 (62.1%) missing valuesMissing
사용끝지상층 has 5914 (64.5%) missing valuesMissing
발한실여부 has 1948 (21.2%) missing valuesMissing
좌석수 has 2004 (21.8%) missing valuesMissing
조건부허가신고사유 has 9174 (100.0%) missing valuesMissing
조건부허가시작일자 has 9174 (100.0%) missing valuesMissing
조건부허가종료일자 has 9174 (100.0%) missing valuesMissing
여성종사자수 has 6729 (73.3%) missing valuesMissing
침대수 has 4857 (52.9%) missing valuesMissing
다중이용업소여부 has 1813 (19.8%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 39.25021328)Skewed
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
건물지상층수 has 4923 (53.7%) zerosZeros
건물지하층수 has 5213 (56.8%) zerosZeros
사용시작지상층 has 1148 (12.5%) zerosZeros
사용끝지상층 has 298 (3.2%) zerosZeros
좌석수 has 746 (8.1%) zerosZeros
여성종사자수 has 2427 (26.5%) zerosZeros
침대수 has 2728 (29.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:06:57.385527
Analysis finished2024-05-11 06:07:01.589239
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
3220000
9174 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 9174
100.0%

Length

2024-05-11T15:07:01.691732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:01.832659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 9174
100.0%

관리번호
Text

UNIQUE 

Distinct9174
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
2024-05-11T15:07:02.084638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters201828
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

Unique9174 ?
Unique (%)100.0%

Sample

1st row3220000-204-1945-00831
2nd row3220000-204-1971-01811
3rd row3220000-204-1974-01667
4th row3220000-204-1974-01875
5th row3220000-204-1975-01870
ValueCountFrequency (%)
3220000-204-1945-00831 1
 
< 0.1%
3220000-212-2019-00045 1
 
< 0.1%
3220000-212-2019-00047 1
 
< 0.1%
3220000-212-2019-00040 1
 
< 0.1%
3220000-212-2019-00041 1
 
< 0.1%
3220000-212-2019-00042 1
 
< 0.1%
3220000-212-2019-00043 1
 
< 0.1%
3220000-212-2019-00044 1
 
< 0.1%
3220000-212-2019-00038 1
 
< 0.1%
3220000-212-2019-00037 1
 
< 0.1%
Other values (9164) 9164
99.9%
2024-05-11T15:07:02.624008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76465
37.9%
2 42677
21.1%
- 27522
 
13.6%
1 18828
 
9.3%
3 13448
 
6.7%
4 5862
 
2.9%
9 5464
 
2.7%
5 3287
 
1.6%
8 3003
 
1.5%
6 2683
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 174306
86.4%
Dash Punctuation 27522
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76465
43.9%
2 42677
24.5%
1 18828
 
10.8%
3 13448
 
7.7%
4 5862
 
3.4%
9 5464
 
3.1%
5 3287
 
1.9%
8 3003
 
1.7%
6 2683
 
1.5%
7 2589
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 27522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76465
37.9%
2 42677
21.1%
- 27522
 
13.6%
1 18828
 
9.3%
3 13448
 
6.7%
4 5862
 
2.9%
9 5464
 
2.7%
5 3287
 
1.6%
8 3003
 
1.5%
6 2683
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76465
37.9%
2 42677
21.1%
- 27522
 
13.6%
1 18828
 
9.3%
3 13448
 
6.7%
4 5862
 
2.9%
9 5464
 
2.7%
5 3287
 
1.6%
8 3003
 
1.5%
6 2683
 
1.3%
Distinct5047
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
Minimum1945-10-18 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:07:02.827312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:03.059256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
3
6223 
1
2951 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 6223
67.8%
1 2951
32.2%

Length

2024-05-11T15:07:03.227528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:03.365375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6223
67.8%
1 2951
32.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
폐업
6223 
영업/정상
2951 

Length

Max length5
Median length2
Mean length2.9650098
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6223
67.8%
영업/정상 2951
32.2%

Length

2024-05-11T15:07:03.529164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:03.666024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6223
67.8%
영업/정상 2951
32.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
2
6223 
1
2951 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6223
67.8%
1 2951
32.2%

Length

2024-05-11T15:07:03.801462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:03.959784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6223
67.8%
1 2951
32.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
폐업
6223 
영업
2951 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6223
67.8%
영업 2951
32.2%

Length

2024-05-11T15:07:04.148095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:04.296246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6223
67.8%
영업 2951
32.2%

폐업일자
Date

MISSING 

Distinct3667
Distinct (%)58.9%
Missing2951
Missing (%)32.2%
Memory size71.8 KiB
Minimum1991-05-31 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:07:04.487696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:04.806470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB

전화번호
Text

MISSING 

Distinct4109
Distinct (%)90.1%
Missing4616
Missing (%)50.3%
Memory size71.8 KiB
2024-05-11T15:07:05.215241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.258885
Min length2

Characters and Unicode

Total characters46760
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

Unique3784 ?
Unique (%)83.0%

Sample

1st row02 5551754
2nd row0205490142
3rd row02 5483285
4th row0205439705
5th row02 5423853
ValueCountFrequency (%)
02 3200
36.5%
070 53
 
0.6%
515 45
 
0.5%
511 43
 
0.5%
545 33
 
0.4%
540 30
 
0.3%
00000 30
 
0.3%
518 30
 
0.3%
555 28
 
0.3%
542 27
 
0.3%
Other values (4127) 5258
59.9%
2024-05-11T15:07:05.885020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7371
15.8%
2 6880
14.7%
5 6549
14.0%
5473
11.7%
4 4318
9.2%
1 3079
6.6%
3 2971
6.4%
6 2870
 
6.1%
7 2778
 
5.9%
8 2516
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41287
88.3%
Space Separator 5473
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7371
17.9%
2 6880
16.7%
5 6549
15.9%
4 4318
10.5%
1 3079
7.5%
3 2971
7.2%
6 2870
 
7.0%
7 2778
 
6.7%
8 2516
 
6.1%
9 1955
 
4.7%
Space Separator
ValueCountFrequency (%)
5473
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7371
15.8%
2 6880
14.7%
5 6549
14.0%
5473
11.7%
4 4318
9.2%
1 3079
6.6%
3 2971
6.4%
6 2870
 
6.1%
7 2778
 
5.9%
8 2516
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7371
15.8%
2 6880
14.7%
5 6549
14.0%
5473
11.7%
4 4318
9.2%
1 3079
6.6%
3 2971
6.4%
6 2870
 
6.1%
7 2778
 
5.9%
8 2516
 
5.4%
Distinct4355
Distinct (%)47.5%
Missing3
Missing (%)< 0.1%
Memory size71.8 KiB
2024-05-11T15:07:06.502868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.2070658
Min length3

Characters and Unicode

Total characters47754
Distinct characters12
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

Unique3000 ?
Unique (%)32.7%

Sample

1st row106.02
2nd row14.72
3rd row12.88
4th row22.50
5th row30.00
ValueCountFrequency (%)
33.00 218
 
2.4%
00 151
 
1.6%
66.00 90
 
1.0%
30.00 78
 
0.9%
99.00 76
 
0.8%
49.50 71
 
0.8%
26.40 70
 
0.8%
50.00 58
 
0.6%
40.00 54
 
0.6%
20.00 53
 
0.6%
Other values (4345) 8252
90.0%
2024-05-11T15:07:07.415360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9171
19.2%
0 8247
17.3%
1 4763
10.0%
2 4093
8.6%
3 3806
8.0%
4 3313
 
6.9%
5 3233
 
6.8%
6 3164
 
6.6%
9 2773
 
5.8%
8 2739
 
5.7%
Other values (2) 2452
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38579
80.8%
Other Punctuation 9175
 
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8247
21.4%
1 4763
12.3%
2 4093
10.6%
3 3806
9.9%
4 3313
8.6%
5 3233
 
8.4%
6 3164
 
8.2%
9 2773
 
7.2%
8 2739
 
7.1%
7 2448
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 9171
> 99.9%
, 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 47754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9171
19.2%
0 8247
17.3%
1 4763
10.0%
2 4093
8.6%
3 3806
8.0%
4 3313
 
6.9%
5 3233
 
6.8%
6 3164
 
6.6%
9 2773
 
5.8%
8 2739
 
5.7%
Other values (2) 2452
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9171
19.2%
0 8247
17.3%
1 4763
10.0%
2 4093
8.6%
3 3806
8.0%
4 3313
 
6.9%
5 3233
 
6.8%
6 3164
 
6.6%
9 2773
 
5.8%
8 2739
 
5.7%
Other values (2) 2452
 
5.1%
Distinct384
Distinct (%)4.2%
Missing1
Missing (%)< 0.1%
Memory size71.8 KiB
2024-05-11T15:07:07.988439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1280933
Min length6

Characters and Unicode

Total characters56213
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

Unique53 ?
Unique (%)0.6%

Sample

1st row135878
2nd row135190
3rd row135952
4th row135948
5th row135887
ValueCountFrequency (%)
135897 405
 
4.4%
135896 205
 
2.2%
135891 203
 
2.2%
135827 187
 
2.0%
135954 187
 
2.0%
135825 157
 
1.7%
135841 140
 
1.5%
135889 120
 
1.3%
135890 116
 
1.3%
135840 116
 
1.3%
Other values (374) 7337
80.0%
2024-05-11T15:07:08.812020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 11650
20.7%
1 11360
20.2%
3 10935
19.5%
8 6378
11.3%
9 5965
10.6%
2 1996
 
3.6%
0 1886
 
3.4%
4 1828
 
3.3%
7 1742
 
3.1%
6 1298
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55038
97.9%
Dash Punctuation 1175
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 11650
21.2%
1 11360
20.6%
3 10935
19.9%
8 6378
11.6%
9 5965
10.8%
2 1996
 
3.6%
0 1886
 
3.4%
4 1828
 
3.3%
7 1742
 
3.2%
6 1298
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56213
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 11650
20.7%
1 11360
20.2%
3 10935
19.5%
8 6378
11.3%
9 5965
10.6%
2 1996
 
3.6%
0 1886
 
3.4%
4 1828
 
3.3%
7 1742
 
3.1%
6 1298
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56213
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 11650
20.7%
1 11360
20.2%
3 10935
19.5%
8 6378
11.3%
9 5965
10.6%
2 1996
 
3.6%
0 1886
 
3.4%
4 1828
 
3.3%
7 1742
 
3.1%
6 1298
 
2.3%
Distinct7274
Distinct (%)79.3%
Missing1
Missing (%)< 0.1%
Memory size71.8 KiB
2024-05-11T15:07:09.296938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length25.235256
Min length15

Characters and Unicode

Total characters231483
Distinct characters481
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6051 ?
Unique (%)66.0%

Sample

1st row서울특별시 강남구 삼성동 152-62번지
2nd row서울특별시 강남구 세곡동 118번지
3rd row서울특별시 강남구 청담동 50-2번지
4th row서울특별시 강남구 청담동 4-9번지
5th row서울특별시 강남구 신사동 510-0번지
ValueCountFrequency (%)
서울특별시 9172
21.2%
강남구 9170
21.2%
신사동 1825
 
4.2%
역삼동 1796
 
4.1%
논현동 1545
 
3.6%
청담동 1064
 
2.5%
대치동 1051
 
2.4%
삼성동 703
 
1.6%
지상1층 645
 
1.5%
개포동 395
 
0.9%
Other values (6979) 15926
36.8%
2024-05-11T15:07:10.024255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41222
 
17.8%
1 9983
 
4.3%
9421
 
4.1%
9367
 
4.0%
9307
 
4.0%
9299
 
4.0%
9298
 
4.0%
9271
 
4.0%
9194
 
4.0%
9174
 
4.0%
Other values (471) 105947
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135195
58.4%
Decimal Number 45341
 
19.6%
Space Separator 41222
 
17.8%
Dash Punctuation 8232
 
3.6%
Uppercase Letter 718
 
0.3%
Other Punctuation 290
 
0.1%
Close Punctuation 169
 
0.1%
Open Punctuation 169
 
0.1%
Lowercase Letter 113
 
< 0.1%
Math Symbol 32
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9421
 
7.0%
9367
 
6.9%
9307
 
6.9%
9299
 
6.9%
9298
 
6.9%
9271
 
6.9%
9194
 
6.8%
9174
 
6.8%
9172
 
6.8%
8293
 
6.1%
Other values (402) 43399
32.1%
Uppercase Letter
ValueCountFrequency (%)
S 99
13.8%
A 98
13.6%
B 76
 
10.6%
E 48
 
6.7%
T 41
 
5.7%
R 36
 
5.0%
P 28
 
3.9%
I 27
 
3.8%
C 23
 
3.2%
J 23
 
3.2%
Other values (15) 219
30.5%
Lowercase Letter
ValueCountFrequency (%)
i 12
10.6%
e 12
10.6%
l 11
 
9.7%
n 10
 
8.8%
r 10
 
8.8%
a 8
 
7.1%
y 6
 
5.3%
t 6
 
5.3%
p 5
 
4.4%
g 5
 
4.4%
Other values (10) 28
24.8%
Decimal Number
ValueCountFrequency (%)
1 9983
22.0%
2 6112
13.5%
6 4800
10.6%
3 3969
 
8.8%
5 3965
 
8.7%
0 3882
 
8.6%
4 3293
 
7.3%
7 3154
 
7.0%
8 3112
 
6.9%
9 3071
 
6.8%
Other Punctuation
ValueCountFrequency (%)
, 224
77.2%
. 46
 
15.9%
/ 10
 
3.4%
& 5
 
1.7%
' 4
 
1.4%
* 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 26
81.2%
> 3
 
9.4%
< 3
 
9.4%
Space Separator
ValueCountFrequency (%)
41222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8232
100.0%
Close Punctuation
ValueCountFrequency (%)
) 169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 169
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135191
58.4%
Common 95455
41.2%
Latin 833
 
0.4%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9421
 
7.0%
9367
 
6.9%
9307
 
6.9%
9299
 
6.9%
9298
 
6.9%
9271
 
6.9%
9194
 
6.8%
9174
 
6.8%
9172
 
6.8%
8293
 
6.1%
Other values (398) 43395
32.1%
Latin
ValueCountFrequency (%)
S 99
 
11.9%
A 98
 
11.8%
B 76
 
9.1%
E 48
 
5.8%
T 41
 
4.9%
R 36
 
4.3%
P 28
 
3.4%
I 27
 
3.2%
C 23
 
2.8%
J 23
 
2.8%
Other values (36) 334
40.1%
Common
ValueCountFrequency (%)
41222
43.2%
1 9983
 
10.5%
- 8232
 
8.6%
2 6112
 
6.4%
6 4800
 
5.0%
3 3969
 
4.2%
5 3965
 
4.2%
0 3882
 
4.1%
4 3293
 
3.4%
7 3154
 
3.3%
Other values (13) 6843
 
7.2%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135190
58.4%
ASCII 96286
41.6%
CJK 4
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41222
42.8%
1 9983
 
10.4%
- 8232
 
8.5%
2 6112
 
6.3%
6 4800
 
5.0%
3 3969
 
4.1%
5 3965
 
4.1%
0 3882
 
4.0%
4 3293
 
3.4%
7 3154
 
3.3%
Other values (58) 7674
 
8.0%
Hangul
ValueCountFrequency (%)
9421
 
7.0%
9367
 
6.9%
9307
 
6.9%
9299
 
6.9%
9298
 
6.9%
9271
 
6.9%
9194
 
6.8%
9174
 
6.8%
9172
 
6.8%
8293
 
6.1%
Other values (397) 43394
32.1%
Number Forms
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct5958
Distinct (%)90.4%
Missing2585
Missing (%)28.2%
Memory size71.8 KiB
2024-05-11T15:07:10.885924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length58
Mean length35.627713
Min length19

Characters and Unicode

Total characters234751
Distinct characters485
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5457 ?
Unique (%)82.8%

Sample

1st row서울특별시 강남구 도산대로30길 23 (논현동)
2nd row서울특별시 강남구 압구정로 212 (신사동)
3rd row서울특별시 강남구 언주로 317 (역삼동)
4th row서울특별시 강남구 압구정로29길 71 (압구정동,(2동 지하 4호))
5th row서울특별시 강남구 남부순환로 2917 (대치동,(청실상가 314호))
ValueCountFrequency (%)
서울특별시 6588
 
14.9%
강남구 6587
 
14.9%
역삼동 1257
 
2.9%
지상1층 1127
 
2.6%
신사동 1119
 
2.5%
논현동 969
 
2.2%
지상2층 916
 
2.1%
청담동 681
 
1.5%
지하1층 581
 
1.3%
대치동 545
 
1.2%
Other values (3817) 23708
53.8%
2024-05-11T15:07:11.729989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37500
 
16.0%
1 11629
 
5.0%
, 7912
 
3.4%
7631
 
3.3%
7464
 
3.2%
7450
 
3.2%
2 7277
 
3.1%
7178
 
3.1%
6754
 
2.9%
6740
 
2.9%
Other values (475) 127216
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132534
56.5%
Decimal Number 41665
 
17.7%
Space Separator 37500
 
16.0%
Other Punctuation 7962
 
3.4%
Close Punctuation 6665
 
2.8%
Open Punctuation 6665
 
2.8%
Uppercase Letter 936
 
0.4%
Dash Punctuation 685
 
0.3%
Lowercase Letter 93
 
< 0.1%
Math Symbol 43
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7631
 
5.8%
7464
 
5.6%
7450
 
5.6%
7178
 
5.4%
6754
 
5.1%
6740
 
5.1%
6717
 
5.1%
6614
 
5.0%
6591
 
5.0%
6588
 
5.0%
Other values (404) 62807
47.4%
Uppercase Letter
ValueCountFrequency (%)
B 261
27.9%
S 115
12.3%
A 92
 
9.8%
E 54
 
5.8%
H 39
 
4.2%
R 36
 
3.8%
C 29
 
3.1%
T 28
 
3.0%
K 28
 
3.0%
I 28
 
3.0%
Other values (15) 226
24.1%
Lowercase Letter
ValueCountFrequency (%)
i 10
10.8%
e 9
 
9.7%
l 9
 
9.7%
r 8
 
8.6%
n 8
 
8.6%
a 6
 
6.5%
t 5
 
5.4%
s 5
 
5.4%
y 5
 
5.4%
g 4
 
4.3%
Other values (10) 24
25.8%
Decimal Number
ValueCountFrequency (%)
1 11629
27.9%
2 7277
17.5%
3 4552
 
10.9%
0 4147
 
10.0%
4 3385
 
8.1%
5 3008
 
7.2%
6 2425
 
5.8%
8 1963
 
4.7%
7 1873
 
4.5%
9 1406
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 7912
99.4%
. 38
 
0.5%
& 4
 
0.1%
/ 4
 
0.1%
' 3
 
< 0.1%
* 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 41
95.3%
> 1
 
2.3%
< 1
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 6660
99.9%
] 5
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 6660
99.9%
[ 5
 
0.1%
Space Separator
ValueCountFrequency (%)
37500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 685
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132530
56.5%
Common 101185
43.1%
Latin 1032
 
0.4%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7631
 
5.8%
7464
 
5.6%
7450
 
5.6%
7178
 
5.4%
6754
 
5.1%
6740
 
5.1%
6717
 
5.1%
6614
 
5.0%
6591
 
5.0%
6588
 
5.0%
Other values (400) 62803
47.4%
Latin
ValueCountFrequency (%)
B 261
25.3%
S 115
 
11.1%
A 92
 
8.9%
E 54
 
5.2%
H 39
 
3.8%
R 36
 
3.5%
C 29
 
2.8%
T 28
 
2.7%
K 28
 
2.7%
I 28
 
2.7%
Other values (36) 322
31.2%
Common
ValueCountFrequency (%)
37500
37.1%
1 11629
 
11.5%
, 7912
 
7.8%
2 7277
 
7.2%
) 6660
 
6.6%
( 6660
 
6.6%
3 4552
 
4.5%
0 4147
 
4.1%
4 3385
 
3.3%
5 3008
 
3.0%
Other values (15) 8455
 
8.4%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132530
56.5%
ASCII 102214
43.5%
CJK 4
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37500
36.7%
1 11629
 
11.4%
, 7912
 
7.7%
2 7277
 
7.1%
) 6660
 
6.5%
( 6660
 
6.5%
3 4552
 
4.5%
0 4147
 
4.1%
4 3385
 
3.3%
5 3008
 
2.9%
Other values (60) 9484
 
9.3%
Hangul
ValueCountFrequency (%)
7631
 
5.8%
7464
 
5.6%
7450
 
5.6%
7178
 
5.4%
6754
 
5.1%
6740
 
5.1%
6717
 
5.1%
6614
 
5.0%
6591
 
5.0%
6588
 
5.0%
Other values (400) 62803
47.4%
Number Forms
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct349
Distinct (%)5.3%
Missing2630
Missing (%)28.7%
Infinite0
Infinite (%)0.0%
Mean6134.5853
Minimum4794
Maximum16489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:12.012224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4794
5-th percentile6015
Q16035
median6119
Q36208
95-th percentile6325
Maximum16489
Range11695
Interquartile range (IQR)173

Descriptive statistics

Standard deviation162.96703
Coefficient of variation (CV)0.026565289
Kurtosis2491.0254
Mean6134.5853
Median Absolute Deviation (MAD)84
Skewness39.250213
Sum40144726
Variance26558.254
MonotonicityNot monotonic
2024-05-11T15:07:12.276035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6018 167
 
1.8%
6035 122
 
1.3%
6017 114
 
1.2%
6019 110
 
1.2%
6120 95
 
1.0%
6014 86
 
0.9%
6028 85
 
0.9%
6119 80
 
0.9%
6129 79
 
0.9%
6030 73
 
0.8%
Other values (339) 5533
60.3%
(Missing) 2630
28.7%
ValueCountFrequency (%)
4794 1
 
< 0.1%
6000 17
0.2%
6001 7
 
0.1%
6002 13
 
0.1%
6004 10
 
0.1%
6005 5
 
0.1%
6006 7
 
0.1%
6008 1
 
< 0.1%
6009 1
 
< 0.1%
6010 38
0.4%
ValueCountFrequency (%)
16489 1
 
< 0.1%
6378 1
 
< 0.1%
6377 1
 
< 0.1%
6376 18
0.2%
6375 2
 
< 0.1%
6374 4
 
< 0.1%
6373 17
0.2%
6372 13
0.1%
6370 3
 
< 0.1%
6369 2
 
< 0.1%
Distinct8044
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
2024-05-11T15:07:12.852953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length6.7710922
Min length1

Characters and Unicode

Total characters62118
Distinct characters928
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7230 ?
Unique (%)78.8%

Sample

1st row고원혜구뜨
2nd row새로나
3rd row킴스헤어라인
4th row윤희
5th row서지희
ValueCountFrequency (%)
헤어 168
 
1.4%
에스테틱 152
 
1.2%
네일 80
 
0.6%
hair 74
 
0.6%
nail 65
 
0.5%
56
 
0.5%
미용실 54
 
0.4%
뷰티 53
 
0.4%
스파 47
 
0.4%
beauty 43
 
0.3%
Other values (8614) 11646
93.6%
2024-05-11T15:07:13.735009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3268
 
5.3%
2423
 
3.9%
2244
 
3.6%
2157
 
3.5%
1647
 
2.7%
1309
 
2.1%
1106
 
1.8%
) 994
 
1.6%
( 992
 
1.6%
923
 
1.5%
Other values (918) 45055
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48325
77.8%
Lowercase Letter 4097
 
6.6%
Uppercase Letter 3515
 
5.7%
Space Separator 3268
 
5.3%
Close Punctuation 998
 
1.6%
Open Punctuation 996
 
1.6%
Decimal Number 486
 
0.8%
Other Punctuation 378
 
0.6%
Dash Punctuation 32
 
0.1%
Connector Punctuation 9
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2423
 
5.0%
2244
 
4.6%
2157
 
4.5%
1647
 
3.4%
1309
 
2.7%
1106
 
2.3%
923
 
1.9%
812
 
1.7%
795
 
1.6%
789
 
1.6%
Other values (828) 34120
70.6%
Lowercase Letter
ValueCountFrequency (%)
a 517
12.6%
e 454
11.1%
i 394
 
9.6%
o 307
 
7.5%
n 299
 
7.3%
l 285
 
7.0%
r 229
 
5.6%
t 210
 
5.1%
u 186
 
4.5%
s 178
 
4.3%
Other values (16) 1038
25.3%
Uppercase Letter
ValueCountFrequency (%)
A 384
 
10.9%
E 258
 
7.3%
N 245
 
7.0%
S 240
 
6.8%
O 233
 
6.6%
L 227
 
6.5%
I 221
 
6.3%
H 210
 
6.0%
B 209
 
5.9%
R 163
 
4.6%
Other values (16) 1125
32.0%
Other Punctuation
ValueCountFrequency (%)
. 106
28.0%
& 103
27.2%
? 66
17.5%
, 33
 
8.7%
# 24
 
6.3%
' 23
 
6.1%
: 15
 
4.0%
3
 
0.8%
! 2
 
0.5%
@ 1
 
0.3%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 107
22.0%
2 93
19.1%
0 59
12.1%
5 43
8.8%
3 42
 
8.6%
4 40
 
8.2%
7 29
 
6.0%
8 27
 
5.6%
6 24
 
4.9%
9 22
 
4.5%
Math Symbol
ValueCountFrequency (%)
+ 3
37.5%
× 2
25.0%
< 1
 
12.5%
> 1
 
12.5%
= 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 994
99.6%
] 4
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 992
99.6%
[ 4
 
0.4%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
3268
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Modifier Letter
ValueCountFrequency (%)
ː 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48309
77.8%
Latin 7615
 
12.3%
Common 6178
 
9.9%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2423
 
5.0%
2244
 
4.6%
2157
 
4.5%
1647
 
3.4%
1309
 
2.7%
1106
 
2.3%
923
 
1.9%
812
 
1.7%
795
 
1.6%
789
 
1.6%
Other values (817) 34104
70.6%
Latin
ValueCountFrequency (%)
a 517
 
6.8%
e 454
 
6.0%
i 394
 
5.2%
A 384
 
5.0%
o 307
 
4.0%
n 299
 
3.9%
l 285
 
3.7%
E 258
 
3.4%
N 245
 
3.2%
S 240
 
3.2%
Other values (44) 4232
55.6%
Common
ValueCountFrequency (%)
3268
52.9%
) 994
 
16.1%
( 992
 
16.1%
1 107
 
1.7%
. 106
 
1.7%
& 103
 
1.7%
2 93
 
1.5%
? 66
 
1.1%
0 59
 
1.0%
5 43
 
0.7%
Other values (26) 347
 
5.6%
Han
ValueCountFrequency (%)
5
31.2%
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48308
77.8%
ASCII 13784
 
22.2%
CJK 16
 
< 0.1%
None 5
 
< 0.1%
Number Forms 3
 
< 0.1%
Modifier Letters 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3268
23.7%
) 994
 
7.2%
( 992
 
7.2%
a 517
 
3.8%
e 454
 
3.3%
i 394
 
2.9%
A 384
 
2.8%
o 307
 
2.2%
n 299
 
2.2%
l 285
 
2.1%
Other values (75) 5890
42.7%
Hangul
ValueCountFrequency (%)
2423
 
5.0%
2244
 
4.6%
2157
 
4.5%
1647
 
3.4%
1309
 
2.7%
1106
 
2.3%
923
 
1.9%
812
 
1.7%
795
 
1.6%
789
 
1.6%
Other values (816) 34103
70.6%
CJK
ValueCountFrequency (%)
5
31.2%
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
None
ValueCountFrequency (%)
3
60.0%
× 2
40.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
Modifier Letters
ValueCountFrequency (%)
ː 1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct7557
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
Minimum1999-01-18 00:00:00
Maximum2024-05-09 17:12:58
2024-05-11T15:07:14.013364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:14.284333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
I
6540 
U
2587 
D
 
47

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6540
71.3%
U 2587
 
28.2%
D 47
 
0.5%

Length

2024-05-11T15:07:14.540759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:14.753736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6540
71.3%
u 2587
 
28.2%
d 47
 
0.5%
Distinct1557
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:07:14.983146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:15.252743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
일반미용업
5590 
피부미용업
2178 
네일아트업
896 
메이크업업
 
340
기타
 
170

Length

Max length5
Median length5
Mean length4.9444081
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 5590
60.9%
피부미용업 2178
 
23.7%
네일아트업 896
 
9.8%
메이크업업 340
 
3.7%
기타 170
 
1.9%

Length

2024-05-11T15:07:15.570496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:15.752341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 5590
60.9%
피부미용업 2178
 
23.7%
네일아트업 896
 
9.8%
메이크업업 340
 
3.7%
기타 170
 
1.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3921
Distinct (%)43.2%
Missing106
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean203671.9
Minimum192949.66
Maximum210050.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:15.964607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192949.66
5-th percentile201936.23
Q1202622.51
median203437.52
Q3204436.97
95-th percentile205973.61
Maximum210050.9
Range17101.238
Interquartile range (IQR)1814.4601

Descriptive statistics

Standard deviation1383.9043
Coefficient of variation (CV)0.0067947728
Kurtosis2.919363
Mean203671.9
Median Absolute Deviation (MAD)910.95905
Skewness1.2422864
Sum1.8468968 × 109
Variance1915191
MonotonicityNot monotonic
2024-05-11T15:07:16.223719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205707.089399978 84
 
0.9%
204044.789948927 37
 
0.4%
204536.822020513 35
 
0.4%
204268.379202885 31
 
0.3%
201620.446225572 29
 
0.3%
205034.15838707 26
 
0.3%
205130.591678902 24
 
0.3%
203518.763332969 24
 
0.3%
202520.972243984 24
 
0.3%
202619.098126049 23
 
0.3%
Other values (3911) 8731
95.2%
(Missing) 106
 
1.2%
ValueCountFrequency (%)
192949.664803569 1
 
< 0.1%
201543.962547061 1
 
< 0.1%
201609.62721933 1
 
< 0.1%
201613.889762888 1
 
< 0.1%
201620.446225572 29
0.3%
201621.76711437 8
 
0.1%
201640.067533451 1
 
< 0.1%
201646.055864734 1
 
< 0.1%
201650.787158848 1
 
< 0.1%
201657.313312924 1
 
< 0.1%
ValueCountFrequency (%)
210050.902574 1
 
< 0.1%
209802.490272781 1
 
< 0.1%
209587.830946603 1
 
< 0.1%
209511.078058283 1
 
< 0.1%
209423.649311203 4
< 0.1%
209409.371497729 1
 
< 0.1%
209401.0 1
 
< 0.1%
209393.872291339 1
 
< 0.1%
209373.675692218 1
 
< 0.1%
209323.900775047 2
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3919
Distinct (%)43.2%
Missing106
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean445206.27
Minimum418315.89
Maximum449806.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:16.582516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum418315.89
5-th percentile442580.37
Q1444136.17
median445252.99
Q3446627.96
95-th percentile447187
Maximum449806.72
Range31490.825
Interquartile range (IQR)2491.7911

Descriptive statistics

Standard deviation1527.999
Coefficient of variation (CV)0.0034321147
Kurtosis9.9725173
Mean445206.27
Median Absolute Deviation (MAD)1245.3994
Skewness-1.0441649
Sum4.0371304 × 109
Variance2334780.9
MonotonicityNot monotonic
2024-05-11T15:07:16.842225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443914.194133105 84
 
0.9%
444529.84042741 37
 
0.4%
444660.784269339 35
 
0.4%
444593.806677242 31
 
0.3%
446358.542778413 29
 
0.3%
446675.932361885 26
 
0.3%
445590.096837802 24
 
0.3%
443946.832938881 24
 
0.3%
446051.579831786 24
 
0.3%
443688.691713202 23
 
0.3%
Other values (3909) 8731
95.2%
(Missing) 106
 
1.2%
ValueCountFrequency (%)
418315.892733314 1
 
< 0.1%
439796.044686133 3
< 0.1%
440112.987487173 1
 
< 0.1%
440114.723537769 1
 
< 0.1%
440151.497594716 1
 
< 0.1%
440183.87349816 1
 
< 0.1%
440202.431192527 1
 
< 0.1%
440208.558412381 4
< 0.1%
440233.388928253 1
 
< 0.1%
440372.477651303 1
 
< 0.1%
ValueCountFrequency (%)
449806.717609161 1
 
< 0.1%
449257.264370347 1
 
< 0.1%
447864.763737276 17
0.2%
447782.51322707 4
 
< 0.1%
447748.161018109 4
 
< 0.1%
447708.404153773 1
 
< 0.1%
447663.86257666 7
0.1%
447649.978394541 5
 
0.1%
447521.520319158 3
 
< 0.1%
447439.752421 5
 
0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
미용업
2872 
<NA>
1813 
피부미용업
1396 
일반미용업
1362 
종합미용업
804 
Other values (12)
927 

Length

Max length23
Median length19
Mean length4.8445607
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 2872
31.3%
<NA> 1813
19.8%
피부미용업 1396
15.2%
일반미용업 1362
14.8%
종합미용업 804
 
8.8%
네일미용업 347
 
3.8%
일반미용업, 화장ㆍ분장 미용업 171
 
1.9%
피부미용업, 네일미용업 90
 
1.0%
화장ㆍ분장 미용업 72
 
0.8%
일반미용업, 네일미용업, 화장ㆍ분장 미용업 69
 
0.8%
Other values (7) 178
 
1.9%

Length

2024-05-11T15:07:17.120550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 3290
32.2%
na 1813
17.7%
일반미용업 1682
16.4%
피부미용업 1594
15.6%
종합미용업 804
 
7.9%
네일미용업 628
 
6.1%
화장ㆍ분장 418
 
4.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)0.5%
Missing2675
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean0.98168949
Minimum0
Maximum45
Zeros4923
Zeros (%)53.7%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:17.343002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum45
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4508973
Coefficient of variation (CV)2.4966115
Kurtosis50.418601
Mean0.98168949
Median Absolute Deviation (MAD)0
Skewness5.3865824
Sum6380
Variance6.0068977
MonotonicityNot monotonic
2024-05-11T15:07:17.558857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 4923
53.7%
3 299
 
3.3%
2 297
 
3.2%
5 273
 
3.0%
4 233
 
2.5%
1 215
 
2.3%
6 141
 
1.5%
7 30
 
0.3%
8 14
 
0.2%
10 11
 
0.1%
Other values (20) 63
 
0.7%
(Missing) 2675
29.2%
ValueCountFrequency (%)
0 4923
53.7%
1 215
 
2.3%
2 297
 
3.2%
3 299
 
3.3%
4 233
 
2.5%
5 273
 
3.0%
6 141
 
1.5%
7 30
 
0.3%
8 14
 
0.2%
9 7
 
0.1%
ValueCountFrequency (%)
45 1
 
< 0.1%
33 2
 
< 0.1%
31 2
 
< 0.1%
27 1
 
< 0.1%
26 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
21 1
 
< 0.1%
20 10
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing2954
Missing (%)32.2%
Infinite0
Infinite (%)0.0%
Mean0.23488746
Minimum0
Maximum16
Zeros5213
Zeros (%)56.8%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:17.728565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7248855
Coefficient of variation (CV)3.0860971
Kurtosis69.762945
Mean0.23488746
Median Absolute Deviation (MAD)0
Skewness6.4085379
Sum1461
Variance0.52545898
MonotonicityNot monotonic
2024-05-11T15:07:17.911344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 5213
56.8%
1 799
 
8.7%
2 112
 
1.2%
3 37
 
0.4%
4 21
 
0.2%
5 14
 
0.2%
6 11
 
0.1%
8 7
 
0.1%
7 5
 
0.1%
16 1
 
< 0.1%
(Missing) 2954
32.2%
ValueCountFrequency (%)
0 5213
56.8%
1 799
 
8.7%
2 112
 
1.2%
3 37
 
0.4%
4 21
 
0.2%
5 14
 
0.2%
6 11
 
0.1%
7 5
 
0.1%
8 7
 
0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
8 7
 
0.1%
7 5
 
0.1%
6 11
 
0.1%
5 14
 
0.2%
4 21
 
0.2%
3 37
 
0.4%
2 112
 
1.2%
1 799
 
8.7%
0 5213
56.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)0.5%
Missing5695
Missing (%)62.1%
Infinite0
Infinite (%)0.0%
Mean1.5113538
Minimum0
Maximum22
Zeros1148
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:18.123966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8210088
Coefficient of variation (CV)1.2048858
Kurtosis20.339923
Mean1.5113538
Median Absolute Deviation (MAD)1
Skewness3.1498092
Sum5258
Variance3.3160729
MonotonicityNot monotonic
2024-05-11T15:07:18.309212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 1148
 
12.5%
1 975
 
10.6%
2 632
 
6.9%
3 371
 
4.0%
4 162
 
1.8%
5 111
 
1.2%
6 25
 
0.3%
7 22
 
0.2%
9 7
 
0.1%
8 5
 
0.1%
Other values (8) 21
 
0.2%
(Missing) 5695
62.1%
ValueCountFrequency (%)
0 1148
12.5%
1 975
10.6%
2 632
6.9%
3 371
 
4.0%
4 162
 
1.8%
5 111
 
1.2%
6 25
 
0.3%
7 22
 
0.2%
8 5
 
0.1%
9 7
 
0.1%
ValueCountFrequency (%)
22 2
 
< 0.1%
19 1
 
< 0.1%
15 5
0.1%
14 4
< 0.1%
13 2
 
< 0.1%
12 2
 
< 0.1%
11 2
 
< 0.1%
10 3
< 0.1%
9 7
0.1%
8 5
0.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)0.6%
Missing5914
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean1.9503067
Minimum0
Maximum26
Zeros298
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:18.492503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile5
Maximum26
Range26
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7665146
Coefficient of variation (CV)0.90576242
Kurtosis31.827536
Mean1.9503067
Median Absolute Deviation (MAD)1
Skewness3.9532795
Sum6358
Variance3.1205737
MonotonicityNot monotonic
2024-05-11T15:07:18.727164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 1303
 
14.2%
2 852
 
9.3%
3 419
 
4.6%
0 298
 
3.2%
4 179
 
2.0%
5 121
 
1.3%
6 30
 
0.3%
7 23
 
0.3%
9 6
 
0.1%
10 6
 
0.1%
Other values (9) 23
 
0.3%
(Missing) 5914
64.5%
ValueCountFrequency (%)
0 298
 
3.2%
1 1303
14.2%
2 852
9.3%
3 419
 
4.6%
4 179
 
2.0%
5 121
 
1.3%
6 30
 
0.3%
7 23
 
0.3%
8 5
 
0.1%
9 6
 
0.1%
ValueCountFrequency (%)
26 1
 
< 0.1%
22 2
 
< 0.1%
19 1
 
< 0.1%
15 5
0.1%
14 3
< 0.1%
13 2
 
< 0.1%
12 2
 
< 0.1%
11 2
 
< 0.1%
10 6
0.1%
9 6
0.1%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
<NA>
7159 
0
1668 
1
 
310
2
 
32
3
 
5

Length

Max length4
Median length4
Mean length3.3410726
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7159
78.0%
0 1668
 
18.2%
1 310
 
3.4%
2 32
 
0.3%
3 5
 
0.1%

Length

2024-05-11T15:07:19.027810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:19.218372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7159
78.0%
0 1668
 
18.2%
1 310
 
3.4%
2 32
 
0.3%
3 5
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
<NA>
7980 
0
804 
1
 
349
2
 
35
3
 
5

Length

Max length4
Median length4
Mean length3.6095487
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> 7980
87.0%
0 804
 
8.8%
1 349
 
3.8%
2 35
 
0.4%
3 5
 
0.1%
6 1
 
< 0.1%

Length

2024-05-11T15:07:19.402982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:19.565911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7980
87.0%
0 804
 
8.8%
1 349
 
3.8%
2 35
 
0.4%
3 5
 
0.1%
6 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
0
5534 
<NA>
3640 

Length

Max length4
Median length1
Mean length2.1903205
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5534
60.3%
<NA> 3640
39.7%

Length

2024-05-11T15:07:19.742564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:19.859257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5534
60.3%
na 3640
39.7%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
0
5534 
<NA>
3640 

Length

Max length4
Median length1
Mean length2.1903205
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5534
60.3%
<NA> 3640
39.7%

Length

2024-05-11T15:07:20.010321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:20.166918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5534
60.3%
na 3640
39.7%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
0
5534 
<NA>
3640 

Length

Max length4
Median length1
Mean length2.1903205
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5534
60.3%
<NA> 3640
39.7%

Length

2024-05-11T15:07:20.305606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:20.443257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5534
60.3%
na 3640
39.7%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1948
Missing (%)21.2%
Memory size18.0 KiB
False
7221 
True
 
5
(Missing)
1948 
ValueCountFrequency (%)
False 7221
78.7%
True 5
 
0.1%
(Missing) 1948
 
21.2%
2024-05-11T15:07:20.594658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)0.6%
Missing2004
Missing (%)21.8%
Infinite0
Infinite (%)0.0%
Mean5.2899582
Minimum0
Maximum75
Zeros746
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:20.770878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median4
Q37
95-th percentile14
Maximum75
Range75
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.8535848
Coefficient of variation (CV)0.9175091
Kurtosis16.219165
Mean5.2899582
Median Absolute Deviation (MAD)2
Skewness2.855914
Sum37929
Variance23.557285
MonotonicityNot monotonic
2024-05-11T15:07:20.985743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
3 1319
14.4%
4 1140
12.4%
0 746
 
8.1%
2 687
 
7.5%
5 683
 
7.4%
6 629
 
6.9%
8 362
 
3.9%
7 297
 
3.2%
10 261
 
2.8%
9 179
 
2.0%
Other values (35) 867
9.5%
(Missing) 2004
21.8%
ValueCountFrequency (%)
0 746
8.1%
1 172
 
1.9%
2 687
7.5%
3 1319
14.4%
4 1140
12.4%
5 683
7.4%
6 629
6.9%
7 297
 
3.2%
8 362
 
3.9%
9 179
 
2.0%
ValueCountFrequency (%)
75 1
< 0.1%
52 1
< 0.1%
50 1
< 0.1%
48 1
< 0.1%
47 1
< 0.1%
45 1
< 0.1%
41 1
< 0.1%
38 1
< 0.1%
36 2
< 0.1%
35 2
< 0.1%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9174
Missing (%)100.0%
Memory size80.8 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
<NA>
7615 
임대
1541 
자가
 
18

Length

Max length4
Median length4
Mean length3.6601264
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> 7615
83.0%
임대 1541
 
16.8%
자가 18
 
0.2%

Length

2024-05-11T15:07:21.270718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:21.450898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7615
83.0%
임대 1541
 
16.8%
자가 18
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
0
4665 
<NA>
4509 

Length

Max length4
Median length1
Mean length2.4744931
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 (%)
0 4665
50.9%
<NA> 4509
49.1%

Length

2024-05-11T15:07:21.962178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:22.125082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4665
50.9%
na 4509
49.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing6729
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean0.024130879
Minimum0
Maximum8
Zeros2427
Zeros (%)26.5%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:22.256476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.34421587
Coefficient of variation (CV)14.264539
Kurtosis305.75502
Mean0.024130879
Median Absolute Deviation (MAD)0
Skewness16.888386
Sum59
Variance0.11848457
MonotonicityNot monotonic
2024-05-11T15:07:22.402947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 2427
 
26.5%
1 7
 
0.1%
6 4
 
< 0.1%
5 2
 
< 0.1%
3 2
 
< 0.1%
2 2
 
< 0.1%
8 1
 
< 0.1%
(Missing) 6729
73.3%
ValueCountFrequency (%)
0 2427
26.5%
1 7
 
0.1%
2 2
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
6 4
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 4
 
< 0.1%
5 2
 
< 0.1%
3 2
 
< 0.1%
2 2
 
< 0.1%
1 7
 
0.1%
0 2427
26.5%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
<NA>
6730 
0
2440 
1
 
2
2
 
2

Length

Max length4
Median length4
Mean length3.2007848
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> 6730
73.4%
0 2440
 
26.6%
1 2
 
< 0.1%
2 2
 
< 0.1%

Length

2024-05-11T15:07:22.606057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:22.758570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6730
73.4%
0 2440
 
26.6%
1 2
 
< 0.1%
2 2
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size71.8 KiB
<NA>
4831 
0
4343 

Length

Max length4
Median length4
Mean length2.5797907
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> 4831
52.7%
0 4343
47.3%

Length

2024-05-11T15:07:22.956283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:23.133155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4831
52.7%
0 4343
47.3%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)0.7%
Missing4857
Missing (%)52.9%
Infinite0
Infinite (%)0.0%
Mean1.6467454
Minimum0
Maximum46
Zeros2728
Zeros (%)29.7%
Negative0
Negative (%)0.0%
Memory size80.8 KiB
2024-05-11T15:07:23.316255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum46
Range46
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2692818
Coefficient of variation (CV)1.9852989
Kurtosis31.2706
Mean1.6467454
Median Absolute Deviation (MAD)0
Skewness4.1957925
Sum7109
Variance10.688204
MonotonicityNot monotonic
2024-05-11T15:07:23.597506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 2728
29.7%
2 299
 
3.3%
1 259
 
2.8%
3 252
 
2.7%
5 171
 
1.9%
4 163
 
1.8%
6 153
 
1.7%
7 86
 
0.9%
8 63
 
0.7%
10 37
 
0.4%
Other values (20) 106
 
1.2%
(Missing) 4857
52.9%
ValueCountFrequency (%)
0 2728
29.7%
1 259
 
2.8%
2 299
 
3.3%
3 252
 
2.7%
4 163
 
1.8%
5 171
 
1.9%
6 153
 
1.7%
7 86
 
0.9%
8 63
 
0.7%
9 27
 
0.3%
ValueCountFrequency (%)
46 1
 
< 0.1%
42 1
 
< 0.1%
35 3
< 0.1%
32 1
 
< 0.1%
31 2
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
24 1
 
< 0.1%
21 2
 
< 0.1%
20 6
0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1813
Missing (%)19.8%
Memory size18.0 KiB
False
7352 
True
 
9
(Missing)
1813 
ValueCountFrequency (%)
False 7352
80.1%
True 9
 
0.1%
(Missing) 1813
 
19.8%
2024-05-11T15:07:23.738037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032200003220000-204-1945-0083119451018<NA>3폐업2폐업19981014<NA><NA><NA>02 5551754106.02135878서울특별시 강남구 삼성동 152-62번지<NA><NA>고원혜구뜨2001-08-03 00:00:00I2018-08-31 23:59:59.0일반미용업204936.619944445301.34032미용업000<NA>0<NA>000N8<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132200003220000-204-1971-0181119710605<NA>3폐업2폐업20030219<NA><NA><NA><NA>14.72135190서울특별시 강남구 세곡동 118번지<NA><NA>새로나2003-02-27 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232200003220000-204-1974-0166719740205<NA>3폐업2폐업20000202<NA><NA><NA>020549014212.88135952서울특별시 강남구 청담동 50-2번지<NA><NA>킴스헤어라인2001-08-03 00:00:00I2018-08-31 23:59:59.0일반미용업204359.310905446886.095685미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332200003220000-204-1974-0187519740330<NA>3폐업2폐업20030224<NA><NA><NA>02 548328522.50135948서울특별시 강남구 청담동 4-9번지<NA><NA>윤희2003-02-27 00:00:00I2018-08-31 23:59:59.0일반미용업203862.95234446778.593985미용업3<NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432200003220000-204-1975-0187019750701<NA>3폐업2폐업19940622<NA><NA><NA>020543970530.00135887서울특별시 강남구 신사동 510-0번지<NA><NA>서지희2001-08-03 00:00:00I2018-08-31 23:59:59.0일반미용업201695.800641446231.505812미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532200003220000-204-1975-0187219750630<NA>3폐업2폐업19970224<NA><NA><NA>02 542385317.89135811서울특별시 강남구 논현동 13-16번지<NA><NA>제비꽃2002-03-14 00:00:00I2018-08-31 23:59:59.0일반미용업201913.141982445978.11223미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632200003220000-204-1976-0184819760302<NA>3폐업2폐업20000831<NA><NA><NA>020568745233.08135927서울특별시 강남구 역삼동 765-5번지<NA><NA>여성시대2003-02-07 00:00:00I2018-08-31 23:59:59.0일반미용업204499.478305443889.120499미용업000<NA>0<NA>000N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732200003220000-204-1976-0187319760416<NA>3폐업2폐업20120626<NA><NA><NA>02 543848216.50135816서울특별시 강남구 논현동 67-11번지서울특별시 강남구 도산대로30길 23 (논현동)6049수나2003-06-19 00:00:00I2018-08-31 23:59:59.0일반미용업202593.466926446245.710231미용업4<NA><NA>1<NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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