Overview

Dataset statistics

Number of variables47
Number of observations339
Missing cells3763
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory133.5 KiB
Average record size in memory403.4 B

Variable types

Categorical16
Text8
DateTime4
Unsupported6
Numeric11
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-17449/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
사용끝지하층 is highly imbalanced (55.9%)Imbalance
건물소유구분명 is highly imbalanced (57.5%)Imbalance
여성종사자수 is highly imbalanced (61.6%)Imbalance
남성종사자수 is highly imbalanced (61.6%)Imbalance
인허가취소일자 has 339 (100.0%) missing valuesMissing
폐업일자 has 127 (37.5%) missing valuesMissing
휴업시작일자 has 339 (100.0%) missing valuesMissing
휴업종료일자 has 339 (100.0%) missing valuesMissing
재개업일자 has 339 (100.0%) missing valuesMissing
전화번호 has 42 (12.4%) missing valuesMissing
도로명주소 has 128 (37.8%) missing valuesMissing
도로명우편번호 has 139 (41.0%) missing valuesMissing
좌표정보(X) has 12 (3.5%) missing valuesMissing
좌표정보(Y) has 12 (3.5%) missing valuesMissing
건물지상층수 has 101 (29.8%) missing valuesMissing
건물지하층수 has 102 (30.1%) missing valuesMissing
사용시작지상층 has 117 (34.5%) missing valuesMissing
사용끝지상층 has 212 (62.5%) missing valuesMissing
한실수 has 78 (23.0%) missing valuesMissing
양실수 has 52 (15.3%) missing valuesMissing
욕실수 has 81 (23.9%) missing valuesMissing
발한실여부 has 52 (15.3%) missing valuesMissing
좌석수 has 84 (24.8%) missing valuesMissing
조건부허가신고사유 has 338 (99.7%) missing valuesMissing
조건부허가시작일자 has 339 (100.0%) missing valuesMissing
조건부허가종료일자 has 339 (100.0%) missing valuesMissing
다중이용업소여부 has 52 (15.3%) 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
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 187 (55.2%) zerosZeros
건물지하층수 has 189 (55.8%) zerosZeros
사용시작지상층 has 152 (44.8%) zerosZeros
사용끝지상층 has 59 (17.4%) zerosZeros
한실수 has 148 (43.7%) zerosZeros
양실수 has 7 (2.1%) zerosZeros
욕실수 has 126 (37.2%) zerosZeros
좌석수 has 130 (38.3%) zerosZeros

Reproduction

Analysis started2024-04-29 19:19:26.303090
Analysis finished2024-04-29 19:19:27.287263
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3220000
339 

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 339
100.0%

Length

2024-04-30T04:19:27.361680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:27.458862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 339
100.0%

관리번호
Text

UNIQUE 

Distinct339
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:19:27.596266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7458
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

Unique339 ?
Unique (%)100.0%

Sample

1st row3220000-201-1972-00003
2nd row3220000-201-1974-00008
3rd row3220000-201-1975-00067
4th row3220000-201-1976-00006
5th row3220000-201-1976-00018
ValueCountFrequency (%)
3220000-201-1972-00003 1
 
0.3%
3220000-201-2003-00014 1
 
0.3%
3220000-201-2004-00003 1
 
0.3%
3220000-201-2004-00002 1
 
0.3%
3220000-201-2004-00001 1
 
0.3%
3220000-201-2003-00020 1
 
0.3%
3220000-201-2003-00019 1
 
0.3%
3220000-201-2003-00018 1
 
0.3%
3220000-201-2003-00017 1
 
0.3%
3220000-201-2003-00016 1
 
0.3%
Other values (329) 329
97.1%
2024-04-30T04:19:27.898838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3042
40.8%
2 1291
17.3%
- 1017
 
13.6%
1 808
 
10.8%
3 447
 
6.0%
9 275
 
3.7%
8 219
 
2.9%
7 106
 
1.4%
4 91
 
1.2%
6 86
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6441
86.4%
Dash Punctuation 1017
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3042
47.2%
2 1291
20.0%
1 808
 
12.5%
3 447
 
6.9%
9 275
 
4.3%
8 219
 
3.4%
7 106
 
1.6%
4 91
 
1.4%
6 86
 
1.3%
5 76
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1017
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3042
40.8%
2 1291
17.3%
- 1017
 
13.6%
1 808
 
10.8%
3 447
 
6.0%
9 275
 
3.7%
8 219
 
2.9%
7 106
 
1.4%
4 91
 
1.2%
6 86
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3042
40.8%
2 1291
17.3%
- 1017
 
13.6%
1 808
 
10.8%
3 447
 
6.0%
9 275
 
3.7%
8 219
 
2.9%
7 106
 
1.4%
4 91
 
1.2%
6 86
 
1.2%
Distinct323
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1972-11-17 00:00:00
Maximum2024-04-22 00:00:00
2024-04-30T04:19:28.047402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:19:28.156241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing339
Missing (%)100.0%
Memory size3.1 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
212 
1
127 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 212
62.5%
1 127
37.5%

Length

2024-04-30T04:19:28.267515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:28.343235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 212
62.5%
1 127
37.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
212 
영업/정상
127 

Length

Max length5
Median length2
Mean length3.1238938
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 212
62.5%
영업/정상 127
37.5%

Length

2024-04-30T04:19:28.442591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:28.533462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 212
62.5%
영업/정상 127
37.5%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2
212 
1
127 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 212
62.5%
1 127
37.5%

Length

2024-04-30T04:19:28.625299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:28.720788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 212
62.5%
1 127
37.5%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
212 
영업
127 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 212
62.5%
영업 127
37.5%

Length

2024-04-30T04:19:28.810133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:28.908837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 212
62.5%
영업 127
37.5%

폐업일자
Date

MISSING 

Distinct204
Distinct (%)96.2%
Missing127
Missing (%)37.5%
Memory size2.8 KiB
Minimum1987-09-15 00:00:00
Maximum2023-12-22 00:00:00
2024-04-30T04:19:29.002412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:19:29.116416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing339
Missing (%)100.0%
Memory size3.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing339
Missing (%)100.0%
Memory size3.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing339
Missing (%)100.0%
Memory size3.1 KiB

전화번호
Text

MISSING 

Distinct286
Distinct (%)96.3%
Missing42
Missing (%)12.4%
Memory size2.8 KiB
2024-04-30T04:19:29.349291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.23569
Min length7

Characters and Unicode

Total characters3040
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

Unique275 ?
Unique (%)92.6%

Sample

1st row0234630462
2nd row0205676817
3rd row0205681188
4th row02 5432183
5th row02 5421511
ValueCountFrequency (%)
02 204
38.2%
569 4
 
0.7%
8371 2
 
0.4%
5435512 2
 
0.4%
5498240 2
 
0.4%
557 2
 
0.4%
5625401 2
 
0.4%
568 2
 
0.4%
5381491 2
 
0.4%
5427177 2
 
0.4%
Other values (303) 310
58.1%
2024-04-30T04:19:29.684916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 559
18.4%
2 506
16.6%
5 484
15.9%
276
9.1%
4 227
7.5%
1 224
7.4%
6 213
 
7.0%
3 184
 
6.1%
8 136
 
4.5%
7 129
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2764
90.9%
Space Separator 276
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 559
20.2%
2 506
18.3%
5 484
17.5%
4 227
8.2%
1 224
8.1%
6 213
 
7.7%
3 184
 
6.7%
8 136
 
4.9%
7 129
 
4.7%
9 102
 
3.7%
Space Separator
ValueCountFrequency (%)
276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3040
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 559
18.4%
2 506
16.6%
5 484
15.9%
276
9.1%
4 227
7.5%
1 224
7.4%
6 213
 
7.0%
3 184
 
6.1%
8 136
 
4.5%
7 129
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 559
18.4%
2 506
16.6%
5 484
15.9%
276
9.1%
4 227
7.5%
1 224
7.4%
6 213
 
7.0%
3 184
 
6.1%
8 136
 
4.5%
7 129
 
4.2%
Distinct323
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:19:29.954390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.8348083
Min length3

Characters and Unicode

Total characters2317
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

Unique314 ?
Unique (%)92.6%

Sample

1st row.00
2nd row102.53
3rd row406.98
4th row183.19
5th row150.80
ValueCountFrequency (%)
00 9
 
2.7%
929.98 2
 
0.6%
6,224.92 2
 
0.6%
1,996.00 2
 
0.6%
1,622.88 2
 
0.6%
1,584.10 2
 
0.6%
3,383.00 2
 
0.6%
1,788.00 2
 
0.6%
1,100.00 2
 
0.6%
9,542.00 1
 
0.3%
Other values (313) 313
92.3%
2024-04-30T04:19:30.370186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 339
14.6%
0 307
13.2%
1 246
10.6%
2 189
8.2%
9 184
7.9%
4 173
7.5%
6 159
6.9%
7 152
6.6%
8 152
6.6%
3 144
6.2%
Other values (2) 272
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1841
79.5%
Other Punctuation 476
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 307
16.7%
1 246
13.4%
2 189
10.3%
9 184
10.0%
4 173
9.4%
6 159
8.6%
7 152
8.3%
8 152
8.3%
3 144
7.8%
5 135
7.3%
Other Punctuation
ValueCountFrequency (%)
. 339
71.2%
, 137
28.8%

Most occurring scripts

ValueCountFrequency (%)
Common 2317
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 339
14.6%
0 307
13.2%
1 246
10.6%
2 189
8.2%
9 184
7.9%
4 173
7.5%
6 159
6.9%
7 152
6.6%
8 152
6.6%
3 144
6.2%
Other values (2) 272
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2317
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 339
14.6%
0 307
13.2%
1 246
10.6%
2 189
8.2%
9 184
7.9%
4 173
7.5%
6 159
6.9%
7 152
6.6%
8 152
6.6%
3 144
6.2%
Other values (2) 272
11.7%
Distinct100
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:19:30.684378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0943953
Min length6

Characters and Unicode

Total characters2066
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

Unique51 ?
Unique (%)15.0%

Sample

1st row135860
2nd row135509
3rd row135928
4th row135-513
5th row135811
ValueCountFrequency (%)
135920 39
 
11.5%
135915 39
 
11.5%
135876 18
 
5.3%
135877 16
 
4.7%
135830 10
 
2.9%
135934 9
 
2.7%
135935 9
 
2.7%
135957 8
 
2.4%
135887 7
 
2.1%
135907 7
 
2.1%
Other values (90) 177
52.2%
2024-04-30T04:19:31.183434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 445
21.5%
1 443
21.4%
3 416
20.1%
9 219
10.6%
8 155
 
7.5%
0 110
 
5.3%
7 92
 
4.5%
2 87
 
4.2%
6 37
 
1.8%
- 32
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2034
98.5%
Dash Punctuation 32
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 445
21.9%
1 443
21.8%
3 416
20.5%
9 219
10.8%
8 155
 
7.6%
0 110
 
5.4%
7 92
 
4.5%
2 87
 
4.3%
6 37
 
1.8%
4 30
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2066
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 445
21.5%
1 443
21.4%
3 416
20.1%
9 219
10.6%
8 155
 
7.5%
0 110
 
5.3%
7 92
 
4.5%
2 87
 
4.2%
6 37
 
1.8%
- 32
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 445
21.5%
1 443
21.4%
3 416
20.1%
9 219
10.6%
8 155
 
7.5%
0 110
 
5.3%
7 92
 
4.5%
2 87
 
4.2%
6 37
 
1.8%
- 32
 
1.5%
Distinct321
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:19:31.604034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length23.126844
Min length16

Characters and Unicode

Total characters7840
Distinct characters126
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique305 ?
Unique (%)90.0%

Sample

1st row서울특별시 강남구 도곡동 956-11번지
2nd row서울특별시 강남구 삼성동 115-28번지
3rd row서울특별시 강남구 역삼동 779-5번지
4th row서울특별시 강남구 역삼동 700-27
5th row서울특별시 강남구 논현동 4-0번지
ValueCountFrequency (%)
서울특별시 338
23.5%
강남구 338
23.5%
역삼동 167
 
11.6%
삼성동 65
 
4.5%
논현동 45
 
3.1%
신사동 26
 
1.8%
청담동 18
 
1.3%
대치동 12
 
0.8%
호텔 4
 
0.3%
678-19번지 3
 
0.2%
Other values (379) 420
29.2%
2024-04-30T04:19:32.286755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1384
17.7%
341
 
4.3%
340
 
4.3%
340
 
4.3%
340
 
4.3%
340
 
4.3%
339
 
4.3%
338
 
4.3%
338
 
4.3%
338
 
4.3%
Other values (116) 3402
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4430
56.5%
Decimal Number 1614
 
20.6%
Space Separator 1384
 
17.7%
Dash Punctuation 326
 
4.2%
Other Punctuation 39
 
0.5%
Uppercase Letter 19
 
0.2%
Math Symbol 15
 
0.2%
Lowercase Letter 5
 
0.1%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
341
 
7.7%
340
 
7.7%
340
 
7.7%
340
 
7.7%
340
 
7.7%
339
 
7.7%
338
 
7.6%
338
 
7.6%
338
 
7.6%
260
 
5.9%
Other values (85) 1116
25.2%
Decimal Number
ValueCountFrequency (%)
1 327
20.3%
2 236
14.6%
7 185
11.5%
6 166
10.3%
8 141
8.7%
4 135
8.4%
3 120
 
7.4%
0 105
 
6.5%
5 101
 
6.3%
9 98
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
E 4
21.1%
H 3
15.8%
L 3
15.8%
O 3
15.8%
T 2
10.5%
F 1
 
5.3%
R 1
 
5.3%
A 1
 
5.3%
S 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
20.0%
f 1
20.0%
o 1
20.0%
l 1
20.0%
a 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 37
94.9%
. 2
 
5.1%
Space Separator
ValueCountFrequency (%)
1384
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 326
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4430
56.5%
Common 3386
43.2%
Latin 24
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
341
 
7.7%
340
 
7.7%
340
 
7.7%
340
 
7.7%
340
 
7.7%
339
 
7.7%
338
 
7.6%
338
 
7.6%
338
 
7.6%
260
 
5.9%
Other values (85) 1116
25.2%
Common
ValueCountFrequency (%)
1384
40.9%
1 327
 
9.7%
- 326
 
9.6%
2 236
 
7.0%
7 185
 
5.5%
6 166
 
4.9%
8 141
 
4.2%
4 135
 
4.0%
3 120
 
3.5%
0 105
 
3.1%
Other values (7) 261
 
7.7%
Latin
ValueCountFrequency (%)
E 4
16.7%
H 3
12.5%
L 3
12.5%
O 3
12.5%
T 2
8.3%
F 1
 
4.2%
R 1
 
4.2%
A 1
 
4.2%
S 1
 
4.2%
t 1
 
4.2%
Other values (4) 4
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4430
56.5%
ASCII 3410
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1384
40.6%
1 327
 
9.6%
- 326
 
9.6%
2 236
 
6.9%
7 185
 
5.4%
6 166
 
4.9%
8 141
 
4.1%
4 135
 
4.0%
3 120
 
3.5%
0 105
 
3.1%
Other values (21) 285
 
8.4%
Hangul
ValueCountFrequency (%)
341
 
7.7%
340
 
7.7%
340
 
7.7%
340
 
7.7%
340
 
7.7%
339
 
7.7%
338
 
7.6%
338
 
7.6%
338
 
7.6%
260
 
5.9%
Other values (85) 1116
25.2%

도로명주소
Text

MISSING 

Distinct209
Distinct (%)99.1%
Missing128
Missing (%)37.8%
Memory size2.8 KiB
2024-04-30T04:19:32.632787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length51
Mean length30.64455
Min length23

Characters and Unicode

Total characters6466
Distinct characters155
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)98.1%

Sample

1st row서울특별시 강남구 언주로94길 13 (역삼동)
2nd row서울특별시 강남구 학동로 141 (논현동)
3rd row서울특별시 강남구 언주로87길 41 (역삼동)
4th row서울특별시 강남구 봉은사로 442 (삼성동)
5th row서울특별시 강남구 테헤란로2길 33 (역삼동)
ValueCountFrequency (%)
서울특별시 210
17.8%
강남구 210
17.8%
역삼동 93
 
7.9%
삼성동 37
 
3.1%
논현동 28
 
2.4%
봉은사로 23
 
2.0%
신사동 16
 
1.4%
도산대로 14
 
1.2%
논현로 13
 
1.1%
언주로87길 11
 
0.9%
Other values (340) 524
44.4%
2024-04-30T04:19:33.003922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
968
 
15.0%
1 237
 
3.7%
230
 
3.6%
229
 
3.5%
227
 
3.5%
( 215
 
3.3%
) 215
 
3.3%
213
 
3.3%
212
 
3.3%
212
 
3.3%
Other values (145) 3508
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3696
57.2%
Decimal Number 1056
 
16.3%
Space Separator 968
 
15.0%
Open Punctuation 215
 
3.3%
Close Punctuation 215
 
3.3%
Other Punctuation 180
 
2.8%
Math Symbol 56
 
0.9%
Dash Punctuation 42
 
0.6%
Uppercase Letter 33
 
0.5%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
230
 
6.2%
229
 
6.2%
227
 
6.1%
213
 
5.8%
212
 
5.7%
212
 
5.7%
211
 
5.7%
211
 
5.7%
210
 
5.7%
210
 
5.7%
Other values (109) 1531
41.4%
Uppercase Letter
ValueCountFrequency (%)
L 5
15.2%
E 5
15.2%
T 4
12.1%
H 4
12.1%
O 4
12.1%
A 2
 
6.1%
S 2
 
6.1%
F 1
 
3.0%
R 1
 
3.0%
X 1
 
3.0%
Other values (4) 4
12.1%
Decimal Number
ValueCountFrequency (%)
1 237
22.4%
3 156
14.8%
2 137
13.0%
7 87
 
8.2%
4 86
 
8.1%
6 83
 
7.9%
5 78
 
7.4%
8 73
 
6.9%
0 61
 
5.8%
9 58
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
a 1
20.0%
l 1
20.0%
o 1
20.0%
f 1
20.0%
t 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 178
98.9%
. 2
 
1.1%
Space Separator
ValueCountFrequency (%)
968
100.0%
Open Punctuation
ValueCountFrequency (%)
( 215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 215
100.0%
Math Symbol
ValueCountFrequency (%)
~ 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3696
57.2%
Common 2732
42.3%
Latin 38
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
230
 
6.2%
229
 
6.2%
227
 
6.1%
213
 
5.8%
212
 
5.7%
212
 
5.7%
211
 
5.7%
211
 
5.7%
210
 
5.7%
210
 
5.7%
Other values (109) 1531
41.4%
Latin
ValueCountFrequency (%)
L 5
13.2%
E 5
13.2%
T 4
10.5%
H 4
10.5%
O 4
10.5%
A 2
 
5.3%
S 2
 
5.3%
F 1
 
2.6%
R 1
 
2.6%
X 1
 
2.6%
Other values (9) 9
23.7%
Common
ValueCountFrequency (%)
968
35.4%
1 237
 
8.7%
( 215
 
7.9%
) 215
 
7.9%
, 178
 
6.5%
3 156
 
5.7%
2 137
 
5.0%
7 87
 
3.2%
4 86
 
3.1%
6 83
 
3.0%
Other values (7) 370
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3696
57.2%
ASCII 2770
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
968
34.9%
1 237
 
8.6%
( 215
 
7.8%
) 215
 
7.8%
, 178
 
6.4%
3 156
 
5.6%
2 137
 
4.9%
7 87
 
3.1%
4 86
 
3.1%
6 83
 
3.0%
Other values (26) 408
14.7%
Hangul
ValueCountFrequency (%)
230
 
6.2%
229
 
6.2%
227
 
6.1%
213
 
5.8%
212
 
5.7%
212
 
5.7%
211
 
5.7%
211
 
5.7%
210
 
5.7%
210
 
5.7%
Other values (109) 1531
41.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct80
Distinct (%)40.0%
Missing139
Missing (%)41.0%
Infinite0
Infinite (%)0.0%
Mean6379.175
Minimum6016
Maximum52691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:33.122081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6016
5-th percentile6033.95
Q16116
median6142
Q36199.25
95-th percentile6241
Maximum52691
Range46675
Interquartile range (IQR)83.25

Descriptive statistics

Standard deviation3291.8283
Coefficient of variation (CV)0.51602727
Kurtosis199.8442
Mean6379.175
Median Absolute Deviation (MAD)43.5
Skewness14.133912
Sum1275835
Variance10836133
MonotonicityNot monotonic
2024-04-30T04:19:33.230194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6221 16
 
4.7%
6142 14
 
4.1%
6220 10
 
2.9%
6160 8
 
2.4%
6141 7
 
2.1%
6159 6
 
1.8%
6134 5
 
1.5%
6158 5
 
1.5%
6193 5
 
1.5%
6125 5
 
1.5%
Other values (70) 119
35.1%
(Missing) 139
41.0%
ValueCountFrequency (%)
6016 1
 
0.3%
6017 1
 
0.3%
6022 2
0.6%
6026 2
0.6%
6027 3
0.9%
6033 1
 
0.3%
6034 1
 
0.3%
6035 4
1.2%
6037 1
 
0.3%
6040 3
0.9%
ValueCountFrequency (%)
52691 1
 
0.3%
6307 2
0.6%
6272 1
 
0.3%
6249 1
 
0.3%
6242 2
0.6%
6241 4
1.2%
6236 2
0.6%
6235 1
 
0.3%
6234 2
0.6%
6233 1
 
0.3%
Distinct332
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:19:33.418308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length6.4365782
Min length1

Characters and Unicode

Total characters2182
Distinct characters319
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

Unique325 ?
Unique (%)95.9%

Sample

1st row대동여인숙
2nd row삼성여관
3rd row삼보여관
4th row블랑호텔 강남점
5th row삼부
ValueCountFrequency (%)
호텔 22
 
4.7%
서울 9
 
1.9%
강남 8
 
1.7%
hotel 6
 
1.3%
모텔 5
 
1.1%
역삼 5
 
1.1%
부띠끄 3
 
0.6%
2
 
0.4%
호텔스타 2
 
0.4%
호텔리베라 2
 
0.4%
Other values (382) 400
86.2%
2024-04-30T04:19:33.752129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
8.1%
142
 
6.5%
125
 
5.7%
75
 
3.4%
60
 
2.7%
53
 
2.4%
51
 
2.3%
46
 
2.1%
45
 
2.1%
37
 
1.7%
Other values (309) 1372
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1750
80.2%
Uppercase Letter 139
 
6.4%
Space Separator 125
 
5.7%
Lowercase Letter 103
 
4.7%
Open Punctuation 28
 
1.3%
Close Punctuation 28
 
1.3%
Decimal Number 8
 
0.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
176
 
10.1%
142
 
8.1%
75
 
4.3%
60
 
3.4%
53
 
3.0%
51
 
2.9%
46
 
2.6%
45
 
2.6%
37
 
2.1%
35
 
2.0%
Other values (255) 1030
58.9%
Uppercase Letter
ValueCountFrequency (%)
L 18
12.9%
H 15
10.8%
O 14
10.1%
E 14
10.1%
A 12
8.6%
T 12
8.6%
N 11
7.9%
M 7
 
5.0%
G 5
 
3.6%
I 4
 
2.9%
Other values (13) 27
19.4%
Lowercase Letter
ValueCountFrequency (%)
a 14
13.6%
e 14
13.6%
o 12
11.7%
t 11
10.7%
l 11
10.7%
n 10
9.7%
m 4
 
3.9%
u 4
 
3.9%
s 3
 
2.9%
c 3
 
2.9%
Other values (11) 17
16.5%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
7 2
25.0%
2 1
12.5%
8 1
12.5%
4 1
12.5%
6 1
12.5%
Space Separator
ValueCountFrequency (%)
125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1750
80.2%
Latin 242
 
11.1%
Common 190
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
176
 
10.1%
142
 
8.1%
75
 
4.3%
60
 
3.4%
53
 
3.0%
51
 
2.9%
46
 
2.6%
45
 
2.6%
37
 
2.1%
35
 
2.0%
Other values (255) 1030
58.9%
Latin
ValueCountFrequency (%)
L 18
 
7.4%
H 15
 
6.2%
a 14
 
5.8%
e 14
 
5.8%
O 14
 
5.8%
E 14
 
5.8%
o 12
 
5.0%
A 12
 
5.0%
T 12
 
5.0%
N 11
 
4.5%
Other values (34) 106
43.8%
Common
ValueCountFrequency (%)
125
65.8%
( 28
 
14.7%
) 28
 
14.7%
1 2
 
1.1%
7 2
 
1.1%
2 1
 
0.5%
8 1
 
0.5%
4 1
 
0.5%
6 1
 
0.5%
: 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1750
80.2%
ASCII 432
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
176
 
10.1%
142
 
8.1%
75
 
4.3%
60
 
3.4%
53
 
3.0%
51
 
2.9%
46
 
2.6%
45
 
2.6%
37
 
2.1%
35
 
2.0%
Other values (255) 1030
58.9%
ASCII
ValueCountFrequency (%)
125
28.9%
( 28
 
6.5%
) 28
 
6.5%
L 18
 
4.2%
H 15
 
3.5%
a 14
 
3.2%
e 14
 
3.2%
O 14
 
3.2%
E 14
 
3.2%
o 12
 
2.8%
Other values (44) 150
34.7%
Distinct288
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1999-01-25 00:00:00
Maximum2024-04-22 16:43:47
2024-04-30T04:19:33.879404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:19:34.210497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
I
208 
U
131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 208
61.4%
U 131
38.6%

Length

2024-04-30T04:19:34.337831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:34.418490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 208
61.4%
u 131
38.6%
Distinct120
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:07:00
2024-04-30T04:19:34.499825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:19:34.610781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
여관업
195 
관광호텔
82 
일반호텔
42 
숙박업 기타
 
9
숙박업(생활)
 
9

Length

Max length7
Median length3
Mean length3.5575221
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여인숙업
2nd row여관업
3rd row여관업
4th row여관업
5th row여관업

Common Values

ValueCountFrequency (%)
여관업 195
57.5%
관광호텔 82
24.2%
일반호텔 42
 
12.4%
숙박업 기타 9
 
2.7%
숙박업(생활) 9
 
2.7%
여인숙업 2
 
0.6%

Length

2024-04-30T04:19:34.725544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:34.819763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 195
56.0%
관광호텔 82
23.6%
일반호텔 42
 
12.1%
숙박업 9
 
2.6%
기타 9
 
2.6%
숙박업(생활 9
 
2.6%
여인숙업 2
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct271
Distinct (%)82.9%
Missing12
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean203802.78
Minimum201604.24
Maximum298528.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:34.937026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201604.24
5-th percentile202160.2
Q1202796.43
median203467
Q3204273.92
95-th percentile204930.16
Maximum298528.21
Range96923.971
Interquartile range (IQR)1477.4885

Descriptive statistics

Standard deviation5331.1266
Coefficient of variation (CV)0.026158262
Kurtosis308.40859
Mean203802.78
Median Absolute Deviation (MAD)745.76768
Skewness17.309737
Sum66643509
Variance28420911
MonotonicityNot monotonic
2024-04-30T04:19:35.056731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203376.74844496 4
 
1.2%
203475.825 3
 
0.9%
204802.926536616 3
 
0.9%
203538.217965992 3
 
0.9%
203362.056528557 3
 
0.9%
204801.754078438 2
 
0.6%
203222.796248226 2
 
0.6%
203651.669007478 2
 
0.6%
204512.989866326 2
 
0.6%
203513.292326829 2
 
0.6%
Other values (261) 301
88.8%
(Missing) 12
 
3.5%
ValueCountFrequency (%)
201604.241620989 1
0.3%
201622.864515589 1
0.3%
201658.416590861 1
0.3%
201664.929814711 1
0.3%
201684.704785227 1
0.3%
201746.195 1
0.3%
201760.330897849 1
0.3%
201794.185260037 1
0.3%
201828.756638827 2
0.6%
201887.115904979 1
0.3%
ValueCountFrequency (%)
298528.212207139 1
0.3%
205747.294111221 1
0.3%
205743.762485994 1
0.3%
205706.475554939 1
0.3%
205636.367492511 1
0.3%
205613.224315917 1
0.3%
205601.904041677 1
0.3%
205513.023202982 1
0.3%
205314.159889285 1
0.3%
205259.527550336 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct271
Distinct (%)82.9%
Missing12
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean444182.14
Minimum188532.76
Maximum447241.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:35.187653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188532.76
5-th percentile443757.55
Q1444368.34
median444780.03
Q3445539.48
95-th percentile446743.56
Maximum447241.37
Range258708.6
Interquartile range (IQR)1171.144

Descriptive statistics

Standard deviation14210.527
Coefficient of variation (CV)0.031992568
Kurtosis324.24812
Mean444182.14
Median Absolute Deviation (MAD)448.90287
Skewness-17.969143
Sum1.4524756 × 108
Variance2.0193908 × 108
MonotonicityNot monotonic
2024-04-30T04:19:35.317060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444292.694242741 4
 
1.2%
444490.505 3
 
0.9%
446693.113699792 3
 
0.9%
444359.109028978 3
 
0.9%
444460.672759185 3
 
0.9%
445016.79397056 2
 
0.6%
445181.486645117 2
 
0.6%
444353.684205677 2
 
0.6%
444870.810346312 2
 
0.6%
444331.1321281 2
 
0.6%
Other values (261) 301
88.8%
(Missing) 12
 
3.5%
ValueCountFrequency (%)
188532.761660312 1
0.3%
441557.179656218 1
0.3%
441630.077624843 1
0.3%
442604.49302286 1
0.3%
443133.151522752 1
0.3%
443388.162252888 1
0.3%
443532.620370528 1
0.3%
443541.255900807 1
0.3%
443557.30252734 1
0.3%
443603.819630338 1
0.3%
ValueCountFrequency (%)
447241.365471181 1
0.3%
447231.954885143 1
0.3%
447092.815391301 2
0.6%
447041.788168808 1
0.3%
447020.420866992 1
0.3%
447007.159051064 1
0.3%
446928.436357824 1
0.3%
446902.21027213 1
0.3%
446895.028902481 1
0.3%
446867.588235408 1
0.3%

위생업태명
Categorical

Distinct7
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
여관업
174 
관광호텔
61 
<NA>
52 
일반호텔
38 
숙박업 기타
 
7
Other values (2)
 
7

Length

Max length7
Median length3
Mean length3.5722714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 174
51.3%
관광호텔 61
 
18.0%
<NA> 52
 
15.3%
일반호텔 38
 
11.2%
숙박업 기타 7
 
2.1%
숙박업(생활) 5
 
1.5%
여인숙업 2
 
0.6%

Length

2024-04-30T04:19:35.461294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:35.562599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 174
50.3%
관광호텔 61
 
17.6%
na 52
 
15.0%
일반호텔 38
 
11.0%
숙박업 7
 
2.0%
기타 7
 
2.0%
숙박업(생활 5
 
1.4%
여인숙업 2
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)5.0%
Missing101
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean1.7352941
Minimum0
Maximum19
Zeros187
Zeros (%)55.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:35.661418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.6781505
Coefficient of variation (CV)2.1196122
Kurtosis3.5838106
Mean1.7352941
Median Absolute Deviation (MAD)0
Skewness2.0926216
Sum413
Variance13.528791
MonotonicityNot monotonic
2024-04-30T04:19:35.771525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 187
55.2%
5 9
 
2.7%
4 9
 
2.7%
10 9
 
2.7%
9 6
 
1.8%
11 6
 
1.8%
6 3
 
0.9%
14 3
 
0.9%
8 3
 
0.9%
7 1
 
0.3%
Other values (2) 2
 
0.6%
(Missing) 101
29.8%
ValueCountFrequency (%)
0 187
55.2%
4 9
 
2.7%
5 9
 
2.7%
6 3
 
0.9%
7 1
 
0.3%
8 3
 
0.9%
9 6
 
1.8%
10 9
 
2.7%
11 6
 
1.8%
12 1
 
0.3%
ValueCountFrequency (%)
19 1
 
0.3%
14 3
 
0.9%
12 1
 
0.3%
11 6
1.8%
10 9
2.7%
9 6
1.8%
8 3
 
0.9%
7 1
 
0.3%
6 3
 
0.9%
5 9
2.7%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.5%
Missing102
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean0.32911392
Minimum0
Maximum6
Zeros189
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:35.883762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.82935832
Coefficient of variation (CV)2.5199734
Kurtosis17.47617
Mean0.32911392
Median Absolute Deviation (MAD)0
Skewness3.72512
Sum78
Variance0.68783523
MonotonicityNot monotonic
2024-04-30T04:19:35.971315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 189
55.8%
1 31
 
9.1%
2 11
 
3.2%
3 3
 
0.9%
5 2
 
0.6%
6 1
 
0.3%
(Missing) 102
30.1%
ValueCountFrequency (%)
0 189
55.8%
1 31
 
9.1%
2 11
 
3.2%
3 3
 
0.9%
5 2
 
0.6%
6 1
 
0.3%
ValueCountFrequency (%)
6 1
 
0.3%
5 2
 
0.6%
3 3
 
0.9%
2 11
 
3.2%
1 31
 
9.1%
0 189
55.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)5.0%
Missing117
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean0.92792793
Minimum0
Maximum19
Zeros152
Zeros (%)44.8%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:36.078959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum19
Range19
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1152825
Coefficient of variation (CV)2.2795763
Kurtosis27.006948
Mean0.92792793
Median Absolute Deviation (MAD)0
Skewness4.3244342
Sum206
Variance4.4744201
MonotonicityNot monotonic
2024-04-30T04:19:36.179187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 152
44.8%
1 27
 
8.0%
2 12
 
3.5%
3 12
 
3.5%
4 10
 
2.9%
9 2
 
0.6%
8 2
 
0.6%
5 2
 
0.6%
10 1
 
0.3%
6 1
 
0.3%
(Missing) 117
34.5%
ValueCountFrequency (%)
0 152
44.8%
1 27
 
8.0%
2 12
 
3.5%
3 12
 
3.5%
4 10
 
2.9%
5 2
 
0.6%
6 1
 
0.3%
8 2
 
0.6%
9 2
 
0.6%
10 1
 
0.3%
ValueCountFrequency (%)
19 1
 
0.3%
10 1
 
0.3%
9 2
 
0.6%
8 2
 
0.6%
6 1
 
0.3%
5 2
 
0.6%
4 10
 
2.9%
3 12
3.5%
2 12
3.5%
1 27
8.0%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)12.6%
Missing212
Missing (%)62.5%
Infinite0
Infinite (%)0.0%
Mean4.8188976
Minimum0
Maximum19
Zeros59
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:36.287159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q310
95-th percentile15.7
Maximum19
Range19
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.4922995
Coefficient of variation (CV)1.1397419
Kurtosis-0.535868
Mean4.8188976
Median Absolute Deviation (MAD)4
Skewness0.80202043
Sum612
Variance30.165354
MonotonicityNot monotonic
2024-04-30T04:19:36.424558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 59
 
17.4%
10 14
 
4.1%
4 10
 
2.9%
5 8
 
2.4%
9 5
 
1.5%
14 5
 
1.5%
6 5
 
1.5%
11 4
 
1.2%
8 4
 
1.2%
17 3
 
0.9%
Other values (6) 10
 
2.9%
(Missing) 212
62.5%
ValueCountFrequency (%)
0 59
17.4%
3 3
 
0.9%
4 10
 
2.9%
5 8
 
2.4%
6 5
 
1.5%
8 4
 
1.2%
9 5
 
1.5%
10 14
 
4.1%
11 4
 
1.2%
12 1
 
0.3%
ValueCountFrequency (%)
19 1
 
0.3%
18 1
 
0.3%
17 3
 
0.9%
16 2
 
0.6%
15 2
 
0.6%
14 5
 
1.5%
12 1
 
0.3%
11 4
 
1.2%
10 14
4.1%
9 5
 
1.5%
Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
186 
<NA>
142 
1
 
10
2
 
1

Length

Max length4
Median length1
Mean length2.2566372
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 186
54.9%
<NA> 142
41.9%
1 10
 
2.9%
2 1
 
0.3%

Length

2024-04-30T04:19:36.542148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:36.652707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 186
54.9%
na 142
41.9%
1 10
 
2.9%
2 1
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
239 
0
92 
1
 
5
2
 
2
9
 
1

Length

Max length4
Median length4
Mean length3.1150442
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 239
70.5%
0 92
 
27.1%
1 5
 
1.5%
2 2
 
0.6%
9 1
 
0.3%

Length

2024-04-30T04:19:36.752704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:36.851439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
70.5%
0 92
 
27.1%
1 5
 
1.5%
2 2
 
0.6%
9 1
 
0.3%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)8.4%
Missing78
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean4.7279693
Minimum0
Maximum303
Zeros148
Zeros (%)43.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:36.955647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile15
Maximum303
Range303
Interquartile range (IQR)6

Descriptive statistics

Standard deviation19.368659
Coefficient of variation (CV)4.0966126
Kurtosis218.39694
Mean4.7279693
Median Absolute Deviation (MAD)0
Skewness14.197011
Sum1234
Variance375.14495
MonotonicityNot monotonic
2024-04-30T04:19:37.061919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 148
43.7%
10 12
 
3.5%
6 12
 
3.5%
3 11
 
3.2%
9 9
 
2.7%
4 9
 
2.7%
12 8
 
2.4%
7 8
 
2.4%
8 8
 
2.4%
2 6
 
1.8%
Other values (12) 30
 
8.8%
(Missing) 78
23.0%
ValueCountFrequency (%)
0 148
43.7%
1 5
 
1.5%
2 6
 
1.8%
3 11
 
3.2%
4 9
 
2.7%
5 5
 
1.5%
6 12
 
3.5%
7 8
 
2.4%
8 8
 
2.4%
9 9
 
2.7%
ValueCountFrequency (%)
303 1
 
0.3%
41 1
 
0.3%
27 1
 
0.3%
25 1
 
0.3%
21 1
 
0.3%
18 4
1.2%
17 1
 
0.3%
16 2
 
0.6%
15 2
 
0.6%
12 8
2.4%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct87
Distinct (%)30.3%
Missing52
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean51.348432
Minimum0
Maximum600
Zeros7
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:37.182919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.3
Q120
median29
Q344.5
95-th percentile195.7
Maximum600
Range600
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation75.724361
Coefficient of variation (CV)1.4747161
Kurtosis21.252919
Mean51.348432
Median Absolute Deviation (MAD)11
Skewness4.1913067
Sum14737
Variance5734.1789
MonotonicityNot monotonic
2024-04-30T04:19:37.327125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 15
 
4.4%
18 15
 
4.4%
24 11
 
3.2%
27 8
 
2.4%
42 8
 
2.4%
21 8
 
2.4%
33 8
 
2.4%
25 8
 
2.4%
40 8
 
2.4%
28 8
 
2.4%
Other values (77) 190
56.0%
(Missing) 52
 
15.3%
ValueCountFrequency (%)
0 7
2.1%
3 1
 
0.3%
5 1
 
0.3%
7 2
 
0.6%
9 1
 
0.3%
10 3
0.9%
11 3
0.9%
12 3
0.9%
13 3
0.9%
14 7
2.1%
ValueCountFrequency (%)
600 1
0.3%
546 1
0.3%
496 1
0.3%
330 2
0.6%
313 1
0.3%
309 1
0.3%
288 1
0.3%
281 1
0.3%
246 1
0.3%
241 1
0.3%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct51
Distinct (%)19.8%
Missing81
Missing (%)23.9%
Infinite0
Infinite (%)0.0%
Mean21.957364
Minimum0
Maximum546
Zeros126
Zeros (%)37.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:37.462246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11.5
Q330.75
95-th percentile54.15
Maximum546
Range546
Interquartile range (IQR)30.75

Descriptive statistics

Standard deviation51.430832
Coefficient of variation (CV)2.3423044
Kurtosis71.408713
Mean21.957364
Median Absolute Deviation (MAD)11.5
Skewness7.740524
Sum5665
Variance2645.1305
MonotonicityNot monotonic
2024-04-30T04:19:37.598165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 126
37.2%
24 11
 
3.2%
27 9
 
2.7%
30 7
 
2.1%
36 6
 
1.8%
32 5
 
1.5%
45 5
 
1.5%
29 5
 
1.5%
21 4
 
1.2%
33 4
 
1.2%
Other values (41) 76
22.4%
(Missing) 81
23.9%
ValueCountFrequency (%)
0 126
37.2%
11 3
 
0.9%
12 2
 
0.6%
14 3
 
0.9%
16 2
 
0.6%
17 1
 
0.3%
18 1
 
0.3%
19 2
 
0.6%
20 2
 
0.6%
21 4
 
1.2%
ValueCountFrequency (%)
546 1
0.3%
500 1
0.3%
222 1
0.3%
217 1
0.3%
80 2
0.6%
74 1
0.3%
73 1
0.3%
64 1
0.3%
61 1
0.3%
60 1
0.3%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.7%
Missing52
Missing (%)15.3%
Memory size810.0 B
True
156 
False
131 
(Missing)
52 
ValueCountFrequency (%)
True 156
46.0%
False 131
38.6%
(Missing) 52
 
15.3%
2024-04-30T04:19:37.695417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct64
Distinct (%)25.1%
Missing84
Missing (%)24.8%
Infinite0
Infinite (%)0.0%
Mean45.65098
Minimum0
Maximum3618
Zeros130
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:19:37.802367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q334
95-th percentile94.6
Maximum3618
Range3618
Interquartile range (IQR)34

Descriptive statistics

Standard deviation246.73736
Coefficient of variation (CV)5.4048643
Kurtosis176.86827
Mean45.65098
Median Absolute Deviation (MAD)0
Skewness12.67136
Sum11641
Variance60879.323
MonotonicityNot monotonic
2024-04-30T04:19:37.912854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 130
38.3%
24 8
 
2.4%
27 5
 
1.5%
32 5
 
1.5%
25 4
 
1.2%
30 4
 
1.2%
45 4
 
1.2%
38 3
 
0.9%
48 3
 
0.9%
54 3
 
0.9%
Other values (54) 86
25.4%
(Missing) 84
24.8%
ValueCountFrequency (%)
0 130
38.3%
2 1
 
0.3%
11 3
 
0.9%
12 2
 
0.6%
14 2
 
0.6%
16 2
 
0.6%
17 1
 
0.3%
18 1
 
0.3%
19 1
 
0.3%
20 2
 
0.6%
ValueCountFrequency (%)
3618 1
0.3%
1200 1
0.3%
980 1
0.3%
301 1
0.3%
300 1
0.3%
148 1
0.3%
128 1
0.3%
124 1
0.3%
120 1
0.3%
104 1
0.3%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing338
Missing (%)99.7%
Memory size2.8 KiB
2024-04-30T04:19:38.030643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row행정처분진행중 지위승계불가
ValueCountFrequency (%)
행정처분진행중 1
50.0%
지위승계불가 1
50.0%
2024-04-30T04:19:38.240749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (3) 3
21.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
92.9%
Space Separator 1
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
Other values (2) 2
15.4%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
92.9%
Common 1
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
92.9%
ASCII 1
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
Other values (2) 2
15.4%
ASCII
ValueCountFrequency (%)
1
100.0%

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing339
Missing (%)100.0%
Memory size3.1 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing339
Missing (%)100.0%
Memory size3.1 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
296 
자가
 
25
임대
 
18

Length

Max length4
Median length4
Mean length3.7463127
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> 296
87.3%
자가 25
 
7.4%
임대 18
 
5.3%

Length

2024-04-30T04:19:38.354155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:38.464721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 296
87.3%
자가 25
 
7.4%
임대 18
 
5.3%

세탁기수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
210 
0
129 

Length

Max length4
Median length4
Mean length2.8584071
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> 210
61.9%
0 129
38.1%

Length

2024-04-30T04:19:38.559614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:38.851343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 210
61.9%
0 129
38.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
291 
0
47 
36
 
1

Length

Max length4
Median length4
Mean length3.5781711
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 291
85.8%
0 47
 
13.9%
36 1
 
0.3%

Length

2024-04-30T04:19:38.951588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:39.058876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 291
85.8%
0 47
 
13.9%
36 1
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
291 
0
47 
35
 
1

Length

Max length4
Median length4
Mean length3.5781711
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 291
85.8%
0 47
 
13.9%
35 1
 
0.3%

Length

2024-04-30T04:19:39.172034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:39.270947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 291
85.8%
0 47
 
13.9%
35 1
 
0.3%

회수건조수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
212 
0
127 

Length

Max length4
Median length4
Mean length2.8761062
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> 212
62.5%
0 127
37.5%

Length

2024-04-30T04:19:39.377779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:39.474575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 212
62.5%
0 127
37.5%

침대수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
213 
0
126 

Length

Max length4
Median length4
Mean length2.8849558
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> 213
62.8%
0 126
37.2%

Length

2024-04-30T04:19:39.561400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:19:39.643964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 213
62.8%
0 126
37.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing52
Missing (%)15.3%
Memory size810.0 B
False
287 
(Missing)
52 
ValueCountFrequency (%)
False 287
84.7%
(Missing) 52
 
15.3%
2024-04-30T04:19:39.712159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032200003220000-201-1972-0000319721117<NA>3폐업2폐업20030222<NA><NA><NA>0234630462.00135860서울특별시 강남구 도곡동 956-11번지<NA><NA>대동여인숙2003-03-05 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업<NA><NA><NA><NA><NA><NA><NA>13<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132200003220000-201-1974-0000819741021<NA>3폐업2폐업20041216<NA><NA><NA>0205676817102.53135509서울특별시 강남구 삼성동 115-28번지<NA><NA>삼성여관2002-11-11 00:00:00I2018-08-31 23:59:59.0여관업204384.977691445523.738755여관업000<NA>0<NA>01111Y11<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232200003220000-201-1975-0006719751210<NA>3폐업2폐업20100126<NA><NA><NA>0205681188406.98135928서울특별시 강남구 역삼동 779-5번지<NA><NA>삼보여관2005-05-09 00:00:00I2018-08-31 23:59:59.0여관업203942.743843443773.130888여관업000<NA>0<NA>0200Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332200003220000-201-1976-000061976-06-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>183.19135-513서울특별시 강남구 역삼동 700-27서울특별시 강남구 언주로94길 13 (역삼동)6147블랑호텔 강남점2023-06-16 10:42:19U2022-12-05 23:08:00.0여관업203757.964541444700.323<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
432200003220000-201-1976-0001819761125<NA>3폐업2폐업19970201<NA><NA><NA>02 5432183150.80135811서울특별시 강남구 논현동 4-0번지<NA><NA>삼부2001-11-26 00:00:00I2018-08-31 23:59:59.0여관업201887.115905446069.444902여관업000<NA>0<NA>01111Y11<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532200003220000-201-1976-0008419761210<NA>3폐업2폐업20200811<NA><NA><NA>02 5421511414.87135815서울특별시 강남구 논현동 56-21서울특별시 강남구 학동로 141 (논현동)6045호텔지2020-08-11 12:23:22U2020-08-13 02:40:00.0관광호텔202253.771266445646.871804관광호텔<NA><NA><NA><NA><NA><NA>93125Y25<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632200003220000-201-1977-0001219770919<NA>3폐업2폐업20041030<NA><NA><NA>0205665935216.37135935서울특별시 강남구 역삼동 826-5번지<NA><NA>유림2002-11-11 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>02222Y22<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732200003220000-201-1977-0001919770404<NA>3폐업2폐업20060426<NA><NA><NA>02 5482298230.48135545서울특별시 강남구 논현동 201-6번지<NA><NA>유진여관2002-11-28 00:00:00I2018-08-31 23:59:59.0여관업202239.45036444795.560503여관업000<NA>0<NA>51017Y17<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832200003220000-201-1977-0014619770618<NA>3폐업2폐업20040320<NA><NA><NA>0205431231.00135892서울특별시 강남구 신사동 585-8번지<NA><NA>신라여관2003-10-30 00:00:00I2018-08-31 23:59:59.0여관업202388.335397446632.27918여관업000<NA>0<NA>870Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932200003220000-201-1977-0014719770125<NA>3폐업2폐업19970718<NA><NA><NA>0205575629.00135841서울특별시 강남구 대치동 904-0번지<NA><NA>대치2001-10-19 00:00:00I2018-08-31 23:59:59.0여관업204836.082081444500.863513여관업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
32932200003220000-201-2022-000022022-06-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 674215659535.53135-995서울특별시 강남구 논현동 74-6서울특별시 강남구 논현로 734, 지하2층~지상11층 (논현동)6049아난티 앳 강남2023-06-15 17:03:12U2022-12-05 23:07:00.0관광호텔202545.820551446151.727131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33032200003220000-214-1979-0000119790328<NA>1영업/정상1영업<NA><NA><NA><NA>02 54201129,749.43135812서울특별시 강남구 논현동 6서울특별시 강남구 도산대로 144 (논현동)6040보코서울강남2022-03-08 11:14:23I2022-03-10 13:22:36.0숙박업(생활)<NA><NA>숙박업(생활)00000001510Y0<NA><NA><NA>자가00000N
33132200003220000-214-2014-000012014-05-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 560 90602281.01135-513서울특별시 강남구 역삼동 701-1서울특별시 강남구 언주로 506 (역삼동, 지상5,7,8,10,12,13,16,17층(각층전체)역삼아르누보씨티)6152역삼아르누보씨티2024-04-15 14:22:07U2023-12-03 23:07:00.0숙박업(생활)203716.938086444579.034009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33232200003220000-214-2015-000012015-07-27<NA>1영업/정상1영업<NA><NA><NA><NA>02647415304158.77135-545서울특별시 강남구 논현동 205-8 지상2,3,4,5,6,12,13(각층전체)서울특별시 강남구 봉은사로 143 (논현동, 지상2,3,4,5,6,12,13(각층전체))6122강남패밀리 호텔2023-04-07 14:27:39U2022-12-04 00:09:00.0숙박업(생활)202596.666692444917.728061<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33332200003220000-214-2016-0000120160721<NA>3폐업2폐업20180430<NA><NA><NA>0216612850290.82135818서울특별시 강남구 논현동 80-24번지서울특별시 강남구 논현로 716, 3,4층 (논현동)6051한솔호스텔2018-05-31 15:16:44I2018-08-31 23:59:59.0숙박업(생활)202589.7445979.625숙박업(생활)0034001500N0<NA><NA><NA><NA>00000N
33432200003220000-214-2021-0000120210409<NA>1영업/정상1영업<NA><NA><NA><NA><NA>515.55135812서울특별시 강남구 논현동 6-9서울특별시 강남구 논현로149길 40, 지상1층102호,2층,3층,4층 (논현동)6040화이트 린넨 하우스2021-06-04 11:22:28I2021-06-06 00:23:02.0숙박업(생활)202166.609544446168.480344숙박업(생활)5114<NA><NA>090N0<NA><NA><NA><NA>00000N
33532200003220000-214-2021-0000220211105<NA>1영업/정상1영업<NA><NA><NA><NA>02 20380853460.16135920서울특별시 강남구 역삼동 718-11서울특별시 강남구 테헤란로28길 3-4, 지상9,10,11층 (역삼동)6220블루밍하우스2021-11-09 13:28:21U2021-11-11 02:40:00.0숙박업(생활)203376.748445444292.694243숙박업(생활)11200000160N0<NA><NA><NA><NA>00000N
33632200003220000-214-2021-0000320211227<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3,221.99135513서울특별시 강남구 역삼동 701-1 역삼 아르누보씨티서울특별시 강남구 언주로 506, 역삼 아르누보씨티 5,7,8,10,12,13,16,17층 (역삼동)6152역삼아르누보씨티호텔앤레지던스2021-12-27 18:29:46I2021-12-29 00:22:42.0숙박업(생활)203716.938086444579.034009숙박업(생활)00517000730N0<NA><NA><NA><NA>00000N
33732200003220000-214-2023-000012023-11-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 501 31712628.19135-915서울특별시 강남구 역삼동 677-10 호텔더디자이너스리즈스윗역삼서울특별시 강남구 테헤란로37길 13-12, 호텔더디자이너스리즈스윗역삼 지상1~14층 (역삼동)6142호텔더디자이너스 리즈 스윗 역삼2023-12-01 09:49:03I2022-11-02 00:03:00.0숙박업(생활)203435.082739444522.846786<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33832200003220000-214-2024-000012024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>491.58135-890서울특별시 강남구 신사동 557-14서울특별시 강남구 논현로155길 25-1, 지하1층~지상3층 (신사동)6033단델리온 신사1호점2024-04-22 16:43:47I2023-12-03 22:04:00.0숙박업(생활)202242.701739446568.295252<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>