Overview

Dataset statistics

Number of variables47
Number of observations462
Missing cells3869
Missing cells (%)17.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory182.4 KiB
Average record size in memory404.3 B

Variable types

Categorical23
Text7
DateTime4
Unsupported4
Numeric7
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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-17929/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (50.5%)Imbalance
업태구분명 is highly imbalanced (96.0%)Imbalance
위생업태명 is highly imbalanced (63.7%)Imbalance
사용끝지상층 is highly imbalanced (81.5%)Imbalance
사용끝지하층 is highly imbalanced (78.8%)Imbalance
조건부허가시작일자 is highly imbalanced (97.8%)Imbalance
조건부허가종료일자 is highly imbalanced (97.8%)Imbalance
건물소유구분명 is highly imbalanced (86.9%)Imbalance
여성종사자수 is highly imbalanced (75.6%)Imbalance
남성종사자수 is highly imbalanced (74.4%)Imbalance
침대수 is highly imbalanced (67.0%)Imbalance
인허가취소일자 has 462 (100.0%) missing valuesMissing
폐업일자 has 65 (14.1%) missing valuesMissing
휴업시작일자 has 462 (100.0%) missing valuesMissing
휴업종료일자 has 462 (100.0%) missing valuesMissing
재개업일자 has 462 (100.0%) missing valuesMissing
전화번호 has 109 (23.6%) missing valuesMissing
도로명주소 has 327 (70.8%) missing valuesMissing
도로명우편번호 has 328 (71.0%) missing valuesMissing
좌표정보(X) has 48 (10.4%) missing valuesMissing
좌표정보(Y) has 48 (10.4%) missing valuesMissing
건물지상층수 has 229 (49.6%) missing valuesMissing
사용시작지상층 has 255 (55.2%) missing valuesMissing
발한실여부 has 34 (7.4%) missing valuesMissing
좌석수 has 85 (18.4%) missing valuesMissing
조건부허가신고사유 has 461 (99.8%) missing valuesMissing
다중이용업소여부 has 32 (6.9%) 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
소재지면적 has 73 (15.8%) zerosZeros
건물지상층수 has 216 (46.8%) zerosZeros
사용시작지상층 has 184 (39.8%) zerosZeros
좌석수 has 30 (6.5%) zerosZeros

Reproduction

Analysis started2024-05-11 04:53:09.026889
Analysis finished2024-05-11 04:53:10.403095
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3020000
462 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 462
100.0%

Length

2024-05-11T04:53:10.637809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:10.799145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 462
100.0%

관리번호
Text

UNIQUE 

Distinct462
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T04:53:11.123201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10164
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

Unique462 ?
Unique (%)100.0%

Sample

1st row3020000-203-1900-00001
2nd row3020000-203-1900-00002
3rd row3020000-203-1900-00003
4th row3020000-203-1900-00004
5th row3020000-203-1900-00005
ValueCountFrequency (%)
3020000-203-1900-00001 1
 
0.2%
3020000-203-2001-01421 1
 
0.2%
3020000-203-2001-01418 1
 
0.2%
3020000-203-2001-01417 1
 
0.2%
3020000-203-2001-01415 1
 
0.2%
3020000-203-2001-01412 1
 
0.2%
3020000-203-2001-01411 1
 
0.2%
3020000-203-2001-01410 1
 
0.2%
3020000-203-2001-01409 1
 
0.2%
3020000-203-2001-01408 1
 
0.2%
Other values (452) 452
97.8%
2024-05-11T04:53:11.709846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4212
41.4%
- 1386
 
13.6%
2 1357
 
13.4%
3 1071
 
10.5%
1 880
 
8.7%
9 468
 
4.6%
8 241
 
2.4%
7 174
 
1.7%
6 138
 
1.4%
4 129
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8778
86.4%
Dash Punctuation 1386
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4212
48.0%
2 1357
 
15.5%
3 1071
 
12.2%
1 880
 
10.0%
9 468
 
5.3%
8 241
 
2.7%
7 174
 
2.0%
6 138
 
1.6%
4 129
 
1.5%
5 108
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1386
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4212
41.4%
- 1386
 
13.6%
2 1357
 
13.4%
3 1071
 
10.5%
1 880
 
8.7%
9 468
 
4.6%
8 241
 
2.4%
7 174
 
1.7%
6 138
 
1.4%
4 129
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4212
41.4%
- 1386
 
13.6%
2 1357
 
13.4%
3 1071
 
10.5%
1 880
 
8.7%
9 468
 
4.6%
8 241
 
2.4%
7 174
 
1.7%
6 138
 
1.4%
4 129
 
1.3%

인허가일자
Date

Distinct407
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum1900-01-01 00:00:00
Maximum2024-01-31 00:00:00
2024-05-11T04:53:11.978262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:53:12.301639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing462
Missing (%)100.0%
Memory size4.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3
397 
1
65 

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 (%)
3 397
85.9%
1 65
 
14.1%

Length

2024-05-11T04:53:12.582074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:12.748688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 397
85.9%
1 65
 
14.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐업
397 
영업/정상
65 

Length

Max length5
Median length2
Mean length2.4220779
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 397
85.9%
영업/정상 65
 
14.1%

Length

2024-05-11T04:53:12.944246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:13.126756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 397
85.9%
영업/정상 65
 
14.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2
397 
1
65 

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 (%)
2 397
85.9%
1 65
 
14.1%

Length

2024-05-11T04:53:13.311920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:13.520181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 397
85.9%
1 65
 
14.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐업
397 
영업
65 

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 397
85.9%
영업 65
 
14.1%

Length

2024-05-11T04:53:13.697975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:13.866946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 397
85.9%
영업 65
 
14.1%

폐업일자
Date

MISSING 

Distinct317
Distinct (%)79.8%
Missing65
Missing (%)14.1%
Memory size3.7 KiB
Minimum1974-07-04 00:00:00
Maximum2024-04-23 00:00:00
2024-05-11T04:53:14.060086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:53:14.333021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing462
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing462
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing462
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct274
Distinct (%)77.6%
Missing109
Missing (%)23.6%
Memory size3.7 KiB
2024-05-11T04:53:14.865657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6912181
Min length2

Characters and Unicode

Total characters3421
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

Unique253 ?
Unique (%)71.7%

Sample

1st row7746282
2nd row7490054
3rd row32731320
4th row7141372
5th row7565430
ValueCountFrequency (%)
02 224
38.2%
0200000000 38
 
6.5%
00000 18
 
3.1%
7979963 4
 
0.7%
7168656 3
 
0.5%
7973807 3
 
0.5%
7746282 3
 
0.5%
0 2
 
0.3%
7743710 2
 
0.3%
7128176 2
 
0.3%
Other values (269) 288
49.1%
2024-05-11T04:53:15.635516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 909
26.6%
2 461
13.5%
7 455
13.3%
289
 
8.4%
9 259
 
7.6%
1 219
 
6.4%
3 182
 
5.3%
5 179
 
5.2%
6 157
 
4.6%
8 157
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3132
91.6%
Space Separator 289
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 909
29.0%
2 461
14.7%
7 455
14.5%
9 259
 
8.3%
1 219
 
7.0%
3 182
 
5.8%
5 179
 
5.7%
6 157
 
5.0%
8 157
 
5.0%
4 154
 
4.9%
Space Separator
ValueCountFrequency (%)
289
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3421
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 909
26.6%
2 461
13.5%
7 455
13.3%
289
 
8.4%
9 259
 
7.6%
1 219
 
6.4%
3 182
 
5.3%
5 179
 
5.2%
6 157
 
4.6%
8 157
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3421
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 909
26.6%
2 461
13.5%
7 455
13.3%
289
 
8.4%
9 259
 
7.6%
1 219
 
6.4%
3 182
 
5.3%
5 179
 
5.2%
6 157
 
4.6%
8 157
 
4.6%

소재지면적
Real number (ℝ)

ZEROS 

Distinct284
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.627186
Minimum0
Maximum180.07
Zeros73
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:16.129553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.03
median16.425
Q331.06
95-th percentile67.666
Maximum180.07
Range180.07
Interquartile range (IQR)22.03

Descriptive statistics

Standard deviation25.225033
Coefficient of variation (CV)1.0676275
Kurtosis7.7489181
Mean23.627186
Median Absolute Deviation (MAD)9.825
Skewness2.3285657
Sum10915.76
Variance636.30227
MonotonicityNot monotonic
2024-05-11T04:53:16.416866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 73
 
15.8%
6.6 13
 
2.8%
10.0 10
 
2.2%
23.1 8
 
1.7%
33.0 7
 
1.5%
13.2 7
 
1.5%
9.9 7
 
1.5%
20.0 6
 
1.3%
16.5 5
 
1.1%
3.3 4
 
0.9%
Other values (274) 322
69.7%
ValueCountFrequency (%)
0.0 73
15.8%
3.3 4
 
0.9%
3.37 1
 
0.2%
4.5 1
 
0.2%
4.95 2
 
0.4%
5.0 1
 
0.2%
6.0 2
 
0.4%
6.25 1
 
0.2%
6.45 1
 
0.2%
6.6 13
 
2.8%
ValueCountFrequency (%)
180.07 1
0.2%
152.46 1
0.2%
148.5 2
0.4%
118.61 1
0.2%
117.36 1
0.2%
115.5 2
0.4%
103.8 1
0.2%
100.0 1
0.2%
97.2 1
0.2%
90.7 1
0.2%

소재지우편번호
Text

Distinct116
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T04:53:16.860894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.030303
Min length6

Characters and Unicode

Total characters2786
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

Unique47 ?
Unique (%)10.2%

Sample

1st row140901
2nd row140872
3rd row140909
4th row140846
5th row140872
ValueCountFrequency (%)
140832 21
 
4.5%
140863 20
 
4.3%
140821 20
 
4.3%
140823 17
 
3.7%
140889 16
 
3.5%
140871 12
 
2.6%
140833 12
 
2.6%
140909 11
 
2.4%
140090 11
 
2.4%
140011 11
 
2.4%
Other values (106) 311
67.3%
2024-05-11T04:53:17.609588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 650
23.3%
1 595
21.4%
4 527
18.9%
8 412
14.8%
2 129
 
4.6%
3 128
 
4.6%
9 116
 
4.2%
6 87
 
3.1%
7 82
 
2.9%
5 46
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2772
99.5%
Dash Punctuation 14
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 650
23.4%
1 595
21.5%
4 527
19.0%
8 412
14.9%
2 129
 
4.7%
3 128
 
4.6%
9 116
 
4.2%
6 87
 
3.1%
7 82
 
3.0%
5 46
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2786
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 650
23.3%
1 595
21.4%
4 527
18.9%
8 412
14.8%
2 129
 
4.6%
3 128
 
4.6%
9 116
 
4.2%
6 87
 
3.1%
7 82
 
2.9%
5 46
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 650
23.3%
1 595
21.4%
4 527
18.9%
8 412
14.8%
2 129
 
4.6%
3 128
 
4.6%
9 116
 
4.2%
6 87
 
3.1%
7 82
 
2.9%
5 46
 
1.7%

지번주소
Text

Distinct390
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T04:53:18.039445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length23.525974
Min length18

Characters and Unicode

Total characters10869
Distinct characters127
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)72.7%

Sample

1st row서울특별시 용산구 후암동 194-1번지
2nd row서울특별시 용산구 한강로2가 92-1번지
3rd row서울특별시 용산구 이촌동 209-22번지
4th row서울특별시 용산구 원효로1가 12-12번지
5th row서울특별시 용산구 한강로2가 93-1번지
ValueCountFrequency (%)
서울특별시 462
23.6%
용산구 462
23.6%
이태원동 53
 
2.7%
한남동 52
 
2.7%
한강로2가 32
 
1.6%
보광동 31
 
1.6%
동자동 29
 
1.5%
한강로3가 27
 
1.4%
용산동2가 25
 
1.3%
이촌동 23
 
1.2%
Other values (422) 762
38.9%
2024-05-11T04:53:18.874477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1924
17.7%
용 523
 
4.8%
산 516
 
4.7%
서 474
 
4.4%
시 466
 
4.3%
구 464
 
4.3%
별 463
 
4.3%
특 462
 
4.3%
울 462
 
4.3%
- 436
 
4.0%
Other values (117) 4679
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6450
59.3%
Decimal Number 2034
 
18.7%
Space Separator 1924
 
17.7%
Dash Punctuation 436
 
4.0%
Open Punctuation 11
 
0.1%
Close Punctuation 11
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 523
 
8.1%
산 516
 
8.0%
서 474
 
7.3%
시 466
 
7.2%
구 464
 
7.2%
별 463
 
7.2%
특 462
 
7.2%
울 462
 
7.2%
지 433
 
6.7%
번 409
 
6.3%
Other values (101) 1778
27.6%
Decimal Number
ValueCountFrequency (%)
1 413
20.3%
2 391
19.2%
3 258
12.7%
4 177
8.7%
6 167
8.2%
5 147
 
7.2%
9 134
 
6.6%
0 132
 
6.5%
8 112
 
5.5%
7 103
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
1924
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 436
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6449
59.3%
Common 4419
40.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 523
 
8.1%
산 516
 
8.0%
서 474
 
7.3%
시 466
 
7.2%
구 464
 
7.2%
별 463
 
7.2%
특 462
 
7.2%
울 462
 
7.2%
지 433
 
6.7%
번 409
 
6.3%
Other values (100) 1777
27.6%
Common
ValueCountFrequency (%)
1924
43.5%
- 436
 
9.9%
1 413
 
9.3%
2 391
 
8.8%
3 258
 
5.8%
4 177
 
4.0%
6 167
 
3.8%
5 147
 
3.3%
9 134
 
3.0%
0 132
 
3.0%
Other values (6) 240
 
5.4%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6449
59.3%
ASCII 4419
40.7%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1924
43.5%
- 436
 
9.9%
1 413
 
9.3%
2 391
 
8.8%
3 258
 
5.8%
4 177
 
4.0%
6 167
 
3.8%
5 147
 
3.3%
9 134
 
3.0%
0 132
 
3.0%
Other values (6) 240
 
5.4%
Hangul
ValueCountFrequency (%)
용 523
 
8.1%
산 516
 
8.0%
서 474
 
7.3%
시 466
 
7.2%
구 464
 
7.2%
별 463
 
7.2%
특 462
 
7.2%
울 462
 
7.2%
지 433
 
6.7%
번 409
 
6.3%
Other values (100) 1777
27.6%
CJK
ValueCountFrequency (%)
內 1
100.0%

도로명주소
Text

MISSING 

Distinct131
Distinct (%)97.0%
Missing327
Missing (%)70.8%
Memory size3.7 KiB
2024-05-11T04:53:19.411756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length30.77037
Min length22

Characters and Unicode

Total characters4154
Distinct characters139
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)94.1%

Sample

1st row서울특별시 용산구 신흥로22가길 12, 1층 (용산동2가)
2nd row서울특별시 용산구 백범로 319-1 (원효로1가)
3rd row서울특별시 용산구 이태원로26길 16 (이태원동)
4th row서울특별시 용산구 우사단로10길 127 (한남동,2층 101호)
5th row서울특별시 용산구 우사단로10길 92 (보광동)
ValueCountFrequency (%)
서울특별시 135
 
17.1%
용산구 135
 
17.1%
1층 35
 
4.4%
한남동 16
 
2.0%
이태원동 16
 
2.0%
한강대로 12
 
1.5%
용문동 11
 
1.4%
보광동 10
 
1.3%
용산동2가 8
 
1.0%
이촌동 7
 
0.9%
Other values (263) 405
51.3%
2024-05-11T04:53:20.368270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
655
 
15.8%
1 192
 
4.6%
용 160
 
3.9%
로 157
 
3.8%
서 153
 
3.7%
산 147
 
3.5%
시 139
 
3.3%
( 138
 
3.3%
) 138
 
3.3%
별 136
 
3.3%
Other values (129) 2139
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2446
58.9%
Space Separator 655
 
15.8%
Decimal Number 653
 
15.7%
Open Punctuation 138
 
3.3%
Close Punctuation 138
 
3.3%
Other Punctuation 99
 
2.4%
Dash Punctuation 22
 
0.5%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 160
 
6.5%
로 157
 
6.4%
서 153
 
6.3%
산 147
 
6.0%
시 139
 
5.7%
별 136
 
5.6%
구 136
 
5.6%
울 135
 
5.5%
특 135
 
5.5%
동 129
 
5.3%
Other values (113) 1019
41.7%
Decimal Number
ValueCountFrequency (%)
1 192
29.4%
2 99
15.2%
3 70
 
10.7%
4 59
 
9.0%
0 51
 
7.8%
5 45
 
6.9%
9 44
 
6.7%
7 36
 
5.5%
6 31
 
4.7%
8 26
 
4.0%
Space Separator
ValueCountFrequency (%)
655
100.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Other Punctuation
ValueCountFrequency (%)
, 99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2445
58.9%
Common 1705
41.0%
Latin 3
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 160
 
6.5%
로 157
 
6.4%
서 153
 
6.3%
산 147
 
6.0%
시 139
 
5.7%
별 136
 
5.6%
구 136
 
5.6%
울 135
 
5.5%
특 135
 
5.5%
동 129
 
5.3%
Other values (112) 1018
41.6%
Common
ValueCountFrequency (%)
655
38.4%
1 192
 
11.3%
( 138
 
8.1%
) 138
 
8.1%
2 99
 
5.8%
, 99
 
5.8%
3 70
 
4.1%
4 59
 
3.5%
0 51
 
3.0%
5 45
 
2.6%
Other values (5) 159
 
9.3%
Latin
ValueCountFrequency (%)
B 3
100.0%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2445
58.9%
ASCII 1708
41.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
655
38.3%
1 192
 
11.2%
( 138
 
8.1%
) 138
 
8.1%
2 99
 
5.8%
, 99
 
5.8%
3 70
 
4.1%
4 59
 
3.5%
0 51
 
3.0%
5 45
 
2.6%
Other values (6) 162
 
9.5%
Hangul
ValueCountFrequency (%)
용 160
 
6.5%
로 157
 
6.4%
서 153
 
6.3%
산 147
 
6.0%
시 139
 
5.7%
별 136
 
5.6%
구 136
 
5.6%
울 135
 
5.5%
특 135
 
5.5%
동 129
 
5.3%
Other values (112) 1018
41.6%
CJK
ValueCountFrequency (%)
內 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)54.5%
Missing328
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean4367.1418
Minimum4300
Maximum4428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:20.838978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile4313
Q14338.25
median4365.5
Q34394.75
95-th percentile4417
Maximum4428
Range128
Interquartile range (IQR)56.5

Descriptive statistics

Standard deviation34.842104
Coefficient of variation (CV)0.0079782397
Kurtosis-1.1198191
Mean4367.1418
Median Absolute Deviation (MAD)28.5
Skewness-0.12678206
Sum585197
Variance1213.9722
MonotonicityNot monotonic
2024-05-11T04:53:21.254587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4356 8
 
1.7%
4391 6
 
1.3%
4410 6
 
1.3%
4394 5
 
1.1%
4343 5
 
1.1%
4337 5
 
1.1%
4374 4
 
0.9%
4313 4
 
0.9%
4405 4
 
0.9%
4376 3
 
0.6%
Other values (63) 84
 
18.2%
(Missing) 328
71.0%
ValueCountFrequency (%)
4300 2
0.4%
4302 1
 
0.2%
4305 1
 
0.2%
4306 1
 
0.2%
4308 1
 
0.2%
4313 4
0.9%
4314 1
 
0.2%
4315 1
 
0.2%
4316 1
 
0.2%
4318 2
0.4%
ValueCountFrequency (%)
4428 2
 
0.4%
4426 1
 
0.2%
4424 1
 
0.2%
4423 1
 
0.2%
4419 1
 
0.2%
4417 2
 
0.4%
4416 1
 
0.2%
4415 1
 
0.2%
4413 2
 
0.4%
4410 6
1.3%

사업장명
Text

Distinct372
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T04:53:21.727393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length4.1861472
Min length1

Characters and Unicode

Total characters1934
Distinct characters281
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

Unique310 ?
Unique (%)67.1%

Sample

1st row광일
2nd row삼성
3rd row모범
4th row용산경찰서구내
5th row태평양
ValueCountFrequency (%)
이용원 12
 
2.3%
바버샵 10
 
1.9%
신신 7
 
1.3%
제일 7
 
1.3%
현대 6
 
1.2%
태양 5
 
1.0%
광일 5
 
1.0%
엉클부스 5
 
1.0%
이발관 4
 
0.8%
삼성 4
 
0.8%
Other values (372) 454
87.5%
2024-05-11T04:53:22.471323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 156
 
8.1%
용 139
 
7.2%
원 138
 
7.1%
57
 
2.9%
성 41
 
2.1%
신 39
 
2.0%
발 34
 
1.8%
대 29
 
1.5%
우 25
 
1.3%
일 24
 
1.2%
Other values (271) 1252
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1728
89.3%
Uppercase Letter 61
 
3.2%
Space Separator 57
 
2.9%
Lowercase Letter 49
 
2.5%
Open Punctuation 15
 
0.8%
Close Punctuation 15
 
0.8%
Decimal Number 5
 
0.3%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 156
 
9.0%
용 139
 
8.0%
원 138
 
8.0%
성 41
 
2.4%
신 39
 
2.3%
발 34
 
2.0%
대 29
 
1.7%
우 25
 
1.4%
일 24
 
1.4%
내 24
 
1.4%
Other values (235) 1079
62.4%
Uppercase Letter
ValueCountFrequency (%)
R 10
16.4%
B 10
16.4%
E 8
13.1%
S 6
9.8%
L 4
 
6.6%
O 4
 
6.6%
K 4
 
6.6%
H 3
 
4.9%
A 3
 
4.9%
M 3
 
4.9%
Other values (5) 6
9.8%
Lowercase Letter
ValueCountFrequency (%)
r 9
18.4%
e 6
12.2%
a 6
12.2%
h 4
8.2%
p 4
8.2%
o 4
8.2%
b 4
8.2%
s 3
 
6.1%
i 2
 
4.1%
u 2
 
4.1%
Other values (4) 5
10.2%
Decimal Number
ValueCountFrequency (%)
9 4
80.0%
3 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
? 1
 
25.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1728
89.3%
Latin 110
 
5.7%
Common 96
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 156
 
9.0%
용 139
 
8.0%
원 138
 
8.0%
성 41
 
2.4%
신 39
 
2.3%
발 34
 
2.0%
대 29
 
1.7%
우 25
 
1.4%
일 24
 
1.4%
내 24
 
1.4%
Other values (235) 1079
62.4%
Latin
ValueCountFrequency (%)
R 10
 
9.1%
B 10
 
9.1%
r 9
 
8.2%
E 8
 
7.3%
e 6
 
5.5%
a 6
 
5.5%
S 6
 
5.5%
L 4
 
3.6%
O 4
 
3.6%
K 4
 
3.6%
Other values (19) 43
39.1%
Common
ValueCountFrequency (%)
57
59.4%
( 15
 
15.6%
) 15
 
15.6%
9 4
 
4.2%
. 3
 
3.1%
3 1
 
1.0%
? 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1728
89.3%
ASCII 206
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 156
 
9.0%
용 139
 
8.0%
원 138
 
8.0%
성 41
 
2.4%
신 39
 
2.3%
발 34
 
2.0%
대 29
 
1.7%
우 25
 
1.4%
일 24
 
1.4%
내 24
 
1.4%
Other values (235) 1079
62.4%
ASCII
ValueCountFrequency (%)
57
27.7%
( 15
 
7.3%
) 15
 
7.3%
R 10
 
4.9%
B 10
 
4.9%
r 9
 
4.4%
E 8
 
3.9%
e 6
 
2.9%
a 6
 
2.9%
S 6
 
2.9%
Other values (26) 64
31.1%

최종수정일자
Date

Distinct268
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum1999-01-26 00:00:00
Maximum2024-04-23 13:05:57
2024-05-11T04:53:22.851871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:53:23.298726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
I
412 
U
50 

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 412
89.2%
U 50
 
10.8%

Length

2024-05-11T04:53:23.725043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:24.015564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 412
89.2%
u 50
 
10.8%

데이터갱신일자
Date

Distinct65
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:05:00
2024-05-11T04:53:24.341263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:53:24.895583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
일반이용업
460 
이용업 기타
 
2

Length

Max length6
Median length5
Mean length5.004329
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 460
99.6%
이용업 기타 2
 
0.4%

Length

2024-05-11T04:53:25.279150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:25.596420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 460
99.1%
이용업 2
 
0.4%
기타 2
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct302
Distinct (%)72.9%
Missing48
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean197981.89
Minimum195661.12
Maximum200822.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:25.938357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195661.12
5-th percentile196044.76
Q1196851.21
median197596.81
Q3199296
95-th percentile200448.08
Maximum200822.98
Range5161.8616
Interquartile range (IQR)2444.7927

Descriptive statistics

Standard deviation1405.3004
Coefficient of variation (CV)0.007098126
Kurtosis-1.0861804
Mean197981.89
Median Absolute Deviation (MAD)1033.7435
Skewness0.35014339
Sum81964501
Variance1974869.2
MonotonicityNot monotonic
2024-05-11T04:53:26.429554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196290.526521217 9
 
1.9%
195981.173932443 7
 
1.5%
196763.077733735 5
 
1.1%
196155.179500364 5
 
1.1%
198622.89264988 4
 
0.9%
200559.36615505 4
 
0.9%
199118.176847228 4
 
0.9%
197668.820819879 4
 
0.9%
195739.258577095 3
 
0.6%
199462.55857419 3
 
0.6%
Other values (292) 366
79.2%
(Missing) 48
 
10.4%
ValueCountFrequency (%)
195661.120716469 2
 
0.4%
195670.19398129 2
 
0.4%
195739.258577095 3
0.6%
195758.260949987 1
 
0.2%
195762.321247461 1
 
0.2%
195898.594965488 1
 
0.2%
195915.785026517 1
 
0.2%
195981.173932443 7
1.5%
195981.203408641 1
 
0.2%
195987.411622052 1
 
0.2%
ValueCountFrequency (%)
200822.982326596 1
 
0.2%
200743.543180415 1
 
0.2%
200692.592639751 1
 
0.2%
200648.866223783 3
0.6%
200636.292669587 1
 
0.2%
200591.154589614 1
 
0.2%
200580.663401657 1
 
0.2%
200559.36615505 4
0.9%
200504.503946848 1
 
0.2%
200502.179579742 3
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct302
Distinct (%)72.9%
Missing48
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean448227.47
Minimum446114.16
Maximum450229.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:26.868391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446114.16
5-th percentile446885.08
Q1447638.73
median448019.44
Q3448936.41
95-th percentile449907.63
Maximum450229.43
Range4115.2725
Interquartile range (IQR)1297.6722

Descriptive statistics

Standard deviation967.14207
Coefficient of variation (CV)0.0021577037
Kurtosis-0.5934083
Mean448227.47
Median Absolute Deviation (MAD)572.83865
Skewness0.26587009
Sum1.8556617 × 108
Variance935363.79
MonotonicityNot monotonic
2024-05-11T04:53:27.448360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448436.078138776 9
 
1.9%
447083.530244918 7
 
1.5%
448504.044237016 5
 
1.1%
448002.693986606 5
 
1.1%
446114.155238838 4
 
0.9%
447696.887165762 4
 
0.9%
447688.4883026 4
 
0.9%
449985.969344304 4
 
0.9%
447887.456942178 3
 
0.6%
447958.068967697 3
 
0.6%
Other values (292) 366
79.2%
(Missing) 48
 
10.4%
ValueCountFrequency (%)
446114.155238838 4
0.9%
446233.81723078 1
 
0.2%
446252.339785985 1
 
0.2%
446270.376661762 1
 
0.2%
446272.36306167 1
 
0.2%
446361.295910071 1
 
0.2%
446425.373848781 1
 
0.2%
446492.478755935 3
0.6%
446494.73009764 1
 
0.2%
446502.757023209 1
 
0.2%
ValueCountFrequency (%)
450229.427777316 1
0.2%
450223.627197625 1
0.2%
450218.028824305 1
0.2%
450211.855107496 1
0.2%
450153.122732911 1
0.2%
450150.14820076 1
0.2%
450126.951675139 1
0.2%
450122.326766311 1
0.2%
450111.76389291 1
0.2%
450096.883470219 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
일반이용업
430 
<NA>
 
32

Length

Max length5
Median length5
Mean length4.9307359
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 430
93.1%
<NA> 32
 
6.9%

Length

2024-05-11T04:53:27.856040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:28.164136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 430
93.1%
na 32
 
6.9%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)3.0%
Missing229
Missing (%)49.6%
Infinite0
Infinite (%)0.0%
Mean0.20600858
Minimum0
Maximum6
Zeros216
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:28.461500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.4
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.86131312
Coefficient of variation (CV)4.1809574
Kurtosis24.879541
Mean0.20600858
Median Absolute Deviation (MAD)0
Skewness4.8553848
Sum48
Variance0.74186029
MonotonicityNot monotonic
2024-05-11T04:53:28.821498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 216
46.8%
1 5
 
1.1%
3 4
 
0.9%
2 3
 
0.6%
4 2
 
0.4%
6 2
 
0.4%
5 1
 
0.2%
(Missing) 229
49.6%
ValueCountFrequency (%)
0 216
46.8%
1 5
 
1.1%
2 3
 
0.6%
3 4
 
0.9%
4 2
 
0.4%
5 1
 
0.2%
6 2
 
0.4%
ValueCountFrequency (%)
6 2
 
0.4%
5 1
 
0.2%
4 2
 
0.4%
3 4
 
0.9%
2 3
 
0.6%
1 5
 
1.1%
0 216
46.8%

건물지하층수
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
229 
0
221 
1
 
9
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length2.487013
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 229
49.6%
0 221
47.8%
1 9
 
1.9%
2 2
 
0.4%
3 1
 
0.2%

Length

2024-05-11T04:53:29.100350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:29.297703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 229
49.6%
0 221
47.8%
1 9
 
1.9%
2 2
 
0.4%
3 1
 
0.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.9%
Missing255
Missing (%)55.2%
Infinite0
Infinite (%)0.0%
Mean0.28985507
Minimum0
Maximum24
Zeros184
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:29.574357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7606937
Coefficient of variation (CV)6.0743932
Kurtosis161.6524
Mean0.28985507
Median Absolute Deviation (MAD)0
Skewness12.126876
Sum60
Variance3.1000422
MonotonicityNot monotonic
2024-05-11T04:53:29.774149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 184
39.8%
1 13
 
2.8%
2 6
 
1.3%
3 2
 
0.4%
5 1
 
0.2%
24 1
 
0.2%
(Missing) 255
55.2%
ValueCountFrequency (%)
0 184
39.8%
1 13
 
2.8%
2 6
 
1.3%
3 2
 
0.4%
5 1
 
0.2%
24 1
 
0.2%
ValueCountFrequency (%)
24 1
 
0.2%
5 1
 
0.2%
3 2
 
0.4%
2 6
 
1.3%
1 13
 
2.8%
0 184
39.8%

사용끝지상층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
430 
0
 
18
1
 
7
2
 
5
5
 
1

Length

Max length4
Median length4
Mean length3.7922078
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 430
93.1%
0 18
 
3.9%
1 7
 
1.5%
2 5
 
1.1%
5 1
 
0.2%
3 1
 
0.2%

Length

2024-05-11T04:53:30.056551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:30.258814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 430
93.1%
0 18
 
3.9%
1 7
 
1.5%
2 5
 
1.1%
5 1
 
0.2%
3 1
 
0.2%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
262 
0
186 
1
 
13
6
 
1

Length

Max length4
Median length4
Mean length2.7012987
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 262
56.7%
0 186
40.3%
1 13
 
2.8%
6 1
 
0.2%

Length

2024-05-11T04:53:30.480603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:30.747828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 262
56.7%
0 186
40.3%
1 13
 
2.8%
6 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
438 
0
 
18
1
 
6

Length

Max length4
Median length4
Mean length3.8441558
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> 438
94.8%
0 18
 
3.9%
1 6
 
1.3%

Length

2024-05-11T04:53:31.107696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:31.428717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 438
94.8%
0 18
 
3.9%
1 6
 
1.3%

한실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
235 
0
227 

Length

Max length4
Median length4
Mean length2.525974
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> 235
50.9%
0 227
49.1%

Length

2024-05-11T04:53:31.734436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:31.988663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
50.9%
0 227
49.1%

양실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
235 
0
227 

Length

Max length4
Median length4
Mean length2.525974
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> 235
50.9%
0 227
49.1%

Length

2024-05-11T04:53:32.317978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:32.641647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
50.9%
0 227
49.1%

욕실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
235 
0
227 

Length

Max length4
Median length4
Mean length2.525974
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> 235
50.9%
0 227
49.1%

Length

2024-05-11T04:53:32.990790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:33.241180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
50.9%
0 227
49.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing34
Missing (%)7.4%
Memory size1.0 KiB
False
428 
(Missing)
 
34
ValueCountFrequency (%)
False 428
92.6%
(Missing) 34
 
7.4%
2024-05-11T04:53:33.488974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)3.2%
Missing85
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean3.4244032
Minimum0
Maximum11
Zeros30
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T04:53:33.761365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile8
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.387966
Coefficient of variation (CV)0.69733786
Kurtosis0.41112097
Mean3.4244032
Median Absolute Deviation (MAD)1
Skewness0.9918382
Sum1291
Variance5.7023816
MonotonicityNot monotonic
2024-05-11T04:53:34.108581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 129
27.9%
3 74
16.0%
4 34
 
7.4%
0 30
 
6.5%
5 23
 
5.0%
8 23
 
5.0%
6 20
 
4.3%
1 15
 
3.2%
7 14
 
3.0%
9 9
 
1.9%
Other values (2) 6
 
1.3%
(Missing) 85
18.4%
ValueCountFrequency (%)
0 30
 
6.5%
1 15
 
3.2%
2 129
27.9%
3 74
16.0%
4 34
 
7.4%
5 23
 
5.0%
6 20
 
4.3%
7 14
 
3.0%
8 23
 
5.0%
9 9
 
1.9%
ValueCountFrequency (%)
11 2
 
0.4%
10 4
 
0.9%
9 9
 
1.9%
8 23
 
5.0%
7 14
 
3.0%
6 20
 
4.3%
5 23
 
5.0%
4 34
 
7.4%
3 74
16.0%
2 129
27.9%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing461
Missing (%)99.8%
Memory size3.7 KiB
2024-05-11T04:53:34.423918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row임시사용승인
ValueCountFrequency (%)
임시사용승인 1
100.0%
2024-05-11T04:53:35.290453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
임 1
16.7%
시 1
16.7%
사 1
16.7%
용 1
16.7%
승 1
16.7%
인 1
16.7%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
461 
20040825
 
1

Length

Max length8
Median length4
Mean length4.008658
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 461
99.8%
20040825 1
 
0.2%

Length

2024-05-11T04:53:35.863642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:36.410364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 461
99.8%
20040825 1
 
0.2%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
461 
20060510
 
1

Length

Max length8
Median length4
Mean length4.008658
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 461
99.8%
20060510 1
 
0.2%

Length

2024-05-11T04:53:36.923920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:37.792049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 461
99.8%
20060510 1
 
0.2%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
448 
임대
 
13
자가
 
1

Length

Max length4
Median length4
Mean length3.9393939
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
97.0%
임대 13
 
2.8%
자가 1
 
0.2%

Length

2024-05-11T04:53:38.174247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:38.718652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
97.0%
임대 13
 
2.8%
자가 1
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
403 
0
59 

Length

Max length4
Median length4
Mean length3.6168831
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> 403
87.2%
0 59
 
12.8%

Length

2024-05-11T04:53:39.028811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:39.320890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 403
87.2%
0 59
 
12.8%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
430 
0
 
30
1
 
2

Length

Max length4
Median length4
Mean length3.7922078
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> 430
93.1%
0 30
 
6.5%
1 2
 
0.4%

Length

2024-05-11T04:53:39.633898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:39.952505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 430
93.1%
0 30
 
6.5%
1 2
 
0.4%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
430 
0
 
27
1
 
5

Length

Max length4
Median length4
Mean length3.7922078
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> 430
93.1%
0 27
 
5.8%
1 5
 
1.1%

Length

2024-05-11T04:53:40.276020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:40.656238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 430
93.1%
0 27
 
5.8%
1 5
 
1.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
409 
0
53 

Length

Max length4
Median length4
Mean length3.6558442
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> 409
88.5%
0 53
 
11.5%

Length

2024-05-11T04:53:41.132254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:41.457083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 409
88.5%
0 53
 
11.5%

침대수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
410 
0
51 
1
 
1

Length

Max length4
Median length4
Mean length3.6623377
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 410
88.7%
0 51
 
11.0%
1 1
 
0.2%

Length

2024-05-11T04:53:41.866939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:53:42.302615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
88.7%
0 51
 
11.0%
1 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing32
Missing (%)6.9%
Memory size1.0 KiB
False
430 
(Missing)
 
32
ValueCountFrequency (%)
False 430
93.1%
(Missing) 32
 
6.9%
2024-05-11T04:53:42.707836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030200003020000-203-1900-0000119000101<NA>3폐업2폐업20001019<NA><NA><NA>77462820.0140901서울특별시 용산구 후암동 194-1번지<NA><NA>광일2003-03-17 00:00:00I2018-08-31 23:59:59.0일반이용업197995.835166449365.844397일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130200003020000-203-1900-0000219000101<NA>3폐업2폐업20030703<NA><NA><NA><NA>0.0140872서울특별시 용산구 한강로2가 92-1번지<NA><NA>삼성2003-07-03 00:00:00I2018-08-31 23:59:59.0일반이용업197383.554088447742.914272일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230200003020000-203-1900-0000319000101<NA>3폐업2폐업20030703<NA><NA><NA><NA>0.0140909서울특별시 용산구 이촌동 209-22번지<NA><NA>모범2003-07-03 00:00:00I2018-08-31 23:59:59.0일반이용업195915.785027447292.400352일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330200003020000-203-1900-0000419000101<NA>3폐업2폐업20030703<NA><NA><NA><NA>0.0140846서울특별시 용산구 원효로1가 12-12번지<NA><NA>용산경찰서구내2003-07-03 00:00:00I2018-08-31 23:59:59.0일반이용업197049.211744448756.30921일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430200003020000-203-1900-0000519000101<NA>3폐업2폐업19950501<NA><NA><NA><NA>0.0140872서울특별시 용산구 한강로2가 93-1번지<NA><NA>태평양2003-04-01 00:00:00I2018-08-31 23:59:59.0일반이용업197372.071348447758.048901일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530200003020000-203-1900-0000619000101<NA>3폐업2폐업19970131<NA><NA><NA><NA>0.0140833서울특별시 용산구 용산동2가 5-626번지<NA><NA>도원2003-04-01 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630200003020000-203-1900-0000719000101<NA>3폐업2폐업20021230<NA><NA><NA><NA>0.0140807서울특별시 용산구 갈월동 98-38번지<NA><NA>청용2003-03-12 00:00:00I2018-08-31 23:59:59.0일반이용업197492.006217448773.77781일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730200003020000-203-1900-0000819000101<NA>3폐업2폐업20030703<NA><NA><NA><NA>0.0140880서울특별시 용산구 한강로3가 40-1번지<NA><NA>용산역구내2003-07-03 00:00:00I2018-08-31 23:59:59.0일반이용업196145.200517447480.626892일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830200003020000-203-1900-0000919000101<NA>3폐업2폐업19970131<NA><NA><NA><NA>0.0140847서울특별시 용산구 원효로2가 68-3번지<NA><NA>청운2003-04-01 00:00:00I2018-08-31 23:59:59.0일반이용업196597.317331448112.026173일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930200003020000-203-1900-0001019000101<NA>3폐업2폐업19940117<NA><NA><NA><NA>0.0140893서울특별시 용산구 한남동 736-5번지<NA><NA>태원2003-04-01 00:00:00I2018-08-31 23:59:59.0일반이용업199873.11316448027.009798일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
45230200003020000-203-2022-0000120220112<NA>3폐업2폐업20220527<NA><NA><NA><NA>17.0140832서울특별시 용산구 용문동 38-214 용문사우나서울특별시 용산구 효창원로37길 29, 용문사우나 (용문동)4356용문사우나 내 이용원2022-05-27 11:28:10U2021-12-04 22:09:00.0일반이용업196290.526521448436.078139<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45330200003020000-203-2022-0000220220114<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.64140824서울특별시 용산구 보광동 265-386서울특별시 용산구 우사단로4길 18, 1층 좌측호 (보광동)4413스마일베어바버샵(SMILE BEAR BARBER SHOP)2022-01-14 14:10:18I2022-01-16 00:22:49.0일반이용업199720.67781447689.920731일반이용업000000000N1<NA><NA><NA><NA>00000N
45430200003020000-203-2022-000032022-06-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.92140-901서울특별시 용산구 후암동 244-79 하남사우나서울특별시 용산구 후암로28길 38, 하남사우나 지하 1층 (후암동)4331하남사우나 내 이발2024-01-31 13:40:31U2023-12-02 00:02:00.0일반이용업198101.445233449672.909205<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45530200003020000-203-2022-0000420220623<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.32140863서울특별시 용산구 이태원동 72-29 1층,2층,3층서울특별시 용산구 이태원로20가길 17, 1층,2층,3층 (이태원동)4391레커(LEKKER)2022-06-23 15:51:50I2021-12-05 22:05:00.0일반이용업199324.602461447922.52795<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45630200003020000-203-2022-0000520220922<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.91140013서울특별시 용산구 한강로3가 98서울특별시 용산구 서빙고로 17, 제몰동 1층 144호 (한강로3가)4387빌리캣 바버샵(해링턴스퀘어점)2022-09-22 10:17:15I2021-12-08 22:04:00.0일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45730200003020000-203-2022-0000620220928<NA>3폐업2폐업20221206<NA><NA><NA>05071337285820.0140823서울특별시 용산구 보광동 217-59서울특별시 용산구 장문로 89, 1층 (보광동)4394바버샵 엉클부스 이태원 보광점2022-12-09 13:17:30U2021-11-01 23:01:00.0일반이용업199887.952353447107.867775<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45830200003020000-203-2022-0000720221201<NA>1영업/정상1영업<NA><NA><NA><NA>02 797 062540.8140841서울특별시 용산구 용산동2가 23-3서울특별시 용산구 신흥로16길 12, 1층 (용산동2가)4339가보게이발관2022-12-01 16:27:29I2021-11-02 00:03:00.0일반이용업198803.189922449164.760068<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45930200003020000-203-2023-000012023-12-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>54.8140-863서울특별시 용산구 이태원동 63-42서울특별시 용산구 이태원로14길 29, 지층 (이태원동)4391디스토션 바버샵2023-12-04 13:54:25I2022-11-02 00:06:00.0일반이용업199147.286157447889.560706<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46030200003020000-203-2023-000022023-12-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.81140-841서울특별시 용산구 용산동2가 26-11서울특별시 용산구 신흥로14길 6, 1층 (용산동2가)4339박병호2023-12-19 11:45:01I2022-11-01 22:01:00.0일반이용업198852.217083449046.005076<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46130200003020000-203-2024-000012024-01-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>103.8140-160서울특별시 용산구 남영동 12-2서울특별시 용산구 두텁바위로 6, 4층 (남영동)4352남자머리2024-01-31 14:32:46I2023-12-02 00:02:00.0일반이용업197518.842759449200.07576<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>