Overview

Dataset statistics

Number of variables47
Number of observations607
Missing cells6098
Missing cells (%)21.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory240.2 KiB
Average record size in memory405.2 B

Variable types

Categorical20
Text7
DateTime3
Unsupported7
Numeric8
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-17928/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (53.5%)Imbalance
위생업태명 is highly imbalanced (77.5%)Imbalance
건물지하층수 is highly imbalanced (76.9%)Imbalance
사용시작지하층 is highly imbalanced (56.8%)Imbalance
사용끝지하층 is highly imbalanced (57.7%)Imbalance
한실수 is highly imbalanced (77.5%)Imbalance
양실수 is highly imbalanced (77.5%)Imbalance
욕실수 is highly imbalanced (77.5%)Imbalance
발한실여부 is highly imbalanced (98.2%)Imbalance
세탁기수 is highly imbalanced (77.5%)Imbalance
여성종사자수 is highly imbalanced (77.5%)Imbalance
남성종사자수 is highly imbalanced (77.5%)Imbalance
회수건조수 is highly imbalanced (77.5%)Imbalance
침대수 is highly imbalanced (77.5%)Imbalance
인허가취소일자 has 607 (100.0%) missing valuesMissing
폐업일자 has 69 (11.4%) missing valuesMissing
휴업시작일자 has 607 (100.0%) missing valuesMissing
휴업종료일자 has 607 (100.0%) missing valuesMissing
재개업일자 has 607 (100.0%) missing valuesMissing
전화번호 has 107 (17.6%) missing valuesMissing
도로명주소 has 437 (72.0%) missing valuesMissing
도로명우편번호 has 443 (73.0%) missing valuesMissing
좌표정보(X) has 327 (53.9%) missing valuesMissing
좌표정보(Y) has 327 (53.9%) missing valuesMissing
건물지상층수 has 22 (3.6%) missing valuesMissing
사용시작지상층 has 22 (3.6%) missing valuesMissing
사용끝지상층 has 22 (3.6%) missing valuesMissing
발한실여부 has 26 (4.3%) missing valuesMissing
좌석수 has 22 (3.6%) missing valuesMissing
조건부허가신고사유 has 607 (100.0%) missing valuesMissing
조건부허가시작일자 has 607 (100.0%) missing valuesMissing
조건부허가종료일자 has 607 (100.0%) missing valuesMissing
다중이용업소여부 has 22 (3.6%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 94 (15.5%) zerosZeros
건물지상층수 has 534 (88.0%) zerosZeros
사용시작지상층 has 426 (70.2%) zerosZeros
사용끝지상층 has 436 (71.8%) zerosZeros
좌석수 has 56 (9.2%) zerosZeros

Reproduction

Analysis started2024-05-11 06:39:47.229449
Analysis finished2024-05-11 06:39:48.513966
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3010000
607 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 607
100.0%

Length

2024-05-11T15:39:48.624724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:48.800233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 607
100.0%

관리번호
Text

UNIQUE 

Distinct607
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:39:49.075240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13354
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

Unique607 ?
Unique (%)100.0%

Sample

1st row3010000-203-1901-01357
2nd row3010000-203-1963-00971
3rd row3010000-203-1963-01237
4th row3010000-203-1963-01259
5th row3010000-203-1964-01115
ValueCountFrequency (%)
3010000-203-1901-01357 1
 
0.2%
3010000-203-2000-01508 1
 
0.2%
3010000-203-2000-01472 1
 
0.2%
3010000-203-2000-01473 1
 
0.2%
3010000-203-2000-01474 1
 
0.2%
3010000-203-2000-01475 1
 
0.2%
3010000-203-2000-01476 1
 
0.2%
3010000-203-2000-01489 1
 
0.2%
3010000-203-2000-01491 1
 
0.2%
3010000-203-2000-01493 1
 
0.2%
Other values (597) 597
98.4%
2024-05-11T15:39:49.623913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5423
40.6%
- 1821
 
13.6%
1 1750
 
13.1%
3 1451
 
10.9%
2 1093
 
8.2%
9 745
 
5.6%
8 299
 
2.2%
7 240
 
1.8%
6 188
 
1.4%
4 183
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11533
86.4%
Dash Punctuation 1821
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5423
47.0%
1 1750
 
15.2%
3 1451
 
12.6%
2 1093
 
9.5%
9 745
 
6.5%
8 299
 
2.6%
7 240
 
2.1%
6 188
 
1.6%
4 183
 
1.6%
5 161
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1821
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13354
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5423
40.6%
- 1821
 
13.6%
1 1750
 
13.1%
3 1451
 
10.9%
2 1093
 
8.2%
9 745
 
5.6%
8 299
 
2.2%
7 240
 
1.8%
6 188
 
1.4%
4 183
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5423
40.6%
- 1821
 
13.6%
1 1750
 
13.1%
3 1451
 
10.9%
2 1093
 
8.2%
9 745
 
5.6%
8 299
 
2.2%
7 240
 
1.8%
6 188
 
1.4%
4 183
 
1.4%
Distinct559
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1901-11-07 00:00:00
Maximum2023-07-17 00:00:00
2024-05-11T15:39:49.877943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:50.138806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3
538 
1
69 

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 (%)
3 538
88.6%
1 69
 
11.4%

Length

2024-05-11T15:39:50.437796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:50.636964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 538
88.6%
1 69
 
11.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
538 
영업/정상
69 

Length

Max length5
Median length2
Mean length2.3410214
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 538
88.6%
영업/정상 69
 
11.4%

Length

2024-05-11T15:39:50.812980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:50.993495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 538
88.6%
영업/정상 69
 
11.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2
538 
1
69 

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 (%)
2 538
88.6%
1 69
 
11.4%

Length

2024-05-11T15:39:51.160342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:51.317853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 538
88.6%
1 69
 
11.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
538 
영업
69 

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 538
88.6%
영업 69
 
11.4%

Length

2024-05-11T15:39:51.472050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:51.622261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 538
88.6%
영업 69
 
11.4%

폐업일자
Text

MISSING 

Distinct445
Distinct (%)82.7%
Missing69
Missing (%)11.4%
Memory size4.9 KiB
2024-05-11T15:39:52.031736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0334572
Min length8

Characters and Unicode

Total characters4322
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)76.8%

Sample

1st row19960306
2nd row19971110
3rd row19980829
4th row20070903
5th row20080328
ValueCountFrequency (%)
19971110 27
 
5.0%
20090609 18
 
3.3%
20041125 11
 
2.0%
19980730 6
 
1.1%
20060424 5
 
0.9%
20041124 4
 
0.7%
19960306 3
 
0.6%
20180718 3
 
0.6%
20070801 2
 
0.4%
20120427 2
 
0.4%
Other values (435) 457
84.9%
2024-05-11T15:39:52.965680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1358
31.4%
2 779
18.0%
1 775
17.9%
9 435
 
10.1%
7 194
 
4.5%
4 167
 
3.9%
3 161
 
3.7%
6 154
 
3.6%
5 140
 
3.2%
8 140
 
3.2%
Other values (2) 19
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4303
99.6%
Dash Punctuation 18
 
0.4%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1358
31.6%
2 779
18.1%
1 775
18.0%
9 435
 
10.1%
7 194
 
4.5%
4 167
 
3.9%
3 161
 
3.7%
6 154
 
3.6%
5 140
 
3.3%
8 140
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4322
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1358
31.4%
2 779
18.0%
1 775
17.9%
9 435
 
10.1%
7 194
 
4.5%
4 167
 
3.9%
3 161
 
3.7%
6 154
 
3.6%
5 140
 
3.2%
8 140
 
3.2%
Other values (2) 19
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1358
31.4%
2 779
18.0%
1 775
17.9%
9 435
 
10.1%
7 194
 
4.5%
4 167
 
3.9%
3 161
 
3.7%
6 154
 
3.6%
5 140
 
3.2%
8 140
 
3.2%
Other values (2) 19
 
0.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB

전화번호
Text

MISSING 

Distinct418
Distinct (%)83.6%
Missing107
Missing (%)17.6%
Memory size4.9 KiB
2024-05-11T15:39:53.568028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.93
Min length2

Characters and Unicode

Total characters4965
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

Unique391 ?
Unique (%)78.2%

Sample

1st row02 7774316
2nd row0203928985
3rd row0202663779
4th row0222355467
5th row0222382354
ValueCountFrequency (%)
02 235
31.8%
0200000000 29
 
3.9%
00000 20
 
2.7%
0 7
 
0.9%
0222378067 3
 
0.4%
2354613 2
 
0.3%
7784120 2
 
0.3%
7552839 2
 
0.3%
7748046 2
 
0.3%
0222325043 2
 
0.3%
Other values (416) 435
58.9%
2024-05-11T15:39:54.500598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1153
23.2%
0 1108
22.3%
7 511
10.3%
3 393
 
7.9%
5 325
 
6.5%
320
 
6.4%
6 274
 
5.5%
8 236
 
4.8%
4 220
 
4.4%
9 215
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4645
93.6%
Space Separator 320
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1153
24.8%
0 1108
23.9%
7 511
11.0%
3 393
 
8.5%
5 325
 
7.0%
6 274
 
5.9%
8 236
 
5.1%
4 220
 
4.7%
9 215
 
4.6%
1 210
 
4.5%
Space Separator
ValueCountFrequency (%)
320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4965
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1153
23.2%
0 1108
22.3%
7 511
10.3%
3 393
 
7.9%
5 325
 
6.5%
320
 
6.4%
6 274
 
5.5%
8 236
 
4.8%
4 220
 
4.4%
9 215
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4965
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1153
23.2%
0 1108
22.3%
7 511
10.3%
3 393
 
7.9%
5 325
 
6.5%
320
 
6.4%
6 274
 
5.5%
8 236
 
4.8%
4 220
 
4.4%
9 215
 
4.3%

소재지면적
Real number (ℝ)

ZEROS 

Distinct377
Distinct (%)62.4%
Missing3
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean31.39707
Minimum0
Maximum135.1
Zeros94
Zeros (%)15.5%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:39:54.857578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.94
median24.445
Q345
95-th percentile87.97
Maximum135.1
Range135.1
Interquartile range (IQR)33.06

Descriptive statistics

Standard deviation26.830932
Coefficient of variation (CV)0.85456803
Kurtosis1.0679676
Mean31.39707
Median Absolute Deviation (MAD)14.545
Skewness1.1033029
Sum18963.83
Variance719.89891
MonotonicityNot monotonic
2024-05-11T15:39:55.177779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 94
 
15.5%
33.0 11
 
1.8%
66.0 10
 
1.6%
10.0 9
 
1.5%
99.0 7
 
1.2%
13.2 6
 
1.0%
16.5 6
 
1.0%
24.0 6
 
1.0%
49.5 6
 
1.0%
59.4 5
 
0.8%
Other values (367) 444
73.1%
ValueCountFrequency (%)
0.0 94
15.5%
3.3 1
 
0.2%
6.0 3
 
0.5%
6.6 2
 
0.3%
7.0 1
 
0.2%
8.04 1
 
0.2%
8.37 1
 
0.2%
8.75 3
 
0.5%
9.0 2
 
0.3%
9.5 1
 
0.2%
ValueCountFrequency (%)
135.1 1
0.2%
132.0 1
0.2%
123.75 1
0.2%
121.0 1
0.2%
120.0 1
0.2%
112.0 1
0.2%
110.54 1
0.2%
109.29 1
0.2%
108.96 1
0.2%
107.58 1
0.2%
Distinct137
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:39:55.737848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0230643
Min length6

Characters and Unicode

Total characters3656
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

Unique50 ?
Unique (%)8.2%

Sample

1st row100191
2nd row100372
3rd row100392
4th row100450
5th row100828
ValueCountFrequency (%)
100450 65
 
10.7%
100440 19
 
3.1%
100101 15
 
2.5%
100360 14
 
2.3%
100070 14
 
2.3%
100095 13
 
2.1%
100281 13
 
2.1%
100051 12
 
2.0%
100411 12
 
2.0%
100192 12
 
2.0%
Other values (127) 418
68.9%
2024-05-11T15:39:56.521707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1642
44.9%
1 899
24.6%
8 195
 
5.3%
4 178
 
4.9%
2 166
 
4.5%
5 158
 
4.3%
3 143
 
3.9%
9 121
 
3.3%
7 71
 
1.9%
6 69
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3642
99.6%
Dash Punctuation 14
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1642
45.1%
1 899
24.7%
8 195
 
5.4%
4 178
 
4.9%
2 166
 
4.6%
5 158
 
4.3%
3 143
 
3.9%
9 121
 
3.3%
7 71
 
1.9%
6 69
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3656
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1642
44.9%
1 899
24.6%
8 195
 
5.3%
4 178
 
4.9%
2 166
 
4.5%
5 158
 
4.3%
3 143
 
3.9%
9 121
 
3.3%
7 71
 
1.9%
6 69
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1642
44.9%
1 899
24.6%
8 195
 
5.3%
4 178
 
4.9%
2 166
 
4.5%
5 158
 
4.3%
3 143
 
3.9%
9 121
 
3.3%
7 71
 
1.9%
6 69
 
1.9%
Distinct543
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:39:56.996496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.049423
Min length16

Characters and Unicode

Total characters13991
Distinct characters178
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

Unique485 ?
Unique (%)79.9%

Sample

1st row서울특별시 중구 을지로1가 37-5번지
2nd row서울특별시 중구 만리동2가 12-59번지
3rd row서울특별시 중구 장충동2가 193-39번지
4th row서울특별시 중구 신당동 34-1번지
5th row서울특별시 중구 신당동 353-120번지 상가주택1호
ValueCountFrequency (%)
서울특별시 607
23.1%
중구 607
23.1%
신당동 102
 
3.9%
황학동 38
 
1.4%
중림동 26
 
1.0%
남대문로5가 23
 
0.9%
지하1층 21
 
0.8%
회현동1가 20
 
0.8%
을지로6가 20
 
0.8%
을지로2가 17
 
0.6%
Other values (656) 1143
43.6%
2024-05-11T15:39:57.712264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2600
18.6%
682
 
4.9%
1 662
 
4.7%
635
 
4.5%
624
 
4.5%
612
 
4.4%
610
 
4.4%
608
 
4.3%
607
 
4.3%
607
 
4.3%
Other values (168) 5744
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8101
57.9%
Decimal Number 2714
 
19.4%
Space Separator 2600
 
18.6%
Dash Punctuation 548
 
3.9%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%
Uppercase Letter 4
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
682
 
8.4%
635
 
7.8%
624
 
7.7%
612
 
7.6%
610
 
7.5%
608
 
7.5%
607
 
7.5%
607
 
7.5%
563
 
6.9%
434
 
5.4%
Other values (151) 2119
26.2%
Decimal Number
ValueCountFrequency (%)
1 662
24.4%
2 454
16.7%
3 293
10.8%
0 255
 
9.4%
5 227
 
8.4%
4 207
 
7.6%
6 166
 
6.1%
7 159
 
5.9%
8 148
 
5.5%
9 143
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2600
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 548
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8101
57.9%
Common 5886
42.1%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
682
 
8.4%
635
 
7.8%
624
 
7.7%
612
 
7.6%
610
 
7.5%
608
 
7.5%
607
 
7.5%
607
 
7.5%
563
 
6.9%
434
 
5.4%
Other values (151) 2119
26.2%
Common
ValueCountFrequency (%)
2600
44.2%
1 662
 
11.2%
- 548
 
9.3%
2 454
 
7.7%
3 293
 
5.0%
0 255
 
4.3%
5 227
 
3.9%
4 207
 
3.5%
6 166
 
2.8%
7 159
 
2.7%
Other values (6) 315
 
5.4%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8101
57.9%
ASCII 5890
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2600
44.1%
1 662
 
11.2%
- 548
 
9.3%
2 454
 
7.7%
3 293
 
5.0%
0 255
 
4.3%
5 227
 
3.9%
4 207
 
3.5%
6 166
 
2.8%
7 159
 
2.7%
Other values (7) 319
 
5.4%
Hangul
ValueCountFrequency (%)
682
 
8.4%
635
 
7.8%
624
 
7.7%
612
 
7.6%
610
 
7.5%
608
 
7.5%
607
 
7.5%
607
 
7.5%
563
 
6.9%
434
 
5.4%
Other values (151) 2119
26.2%

도로명주소
Text

MISSING 

Distinct165
Distinct (%)97.1%
Missing437
Missing (%)72.0%
Memory size4.9 KiB
2024-05-11T15:39:58.209925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length46
Mean length29.729412
Min length20

Characters and Unicode

Total characters5054
Distinct characters173
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

Unique161 ?
Unique (%)94.7%

Sample

1st row서울특별시 중구 퇴계로90길 48 (신당동)
2nd row서울특별시 중구 서소문로 지하 115, 지하1층 (서소문동, 한산빌딩)
3rd row서울특별시 중구 다산로28길 34 (신당동)
4th row서울특별시 중구 청계천로 54 (삼각동, 지하1층)
5th row서울특별시 중구 세종대로18길 32 (소공동)
ValueCountFrequency (%)
서울특별시 170
 
16.8%
중구 170
 
16.8%
신당동 26
 
2.6%
2층 17
 
1.7%
지하1층 17
 
1.7%
1층 15
 
1.5%
을지로 12
 
1.2%
중림동 10
 
1.0%
소공동 10
 
1.0%
을지로6가 9
 
0.9%
Other values (321) 555
54.9%
2024-05-11T15:39:58.946944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
841
 
16.6%
212
 
4.2%
191
 
3.8%
1 185
 
3.7%
182
 
3.6%
) 178
 
3.5%
( 178
 
3.5%
175
 
3.5%
175
 
3.5%
173
 
3.4%
Other values (163) 2564
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2906
57.5%
Space Separator 841
 
16.6%
Decimal Number 800
 
15.8%
Close Punctuation 178
 
3.5%
Open Punctuation 178
 
3.5%
Other Punctuation 112
 
2.2%
Dash Punctuation 29
 
0.6%
Uppercase Letter 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
212
 
7.3%
191
 
6.6%
182
 
6.3%
175
 
6.0%
175
 
6.0%
173
 
6.0%
170
 
5.8%
170
 
5.8%
153
 
5.3%
88
 
3.0%
Other values (144) 1217
41.9%
Decimal Number
ValueCountFrequency (%)
1 185
23.1%
2 148
18.5%
3 81
10.1%
4 73
 
9.1%
0 67
 
8.4%
5 53
 
6.6%
6 52
 
6.5%
9 50
 
6.2%
7 46
 
5.8%
8 45
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 7
70.0%
L 1
 
10.0%
I 1
 
10.0%
G 1
 
10.0%
Space Separator
ValueCountFrequency (%)
841
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 178
100.0%
Other Punctuation
ValueCountFrequency (%)
, 112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2906
57.5%
Common 2138
42.3%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
212
 
7.3%
191
 
6.6%
182
 
6.3%
175
 
6.0%
175
 
6.0%
173
 
6.0%
170
 
5.8%
170
 
5.8%
153
 
5.3%
88
 
3.0%
Other values (144) 1217
41.9%
Common
ValueCountFrequency (%)
841
39.3%
1 185
 
8.7%
) 178
 
8.3%
( 178
 
8.3%
2 148
 
6.9%
, 112
 
5.2%
3 81
 
3.8%
4 73
 
3.4%
0 67
 
3.1%
5 53
 
2.5%
Other values (5) 222
 
10.4%
Latin
ValueCountFrequency (%)
B 7
70.0%
L 1
 
10.0%
I 1
 
10.0%
G 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2906
57.5%
ASCII 2148
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
841
39.2%
1 185
 
8.6%
) 178
 
8.3%
( 178
 
8.3%
2 148
 
6.9%
, 112
 
5.2%
3 81
 
3.8%
4 73
 
3.4%
0 67
 
3.1%
5 53
 
2.5%
Other values (9) 232
 
10.8%
Hangul
ValueCountFrequency (%)
212
 
7.3%
191
 
6.6%
182
 
6.3%
175
 
6.0%
175
 
6.0%
173
 
6.0%
170
 
5.8%
170
 
5.8%
153
 
5.3%
88
 
3.0%
Other values (144) 1217
41.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct77
Distinct (%)47.0%
Missing443
Missing (%)73.0%
Infinite0
Infinite (%)0.0%
Mean4561.0732
Minimum4501
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:39:59.189749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4501
5-th percentile4507
Q14533
median4556
Q34585
95-th percentile4630.25
Maximum4637
Range136
Interquartile range (IQR)52

Descriptive statistics

Standard deviation36.230103
Coefficient of variation (CV)0.0079433287
Kurtosis-0.69742432
Mean4561.0732
Median Absolute Deviation (MAD)23.5
Skewness0.35293519
Sum748016
Variance1312.6204
MonotonicityNot monotonic
2024-05-11T15:39:59.425029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4564 9
 
1.5%
4533 6
 
1.0%
4576 6
 
1.0%
4545 5
 
0.8%
4516 5
 
0.8%
4531 4
 
0.7%
4556 4
 
0.7%
4546 4
 
0.7%
4571 4
 
0.7%
4605 4
 
0.7%
Other values (67) 113
 
18.6%
(Missing) 443
73.0%
ValueCountFrequency (%)
4501 1
 
0.2%
4502 3
0.5%
4503 2
0.3%
4504 1
 
0.2%
4506 1
 
0.2%
4507 3
0.5%
4508 1
 
0.2%
4511 1
 
0.2%
4512 1
 
0.2%
4513 2
0.3%
ValueCountFrequency (%)
4637 4
0.7%
4634 2
0.3%
4633 1
 
0.2%
4631 2
0.3%
4626 1
 
0.2%
4625 1
 
0.2%
4620 1
 
0.2%
4618 2
0.3%
4617 1
 
0.2%
4616 1
 
0.2%
Distinct493
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:39:59.934709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length27
Mean length4.2372323
Min length1

Characters and Unicode

Total characters2572
Distinct characters349
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique419 ?
Unique (%)69.0%

Sample

1st row반도
2nd row선미
3rd row대덕
4th row유락
5th row신성
ValueCountFrequency (%)
이용원 13
 
1.9%
바버샵 13
 
1.9%
엉클부스 9
 
1.3%
이발소 7
 
1.0%
이발관 5
 
0.7%
한일 5
 
0.7%
현대 5
 
0.7%
동화 5
 
0.7%
제일 4
 
0.6%
대우 4
 
0.6%
Other values (505) 612
89.7%
2024-05-11T15:40:00.759195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
6.8%
122
 
4.7%
114
 
4.4%
75
 
2.9%
53
 
2.1%
52
 
2.0%
50
 
1.9%
48
 
1.9%
48
 
1.9%
46
 
1.8%
Other values (339) 1790
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2357
91.6%
Space Separator 75
 
2.9%
Modifier Symbol 40
 
1.6%
Uppercase Letter 38
 
1.5%
Lowercase Letter 28
 
1.1%
Close Punctuation 13
 
0.5%
Open Punctuation 13
 
0.5%
Decimal Number 7
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
174
 
7.4%
122
 
5.2%
114
 
4.8%
53
 
2.2%
52
 
2.2%
50
 
2.1%
48
 
2.0%
48
 
2.0%
46
 
2.0%
43
 
1.8%
Other values (297) 1607
68.2%
Uppercase Letter
ValueCountFrequency (%)
R 6
15.8%
E 4
 
10.5%
A 3
 
7.9%
B 3
 
7.9%
H 3
 
7.9%
T 2
 
5.3%
P 2
 
5.3%
I 2
 
5.3%
L 2
 
5.3%
G 1
 
2.6%
Other values (10) 10
26.3%
Lowercase Letter
ValueCountFrequency (%)
r 4
14.3%
e 4
14.3%
b 3
10.7%
s 3
10.7%
o 3
10.7%
h 2
7.1%
a 2
7.1%
p 2
7.1%
y 2
7.1%
l 1
 
3.6%
Other values (2) 2
7.1%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
2 2
28.6%
3 1
14.3%
0 1
14.3%
4 1
14.3%
Space Separator
ValueCountFrequency (%)
75
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2357
91.6%
Common 149
 
5.8%
Latin 66
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
174
 
7.4%
122
 
5.2%
114
 
4.8%
53
 
2.2%
52
 
2.2%
50
 
2.1%
48
 
2.0%
48
 
2.0%
46
 
2.0%
43
 
1.8%
Other values (297) 1607
68.2%
Latin
ValueCountFrequency (%)
R 6
 
9.1%
E 4
 
6.1%
r 4
 
6.1%
e 4
 
6.1%
A 3
 
4.5%
B 3
 
4.5%
b 3
 
4.5%
H 3
 
4.5%
s 3
 
4.5%
o 3
 
4.5%
Other values (22) 30
45.5%
Common
ValueCountFrequency (%)
75
50.3%
` 40
26.8%
) 13
 
8.7%
( 13
 
8.7%
1 2
 
1.3%
2 2
 
1.3%
& 1
 
0.7%
3 1
 
0.7%
0 1
 
0.7%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2357
91.6%
ASCII 215
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
174
 
7.4%
122
 
5.2%
114
 
4.8%
53
 
2.2%
52
 
2.2%
50
 
2.1%
48
 
2.0%
48
 
2.0%
46
 
2.0%
43
 
1.8%
Other values (297) 1607
68.2%
ASCII
ValueCountFrequency (%)
75
34.9%
` 40
18.6%
) 13
 
6.0%
( 13
 
6.0%
R 6
 
2.8%
E 4
 
1.9%
r 4
 
1.9%
e 4
 
1.9%
A 3
 
1.4%
B 3
 
1.4%
Other values (32) 50
23.3%
Distinct338
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1999-03-04 00:00:00
Maximum2024-04-22 14:30:40
2024-05-11T15:40:01.021881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:01.250473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
I
547 
U
60 

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 547
90.1%
U 60
 
9.9%

Length

2024-05-11T15:40:01.476872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:01.659339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 547
90.1%
u 60
 
9.9%
Distinct65
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:09:00
2024-05-11T15:40:01.853937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:02.149649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
일반이용업
607 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 607
100.0%

Length

2024-05-11T15:40:02.445189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:02.670895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 607
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct227
Distinct (%)81.1%
Missing327
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean199409.22
Minimum196698.94
Maximum201962.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:40:02.858072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196698.94
5-th percentile197142.65
Q1198141.35
median199367.18
Q3200619.86
95-th percentile201705.97
Maximum201962.77
Range5263.8265
Interquartile range (IQR)2478.5042

Descriptive statistics

Standard deviation1475.5915
Coefficient of variation (CV)0.007399816
Kurtosis-1.1808785
Mean199409.22
Median Absolute Deviation (MAD)1235.2506
Skewness0.025891022
Sum55834582
Variance2177370.4
MonotonicityNot monotonic
2024-05-11T15:40:03.412591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200573.641273539 9
 
1.5%
198259.65357739 5
 
0.8%
199526.416139264 4
 
0.7%
197156.145532304 3
 
0.5%
198000.967176821 3
 
0.5%
197258.590020479 3
 
0.5%
200750.455125653 3
 
0.5%
200463.625303538 3
 
0.5%
198744.433228989 3
 
0.5%
197762.501510022 3
 
0.5%
Other values (217) 241
39.7%
(Missing) 327
53.9%
ValueCountFrequency (%)
196698.938913062 1
 
0.2%
196743.854095597 1
 
0.2%
196761.687610065 1
 
0.2%
196802.101602651 1
 
0.2%
196864.942838297 3
0.5%
196944.331847873 1
 
0.2%
196948.933328771 1
 
0.2%
197010.426880715 1
 
0.2%
197037.368787577 1
 
0.2%
197107.072024703 1
 
0.2%
ValueCountFrequency (%)
201962.76537651 1
 
0.2%
201921.015036258 1
 
0.2%
201836.842939791 1
 
0.2%
201826.338461468 1
 
0.2%
201823.908977364 2
0.3%
201821.703236371 1
 
0.2%
201809.698959628 1
 
0.2%
201801.667760135 1
 
0.2%
201782.858463548 1
 
0.2%
201781.069682976 3
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)81.4%
Missing327
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean451186.53
Minimum449638.82
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:40:03.635871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449638.82
5-th percentile450245.26
Q1450871.33
median451256.19
Q3451609.82
95-th percentile451816.84
Maximum452076.82
Range2437.9944
Interquartile range (IQR)738.48742

Descriptive statistics

Standard deviation501.64102
Coefficient of variation (CV)0.0011118262
Kurtosis0.072430845
Mean451186.53
Median Absolute Deviation (MAD)364.25474
Skewness-0.72631431
Sum1.2633223 × 108
Variance251643.71
MonotonicityNot monotonic
2024-05-11T15:40:03.895057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451621.036467544 9
 
1.5%
451392.198218657 5
 
0.8%
451693.211256949 4
 
0.7%
450649.69804319 3
 
0.5%
451745.025547093 3
 
0.5%
451650.507619575 3
 
0.5%
450606.976833455 3
 
0.5%
449638.824308081 3
 
0.5%
450497.460903907 3
 
0.5%
451680.643551643 3
 
0.5%
Other values (218) 241
39.7%
(Missing) 327
53.9%
ValueCountFrequency (%)
449638.824308081 3
0.5%
449809.744684888 1
 
0.2%
450044.630607241 1
 
0.2%
450054.422130374 1
 
0.2%
450077.627204846 1
 
0.2%
450093.361161044 1
 
0.2%
450100.127638921 2
0.3%
450130.873093391 1
 
0.2%
450138.76808486 1
 
0.2%
450154.733137123 1
 
0.2%
ValueCountFrequency (%)
452076.818664092 2
0.3%
452025.526057499 2
0.3%
451967.88007363 1
0.2%
451950.239872648 1
0.2%
451945.75542127 1
0.2%
451919.349435294 1
0.2%
451867.372461174 1
0.2%
451857.893414981 1
0.2%
451850.760951662 1
0.2%
451827.973207366 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
일반이용업
585 
<NA>
 
22

Length

Max length5
Median length5
Mean length4.9637562
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:04.121041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:04.354723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 585
96.4%
na 22
 
3.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)2.4%
Missing22
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean0.44957265
Minimum0
Maximum27
Zeros534
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:40:04.534400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum27
Range27
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2078481
Coefficient of variation (CV)4.9109929
Kurtosis79.252242
Mean0.44957265
Median Absolute Deviation (MAD)0
Skewness8.1651598
Sum263
Variance4.8745931
MonotonicityNot monotonic
2024-05-11T15:40:04.754490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 534
88.0%
3 19
 
3.1%
2 6
 
1.0%
1 6
 
1.0%
4 5
 
0.8%
5 4
 
0.7%
7 2
 
0.3%
10 2
 
0.3%
20 2
 
0.3%
24 1
 
0.2%
Other values (4) 4
 
0.7%
(Missing) 22
 
3.6%
ValueCountFrequency (%)
0 534
88.0%
1 6
 
1.0%
2 6
 
1.0%
3 19
 
3.1%
4 5
 
0.8%
5 4
 
0.7%
6 1
 
0.2%
7 2
 
0.3%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
27 1
 
0.2%
24 1
 
0.2%
20 2
 
0.3%
10 2
 
0.3%
9 1
 
0.2%
8 1
 
0.2%
7 2
 
0.3%
6 1
 
0.2%
5 4
0.7%
4 5
0.8%

건물지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
550 
1
 
28
<NA>
 
22
2
 
3
5
 
3

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 550
90.6%
1 28
 
4.6%
<NA> 22
 
3.6%
2 3
 
0.5%
5 3
 
0.5%
4 1
 
0.2%

Length

2024-05-11T15:40:04.968131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:05.153259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 550
90.6%
1 28
 
4.6%
na 22
 
3.6%
2 3
 
0.5%
5 3
 
0.5%
4 1
 
0.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)2.6%
Missing22
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean0.71452991
Minimum0
Maximum18
Zeros426
Zeros (%)70.2%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:40:05.306051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9148512
Coefficient of variation (CV)2.6798754
Kurtosis32.937531
Mean0.71452991
Median Absolute Deviation (MAD)0
Skewness5.131891
Sum418
Variance3.666655
MonotonicityNot monotonic
2024-05-11T15:40:05.485233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 426
70.2%
1 64
 
10.5%
2 51
 
8.4%
3 22
 
3.6%
4 5
 
0.8%
5 4
 
0.7%
9 3
 
0.5%
7 2
 
0.3%
12 2
 
0.3%
10 1
 
0.2%
Other values (5) 5
 
0.8%
(Missing) 22
 
3.6%
ValueCountFrequency (%)
0 426
70.2%
1 64
 
10.5%
2 51
 
8.4%
3 22
 
3.6%
4 5
 
0.8%
5 4
 
0.7%
7 2
 
0.3%
8 1
 
0.2%
9 3
 
0.5%
10 1
 
0.2%
ValueCountFrequency (%)
18 1
 
0.2%
16 1
 
0.2%
15 1
 
0.2%
14 1
 
0.2%
12 2
0.3%
10 1
 
0.2%
9 3
0.5%
8 1
 
0.2%
7 2
0.3%
5 4
0.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)2.6%
Missing22
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean0.65982906
Minimum0
Maximum18
Zeros436
Zeros (%)71.8%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:40:05.655307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8456289
Coefficient of variation (CV)2.7971318
Kurtosis36.837419
Mean0.65982906
Median Absolute Deviation (MAD)0
Skewness5.40812
Sum386
Variance3.4063459
MonotonicityNot monotonic
2024-05-11T15:40:05.822978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 436
71.8%
1 62
 
10.2%
2 47
 
7.7%
3 20
 
3.3%
4 4
 
0.7%
5 4
 
0.7%
9 3
 
0.5%
7 2
 
0.3%
10 1
 
0.2%
12 1
 
0.2%
Other values (5) 5
 
0.8%
(Missing) 22
 
3.6%
ValueCountFrequency (%)
0 436
71.8%
1 62
 
10.2%
2 47
 
7.7%
3 20
 
3.3%
4 4
 
0.7%
5 4
 
0.7%
7 2
 
0.3%
8 1
 
0.2%
9 3
 
0.5%
10 1
 
0.2%
ValueCountFrequency (%)
18 1
 
0.2%
16 1
 
0.2%
15 1
 
0.2%
14 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
9 3
0.5%
8 1
 
0.2%
7 2
0.3%
5 4
0.7%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
459 
1
106 
<NA>
 
22
2
 
13
3
 
6

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 459
75.6%
1 106
 
17.5%
<NA> 22
 
3.6%
2 13
 
2.1%
3 6
 
1.0%
8 1
 
0.2%

Length

2024-05-11T15:40:06.038572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:06.226247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 459
75.6%
1 106
 
17.5%
na 22
 
3.6%
2 13
 
2.1%
3 6
 
1.0%
8 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
462 
1
105 
<NA>
 
22
2
 
13
3
 
4

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 462
76.1%
1 105
 
17.3%
<NA> 22
 
3.6%
2 13
 
2.1%
3 4
 
0.7%
8 1
 
0.2%

Length

2024-05-11T15:40:06.425985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:06.621348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 462
76.1%
1 105
 
17.3%
na 22
 
3.6%
2 13
 
2.1%
3 4
 
0.7%
8 1
 
0.2%

한실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:06.849779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:07.040875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

양실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:07.236308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:07.383019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

욕실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:07.529136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:07.671593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing26
Missing (%)4.3%
Memory size1.3 KiB
False
580 
True
 
1
(Missing)
 
26
ValueCountFrequency (%)
False 580
95.6%
True 1
 
0.2%
(Missing) 26
 
4.3%
2024-05-11T15:40:07.779491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)2.9%
Missing22
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean4.6547009
Minimum0
Maximum19
Zeros56
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:40:07.913134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q37
95-th percentile10
Maximum19
Range19
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0470763
Coefficient of variation (CV)0.65462344
Kurtosis0.47660352
Mean4.6547009
Median Absolute Deviation (MAD)2
Skewness0.60253048
Sum2723
Variance9.2846739
MonotonicityNot monotonic
2024-05-11T15:40:08.063439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3 97
16.0%
2 95
15.7%
5 59
9.7%
7 59
9.7%
0 56
9.2%
6 50
8.2%
4 49
8.1%
8 46
7.6%
9 29
 
4.8%
10 21
 
3.5%
Other values (7) 24
 
4.0%
(Missing) 22
 
3.6%
ValueCountFrequency (%)
0 56
9.2%
1 9
 
1.5%
2 95
15.7%
3 97
16.0%
4 49
8.1%
5 59
9.7%
6 50
8.2%
7 59
9.7%
8 46
7.6%
9 29
 
4.8%
ValueCountFrequency (%)
19 1
 
0.2%
16 1
 
0.2%
15 2
 
0.3%
13 1
 
0.2%
12 2
 
0.3%
11 8
 
1.3%
10 21
 
3.5%
9 29
4.8%
8 46
7.6%
7 59
9.7%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing607
Missing (%)100.0%
Memory size5.5 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
510 
임대
97 

Length

Max length4
Median length4
Mean length3.6803954
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> 510
84.0%
임대 97
 
16.0%

Length

2024-05-11T15:40:08.244612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:08.416044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 510
84.0%
임대 97
 
16.0%

세탁기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:08.607681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:08.778202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:08.974669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:09.138562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:09.306642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:09.503131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

회수건조수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:09.656497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:09.817531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
585 
<NA>
 
22

Length

Max length4
Median length1
Mean length1.1087315
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 585
96.4%
<NA> 22
 
3.6%

Length

2024-05-11T15:40:09.991138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:40:10.150061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 585
96.4%
na 22
 
3.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing22
Missing (%)3.6%
Memory size1.3 KiB
False
585 
(Missing)
 
22
ValueCountFrequency (%)
False 585
96.4%
(Missing) 22
 
3.6%
2024-05-11T15:40:10.291466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030100003010000-203-1901-0135719011107<NA>3폐업2폐업19960306<NA><NA><NA>02 777431675.36100191서울특별시 중구 을지로1가 37-5번지<NA><NA>반도2001-10-08 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N9<NA><NA><NA><NA>00000N
130100003010000-203-1963-0097119630619<NA>3폐업2폐업19971110<NA><NA><NA>02039289850.0100372서울특별시 중구 만리동2가 12-59번지<NA><NA>선미2001-10-08 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N3<NA><NA><NA><NA>00000N
230100003010000-203-1963-0123719630607<NA>3폐업2폐업19980829<NA><NA><NA>020266377921.6100392서울특별시 중구 장충동2가 193-39번지<NA><NA>대덕2001-10-08 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N0<NA><NA><NA><NA>00000N
330100003010000-203-1963-0125919630704<NA>3폐업2폐업20070903<NA><NA><NA><NA>24.09100450서울특별시 중구 신당동 34-1번지<NA><NA>유락2006-11-10 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업001100000N5<NA><NA><NA><NA>00000N
430100003010000-203-1964-0111519640122<NA>3폐업2폐업20080328<NA><NA><NA>022235546713.76100828서울특별시 중구 신당동 353-120번지 상가주택1호<NA><NA>신성2006-11-10 00:00:00I2018-08-31 23:59:59.0일반이용업200663.63168450054.42213일반이용업001100000N2<NA><NA><NA><NA>00000N
530100003010000-203-1964-0121719640128<NA>1영업/정상1영업<NA><NA><NA><NA>022238235413.2100819서울특별시 중구 신당동 156-11번지서울특별시 중구 퇴계로90길 48 (신당동)4583덕원2011-08-03 09:47:02I2018-08-31 23:59:59.0일반이용업201836.84294451216.268401일반이용업001100000N2<NA><NA><NA><NA>00000N
630100003010000-203-1964-0121819640718<NA>3폐업2폐업20090528<NA><NA><NA>02 7329951<NA>100101서울특별시 중구 태평로1가 31번지<NA><NA>시청구내2009-05-28 11:14:04I2018-08-31 23:59:59.0일반이용업198004.737917451589.338994일반이용업000000000N19<NA><NA><NA><NA>00000N
730100003010000-203-1965-0129419650721<NA>3폐업2폐업20171113<NA><NA><NA>02 753975989.65100813서울특별시 중구 서소문동 47-2번지 한산빌딩 지하1층서울특별시 중구 서소문로 지하 115, 지하1층 (서소문동, 한산빌딩)<NA>성은이용원2017-11-13 10:28:22I2018-08-31 23:59:59.0일반이용업197591.838492451245.243387일반이용업000011000N5<NA><NA><NA>임대00000N
830100003010000-203-1966-0100619661217<NA>3폐업2폐업19951028<NA><NA><NA>02 0000027.14100330서울특별시 중구 주교동 139-1번지<NA><NA>우진2001-10-08 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N5<NA><NA><NA><NA>00000N
930100003010000-203-1966-0116219660725<NA>3폐업2폐업19960718<NA><NA><NA>02 000000.0100195서울특별시 중구 을지로5가 272-6번지<NA><NA>고바우2001-10-08 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N0<NA><NA><NA><NA>00000N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
59730100003010000-203-2022-0000120220216<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.36100371서울특별시 중구 만리동1가 231서울특별시 중구 만리재로33길 21, 상가동 102호 (만리동1가, LIG 서울역 리가)4501빌트 바버샵2022-02-16 16:04:29I2022-02-18 00:22:37.0일반이용업197010.426881450402.802353일반이용업001100000N2<NA><NA><NA>임대00000N
59830100003010000-203-2022-0000220220426<NA>3폐업2폐업20230117<NA><NA><NA><NA>14.17100340서울특별시 중구 산림동 207-2서울특별시 중구 을지로 157, 2층 다열 274호 (산림동)4545엉클부스 익스프레스2023-01-17 13:32:26U2022-11-30 23:09:00.0일반이용업199526.416139451693.211257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59930100003010000-203-2022-000032022-06-22<NA>3폐업2폐업2024-03-12<NA><NA><NA><NA>80.0100-850서울특별시 중구 을지로6가 17-2서울특별시 중구 장충단로13길 20, 6층 (을지로6가)4563마제스티 동대문2024-03-12 09:12:01U2023-12-02 23:04:00.0일반이용업200613.510298451817.515367<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60030100003010000-203-2022-000042022-07-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.3100-874서울특별시 중구 회현동1가 180-2 광주약국서울특별시 중구 퇴계로6길 5, 2층 (회현동1가)4634나눔이발관2024-03-12 10:48:01U2023-12-02 23:04:00.0일반이용업198015.667603450640.47116<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60130100003010000-203-2022-0000520221018<NA>1영업/정상1영업<NA><NA><NA><NA><NA>80.26100826서울특별시 중구 신당동 340-37서울특별시 중구 동호로10길 55, 지하1층 (신당동)4590웨슬리바버샵(Wesley Barbershop)2022-10-18 11:32:18I2021-10-30 22:00:00.0일반이용업201048.794294450449.292307<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60230100003010000-203-2022-000062022-12-08<NA>3폐업2폐업2023-06-16<NA><NA><NA><NA>37.42100-851서울특별시 중구 을지로6가 18-21서울특별시 중구 장충단로 247, 9층 902-19호 (을지로6가)4564바버샵 엉클부스2023-06-16 20:23:48U2022-12-05 23:08:00.0일반이용업200573.641274451621.036468<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60330100003010000-203-2023-000012023-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>72.37100-859서울특별시 중구 중림동 200서울특별시 중구 중림로 10, 상가3동 203호 (중림동, 중림동 삼성 사이버 빌리지)4502203 바버샵2024-04-17 11:50:28U2023-12-03 23:09:00.0일반이용업196864.942838450649.698043<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60430100003010000-203-2023-000022023-01-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.32100-273서울특별시 중구 필동3가 34서울특별시 중구 필동로 24, 2층 (필동3가)4626영호룸2023-06-28 16:05:43U2022-12-05 21:00:00.0일반이용업199581.574642450809.821248<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60530100003010000-203-2023-000032023-06-27<NA>3폐업2폐업2024-04-22<NA><NA><NA>022275582837.42100-851서울특별시 중구 을지로6가 18-21서울특별시 중구 장충단로 247, 9층 902-19호 (을지로6가)4564바버샵 엉클부스2024-04-22 14:30:40U2023-12-03 22:04:00.0일반이용업200573.641274451621.036468<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60630100003010000-203-2023-000042023-07-17<NA>3폐업2폐업2024-02-20<NA><NA><NA>022268285814.17100-340서울특별시 중구 산림동 207-2서울특별시 중구 을지로 157, 2층 다274호 (산림동)4545엉클부스2024-02-20 15:10:51U2023-12-01 22:02:00.0일반이용업199526.416139451693.211257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>