Overview

Dataset statistics

Number of variables47
Number of observations4443
Missing cells50583
Missing cells (%)24.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory405.0 B

Variable types

Categorical18
Text6
DateTime4
Unsupported7
Numeric10
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-17926/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (54.3%)Imbalance
사용시작지하층 is highly imbalanced (61.9%)Imbalance
사용끝지하층 is highly imbalanced (78.9%)Imbalance
여성종사자수 is highly imbalanced (69.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.3%)Imbalance
인허가취소일자 has 4443 (100.0%) missing valuesMissing
폐업일자 has 1500 (33.8%) missing valuesMissing
휴업시작일자 has 4443 (100.0%) missing valuesMissing
휴업종료일자 has 4443 (100.0%) missing valuesMissing
재개업일자 has 4443 (100.0%) missing valuesMissing
전화번호 has 1903 (42.8%) missing valuesMissing
도로명주소 has 1683 (37.9%) missing valuesMissing
도로명우편번호 has 1702 (38.3%) missing valuesMissing
좌표정보(X) has 89 (2.0%) missing valuesMissing
좌표정보(Y) has 89 (2.0%) missing valuesMissing
건물지상층수 has 1272 (28.6%) missing valuesMissing
건물지하층수 has 1567 (35.3%) missing valuesMissing
사용시작지상층 has 1642 (37.0%) missing valuesMissing
사용끝지상층 has 2452 (55.2%) missing valuesMissing
발한실여부 has 936 (21.1%) missing valuesMissing
좌석수 has 981 (22.1%) missing valuesMissing
조건부허가신고사유 has 4443 (100.0%) missing valuesMissing
조건부허가시작일자 has 4443 (100.0%) missing valuesMissing
조건부허가종료일자 has 4443 (100.0%) missing valuesMissing
침대수 has 2784 (62.7%) missing valuesMissing
다중이용업소여부 has 880 (19.8%) 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 83 (1.9%) zerosZeros
건물지상층수 has 2034 (45.8%) zerosZeros
건물지하층수 has 2352 (52.9%) zerosZeros
사용시작지상층 has 797 (17.9%) zerosZeros
사용끝지상층 has 126 (2.8%) zerosZeros
좌석수 has 300 (6.8%) zerosZeros
침대수 has 1160 (26.1%) zerosZeros

Reproduction

Analysis started2024-04-17 20:12:27.429015
Analysis finished2024-04-17 20:12:28.649935
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
3240000
4443 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 4443
100.0%

Length

2024-04-18T05:12:28.701421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:28.785558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 4443
100.0%

관리번호
Text

UNIQUE 

Distinct4443
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
2024-04-18T05:12:28.925470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters97746
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

Unique4443 ?
Unique (%)100.0%

Sample

1st row3240000-204-1920-00847
2nd row3240000-204-1978-01556
3rd row3240000-204-1979-01521
4th row3240000-204-1979-01544
5th row3240000-204-1979-01551
ValueCountFrequency (%)
3240000-204-1920-00847 1
 
< 0.1%
3240000-211-2020-00013 1
 
< 0.1%
3240000-211-2020-00019 1
 
< 0.1%
3240000-211-2020-00018 1
 
< 0.1%
3240000-211-2020-00017 1
 
< 0.1%
3240000-211-2020-00016 1
 
< 0.1%
3240000-211-2020-00015 1
 
< 0.1%
3240000-211-2020-00005 1
 
< 0.1%
3240000-211-2020-00012 1
 
< 0.1%
3240000-211-2020-00003 1
 
< 0.1%
Other values (4433) 4433
99.8%
2024-04-18T05:12:29.170029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37625
38.5%
2 15261
15.6%
- 13329
 
13.6%
1 8659
 
8.9%
4 8039
 
8.2%
3 6124
 
6.3%
9 3083
 
3.2%
8 1611
 
1.6%
5 1562
 
1.6%
6 1281
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84417
86.4%
Dash Punctuation 13329
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37625
44.6%
2 15261
18.1%
1 8659
 
10.3%
4 8039
 
9.5%
3 6124
 
7.3%
9 3083
 
3.7%
8 1611
 
1.9%
5 1562
 
1.9%
6 1281
 
1.5%
7 1172
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 13329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37625
38.5%
2 15261
15.6%
- 13329
 
13.6%
1 8659
 
8.9%
4 8039
 
8.2%
3 6124
 
6.3%
9 3083
 
3.2%
8 1611
 
1.6%
5 1562
 
1.6%
6 1281
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37625
38.5%
2 15261
15.6%
- 13329
 
13.6%
1 8659
 
8.9%
4 8039
 
8.2%
3 6124
 
6.3%
9 3083
 
3.2%
8 1611
 
1.6%
5 1562
 
1.6%
6 1281
 
1.3%

인허가일자
Date

Distinct2985
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
Minimum1920-12-20 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T05:12:29.286734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:12:29.388644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
3
2943 
1
1500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2943
66.2%
1 1500
33.8%

Length

2024-04-18T05:12:29.481470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:29.556076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2943
66.2%
1 1500
33.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
폐업
2943 
영업/정상
1500 

Length

Max length5
Median length2
Mean length3.0128292
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2943
66.2%
영업/정상 1500
33.8%

Length

2024-04-18T05:12:29.658888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:29.743008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2943
66.2%
영업/정상 1500
33.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
2
2943 
1
1500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 2943
66.2%
1 1500
33.8%

Length

2024-04-18T05:12:29.817608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:29.887702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2943
66.2%
1 1500
33.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
폐업
2943 
영업
1500 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2943
66.2%
영업 1500
33.8%

Length

2024-04-18T05:12:29.963505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:30.034451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2943
66.2%
영업 1500
33.8%

폐업일자
Date

MISSING 

Distinct2048
Distinct (%)69.6%
Missing1500
Missing (%)33.8%
Memory size34.8 KiB
Minimum1989-05-25 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T05:12:30.142884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:12:30.243027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

전화번호
Text

MISSING 

Distinct2149
Distinct (%)84.6%
Missing1903
Missing (%)42.8%
Memory size34.8 KiB
2024-04-18T05:12:30.459953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9775591
Min length2

Characters and Unicode

Total characters25343
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

Unique2013 ?
Unique (%)79.3%

Sample

1st row02 4773826
2nd row02 4781585
3rd row0204860749
4th row02 4274335
5th row0234273028
ValueCountFrequency (%)
02 1888
38.9%
070 58
 
1.2%
0200000000 51
 
1.0%
470 36
 
0.7%
442 31
 
0.6%
473 28
 
0.6%
426 28
 
0.6%
00000 26
 
0.5%
488 24
 
0.5%
481 24
 
0.5%
Other values (2165) 2664
54.8%
2024-04-18T05:12:30.785362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4677
18.5%
2 4055
16.0%
4 3374
13.3%
3087
12.2%
7 2182
8.6%
8 2002
7.9%
3 1330
 
5.2%
6 1261
 
5.0%
1 1211
 
4.8%
5 1140
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22256
87.8%
Space Separator 3087
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4677
21.0%
2 4055
18.2%
4 3374
15.2%
7 2182
9.8%
8 2002
9.0%
3 1330
 
6.0%
6 1261
 
5.7%
1 1211
 
5.4%
5 1140
 
5.1%
9 1024
 
4.6%
Space Separator
ValueCountFrequency (%)
3087
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25343
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4677
18.5%
2 4055
16.0%
4 3374
13.3%
3087
12.2%
7 2182
8.6%
8 2002
7.9%
3 1330
 
5.2%
6 1261
 
5.0%
1 1211
 
4.8%
5 1140
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25343
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4677
18.5%
2 4055
16.0%
4 3374
13.3%
3087
12.2%
7 2182
8.6%
8 2002
7.9%
3 1330
 
5.2%
6 1261
 
5.0%
1 1211
 
4.8%
5 1140
 
4.5%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1681
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.158321
Minimum0
Maximum399.36
Zeros83
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:30.902607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.343
Q119.8
median26.45
Q339.305
95-th percentile97.886
Maximum399.36
Range399.36
Interquartile range (IQR)19.505

Descriptive statistics

Standard deviation32.805392
Coefficient of variation (CV)0.90727089
Kurtosis19.905687
Mean36.158321
Median Absolute Deviation (MAD)8.43
Skewness3.6431713
Sum160651.42
Variance1076.1937
MonotonicityNot monotonic
2024-04-18T05:12:31.025679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 204
 
4.6%
26.4 125
 
2.8%
30.0 117
 
2.6%
23.1 88
 
2.0%
0.0 83
 
1.9%
20.0 74
 
1.7%
19.8 69
 
1.6%
24.0 63
 
1.4%
26.0 61
 
1.4%
16.5 48
 
1.1%
Other values (1671) 3511
79.0%
ValueCountFrequency (%)
0.0 83
1.9%
2.42 1
 
< 0.1%
3.3 4
 
0.1%
3.75 1
 
< 0.1%
3.82 1
 
< 0.1%
3.96 1
 
< 0.1%
4.17 1
 
< 0.1%
4.38 1
 
< 0.1%
5.0 2
 
< 0.1%
5.08 1
 
< 0.1%
ValueCountFrequency (%)
399.36 1
 
< 0.1%
361.86 1
 
< 0.1%
331.84 1
 
< 0.1%
319.3 1
 
< 0.1%
307.96 1
 
< 0.1%
303.31 1
 
< 0.1%
280.0 1
 
< 0.1%
278.53 1
 
< 0.1%
270.26 1
 
< 0.1%
264.0 3
0.1%

소재지우편번호
Text

Distinct171
Distinct (%)3.8%
Missing1
Missing (%)< 0.1%
Memory size34.8 KiB
2024-04-18T05:12:31.290455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0959027
Min length6

Characters and Unicode

Total characters27078
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

Unique24 ?
Unique (%)0.5%

Sample

1st row134848
2nd row134864
3rd row134864
4th row134854
5th row134830
ValueCountFrequency (%)
134830 231
 
5.2%
134864 183
 
4.1%
134861 162
 
3.6%
134859 146
 
3.3%
134867 143
 
3.2%
134840 141
 
3.2%
134841 123
 
2.8%
134890 112
 
2.5%
134874 112
 
2.5%
134880 106
 
2.4%
Other values (161) 2983
67.2%
2024-04-18T05:12:31.637773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 5718
21.1%
1 5508
20.3%
3 5100
18.8%
8 4785
17.7%
0 1522
 
5.6%
6 1053
 
3.9%
7 1001
 
3.7%
5 825
 
3.0%
2 636
 
2.3%
9 504
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26652
98.4%
Dash Punctuation 426
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5718
21.5%
1 5508
20.7%
3 5100
19.1%
8 4785
18.0%
0 1522
 
5.7%
6 1053
 
4.0%
7 1001
 
3.8%
5 825
 
3.1%
2 636
 
2.4%
9 504
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 426
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27078
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 5718
21.1%
1 5508
20.3%
3 5100
18.8%
8 4785
17.7%
0 1522
 
5.6%
6 1053
 
3.9%
7 1001
 
3.7%
5 825
 
3.0%
2 636
 
2.3%
9 504
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27078
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 5718
21.1%
1 5508
20.3%
3 5100
18.8%
8 4785
17.7%
0 1522
 
5.6%
6 1053
 
3.9%
7 1001
 
3.7%
5 825
 
3.0%
2 636
 
2.3%
9 504
 
1.9%

지번주소
Text

Distinct3737
Distinct (%)84.1%
Missing1
Missing (%)< 0.1%
Memory size34.8 KiB
2024-04-18T05:12:31.879115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length50
Mean length25.185952
Min length15

Characters and Unicode

Total characters111876
Distinct characters387
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3228 ?
Unique (%)72.7%

Sample

1st row서울특별시 강동구 성내동 271-2번지 해바라기A 상가동 1 6호
2nd row서울특별시 강동구 천호동 453-14번지
3rd row서울특별시 강동구 천호동 453-7
4th row서울특별시 강동구 암사동 424-32번지
5th row서울특별시 강동구 명일동 326-2
ValueCountFrequency (%)
서울특별시 4442
20.8%
강동구 4442
20.8%
천호동 1078
 
5.0%
성내동 999
 
4.7%
암사동 644
 
3.0%
길동 616
 
2.9%
1층 565
 
2.6%
명일동 459
 
2.1%
둔촌동 281
 
1.3%
고덕동 197
 
0.9%
Other values (3803) 7640
35.8%
2024-04-18T05:12:32.229131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19889
17.8%
동 9204
 
8.2%
1 4844
 
4.3%
강 4678
 
4.2%
시 4515
 
4.0%
서 4457
 
4.0%
구 4454
 
4.0%
울 4447
 
4.0%
별 4444
 
4.0%
특 4442
 
4.0%
Other values (377) 46502
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64682
57.8%
Decimal Number 23041
 
20.6%
Space Separator 19889
 
17.8%
Dash Punctuation 3852
 
3.4%
Close Punctuation 113
 
0.1%
Open Punctuation 113
 
0.1%
Uppercase Letter 98
 
0.1%
Other Punctuation 58
 
0.1%
Lowercase Letter 27
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9204
14.2%
강 4678
 
7.2%
시 4515
 
7.0%
서 4457
 
6.9%
구 4454
 
6.9%
울 4447
 
6.9%
별 4444
 
6.9%
특 4442
 
6.9%
지 3216
 
5.0%
번 3007
 
4.6%
Other values (322) 17818
27.5%
Lowercase Letter
ValueCountFrequency (%)
l 4
14.8%
i 3
11.1%
d 2
 
7.4%
a 2
 
7.4%
c 2
 
7.4%
y 2
 
7.4%
b 2
 
7.4%
j 1
 
3.7%
t 1
 
3.7%
x 1
 
3.7%
Other values (7) 7
25.9%
Uppercase Letter
ValueCountFrequency (%)
A 31
31.6%
G 12
 
12.2%
B 12
 
12.2%
S 10
 
10.2%
D 5
 
5.1%
K 5
 
5.1%
H 4
 
4.1%
L 4
 
4.1%
I 3
 
3.1%
R 3
 
3.1%
Other values (6) 9
 
9.2%
Decimal Number
ValueCountFrequency (%)
1 4844
21.0%
2 3094
13.4%
4 3052
13.2%
3 3012
13.1%
0 2111
9.2%
5 1924
 
8.4%
6 1325
 
5.8%
9 1289
 
5.6%
7 1232
 
5.3%
8 1158
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 43
74.1%
. 6
 
10.3%
@ 4
 
6.9%
& 2
 
3.4%
/ 2
 
3.4%
# 1
 
1.7%
Space Separator
ValueCountFrequency (%)
19889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3852
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64682
57.8%
Common 47069
42.1%
Latin 125
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9204
14.2%
강 4678
 
7.2%
시 4515
 
7.0%
서 4457
 
6.9%
구 4454
 
6.9%
울 4447
 
6.9%
별 4444
 
6.9%
특 4442
 
6.9%
지 3216
 
5.0%
번 3007
 
4.6%
Other values (322) 17818
27.5%
Latin
ValueCountFrequency (%)
A 31
24.8%
G 12
 
9.6%
B 12
 
9.6%
S 10
 
8.0%
D 5
 
4.0%
K 5
 
4.0%
l 4
 
3.2%
H 4
 
3.2%
L 4
 
3.2%
I 3
 
2.4%
Other values (23) 35
28.0%
Common
ValueCountFrequency (%)
19889
42.3%
1 4844
 
10.3%
- 3852
 
8.2%
2 3094
 
6.6%
4 3052
 
6.5%
3 3012
 
6.4%
0 2111
 
4.5%
5 1924
 
4.1%
6 1325
 
2.8%
9 1289
 
2.7%
Other values (12) 2677
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64682
57.8%
ASCII 47194
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19889
42.1%
1 4844
 
10.3%
- 3852
 
8.2%
2 3094
 
6.6%
4 3052
 
6.5%
3 3012
 
6.4%
0 2111
 
4.5%
5 1924
 
4.1%
6 1325
 
2.8%
9 1289
 
2.7%
Other values (45) 2802
 
5.9%
Hangul
ValueCountFrequency (%)
동 9204
14.2%
강 4678
 
7.2%
시 4515
 
7.0%
서 4457
 
6.9%
구 4454
 
6.9%
울 4447
 
6.9%
별 4444
 
6.9%
특 4442
 
6.9%
지 3216
 
5.0%
번 3007
 
4.6%
Other values (322) 17818
27.5%

도로명주소
Text

MISSING 

Distinct2496
Distinct (%)90.4%
Missing1683
Missing (%)37.9%
Memory size34.8 KiB
2024-04-18T05:12:32.429547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length33.502899
Min length17

Characters and Unicode

Total characters92468
Distinct characters367
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2286 ?
Unique (%)82.8%

Sample

1st row서울특별시 강동구 천호대로159길 25 (천호동)
2nd row서울특별시 강동구 상암로47길 76 (명일동)
3rd row서울특별시 강동구 진황도로27길 23 (천호동)
4th row서울특별시 강동구 올림픽로60길 21, 101호 (성내동)
5th row서울특별시 강동구 상일로17길 16, 1층 (고덕동)
ValueCountFrequency (%)
서울특별시 2760
 
15.4%
강동구 2760
 
15.4%
1층 926
 
5.2%
성내동 594
 
3.3%
천호동 579
 
3.2%
길동 367
 
2.1%
암사동 358
 
2.0%
명일동 292
 
1.6%
2층 257
 
1.4%
101호 222
 
1.2%
Other values (1881) 8779
49.1%
2024-04-18T05:12:32.756552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15135
 
16.4%
동 5941
 
6.4%
1 4888
 
5.3%
구 3054
 
3.3%
강 2995
 
3.2%
, 2904
 
3.1%
) 2837
 
3.1%
( 2837
 
3.1%
시 2826
 
3.1%
서 2772
 
3.0%
Other values (357) 46279
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51768
56.0%
Decimal Number 16614
 
18.0%
Space Separator 15135
 
16.4%
Other Punctuation 2921
 
3.2%
Close Punctuation 2837
 
3.1%
Open Punctuation 2837
 
3.1%
Dash Punctuation 221
 
0.2%
Uppercase Letter 104
 
0.1%
Lowercase Letter 26
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5941
 
11.5%
구 3054
 
5.9%
강 2995
 
5.8%
시 2826
 
5.5%
서 2772
 
5.4%
울 2763
 
5.3%
별 2762
 
5.3%
특 2760
 
5.3%
로 2687
 
5.2%
호 2502
 
4.8%
Other values (302) 20706
40.0%
Uppercase Letter
ValueCountFrequency (%)
B 36
34.6%
A 16
15.4%
S 10
 
9.6%
G 9
 
8.7%
D 5
 
4.8%
K 5
 
4.8%
H 4
 
3.8%
I 3
 
2.9%
Y 3
 
2.9%
R 3
 
2.9%
Other values (8) 10
 
9.6%
Lowercase Letter
ValueCountFrequency (%)
l 4
15.4%
i 3
11.5%
a 2
 
7.7%
c 2
 
7.7%
y 2
 
7.7%
d 2
 
7.7%
t 1
 
3.8%
j 1
 
3.8%
e 1
 
3.8%
r 1
 
3.8%
Other values (7) 7
26.9%
Decimal Number
ValueCountFrequency (%)
1 4888
29.4%
2 2208
13.3%
0 1942
 
11.7%
3 1651
 
9.9%
4 1230
 
7.4%
5 1203
 
7.2%
6 1028
 
6.2%
7 904
 
5.4%
9 830
 
5.0%
8 730
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 2904
99.4%
. 12
 
0.4%
& 2
 
0.1%
/ 2
 
0.1%
# 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2837
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51768
56.0%
Common 40570
43.9%
Latin 130
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5941
 
11.5%
구 3054
 
5.9%
강 2995
 
5.8%
시 2826
 
5.5%
서 2772
 
5.4%
울 2763
 
5.3%
별 2762
 
5.3%
특 2760
 
5.3%
로 2687
 
5.2%
호 2502
 
4.8%
Other values (302) 20706
40.0%
Latin
ValueCountFrequency (%)
B 36
27.7%
A 16
12.3%
S 10
 
7.7%
G 9
 
6.9%
D 5
 
3.8%
K 5
 
3.8%
H 4
 
3.1%
l 4
 
3.1%
i 3
 
2.3%
I 3
 
2.3%
Other values (25) 35
26.9%
Common
ValueCountFrequency (%)
15135
37.3%
1 4888
 
12.0%
, 2904
 
7.2%
) 2837
 
7.0%
( 2837
 
7.0%
2 2208
 
5.4%
0 1942
 
4.8%
3 1651
 
4.1%
4 1230
 
3.0%
5 1203
 
3.0%
Other values (10) 3735
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51768
56.0%
ASCII 40700
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15135
37.2%
1 4888
 
12.0%
, 2904
 
7.1%
) 2837
 
7.0%
( 2837
 
7.0%
2 2208
 
5.4%
0 1942
 
4.8%
3 1651
 
4.1%
4 1230
 
3.0%
5 1203
 
3.0%
Other values (45) 3865
 
9.5%
Hangul
ValueCountFrequency (%)
동 5941
 
11.5%
구 3054
 
5.9%
강 2995
 
5.8%
시 2826
 
5.5%
서 2772
 
5.4%
울 2763
 
5.3%
별 2762
 
5.3%
특 2760
 
5.3%
로 2687
 
5.2%
호 2502
 
4.8%
Other values (302) 20706
40.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct188
Distinct (%)6.9%
Missing1702
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean5318.5524
Minimum5201
Maximum5415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:33.144504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5201
5-th percentile5226
Q15266
median5326
Q35366
95-th percentile5404
Maximum5415
Range214
Interquartile range (IQR)100

Descriptive statistics

Standard deviation56.458982
Coefficient of variation (CV)0.010615479
Kurtosis-1.1576084
Mean5318.5524
Median Absolute Deviation (MAD)52
Skewness-0.16259543
Sum14578152
Variance3187.6167
MonotonicityNot monotonic
2024-04-18T05:12:33.246597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5328 57
 
1.3%
5269 53
 
1.2%
5292 51
 
1.1%
5404 50
 
1.1%
5335 48
 
1.1%
5378 46
 
1.0%
5351 45
 
1.0%
5242 44
 
1.0%
5405 42
 
0.9%
5222 42
 
0.9%
Other values (178) 2263
50.9%
(Missing) 1702
38.3%
ValueCountFrequency (%)
5201 2
 
< 0.1%
5208 2
 
< 0.1%
5210 11
0.2%
5211 22
0.5%
5212 1
 
< 0.1%
5213 1
 
< 0.1%
5214 2
 
< 0.1%
5215 4
 
0.1%
5216 2
 
< 0.1%
5217 4
 
0.1%
ValueCountFrequency (%)
5415 4
 
0.1%
5414 1
 
< 0.1%
5413 1
 
< 0.1%
5412 5
 
0.1%
5411 6
 
0.1%
5409 2
 
< 0.1%
5408 10
 
0.2%
5407 7
 
0.2%
5406 27
0.6%
5405 42
0.9%

사업장명
Text

Distinct3686
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
2024-04-18T05:12:33.461481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length5.4040063
Min length1

Characters and Unicode

Total characters24010
Distinct characters776
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3215 ?
Unique (%)72.4%

Sample

1st row청진헤어멧세지
2nd row보라
3rd row조이헤어아떼
4th row중희
5th row이현미헤어
ValueCountFrequency (%)
헤어 54
 
1.0%
네일 36
 
0.7%
hair 31
 
0.6%
미용실 29
 
0.5%
nail 19
 
0.4%
천호점 18
 
0.3%
태후사랑 16
 
0.3%
헤어샵 15
 
0.3%
에스테틱 15
 
0.3%
13
 
0.2%
Other values (3813) 5063
95.4%
2024-04-18T05:12:33.791603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 1595
 
6.6%
헤 1529
 
6.4%
871
 
3.6%
미 650
 
2.7%
스 595
 
2.5%
리 545
 
2.3%
이 503
 
2.1%
일 445
 
1.9%
용 362
 
1.5%
실 361
 
1.5%
Other values (766) 16554
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20509
85.4%
Lowercase Letter 982
 
4.1%
Space Separator 871
 
3.6%
Uppercase Letter 839
 
3.5%
Close Punctuation 215
 
0.9%
Open Punctuation 215
 
0.9%
Other Punctuation 181
 
0.8%
Decimal Number 169
 
0.7%
Dash Punctuation 21
 
0.1%
Connector Punctuation 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 1595
 
7.8%
헤 1529
 
7.5%
미 650
 
3.2%
스 595
 
2.9%
리 545
 
2.7%
이 503
 
2.5%
일 445
 
2.2%
용 362
 
1.8%
실 361
 
1.8%
네 357
 
1.7%
Other values (690) 13567
66.2%
Uppercase Letter
ValueCountFrequency (%)
N 80
 
9.5%
A 78
 
9.3%
S 74
 
8.8%
H 62
 
7.4%
O 58
 
6.9%
M 56
 
6.7%
I 52
 
6.2%
L 52
 
6.2%
J 41
 
4.9%
E 39
 
4.6%
Other values (16) 247
29.4%
Lowercase Letter
ValueCountFrequency (%)
a 147
15.0%
i 125
12.7%
e 100
10.2%
l 83
8.5%
n 79
8.0%
o 65
 
6.6%
r 61
 
6.2%
y 43
 
4.4%
h 43
 
4.4%
s 40
 
4.1%
Other values (15) 196
20.0%
Decimal Number
ValueCountFrequency (%)
0 48
28.4%
2 28
16.6%
1 25
14.8%
3 21
12.4%
5 11
 
6.5%
8 10
 
5.9%
9 7
 
4.1%
7 7
 
4.1%
4 7
 
4.1%
6 5
 
3.0%
Other Punctuation
ValueCountFrequency (%)
? 74
40.9%
& 38
21.0%
. 24
 
13.3%
# 21
 
11.6%
' 13
 
7.2%
, 7
 
3.9%
: 3
 
1.7%
＆ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
871
100.0%
Close Punctuation
ValueCountFrequency (%)
) 215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20489
85.3%
Latin 1820
 
7.6%
Common 1680
 
7.0%
Han 20
 
0.1%
Cyrillic 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 1595
 
7.8%
헤 1529
 
7.5%
미 650
 
3.2%
스 595
 
2.9%
리 545
 
2.7%
이 503
 
2.5%
일 445
 
2.2%
용 362
 
1.8%
실 361
 
1.8%
네 357
 
1.7%
Other values (684) 13547
66.1%
Latin
ValueCountFrequency (%)
a 147
 
8.1%
i 125
 
6.9%
e 100
 
5.5%
l 83
 
4.6%
N 80
 
4.4%
n 79
 
4.3%
A 78
 
4.3%
S 74
 
4.1%
o 65
 
3.6%
H 62
 
3.4%
Other values (40) 927
50.9%
Common
ValueCountFrequency (%)
871
51.8%
) 215
 
12.8%
( 215
 
12.8%
? 74
 
4.4%
0 48
 
2.9%
& 38
 
2.3%
2 28
 
1.7%
1 25
 
1.5%
. 24
 
1.4%
# 21
 
1.2%
Other values (15) 121
 
7.2%
Han
ValueCountFrequency (%)
美 15
75.0%
精 1
 
5.0%
人 1
 
5.0%
花 1
 
5.0%
秀 1
 
5.0%
姜 1
 
5.0%
Cyrillic
ValueCountFrequency (%)
Ъ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20485
85.3%
ASCII 3499
 
14.6%
CJK 20
 
0.1%
Compat Jamo 4
 
< 0.1%
Cyrillic 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 1595
 
7.8%
헤 1529
 
7.5%
미 650
 
3.2%
스 595
 
2.9%
리 545
 
2.7%
이 503
 
2.5%
일 445
 
2.2%
용 362
 
1.8%
실 361
 
1.8%
네 357
 
1.7%
Other values (682) 13543
66.1%
ASCII
ValueCountFrequency (%)
871
24.9%
) 215
 
6.1%
( 215
 
6.1%
a 147
 
4.2%
i 125
 
3.6%
e 100
 
2.9%
l 83
 
2.4%
N 80
 
2.3%
n 79
 
2.3%
A 78
 
2.2%
Other values (64) 1506
43.0%
CJK
ValueCountFrequency (%)
美 15
75.0%
精 1
 
5.0%
人 1
 
5.0%
花 1
 
5.0%
秀 1
 
5.0%
姜 1
 
5.0%
Compat Jamo
ValueCountFrequency (%)
ㅍ 3
75.0%
ㄹ 1
 
25.0%
Cyrillic
ValueCountFrequency (%)
Ъ 1
100.0%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정일자
Date

Distinct3407
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
Minimum1999-01-18 00:00:00
Maximum2024-04-16 13:30:15
2024-04-18T05:12:33.895962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:12:33.999683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
I
3072 
U
1353 
D
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3072
69.1%
U 1353
30.5%
D 18
 
0.4%

Length

2024-04-18T05:12:34.095914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:34.169849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3072
69.1%
u 1353
30.5%
d 18
 
0.4%

데이터갱신일자
Date

Distinct877
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-18T05:12:34.256117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:12:34.354778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
일반미용업
3332 
피부미용업
576 
네일아트업
409 
메이크업업
 
95
기타
 
29

Length

Max length6
Median length5
Mean length4.9808688
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 3332
75.0%
피부미용업 576
 
13.0%
네일아트업 409
 
9.2%
메이크업업 95
 
2.1%
기타 29
 
0.7%
미용업 기타 2
 
< 0.1%

Length

2024-04-18T05:12:34.456665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:34.544955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 3332
75.0%
피부미용업 576
 
13.0%
네일아트업 409
 
9.2%
메이크업업 95
 
2.1%
기타 31
 
0.7%
미용업 2
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2164
Distinct (%)49.7%
Missing89
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean212138.02
Minimum210558.1
Maximum216029.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:34.664733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210558.1
5-th percentile210905.21
Q1211403.62
median211917.07
Q3212636.86
95-th percentile214556.26
Maximum216029.39
Range5471.2924
Interquartile range (IQR)1233.2334

Descriptive statistics

Standard deviation1011.1156
Coefficient of variation (CV)0.0047663103
Kurtosis1.8406972
Mean212138.02
Median Absolute Deviation (MAD)628.92213
Skewness1.2720381
Sum9.2364893 × 108
Variance1022354.8
MonotonicityNot monotonic
2024-04-18T05:12:34.781990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
212334.9584644 43
 
1.0%
211176.084703491 28
 
0.6%
210871.293674366 26
 
0.6%
211047.878697259 19
 
0.4%
211542.314116941 17
 
0.4%
213522.288105074 17
 
0.4%
212926.089912845 16
 
0.4%
214958.713997465 16
 
0.4%
213048.692179757 15
 
0.3%
213493.90717524 15
 
0.3%
Other values (2154) 4142
93.2%
(Missing) 89
 
2.0%
ValueCountFrequency (%)
210558.095600946 1
 
< 0.1%
210573.186608263 2
< 0.1%
210575.541535172 1
 
< 0.1%
210621.633987432 1
 
< 0.1%
210626.58631048 2
< 0.1%
210634.766328037 2
< 0.1%
210638.200179834 1
 
< 0.1%
210644.063727145 2
< 0.1%
210657.072352124 3
0.1%
210661.929283313 1
 
< 0.1%
ValueCountFrequency (%)
216029.388021 4
0.1%
215888.898816 1
 
< 0.1%
215875.024969 2
 
< 0.1%
215743.278884315 1
 
< 0.1%
215728.497758 1
 
< 0.1%
215701.974291112 1
 
< 0.1%
215674.816462841 1
 
< 0.1%
215672.146934322 5
0.1%
215661.222623 1
 
< 0.1%
215659.154061 2
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2163
Distinct (%)49.7%
Missing89
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean448900.37
Minimum446462.9
Maximum452309.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:34.883058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446462.9
5-th percentile447240.13
Q1448085.85
median448878.89
Q3449733.63
95-th percentile450632.62
Maximum452309.71
Range5846.81
Interquartile range (IQR)1647.7843

Descriptive statistics

Standard deviation1053.0673
Coefficient of variation (CV)0.0023458819
Kurtosis-0.49772789
Mean448900.37
Median Absolute Deviation (MAD)827.8824
Skewness0.20022045
Sum1.9545122 × 109
Variance1108950.7
MonotonicityNot monotonic
2024-04-18T05:12:34.984473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450346.790651613 43
 
1.0%
448449.888935391 28
 
0.6%
448421.092547965 26
 
0.6%
450021.504957301 19
 
0.4%
450169.517626003 17
 
0.4%
448273.114107211 17
 
0.4%
450751.524331915 16
 
0.4%
450615.470981382 16
 
0.4%
450038.847319845 15
 
0.3%
447998.456214523 15
 
0.3%
Other values (2153) 4142
93.2%
(Missing) 89
 
2.0%
ValueCountFrequency (%)
446462.901761568 1
 
< 0.1%
446598.591776331 2
 
< 0.1%
446680.303498539 1
 
< 0.1%
446692.439727784 2
 
< 0.1%
446699.196101461 1
 
< 0.1%
446766.631391106 2
 
< 0.1%
446791.711465932 1
 
< 0.1%
446817.640555401 3
0.1%
446827.001052015 6
0.1%
446827.961587557 1
 
< 0.1%
ValueCountFrequency (%)
452309.711718 2
 
< 0.1%
452305.723682264 1
 
< 0.1%
452233.685440247 1
 
< 0.1%
452195.587817951 1
 
< 0.1%
452189.755118282 2
 
< 0.1%
452107.257532 5
0.1%
452096.801259 2
 
< 0.1%
452076.939632 6
0.1%
452042.723062516 2
 
< 0.1%
451839.097942 1
 
< 0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
미용업
2075 
<NA>
880 
일반미용업
700 
피부미용업
385 
네일미용업
 
135
Other values (11)
268 

Length

Max length23
Median length19
Mean length4.3637182
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 2075
46.7%
<NA> 880
19.8%
일반미용업 700
 
15.8%
피부미용업 385
 
8.7%
네일미용업 135
 
3.0%
종합미용업 54
 
1.2%
일반미용업, 화장ㆍ분장 미용업 43
 
1.0%
피부미용업, 네일미용업 41
 
0.9%
네일미용업, 화장ㆍ분장 미용업 35
 
0.8%
피부미용업, 네일미용업, 화장ㆍ분장 미용업 23
 
0.5%
Other values (6) 72
 
1.6%

Length

2024-04-18T05:12:35.089561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 2218
46.0%
na 880
 
18.3%
일반미용업 783
 
16.2%
피부미용업 478
 
9.9%
네일미용업 263
 
5.5%
화장ㆍ분장 143
 
3.0%
종합미용업 54
 
1.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)0.6%
Missing1272
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean1.089877
Minimum0
Maximum28
Zeros2034
Zeros (%)45.8%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:35.173167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum28
Range28
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9489854
Coefficient of variation (CV)1.7882618
Kurtosis24.808012
Mean1.089877
Median Absolute Deviation (MAD)0
Skewness3.4331482
Sum3456
Variance3.7985442
MonotonicityNot monotonic
2024-04-18T05:12:35.249233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 2034
45.8%
2 261
 
5.9%
1 248
 
5.6%
3 237
 
5.3%
4 234
 
5.3%
5 95
 
2.1%
6 21
 
0.5%
7 14
 
0.3%
9 5
 
0.1%
11 4
 
0.1%
Other values (9) 18
 
0.4%
(Missing) 1272
28.6%
ValueCountFrequency (%)
0 2034
45.8%
1 248
 
5.6%
2 261
 
5.9%
3 237
 
5.3%
4 234
 
5.3%
5 95
 
2.1%
6 21
 
0.5%
7 14
 
0.3%
8 2
 
< 0.1%
9 5
 
0.1%
ValueCountFrequency (%)
28 1
 
< 0.1%
24 1
 
< 0.1%
16 1
 
< 0.1%
15 3
0.1%
14 3
0.1%
13 2
 
< 0.1%
12 2
 
< 0.1%
11 4
0.1%
10 3
0.1%
9 5
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.3%
Missing1567
Missing (%)35.3%
Infinite0
Infinite (%)0.0%
Mean0.21766342
Minimum0
Maximum14
Zeros2352
Zeros (%)52.9%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:35.322222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58673531
Coefficient of variation (CV)2.6956083
Kurtosis121.15679
Mean0.21766342
Median Absolute Deviation (MAD)0
Skewness7.3581813
Sum626
Variance0.34425833
MonotonicityNot monotonic
2024-04-18T05:12:35.397937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 2352
52.9%
1 478
 
10.8%
2 19
 
0.4%
3 14
 
0.3%
4 8
 
0.2%
6 2
 
< 0.1%
5 2
 
< 0.1%
14 1
 
< 0.1%
(Missing) 1567
35.3%
ValueCountFrequency (%)
0 2352
52.9%
1 478
 
10.8%
2 19
 
0.4%
3 14
 
0.3%
4 8
 
0.2%
5 2
 
< 0.1%
6 2
 
< 0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
14 1
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 8
 
0.2%
3 14
 
0.3%
2 19
 
0.4%
1 478
 
10.8%
0 2352
52.9%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.4%
Missing1642
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean0.97393788
Minimum0
Maximum11
Zeros797
Zeros (%)17.9%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:35.498016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0157857
Coefficient of variation (CV)1.0429676
Kurtosis21.815454
Mean0.97393788
Median Absolute Deviation (MAD)0
Skewness3.3481926
Sum2728
Variance1.0318205
MonotonicityNot monotonic
2024-04-18T05:12:35.590001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1580
35.6%
0 797
17.9%
2 280
 
6.3%
3 79
 
1.8%
4 30
 
0.7%
5 12
 
0.3%
6 12
 
0.3%
7 4
 
0.1%
11 4
 
0.1%
9 3
 
0.1%
(Missing) 1642
37.0%
ValueCountFrequency (%)
0 797
17.9%
1 1580
35.6%
2 280
 
6.3%
3 79
 
1.8%
4 30
 
0.7%
5 12
 
0.3%
6 12
 
0.3%
7 4
 
0.1%
9 3
 
0.1%
11 4
 
0.1%
ValueCountFrequency (%)
11 4
 
0.1%
9 3
 
0.1%
7 4
 
0.1%
6 12
 
0.3%
5 12
 
0.3%
4 30
 
0.7%
3 79
 
1.8%
2 280
 
6.3%
1 1580
35.6%
0 797
17.9%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.5%
Missing2452
Missing (%)55.2%
Infinite0
Infinite (%)0.0%
Mean1.2651934
Minimum0
Maximum11
Zeros126
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:35.668707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9510581
Coefficient of variation (CV)0.75170968
Kurtosis28.087272
Mean1.2651934
Median Absolute Deviation (MAD)0
Skewness4.1334286
Sum2519
Variance0.90451151
MonotonicityNot monotonic
2024-04-18T05:12:35.746692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1472
33.1%
2 265
 
6.0%
0 126
 
2.8%
3 69
 
1.6%
4 31
 
0.7%
6 10
 
0.2%
5 9
 
0.2%
7 3
 
0.1%
9 3
 
0.1%
11 3
 
0.1%
(Missing) 2452
55.2%
ValueCountFrequency (%)
0 126
 
2.8%
1 1472
33.1%
2 265
 
6.0%
3 69
 
1.6%
4 31
 
0.7%
5 9
 
0.2%
6 10
 
0.2%
7 3
 
0.1%
9 3
 
0.1%
11 3
 
0.1%
ValueCountFrequency (%)
11 3
 
0.1%
9 3
 
0.1%
7 3
 
0.1%
6 10
 
0.2%
5 9
 
0.2%
4 31
 
0.7%
3 69
 
1.6%
2 265
 
6.0%
1 1472
33.1%
0 126
 
2.8%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
3368 
0
1019 
1
 
40
2
 
11
3
 
5

Length

Max length4
Median length4
Mean length3.2741391
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3368
75.8%
0 1019
 
22.9%
1 40
 
0.9%
2 11
 
0.2%
3 5
 
0.1%

Length

2024-04-18T05:12:35.844785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:35.929045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3368
75.8%
0 1019
 
22.9%
1 40
 
0.9%
2 11
 
0.2%
3 5
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
4055 
0
 
336
1
 
36
2
 
11
3
 
5

Length

Max length4
Median length4
Mean length3.7380149
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4055
91.3%
0 336
 
7.6%
1 36
 
0.8%
2 11
 
0.2%
3 5
 
0.1%

Length

2024-04-18T05:12:36.020578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:36.119963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4055
91.3%
0 336
 
7.6%
1 36
 
0.8%
2 11
 
0.2%
3 5
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
0
2480 
<NA>
1963 

Length

Max length4
Median length1
Mean length2.3254558
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 2480
55.8%
<NA> 1963
44.2%

Length

2024-04-18T05:12:36.217478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:36.295622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2480
55.8%
na 1963
44.2%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
0
2480 
<NA>
1963 

Length

Max length4
Median length1
Mean length2.3254558
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 2480
55.8%
<NA> 1963
44.2%

Length

2024-04-18T05:12:36.392602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:36.471028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2480
55.8%
na 1963
44.2%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
0
2480 
<NA>
1963 

Length

Max length4
Median length1
Mean length2.3254558
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 2480
55.8%
<NA> 1963
44.2%

Length

2024-04-18T05:12:36.550088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:36.626668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2480
55.8%
na 1963
44.2%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing936
Missing (%)21.1%
Memory size8.8 KiB
False
3507 
(Missing)
936 
ValueCountFrequency (%)
False 3507
78.9%
(Missing) 936
 
21.1%
2024-04-18T05:12:36.691158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)0.8%
Missing981
Missing (%)22.1%
Infinite0
Infinite (%)0.0%
Mean3.3275563
Minimum0
Maximum44
Zeros300
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:36.760578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile7
Maximum44
Range44
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3741694
Coefficient of variation (CV)0.71348738
Kurtosis55.451211
Mean3.3275563
Median Absolute Deviation (MAD)1
Skewness4.9457902
Sum11520
Variance5.6366805
MonotonicityNot monotonic
2024-04-18T05:12:36.849784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3 1474
33.2%
4 610
13.7%
2 500
 
11.3%
0 300
 
6.8%
5 215
 
4.8%
6 106
 
2.4%
1 70
 
1.6%
7 52
 
1.2%
8 45
 
1.0%
10 27
 
0.6%
Other values (17) 63
 
1.4%
(Missing) 981
22.1%
ValueCountFrequency (%)
0 300
 
6.8%
1 70
 
1.6%
2 500
 
11.3%
3 1474
33.2%
4 610
13.7%
5 215
 
4.8%
6 106
 
2.4%
7 52
 
1.2%
8 45
 
1.0%
9 20
 
0.5%
ValueCountFrequency (%)
44 1
< 0.1%
36 1
< 0.1%
34 1
< 0.1%
26 2
< 0.1%
24 1
< 0.1%
22 2
< 0.1%
21 1
< 0.1%
20 1
< 0.1%
19 1
< 0.1%
18 1
< 0.1%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)100.0%
Memory size39.2 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
2514 
임대
1887 
자가
 
42

Length

Max length4
Median length4
Mean length3.1316678
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2514
56.6%
임대 1887
42.5%
자가 42
 
0.9%

Length

2024-04-18T05:12:36.947988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:37.037336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2514
56.6%
임대 1887
42.5%
자가 42
 
0.9%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
2646 
0
1797 

Length

Max length4
Median length4
Mean length2.7866307
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2646
59.6%
0 1797
40.4%

Length

2024-04-18T05:12:37.129841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:37.216039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2646
59.6%
0 1797
40.4%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
3476 
0
956 
1
 
7
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.3470628
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3476
78.2%
0 956
 
21.5%
1 7
 
0.2%
2 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%

Length

2024-04-18T05:12:37.298493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:37.386812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3476
78.2%
0 956
 
21.5%
1 7
 
0.2%
2 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%

남성종사자수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
3477 
0
966 

Length

Max length4
Median length4
Mean length3.347738
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3477
78.3%
0 966
 
21.7%

Length

2024-04-18T05:12:37.479220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:37.558768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3477
78.3%
0 966
 
21.7%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
<NA>
2754 
0
1689 

Length

Max length4
Median length4
Mean length2.8595544
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2754
62.0%
0 1689
38.0%

Length

2024-04-18T05:12:37.638950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:12:37.719163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2754
62.0%
0 1689
38.0%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.8%
Missing2784
Missing (%)62.7%
Infinite0
Infinite (%)0.0%
Mean0.84689572
Minimum0
Maximum12
Zeros1160
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2024-04-18T05:12:37.794661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.682076
Coefficient of variation (CV)1.9861666
Kurtosis8.019138
Mean0.84689572
Median Absolute Deviation (MAD)0
Skewness2.6301066
Sum1405
Variance2.8293797
MonotonicityNot monotonic
2024-04-18T05:12:37.876666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1160
26.1%
2 153
 
3.4%
1 130
 
2.9%
3 97
 
2.2%
4 45
 
1.0%
6 22
 
0.5%
5 19
 
0.4%
8 13
 
0.3%
7 11
 
0.2%
10 4
 
0.1%
Other values (3) 5
 
0.1%
(Missing) 2784
62.7%
ValueCountFrequency (%)
0 1160
26.1%
1 130
 
2.9%
2 153
 
3.4%
3 97
 
2.2%
4 45
 
1.0%
5 19
 
0.4%
6 22
 
0.5%
7 11
 
0.2%
8 13
 
0.3%
9 3
 
0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 1
 
< 0.1%
10 4
 
0.1%
9 3
 
0.1%
8 13
 
0.3%
7 11
 
0.2%
6 22
 
0.5%
5 19
 
0.4%
4 45
1.0%
3 97
2.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing880
Missing (%)19.8%
Memory size8.8 KiB
False
3561 
True
 
2
(Missing)
880 
ValueCountFrequency (%)
False 3561
80.1%
True 2
 
< 0.1%
(Missing) 880
 
19.8%
2024-04-18T05:12:37.956861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032400003240000-204-1920-0084719201220<NA>3폐업2폐업19960322<NA><NA><NA>02 477382621.42134848서울특별시 강동구 성내동 271-2번지 해바라기A 상가동 1 6호<NA><NA>청진헤어멧세지2002-06-06 00:00:00I2018-08-31 23:59:59.0일반미용업211071.489376447715.668884미용업000<NA>0<NA>000N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132400003240000-204-1978-0155619780902<NA>3폐업2폐업19950321<NA><NA><NA>02 478158536.39134864서울특별시 강동구 천호동 453-14번지<NA><NA>보라2002-06-06 00:00:00I2018-08-31 23:59:59.0일반미용업211184.908455448405.548512미용업000<NA>0<NA>000N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232400003240000-204-1979-0152119791113<NA>3폐업2폐업20210907<NA><NA><NA>020486074916.1134864서울특별시 강동구 천호동 453-7서울특별시 강동구 천호대로159길 25 (천호동)5335조이헤어아떼2021-09-07 14:33:29U2021-09-09 02:40:00.0일반미용업211220.108222448503.534642미용업000000000N2<NA><NA><NA><NA>00000N
332400003240000-204-1979-0154419791113<NA>3폐업2폐업19960227<NA><NA><NA>02 427433514.7134854서울특별시 강동구 암사동 424-32번지<NA><NA>중희2002-06-06 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432400003240000-204-1979-0155119791122<NA>1영업/정상1영업<NA><NA><NA><NA>023427302833.0134830서울특별시 강동구 명일동 326-2서울특별시 강동구 상암로47길 76 (명일동)5292이현미헤어2021-07-12 15:10:45U2021-07-14 02:40:00.0일반미용업212708.436269449752.363199미용업2<NA>11<NA><NA><NA><NA><NA>N5<NA><NA><NA>임대<NA><NA><NA><NA><NA>N
532400003240000-204-1979-0155819791113<NA>3폐업2폐업19990610<NA><NA><NA>02 472033115.6134870서울특별시 강동구 천호동 403-9번지<NA><NA>동심2002-06-06 00:00:00I2018-08-31 23:59:59.0일반미용업211317.669396448731.941979미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632400003240000-204-1979-0156219791113<NA>3폐업2폐업20010219<NA><NA><NA>020477894015.05134841서울특별시 강동구 성내동 157-4번지<NA><NA>진2001-02-19 00:00:00I2018-08-31 23:59:59.0일반미용업211393.96789448155.391126미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732400003240000-204-1979-0156319791113<NA>3폐업2폐업19931106<NA><NA><NA>020476798119.2134870서울특별시 강동구 천호동 403-21번지<NA><NA>진선미2002-06-06 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832400003240000-204-1979-0156819791113<NA>3폐업2폐업20030403<NA><NA><NA>020478819820.4134825서울특별시 강동구 명일동 47-6번지 배재203<NA><NA>이인영헤어갤러리2003-04-03 00:00:00I2018-08-31 23:59:59.0일반미용업213676.319091450194.855705미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932400003240000-204-1979-0156919791113<NA>3폐업2폐업19930215<NA><NA><NA>020000000012.61134870서울특별시 강동구 천호동 392-29번지<NA><NA>명미2002-06-06 00:00:00I2018-08-31 23:59:59.0일반미용업211542.204026449000.759673미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
443332400003240000-226-2020-0000420200814<NA>1영업/정상1영업<NA><NA><NA><NA>02477 774564.25134864서울특별시 강동구 천호동 449-49 힐탑프라자서울특별시 강동구 천호대로 1073, 힐탑프라자 201,213호 (천호동)5340리본에스테틱2020-08-14 14:44:20I2020-08-16 00:23:14.0피부미용업211542.314117448273.114107피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA><NA><NA>000N4<NA><NA><NA>임대00004N
443432400003240000-226-2020-000052020-08-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.16134-837서울특별시 강동구 상일동 284서울특별시 강동구 상일로5길 17, 1층 (상일동)5283브릴뷰티랩2023-06-19 16:19:38U2022-12-05 22:01:00.0네일아트업215131.241334449635.67028<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
443532400003240000-226-2021-0000120210405<NA>3폐업2폐업20210628<NA><NA><NA><NA>31.53134080서울특별시 강동구 고덕동 694 고덕그라시움(제4상가)서울특별시 강동구 고덕로 385, 고덕그라시움(제4상가) B105호 (고덕동)5223고덕네일 라뜰리에뷰티 2호점2021-06-28 11:20:55U2021-06-30 02:40:00.0네일아트업214687.925331450626.949693피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA>11000N1<NA><NA><NA><NA>00001N
443632400003240000-226-2022-0000120220330<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.0134801서울특별시 강동구 고덕동 195-3서울특별시 강동구 상일로15길 34-17, 1층 (고덕동)5222봄그리다2022-04-07 13:53:24U2021-12-04 00:09:00.0네일아트업214923.465674450719.764458<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
443732400003240000-226-2023-000012023-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>41.63134-100서울특별시 강동구 강일동 215 강동리버스트6단지서울특별시 강동구 아리수로93가길 87, 강동리버스트6단지 203호 (강일동)5201멜로우뷰티2023-04-11 14:52:20I2022-12-03 23:03:00.0메이크업업214921.411961452042.723063<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
443832400003240000-226-2023-000022023-07-21<NA>1영업/정상1영업<NA><NA><NA><NA>02 6489333630.25134-851서울특별시 강동구 성내동 319-10서울특별시 강동구 성내로 7, 201호 (성내동)5392시선뷰티샵2023-07-21 15:04:34I2022-12-06 22:03:00.0메이크업업210692.588313447609.209611<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
443932400003240000-226-2023-000032023-07-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.63134-814서울특별시 강동구 길동 415-13 강동 큐브 2차서울특별시 강동구 진황도로 85, 102호 (길동, 강동 큐브 2차)5354큐빅네일2023-07-28 16:38:21I2022-12-06 21:00:00.0네일아트업211963.942242448273.205059<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
444032400003240000-226-2023-000042023-10-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.8134-812서울특별시 강동구 길동 354-8서울특별시 강동구 명일로19길 13, 1층 (길동)5344키쿠앤루2023-10-26 14:51:32I2022-10-30 22:08:00.0피부미용업212809.234446448579.272737<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
444132400003240000-226-2023-000052023-11-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.28134-809서울특별시 강동구 길동 150서울특별시 강동구 천호대로191길 17, 1층 103호 (길동)5350살롱드꽃용2023-11-13 16:26:01I2022-10-31 23:05:00.0메이크업업212629.0406448133.378622<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
444232400003240000-226-2024-000012024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.92134-812서울특별시 강동구 길동 367-14 DYD 도시공간서울특별시 강동구 양재대로115길 10, 1층 101호 (길동, DYD 도시공간)5342네일 모어드(nail mored)2024-04-08 09:21:03I2023-12-03 23:00:00.0네일아트업212285.115465448536.653139<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>