Overview

Dataset statistics

Number of variables47
Number of observations2375
Missing cells24865
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory937.1 KiB
Average record size in memory404.1 B

Variable types

Categorical19
Text7
DateTime4
Unsupported4
Numeric11
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-17905/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
사용시작지하층 is highly imbalanced (57.2%)Imbalance
사용끝지하층 is highly imbalanced (73.3%)Imbalance
조건부허가시작일자 is highly imbalanced (99.0%)Imbalance
조건부허가종료일자 is highly imbalanced (99.0%)Imbalance
건물소유구분명 is highly imbalanced (74.7%)Imbalance
남성종사자수 is highly imbalanced (59.7%)Imbalance
인허가취소일자 has 2375 (100.0%) missing valuesMissing
폐업일자 has 934 (39.3%) missing valuesMissing
휴업시작일자 has 2375 (100.0%) missing valuesMissing
휴업종료일자 has 2375 (100.0%) missing valuesMissing
재개업일자 has 2375 (100.0%) missing valuesMissing
전화번호 has 1028 (43.3%) missing valuesMissing
도로명주소 has 863 (36.3%) missing valuesMissing
도로명우편번호 has 889 (37.4%) missing valuesMissing
좌표정보(X) has 149 (6.3%) missing valuesMissing
좌표정보(Y) has 149 (6.3%) missing valuesMissing
건물지상층수 has 657 (27.7%) missing valuesMissing
건물지하층수 has 692 (29.1%) missing valuesMissing
사용시작지상층 has 1049 (44.2%) missing valuesMissing
사용끝지상층 has 1771 (74.6%) missing valuesMissing
발한실여부 has 467 (19.7%) missing valuesMissing
좌석수 has 498 (21.0%) missing valuesMissing
조건부허가신고사유 has 2371 (99.8%) missing valuesMissing
여성종사자수 has 1838 (77.4%) missing valuesMissing
침대수 has 1564 (65.9%) missing valuesMissing
다중이용업소여부 has 444 (18.7%) missing valuesMissing
좌석수 is highly skewed (γ1 = 21.98601829)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 31 (1.3%) zerosZeros
건물지상층수 has 1489 (62.7%) zerosZeros
건물지하층수 has 1525 (64.2%) zerosZeros
사용시작지상층 has 845 (35.6%) zerosZeros
사용끝지상층 has 139 (5.9%) zerosZeros
좌석수 has 296 (12.5%) zerosZeros
여성종사자수 has 501 (21.1%) zerosZeros
침대수 has 537 (22.6%) zerosZeros

Reproduction

Analysis started2024-04-06 11:25:13.081127
Analysis finished2024-04-06 11:25:15.388680
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
3030000
2375 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 2375
100.0%

Length

2024-04-06T20:25:15.688172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:15.983011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 2375
100.0%

관리번호
Text

UNIQUE 

Distinct2375
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
2024-04-06T20:25:16.416206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters52250
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

Unique2375 ?
Unique (%)100.0%

Sample

1st row3030000-204-1938-00930
2nd row3030000-204-1957-00968
3rd row3030000-204-1964-01022
4th row3030000-204-1965-00708
5th row3030000-204-1967-00516
ValueCountFrequency (%)
3030000-204-1938-00930 1
 
< 0.1%
3030000-212-2011-00017 1
 
< 0.1%
3030000-212-2013-00004 1
 
< 0.1%
3030000-212-2012-00002 1
 
< 0.1%
3030000-212-2012-00003 1
 
< 0.1%
3030000-212-2012-00004 1
 
< 0.1%
3030000-212-2012-00005 1
 
< 0.1%
3030000-212-2013-00002 1
 
< 0.1%
3030000-212-2013-00003 1
 
< 0.1%
3030000-212-2013-00005 1
 
< 0.1%
Other values (2365) 2365
99.6%
2024-04-06T20:25:17.023328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22654
43.4%
- 7125
 
13.6%
3 5807
 
11.1%
2 5760
 
11.0%
1 5145
 
9.8%
9 1557
 
3.0%
4 1431
 
2.7%
5 802
 
1.5%
8 750
 
1.4%
7 629
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45125
86.4%
Dash Punctuation 7125
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22654
50.2%
3 5807
 
12.9%
2 5760
 
12.8%
1 5145
 
11.4%
9 1557
 
3.5%
4 1431
 
3.2%
5 802
 
1.8%
8 750
 
1.7%
7 629
 
1.4%
6 590
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 7125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22654
43.4%
- 7125
 
13.6%
3 5807
 
11.1%
2 5760
 
11.0%
1 5145
 
9.8%
9 1557
 
3.0%
4 1431
 
2.7%
5 802
 
1.5%
8 750
 
1.4%
7 629
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22654
43.4%
- 7125
 
13.6%
3 5807
 
11.1%
2 5760
 
11.0%
1 5145
 
9.8%
9 1557
 
3.0%
4 1431
 
2.7%
5 802
 
1.5%
8 750
 
1.4%
7 629
 
1.2%
Distinct1799
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
Minimum1938-02-20 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T20:25:17.362485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:17.577974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2375
Missing (%)100.0%
Memory size21.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
3
1441 
1
934 

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 1441
60.7%
1 934
39.3%

Length

2024-04-06T20:25:18.121102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:18.265363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1441
60.7%
1 934
39.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
폐업
1441 
영업/정상
934 

Length

Max length5
Median length2
Mean length3.1797895
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1441
60.7%
영업/정상 934
39.3%

Length

2024-04-06T20:25:18.472206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:18.638178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1441
60.7%
영업/정상 934
39.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
2
1441 
1
934 

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 1441
60.7%
1 934
39.3%

Length

2024-04-06T20:25:18.788073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:19.004656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1441
60.7%
1 934
39.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
폐업
1441 
영업
934 

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 1441
60.7%
영업 934
39.3%

Length

2024-04-06T20:25:19.213425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:19.352743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1441
60.7%
영업 934
39.3%

폐업일자
Date

MISSING 

Distinct1051
Distinct (%)72.9%
Missing934
Missing (%)39.3%
Memory size18.7 KiB
Minimum1994-01-25 00:00:00
Maximum2024-04-01 00:00:00
2024-04-06T20:25:19.532085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:19.801427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2375
Missing (%)100.0%
Memory size21.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2375
Missing (%)100.0%
Memory size21.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2375
Missing (%)100.0%
Memory size21.0 KiB

전화번호
Text

MISSING 

Distinct967
Distinct (%)71.8%
Missing1028
Missing (%)43.3%
Memory size18.7 KiB
2024-04-06T20:25:20.202270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.7112101
Min length2

Characters and Unicode

Total characters13081
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

Unique882 ?
Unique (%)65.5%

Sample

1st row0200000000
2nd row0200000000
3rd row0200000000
4th row0200000000
5th row02 2930586
ValueCountFrequency (%)
02 545
29.4%
0200000000 118
 
6.4%
00000 86
 
4.6%
0 28
 
1.5%
0222993224 4
 
0.2%
0222933561 4
 
0.2%
0222922725 3
 
0.2%
070 3
 
0.2%
0222952701 3
 
0.2%
4693830 3
 
0.2%
Other values (969) 1054
56.9%
2024-04-06T20:25:20.953179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3386
25.9%
2 3282
25.1%
9 1038
 
7.9%
4 826
 
6.3%
798
 
6.1%
6 737
 
5.6%
3 654
 
5.0%
8 623
 
4.8%
5 597
 
4.6%
1 587
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12283
93.9%
Space Separator 798
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3386
27.6%
2 3282
26.7%
9 1038
 
8.5%
4 826
 
6.7%
6 737
 
6.0%
3 654
 
5.3%
8 623
 
5.1%
5 597
 
4.9%
1 587
 
4.8%
7 553
 
4.5%
Space Separator
ValueCountFrequency (%)
798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13081
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3386
25.9%
2 3282
25.1%
9 1038
 
7.9%
4 826
 
6.3%
798
 
6.1%
6 737
 
5.6%
3 654
 
5.0%
8 623
 
4.8%
5 597
 
4.6%
1 587
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13081
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3386
25.9%
2 3282
25.1%
9 1038
 
7.9%
4 826
 
6.3%
798
 
6.1%
6 737
 
5.6%
3 654
 
5.0%
8 623
 
4.8%
5 597
 
4.6%
1 587
 
4.5%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1280
Distinct (%)53.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.05168
Minimum0
Maximum697.2
Zeros31
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:21.255047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.997
Q118.48
median27
Q345.595
95-th percentile115.3
Maximum697.2
Range697.2
Interquartile range (IQR)27.115

Descriptive statistics

Standard deviation39.788513
Coefficient of variation (CV)0.99342931
Kurtosis41.316559
Mean40.05168
Median Absolute Deviation (MAD)11
Skewness4.395734
Sum95122.74
Variance1583.1258
MonotonicityNot monotonic
2024-04-06T20:25:21.494610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 57
 
2.4%
26.4 43
 
1.8%
0.0 31
 
1.3%
16.5 31
 
1.3%
23.1 31
 
1.3%
19.8 29
 
1.2%
30.0 22
 
0.9%
8.9 21
 
0.9%
18.0 19
 
0.8%
15.0 18
 
0.8%
Other values (1270) 2073
87.3%
ValueCountFrequency (%)
0.0 31
1.3%
0.18 1
 
< 0.1%
3.3 2
 
0.1%
5.0 2
 
0.1%
6.2 1
 
< 0.1%
6.47 1
 
< 0.1%
6.5 2
 
0.1%
6.61 1
 
< 0.1%
6.7 1
 
< 0.1%
7.0 1
 
< 0.1%
ValueCountFrequency (%)
697.2 1
< 0.1%
432.01 1
< 0.1%
320.0 1
< 0.1%
284.58 1
< 0.1%
274.53 1
< 0.1%
243.87 1
< 0.1%
240.0 1
< 0.1%
231.0 1
< 0.1%
230.0 1
< 0.1%
225.59 1
< 0.1%
Distinct161
Distinct (%)6.8%
Missing1
Missing (%)< 0.1%
Memory size18.7 KiB
2024-04-06T20:25:22.054827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1246841
Min length6

Characters and Unicode

Total characters14540
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 (%)1.0%

Sample

1st row133867
2nd row133818
3rd row133882
4th row133811
5th row133817
ValueCountFrequency (%)
133882 73
 
3.1%
133070 73
 
3.1%
133848 68
 
2.9%
133803 65
 
2.7%
133871 62
 
2.6%
133809 59
 
2.5%
133010 57
 
2.4%
133822 54
 
2.3%
133858 54
 
2.3%
133823 50
 
2.1%
Other values (151) 1759
74.1%
2024-04-06T20:25:23.088232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 5232
36.0%
1 2764
19.0%
8 2424
16.7%
0 1011
 
7.0%
2 729
 
5.0%
7 510
 
3.5%
5 482
 
3.3%
4 435
 
3.0%
6 370
 
2.5%
- 296
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14244
98.0%
Dash Punctuation 296
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 5232
36.7%
1 2764
19.4%
8 2424
17.0%
0 1011
 
7.1%
2 729
 
5.1%
7 510
 
3.6%
5 482
 
3.4%
4 435
 
3.1%
6 370
 
2.6%
9 287
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14540
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 5232
36.0%
1 2764
19.0%
8 2424
16.7%
0 1011
 
7.0%
2 729
 
5.0%
7 510
 
3.5%
5 482
 
3.3%
4 435
 
3.0%
6 370
 
2.5%
- 296
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 5232
36.0%
1 2764
19.0%
8 2424
16.7%
0 1011
 
7.0%
2 729
 
5.0%
7 510
 
3.5%
5 482
 
3.3%
4 435
 
3.0%
6 370
 
2.5%
- 296
 
2.0%
Distinct1862
Distinct (%)78.4%
Missing1
Missing (%)< 0.1%
Memory size18.7 KiB
2024-04-06T20:25:23.646408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length46
Mean length25.559815
Min length17

Characters and Unicode

Total characters60679
Distinct characters300
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

Unique1574 ?
Unique (%)66.3%

Sample

1st row서울특별시 성동구 행당동 286-30번지
2nd row서울특별시 성동구 사근동 309-11번지
3rd row서울특별시 성동구 도선동 185-8번지
4th row서울특별시 성동구 마장동 311-1번지
5th row서울특별시 성동구 사근동 176-7번지
ValueCountFrequency (%)
서울특별시 2374
21.6%
성동구 2374
21.6%
행당동 407
 
3.7%
성수동2가 315
 
2.9%
성수동1가 278
 
2.5%
하왕십리동 246
 
2.2%
옥수동 162
 
1.5%
지상1층 145
 
1.3%
용답동 144
 
1.3%
금호동4가 106
 
1.0%
Other values (2061) 4421
40.3%
2024-04-06T20:25:24.715004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10446
17.2%
4923
 
8.1%
3081
 
5.1%
1 2567
 
4.2%
2414
 
4.0%
2413
 
4.0%
2376
 
3.9%
2375
 
3.9%
2374
 
3.9%
2374
 
3.9%
Other values (290) 25336
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35855
59.1%
Decimal Number 12044
 
19.8%
Space Separator 10446
 
17.2%
Dash Punctuation 1751
 
2.9%
Close Punctuation 166
 
0.3%
Open Punctuation 165
 
0.3%
Uppercase Letter 152
 
0.3%
Lowercase Letter 57
 
0.1%
Other Punctuation 43
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4923
13.7%
3081
 
8.6%
2414
 
6.7%
2413
 
6.7%
2376
 
6.6%
2375
 
6.6%
2374
 
6.6%
2374
 
6.6%
1938
 
5.4%
1644
 
4.6%
Other values (232) 9943
27.7%
Uppercase Letter
ValueCountFrequency (%)
B 26
17.1%
A 18
11.8%
T 16
10.5%
L 10
 
6.6%
C 10
 
6.6%
S 8
 
5.3%
I 7
 
4.6%
K 7
 
4.6%
O 6
 
3.9%
P 5
 
3.3%
Other values (13) 39
25.7%
Lowercase Letter
ValueCountFrequency (%)
e 9
15.8%
o 8
14.0%
a 8
14.0%
r 7
12.3%
w 6
10.5%
c 3
 
5.3%
k 2
 
3.5%
b 2
 
3.5%
t 2
 
3.5%
p 2
 
3.5%
Other values (6) 8
14.0%
Decimal Number
ValueCountFrequency (%)
1 2567
21.3%
2 1734
14.4%
3 1400
11.6%
0 1130
9.4%
6 1110
9.2%
5 922
 
7.7%
4 895
 
7.4%
7 848
 
7.0%
9 736
 
6.1%
8 702
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 31
72.1%
@ 8
 
18.6%
. 2
 
4.7%
? 1
 
2.3%
& 1
 
2.3%
Space Separator
ValueCountFrequency (%)
10446
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1751
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Open Punctuation
ValueCountFrequency (%)
( 165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35855
59.1%
Common 24615
40.6%
Latin 209
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4923
13.7%
3081
 
8.6%
2414
 
6.7%
2413
 
6.7%
2376
 
6.6%
2375
 
6.6%
2374
 
6.6%
2374
 
6.6%
1938
 
5.4%
1644
 
4.6%
Other values (232) 9943
27.7%
Latin
ValueCountFrequency (%)
B 26
 
12.4%
A 18
 
8.6%
T 16
 
7.7%
L 10
 
4.8%
C 10
 
4.8%
e 9
 
4.3%
o 8
 
3.8%
a 8
 
3.8%
S 8
 
3.8%
I 7
 
3.3%
Other values (29) 89
42.6%
Common
ValueCountFrequency (%)
10446
42.4%
1 2567
 
10.4%
- 1751
 
7.1%
2 1734
 
7.0%
3 1400
 
5.7%
0 1130
 
4.6%
6 1110
 
4.5%
5 922
 
3.7%
4 895
 
3.6%
7 848
 
3.4%
Other values (9) 1812
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35855
59.1%
ASCII 24824
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10446
42.1%
1 2567
 
10.3%
- 1751
 
7.1%
2 1734
 
7.0%
3 1400
 
5.6%
0 1130
 
4.6%
6 1110
 
4.5%
5 922
 
3.7%
4 895
 
3.6%
7 848
 
3.4%
Other values (48) 2021
 
8.1%
Hangul
ValueCountFrequency (%)
4923
13.7%
3081
 
8.6%
2414
 
6.7%
2413
 
6.7%
2376
 
6.6%
2375
 
6.6%
2374
 
6.6%
2374
 
6.6%
1938
 
5.4%
1644
 
4.6%
Other values (232) 9943
27.7%

도로명주소
Text

MISSING 

Distinct1416
Distinct (%)93.7%
Missing863
Missing (%)36.3%
Memory size18.7 KiB
2024-04-06T20:25:25.219907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length54
Mean length35.673942
Min length22

Characters and Unicode

Total characters53939
Distinct characters294
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

Unique1335 ?
Unique (%)88.3%

Sample

1st row서울특별시 성동구 금호로 40, 상가동 지1층 25호 (금호동4가, 힐스테이트 서울숲리버)
2nd row서울특별시 성동구 왕십리로22길 9 (도선동)
3rd row서울특별시 성동구 왕십리로19길 11 (행당동,(지상1층))
4th row서울특별시 성동구 고산자로6길 24 (행당동)
5th row서울특별시 성동구 사근동길 63 (사근동,1층)
ValueCountFrequency (%)
서울특별시 1512
 
14.5%
성동구 1512
 
14.5%
1층 443
 
4.3%
2층 258
 
2.5%
행당동 239
 
2.3%
왕십리로 185
 
1.8%
성수동1가 184
 
1.8%
성수동2가 183
 
1.8%
하왕십리동 160
 
1.5%
옥수동 90
 
0.9%
Other values (1369) 5642
54.2%
2024-04-06T20:25:26.159475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8897
 
16.5%
3457
 
6.4%
1 2880
 
5.3%
2144
 
4.0%
, 1800
 
3.3%
2 1723
 
3.2%
1672
 
3.1%
) 1589
 
2.9%
( 1588
 
2.9%
1571
 
2.9%
Other values (284) 26618
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30430
56.4%
Decimal Number 8974
 
16.6%
Space Separator 8897
 
16.5%
Other Punctuation 1805
 
3.3%
Close Punctuation 1589
 
2.9%
Open Punctuation 1588
 
2.9%
Dash Punctuation 363
 
0.7%
Uppercase Letter 242
 
0.4%
Lowercase Letter 49
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3457
 
11.4%
2144
 
7.0%
1672
 
5.5%
1571
 
5.2%
1535
 
5.0%
1519
 
5.0%
1513
 
5.0%
1512
 
5.0%
1211
 
4.0%
1071
 
3.5%
Other values (230) 13225
43.5%
Uppercase Letter
ValueCountFrequency (%)
B 64
26.4%
C 34
14.0%
L 28
11.6%
A 22
 
9.1%
I 21
 
8.7%
J 14
 
5.8%
T 10
 
4.1%
E 10
 
4.1%
S 7
 
2.9%
K 6
 
2.5%
Other values (10) 26
10.7%
Lowercase Letter
ValueCountFrequency (%)
e 8
16.3%
r 6
12.2%
o 6
12.2%
a 6
12.2%
w 5
10.2%
c 4
8.2%
b 3
 
6.1%
k 3
 
6.1%
z 2
 
4.1%
l 2
 
4.1%
Other values (4) 4
8.2%
Decimal Number
ValueCountFrequency (%)
1 2880
32.1%
2 1723
19.2%
3 935
 
10.4%
0 845
 
9.4%
4 680
 
7.6%
6 440
 
4.9%
5 428
 
4.8%
7 413
 
4.6%
8 349
 
3.9%
9 281
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 1800
99.7%
@ 2
 
0.1%
. 1
 
0.1%
& 1
 
0.1%
? 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8897
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1589
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1588
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 363
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30430
56.4%
Common 23218
43.0%
Latin 291
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3457
 
11.4%
2144
 
7.0%
1672
 
5.5%
1571
 
5.2%
1535
 
5.0%
1519
 
5.0%
1513
 
5.0%
1512
 
5.0%
1211
 
4.0%
1071
 
3.5%
Other values (230) 13225
43.5%
Latin
ValueCountFrequency (%)
B 64
22.0%
C 34
11.7%
L 28
 
9.6%
A 22
 
7.6%
I 21
 
7.2%
J 14
 
4.8%
T 10
 
3.4%
E 10
 
3.4%
e 8
 
2.7%
S 7
 
2.4%
Other values (24) 73
25.1%
Common
ValueCountFrequency (%)
8897
38.3%
1 2880
 
12.4%
, 1800
 
7.8%
2 1723
 
7.4%
) 1589
 
6.8%
( 1588
 
6.8%
3 935
 
4.0%
0 845
 
3.6%
4 680
 
2.9%
6 440
 
1.9%
Other values (10) 1841
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30430
56.4%
ASCII 23509
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8897
37.8%
1 2880
 
12.3%
, 1800
 
7.7%
2 1723
 
7.3%
) 1589
 
6.8%
( 1588
 
6.8%
3 935
 
4.0%
0 845
 
3.6%
4 680
 
2.9%
6 440
 
1.9%
Other values (44) 2132
 
9.1%
Hangul
ValueCountFrequency (%)
3457
 
11.4%
2144
 
7.0%
1672
 
5.5%
1571
 
5.2%
1535
 
5.0%
1519
 
5.0%
1513
 
5.0%
1512
 
5.0%
1211
 
4.0%
1071
 
3.5%
Other values (230) 13225
43.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct97
Distinct (%)6.5%
Missing889
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean4745.5363
Minimum4700
Maximum4808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:26.417814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4700
5-th percentile4701
Q14714
median4737
Q34778
95-th percentile4803.75
Maximum4808
Range108
Interquartile range (IQR)64

Descriptive statistics

Standard deviation33.800858
Coefficient of variation (CV)0.0071226634
Kurtosis-1.3394432
Mean4745.5363
Median Absolute Deviation (MAD)28
Skewness0.27155634
Sum7051867
Variance1142.498
MonotonicityNot monotonic
2024-04-06T20:25:26.696795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4701 83
 
3.5%
4709 65
 
2.7%
4700 54
 
2.3%
4782 52
 
2.2%
4804 48
 
2.0%
4714 45
 
1.9%
4710 43
 
1.8%
4778 41
 
1.7%
4760 34
 
1.4%
4745 34
 
1.4%
Other values (87) 987
41.6%
(Missing) 889
37.4%
ValueCountFrequency (%)
4700 54
2.3%
4701 83
3.5%
4702 13
 
0.5%
4703 1
 
< 0.1%
4704 6
 
0.3%
4705 2
 
0.1%
4706 4
 
0.2%
4707 14
 
0.6%
4708 20
 
0.8%
4709 65
2.7%
ValueCountFrequency (%)
4808 5
 
0.2%
4805 22
0.9%
4804 48
2.0%
4803 4
 
0.2%
4802 1
 
< 0.1%
4801 24
1.0%
4800 4
 
0.2%
4799 4
 
0.2%
4798 1
 
< 0.1%
4797 4
 
0.2%
Distinct2075
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
2024-04-06T20:25:27.192586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length5.9747368
Min length1

Characters and Unicode

Total characters14190
Distinct characters670
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1864 ?
Unique (%)78.5%

Sample

1st row노블
2nd row지현
3rd row화용
4th row형제
5th row화옥
ValueCountFrequency (%)
헤어 39
 
1.3%
hair 29
 
1.0%
네일 28
 
0.9%
왕십리점 20
 
0.7%
성수점 16
 
0.5%
에스테틱 16
 
0.5%
뷰티 12
 
0.4%
미용실 11
 
0.4%
리안헤어 10
 
0.3%
헤어클럽 9
 
0.3%
Other values (2291) 2810
93.7%
2024-04-06T20:25:28.069700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
825
 
5.8%
778
 
5.5%
626
 
4.4%
340
 
2.4%
332
 
2.3%
299
 
2.1%
279
 
2.0%
222
 
1.6%
219
 
1.5%
217
 
1.5%
Other values (660) 10053
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11406
80.4%
Lowercase Letter 775
 
5.5%
Uppercase Letter 766
 
5.4%
Space Separator 626
 
4.4%
Open Punctuation 210
 
1.5%
Close Punctuation 210
 
1.5%
Other Punctuation 98
 
0.7%
Decimal Number 86
 
0.6%
Dash Punctuation 5
 
< 0.1%
Connector Punctuation 3
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
825
 
7.2%
778
 
6.8%
340
 
3.0%
332
 
2.9%
299
 
2.6%
279
 
2.4%
222
 
1.9%
219
 
1.9%
217
 
1.9%
191
 
1.7%
Other values (581) 7704
67.5%
Uppercase Letter
ValueCountFrequency (%)
A 91
 
11.9%
I 56
 
7.3%
S 56
 
7.3%
O 54
 
7.0%
E 51
 
6.7%
N 48
 
6.3%
L 43
 
5.6%
H 43
 
5.6%
R 42
 
5.5%
T 34
 
4.4%
Other values (16) 248
32.4%
Lowercase Letter
ValueCountFrequency (%)
a 99
12.8%
i 77
9.9%
e 76
9.8%
n 67
 
8.6%
o 62
 
8.0%
l 56
 
7.2%
r 54
 
7.0%
s 43
 
5.5%
t 39
 
5.0%
y 32
 
4.1%
Other values (15) 170
21.9%
Decimal Number
ValueCountFrequency (%)
2 19
22.1%
0 18
20.9%
1 14
16.3%
3 13
15.1%
6 5
 
5.8%
4 5
 
5.8%
8 4
 
4.7%
5 4
 
4.7%
9 3
 
3.5%
7 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 24
24.5%
? 21
21.4%
& 16
16.3%
, 15
15.3%
# 8
 
8.2%
' 6
 
6.1%
: 5
 
5.1%
; 2
 
2.0%
! 1
 
1.0%
Math Symbol
ValueCountFrequency (%)
× 1
33.3%
= 1
33.3%
+ 1
33.3%
Space Separator
ValueCountFrequency (%)
626
100.0%
Open Punctuation
ValueCountFrequency (%)
( 210
100.0%
Close Punctuation
ValueCountFrequency (%)
) 210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11396
80.3%
Latin 1541
 
10.9%
Common 1243
 
8.8%
Han 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
825
 
7.2%
778
 
6.8%
340
 
3.0%
332
 
2.9%
299
 
2.6%
279
 
2.4%
222
 
1.9%
219
 
1.9%
217
 
1.9%
191
 
1.7%
Other values (572) 7694
67.5%
Latin
ValueCountFrequency (%)
a 99
 
6.4%
A 91
 
5.9%
i 77
 
5.0%
e 76
 
4.9%
n 67
 
4.3%
o 62
 
4.0%
l 56
 
3.6%
I 56
 
3.6%
S 56
 
3.6%
O 54
 
3.5%
Other values (41) 847
55.0%
Common
ValueCountFrequency (%)
626
50.4%
( 210
 
16.9%
) 210
 
16.9%
. 24
 
1.9%
? 21
 
1.7%
2 19
 
1.5%
0 18
 
1.4%
& 16
 
1.3%
, 15
 
1.2%
1 14
 
1.1%
Other values (18) 70
 
5.6%
Han
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11396
80.3%
ASCII 2783
 
19.6%
CJK 8
 
0.1%
CJK Compat Ideographs 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
825
 
7.2%
778
 
6.8%
340
 
3.0%
332
 
2.9%
299
 
2.6%
279
 
2.4%
222
 
1.9%
219
 
1.9%
217
 
1.9%
191
 
1.7%
Other values (572) 7694
67.5%
ASCII
ValueCountFrequency (%)
626
22.5%
( 210
 
7.5%
) 210
 
7.5%
a 99
 
3.6%
A 91
 
3.3%
i 77
 
2.8%
e 76
 
2.7%
n 67
 
2.4%
o 62
 
2.2%
l 56
 
2.0%
Other values (68) 1209
43.4%
CJK
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
CJK Compat Ideographs
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
× 1
100.0%
Distinct1814
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
Minimum1999-03-02 00:00:00
Maximum2024-04-03 15:02:42
2024-04-06T20:25:28.391749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:28.685153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
I
1773 
U
594 
D
 
8

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 1773
74.7%
U 594
 
25.0%
D 8
 
0.3%

Length

2024-04-06T20:25:28.971329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:29.127632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1773
74.7%
u 594
 
25.0%
d 8
 
0.3%
Distinct671
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-06T20:25:29.306980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:29.635675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
일반미용업
1775 
피부미용업
302 
네일아트업
236 
메이크업업
 
55
기타
 
7

Length

Max length5
Median length5
Mean length4.9911579
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 1775
74.7%
피부미용업 302
 
12.7%
네일아트업 236
 
9.9%
메이크업업 55
 
2.3%
기타 7
 
0.3%

Length

2024-04-06T20:25:29.906911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:30.170389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 1775
74.7%
피부미용업 302
 
12.7%
네일아트업 236
 
9.9%
메이크업업 55
 
2.3%
기타 7
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1211
Distinct (%)54.4%
Missing149
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean203236.2
Minimum200812.99
Maximum206289.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:30.361727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200812.99
5-th percentile201312.55
Q1202294.73
median203020.6
Q3204288.24
95-th percentile205207.43
Maximum206289.35
Range5476.353
Interquartile range (IQR)1993.5095

Descriptive statistics

Standard deviation1260.6648
Coefficient of variation (CV)0.006202954
Kurtosis-0.88139039
Mean203236.2
Median Absolute Deviation (MAD)1009.4174
Skewness0.19751071
Sum4.5240378 × 108
Variance1589275.7
MonotonicityNot monotonic
2024-04-06T20:25:30.625302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202113.869605464 54
 
2.3%
202372.912023599 52
 
2.2%
202511.142930696 37
 
1.6%
202326.503044305 33
 
1.4%
203017.021457357 30
 
1.3%
202310.024153 28
 
1.2%
204827.43305161 24
 
1.0%
200812.992681398 13
 
0.5%
201153.981577199 13
 
0.5%
201383.023709556 11
 
0.5%
Other values (1201) 1931
81.3%
(Missing) 149
 
6.3%
ValueCountFrequency (%)
200812.992681398 13
0.5%
200896.532906303 2
 
0.1%
200906.190812824 2
 
0.1%
200913.361072125 2
 
0.1%
200951.206580662 3
 
0.1%
200967.537033206 3
 
0.1%
200992.431390651 1
 
< 0.1%
201003.806213 1
 
< 0.1%
201006.532910436 1
 
< 0.1%
201040.203347749 1
 
< 0.1%
ValueCountFrequency (%)
206289.345712421 1
 
< 0.1%
206267.144320265 2
0.1%
206243.875021499 1
 
< 0.1%
206209.280864162 4
0.2%
206194.671177891 1
 
< 0.1%
206111.359005992 1
 
< 0.1%
206000.441727742 2
0.1%
205988.094337105 1
 
< 0.1%
205980.145961489 1
 
< 0.1%
205973.675382673 3
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1211
Distinct (%)54.4%
Missing149
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean450210.49
Minimum448122.67
Maximum452076.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:30.844792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448122.67
5-th percentile448467.74
Q1449380.32
median450223.59
Q3451179.29
95-th percentile451709.95
Maximum452076.36
Range3953.6949
Interquartile range (IQR)1798.9607

Descriptive statistics

Standard deviation1046.5446
Coefficient of variation (CV)0.0023245673
Kurtosis-1.2065
Mean450210.49
Median Absolute Deviation (MAD)898.15028
Skewness-0.10025383
Sum1.0021686 × 109
Variance1095255.6
MonotonicityNot monotonic
2024-04-06T20:25:31.158298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451897.581865192 54
 
2.3%
451536.680876573 52
 
2.2%
450401.303715561 37
 
1.6%
450625.58422744 33
 
1.4%
451346.281102634 30
 
1.3%
451594.707188 28
 
1.2%
449134.994665839 24
 
1.0%
448855.571620972 13
 
0.5%
449188.97052419 13
 
0.5%
449744.280482389 11
 
0.5%
Other values (1201) 1931
81.3%
(Missing) 149
 
6.3%
ValueCountFrequency (%)
448122.666937252 5
0.2%
448161.483897254 1
 
< 0.1%
448204.648305568 1
 
< 0.1%
448221.641970907 1
 
< 0.1%
448228.610508055 1
 
< 0.1%
448229.126737125 2
 
0.1%
448230.017333138 4
0.2%
448232.182116128 2
 
0.1%
448233.668314987 2
 
0.1%
448236.227470207 1
 
< 0.1%
ValueCountFrequency (%)
452076.36180744 1
< 0.1%
452041.559037331 1
< 0.1%
452025.098341202 1
< 0.1%
452019.132498433 1
< 0.1%
452014.305822436 1
< 0.1%
451990.784198029 1
< 0.1%
451988.475241522 1
< 0.1%
451976.118093839 1
< 0.1%
451970.785176715 1
< 0.1%
451963.04040364 2
0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
미용업
725 
일반미용업
589 
<NA>
444 
종합미용업
250 
피부미용업
191 
Other values (11)
176 

Length

Max length23
Median length19
Mean length4.4770526
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 725
30.5%
일반미용업 589
24.8%
<NA> 444
18.7%
종합미용업 250
 
10.5%
피부미용업 191
 
8.0%
네일미용업 105
 
4.4%
피부미용업, 네일미용업 20
 
0.8%
화장ㆍ분장 미용업 15
 
0.6%
네일미용업, 화장ㆍ분장 미용업 12
 
0.5%
피부미용업, 네일미용업, 화장ㆍ분장 미용업 6
 
0.3%
Other values (6) 18
 
0.8%

Length

2024-04-06T20:25:31.444143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 769
30.9%
일반미용업 604
24.3%
na 444
17.9%
종합미용업 250
 
10.1%
피부미용업 225
 
9.0%
네일미용업 151
 
6.1%
화장ㆍ분장 44
 
1.8%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.9%
Missing657
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean0.45518044
Minimum0
Maximum19
Zeros1489
Zeros (%)62.7%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:31.669617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4142236
Coefficient of variation (CV)3.1069517
Kurtosis40.404977
Mean0.45518044
Median Absolute Deviation (MAD)0
Skewness5.0363534
Sum782
Variance2.0000285
MonotonicityNot monotonic
2024-04-06T20:25:32.511149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 1489
62.7%
3 65
 
2.7%
4 57
 
2.4%
2 51
 
2.1%
1 23
 
1.0%
5 15
 
0.6%
6 8
 
0.3%
7 3
 
0.1%
19 1
 
< 0.1%
12 1
 
< 0.1%
Other values (5) 5
 
0.2%
(Missing) 657
27.7%
ValueCountFrequency (%)
0 1489
62.7%
1 23
 
1.0%
2 51
 
2.1%
3 65
 
2.7%
4 57
 
2.4%
5 15
 
0.6%
6 8
 
0.3%
7 3
 
0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
19 1
 
< 0.1%
17 1
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
7 3
 
0.1%
6 8
0.3%
5 15
0.6%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.4%
Missing692
Missing (%)29.1%
Infinite0
Infinite (%)0.0%
Mean0.11586453
Minimum0
Maximum6
Zeros1525
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:32.774229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.41978876
Coefficient of variation (CV)3.6230999
Kurtosis45.399172
Mean0.11586453
Median Absolute Deviation (MAD)0
Skewness5.5467656
Sum195
Variance0.1762226
MonotonicityNot monotonic
2024-04-06T20:25:32.937568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1525
64.2%
1 137
 
5.8%
2 11
 
0.5%
3 6
 
0.3%
4 3
 
0.1%
6 1
 
< 0.1%
(Missing) 692
29.1%
ValueCountFrequency (%)
0 1525
64.2%
1 137
 
5.8%
2 11
 
0.5%
3 6
 
0.3%
4 3
 
0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
4 3
 
0.1%
3 6
 
0.3%
2 11
 
0.5%
1 137
 
5.8%
0 1525
64.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.5%
Missing1049
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean0.54147813
Minimum0
Maximum6
Zeros845
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:33.277283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.87187445
Coefficient of variation (CV)1.6101748
Kurtosis5.1931129
Mean0.54147813
Median Absolute Deviation (MAD)0
Skewness2.0178313
Sum718
Variance0.76016506
MonotonicityNot monotonic
2024-04-06T20:25:33.572778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 845
35.6%
1 315
 
13.3%
2 117
 
4.9%
3 34
 
1.4%
4 10
 
0.4%
5 3
 
0.1%
6 2
 
0.1%
(Missing) 1049
44.2%
ValueCountFrequency (%)
0 845
35.6%
1 315
 
13.3%
2 117
 
4.9%
3 34
 
1.4%
4 10
 
0.4%
5 3
 
0.1%
6 2
 
0.1%
ValueCountFrequency (%)
6 2
 
0.1%
5 3
 
0.1%
4 10
 
0.4%
3 34
 
1.4%
2 117
 
4.9%
1 315
 
13.3%
0 845
35.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.3%
Missing1771
Missing (%)74.6%
Infinite0
Infinite (%)0.0%
Mean1.1324503
Minimum0
Maximum13
Zeros139
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:33.778986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0361653
Coefficient of variation (CV)0.91497633
Kurtosis29.792134
Mean1.1324503
Median Absolute Deviation (MAD)0
Skewness3.3762528
Sum684
Variance1.0736384
MonotonicityNot monotonic
2024-04-06T20:25:33.970831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 315
 
13.3%
0 139
 
5.9%
2 109
 
4.6%
3 28
 
1.2%
4 8
 
0.3%
6 2
 
0.1%
5 2
 
0.1%
13 1
 
< 0.1%
(Missing) 1771
74.6%
ValueCountFrequency (%)
0 139
5.9%
1 315
13.3%
2 109
 
4.6%
3 28
 
1.2%
4 8
 
0.3%
5 2
 
0.1%
6 2
 
0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
6 2
 
0.1%
5 2
 
0.1%
4 8
 
0.3%
3 28
 
1.2%
2 109
 
4.6%
1 315
13.3%
0 139
5.9%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
1382 
0
950 
1
 
33
2
 
7
3
 
2

Length

Max length4
Median length4
Mean length2.7456842
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1382
58.2%
0 950
40.0%
1 33
 
1.4%
2 7
 
0.3%
3 2
 
0.1%
4 1
 
< 0.1%

Length

2024-04-06T20:25:34.223690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:34.472012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1382
58.2%
0 950
40.0%
1 33
 
1.4%
2 7
 
0.3%
3 2
 
0.1%
4 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
2090 
0
242 
1
 
34
2
 
7
3
 
2

Length

Max length4
Median length4
Mean length3.64
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2090
88.0%
0 242
 
10.2%
1 34
 
1.4%
2 7
 
0.3%
3 2
 
0.1%

Length

2024-04-06T20:25:34.777970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:35.033443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2090
88.0%
0 242
 
10.2%
1 34
 
1.4%
2 7
 
0.3%
3 2
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
0
1578 
<NA>
797 

Length

Max length4
Median length1
Mean length2.0067368
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1578
66.4%
<NA> 797
33.6%

Length

2024-04-06T20:25:35.326923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:35.522467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1578
66.4%
na 797
33.6%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
0
1578 
<NA>
797 

Length

Max length4
Median length1
Mean length2.0067368
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1578
66.4%
<NA> 797
33.6%

Length

2024-04-06T20:25:35.700140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:35.901126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1578
66.4%
na 797
33.6%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
0
1578 
<NA>
797 

Length

Max length4
Median length1
Mean length2.0067368
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1578
66.4%
<NA> 797
33.6%

Length

2024-04-06T20:25:36.114825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:36.303705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1578
66.4%
na 797
33.6%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing467
Missing (%)19.7%
Memory size4.8 KiB
False
1908 
(Missing)
467 
ValueCountFrequency (%)
False 1908
80.3%
(Missing) 467
 
19.7%
2024-04-06T20:25:36.435636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct24
Distinct (%)1.3%
Missing498
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean3.4299414
Minimum0
Maximum214
Zeros296
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:36.601456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile8
Maximum214
Range214
Interquartile range (IQR)2

Descriptive statistics

Standard deviation8.2738973
Coefficient of variation (CV)2.4122562
Kurtosis525.61621
Mean3.4299414
Median Absolute Deviation (MAD)1
Skewness21.986018
Sum6438
Variance68.457376
MonotonicityNot monotonic
2024-04-06T20:25:36.821730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3 586
24.7%
2 358
15.1%
4 299
12.6%
0 296
12.5%
5 115
 
4.8%
6 76
 
3.2%
8 40
 
1.7%
1 30
 
1.3%
10 22
 
0.9%
7 18
 
0.8%
Other values (14) 37
 
1.6%
(Missing) 498
21.0%
ValueCountFrequency (%)
0 296
12.5%
1 30
 
1.3%
2 358
15.1%
3 586
24.7%
4 299
12.6%
5 115
 
4.8%
6 76
 
3.2%
7 18
 
0.8%
8 40
 
1.7%
9 13
 
0.5%
ValueCountFrequency (%)
214 1
 
< 0.1%
195 1
 
< 0.1%
194 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
20 1
 
< 0.1%
18 2
 
0.1%
16 5
0.2%
15 1
 
< 0.1%
14 1
 
< 0.1%
Distinct3
Distinct (%)75.0%
Missing2371
Missing (%)99.8%
Memory size18.7 KiB
2024-04-06T20:25:37.086081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length61.5
Mean length50
Min length8

Characters and Unicode

Total characters200
Distinct characters64
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row이 영업신고의 효력은 건축물 임시사용승인기간 2012.4.30까지이며 건축물 사용승인 연장 또는 준공 완료시 재신청 해야 함
2nd row이 영업신고의 효력은 건축물 임시사용승인기간 2012.4.30까지이며 건축물 사용승인 연장 또는 준공 완료시 재신청 해야 함
3rd row직권폐업(말소)
4th row아래 영업기간 동안만 영업가능, 기간연장시 시설물사용기간 연장승인 후 영업기간 변경신청하여야 함.
ValueCountFrequency (%)
건축물 4
 
9.5%
3
 
7.1%
2
 
4.8%
준공 2
 
4.8%
영업기간 2
 
4.8%
영업신고의 2
 
4.8%
재신청 2
 
4.8%
완료시 2
 
4.8%
해야 2
 
4.8%
또는 2
 
4.8%
Other values (14) 19
45.2%
2024-04-06T20:25:37.618310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
19.0%
6
 
3.0%
6
 
3.0%
6
 
3.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
. 5
 
2.5%
Other values (54) 113
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140
70.0%
Space Separator 38
 
19.0%
Decimal Number 14
 
7.0%
Other Punctuation 6
 
3.0%
Close Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
4.3%
6
 
4.3%
6
 
4.3%
6
 
4.3%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
Other values (44) 86
61.4%
Decimal Number
ValueCountFrequency (%)
0 4
28.6%
2 4
28.6%
1 2
14.3%
4 2
14.3%
3 2
14.3%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140
70.0%
Common 60
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
4.3%
6
 
4.3%
6
 
4.3%
6
 
4.3%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
Other values (44) 86
61.4%
Common
ValueCountFrequency (%)
38
63.3%
. 5
 
8.3%
0 4
 
6.7%
2 4
 
6.7%
1 2
 
3.3%
4 2
 
3.3%
3 2
 
3.3%
, 1
 
1.7%
) 1
 
1.7%
( 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140
70.0%
ASCII 60
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
63.3%
. 5
 
8.3%
0 4
 
6.7%
2 4
 
6.7%
1 2
 
3.3%
4 2
 
3.3%
3 2
 
3.3%
, 1
 
1.7%
) 1
 
1.7%
( 1
 
1.7%
Hangul
ValueCountFrequency (%)
6
 
4.3%
6
 
4.3%
6
 
4.3%
6
 
4.3%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
Other values (44) 86
61.4%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
2371 
20120301
 
2
20100801
 
1
20160418
 
1

Length

Max length8
Median length4
Mean length4.0067368
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2371
99.8%
20120301 2
 
0.1%
20100801 1
 
< 0.1%
20160418 1
 
< 0.1%

Length

2024-04-06T20:25:37.867233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:38.071325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2371
99.8%
20120301 2
 
0.1%
20100801 1
 
< 0.1%
20160418 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
2371 
20120430
 
2
20111231
 
1
20190405
 
1

Length

Max length8
Median length4
Mean length4.0067368
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2371
99.8%
20120430 2
 
0.1%
20111231 1
 
< 0.1%
20190405 1
 
< 0.1%

Length

2024-04-06T20:25:38.270412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:38.441631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2371
99.8%
20120430 2
 
0.1%
20111231 1
 
< 0.1%
20190405 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
2194 
임대
 
177
자가
 
4

Length

Max length4
Median length4
Mean length3.8475789
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> 2194
92.4%
임대 177
 
7.5%
자가 4
 
0.2%

Length

2024-04-06T20:25:38.664461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:38.817277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2194
92.4%
임대 177
 
7.5%
자가 4
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
1504 
0
871 

Length

Max length4
Median length4
Mean length2.8997895
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1504
63.3%
0 871
36.7%

Length

2024-04-06T20:25:38.990018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:39.135458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1504
63.3%
0 871
36.7%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.1%
Missing1838
Missing (%)77.4%
Infinite0
Infinite (%)0.0%
Mean0.10986965
Minimum0
Maximum5
Zeros501
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:39.279446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50835866
Coefficient of variation (CV)4.6269254
Kurtosis46.801238
Mean0.10986965
Median Absolute Deviation (MAD)0
Skewness6.3378928
Sum59
Variance0.25842853
MonotonicityNot monotonic
2024-04-06T20:25:39.456089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 501
 
21.1%
1 26
 
1.1%
3 5
 
0.2%
5 2
 
0.1%
2 2
 
0.1%
4 1
 
< 0.1%
(Missing) 1838
77.4%
ValueCountFrequency (%)
0 501
21.1%
1 26
 
1.1%
2 2
 
0.1%
3 5
 
0.2%
4 1
 
< 0.1%
5 2
 
0.1%
ValueCountFrequency (%)
5 2
 
0.1%
4 1
 
< 0.1%
3 5
 
0.2%
2 2
 
0.1%
1 26
 
1.1%
0 501
21.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
1838 
0
527 
1
 
7
2
 
3

Length

Max length4
Median length4
Mean length3.3216842
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1838
77.4%
0 527
 
22.2%
1 7
 
0.3%
2 3
 
0.1%

Length

2024-04-06T20:25:39.686971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:39.954239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1838
77.4%
0 527
 
22.2%
1 7
 
0.3%
2 3
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
<NA>
1553 
0
822 

Length

Max length4
Median length4
Mean length2.9616842
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1553
65.4%
0 822
34.6%

Length

2024-04-06T20:25:40.211216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:40.418129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1553
65.4%
0 822
34.6%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.5%
Missing1564
Missing (%)65.9%
Infinite0
Infinite (%)0.0%
Mean0.95314427
Minimum0
Maximum11
Zeros537
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-04-06T20:25:40.574557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7827083
Coefficient of variation (CV)1.8703446
Kurtosis8.4726515
Mean0.95314427
Median Absolute Deviation (MAD)0
Skewness2.6357696
Sum773
Variance3.1780487
MonotonicityNot monotonic
2024-04-06T20:25:40.745481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 537
 
22.6%
2 92
 
3.9%
1 68
 
2.9%
3 46
 
1.9%
4 30
 
1.3%
5 14
 
0.6%
6 8
 
0.3%
10 6
 
0.3%
7 3
 
0.1%
8 3
 
0.1%
Other values (2) 4
 
0.2%
(Missing) 1564
65.9%
ValueCountFrequency (%)
0 537
22.6%
1 68
 
2.9%
2 92
 
3.9%
3 46
 
1.9%
4 30
 
1.3%
5 14
 
0.6%
6 8
 
0.3%
7 3
 
0.1%
8 3
 
0.1%
9 2
 
0.1%
ValueCountFrequency (%)
11 2
 
0.1%
10 6
 
0.3%
9 2
 
0.1%
8 3
 
0.1%
7 3
 
0.1%
6 8
 
0.3%
5 14
 
0.6%
4 30
 
1.3%
3 46
1.9%
2 92
3.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing444
Missing (%)18.7%
Memory size4.8 KiB
False
1931 
(Missing)
444 
ValueCountFrequency (%)
False 1931
81.3%
(Missing) 444
 
18.7%
2024-04-06T20:25:40.905950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030300003030000-204-1938-0093019380220<NA>3폐업2폐업19941103<NA><NA><NA>020000000018.31133867서울특별시 성동구 행당동 286-30번지<NA><NA>노블2004-02-17 00:00:00I2018-08-31 23:59:59.0일반미용업202890.719473451032.813701미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130300003030000-204-1957-0096819570414<NA>3폐업2폐업19941103<NA><NA><NA>020000000014.85133818서울특별시 성동구 사근동 309-11번지<NA><NA>지현2001-09-25 00:00:00I2018-08-31 23:59:59.0일반미용업203755.894586450927.418898미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230300003030000-204-1964-0102219640728<NA>3폐업2폐업20070403<NA><NA><NA><NA>13.0133882서울특별시 성동구 도선동 185-8번지<NA><NA>화용2007-04-02 00:00:00I2018-08-31 23:59:59.0일반미용업202842.458472451322.546397미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330300003030000-204-1965-0070819650804<NA>3폐업2폐업20030215<NA><NA><NA>020000000020.03133811서울특별시 성동구 마장동 311-1번지<NA><NA>형제2003-02-17 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430300003030000-204-1967-0051619670610<NA>3폐업2폐업19980804<NA><NA><NA>020000000018.0133817서울특별시 성동구 사근동 176-7번지<NA><NA>화옥2001-09-25 00:00:00I2018-08-31 23:59:59.0일반미용업204029.399658450907.904927미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530300003030000-204-1967-0063019671106<NA>3폐업2폐업19961108<NA><NA><NA>02 293058612.69133880서울특별시 성동구 홍익동 240-0번지<NA><NA>향수2001-09-25 00:00:00I2018-08-31 23:59:59.0일반미용업202972.211646451482.171535미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630300003030000-204-1967-0064819670710<NA>3폐업2폐업20030215<NA><NA><NA>020000000020.33133864서울특별시 성동구 행당동 128-22번지<NA><NA>샬롬2003-02-17 00:00:00I2018-08-31 23:59:59.0일반미용업203353.475522450634.473989미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730300003030000-204-1967-0103819671205<NA>3폐업2폐업20011222<NA><NA><NA>020927584648.93133856서울특별시 성동구 하왕십리동 881-0번지<NA><NA>영헤어샵2001-12-27 00:00:00I2018-08-31 23:59:59.0일반미용업202328.119718451346.582221미용업000<NA>0<NA>000N8<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830300003030000-204-1968-0086019681022<NA>3폐업2폐업20011222<NA><NA><NA>020000000012.3133828서울특별시 성동구 성수동2가 560-1번지<NA><NA>지혜2002-01-07 00:00:00I2018-08-31 23:59:59.0일반미용업204814.703936448278.927222미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930300003030000-204-1969-0067319690403<NA>3폐업2폐업20050905<NA><NA><NA>020000000016.45133838서울특별시 성동구 옥수동 5-0번지<NA><NA>향원2004-11-30 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
236530300003030000-225-2023-000012023-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.31133-822서울특별시 성동구 성수동1가 13-177서울특별시 성동구 상원6길 10-1, 4층 (성수동1가)4790유앤유2023-05-19 12:01:08U2022-12-04 22:01:00.0메이크업업204294.652753449609.789051<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236630300003030000-225-2023-000022023-06-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>124.33133-824서울특별시 성동구 성수동1가 668-3서울특별시 성동구 서울숲6길 9, 3층 (성수동1가)4768베이 뷰티 스튜디오(BAIE BEAUTY STUDIO)2023-06-08 12:21:34I2022-12-05 23:00:00.0일반미용업203708.933743449507.876899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236730300003030000-226-2016-0000120160426<NA>3폐업2폐업20191119<NA><NA><NA>02 757771527.76133855서울특별시 성동구 하왕십리동 700번지 센트라스 L동 114-2호서울특별시 성동구 왕십리로 410, L동 1층 114-2호 (하왕십리동, 센트라스)4701아이꼬2019-11-19 14:10:07U2019-11-21 02:40:00.0네일아트업202310.024153451594.707188피부미용업, 네일미용업, 화장ㆍ분장 미용업000011000N4<NA><NA><NA>임대00002N
236830300003030000-226-2018-0000120180716<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.27133020서울특별시 성동구 하왕십리동 1070번지 센트라스서울특별시 성동구 왕십리로 410, C동 2층 203호 (하왕십리동, 센트라스)4701네일쥬스2018-07-16 15:18:15I2018-08-31 23:59:59.0네일아트업202372.912024451536.680877피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA><NA><NA>000N3<NA><NA><NA><NA>00001N
236930300003030000-226-2019-0000120190620<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.17133094서울특별시 성동구 금호동4가 1553번지 힐스테이트 서울숲리버서울특별시 성동구 금호로 40, 상가동 지하2층 20-5호 (금호동4가, 힐스테이트 서울숲리버)4743네일살롱 바이선하(NAIL SALON by Sunha)2019-06-20 14:39:05I2019-06-22 02:21:18.0네일아트업<NA><NA>피부미용업, 네일미용업, 화장ㆍ분장 미용업02<NA><NA><NA><NA>000N5<NA><NA><NA><NA>00001N
237030300003030000-226-2019-0000220190816<NA>1영업/정상1영업<NA><NA><NA><NA>022295310931.28133880서울특별시 성동구 홍익동 96번지서울특별시 성동구 무학로12길 12, 1층 (홍익동)4706꽃단장2020-06-04 17:52:57U2020-06-06 02:40:00.0네일아트업202707.146556451638.576616피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA><NA><NA>000N3<NA><NA><NA><NA>00001N
237130300003030000-226-2021-0000120210511<NA>1영업/정상1영업<NA><NA><NA><NA><NA>68.0133882서울특별시 성동구 도선동 46 W에비뉴타워서울특별시 성동구 왕십리로 320, 4층 402호 (도선동)4709뷰티하임2021-07-01 09:16:29U2021-07-03 02:40:00.0메이크업업202967.042457451118.8096피부미용업, 네일미용업, 화장ㆍ분장 미용업000000000N3<NA><NA><NA><NA>00003N
237230300003030000-226-2021-0000220210914<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.19133010서울특별시 성동구 상왕십리동 811 텐즈힐서울특별시 성동구 마장로 137, 1층 163호 (상왕십리동, 텐즈힐)4700모드네일2021-09-14 13:28:39I2021-09-16 00:22:48.0네일아트업202113.869605451897.581865피부미용업, 네일미용업, 화장ㆍ분장 미용업000000000N2<NA><NA><NA><NA>00001N
237330300003030000-226-2023-000012023-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.97133-020서울특별시 성동구 하왕십리동 1070 센트라스서울특별시 성동구 왕십리로 410, I동 1층 143호 (하왕십리동, 센트라스)4701엘로디뷰티2023-03-06 16:06:27I2022-12-03 00:08:00.0메이크업업202372.912024451536.680877<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
237430300003030000-226-2024-000012024-01-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>44.01133-923서울특별시 성동구 성수동1가 718 트리마제서울특별시 성동구 왕십리로 16, 근린생활시설동 2층 206호 (성수동1가, 트리마제)4773성수 두손네일2024-02-06 15:18:11I2023-12-02 00:08:00.0네일아트업203911.513091448508.756036<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>