Overview

Dataset statistics

Number of variables47
Number of observations6074
Missing cells60538
Missing cells (%)21.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 MiB
Average record size in memory403.0 B

Variable types

Categorical20
Text8
DateTime4
Unsupported4
Numeric9
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-17925/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
사용시작지하층 is highly imbalanced (62.6%)Imbalance
사용끝지하층 is highly imbalanced (78.6%)Imbalance
조건부허가시작일자 is highly imbalanced (99.8%)Imbalance
조건부허가종료일자 is highly imbalanced (99.8%)Imbalance
건물소유구분명 is highly imbalanced (58.6%)Imbalance
여성종사자수 is highly imbalanced (60.6%)Imbalance
남성종사자수 is highly imbalanced (50.4%)Imbalance
인허가취소일자 has 6074 (100.0%) missing valuesMissing
폐업일자 has 2156 (35.5%) missing valuesMissing
휴업시작일자 has 6074 (100.0%) missing valuesMissing
휴업종료일자 has 6074 (100.0%) missing valuesMissing
재개업일자 has 6074 (100.0%) missing valuesMissing
전화번호 has 2507 (41.3%) missing valuesMissing
도로명주소 has 2078 (34.2%) missing valuesMissing
도로명우편번호 has 2091 (34.4%) missing valuesMissing
좌표정보(X) has 938 (15.4%) missing valuesMissing
좌표정보(Y) has 938 (15.4%) missing valuesMissing
건물지상층수 has 2324 (38.3%) missing valuesMissing
건물지하층수 has 2600 (42.8%) missing valuesMissing
사용시작지상층 has 3041 (50.1%) missing valuesMissing
사용끝지상층 has 3864 (63.6%) missing valuesMissing
발한실여부 has 1175 (19.3%) missing valuesMissing
좌석수 has 1637 (27.0%) missing valuesMissing
조건부허가신고사유 has 6073 (> 99.9%) missing valuesMissing
침대수 has 3695 (60.8%) missing valuesMissing
다중이용업소여부 has 1121 (18.5%) missing valuesMissing
사용끝지상층 is highly skewed (γ1 = 28.3834455)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
건물지상층수 has 3077 (50.7%) zerosZeros
건물지하층수 has 3280 (54.0%) zerosZeros
사용시작지상층 has 869 (14.3%) zerosZeros
사용끝지상층 has 130 (2.1%) zerosZeros
좌석수 has 194 (3.2%) zerosZeros
침대수 has 1522 (25.1%) zerosZeros

Reproduction

Analysis started2024-05-11 01:10:04.713644
Analysis finished2024-05-11 01:10:10.198544
Duration5.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
3230000
6074 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 6074
100.0%

Length

2024-05-11T01:10:10.409624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:10.805399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 6074
100.0%

관리번호
Text

UNIQUE 

Distinct6074
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
2024-05-11T01:10:11.617614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters133628
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

Unique6074 ?
Unique (%)100.0%

Sample

1st row3230000-204-1969-01858
2nd row3230000-204-1970-01554
3rd row3230000-204-1974-01053
4th row3230000-204-1977-01659
5th row3230000-204-1978-01636
ValueCountFrequency (%)
3230000-204-1969-01858 1
 
< 0.1%
3230000-212-2010-00100 1
 
< 0.1%
3230000-212-2011-00003 1
 
< 0.1%
3230000-212-2011-00002 1
 
< 0.1%
3230000-212-2011-00001 1
 
< 0.1%
3230000-212-2010-00106 1
 
< 0.1%
3230000-212-2010-00105 1
 
< 0.1%
3230000-212-2010-00104 1
 
< 0.1%
3230000-212-2011-00013 1
 
< 0.1%
3230000-212-2010-00102 1
 
< 0.1%
Other values (6064) 6064
99.8%
2024-05-11T01:10:12.831296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51106
38.2%
2 21586
16.2%
- 18222
 
13.6%
3 15080
 
11.3%
1 12436
 
9.3%
4 3916
 
2.9%
9 3769
 
2.8%
5 2122
 
1.6%
8 2078
 
1.6%
6 1672
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 115406
86.4%
Dash Punctuation 18222
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51106
44.3%
2 21586
18.7%
3 15080
 
13.1%
1 12436
 
10.8%
4 3916
 
3.4%
9 3769
 
3.3%
5 2122
 
1.8%
8 2078
 
1.8%
6 1672
 
1.4%
7 1641
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 18222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 133628
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51106
38.2%
2 21586
16.2%
- 18222
 
13.6%
3 15080
 
11.3%
1 12436
 
9.3%
4 3916
 
2.9%
9 3769
 
2.8%
5 2122
 
1.6%
8 2078
 
1.6%
6 1672
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51106
38.2%
2 21586
16.2%
- 18222
 
13.6%
3 15080
 
11.3%
1 12436
 
9.3%
4 3916
 
2.9%
9 3769
 
2.8%
5 2122
 
1.6%
8 2078
 
1.6%
6 1672
 
1.3%
Distinct3528
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
Minimum1969-08-27 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T01:10:13.435554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:10:14.123139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6074
Missing (%)100.0%
Memory size53.5 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
3
3918 
1
2156 

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 3918
64.5%
1 2156
35.5%

Length

2024-05-11T01:10:14.659325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:15.167633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3918
64.5%
1 2156
35.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
폐업
3918 
영업/정상
2156 

Length

Max length5
Median length2
Mean length3.0648666
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3918
64.5%
영업/정상 2156
35.5%

Length

2024-05-11T01:10:15.707121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:16.149553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3918
64.5%
영업/정상 2156
35.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
2
3918 
1
2156 

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 3918
64.5%
1 2156
35.5%

Length

2024-05-11T01:10:16.630250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:17.105658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3918
64.5%
1 2156
35.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
폐업
3918 
영업
2156 

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 3918
64.5%
영업 2156
35.5%

Length

2024-05-11T01:10:17.692531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:18.046649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3918
64.5%
영업 2156
35.5%

폐업일자
Date

MISSING 

Distinct2581
Distinct (%)65.9%
Missing2156
Missing (%)35.5%
Memory size47.6 KiB
Minimum1990-10-24 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T01:10:18.481979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:10:18.992684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6074
Missing (%)100.0%
Memory size53.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6074
Missing (%)100.0%
Memory size53.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6074
Missing (%)100.0%
Memory size53.5 KiB

전화번호
Text

MISSING 

Distinct3085
Distinct (%)86.5%
Missing2507
Missing (%)41.3%
Memory size47.6 KiB
2024-05-11T01:10:19.707853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.594337
Min length2

Characters and Unicode

Total characters37790
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

Unique2784 ?
Unique (%)78.0%

Sample

1st row0204004671
2nd row02 4008322
3rd row02 4009398
4th row02 4809108
5th row02 4433636
ValueCountFrequency (%)
02 2744
35.9%
070 77
 
1.0%
422 56
 
0.7%
400 51
 
0.7%
00000 48
 
0.6%
0 47
 
0.6%
423 46
 
0.6%
420 43
 
0.6%
415 39
 
0.5%
412 38
 
0.5%
Other values (3059) 4453
58.3%
2024-05-11T01:10:20.797544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7169
19.0%
2 6290
16.6%
5397
14.3%
4 4907
13.0%
1 2716
 
7.2%
3 2434
 
6.4%
7 2044
 
5.4%
8 1891
 
5.0%
5 1772
 
4.7%
6 1617
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32393
85.7%
Space Separator 5397
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7169
22.1%
2 6290
19.4%
4 4907
15.1%
1 2716
 
8.4%
3 2434
 
7.5%
7 2044
 
6.3%
8 1891
 
5.8%
5 1772
 
5.5%
6 1617
 
5.0%
9 1553
 
4.8%
Space Separator
ValueCountFrequency (%)
5397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7169
19.0%
2 6290
16.6%
5397
14.3%
4 4907
13.0%
1 2716
 
7.2%
3 2434
 
6.4%
7 2044
 
5.4%
8 1891
 
5.0%
5 1772
 
4.7%
6 1617
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7169
19.0%
2 6290
16.6%
5397
14.3%
4 4907
13.0%
1 2716
 
7.2%
3 2434
 
6.4%
7 2044
 
5.4%
8 1891
 
5.0%
5 1772
 
4.7%
6 1617
 
4.3%
Distinct2244
Distinct (%)37.0%
Missing1
Missing (%)< 0.1%
Memory size47.6 KiB
2024-05-11T01:10:21.621036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9015314
Min length3

Characters and Unicode

Total characters29767
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1427 ?
Unique (%)23.5%

Sample

1st row19.95
2nd row12.94
3rd row11.55
4th row15.58
5th row33.86
ValueCountFrequency (%)
00 508
 
8.4%
33.00 346
 
5.7%
30.00 110
 
1.8%
26.40 85
 
1.4%
66.00 73
 
1.2%
24.00 59
 
1.0%
25.00 59
 
1.0%
23.00 53
 
0.9%
23.10 52
 
0.9%
20.00 48
 
0.8%
Other values (2234) 4680
77.1%
2024-05-11T01:10:22.957689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6950
23.3%
. 6073
20.4%
2 2682
 
9.0%
3 2611
 
8.8%
1 2472
 
8.3%
4 1859
 
6.2%
6 1720
 
5.8%
5 1658
 
5.6%
9 1343
 
4.5%
8 1282
 
4.3%
Other values (2) 1117
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23693
79.6%
Other Punctuation 6074
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6950
29.3%
2 2682
 
11.3%
3 2611
 
11.0%
1 2472
 
10.4%
4 1859
 
7.8%
6 1720
 
7.3%
5 1658
 
7.0%
9 1343
 
5.7%
8 1282
 
5.4%
7 1116
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 6073
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 29767
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6950
23.3%
. 6073
20.4%
2 2682
 
9.0%
3 2611
 
8.8%
1 2472
 
8.3%
4 1859
 
6.2%
6 1720
 
5.8%
5 1658
 
5.6%
9 1343
 
4.5%
8 1282
 
4.3%
Other values (2) 1117
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29767
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6950
23.3%
. 6073
20.4%
2 2682
 
9.0%
3 2611
 
8.8%
1 2472
 
8.3%
4 1859
 
6.2%
6 1720
 
5.8%
5 1658
 
5.6%
9 1343
 
4.5%
8 1282
 
4.3%
Other values (2) 1117
 
3.8%
Distinct225
Distinct (%)3.7%
Missing2
Missing (%)< 0.1%
Memory size47.6 KiB
2024-05-11T01:10:23.879812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1222003
Min length6

Characters and Unicode

Total characters37174
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

Unique31 ?
Unique (%)0.5%

Sample

1st row138210
2nd row138210
3rd row138831
4th row138872
5th row138120
ValueCountFrequency (%)
138210 665
 
11.0%
138888 174
 
2.9%
138934 160
 
2.6%
138200 129
 
2.1%
138861 107
 
1.8%
138862 104
 
1.7%
138830 93
 
1.5%
138160 92
 
1.5%
138829 89
 
1.5%
138812 88
 
1.4%
Other values (215) 4371
72.0%
2024-05-11T01:10:25.112708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 11417
30.7%
1 8260
22.2%
3 7258
19.5%
0 2170
 
5.8%
2 2055
 
5.5%
4 1369
 
3.7%
6 1106
 
3.0%
5 1081
 
2.9%
9 982
 
2.6%
- 742
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36432
98.0%
Dash Punctuation 742
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 11417
31.3%
1 8260
22.7%
3 7258
19.9%
0 2170
 
6.0%
2 2055
 
5.6%
4 1369
 
3.8%
6 1106
 
3.0%
5 1081
 
3.0%
9 982
 
2.7%
7 734
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 742
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37174
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 11417
30.7%
1 8260
22.2%
3 7258
19.5%
0 2170
 
5.8%
2 2055
 
5.5%
4 1369
 
3.7%
6 1106
 
3.0%
5 1081
 
2.9%
9 982
 
2.6%
- 742
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37174
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 11417
30.7%
1 8260
22.2%
3 7258
19.5%
0 2170
 
5.8%
2 2055
 
5.5%
4 1369
 
3.7%
6 1106
 
3.0%
5 1081
 
2.9%
9 982
 
2.6%
- 742
 
2.0%
Distinct4677
Distinct (%)77.0%
Missing1
Missing (%)< 0.1%
Memory size47.6 KiB
2024-05-11T01:10:25.726100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length48
Mean length25.328833
Min length8

Characters and Unicode

Total characters153822
Distinct characters402
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3952 ?
Unique (%)65.1%

Sample

1st row서울특별시 송파구 장지동 산 307-21번지
2nd row서울특별시 송파구 장지동 산 356-1번지
3rd row서울특별시 송파구 방이동 135-26번지
4th row서울특별시 송파구 풍납동 141-1번지
5th row서울특별시 송파구 마천동 산 129-13번지 지상1층
ValueCountFrequency (%)
서울특별시 6072
20.4%
송파구 6072
20.4%
잠실동 847
 
2.8%
장지동 799
 
2.7%
가락동 748
 
2.5%
문정동 696
 
2.3%
667
 
2.2%
방이동 540
 
1.8%
송파동 495
 
1.7%
지상1층 453
 
1.5%
Other values (4235) 12349
41.5%
2024-05-11T01:10:26.781629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28263
18.4%
7146
 
4.6%
1 7041
 
4.6%
6692
 
4.4%
6367
 
4.1%
6236
 
4.1%
6119
 
4.0%
6094
 
4.0%
6078
 
4.0%
6076
 
4.0%
Other values (392) 67710
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92900
60.4%
Space Separator 28263
 
18.4%
Decimal Number 26986
 
17.5%
Dash Punctuation 4820
 
3.1%
Uppercase Letter 364
 
0.2%
Close Punctuation 178
 
0.1%
Open Punctuation 172
 
0.1%
Other Punctuation 112
 
0.1%
Lowercase Letter 21
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7146
 
7.7%
6692
 
7.2%
6367
 
6.9%
6236
 
6.7%
6119
 
6.6%
6094
 
6.6%
6078
 
6.5%
6076
 
6.5%
6073
 
6.5%
6072
 
6.5%
Other values (335) 29947
32.2%
Uppercase Letter
ValueCountFrequency (%)
A 123
33.8%
B 62
17.0%
S 31
 
8.5%
N 15
 
4.1%
T 15
 
4.1%
K 13
 
3.6%
C 12
 
3.3%
D 11
 
3.0%
F 10
 
2.7%
I 9
 
2.5%
Other values (14) 63
17.3%
Lowercase Letter
ValueCountFrequency (%)
l 4
19.0%
o 3
14.3%
e 3
14.3%
a 2
9.5%
c 2
9.5%
t 2
9.5%
n 1
 
4.8%
r 1
 
4.8%
i 1
 
4.8%
b 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 7041
26.1%
2 4415
16.4%
0 2524
 
9.4%
3 2244
 
8.3%
4 2206
 
8.2%
5 1863
 
6.9%
8 1725
 
6.4%
9 1693
 
6.3%
6 1670
 
6.2%
7 1605
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 83
74.1%
/ 9
 
8.0%
. 7
 
6.2%
@ 7
 
6.2%
' 4
 
3.6%
: 1
 
0.9%
? 1
 
0.9%
Space Separator
ValueCountFrequency (%)
28263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4820
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 172
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92899
60.4%
Common 60537
39.4%
Latin 385
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7146
 
7.7%
6692
 
7.2%
6367
 
6.9%
6236
 
6.7%
6119
 
6.6%
6094
 
6.6%
6078
 
6.5%
6076
 
6.5%
6073
 
6.5%
6072
 
6.5%
Other values (334) 29946
32.2%
Latin
ValueCountFrequency (%)
A 123
31.9%
B 62
16.1%
S 31
 
8.1%
N 15
 
3.9%
T 15
 
3.9%
K 13
 
3.4%
C 12
 
3.1%
D 11
 
2.9%
F 10
 
2.6%
I 9
 
2.3%
Other values (25) 84
21.8%
Common
ValueCountFrequency (%)
28263
46.7%
1 7041
 
11.6%
- 4820
 
8.0%
2 4415
 
7.3%
0 2524
 
4.2%
3 2244
 
3.7%
4 2206
 
3.6%
5 1863
 
3.1%
8 1725
 
2.8%
9 1693
 
2.8%
Other values (12) 3743
 
6.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92899
60.4%
ASCII 60922
39.6%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28263
46.4%
1 7041
 
11.6%
- 4820
 
7.9%
2 4415
 
7.2%
0 2524
 
4.1%
3 2244
 
3.7%
4 2206
 
3.6%
5 1863
 
3.1%
8 1725
 
2.8%
9 1693
 
2.8%
Other values (47) 4128
 
6.8%
Hangul
ValueCountFrequency (%)
7146
 
7.7%
6692
 
7.2%
6367
 
6.9%
6236
 
6.7%
6119
 
6.6%
6094
 
6.6%
6078
 
6.5%
6076
 
6.5%
6073
 
6.5%
6072
 
6.5%
Other values (334) 29946
32.2%
CJK
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct3725
Distinct (%)93.2%
Missing2078
Missing (%)34.2%
Memory size47.6 KiB
2024-05-11T01:10:27.356434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length59
Mean length36.012763
Min length22

Characters and Unicode

Total characters143907
Distinct characters401
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3486 ?
Unique (%)87.2%

Sample

1st row서울특별시 송파구 송파대로 567, 지상3층 (잠실동)
2nd row서울특별시 송파구 백제고분로40길 10, 1층 (석촌동)
3rd row서울특별시 송파구 가락로39길 21 (방이동)
4th row서울특별시 송파구 동남로 189, 지상3층 303호 (가락동, 쌍용프라자)
5th row서울특별시 송파구 가락로37길 19, 지상1층 (방이동)
ValueCountFrequency (%)
서울특별시 3996
 
14.5%
송파구 3996
 
14.5%
1층 949
 
3.4%
잠실동 605
 
2.2%
2층 549
 
2.0%
문정동 507
 
1.8%
가락동 415
 
1.5%
지상1층 390
 
1.4%
올림픽로 378
 
1.4%
송파동 363
 
1.3%
Other values (2787) 15447
56.0%
2024-05-11T01:10:28.491308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23616
 
16.4%
1 7299
 
5.1%
5360
 
3.7%
4999
 
3.5%
4746
 
3.3%
, 4707
 
3.3%
2 4563
 
3.2%
4168
 
2.9%
) 4071
 
2.8%
( 4069
 
2.8%
Other values (391) 76309
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81574
56.7%
Decimal Number 24351
 
16.9%
Space Separator 23616
 
16.4%
Other Punctuation 4726
 
3.3%
Close Punctuation 4071
 
2.8%
Open Punctuation 4069
 
2.8%
Uppercase Letter 824
 
0.6%
Dash Punctuation 643
 
0.4%
Lowercase Letter 20
 
< 0.1%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5360
 
6.6%
4999
 
6.1%
4746
 
5.8%
4168
 
5.1%
4016
 
4.9%
4013
 
4.9%
4003
 
4.9%
3999
 
4.9%
3996
 
4.9%
3996
 
4.9%
Other values (334) 38278
46.9%
Uppercase Letter
ValueCountFrequency (%)
B 273
33.1%
A 259
31.4%
C 46
 
5.6%
G 40
 
4.9%
S 29
 
3.5%
E 27
 
3.3%
Y 22
 
2.7%
F 18
 
2.2%
T 16
 
1.9%
N 15
 
1.8%
Other values (15) 79
 
9.6%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.0%
c 3
15.0%
l 3
15.0%
f 2
10.0%
a 2
10.0%
i 1
 
5.0%
r 1
 
5.0%
n 1
 
5.0%
t 1
 
5.0%
o 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
1 7299
30.0%
2 4563
18.7%
3 2596
 
10.7%
0 2546
 
10.5%
4 2025
 
8.3%
5 1434
 
5.9%
6 1190
 
4.9%
8 940
 
3.9%
7 930
 
3.8%
9 828
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 4707
99.6%
/ 7
 
0.1%
. 6
 
0.1%
@ 4
 
0.1%
' 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
23616
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4071
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4069
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 643
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81573
56.7%
Common 61489
42.7%
Latin 844
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5360
 
6.6%
4999
 
6.1%
4746
 
5.8%
4168
 
5.1%
4016
 
4.9%
4013
 
4.9%
4003
 
4.9%
3999
 
4.9%
3996
 
4.9%
3996
 
4.9%
Other values (333) 38277
46.9%
Latin
ValueCountFrequency (%)
B 273
32.3%
A 259
30.7%
C 46
 
5.5%
G 40
 
4.7%
S 29
 
3.4%
E 27
 
3.2%
Y 22
 
2.6%
F 18
 
2.1%
T 16
 
1.9%
N 15
 
1.8%
Other values (27) 99
 
11.7%
Common
ValueCountFrequency (%)
23616
38.4%
1 7299
 
11.9%
, 4707
 
7.7%
2 4563
 
7.4%
) 4071
 
6.6%
( 4069
 
6.6%
3 2596
 
4.2%
0 2546
 
4.1%
4 2025
 
3.3%
5 1434
 
2.3%
Other values (10) 4563
 
7.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81573
56.7%
ASCII 62333
43.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23616
37.9%
1 7299
 
11.7%
, 4707
 
7.6%
2 4563
 
7.3%
) 4071
 
6.5%
( 4069
 
6.5%
3 2596
 
4.2%
0 2546
 
4.1%
4 2025
 
3.2%
5 1434
 
2.3%
Other values (47) 5407
 
8.7%
Hangul
ValueCountFrequency (%)
5360
 
6.6%
4999
 
6.1%
4746
 
5.8%
4168
 
5.1%
4016
 
4.9%
4013
 
4.9%
4003
 
4.9%
3999
 
4.9%
3996
 
4.9%
3996
 
4.9%
Other values (333) 38277
46.9%
CJK
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct316
Distinct (%)7.9%
Missing2091
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean5668.1338
Minimum5501
Maximum5855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:28.921100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5501
5-th percentile5504
Q15563
median5662
Q35769
95-th percentile5852
Maximum5855
Range354
Interquartile range (IQR)206

Descriptive statistics

Standard deviation111.98568
Coefficient of variation (CV)0.019757064
Kurtosis-1.2297119
Mean5668.1338
Median Absolute Deviation (MAD)102
Skewness0.17801919
Sum22576177
Variance12540.793
MonotonicityNot monotonic
2024-05-11T01:10:29.438735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5855 125
 
2.1%
5501 92
 
1.5%
5504 75
 
1.2%
5852 68
 
1.1%
5698 64
 
1.1%
5502 63
 
1.0%
5854 58
 
1.0%
5507 56
 
0.9%
5558 56
 
0.9%
5559 55
 
0.9%
Other values (306) 3271
53.9%
(Missing) 2091
34.4%
ValueCountFrequency (%)
5501 92
1.5%
5502 63
1.0%
5503 24
 
0.4%
5504 75
1.2%
5505 3
 
< 0.1%
5506 2
 
< 0.1%
5507 56
0.9%
5508 6
 
0.1%
5509 2
 
< 0.1%
5510 52
0.9%
ValueCountFrequency (%)
5855 125
2.1%
5854 58
1.0%
5852 68
1.1%
5849 32
 
0.5%
5847 1
 
< 0.1%
5846 1
 
< 0.1%
5841 18
 
0.3%
5840 3
 
< 0.1%
5839 2
 
< 0.1%
5838 40
 
0.7%
Distinct5172
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
2024-05-11T01:10:30.227805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length6.3263089
Min length1

Characters and Unicode

Total characters38426
Distinct characters811
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4566 ?
Unique (%)75.2%

Sample

1st row월궁
2nd row영미용실
3rd row싸파리미용실
4th row쿨헤어드레서
5th row한수진헤어쇼
ValueCountFrequency (%)
헤어 280
 
3.3%
미용실 102
 
1.2%
네일 94
 
1.1%
에스테틱 81
 
1.0%
hair 65
 
0.8%
헤어샵 49
 
0.6%
뷰티 39
 
0.5%
nail 35
 
0.4%
잠실점 34
 
0.4%
블루클럽 32
 
0.4%
Other values (5432) 7685
90.5%
2024-05-11T01:10:31.486882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2427
 
6.3%
2279
 
5.9%
2164
 
5.6%
1076
 
2.8%
1005
 
2.6%
797
 
2.1%
782
 
2.0%
706
 
1.8%
693
 
1.8%
509
 
1.3%
Other values (801) 25988
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30614
79.7%
Space Separator 2427
 
6.3%
Lowercase Letter 2161
 
5.6%
Uppercase Letter 1815
 
4.7%
Open Punctuation 407
 
1.1%
Close Punctuation 407
 
1.1%
Other Punctuation 314
 
0.8%
Decimal Number 252
 
0.7%
Dash Punctuation 17
 
< 0.1%
Connector Punctuation 6
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2279
 
7.4%
2164
 
7.1%
1076
 
3.5%
1005
 
3.3%
797
 
2.6%
782
 
2.6%
706
 
2.3%
693
 
2.3%
509
 
1.7%
489
 
1.6%
Other values (717) 20114
65.7%
Uppercase Letter
ValueCountFrequency (%)
A 181
 
10.0%
N 136
 
7.5%
S 132
 
7.3%
I 124
 
6.8%
H 123
 
6.8%
O 117
 
6.4%
E 108
 
6.0%
R 103
 
5.7%
B 95
 
5.2%
L 87
 
4.8%
Other values (16) 609
33.6%
Lowercase Letter
ValueCountFrequency (%)
a 303
14.0%
i 232
10.7%
e 204
9.4%
l 163
 
7.5%
n 160
 
7.4%
r 158
 
7.3%
o 156
 
7.2%
h 114
 
5.3%
s 103
 
4.8%
y 94
 
4.3%
Other values (15) 474
21.9%
Other Punctuation
ValueCountFrequency (%)
& 91
29.0%
. 71
22.6%
# 38
12.1%
? 37
11.8%
, 28
 
8.9%
' 26
 
8.3%
: 11
 
3.5%
; 5
 
1.6%
! 3
 
1.0%
% 2
 
0.6%
Other values (2) 2
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 60
23.8%
2 52
20.6%
0 51
20.2%
3 20
 
7.9%
9 17
 
6.7%
5 13
 
5.2%
4 12
 
4.8%
7 11
 
4.4%
8 9
 
3.6%
6 7
 
2.8%
Math Symbol
ValueCountFrequency (%)
= 2
50.0%
< 1
25.0%
> 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 405
99.5%
[ 2
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 405
99.5%
] 2
 
0.5%
Space Separator
ValueCountFrequency (%)
2427
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30599
79.6%
Latin 3976
 
10.3%
Common 3836
 
10.0%
Han 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2279
 
7.4%
2164
 
7.1%
1076
 
3.5%
1005
 
3.3%
797
 
2.6%
782
 
2.6%
706
 
2.3%
693
 
2.3%
509
 
1.7%
489
 
1.6%
Other values (710) 20099
65.7%
Latin
ValueCountFrequency (%)
a 303
 
7.6%
i 232
 
5.8%
e 204
 
5.1%
A 181
 
4.6%
l 163
 
4.1%
n 160
 
4.0%
r 158
 
4.0%
o 156
 
3.9%
N 136
 
3.4%
S 132
 
3.3%
Other values (41) 2151
54.1%
Common
ValueCountFrequency (%)
2427
63.3%
( 405
 
10.6%
) 405
 
10.6%
& 91
 
2.4%
. 71
 
1.9%
1 60
 
1.6%
2 52
 
1.4%
0 51
 
1.3%
# 38
 
1.0%
? 37
 
1.0%
Other values (23) 199
 
5.2%
Han
ValueCountFrequency (%)
6
40.0%
4
26.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30599
79.6%
ASCII 7811
 
20.3%
CJK 15
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2427
31.1%
( 405
 
5.2%
) 405
 
5.2%
a 303
 
3.9%
i 232
 
3.0%
e 204
 
2.6%
A 181
 
2.3%
l 163
 
2.1%
n 160
 
2.0%
r 158
 
2.0%
Other values (73) 3173
40.6%
Hangul
ValueCountFrequency (%)
2279
 
7.4%
2164
 
7.1%
1076
 
3.5%
1005
 
3.3%
797
 
2.6%
782
 
2.6%
706
 
2.3%
693
 
2.3%
509
 
1.7%
489
 
1.6%
Other values (710) 20099
65.7%
CJK
ValueCountFrequency (%)
6
40.0%
4
26.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
None
ValueCountFrequency (%)
1
100.0%
Distinct4604
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
Minimum1999-01-11 00:00:00
Maximum2024-05-09 16:29:07
2024-05-11T01:10:32.135030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:10:32.760894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
I
4562 
U
1484 
D
 
28

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 4562
75.1%
U 1484
 
24.4%
D 28
 
0.5%

Length

2024-05-11T01:10:33.328672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:33.704187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4562
75.1%
u 1484
 
24.4%
d 28
 
0.5%
Distinct1289
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T01:10:34.495430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:10:35.211919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
일반미용업
4311 
피부미용업
1042 
네일아트업
554 
메이크업업
 
151
기타
 
16

Length

Max length5
Median length5
Mean length4.9920975
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 4311
71.0%
피부미용업 1042
 
17.2%
네일아트업 554
 
9.1%
메이크업업 151
 
2.5%
기타 16
 
0.3%

Length

2024-05-11T01:10:36.172809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:36.727647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 4311
71.0%
피부미용업 1042
 
17.2%
네일아트업 554
 
9.1%
메이크업업 151
 
2.5%
기타 16
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2203
Distinct (%)42.9%
Missing938
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean210046.44
Minimum206397.35
Maximum213999.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:37.505620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206397.35
5-th percentile207322.31
Q1208707.09
median210119.47
Q3211188
95-th percentile212976.52
Maximum213999.96
Range7602.6088
Interquartile range (IQR)2480.9067

Descriptive statistics

Standard deviation1719.1584
Coefficient of variation (CV)0.0081846585
Kurtosis-0.76582408
Mean210046.44
Median Absolute Deviation (MAD)1137.7022
Skewness0.044379844
Sum1.0787985 × 109
Variance2955505.7
MonotonicityNot monotonic
2024-05-11T01:10:38.611299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207373.50021477 94
 
1.5%
208707.089897534 82
 
1.4%
207624.424720682 64
 
1.1%
210045.748264305 55
 
0.9%
209394.231297346 46
 
0.8%
208233.926974585 44
 
0.7%
208589.363343145 43
 
0.7%
209151.713940169 39
 
0.6%
210986.460698452 36
 
0.6%
207553.918225133 35
 
0.6%
Other values (2193) 4598
75.7%
(Missing) 938
 
15.4%
ValueCountFrequency (%)
206397.34797252 10
0.2%
206726.499021996 8
0.1%
206731.192156063 3
 
< 0.1%
206904.080439527 1
 
< 0.1%
206908.348523164 1
 
< 0.1%
206916.75835 2
 
< 0.1%
206932.357872339 2
 
< 0.1%
206935.637104642 4
 
0.1%
206943.862539331 1
 
< 0.1%
206949.842815831 2
 
< 0.1%
ValueCountFrequency (%)
213999.956783491 2
< 0.1%
213977.355937651 1
 
< 0.1%
213880.072396674 1
 
< 0.1%
213842.444758266 1
 
< 0.1%
213825.587627548 1
 
< 0.1%
213804.777278019 3
< 0.1%
213802.190866422 2
< 0.1%
213801.158118214 1
 
< 0.1%
213791.304800814 1
 
< 0.1%
213756.046105161 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2202
Distinct (%)42.9%
Missing938
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean444592.65
Minimum441045.43
Maximum448556.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:39.196329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441045.43
5-th percentile442383.93
Q1443729.4
median444670.66
Q3445385.08
95-th percentile446519.61
Maximum448556.91
Range7511.4753
Interquartile range (IQR)1655.6867

Descriptive statistics

Standard deviation1303.9747
Coefficient of variation (CV)0.002932965
Kurtosis0.67095209
Mean444592.65
Median Absolute Deviation (MAD)785.24046
Skewness0.2199713
Sum2.2834279 × 109
Variance1700350
MonotonicityNot monotonic
2024-05-11T01:10:39.916318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445545.656024061 94
 
1.5%
446299.352775446 82
 
1.4%
445533.439634339 64
 
1.1%
442930.687284628 55
 
0.9%
443951.236927017 46
 
0.8%
445435.257647797 44
 
0.7%
445455.90405262 43
 
0.7%
446519.612162961 39
 
0.6%
441725.293491662 36
 
0.6%
445383.338011122 35
 
0.6%
Other values (2192) 4598
75.7%
(Missing) 938
 
15.4%
ValueCountFrequency (%)
441045.433058379 3
 
< 0.1%
441406.981434166 2
 
< 0.1%
441411.906445707 5
 
0.1%
441412.0 8
0.1%
441426.0 5
 
0.1%
441552.016970987 1
 
< 0.1%
441586.029967716 8
0.1%
441590.062253247 2
 
< 0.1%
441602.0 16
0.3%
441609.522612664 3
 
< 0.1%
ValueCountFrequency (%)
448556.908326858 1
 
< 0.1%
448508.139863301 2
 
< 0.1%
448472.581253344 1
 
< 0.1%
448435.73123223 2
 
< 0.1%
448425.885637954 1
 
< 0.1%
448420.462280533 5
0.1%
448415.993688122 2
 
< 0.1%
448412.552331607 2
 
< 0.1%
448408.626216441 1
 
< 0.1%
448406.785482205 1
 
< 0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
미용업
2067 
일반미용업
1522 
<NA>
1121 
피부미용업
629 
종합미용업
252 
Other values (11)
483 

Length

Max length23
Median length19
Mean length4.5783668
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 2067
34.0%
일반미용업 1522
25.1%
<NA> 1121
18.5%
피부미용업 629
 
10.4%
종합미용업 252
 
4.1%
네일미용업 232
 
3.8%
일반미용업, 네일미용업, 화장ㆍ분장 미용업 53
 
0.9%
피부미용업, 네일미용업 43
 
0.7%
일반미용업, 네일미용업 33
 
0.5%
화장ㆍ분장 미용업 32
 
0.5%
Other values (6) 90
 
1.5%

Length

2024-05-11T01:10:40.512128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 2226
34.1%
일반미용업 1640
25.1%
na 1121
17.2%
피부미용업 721
 
11.0%
네일미용업 408
 
6.3%
종합미용업 252
 
3.9%
화장ㆍ분장 159
 
2.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)0.5%
Missing2324
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.6264
Minimum0
Maximum46
Zeros3077
Zeros (%)50.7%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:41.016901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9663471
Coefficient of variation (CV)3.1391237
Kurtosis136.23944
Mean0.6264
Median Absolute Deviation (MAD)0
Skewness8.7065388
Sum2349
Variance3.8665208
MonotonicityNot monotonic
2024-05-11T01:10:41.582629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 3077
50.7%
3 154
 
2.5%
1 151
 
2.5%
4 149
 
2.5%
2 89
 
1.5%
5 74
 
1.2%
6 23
 
0.4%
10 8
 
0.1%
7 8
 
0.1%
11 2
 
< 0.1%
Other values (10) 15
 
0.2%
(Missing) 2324
38.3%
ValueCountFrequency (%)
0 3077
50.7%
1 151
 
2.5%
2 89
 
1.5%
3 154
 
2.5%
4 149
 
2.5%
5 74
 
1.2%
6 23
 
0.4%
7 8
 
0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
46 1
 
< 0.1%
33 1
 
< 0.1%
30 2
 
< 0.1%
23 1
 
< 0.1%
21 1
 
< 0.1%
20 2
 
< 0.1%
15 1
 
< 0.1%
12 2
 
< 0.1%
11 2
 
< 0.1%
10 8
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.2%
Missing2600
Missing (%)42.8%
Infinite0
Infinite (%)0.0%
Mean0.075705239
Minimum0
Maximum14
Zeros3280
Zeros (%)54.0%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:42.049484image/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 deviation0.43031187
Coefficient of variation (CV)5.6840435
Kurtosis357.73376
Mean0.075705239
Median Absolute Deviation (MAD)0
Skewness14.453631
Sum263
Variance0.1851683
MonotonicityNot monotonic
2024-05-11T01:10:42.585907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 3280
54.0%
1 168
 
2.8%
2 9
 
0.1%
3 7
 
0.1%
4 4
 
0.1%
5 4
 
0.1%
14 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 2600
42.8%
ValueCountFrequency (%)
0 3280
54.0%
1 168
 
2.8%
2 9
 
0.1%
3 7
 
0.1%
4 4
 
0.1%
5 4
 
0.1%
6 1
 
< 0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
14 1
 
< 0.1%
6 1
 
< 0.1%
5 4
 
0.1%
4 4
 
0.1%
3 7
 
0.1%
2 9
 
0.1%
1 168
 
2.8%
0 3280
54.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.4%
Missing3041
Missing (%)50.1%
Infinite0
Infinite (%)0.0%
Mean1.1770524
Minimum0
Maximum12
Zeros869
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:43.096942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2984569
Coefficient of variation (CV)1.1031428
Kurtosis14.457563
Mean1.1770524
Median Absolute Deviation (MAD)1
Skewness2.9217919
Sum3570
Variance1.6859904
MonotonicityNot monotonic
2024-05-11T01:10:43.564927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 1361
22.4%
0 869
 
14.3%
2 528
 
8.7%
3 152
 
2.5%
4 47
 
0.8%
5 33
 
0.5%
6 15
 
0.2%
9 8
 
0.1%
10 7
 
0.1%
7 5
 
0.1%
Other values (3) 8
 
0.1%
(Missing) 3041
50.1%
ValueCountFrequency (%)
0 869
14.3%
1 1361
22.4%
2 528
 
8.7%
3 152
 
2.5%
4 47
 
0.8%
5 33
 
0.5%
6 15
 
0.2%
7 5
 
0.1%
8 4
 
0.1%
9 8
 
0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 3
 
< 0.1%
10 7
 
0.1%
9 8
 
0.1%
8 4
 
0.1%
7 5
 
0.1%
6 15
 
0.2%
5 33
 
0.5%
4 47
 
0.8%
3 152
2.5%

사용끝지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct15
Distinct (%)0.7%
Missing3864
Missing (%)63.6%
Infinite0
Infinite (%)0.0%
Mean1.6239819
Minimum0
Maximum101
Zeros130
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:43.963362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum101
Range101
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.5234553
Coefficient of variation (CV)1.5538691
Kurtosis1092.4003
Mean1.6239819
Median Absolute Deviation (MAD)0
Skewness28.383445
Sum3589
Variance6.3678266
MonotonicityNot monotonic
2024-05-11T01:10:44.471899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 1291
 
21.3%
2 515
 
8.5%
3 149
 
2.5%
0 130
 
2.1%
4 47
 
0.8%
5 33
 
0.5%
6 15
 
0.2%
9 8
 
0.1%
10 7
 
0.1%
7 5
 
0.1%
Other values (5) 10
 
0.2%
(Missing) 3864
63.6%
ValueCountFrequency (%)
0 130
 
2.1%
1 1291
21.3%
2 515
 
8.5%
3 149
 
2.5%
4 47
 
0.8%
5 33
 
0.5%
6 15
 
0.2%
7 5
 
0.1%
8 4
 
0.1%
9 8
 
0.1%
ValueCountFrequency (%)
101 1
 
< 0.1%
23 1
 
< 0.1%
12 1
 
< 0.1%
11 3
 
< 0.1%
10 7
 
0.1%
9 8
 
0.1%
8 4
 
0.1%
7 5
 
0.1%
6 15
0.2%
5 33
0.5%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
4845 
0
1043 
1
 
166
2
 
15
3
 
5

Length

Max length4
Median length4
Mean length3.3929865
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4845
79.8%
0 1043
 
17.2%
1 166
 
2.7%
2 15
 
0.2%
3 5
 
0.1%

Length

2024-05-11T01:10:44.996764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:45.387608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4845
79.8%
0 1043
 
17.2%
1 166
 
2.7%
2 15
 
0.2%
3 5
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
5588 
0
 
301
1
 
165
2
 
15
3
 
5

Length

Max length4
Median length4
Mean length3.7599605
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> 5588
92.0%
0 301
 
5.0%
1 165
 
2.7%
2 15
 
0.2%
3 5
 
0.1%

Length

2024-05-11T01:10:45.774358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:46.125145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5588
92.0%
0 301
 
5.0%
1 165
 
2.7%
2 15
 
0.2%
3 5
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
0
3332 
<NA>
2742 

Length

Max length4
Median length1
Mean length2.354297
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3332
54.9%
<NA> 2742
45.1%

Length

2024-05-11T01:10:46.730014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:47.182893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3332
54.9%
na 2742
45.1%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
0
3332 
<NA>
2742 

Length

Max length4
Median length1
Mean length2.354297
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3332
54.9%
<NA> 2742
45.1%

Length

2024-05-11T01:10:47.580811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:47.931283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3332
54.9%
na 2742
45.1%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
0
3332 
<NA>
2742 

Length

Max length4
Median length1
Mean length2.354297
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3332
54.9%
<NA> 2742
45.1%

Length

2024-05-11T01:10:48.420721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:48.787294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3332
54.9%
na 2742
45.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1175
Missing (%)19.3%
Memory size12.0 KiB
False
4899 
(Missing)
1175 
ValueCountFrequency (%)
False 4899
80.7%
(Missing) 1175
 
19.3%
2024-05-11T01:10:49.150586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)0.6%
Missing1637
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean3.9139058
Minimum0
Maximum87
Zeros194
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:49.570038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q35
95-th percentile8
Maximum87
Range87
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.7845345
Coefficient of variation (CV)0.71144647
Kurtosis187.22093
Mean3.9139058
Median Absolute Deviation (MAD)1
Skewness7.8955081
Sum17366
Variance7.7536321
MonotonicityNot monotonic
2024-05-11T01:10:50.029070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3 1525
25.1%
4 896
14.8%
2 595
 
9.8%
5 387
 
6.4%
6 288
 
4.7%
0 194
 
3.2%
8 130
 
2.1%
1 113
 
1.9%
7 109
 
1.8%
10 70
 
1.2%
Other values (18) 130
 
2.1%
(Missing) 1637
27.0%
ValueCountFrequency (%)
0 194
 
3.2%
1 113
 
1.9%
2 595
 
9.8%
3 1525
25.1%
4 896
14.8%
5 387
 
6.4%
6 288
 
4.7%
7 109
 
1.8%
8 130
 
2.1%
9 45
 
0.7%
ValueCountFrequency (%)
87 1
 
< 0.1%
32 1
 
< 0.1%
25 3
< 0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%
20 4
0.1%
19 1
 
< 0.1%
18 3
< 0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing6073
Missing (%)> 99.9%
Memory size47.6 KiB
2024-05-11T01:10:50.548526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length48
Mean length48
Min length48

Characters and Unicode

Total characters48
Distinct characters34
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row건축기획과-21910(2014.10.2)에의거 영업신고기간은 임시사용 승인기간으로 제한
ValueCountFrequency (%)
건축기획과-21910(2014.10.2)에의거 1
20.0%
영업신고기간은 1
20.0%
임시사용 1
20.0%
승인기간으로 1
20.0%
제한 1
20.0%
2024-05-11T01:10:51.501772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
8.3%
1 4
 
8.3%
2 3
 
6.2%
0 3
 
6.2%
3
 
6.2%
. 2
 
4.2%
2
 
4.2%
1
 
2.1%
1
 
2.1%
1
 
2.1%
Other values (24) 24
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27
56.2%
Decimal Number 12
25.0%
Space Separator 4
 
8.3%
Other Punctuation 2
 
4.2%
Close Punctuation 1
 
2.1%
Open Punctuation 1
 
2.1%
Dash Punctuation 1
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
11.1%
2
 
7.4%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
Other values (14) 14
51.9%
Decimal Number
ValueCountFrequency (%)
1 4
33.3%
2 3
25.0%
0 3
25.0%
4 1
 
8.3%
9 1
 
8.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27
56.2%
Common 21
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
11.1%
2
 
7.4%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
Other values (14) 14
51.9%
Common
ValueCountFrequency (%)
4
19.0%
1 4
19.0%
2 3
14.3%
0 3
14.3%
. 2
9.5%
) 1
 
4.8%
4 1
 
4.8%
( 1
 
4.8%
9 1
 
4.8%
- 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27
56.2%
ASCII 21
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
19.0%
1 4
19.0%
2 3
14.3%
0 3
14.3%
. 2
9.5%
) 1
 
4.8%
4 1
 
4.8%
( 1
 
4.8%
9 1
 
4.8%
- 1
 
4.8%
Hangul
ValueCountFrequency (%)
3
 
11.1%
2
 
7.4%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
Other values (14) 14
51.9%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
6073 
20150317
 
1

Length

Max length8
Median length4
Mean length4.0006585
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6073
> 99.9%
20150317 1
 
< 0.1%

Length

2024-05-11T01:10:52.081541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:52.500337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6073
> 99.9%
20150317 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
6073 
20160604
 
1

Length

Max length8
Median length4
Mean length4.0006585
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6073
> 99.9%
20160604 1
 
< 0.1%

Length

2024-05-11T01:10:53.079059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:53.444770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6073
> 99.9%
20160604 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
5090 
임대
971 
자가
 
13

Length

Max length4
Median length4
Mean length3.675996
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> 5090
83.8%
임대 971
 
16.0%
자가 13
 
0.2%

Length

2024-05-11T01:10:53.855096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:54.329421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5090
83.8%
임대 971
 
16.0%
자가 13
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
3484 
0
2590 

Length

Max length4
Median length4
Mean length2.7207771
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> 3484
57.4%
0 2590
42.6%

Length

2024-05-11T01:10:54.942149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:55.336379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3484
57.4%
0 2590
42.6%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
4669 
0
1401 
1
 
3
2
 
1

Length

Max length4
Median length4
Mean length3.3060586
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4669
76.9%
0 1401
 
23.1%
1 3
 
< 0.1%
2 1
 
< 0.1%

Length

2024-05-11T01:10:55.772185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:56.303475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4669
76.9%
0 1401
 
23.1%
1 3
 
< 0.1%
2 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
4669 
0
1402 
1
 
3

Length

Max length4
Median length4
Mean length3.3060586
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> 4669
76.9%
0 1402
 
23.1%
1 3
 
< 0.1%

Length

2024-05-11T01:10:56.824274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:57.195697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4669
76.9%
0 1402
 
23.1%
1 3
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.6 KiB
<NA>
3648 
0
2426 

Length

Max length4
Median length4
Mean length2.8017781
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> 3648
60.1%
0 2426
39.9%

Length

2024-05-11T01:10:57.653672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:58.026894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3648
60.1%
0 2426
39.9%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.7%
Missing3695
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean1.0508617
Minimum0
Maximum23
Zeros1522
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size53.5 KiB
2024-05-11T01:10:58.502060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum23
Range23
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9663748
Coefficient of variation (CV)1.8712023
Kurtosis14.304429
Mean1.0508617
Median Absolute Deviation (MAD)0
Skewness2.9942294
Sum2500
Variance3.8666298
MonotonicityNot monotonic
2024-05-11T01:10:58.919512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 1522
25.1%
1 254
 
4.2%
2 239
 
3.9%
3 129
 
2.1%
4 75
 
1.2%
5 61
 
1.0%
6 35
 
0.6%
7 24
 
0.4%
8 15
 
0.2%
10 10
 
0.2%
Other values (6) 15
 
0.2%
(Missing) 3695
60.8%
ValueCountFrequency (%)
0 1522
25.1%
1 254
 
4.2%
2 239
 
3.9%
3 129
 
2.1%
4 75
 
1.2%
5 61
 
1.0%
6 35
 
0.6%
7 24
 
0.4%
8 15
 
0.2%
9 6
 
0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
18 1
 
< 0.1%
14 1
 
< 0.1%
12 3
 
< 0.1%
11 3
 
< 0.1%
10 10
 
0.2%
9 6
 
0.1%
8 15
0.2%
7 24
0.4%
6 35
0.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1121
Missing (%)18.5%
Memory size12.0 KiB
False
4953 
(Missing)
1121 
ValueCountFrequency (%)
False 4953
81.5%
(Missing) 1121
 
18.5%
2024-05-11T01:10:59.261259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032300003230000-204-1969-0185819690827<NA>3폐업2폐업19971217<NA><NA><NA>020400467119.95138210서울특별시 송파구 장지동 산 307-21번지<NA><NA>월궁2002-09-04 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
132300003230000-204-1970-0155419701002<NA>3폐업2폐업19990319<NA><NA><NA>02 400832212.94138210서울특별시 송파구 장지동 산 356-1번지<NA><NA>영미용실2002-09-04 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
232300003230000-204-1974-0105319740605<NA>3폐업2폐업20000107<NA><NA><NA>02 400939811.55138831서울특별시 송파구 방이동 135-26번지<NA><NA>싸파리미용실2002-11-07 00:00:00I2018-08-31 23:59:59.0일반미용업210412.541549445310.69121미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332300003230000-204-1977-0165920030227<NA>3폐업2폐업20041122<NA><NA><NA>02 480910815.58138872서울특별시 송파구 풍납동 141-1번지<NA><NA>쿨헤어드레서2003-06-10 00:00:00I2018-08-31 23:59:59.0일반미용업210450.962495448387.203818미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432300003230000-204-1978-0163619780403<NA>3폐업2폐업20030227<NA><NA><NA>02 443363633.86138120서울특별시 송파구 마천동 산 129-13번지 지상1층<NA><NA>한수진헤어쇼2003-03-12 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532300003230000-204-1978-0169019781124<NA>3폐업2폐업19901024<NA><NA><NA>020000000013.02138210서울특별시 송파구 장지동 산 222-137번지<NA><NA>2002-09-04 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
632300003230000-204-1978-0184020030227<NA>3폐업2폐업20060227<NA><NA><NA>02 400599523.92138815서울특별시 송파구 거여동 208-3번지<NA><NA>희미용실2005-07-13 00:00:00I2018-08-31 23:59:59.0일반미용업213188.064101443657.01366미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732300003230000-204-1979-0096220030227<NA>3폐업2폐업20131227<NA><NA><NA>02 423270554.00138916서울특별시 송파구 잠실동 27번지 지상3층서울특별시 송파구 송파대로 567, 지상3층 (잠실동)5503순수헤어2013-01-11 10:44:56I2018-08-31 23:59:59.0일반미용업208317.419891445894.98085미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N7<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832300003230000-204-1979-0109719791113<NA>3폐업2폐업20030227<NA><NA><NA>02 423304922.87138911서울특별시 송파구 잠실동 22-0번지 주공2단지 상가동 3층호<NA><NA>초원2003-03-12 00:00:00I2018-08-31 23:59:59.0일반미용업207750.499014445762.808121미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932300003230000-204-1979-0119120030227<NA>3폐업2폐업20031126<NA><NA><NA>020418576515.91138862서울특별시 송파구 잠실동 207-3번지<NA><NA>미모헤어샵2003-06-12 00:00:00I2018-08-31 23:59:59.0일반미용업207431.905944445237.060567미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
606432300003230000-226-2021-000022021-04-30<NA>3폐업2폐업2023-05-24<NA><NA><NA><NA>26.00138-836서울특별시 송파구 방이동 224-4서울특별시 송파구 오금로31가길 11-1, 1층 (방이동)5646미음네일2023-05-24 16:49:11U2022-12-04 22:06:00.0네일아트업210760.70665444982.940699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
606532300003230000-226-2021-0000320210625<NA>3폐업2폐업20220325<NA><NA><NA><NA>10.00138850서울특별시 송파구 송파동 87-20 승운빌딩서울특별시 송파구 송파대로42길 20, 승운빌딩 2층 201호 (송파동)5667제이 속눈썹2022-03-25 16:03:21U2022-03-27 02:40:00.0메이크업업209640.808435444797.172914피부미용업, 네일미용업, 화장ㆍ분장 미용업002000000N2<NA><NA><NA><NA>00000N
606632300003230000-226-2021-000042021-12-30<NA>3폐업2폐업2023-02-01<NA><NA><NA><NA>14.58138-160서울특별시 송파구 가락동 913 헬리오시티서울특별시 송파구 송파대로 345, 근린생활시설 1B동 지하1층 B181호 (가락동, 헬리오시티)5698채움린2023-02-01 09:19:03U2022-12-02 00:03:00.0피부미용업209412.19781443928.783342<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
606732300003230000-226-2021-000052021-03-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.20138-160서울특별시 송파구 가락동 913 헬리오시티서울특별시 송파구 송파대로 345, A동 지하1층 26호 (가락동, 헬리오시티)5698아이앤래쉬2023-06-08 16:10:34I2022-12-05 23:00:00.0메이크업업209412.19781443928.783342<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
606832300003230000-226-2022-000012022-02-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.70138-908서울특별시 송파구 잠실동 19-9 잠실파인애플상가서울특별시 송파구 올림픽로 119, 잠실파인애플상가 2A동 2층 68호 (잠실동)5501마이 네일 봄2023-07-18 10:16:18U2022-12-06 22:00:00.0네일아트업207373.500215445545.656024<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
606932300003230000-226-2022-000022022-09-27<NA>3폐업2폐업2023-02-28<NA><NA><NA><NA>41.20138-888서울특별시 송파구 문정동 652 송파법조타운푸르지오시티서울특별시 송파구 법원로4길 5, 송파법조타운푸르지오시티상가 2층 205호 (문정동)5855올망졸망네일2023-02-28 14:23:19U2022-12-03 00:03:00.0네일아트업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
607032300003230000-226-2022-0000320221017<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.00138854서울특별시 송파구 송파동 193-14서울특별시 송파구 송파대로36길 7-36, 1층 (송파동)5676앙뷰티2022-10-17 14:34:36I2021-10-30 23:09:00.0네일아트업209915.955118444258.197842<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
607132300003230000-226-2022-0000420221114<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00138832서울특별시 송파구 방이동 144-10 두레빌딩서울특별시 송파구 위례성대로6길 40, 두레빌딩 2층 201호 (방이동)5632바이윤 래쉬앤 브로우2022-11-14 16:13:51I2021-10-31 23:06:00.0피부미용업210227.044813445537.010146<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
607232300003230000-226-2022-000052022-12-26<NA>3폐업2폐업2023-08-30<NA><NA><NA><NA>22.81138-828서울특별시 송파구 방이동 51-2 청호빌딩서울특별시 송파구 백제고분로 501, 청호빌딩 지하1층 13호 (방이동)5545시니크랩2023-08-30 09:31:11U2022-12-09 00:01:00.0네일아트업210068.709244445895.51526<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
607332300003230000-226-2022-000062022-12-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.42138-715서울특별시 송파구 가락동 99-3 제일오피스텔서울특별시 송파구 송파대로 260, 제일오피스텔 7층 722, 723호 (가락동)5719에스테틱 루아즈(ROUAGE)2023-08-25 12:59:35I2022-12-07 22:07:00.0피부미용업210431.832858443465.459232<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>