Overview

Dataset statistics

Number of variables4
Number of observations64
Missing cells94
Missing cells (%)36.7%
Duplicate rows1
Duplicate rows (%)1.6%
Total size in memory2.1 KiB
Average record size in memory34.1 B

Variable types

Text3
DateTime1

Dataset

Description경상남도 양산시 동물미용업 현황에 대한 데이터로 업소명, 소재지, 전화번호, 데이터기준일자 항목을 제공합니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15099906

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (1.6%) duplicate rowsDuplicates
업소명 has 22 (34.4%) missing valuesMissing
소재지 has 22 (34.4%) missing valuesMissing
전화번호 has 28 (43.8%) missing valuesMissing
데이터기준일자 has 22 (34.4%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:25:34.012106
Analysis finished2023-12-10 23:25:34.414302
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing22
Missing (%)34.4%
Memory size644.0 B
2023-12-11T08:25:34.566463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.7619048
Min length3

Characters and Unicode

Total characters200
Distinct characters99
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row퍼피홀릭
2nd row날개단강아지
3rd row폼나개
4th row갠지샵
5th row페어리몽드
ValueCountFrequency (%)
범어애견 1
 
2.3%
폼나개 1
 
2.3%
쁘니애견미용실 1
 
2.3%
도그톡톡 1
 
2.3%
예쁜개집애 1
 
2.3%
핑크펫샵 1
 
2.3%
펫츠로그 1
 
2.3%
펫살롱 1
 
2.3%
고양이이야기 1
 
2.3%
러블리멍 1
 
2.3%
Other values (34) 34
77.3%
2023-12-11T08:25:34.997817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
몽 9
 
4.5%
애 9
 
4.5%
견 9
 
4.5%
펫 8
 
4.0%
개 7
 
3.5%
이 6
 
3.0%
미 6
 
3.0%
그 6
 
3.0%
용 5
 
2.5%
실 4
 
2.0%
Other values (89) 131
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
99.0%
Space Separator 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
몽 9
 
4.5%
애 9
 
4.5%
견 9
 
4.5%
펫 8
 
4.0%
개 7
 
3.5%
이 6
 
3.0%
미 6
 
3.0%
그 6
 
3.0%
용 5
 
2.5%
실 4
 
2.0%
Other values (88) 129
65.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
99.0%
Common 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
몽 9
 
4.5%
애 9
 
4.5%
견 9
 
4.5%
펫 8
 
4.0%
개 7
 
3.5%
이 6
 
3.0%
미 6
 
3.0%
그 6
 
3.0%
용 5
 
2.5%
실 4
 
2.0%
Other values (88) 129
65.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
99.0%
ASCII 2
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
몽 9
 
4.5%
애 9
 
4.5%
견 9
 
4.5%
펫 8
 
4.0%
개 7
 
3.5%
이 6
 
3.0%
미 6
 
3.0%
그 6
 
3.0%
용 5
 
2.5%
실 4
 
2.0%
Other values (88) 129
65.2%
ASCII
ValueCountFrequency (%)
2
100.0%

소재지
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing22
Missing (%)34.4%
Memory size644.0 B
2023-12-11T08:25:35.266110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length26
Mean length22.285714
Min length15

Characters and Unicode

Total characters936
Distinct characters97
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row경상남도 양산시 물금읍 백호로 156 104호
2nd row경상남도 양산시 물금읍 백호2길 46 1층
3rd row경상남도 양산시 물금읍 황산로 505 5층
4th row경상남도 양산시 물금읍 백호로 96 미소프라자122호
5th row경상남도 양산시 물금읍 증산역로 149 112호
ValueCountFrequency (%)
경상남도 42
18.8%
양산시 42
18.8%
물금읍 13
 
5.8%
1층 8
 
3.6%
101호 5
 
2.2%
백호로 3
 
1.3%
156 3
 
1.3%
양주3길 3
 
1.3%
대운로 2
 
0.9%
양주로 2
 
0.9%
Other values (96) 101
45.1%
2023-12-11T08:25:35.681382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
19.4%
1 53
 
5.7%
상 50
 
5.3%
양 48
 
5.1%
산 47
 
5.0%
남 45
 
4.8%
시 44
 
4.7%
경 42
 
4.5%
도 42
 
4.5%
로 24
 
2.6%
Other values (87) 359
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 576
61.5%
Space Separator 182
 
19.4%
Decimal Number 171
 
18.3%
Dash Punctuation 5
 
0.5%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 50
 
8.7%
양 48
 
8.3%
산 47
 
8.2%
남 45
 
7.8%
시 44
 
7.6%
경 42
 
7.3%
도 42
 
7.3%
로 24
 
4.2%
호 22
 
3.8%
길 20
 
3.5%
Other values (73) 192
33.3%
Decimal Number
ValueCountFrequency (%)
1 53
31.0%
2 20
 
11.7%
4 18
 
10.5%
5 17
 
9.9%
0 16
 
9.4%
3 16
 
9.4%
6 12
 
7.0%
8 7
 
4.1%
7 6
 
3.5%
9 6
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
F 1
50.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 576
61.5%
Common 358
38.2%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 50
 
8.7%
양 48
 
8.3%
산 47
 
8.2%
남 45
 
7.8%
시 44
 
7.6%
경 42
 
7.3%
도 42
 
7.3%
로 24
 
4.2%
호 22
 
3.8%
길 20
 
3.5%
Other values (73) 192
33.3%
Common
ValueCountFrequency (%)
182
50.8%
1 53
 
14.8%
2 20
 
5.6%
4 18
 
5.0%
5 17
 
4.7%
0 16
 
4.5%
3 16
 
4.5%
6 12
 
3.4%
8 7
 
2.0%
7 6
 
1.7%
Other values (2) 11
 
3.1%
Latin
ValueCountFrequency (%)
A 1
50.0%
F 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 576
61.5%
ASCII 360
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
50.6%
1 53
 
14.7%
2 20
 
5.6%
4 18
 
5.0%
5 17
 
4.7%
0 16
 
4.4%
3 16
 
4.4%
6 12
 
3.3%
8 7
 
1.9%
7 6
 
1.7%
Other values (4) 13
 
3.6%
Hangul
ValueCountFrequency (%)
상 50
 
8.7%
양 48
 
8.3%
산 47
 
8.2%
남 45
 
7.8%
시 44
 
7.6%
경 42
 
7.3%
도 42
 
7.3%
로 24
 
4.2%
호 22
 
3.8%
길 20
 
3.5%
Other values (73) 192
33.3%

전화번호
Text

MISSING 

Distinct36
Distinct (%)100.0%
Missing28
Missing (%)43.8%
Memory size644.0 B
2023-12-11T08:25:35.926580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.25
Min length12

Characters and Unicode

Total characters477
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

Unique36 ?
Unique (%)100.0%

Sample

1st row055-363-1500
2nd row0507-1491-7654
3rd row0507-1353-8642
4th row055-382-2853
5th row0507-1326-9370
ValueCountFrequency (%)
055-382-0079 1
 
2.8%
070-7374-5801 1
 
2.8%
0507-1340-8747 1
 
2.8%
055-383-1242 1
 
2.8%
055-363-0082 1
 
2.8%
0507-1323-0332 1
 
2.8%
0507-1320-2536 1
 
2.8%
055-384-0486 1
 
2.8%
0507-1412-6081 1
 
2.8%
055-363-1500 1
 
2.8%
Other values (26) 26
72.2%
2023-12-11T08:25:36.296134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87
18.2%
- 72
15.1%
5 68
14.3%
3 46
9.6%
1 46
9.6%
7 37
7.8%
4 32
 
6.7%
8 27
 
5.7%
2 26
 
5.5%
6 22
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 405
84.9%
Dash Punctuation 72
 
15.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87
21.5%
5 68
16.8%
3 46
11.4%
1 46
11.4%
7 37
9.1%
4 32
 
7.9%
8 27
 
6.7%
2 26
 
6.4%
6 22
 
5.4%
9 14
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87
18.2%
- 72
15.1%
5 68
14.3%
3 46
9.6%
1 46
9.6%
7 37
7.8%
4 32
 
6.7%
8 27
 
5.7%
2 26
 
5.5%
6 22
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87
18.2%
- 72
15.1%
5 68
14.3%
3 46
9.6%
1 46
9.6%
7 37
7.8%
4 32
 
6.7%
8 27
 
5.7%
2 26
 
5.5%
6 22
 
4.6%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing22
Missing (%)34.4%
Memory size644.0 B
Minimum2022-04-20 00:00:00
Maximum2022-04-20 00:00:00
2023-12-11T08:25:36.415814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:25:36.502783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T08:25:36.566543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지전화번호
업소명1.0001.0001.000
소재지1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2023-12-11T08:25:34.213013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:25:34.287615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T08:25:34.363296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업소명소재지전화번호데이터기준일자
0퍼피홀릭경상남도 양산시 물금읍 백호로 156 104호055-363-15002022-04-20
1날개단강아지경상남도 양산시 물금읍 백호2길 46 1층<NA>2022-04-20
2폼나개경상남도 양산시 물금읍 황산로 505 5층0507-1491-76542022-04-20
3갠지샵경상남도 양산시 물금읍 백호로 96 미소프라자122호<NA>2022-04-20
4페어리몽드경상남도 양산시 물금읍 증산역로 149 112호0507-1353-86422022-04-20
5바비몽경상남도 양산시 물금읍 물금1길 44055-382-28532022-04-20
6몽그리몽경상남도 양산시 물금읍 범구로 14 오슬로파크 지상1층 F동5호0507-1326-93702022-04-20
7뛰뛰멍경상남도 양산시 물금읍 백호로 156 후문상가 101호<NA>2022-04-20
8퍼피파파경상남도 양산시 물금읍 백호1길 42 101호055-385-01612022-04-20
9루에나펫스파살롱경상남도 양산시 물금읍 물금로 9 더스퀘어상가 103호0507-1330-32452022-04-20
업소명소재지전화번호데이터기준일자
54<NA><NA><NA><NA>
55<NA><NA><NA><NA>
56<NA><NA><NA><NA>
57<NA><NA><NA><NA>
58도그블라썸경상남도 양산시 소주회야1길 5-560507-1325-41252022-04-20
59<NA><NA><NA><NA>
60<NA><NA><NA><NA>
61<NA><NA><NA><NA>
62<NA><NA><NA><NA>
63스타독경상남도 양산시 북정중앙로 20055-366-94472022-04-20

Duplicate rows

Most frequently occurring

업소명소재지전화번호데이터기준일자# duplicates
0<NA><NA><NA><NA>22