Overview

Dataset statistics

Number of variables6
Number of observations88
Missing cells76
Missing cells (%)14.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory49.5 B

Variable types

Text4
Categorical2

Dataset

Description제주특별자치도에 소재한 후원 방문 판매업과 관련한 데이터로 상호, 등록번호, 소재지, 연락처, 취급품목 등의 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/3082768/fileData.do

Alerts

취급품목 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연락처 has 76 (86.4%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:03:04.496834
Analysis finished2023-12-12 20:03:05.327463
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct85
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-13T05:03:05.558111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.5909091
Min length3

Characters and Unicode

Total characters668
Distinct characters156
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)94.3%

Sample

1st row한국화장품 제주오라지사
2nd row아모레 연동특약점
3rd row아모레퍼시픽 동제주점
4th row아모레 남제주특약점
5th row제주건강생활
ValueCountFrequency (%)
인셀덤 40
25.6%
제주 7
 
4.5%
아모레퍼시픽 5
 
3.2%
제주인셀덤 3
 
1.9%
인셀덤대리점 3
 
1.9%
제주점 2
 
1.3%
주식회사 2
 
1.3%
아모레 2
 
1.3%
연지 1
 
0.6%
쥬단학 1
 
0.6%
Other values (90) 90
57.7%
2023-12-13T05:03:06.003111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
 
10.2%
인 65
 
9.7%
셀 63
 
9.4%
덤 63
 
9.4%
주 28
 
4.2%
제 25
 
3.7%
점 22
 
3.3%
리 14
 
2.1%
아 14
 
2.1%
레 11
 
1.6%
Other values (146) 295
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
87.9%
Space Separator 68
 
10.2%
Lowercase Letter 4
 
0.6%
Uppercase Letter 4
 
0.6%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 65
 
11.1%
셀 63
 
10.7%
덤 63
 
10.7%
주 28
 
4.8%
제 25
 
4.3%
점 22
 
3.7%
리 14
 
2.4%
아 14
 
2.4%
레 11
 
1.9%
라 11
 
1.9%
Other values (134) 271
46.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
25.0%
u 1
25.0%
v 1
25.0%
i 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
V 1
25.0%
I 1
25.0%
N 1
25.0%
G 1
25.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
87.9%
Common 72
 
10.8%
Latin 9
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 65
 
11.1%
셀 63
 
10.7%
덤 63
 
10.7%
주 28
 
4.8%
제 25
 
4.3%
점 22
 
3.7%
리 14
 
2.4%
아 14
 
2.4%
레 11
 
1.9%
라 11
 
1.9%
Other values (134) 271
46.2%
Latin
ValueCountFrequency (%)
s 1
11.1%
u 1
11.1%
v 1
11.1%
i 1
11.1%
V 1
11.1%
Ⅱ 1
11.1%
I 1
11.1%
N 1
11.1%
G 1
11.1%
Common
ValueCountFrequency (%)
68
94.4%
) 2
 
2.8%
( 2
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
87.9%
ASCII 80
 
12.0%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
85.0%
) 2
 
2.5%
( 2
 
2.5%
s 1
 
1.2%
u 1
 
1.2%
v 1
 
1.2%
i 1
 
1.2%
V 1
 
1.2%
I 1
 
1.2%
N 1
 
1.2%
Hangul
ValueCountFrequency (%)
인 65
 
11.1%
셀 63
 
10.7%
덤 63
 
10.7%
주 28
 
4.8%
제 25
 
4.3%
점 22
 
3.7%
리 14
 
2.4%
아 14
 
2.4%
레 11
 
1.9%
라 11
 
1.9%
Other values (134) 271
46.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

등록번호
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-13T05:03:06.297299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.693182
Min length11

Characters and Unicode

Total characters1029
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st row제주-2013-제1호
2nd row제주-2013-제3호
3rd row제주-2013-제5호
4th row제주-2013-제8호
5th row제주-2013-제11호
ValueCountFrequency (%)
제주-2013-제1호 1
 
1.1%
제주-2013-제3호 1
 
1.1%
제주-2022-제19호 1
 
1.1%
제주-2022-제18호 1
 
1.1%
제주-2022-제17호 1
 
1.1%
제주-2022-제16호 1
 
1.1%
제주-2022-제15호 1
 
1.1%
제주-2022-제14호 1
 
1.1%
제주-2022-제12호 1
 
1.1%
제주-2022-제11호 1
 
1.1%
Other values (78) 78
88.6%
2023-12-13T05:03:06.749515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 236
22.9%
제 176
17.1%
- 176
17.1%
0 111
10.8%
주 88
 
8.6%
호 88
 
8.6%
1 64
 
6.2%
3 37
 
3.6%
4 12
 
1.2%
7 10
 
1.0%
Other values (4) 31
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 501
48.7%
Other Letter 352
34.2%
Dash Punctuation 176
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 236
47.1%
0 111
22.2%
1 64
 
12.8%
3 37
 
7.4%
4 12
 
2.4%
7 10
 
2.0%
9 9
 
1.8%
5 8
 
1.6%
8 7
 
1.4%
6 7
 
1.4%
Other Letter
ValueCountFrequency (%)
제 176
50.0%
주 88
25.0%
호 88
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 677
65.8%
Hangul 352
34.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 236
34.9%
- 176
26.0%
0 111
16.4%
1 64
 
9.5%
3 37
 
5.5%
4 12
 
1.8%
7 10
 
1.5%
9 9
 
1.3%
5 8
 
1.2%
8 7
 
1.0%
Hangul
ValueCountFrequency (%)
제 176
50.0%
주 88
25.0%
호 88
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 677
65.8%
Hangul 352
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 236
34.9%
- 176
26.0%
0 111
16.4%
1 64
 
9.5%
3 37
 
5.5%
4 12
 
1.8%
7 10
 
1.5%
9 9
 
1.3%
5 8
 
1.2%
8 7
 
1.0%
Hangul
ValueCountFrequency (%)
제 176
50.0%
주 88
25.0%
호 88
25.0%

소재지
Text

Distinct81
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-13T05:03:07.185712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length20.920455
Min length16

Characters and Unicode

Total characters1841
Distinct characters99
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)86.4%

Sample

1st row제주특별자치도 제주시 연삼로 461
2nd row제주특별자치도 제주시 연북로 46
3rd row제주특별자치도 제주시 화삼로 1길 17
4th row제주특별자치도 서귀포시 중정로 123
5th row제주특별자치도 제주시 복지로 18-17
ValueCountFrequency (%)
제주특별자치도 88
24.0%
제주시 68
18.5%
서귀포시 20
 
5.4%
노연로 4
 
1.1%
116 4
 
1.1%
4 4
 
1.1%
중앙로 4
 
1.1%
46 3
 
0.8%
13 3
 
0.8%
14 3
 
0.8%
Other values (140) 166
45.2%
2023-12-13T05:03:07.791991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
279
15.2%
주 159
 
8.6%
제 157
 
8.5%
도 93
 
5.1%
특 88
 
4.8%
별 88
 
4.8%
자 88
 
4.8%
치 88
 
4.8%
시 88
 
4.8%
1 71
 
3.9%
Other values (89) 642
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1270
69.0%
Space Separator 279
 
15.2%
Decimal Number 271
 
14.7%
Dash Punctuation 21
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 159
12.5%
제 157
12.4%
도 93
 
7.3%
특 88
 
6.9%
별 88
 
6.9%
자 88
 
6.9%
치 88
 
6.9%
시 88
 
6.9%
로 58
 
4.6%
길 49
 
3.9%
Other values (77) 314
24.7%
Decimal Number
ValueCountFrequency (%)
1 71
26.2%
2 37
13.7%
4 32
11.8%
9 23
 
8.5%
6 22
 
8.1%
5 21
 
7.7%
3 20
 
7.4%
8 17
 
6.3%
7 14
 
5.2%
0 14
 
5.2%
Space Separator
ValueCountFrequency (%)
279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1270
69.0%
Common 571
31.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 159
12.5%
제 157
12.4%
도 93
 
7.3%
특 88
 
6.9%
별 88
 
6.9%
자 88
 
6.9%
치 88
 
6.9%
시 88
 
6.9%
로 58
 
4.6%
길 49
 
3.9%
Other values (77) 314
24.7%
Common
ValueCountFrequency (%)
279
48.9%
1 71
 
12.4%
2 37
 
6.5%
4 32
 
5.6%
9 23
 
4.0%
6 22
 
3.9%
5 21
 
3.7%
- 21
 
3.7%
3 20
 
3.5%
8 17
 
3.0%
Other values (2) 28
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1270
69.0%
ASCII 571
31.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
279
48.9%
1 71
 
12.4%
2 37
 
6.5%
4 32
 
5.6%
9 23
 
4.0%
6 22
 
3.9%
5 21
 
3.7%
- 21
 
3.7%
3 20
 
3.5%
8 17
 
3.0%
Other values (2) 28
 
4.9%
Hangul
ValueCountFrequency (%)
주 159
12.5%
제 157
12.4%
도 93
 
7.3%
특 88
 
6.9%
별 88
 
6.9%
자 88
 
6.9%
치 88
 
6.9%
시 88
 
6.9%
로 58
 
4.6%
길 49
 
3.9%
Other values (77) 314
24.7%

연락처
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing76
Missing (%)86.4%
Memory size836.0 B
2023-12-13T05:03:08.014049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters144
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

Unique12 ?
Unique (%)100.0%

Sample

1st row064-755-0334
2nd row064-713-7766
3rd row064-784-0759
4th row064-783-6139
5th row064-742-8593
ValueCountFrequency (%)
064-755-0334 1
8.3%
064-713-7766 1
8.3%
064-784-0759 1
8.3%
064-783-6139 1
8.3%
064-742-8593 1
8.3%
064-748-0090 1
8.3%
064-756-8887 1
8.3%
064-752-2001 1
8.3%
064-748-7115 1
8.3%
064-733-7115 1
8.3%
Other values (2) 2
16.7%
2023-12-13T05:03:08.362583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 24
16.7%
0 21
14.6%
7 19
13.2%
4 17
11.8%
6 16
11.1%
5 11
7.6%
3 10
6.9%
1 9
 
6.2%
8 9
 
6.2%
9 4
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 120
83.3%
Dash Punctuation 24
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
17.5%
7 19
15.8%
4 17
14.2%
6 16
13.3%
5 11
9.2%
3 10
8.3%
1 9
7.5%
8 9
7.5%
9 4
 
3.3%
2 4
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 144
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 24
16.7%
0 21
14.6%
7 19
13.2%
4 17
11.8%
6 16
11.1%
5 11
7.6%
3 10
6.9%
1 9
 
6.2%
8 9
 
6.2%
9 4
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 24
16.7%
0 21
14.6%
7 19
13.2%
4 17
11.8%
6 16
11.1%
5 11
7.6%
3 10
6.9%
1 9
 
6.2%
8 9
 
6.2%
9 4
 
2.8%

취급품목
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
화장품·건강식품
88 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화장품·건강식품
2nd row화장품·건강식품
3rd row화장품·건강식품
4th row화장품·건강식품
5th row화장품·건강식품

Common Values

ValueCountFrequency (%)
화장품·건강식품 88
100.0%

Length

2023-12-13T05:03:08.520589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:03:08.635463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화장품·건강식품 88
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
2022-10-31
88 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-31
2nd row2022-10-31
3rd row2022-10-31
4th row2022-10-31
5th row2022-10-31

Common Values

ValueCountFrequency (%)
2022-10-31 88
100.0%

Length

2023-12-13T05:03:08.761345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:03:08.878285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-31 88
100.0%

Correlations

2023-12-13T05:03:08.972178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호등록번호소재지연락처
상호1.0001.0000.9981.000
등록번호1.0001.0001.0001.000
소재지0.9981.0001.0001.000
연락처1.0001.0001.0001.000

Missing values

2023-12-13T05:03:05.163178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:03:05.281947image/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.

Sample

상호등록번호소재지연락처취급품목데이터기준일자
0한국화장품 제주오라지사제주-2013-제1호제주특별자치도 제주시 연삼로 461064-755-0334화장품·건강식품2022-10-31
1아모레 연동특약점제주-2013-제3호제주특별자치도 제주시 연북로 46064-713-7766화장품·건강식품2022-10-31
2아모레퍼시픽 동제주점제주-2013-제5호제주특별자치도 제주시 화삼로 1길 17064-784-0759화장품·건강식품2022-10-31
3아모레 남제주특약점제주-2013-제8호제주특별자치도 서귀포시 중정로 123064-783-6139화장품·건강식품2022-10-31
4제주건강생활제주-2013-제11호제주특별자치도 제주시 복지로 18-17064-742-8593화장품·건강식품2022-10-31
5오휘 신제주지사제주-2013-제23호제주특별자치도 제주시 선덕로6064-748-0090화장품·건강식품2022-10-31
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