Overview

Dataset statistics

Number of variables4
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory33.3 B

Variable types

Categorical2
Text2

Dataset

Description제주특별자치도 제주시 관내에 소재하고 있는 안경 업소와 관련 현황 데이터를 제공합니다.
Author제주특별자치도 제주시
URLhttps://www.data.go.kr/data/15056182/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구분 is highly imbalanced (72.4%)Imbalance
상호 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:31:46.339586
Analysis finished2023-12-12 07:31:46.715963
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
제주
92 
동부
 
4
서부
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주 92
92.9%
동부 4
 
4.0%
서부 3
 
3.0%

Length

2023-12-12T16:31:46.773271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:31:46.861688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주 92
92.9%
동부 4
 
4.0%
서부 3
 
3.0%

상호
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-12T16:31:47.090737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.4646465
Min length3

Characters and Unicode

Total characters739
Distinct characters161
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row뢰임안경
2nd rowdetail
3rd row오뜨아이제주점
4th row으뜸플러스안경제주아라점
5th row으뜸플러스안경제주삼화점
ValueCountFrequency (%)
안경 4
 
3.3%
안경원 4
 
3.3%
오렌즈 2
 
1.6%
글라스스토리 2
 
1.6%
다비치안경 2
 
1.6%
노형점 2
 
1.6%
뢰임안경 1
 
0.8%
안경세상 1
 
0.8%
안경사랑 1
 
0.8%
일공공일안경노형점 1
 
0.8%
Other values (102) 102
83.6%
2023-12-12T16:31:47.508462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 79
 
10.7%
경 78
 
10.6%
점 39
 
5.3%
제 24
 
3.2%
23
 
3.1%
주 23
 
3.1%
이 21
 
2.8%
스 21
 
2.8%
원 20
 
2.7%
리 16
 
2.2%
Other values (151) 395
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 685
92.7%
Space Separator 23
 
3.1%
Uppercase Letter 12
 
1.6%
Lowercase Letter 8
 
1.1%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Other Punctuation 3
 
0.4%
Dash Punctuation 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 79
 
11.5%
경 78
 
11.4%
점 39
 
5.7%
제 24
 
3.5%
주 23
 
3.4%
이 21
 
3.1%
스 21
 
3.1%
원 20
 
2.9%
리 16
 
2.3%
렌 16
 
2.3%
Other values (132) 348
50.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 1
12.5%
a 1
12.5%
d 1
12.5%
i 1
12.5%
l 1
12.5%
y 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
E 7
58.3%
L 2
 
16.7%
V 1
 
8.3%
O 1
 
8.3%
Y 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 685
92.7%
Common 33
 
4.5%
Latin 21
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 79
 
11.5%
경 78
 
11.4%
점 39
 
5.7%
제 24
 
3.5%
주 23
 
3.4%
이 21
 
3.1%
스 21
 
3.1%
원 20
 
2.9%
리 16
 
2.3%
렌 16
 
2.3%
Other values (132) 348
50.8%
Latin
ValueCountFrequency (%)
E 7
33.3%
L 2
 
9.5%
e 2
 
9.5%
t 1
 
4.8%
a 1
 
4.8%
d 1
 
4.8%
i 1
 
4.8%
l 1
 
4.8%
Ⅱ 1
 
4.8%
V 1
 
4.8%
Other values (3) 3
14.3%
Common
ValueCountFrequency (%)
23
69.7%
) 3
 
9.1%
( 3
 
9.1%
& 2
 
6.1%
. 1
 
3.0%
- 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 685
92.7%
ASCII 53
 
7.2%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 79
 
11.5%
경 78
 
11.4%
점 39
 
5.7%
제 24
 
3.5%
주 23
 
3.4%
이 21
 
3.1%
스 21
 
3.1%
원 20
 
2.9%
리 16
 
2.3%
렌 16
 
2.3%
Other values (132) 348
50.8%
ASCII
ValueCountFrequency (%)
23
43.4%
E 7
 
13.2%
) 3
 
5.7%
( 3
 
5.7%
L 2
 
3.8%
e 2
 
3.8%
& 2
 
3.8%
. 1
 
1.9%
t 1
 
1.9%
a 1
 
1.9%
Other values (8) 8
 
15.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-12T16:31:47.863713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length19.262626
Min length17

Characters and Unicode

Total characters1907
Distinct characters75
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

Unique99 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 중앙로 350
2nd row제주특별자치도 제주시 아란7길 10-1
3rd row제주특별자치도 제주시 구남로2길 46
4th row제주특별자치도 제주시 중앙로 564
5th row제주특별자치도 제주시 건주로4길 6-8
ValueCountFrequency (%)
제주특별자치도 99
24.6%
제주시 99
24.6%
중앙로 19
 
4.7%
동광로 6
 
1.5%
서광로 5
 
1.2%
월랑로 4
 
1.0%
일주동로 4
 
1.0%
노연로 4
 
1.0%
신광로 4
 
1.0%
1 4
 
1.0%
Other values (130) 154
38.3%
2023-12-12T16:31:48.328197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
303
15.9%
주 205
 
10.7%
제 199
 
10.4%
도 100
 
5.2%
특 99
 
5.2%
별 99
 
5.2%
자 99
 
5.2%
치 99
 
5.2%
시 99
 
5.2%
로 91
 
4.8%
Other values (65) 514
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1321
69.3%
Space Separator 303
 
15.9%
Decimal Number 270
 
14.2%
Dash Punctuation 13
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 205
15.5%
제 199
15.1%
도 100
7.6%
특 99
7.5%
별 99
7.5%
자 99
7.5%
치 99
7.5%
시 99
7.5%
로 91
6.9%
앙 20
 
1.5%
Other values (53) 211
16.0%
Decimal Number
ValueCountFrequency (%)
1 60
22.2%
3 39
14.4%
2 36
13.3%
6 26
9.6%
0 24
 
8.9%
5 21
 
7.8%
4 20
 
7.4%
9 17
 
6.3%
8 16
 
5.9%
7 11
 
4.1%
Space Separator
ValueCountFrequency (%)
303
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1321
69.3%
Common 586
30.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 205
15.5%
제 199
15.1%
도 100
7.6%
특 99
7.5%
별 99
7.5%
자 99
7.5%
치 99
7.5%
시 99
7.5%
로 91
6.9%
앙 20
 
1.5%
Other values (53) 211
16.0%
Common
ValueCountFrequency (%)
303
51.7%
1 60
 
10.2%
3 39
 
6.7%
2 36
 
6.1%
6 26
 
4.4%
0 24
 
4.1%
5 21
 
3.6%
4 20
 
3.4%
9 17
 
2.9%
8 16
 
2.7%
Other values (2) 24
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1321
69.3%
ASCII 586
30.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
303
51.7%
1 60
 
10.2%
3 39
 
6.7%
2 36
 
6.1%
6 26
 
4.4%
0 24
 
4.1%
5 21
 
3.6%
4 20
 
3.4%
9 17
 
2.9%
8 16
 
2.7%
Other values (2) 24
 
4.1%
Hangul
ValueCountFrequency (%)
주 205
15.5%
제 199
15.1%
도 100
7.6%
특 99
7.5%
별 99
7.5%
자 99
7.5%
치 99
7.5%
시 99
7.5%
로 91
6.9%
앙 20
 
1.5%
Other values (53) 211
16.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2021-08-30
99 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-30
2nd row2021-08-30
3rd row2021-08-30
4th row2021-08-30
5th row2021-08-30

Common Values

ValueCountFrequency (%)
2021-08-30 99
100.0%

Length

2023-12-12T16:31:48.484797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:31:48.588871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-30 99
100.0%

Correlations

2023-12-12T16:31:48.661014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상호소재지
구분1.0001.0001.000
상호1.0001.0001.000
소재지1.0001.0001.000

Missing values

2023-12-12T16:31:46.598585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:31:46.683936image/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

구분상호소재지데이터기준일자
0제주뢰임안경제주특별자치도 제주시 중앙로 3502021-08-30
1제주detail제주특별자치도 제주시 아란7길 10-12021-08-30
2제주오뜨아이제주점제주특별자치도 제주시 구남로2길 462021-08-30
3제주으뜸플러스안경제주아라점제주특별자치도 제주시 중앙로 5642021-08-30
4제주으뜸플러스안경제주삼화점제주특별자치도 제주시 건주로4길 6-82021-08-30
5제주으뜸플러스안경신제주점제주특별자치도 제주시 원노형남2길 352021-08-30
6제주눈을맞추다노형점제주특별자치도 제주시 노형9길 12021-08-30
7제주지니스안경제주외도점제주특별자치도 제주시 우정로 62-12021-08-30
8제주지니스안경일도인제사거리점제주특별자치도 제주시 동광로 1222021-08-30
9제주렌즈미신라점제주특별자치도 제주시 노연로 892021-08-30
구분상호소재지데이터기준일자
89제주뉴독일안경제주특별자치도 제주시 연북로 102021-08-30
90제주빠리안경제주특별자치도 제주시 서광로 2972021-08-30
91제주명동안경동문점제주특별자치도 제주시 동문로 8-12021-08-30
92서부하귀안경제주특별자치도 제주시 하귀로 36-12021-08-30
93서부공일안경원제주특별자치도 제주시 한림읍 한림중앙로 1-12021-08-30
94서부안경마을제주특별자치도 제주시 한림읍 한림로 6592021-08-30
95동부글라스스토리(제주함덕점)제주특별자치도 제주시 조천읍 신북로 4992021-08-30
96동부하나로안경원제주특별자치도 제주시 조천읍 함와로 402021-08-30
97동부대학병원안경원제주특별자치도 제주시 조천읍 일주동로 952-52021-08-30
98동부세화안경원제주특별자치도 제주시 구좌읍 구좌로 37-22021-08-30