Overview

Dataset statistics

Number of variables6
Number of observations213
Missing cells484
Missing cells (%)37.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.5 KiB
Average record size in memory50.6 B

Variable types

Text3
Categorical1
Unsupported2

Dataset

Description제주특별자치도 내 소재하고 있는 공중위생업소 이용업에 관련한 데이터로 업소명, 소재지, 전화번호 등의 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15056147/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 57 (26.8%) missing valuesMissing
Unnamed: 4 has 213 (100.0%) missing valuesMissing
Unnamed: 5 has 213 (100.0%) missing valuesMissing
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 22:45:06.910121
Analysis finished2023-12-12 22:45:07.650654
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct207
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T07:45:07.814367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length5.3051643
Min length1

Characters and Unicode

Total characters1130
Distinct characters220
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)94.8%

Sample

1st row영동
2nd row한일
3rd row신생
4th row덕훈
5th row창성
ValueCountFrequency (%)
한라이용원 3
 
1.4%
강남이용원 2
 
0.9%
대성이용원 2
 
0.9%
동신이용원 2
 
0.9%
중앙이발관 2
 
0.9%
구내 2
 
0.9%
한수위사우나구내이발소 1
 
0.5%
닥터포헤어제주점 1
 
0.5%
팔래스구내 1
 
0.5%
에이치엔에이치바버샵 1
 
0.5%
Other values (202) 202
92.2%
2023-12-13T07:45:08.184296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 116
 
10.3%
용 97
 
8.6%
원 94
 
8.3%
내 46
 
4.1%
구 41
 
3.6%
우 31
 
2.7%
나 29
 
2.6%
사 27
 
2.4%
탕 23
 
2.0%
신 21
 
1.9%
Other values (210) 605
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1111
98.3%
Space Separator 6
 
0.5%
Uppercase Letter 5
 
0.4%
Lowercase Letter 5
 
0.4%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 116
 
10.4%
용 97
 
8.7%
원 94
 
8.5%
내 46
 
4.1%
구 41
 
3.7%
우 31
 
2.8%
나 29
 
2.6%
사 27
 
2.4%
탕 23
 
2.1%
신 21
 
1.9%
Other values (196) 586
52.7%
Uppercase Letter
ValueCountFrequency (%)
M 1
20.0%
O 1
20.0%
T 1
20.0%
A 1
20.0%
H 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
y 1
20.0%
b 1
20.0%
r 1
20.0%
i 1
20.0%
a 1
20.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1111
98.3%
Latin 10
 
0.9%
Common 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 116
 
10.4%
용 97
 
8.7%
원 94
 
8.5%
내 46
 
4.1%
구 41
 
3.7%
우 31
 
2.8%
나 29
 
2.6%
사 27
 
2.4%
탕 23
 
2.1%
신 21
 
1.9%
Other values (196) 586
52.7%
Latin
ValueCountFrequency (%)
M 1
10.0%
O 1
10.0%
T 1
10.0%
A 1
10.0%
y 1
10.0%
b 1
10.0%
r 1
10.0%
i 1
10.0%
a 1
10.0%
H 1
10.0%
Common
ValueCountFrequency (%)
6
66.7%
) 1
 
11.1%
. 1
 
11.1%
( 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1111
98.3%
ASCII 19
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 116
 
10.4%
용 97
 
8.7%
원 94
 
8.5%
내 46
 
4.1%
구 41
 
3.7%
우 31
 
2.8%
나 29
 
2.6%
사 27
 
2.4%
탕 23
 
2.1%
신 21
 
1.9%
Other values (196) 586
52.7%
ASCII
ValueCountFrequency (%)
6
31.6%
) 1
 
5.3%
M 1
 
5.3%
O 1
 
5.3%
T 1
 
5.3%
. 1
 
5.3%
A 1
 
5.3%
y 1
 
5.3%
b 1
 
5.3%
r 1
 
5.3%
Other values (4) 4
21.1%

소재지
Text

Distinct212
Distinct (%)100.0%
Missing1
Missing (%)0.5%
Memory size1.8 KiB
2023-12-13T07:45:08.608617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length21.523585
Min length17

Characters and Unicode

Total characters4563
Distinct characters132
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

Unique212 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 남녕로 15
2nd row제주특별자치도 제주시 용담로 126
3rd row제주특별자치도 제주시 일주동로 372
4th row제주특별자치도 제주시 서문로 63-2
5th row제주특별자치도 제주시 무근성길 36
ValueCountFrequency (%)
제주특별자치도 212
23.2%
제주시 144
 
15.8%
서귀포시 68
 
7.5%
한림읍 10
 
1.1%
조천읍 9
 
1.0%
성산읍 9
 
1.0%
2 8
 
0.9%
대정읍 8
 
0.9%
3 7
 
0.8%
10 6
 
0.7%
Other values (302) 431
47.3%
2023-12-13T07:45:09.174790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
702
15.4%
주 362
 
7.9%
제 361
 
7.9%
자 216
 
4.7%
도 216
 
4.7%
특 212
 
4.6%
별 212
 
4.6%
치 212
 
4.6%
시 212
 
4.6%
로 181
 
4.0%
Other values (122) 1677
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3191
69.9%
Space Separator 702
 
15.4%
Decimal Number 635
 
13.9%
Dash Punctuation 35
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 362
11.3%
제 361
11.3%
자 216
 
6.8%
도 216
 
6.8%
특 212
 
6.6%
별 212
 
6.6%
치 212
 
6.6%
시 212
 
6.6%
로 181
 
5.7%
길 109
 
3.4%
Other values (110) 898
28.1%
Decimal Number
ValueCountFrequency (%)
1 145
22.8%
2 97
15.3%
3 71
11.2%
6 59
9.3%
5 54
 
8.5%
4 53
 
8.3%
9 43
 
6.8%
7 42
 
6.6%
8 36
 
5.7%
0 35
 
5.5%
Space Separator
ValueCountFrequency (%)
702
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3191
69.9%
Common 1372
30.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 362
11.3%
제 361
11.3%
자 216
 
6.8%
도 216
 
6.8%
특 212
 
6.6%
별 212
 
6.6%
치 212
 
6.6%
시 212
 
6.6%
로 181
 
5.7%
길 109
 
3.4%
Other values (110) 898
28.1%
Common
ValueCountFrequency (%)
702
51.2%
1 145
 
10.6%
2 97
 
7.1%
3 71
 
5.2%
6 59
 
4.3%
5 54
 
3.9%
4 53
 
3.9%
9 43
 
3.1%
7 42
 
3.1%
8 36
 
2.6%
Other values (2) 70
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3191
69.9%
ASCII 1372
30.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
702
51.2%
1 145
 
10.6%
2 97
 
7.1%
3 71
 
5.2%
6 59
 
4.3%
5 54
 
3.9%
4 53
 
3.9%
9 43
 
3.1%
7 42
 
3.1%
8 36
 
2.6%
Other values (2) 70
 
5.1%
Hangul
ValueCountFrequency (%)
주 362
11.3%
제 361
11.3%
자 216
 
6.8%
도 216
 
6.8%
특 212
 
6.6%
별 212
 
6.6%
치 212
 
6.6%
시 212
 
6.6%
로 181
 
5.7%
길 109
 
3.4%
Other values (110) 898
28.1%

전화번호
Text

MISSING 

Distinct156
Distinct (%)100.0%
Missing57
Missing (%)26.8%
Memory size1.8 KiB
2023-12-13T07:45:09.451073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1872
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

Unique156 ?
Unique (%)100.0%

Sample

1st row064-744-0597
2nd row064-722-2434
3rd row064-758-5447
4th row064-751-3656
5th row064-752-3541
ValueCountFrequency (%)
064-743-4958 1
 
0.6%
064-782-2088 1
 
0.6%
064-738-5512 1
 
0.6%
064-796-6111 1
 
0.6%
064-757-1242 1
 
0.6%
064-711-8588 1
 
0.6%
064-764-3396 1
 
0.6%
064-738-2250 1
 
0.6%
064-767-2047 1
 
0.6%
064-783-9645 1
 
0.6%
Other values (146) 146
93.6%
2023-12-13T07:45:09.872897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 312
16.7%
4 270
14.4%
7 241
12.9%
6 240
12.8%
0 213
11.4%
2 124
 
6.6%
5 117
 
6.2%
3 109
 
5.8%
8 96
 
5.1%
9 80
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1560
83.3%
Dash Punctuation 312
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 270
17.3%
7 241
15.4%
6 240
15.4%
0 213
13.7%
2 124
7.9%
5 117
7.5%
3 109
7.0%
8 96
 
6.2%
9 80
 
5.1%
1 70
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 312
16.7%
4 270
14.4%
7 241
12.9%
6 240
12.8%
0 213
11.4%
2 124
 
6.6%
5 117
 
6.2%
3 109
 
5.8%
8 96
 
5.1%
9 80
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 312
16.7%
4 270
14.4%
7 241
12.9%
6 240
12.8%
0 213
11.4%
2 124
 
6.6%
5 117
 
6.2%
3 109
 
5.8%
8 96
 
5.1%
9 80
 
4.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2022-12-31
213 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 213
100.0%

Length

2023-12-13T07:45:10.026375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:45:10.142904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 213
100.0%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

Missing values

2023-12-13T07:45:07.144683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:45:07.251311image/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.
2023-12-13T07:45:07.609608image/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

업소명소재지전화번호데이터기준일자Unnamed: 4Unnamed: 5
0영동제주특별자치도 제주시 남녕로 15064-744-05972022-12-31<NA><NA>
1한일제주특별자치도 제주시 용담로 126064-722-24342022-12-31<NA><NA>
2신생제주특별자치도 제주시 일주동로 372064-758-54472022-12-31<NA><NA>
3덕훈제주특별자치도 제주시 서문로 63-2064-751-36562022-12-31<NA><NA>
4창성제주특별자치도 제주시 무근성길 36064-752-35412022-12-31<NA><NA>
5청운이발관제주특별자치도 제주시 한경면 고산로 31-1064-773-04242022-12-31<NA><NA>
6문성제주특별자치도 제주시 설촌로10길 15064-756-34782022-12-31<NA><NA>
7함덕이용원제주특별자치도 제주시 조천읍 신북로 510064-783-87082022-12-31<NA><NA>
8한라이용원제주특별자치도 제주시 구좌읍 김녕로 90064-783-56962022-12-31<NA><NA>
9중앙이발관제주특별자치도 제주시 한경면 고산로 21064-772-30752022-12-31<NA><NA>
업소명소재지전화번호데이터기준일자Unnamed: 4Unnamed: 5
203대성이용원제주특별자치도 서귀포시 호근남로 3064-739-67252022-12-31<NA><NA>
204상진이용원제주특별자치도 서귀포시 대정읍 하모이삼로52번길 1064-794-39432022-12-31<NA><NA>
205명품이발소제주특별자치도 서귀포시 안덕면 화순로87번길 20-4064-794-86692022-12-31<NA><NA>
206대원이용원제주특별자치도 서귀포시 명동로 14<NA>2022-12-31<NA><NA>
207광하탕이용원제주특별자치도 서귀포시 중앙로89번길 10<NA>2022-12-31<NA><NA>
208헤어바이아톰(Hair by A.TOM)제주특별자치도 서귀포시 성산읍 성산등용로17번길 55064-782-74442022-12-31<NA><NA>
209가윗소리제주특별자치도 서귀포시 대정읍 암반수마농로 37064-752-88912022-12-31<NA><NA>
210소망이용원제주특별자치도 서귀포시 표선면 표선동서로 239064-787-46892022-12-31<NA><NA>
211대정가위손이용원제주특별자치도 서귀포시 대정읍 상모로 305064-794-20072022-12-31<NA><NA>
212터틀이발소제주특별자치도 서귀포시 중정로62번길 15<NA>2022-12-31<NA><NA>