Overview

Dataset statistics

Number of variables4
Number of observations89
Missing cells17
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory33.5 B

Variable types

Categorical1
Text3

Dataset

Description경상남도 고성군에 소재하고 있는 미용업 현황에 관한 데이터로 업종명, 업소명, 주소, 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15006970/fileData.do

Alerts

업종명 is highly imbalanced (67.0%)Imbalance
전화번호 has 17 (19.1%) missing valuesMissing
업소명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:08:41.376531
Analysis finished2023-12-12 02:08:41.971653
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size844.0 B
미용업(일반)
76 
미용업(피부)
10 
미용업(종합)
 
1
미용업(손톱ㆍ발톱)
 
1
미용업(일반), 미용업(화장ㆍ분장)
 
1

Length

Max length19
Median length7
Mean length7.1685393
Min length7

Unique

Unique3 ?
Unique (%)3.4%

Sample

1st row미용업(일반)
2nd row미용업(일반)
3rd row미용업(일반)
4th row미용업(일반)
5th row미용업(일반)

Common Values

ValueCountFrequency (%)
미용업(일반) 76
85.4%
미용업(피부) 10
 
11.2%
미용업(종합) 1
 
1.1%
미용업(손톱ㆍ발톱) 1
 
1.1%
미용업(일반), 미용업(화장ㆍ분장) 1
 
1.1%

Length

2023-12-12T11:08:42.068562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:08:42.202236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업(일반 77
85.6%
미용업(피부 10
 
11.1%
미용업(종합 1
 
1.1%
미용업(손톱ㆍ발톱 1
 
1.1%
미용업(화장ㆍ분장 1
 
1.1%

업소명
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-12T11:08:42.588472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length5.5842697
Min length2

Characters and Unicode

Total characters497
Distinct characters167
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

Unique89 ?
Unique (%)100.0%

Sample

1st row현대미용실
2nd row숙녀미용실
3rd row우리미용실
4th row화성미용실
5th row이즘헤어
ValueCountFrequency (%)
현대미용실 1
 
1.1%
성모미용실 1
 
1.1%
헤어퀸 1
 
1.1%
쎄시헤어 1
 
1.1%
클리퍼 1
 
1.1%
갈롱머리방 1
 
1.1%
조은헤어샵 1
 
1.1%
신신미용실 1
 
1.1%
헤어 1
 
1.1%
라보떼 1
 
1.1%
Other values (83) 83
89.2%
2023-12-12T11:08:43.195821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 44
 
8.9%
어 36
 
7.2%
실 35
 
7.0%
헤 34
 
6.8%
용 34
 
6.8%
리 13
 
2.6%
샵 10
 
2.0%
라 10
 
2.0%
스 9
 
1.8%
이 7
 
1.4%
Other values (157) 265
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
95.0%
Uppercase Letter 12
 
2.4%
Space Separator 4
 
0.8%
Decimal Number 3
 
0.6%
Lowercase Letter 2
 
0.4%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 44
 
9.3%
어 36
 
7.6%
실 35
 
7.4%
헤 34
 
7.2%
용 34
 
7.2%
리 13
 
2.8%
샵 10
 
2.1%
라 10
 
2.1%
스 9
 
1.9%
이 7
 
1.5%
Other values (142) 240
50.8%
Uppercase Letter
ValueCountFrequency (%)
T 2
16.7%
E 2
16.7%
D 2
16.7%
I 1
8.3%
J 1
8.3%
H 1
8.3%
S 1
8.3%
C 1
8.3%
A 1
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
95.0%
Latin 14
 
2.8%
Common 11
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 44
 
9.3%
어 36
 
7.6%
실 35
 
7.4%
헤 34
 
7.2%
용 34
 
7.2%
리 13
 
2.8%
샵 10
 
2.1%
라 10
 
2.1%
스 9
 
1.9%
이 7
 
1.5%
Other values (142) 240
50.8%
Latin
ValueCountFrequency (%)
T 2
14.3%
E 2
14.3%
o 2
14.3%
D 2
14.3%
I 1
7.1%
J 1
7.1%
H 1
7.1%
S 1
7.1%
C 1
7.1%
A 1
7.1%
Common
ValueCountFrequency (%)
4
36.4%
1 2
18.2%
) 2
18.2%
( 2
18.2%
9 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
95.0%
ASCII 25
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 44
 
9.3%
어 36
 
7.6%
실 35
 
7.4%
헤 34
 
7.2%
용 34
 
7.2%
리 13
 
2.8%
샵 10
 
2.1%
라 10
 
2.1%
스 9
 
1.9%
이 7
 
1.5%
Other values (142) 240
50.8%
ASCII
ValueCountFrequency (%)
4
16.0%
1 2
 
8.0%
T 2
 
8.0%
E 2
 
8.0%
o 2
 
8.0%
D 2
 
8.0%
) 2
 
8.0%
( 2
 
8.0%
I 1
 
4.0%
J 1
 
4.0%
Other values (5) 5
20.0%

주소
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-12T11:08:43.635550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length25.438202
Min length19

Characters and Unicode

Total characters2264
Distinct characters87
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st row경상남도 고성군 고성읍 성내로 141-2
2nd row경상남도 고성군 고성읍 중앙로25번길 58, 마3동 103호 (시장상가)
3rd row경상남도 고성군 고성읍 성내로143번길 11-4
4th row경상남도 고성군 거류면 당동5길 7
5th row경상남도 고성군 회화면 배둔로 18
ValueCountFrequency (%)
경상남도 89
17.8%
고성군 89
17.8%
고성읍 68
 
13.6%
중앙로25번길 11
 
2.2%
58 9
 
1.8%
회화면 9
 
1.8%
성내로 9
 
1.8%
동외로151번길 8
 
1.6%
동외로 6
 
1.2%
거류면 6
 
1.2%
Other values (141) 196
39.2%
2023-12-12T11:08:44.291667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
411
18.2%
성 175
 
7.7%
고 160
 
7.1%
1 113
 
5.0%
상 101
 
4.5%
남 96
 
4.2%
경 89
 
3.9%
도 89
 
3.9%
군 89
 
3.9%
로 85
 
3.8%
Other values (77) 856
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1371
60.6%
Space Separator 411
 
18.2%
Decimal Number 406
 
17.9%
Dash Punctuation 21
 
0.9%
Other Punctuation 20
 
0.9%
Close Punctuation 17
 
0.8%
Open Punctuation 17
 
0.8%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 175
12.8%
고 160
11.7%
상 101
 
7.4%
남 96
 
7.0%
경 89
 
6.5%
도 89
 
6.5%
군 89
 
6.5%
로 85
 
6.2%
읍 68
 
5.0%
길 48
 
3.5%
Other values (61) 371
27.1%
Decimal Number
ValueCountFrequency (%)
1 113
27.8%
5 61
15.0%
2 54
13.3%
3 39
 
9.6%
6 27
 
6.7%
8 27
 
6.7%
4 26
 
6.4%
0 25
 
6.2%
7 17
 
4.2%
9 17
 
4.2%
Space Separator
ValueCountFrequency (%)
411
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1371
60.6%
Common 892
39.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 175
12.8%
고 160
11.7%
상 101
 
7.4%
남 96
 
7.0%
경 89
 
6.5%
도 89
 
6.5%
군 89
 
6.5%
로 85
 
6.2%
읍 68
 
5.0%
길 48
 
3.5%
Other values (61) 371
27.1%
Common
ValueCountFrequency (%)
411
46.1%
1 113
 
12.7%
5 61
 
6.8%
2 54
 
6.1%
3 39
 
4.4%
6 27
 
3.0%
8 27
 
3.0%
4 26
 
2.9%
0 25
 
2.8%
- 21
 
2.4%
Other values (5) 88
 
9.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1371
60.6%
ASCII 893
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
411
46.0%
1 113
 
12.7%
5 61
 
6.8%
2 54
 
6.0%
3 39
 
4.4%
6 27
 
3.0%
8 27
 
3.0%
4 26
 
2.9%
0 25
 
2.8%
- 21
 
2.4%
Other values (6) 89
 
10.0%
Hangul
ValueCountFrequency (%)
성 175
12.8%
고 160
11.7%
상 101
 
7.4%
남 96
 
7.0%
경 89
 
6.5%
도 89
 
6.5%
군 89
 
6.5%
로 85
 
6.2%
읍 68
 
5.0%
길 48
 
3.5%
Other values (61) 371
27.1%

전화번호
Text

MISSING 

Distinct70
Distinct (%)97.2%
Missing17
Missing (%)19.1%
Memory size844.0 B
2023-12-12T11:08:44.625391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters864
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

Unique68 ?
Unique (%)94.4%

Sample

1st row055-672-6989
2nd row055-674-2401
3rd row055-674-3062
4th row055-672-1553
5th row055-673-2855
ValueCountFrequency (%)
055-673-8877 2
 
2.8%
055-672-4018 2
 
2.8%
055-674-7077 1
 
1.4%
055-672-9070 1
 
1.4%
055-674-6408 1
 
1.4%
055-674-8151 1
 
1.4%
055-672-4601 1
 
1.4%
055-674-8171 1
 
1.4%
055-674-3808 1
 
1.4%
055-672-2272 1
 
1.4%
Other values (60) 60
83.3%
2023-12-12T11:08:45.141220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 164
19.0%
- 144
16.7%
0 105
12.2%
7 101
11.7%
6 98
11.3%
4 55
 
6.4%
2 52
 
6.0%
3 47
 
5.4%
1 39
 
4.5%
8 37
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 720
83.3%
Dash Punctuation 144
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 164
22.8%
0 105
14.6%
7 101
14.0%
6 98
13.6%
4 55
 
7.6%
2 52
 
7.2%
3 47
 
6.5%
1 39
 
5.4%
8 37
 
5.1%
9 22
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 864
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 164
19.0%
- 144
16.7%
0 105
12.2%
7 101
11.7%
6 98
11.3%
4 55
 
6.4%
2 52
 
6.0%
3 47
 
5.4%
1 39
 
4.5%
8 37
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 164
19.0%
- 144
16.7%
0 105
12.2%
7 101
11.7%
6 98
11.3%
4 55
 
6.4%
2 52
 
6.0%
3 47
 
5.4%
1 39
 
4.5%
8 37
 
4.3%

Correlations

2023-12-12T11:08:45.285123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업소명주소전화번호
업종명1.0001.0001.0001.000
업소명1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-12T11:08:41.789261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:08:41.915191image/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

업종명업소명주소전화번호
0미용업(일반)현대미용실경상남도 고성군 고성읍 성내로 141-2055-672-6989
1미용업(일반)숙녀미용실경상남도 고성군 고성읍 중앙로25번길 58, 마3동 103호 (시장상가)055-674-2401
2미용업(일반)우리미용실경상남도 고성군 고성읍 성내로143번길 11-4055-674-3062
3미용업(일반)화성미용실경상남도 고성군 거류면 당동5길 7055-672-1553
4미용업(일반)이즘헤어경상남도 고성군 회화면 배둔로 18055-673-2855
5미용업(일반)무궁화미용실경상남도 고성군 고성읍 동외로151번길 10-15055-672-2868
6미용업(일반)중앙미용실경상남도 고성군 고성읍 동외로 169-1055-674-3601
7미용업(일반)롯데미용실경상남도 고성군 고성읍 동외로151번길 10-17055-672-4721
8미용업(일반)진양미용실경상남도 고성군 회화면 관인로13번길 28055-673-1898
9미용업(일반)당동미용실경상남도 고성군 거류면 당동4길 30055-672-2014
업종명업소명주소전화번호
79미용업(피부)피부향기경상남도 고성군 고성읍 중앙로43번길 81055-673-7522
80미용업(피부)최화정스킨케어경상남도 고성군 고성읍 동외로168번길 79, 2층 202호 (상가)055-674-7778
81미용업(피부)수인스킨케어경상남도 고성군 고성읍 중앙로25번길 58, 다5동 2층 209호055-673-7675
82미용업(피부)도도에스테틱(DoDo AESTHETIC)경상남도 고성군 고성읍 송학로 157055-674-1388
83미용업(피부)후스킨케어경상남도 고성군 고성읍 동외로151번길 25, 1층<NA>
84미용업(피부)동안클럽경상남도 고성군 고성읍 남포로 95055-674-6254
85미용업(피부)금강피부관리실경상남도 고성군 고성읍 성내로 55, 2층 (금강사우나)<NA>
86미용업(종합)여우야스킨케어경상남도 고성군 고성읍 성내로 67<NA>
87미용업(손톱ㆍ발톱)J블리경상남도 고성군 고성읍 성내로 131<NA>
88미용업(일반), 미용업(화장ㆍ분장)아이랑헤어경상남도 고성군 고성읍 송학고분로 349<NA>