Overview

Dataset statistics

Number of variables5
Number of observations95
Missing cells17
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory41.4 B

Variable types

Categorical2
Text3

Dataset

Description전라남도 담양군 이미용업 현황(업소명, 소재지, 전화번호)등에 대한 정보를 제공하고 있으며, 공공데이터포털에 제공데이터는 기관승인 없이 무료로 활용이 가능합니다.
Author전라남도 담양군
URLhttps://www.data.go.kr/data/15006896/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지전화 has 17 (17.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 22:21:51.594258
Analysis finished2023-12-12 22:21:52.348184
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct4
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size892.0 B
미용업
56 
이용업
25 
피부미용업
7 
네일미용업
7 

Length

Max length5
Median length3
Mean length3.2947368
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 56
58.9%
이용업 25
26.3%
피부미용업 7
 
7.4%
네일미용업 7
 
7.4%

Length

2023-12-13T07:21:52.421934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:21:52.516361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업 56
58.9%
이용업 25
26.3%
피부미용업 7
 
7.4%
네일미용업 7
 
7.4%

업소명
Text

Distinct90
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-13T07:21:52.747626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.2631579
Min length2

Characters and Unicode

Total characters500
Distinct characters160
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)89.5%

Sample

1st row정화이발관
2nd row무궁화이발관
3rd row미도파이발관
4th row우리이발관
5th row창평이발관
ValueCountFrequency (%)
미용실 3
 
2.8%
오늘헤어 2
 
1.9%
스타이용원 2
 
1.9%
아름미용실 2
 
1.9%
서울미용실 2
 
1.9%
수북미용실 2
 
1.9%
이지헤어 1
 
0.9%
40헤어샵 1
 
0.9%
샬롬헤어 1
 
0.9%
어썸 1
 
0.9%
Other values (90) 90
84.1%
2023-12-13T07:21:53.132135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 36
 
7.2%
미 31
 
6.2%
이 26
 
5.2%
어 25
 
5.0%
헤 23
 
4.6%
실 23
 
4.6%
원 14
 
2.8%
관 13
 
2.6%
샵 12
 
2.4%
발 12
 
2.4%
Other values (150) 285
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 473
94.6%
Space Separator 12
 
2.4%
Decimal Number 8
 
1.6%
Lowercase Letter 4
 
0.8%
Other Punctuation 2
 
0.4%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 36
 
7.6%
미 31
 
6.6%
이 26
 
5.5%
어 25
 
5.3%
헤 23
 
4.9%
실 23
 
4.9%
원 14
 
3.0%
관 13
 
2.7%
샵 12
 
2.5%
발 12
 
2.5%
Other values (137) 258
54.5%
Decimal Number
ValueCountFrequency (%)
0 2
25.0%
1 2
25.0%
4 1
12.5%
8 1
12.5%
5 1
12.5%
2 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
i 1
25.0%
a 1
25.0%
h 1
25.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 473
94.6%
Common 22
 
4.4%
Latin 5
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 36
 
7.6%
미 31
 
6.6%
이 26
 
5.5%
어 25
 
5.3%
헤 23
 
4.9%
실 23
 
4.9%
원 14
 
3.0%
관 13
 
2.7%
샵 12
 
2.5%
발 12
 
2.5%
Other values (137) 258
54.5%
Common
ValueCountFrequency (%)
12
54.5%
0 2
 
9.1%
1 2
 
9.1%
. 2
 
9.1%
4 1
 
4.5%
8 1
 
4.5%
5 1
 
4.5%
2 1
 
4.5%
Latin
ValueCountFrequency (%)
r 1
20.0%
i 1
20.0%
a 1
20.0%
h 1
20.0%
J 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 473
94.6%
ASCII 27
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 36
 
7.6%
미 31
 
6.6%
이 26
 
5.5%
어 25
 
5.3%
헤 23
 
4.9%
실 23
 
4.9%
원 14
 
3.0%
관 13
 
2.7%
샵 12
 
2.5%
발 12
 
2.5%
Other values (137) 258
54.5%
ASCII
ValueCountFrequency (%)
12
44.4%
0 2
 
7.4%
1 2
 
7.4%
. 2
 
7.4%
4 1
 
3.7%
8 1
 
3.7%
5 1
 
3.7%
2 1
 
3.7%
r 1
 
3.7%
i 1
 
3.7%
Other values (3) 3
 
11.1%

업소소재지(도로명)
Text

Distinct89
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-13T07:21:53.496788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length21.294737
Min length18

Characters and Unicode

Total characters2023
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

Unique83 ?
Unique (%)87.4%

Sample

1st row전라남도 담양군 대전면 추성1로 185
2nd row전라남도 담양군 담양읍 추성로 1303
3rd row전라남도 담양군 고서면 가사문학로 324-5
4th row전라남도 담양군 대전면 추성1로 211
5th row전라남도 담양군 창평면 의병로 165
ValueCountFrequency (%)
전라남도 95
19.4%
담양군 95
19.4%
담양읍 63
 
12.9%
중앙로 19
 
3.9%
추성1로 11
 
2.2%
추성로 8
 
1.6%
대전면 8
 
1.6%
수북면 7
 
1.4%
창평면 7
 
1.4%
의병로 6
 
1.2%
Other values (122) 170
34.8%
2023-12-13T07:21:54.005499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
394
19.5%
담 159
 
7.9%
양 159
 
7.9%
전 103
 
5.1%
도 96
 
4.7%
라 95
 
4.7%
남 95
 
4.7%
군 95
 
4.7%
1 91
 
4.5%
읍 63
 
3.1%
Other values (77) 673
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1286
63.6%
Space Separator 394
 
19.5%
Decimal Number 306
 
15.1%
Dash Punctuation 26
 
1.3%
Other Punctuation 8
 
0.4%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
담 159
12.4%
양 159
12.4%
전 103
 
8.0%
도 96
 
7.5%
라 95
 
7.4%
남 95
 
7.4%
군 95
 
7.4%
읍 63
 
4.9%
로 58
 
4.5%
길 37
 
2.9%
Other values (61) 326
25.3%
Decimal Number
ValueCountFrequency (%)
1 91
29.7%
2 48
15.7%
3 31
 
10.1%
5 29
 
9.5%
4 21
 
6.9%
9 19
 
6.2%
0 18
 
5.9%
6 17
 
5.6%
7 17
 
5.6%
8 15
 
4.9%
Space Separator
ValueCountFrequency (%)
394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1286
63.6%
Common 736
36.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
담 159
12.4%
양 159
12.4%
전 103
 
8.0%
도 96
 
7.5%
라 95
 
7.4%
남 95
 
7.4%
군 95
 
7.4%
읍 63
 
4.9%
로 58
 
4.5%
길 37
 
2.9%
Other values (61) 326
25.3%
Common
ValueCountFrequency (%)
394
53.5%
1 91
 
12.4%
2 48
 
6.5%
3 31
 
4.2%
5 29
 
3.9%
- 26
 
3.5%
4 21
 
2.9%
9 19
 
2.6%
0 18
 
2.4%
6 17
 
2.3%
Other values (5) 42
 
5.7%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1286
63.6%
ASCII 737
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
394
53.5%
1 91
 
12.3%
2 48
 
6.5%
3 31
 
4.2%
5 29
 
3.9%
- 26
 
3.5%
4 21
 
2.8%
9 19
 
2.6%
0 18
 
2.4%
6 17
 
2.3%
Other values (6) 43
 
5.8%
Hangul
ValueCountFrequency (%)
담 159
12.4%
양 159
12.4%
전 103
 
8.0%
도 96
 
7.5%
라 95
 
7.4%
남 95
 
7.4%
군 95
 
7.4%
읍 63
 
4.9%
로 58
 
4.5%
길 37
 
2.9%
Other values (61) 326
25.3%

소재지전화
Text

MISSING 

Distinct76
Distinct (%)97.4%
Missing17
Missing (%)17.9%
Memory size892.0 B
2023-12-13T07:21:54.315434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.269231
Min length12

Characters and Unicode

Total characters957
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)94.9%

Sample

1st row061-382-5131
2nd row061-381-4321
3rd row061-383-5246
4th row061-382-5819
5th row061-382-3007
ValueCountFrequency (%)
061-383-4569 2
 
2.5%
061-383-1124 2
 
2.5%
061-381-3343 1
 
1.3%
061-382-5131 1
 
1.3%
061-383-4705 1
 
1.3%
070-8125-1687 1
 
1.3%
061-381-2486 1
 
1.3%
061-382-4748 1
 
1.3%
061-381-6586 1
 
1.3%
061-381-3794 1
 
1.3%
Other values (67) 67
84.8%
2023-12-13T07:21:55.069732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 155
16.2%
3 135
14.1%
1 134
14.0%
0 131
13.7%
8 100
10.4%
6 96
10.0%
5 49
 
5.1%
2 47
 
4.9%
4 39
 
4.1%
7 39
 
4.1%
Other values (2) 32
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 801
83.7%
Dash Punctuation 155
 
16.2%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 135
16.9%
1 134
16.7%
0 131
16.4%
8 100
12.5%
6 96
12.0%
5 49
 
6.1%
2 47
 
5.9%
4 39
 
4.9%
7 39
 
4.9%
9 31
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 957
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 155
16.2%
3 135
14.1%
1 134
14.0%
0 131
13.7%
8 100
10.4%
6 96
10.0%
5 49
 
5.1%
2 47
 
4.9%
4 39
 
4.1%
7 39
 
4.1%
Other values (2) 32
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 957
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 155
16.2%
3 135
14.1%
1 134
14.0%
0 131
13.7%
8 100
10.4%
6 96
10.0%
5 49
 
5.1%
2 47
 
4.9%
4 39
 
4.1%
7 39
 
4.1%
Other values (2) 32
 
3.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-09-14
95 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-14
2nd row2023-09-14
3rd row2023-09-14
4th row2023-09-14
5th row2023-09-14

Common Values

ValueCountFrequency (%)
2023-09-14 95
100.0%

Length

2023-12-13T07:21:55.200234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:21:55.277840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-14 95
100.0%

Correlations

2023-12-13T07:21:55.339300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업소명업소소재지(도로명)소재지전화
업종명1.0000.9900.0001.000
업소명0.9901.0000.9970.999
업소소재지(도로명)0.0000.9971.0000.991
소재지전화1.0000.9990.9911.000

Missing values

2023-12-13T07:21:52.226645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:21:52.306168image/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

업종명업소명업소소재지(도로명)소재지전화데이터기준일자
0이용업정화이발관전라남도 담양군 대전면 추성1로 185061-382-51312023-09-14
1이용업무궁화이발관전라남도 담양군 담양읍 추성로 1303061-381-43212023-09-14
2이용업미도파이발관전라남도 담양군 고서면 가사문학로 324-5061-383-52462023-09-14
3이용업우리이발관전라남도 담양군 대전면 추성1로 211061-382-58192023-09-14
4이용업창평이발관전라남도 담양군 창평면 의병로 165<NA>2023-09-14
5이용업육일이용원전라남도 담양군 고서면 원등1길 27061-382-30072023-09-14
6이용업중앙이발관전라남도 담양군 금성면 석현길 101061-382-40182023-09-14
7이용업송죽이용원전라남도 담양군 담양읍 객사4길 37-1061-382-32452023-09-14
8이용업오강이용원전라남도 담양군 대덕면 성곡오산길 3061-383-18742023-09-14
9이용업중앙이용원전라남도 담양군 담양읍 추성로 1310061-382-90302023-09-14
업종명업소명업소소재지(도로명)소재지전화데이터기준일자
85피부미용업쉘모아 에스테틱전라남도 담양군 담양읍 천변2길 10061-382-03962023-09-14
86피부미용업180도 반하다전라남도 담양군 담양읍 죽향대로 12040507-1445-96972023-09-14
87피부미용업엘르샵전라남도 담양군 담양읍 객사4길 19<NA>2023-09-14
88네일미용업바른네일전라남도 담양군 담양읍 삼거리길 8-8, 2층0507-1405-47352023-09-14
89네일미용업스마일네일전라남도 담양군 담양읍 중앙로 56<NA>2023-09-14
90네일미용업유네일속눈썹전라남도 담양군 담양읍 미리산길 67 (담양금강아파트)0507-1399-01532023-09-14
91네일미용업투네일전라남도 담양군 담양읍 지침1길 11-3 1층 3호0507-1420-99282023-09-14
92네일미용업손톱공주전라남도 담양군 담양읍 천변1길 2, 손톱공주<NA>2023-09-14
93네일미용업네일리아전라남도 담양군 담양읍 천변7길 2-3, 2층0507-1335-93372023-09-14
94네일미용업네일어때전라남도 담양군 담양읍 중앙로 63-10507-1304-49392023-09-14