Overview

Dataset statistics

Number of variables4
Number of observations114
Missing cells15
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory33.2 B

Variable types

Categorical1
Text3

Dataset

Description충청남도 청양군의 공중위생관리업 현황으로 숙박업, 미용업, 이용업, 목욕장업의 업소명, 영업소주소, 소재지전화를 데이터로 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15025297/fileData.do

Alerts

소재지전화 has 15 (13.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:15:13.983182
Analysis finished2023-12-12 07:15:14.431607
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct11
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
미용업
40 
숙박업(일반)
22 
이용업
18 
일반미용업
10 
종합미용업
5 
Other values (6)
19 

Length

Max length23
Median length3
Mean length5.0350877
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 40
35.1%
숙박업(일반) 22
19.3%
이용업 18
15.8%
일반미용업 10
 
8.8%
종합미용업 5
 
4.4%
숙박업(생활) 4
 
3.5%
목욕장업 4
 
3.5%
피부미용업 4
 
3.5%
네일미용업 3
 
2.6%
일반미용업, 네일미용업, 화장ㆍ분장 미용업 2
 
1.8%

Length

2023-12-12T16:15:14.507158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 44
34.9%
숙박업(일반 22
17.5%
이용업 18
14.3%
일반미용업 12
 
9.5%
네일미용업 7
 
5.6%
피부미용업 6
 
4.8%
종합미용업 5
 
4.0%
숙박업(생활 4
 
3.2%
목욕장업 4
 
3.2%
화장ㆍ분장 4
 
3.2%

업소명
Text

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T16:15:14.784247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.7982456
Min length2

Characters and Unicode

Total characters661
Distinct characters206
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)96.5%

Sample

1st row나우모텔
2nd row크리스탈모텔
3rd row향수
4th row꿈의궁전모텔
5th row백악관모텔
ValueCountFrequency (%)
이용원 7
 
4.9%
헤어 4
 
2.8%
미용실 3
 
2.1%
토브 2
 
1.4%
머리하는날 2
 
1.4%
헤어샵 2
 
1.4%
개성시대 2
 
1.4%
룻헤어커커 1
 
0.7%
미스터헤어뱅크 1
 
0.7%
고운헤어샵 1
 
0.7%
Other values (118) 118
82.5%
2023-12-12T16:15:15.214523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 36
 
5.4%
미 30
 
4.5%
29
 
4.4%
이 28
 
4.2%
어 23
 
3.5%
헤 22
 
3.3%
원 21
 
3.2%
텔 20
 
3.0%
실 18
 
2.7%
모 15
 
2.3%
Other values (196) 419
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 584
88.4%
Space Separator 29
 
4.4%
Uppercase Letter 28
 
4.2%
Lowercase Letter 7
 
1.1%
Open Punctuation 5
 
0.8%
Close Punctuation 5
 
0.8%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 36
 
6.2%
미 30
 
5.1%
이 28
 
4.8%
어 23
 
3.9%
헤 22
 
3.8%
원 21
 
3.6%
텔 20
 
3.4%
실 18
 
3.1%
모 15
 
2.6%
리 12
 
2.1%
Other values (171) 359
61.5%
Uppercase Letter
ValueCountFrequency (%)
A 5
17.9%
N 4
14.3%
O 3
10.7%
B 2
 
7.1%
L 2
 
7.1%
T 2
 
7.1%
H 2
 
7.1%
E 2
 
7.1%
Y 1
 
3.6%
U 1
 
3.6%
Other values (4) 4
14.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
28.6%
l 2
28.6%
a 1
14.3%
r 1
14.3%
e 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 1
33.3%
. 1
33.3%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 583
88.2%
Common 42
 
6.4%
Latin 35
 
5.3%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 36
 
6.2%
미 30
 
5.1%
이 28
 
4.8%
어 23
 
3.9%
헤 22
 
3.8%
원 21
 
3.6%
텔 20
 
3.4%
실 18
 
3.1%
모 15
 
2.6%
리 12
 
2.1%
Other values (170) 358
61.4%
Latin
ValueCountFrequency (%)
A 5
14.3%
N 4
11.4%
O 3
 
8.6%
i 2
 
5.7%
l 2
 
5.7%
B 2
 
5.7%
L 2
 
5.7%
T 2
 
5.7%
H 2
 
5.7%
E 2
 
5.7%
Other values (9) 9
25.7%
Common
ValueCountFrequency (%)
29
69.0%
( 5
 
11.9%
) 5
 
11.9%
, 1
 
2.4%
. 1
 
2.4%
& 1
 
2.4%
Han
ValueCountFrequency (%)
水 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
87.7%
ASCII 77
 
11.6%
Compat Jamo 3
 
0.5%
CJK 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 36
 
6.2%
미 30
 
5.2%
이 28
 
4.8%
어 23
 
4.0%
헤 22
 
3.8%
원 21
 
3.6%
텔 20
 
3.4%
실 18
 
3.1%
모 15
 
2.6%
리 12
 
2.1%
Other values (167) 355
61.2%
ASCII
ValueCountFrequency (%)
29
37.7%
( 5
 
6.5%
A 5
 
6.5%
) 5
 
6.5%
N 4
 
5.2%
O 3
 
3.9%
i 2
 
2.6%
l 2
 
2.6%
B 2
 
2.6%
L 2
 
2.6%
Other values (15) 18
23.4%
Compat Jamo
ValueCountFrequency (%)
ㄷ 1
33.3%
ㅣ 1
33.3%
ㅇ 1
33.3%
CJK
ValueCountFrequency (%)
水 1
100.0%

영업소 주소(도로명)
Text

Distinct109
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T16:15:15.614709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length22.72807
Min length18

Characters and Unicode

Total characters2591
Distinct characters111
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)92.1%

Sample

1st row충청남도 청양군 청양읍 중앙로9길 7
2nd row충청남도 청양군 청양읍 중앙로11길 9
3rd row충청남도 청양군 정산면 칠갑산로 1806
4th row충청남도 청양군 대치면 칠갑산로 419-2
5th row충청남도 청양군 청양읍 중앙로8길 11
ValueCountFrequency (%)
충청남도 114
18.8%
청양군 114
18.8%
청양읍 74
 
12.2%
중앙로 21
 
3.5%
정산면 16
 
2.6%
1층 11
 
1.8%
칠갑산로 11
 
1.8%
13 5
 
0.8%
충절로 5
 
0.8%
장평면 5
 
0.8%
Other values (141) 231
38.1%
2023-12-12T16:15:16.179845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
493
19.0%
청 311
 
12.0%
양 194
 
7.5%
충 121
 
4.7%
남 119
 
4.6%
군 114
 
4.4%
도 114
 
4.4%
1 113
 
4.4%
로 90
 
3.5%
읍 74
 
2.9%
Other values (101) 848
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1668
64.4%
Space Separator 493
 
19.0%
Decimal Number 368
 
14.2%
Dash Punctuation 28
 
1.1%
Other Punctuation 28
 
1.1%
Uppercase Letter 3
 
0.1%
Close Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 311
18.6%
양 194
11.6%
충 121
 
7.3%
남 119
 
7.1%
군 114
 
6.8%
도 114
 
6.8%
로 90
 
5.4%
읍 74
 
4.4%
길 61
 
3.7%
산 51
 
3.1%
Other values (81) 419
25.1%
Decimal Number
ValueCountFrequency (%)
1 113
30.7%
2 48
13.0%
3 36
 
9.8%
7 30
 
8.2%
0 28
 
7.6%
5 27
 
7.3%
9 26
 
7.1%
6 25
 
6.8%
4 19
 
5.2%
8 16
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
D 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 26
92.9%
& 2
 
7.1%
Space Separator
ValueCountFrequency (%)
493
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1668
64.4%
Common 920
35.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 311
18.6%
양 194
11.6%
충 121
 
7.3%
남 119
 
7.1%
군 114
 
6.8%
도 114
 
6.8%
로 90
 
5.4%
읍 74
 
4.4%
길 61
 
3.7%
산 51
 
3.1%
Other values (81) 419
25.1%
Common
ValueCountFrequency (%)
493
53.6%
1 113
 
12.3%
2 48
 
5.2%
3 36
 
3.9%
7 30
 
3.3%
0 28
 
3.0%
- 28
 
3.0%
5 27
 
2.9%
9 26
 
2.8%
, 26
 
2.8%
Other values (7) 65
 
7.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1668
64.4%
ASCII 923
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
493
53.4%
1 113
 
12.2%
2 48
 
5.2%
3 36
 
3.9%
7 30
 
3.3%
0 28
 
3.0%
- 28
 
3.0%
5 27
 
2.9%
9 26
 
2.8%
, 26
 
2.8%
Other values (10) 68
 
7.4%
Hangul
ValueCountFrequency (%)
청 311
18.6%
양 194
11.6%
충 121
 
7.3%
남 119
 
7.1%
군 114
 
6.8%
도 114
 
6.8%
로 90
 
5.4%
읍 74
 
4.4%
길 61
 
3.7%
산 51
 
3.1%
Other values (81) 419
25.1%

소재지전화
Text

MISSING 

Distinct99
Distinct (%)100.0%
Missing15
Missing (%)13.2%
Memory size1.0 KiB
2023-12-12T16:15:16.459400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.838384
Min length12

Characters and Unicode

Total characters1370
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

Unique99 ?
Unique (%)100.0%

Sample

1st row 041- 944-0933
2nd row 041- 943-6612
3rd row 041-943-8077
4th row 041- 943-8255
5th row 041- 943-8881
ValueCountFrequency (%)
041 89
43.0%
942 7
 
3.4%
943 6
 
2.9%
940 2
 
1.0%
944 2
 
1.0%
943-7511 1
 
0.5%
943-5049 1
 
0.5%
944-0411 1
 
0.5%
942-7040 1
 
0.5%
942-1035 1
 
0.5%
Other values (96) 96
46.4%
2023-12-12T16:15:16.876707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 253
18.5%
- 198
14.5%
180
13.1%
0 150
10.9%
1 140
10.2%
9 129
9.4%
3 98
 
7.2%
2 73
 
5.3%
5 43
 
3.1%
8 41
 
3.0%
Other values (2) 65
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 992
72.4%
Dash Punctuation 198
 
14.5%
Space Separator 180
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 253
25.5%
0 150
15.1%
1 140
14.1%
9 129
13.0%
3 98
 
9.9%
2 73
 
7.4%
5 43
 
4.3%
8 41
 
4.1%
7 37
 
3.7%
6 28
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 198
100.0%
Space Separator
ValueCountFrequency (%)
180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1370
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 253
18.5%
- 198
14.5%
180
13.1%
0 150
10.9%
1 140
10.2%
9 129
9.4%
3 98
 
7.2%
2 73
 
5.3%
5 43
 
3.1%
8 41
 
3.0%
Other values (2) 65
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 253
18.5%
- 198
14.5%
180
13.1%
0 150
10.9%
1 140
10.2%
9 129
9.4%
3 98
 
7.2%
2 73
 
5.3%
5 43
 
3.1%
8 41
 
3.0%
Other values (2) 65
 
4.7%

Correlations

2023-12-12T16:15:17.017796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명소재지전화
업종명1.0001.000
소재지전화1.0001.000

Missing values

2023-12-12T16:15:14.281435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:15:14.390250image/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

업종명업소명영업소 주소(도로명)소재지전화
0숙박업(일반)나우모텔충청남도 청양군 청양읍 중앙로9길 7041- 944-0933
1숙박업(일반)크리스탈모텔충청남도 청양군 청양읍 중앙로11길 9041- 943-6612
2숙박업(일반)향수충청남도 청양군 정산면 칠갑산로 1806041-943-8077
3숙박업(일반)꿈의궁전모텔충청남도 청양군 대치면 칠갑산로 419-2041- 943-8255
4숙박업(일반)백악관모텔충청남도 청양군 청양읍 중앙로8길 11041- 943-8881
5숙박업(일반)레전드모텔충청남도 청양군 청양읍 칠갑산로8길 8041- 943-9333
6숙박업(일반)에덴모텔충청남도 청양군 청양읍 충절로 1390041- 942-7971
7숙박업(일반)샤인모텔충청남도 청양군 정산면 충의로 1314041- 943-9008
8숙박업(일반)파라다이스 모텔충청남도 청양군 대치면 칠갑산로 424-6041- 943-2233
9숙박업(일반)힐링모텔충청남도 청양군 청양읍 중앙로12길 14041- 943-2465
업종명업소명영업소 주소(도로명)소재지전화
104종합미용업프로헤어샵충청남도 청양군 청양읍 칠갑산로6길 3041 -943 -4512
105종합미용업복이미용실충청남도 청양군 청양읍 중앙로5길 20, 나동 108~109호041 -942 -3636
106종합미용업커런덤충청남도 청양군 청양읍 칠갑산로2길 11, 라동 121호<NA>
107네일미용업포일네일살롱충청남도 청양군 청양읍 중앙로 136-1, 1동 1층0507-1333-2454
108네일미용업Ariel Nail(아리엘)충청남도 청양군 청양읍 중앙로 70-7, 동아노블타운 102호<NA>
109네일미용업네일, 그대와충청남도 청양군 청양읍 중앙로3길 15<NA>
110일반미용업, 네일미용업, 화장ㆍ분장 미용업은헤어충청남도 청양군 청양읍 고리섬들길 63, 2층041- 944-1316
111일반미용업, 네일미용업, 화장ㆍ분장 미용업대박미용실충청남도 청양군 청양읍 칠갑산로 270-1, 1층041- 943-5833
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