Overview

Dataset statistics

Number of variables5
Number of observations229
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory40.6 B

Variable types

Categorical2
Text3

Dataset

Description충청북도 증평군 공중위생업, 업종명,업소명,업소소재지(도로명),소재지전화(개인휴대폰번호제외) 등 현황 안내
URLhttps://www.data.go.kr/data/15006915/fileData.do

Alerts

데이터기준일 has constant value ""Constant
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:04:08.195150
Analysis finished2023-12-12 01:04:08.656913
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct19
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
미용업
55 
일반미용업
43 
숙박업(일반)
30 
이용업
19 
세탁업
18 
Other values (14)
64 

Length

Max length23
Median length16
Mean length5.279476
Min length3

Unique

Unique5 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 55
24.0%
일반미용업 43
18.8%
숙박업(일반) 30
13.1%
이용업 19
 
8.3%
세탁업 18
 
7.9%
피부미용업 16
 
7.0%
종합미용업 14
 
6.1%
네일미용업 8
 
3.5%
목욕장업 5
 
2.2%
건물위생관리업 5
 
2.2%
Other values (9) 16
 
7.0%

Length

2023-12-12T10:04:08.736998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 67
25.8%
일반미용업 48
18.5%
숙박업(일반 30
11.5%
피부미용업 23
 
8.8%
이용업 19
 
7.3%
세탁업 18
 
6.9%
네일미용업 18
 
6.9%
종합미용업 14
 
5.4%
화장ㆍ분장 12
 
4.6%
목욕장업 5
 
1.9%
Other values (2) 6
 
2.3%

업소명
Text

UNIQUE 

Distinct229
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T10:04:09.070773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length6.0655022
Min length2

Characters and Unicode

Total characters1389
Distinct characters311
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)100.0%

Sample

1st row부여여인숙
2nd row현수장여관
3rd row충북장여관
4th row초원여인숙
5th row수정여관
ValueCountFrequency (%)
헤어 10
 
3.3%
헤어샵 8
 
2.6%
미용실 4
 
1.3%
헤어살롱 3
 
1.0%
증평점 2
 
0.7%
미대언니들 2
 
0.7%
헤어아트 2
 
0.7%
살롱드 2
 
0.7%
네일 2
 
0.7%
hair 2
 
0.7%
Other values (266) 269
87.9%
2023-12-12T10:04:09.496949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
5.5%
헤 71
 
5.1%
어 70
 
5.0%
미 38
 
2.7%
이 31
 
2.2%
리 31
 
2.2%
용 29
 
2.1%
실 25
 
1.8%
스 23
 
1.7%
샵 19
 
1.4%
Other values (301) 975
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1170
84.2%
Space Separator 77
 
5.5%
Lowercase Letter 69
 
5.0%
Uppercase Letter 39
 
2.8%
Other Punctuation 12
 
0.9%
Close Punctuation 10
 
0.7%
Open Punctuation 10
 
0.7%
Connector Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
헤 71
 
6.1%
어 70
 
6.0%
미 38
 
3.2%
이 31
 
2.6%
리 31
 
2.6%
용 29
 
2.5%
실 25
 
2.1%
스 23
 
2.0%
샵 19
 
1.6%
세 18
 
1.5%
Other values (258) 815
69.7%
Uppercase Letter
ValueCountFrequency (%)
A 5
12.8%
B 4
 
10.3%
S 4
 
10.3%
R 3
 
7.7%
Q 2
 
5.1%
G 2
 
5.1%
W 2
 
5.1%
H 2
 
5.1%
L 2
 
5.1%
N 2
 
5.1%
Other values (8) 11
28.2%
Lowercase Letter
ValueCountFrequency (%)
l 9
13.0%
i 9
13.0%
a 9
13.0%
o 7
10.1%
r 6
8.7%
n 5
7.2%
e 5
7.2%
h 4
5.8%
d 4
5.8%
w 3
 
4.3%
Other values (6) 8
11.6%
Other Punctuation
ValueCountFrequency (%)
& 5
41.7%
, 3
25.0%
# 2
 
16.7%
· 1
 
8.3%
: 1
 
8.3%
Space Separator
ValueCountFrequency (%)
77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1170
84.2%
Common 111
 
8.0%
Latin 108
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
헤 71
 
6.1%
어 70
 
6.0%
미 38
 
3.2%
이 31
 
2.6%
리 31
 
2.6%
용 29
 
2.5%
실 25
 
2.1%
스 23
 
2.0%
샵 19
 
1.6%
세 18
 
1.5%
Other values (258) 815
69.7%
Latin
ValueCountFrequency (%)
l 9
 
8.3%
i 9
 
8.3%
a 9
 
8.3%
o 7
 
6.5%
r 6
 
5.6%
A 5
 
4.6%
n 5
 
4.6%
e 5
 
4.6%
B 4
 
3.7%
S 4
 
3.7%
Other values (24) 45
41.7%
Common
ValueCountFrequency (%)
77
69.4%
) 10
 
9.0%
( 10
 
9.0%
& 5
 
4.5%
, 3
 
2.7%
_ 2
 
1.8%
# 2
 
1.8%
· 1
 
0.9%
: 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1170
84.2%
ASCII 218
 
15.7%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
35.3%
) 10
 
4.6%
( 10
 
4.6%
l 9
 
4.1%
i 9
 
4.1%
a 9
 
4.1%
o 7
 
3.2%
r 6
 
2.8%
A 5
 
2.3%
n 5
 
2.3%
Other values (32) 71
32.6%
Hangul
ValueCountFrequency (%)
헤 71
 
6.1%
어 70
 
6.0%
미 38
 
3.2%
이 31
 
2.6%
리 31
 
2.6%
용 29
 
2.5%
실 25
 
2.1%
스 23
 
2.0%
샵 19
 
1.6%
세 18
 
1.5%
Other values (258) 815
69.7%
None
ValueCountFrequency (%)
· 1
100.0%

영업소 주소(도로명)
Text

Distinct216
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T10:04:09.911100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length22.921397
Min length18

Characters and Unicode

Total characters5249
Distinct characters123
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

Unique205 ?
Unique (%)89.5%

Sample

1st row충청북도 증평군 증평읍 중앙로12길 5
2nd row충청북도 증평군 증평읍 아랫장뜰길 31
3rd row충청북도 증평군 증평읍 윗장뜰길 53
4th row충청북도 증평군 증평읍 중앙로 216-7
5th row충청북도 증평군 증평읍 중앙로 194-14
ValueCountFrequency (%)
충청북도 229
18.4%
증평군 229
18.4%
증평읍 226
18.2%
중앙로 33
 
2.7%
1층 20
 
1.6%
광장로 20
 
1.6%
윗장뜰길 16
 
1.3%
101호 13
 
1.0%
장뜰로 10
 
0.8%
아랫장뜰길 10
 
0.8%
Other values (249) 437
35.2%
2023-12-12T10:04:10.511526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1014
19.3%
증 461
 
8.8%
평 461
 
8.8%
1 238
 
4.5%
도 233
 
4.4%
충 232
 
4.4%
청 232
 
4.4%
북 231
 
4.4%
군 229
 
4.4%
읍 226
 
4.3%
Other values (113) 1692
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3261
62.1%
Space Separator 1014
 
19.3%
Decimal Number 834
 
15.9%
Other Punctuation 66
 
1.3%
Dash Punctuation 48
 
0.9%
Open Punctuation 11
 
0.2%
Close Punctuation 11
 
0.2%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
증 461
14.1%
평 461
14.1%
도 233
 
7.1%
충 232
 
7.1%
청 232
 
7.1%
북 231
 
7.1%
군 229
 
7.0%
읍 226
 
6.9%
로 164
 
5.0%
길 109
 
3.3%
Other values (96) 683
20.9%
Decimal Number
ValueCountFrequency (%)
1 238
28.5%
2 139
16.7%
0 82
 
9.8%
3 71
 
8.5%
5 65
 
7.8%
6 59
 
7.1%
7 53
 
6.4%
4 49
 
5.9%
8 41
 
4.9%
9 37
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
D 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1014
100.0%
Other Punctuation
ValueCountFrequency (%)
, 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3261
62.1%
Common 1984
37.8%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
증 461
14.1%
평 461
14.1%
도 233
 
7.1%
충 232
 
7.1%
청 232
 
7.1%
북 231
 
7.1%
군 229
 
7.0%
읍 226
 
6.9%
로 164
 
5.0%
길 109
 
3.3%
Other values (96) 683
20.9%
Common
ValueCountFrequency (%)
1014
51.1%
1 238
 
12.0%
2 139
 
7.0%
0 82
 
4.1%
3 71
 
3.6%
, 66
 
3.3%
5 65
 
3.3%
6 59
 
3.0%
7 53
 
2.7%
4 49
 
2.5%
Other values (5) 148
 
7.5%
Latin
ValueCountFrequency (%)
A 3
75.0%
D 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3261
62.1%
ASCII 1988
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1014
51.0%
1 238
 
12.0%
2 139
 
7.0%
0 82
 
4.1%
3 71
 
3.6%
, 66
 
3.3%
5 65
 
3.3%
6 59
 
3.0%
7 53
 
2.7%
4 49
 
2.5%
Other values (7) 152
 
7.6%
Hangul
ValueCountFrequency (%)
증 461
14.1%
평 461
14.1%
도 233
 
7.1%
충 232
 
7.1%
청 232
 
7.1%
북 231
 
7.1%
군 229
 
7.0%
읍 226
 
6.9%
로 164
 
5.0%
길 109
 
3.3%
Other values (96) 683
20.9%

소재지전화
Text

Distinct149
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T10:04:10.972777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length11.371179
Min length6

Characters and Unicode

Total characters2604
Distinct characters18
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

Unique143 ?
Unique (%)62.4%

Sample

1st row 043- 836-2351
2nd row 043- 836-2353
3rd row 043- 836-2191
4th row 043- 836-2558
5th row 043- 836-2078
ValueCountFrequency (%)
043 147
33.9%
개인번호포함 75
17.3%
838 33
 
7.6%
836 14
 
3.2%
070 4
 
0.9%
838-5665 3
 
0.7%
836-2353 2
 
0.5%
6989 2
 
0.5%
838-2253 2
 
0.5%
838-2070 2
 
0.5%
Other values (149) 149
34.4%
2023-12-12T10:04:11.607096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 367
14.1%
- 308
11.8%
302
11.6%
8 278
10.7%
0 234
9.0%
4 214
 
8.2%
6 124
 
4.8%
5 76
 
2.9%
인 75
 
2.9%
개 75
 
2.9%
Other values (8) 551
21.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1544
59.3%
Other Letter 450
 
17.3%
Dash Punctuation 308
 
11.8%
Space Separator 302
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 367
23.8%
8 278
18.0%
0 234
15.2%
4 214
13.9%
6 124
 
8.0%
5 76
 
4.9%
1 74
 
4.8%
2 66
 
4.3%
9 63
 
4.1%
7 48
 
3.1%
Other Letter
ValueCountFrequency (%)
인 75
16.7%
개 75
16.7%
함 75
16.7%
포 75
16.7%
호 75
16.7%
번 75
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 308
100.0%
Space Separator
ValueCountFrequency (%)
302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2154
82.7%
Hangul 450
 
17.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 367
17.0%
- 308
14.3%
302
14.0%
8 278
12.9%
0 234
10.9%
4 214
9.9%
6 124
 
5.8%
5 76
 
3.5%
1 74
 
3.4%
2 66
 
3.1%
Other values (2) 111
 
5.2%
Hangul
ValueCountFrequency (%)
인 75
16.7%
개 75
16.7%
함 75
16.7%
포 75
16.7%
호 75
16.7%
번 75
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2154
82.7%
Hangul 450
 
17.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 367
17.0%
- 308
14.3%
302
14.0%
8 278
12.9%
0 234
10.9%
4 214
9.9%
6 124
 
5.8%
5 76
 
3.5%
1 74
 
3.4%
2 66
 
3.1%
Other values (2) 111
 
5.2%
Hangul
ValueCountFrequency (%)
인 75
16.7%
개 75
16.7%
함 75
16.7%
포 75
16.7%
호 75
16.7%
번 75
16.7%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-08-03
229 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-03
2nd row2023-08-03
3rd row2023-08-03
4th row2023-08-03
5th row2023-08-03

Common Values

ValueCountFrequency (%)
2023-08-03 229
100.0%

Length

2023-12-12T10:04:11.765795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:04:11.869337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-03 229
100.0%

Missing values

2023-12-12T10:04:08.503475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:04:08.618247image/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)소재지전화데이터기준일
0숙박업(일반)부여여인숙충청북도 증평군 증평읍 중앙로12길 5043- 836-23512023-08-03
1숙박업(일반)현수장여관충청북도 증평군 증평읍 아랫장뜰길 31043- 836-23532023-08-03
2숙박업(일반)충북장여관충청북도 증평군 증평읍 윗장뜰길 53043- 836-21912023-08-03
3숙박업(일반)초원여인숙충청북도 증평군 증평읍 중앙로 216-7043- 836-25582023-08-03
4숙박업(일반)수정여관충청북도 증평군 증평읍 중앙로 194-14043- 836-20782023-08-03
5숙박업(일반)증평여인숙충청북도 증평군 증평읍 중앙로 236-9043- 836-36002023-08-03
6숙박업(일반)그랜드모텔충청북도 증평군 증평읍 중앙로 268043- 836-19442023-08-03
7숙박업(일반)서울여인숙충청북도 증평군 증평읍 중앙로 226043- 838-60802023-08-03
8숙박업(일반)태평파크장여관충청북도 증평군 증평읍 윗장뜰길 29043- 836-55112023-08-03
9숙박업(일반)프리마모텔충청북도 증평군 증평읍 중앙로 193-7043- 836-60012023-08-03
업종명업소명영업소 주소(도로명)소재지전화데이터기준일
219네일미용업, 화장ㆍ분장 미용업Nail art 손길충청북도 증평군 증평읍 아랫장뜰길 54-1043 -838 -03332023-08-03
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221네일미용업, 화장ㆍ분장 미용업눈썹정원사충청북도 증평군 증평읍 장뜰로 103개인번호포함2023-08-03
222네일미용업, 화장ㆍ분장 미용업네일해, Yeon충청북도 증평군 증평읍 광장로 113개인번호포함2023-08-03
223네일미용업, 화장ㆍ분장 미용업다온뷰티샵충청북도 증평군 증평읍 인삼로 77개인번호포함2023-08-03
224일반미용업, 피부미용업, 화장ㆍ분장 미용업살롱드 봄 헤어충청북도 증평군 증평읍 광장로 133, 성음음악학원개인번호포함2023-08-03
225일반미용업, 피부미용업, 화장ㆍ분장 미용업A BROW (에이 브로우)충청북도 증평군 증평읍 초중9길 52, 101호개인번호포함2023-08-03
226일반미용업, 네일미용업, 화장ㆍ분장 미용업머리꽃· 피우다충청북도 증평군 증평읍 중앙로 173개인번호포함2023-08-03
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228피부미용업, 네일미용업, 화장ㆍ분장 미용업네일_윌로우(Nail_Willow)충청북도 증평군 증평읍 교동길 22개인번호포함2023-08-03