Overview

Dataset statistics

Number of variables4
Number of observations666
Missing cells193
Missing cells (%)7.2%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory20.9 KiB
Average record size in memory32.2 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시 중구 관내 공중위생업소(숙박업, 목욕장업, 이미용업, 세탁업, 건물위생관리업 등) 현황 파일 데이터로 업종명, 영업소명, 주소, 전호번호의 정보를 제공합니다.
Author부산광역시 중구
URLhttps://www.data.go.kr/data/3069341/fileData.do

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates
업소전화번호 has 193 (29.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 17:26:56.640987
Analysis finished2024-03-14 17:26:57.659212
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct21
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
숙박업(일반)
134 
일반미용업
102 
미용업
101 
종합미용업
50 
피부미용업
48 
Other values (16)
231 

Length

Max length23
Median length16
Mean length5.7627628
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 134
20.1%
일반미용업 102
15.3%
미용업 101
15.2%
종합미용업 50
 
7.5%
피부미용업 48
 
7.2%
네일미용업 43
 
6.5%
이용업 39
 
5.9%
세탁업 34
 
5.1%
건물위생관리업 29
 
4.4%
목욕장업 23
 
3.5%
Other values (11) 63
9.5%

Length

2024-03-15T02:26:57.922546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 136
18.0%
숙박업(일반 134
17.7%
일반미용업 118
15.6%
피부미용업 74
9.8%
네일미용업 70
9.3%
종합미용업 50
 
6.6%
이용업 39
 
5.2%
화장ㆍ분장 35
 
4.6%
세탁업 34
 
4.5%
건물위생관리업 29
 
3.8%
Other values (2) 37
 
4.9%

업소명
Text

Distinct659
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-03-15T02:26:58.873724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length6.4099099
Min length1

Characters and Unicode

Total characters4269
Distinct characters459
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

Unique653 ?
Unique (%)98.0%

Sample

1st row양지장
2nd row더로찌
3rd row유일모텔
4th row부산
5th row로얄장
ValueCountFrequency (%)
호텔 15
 
1.7%
헤어 15
 
1.7%
남포점 9
 
1.0%
hair 8
 
0.9%
광복점 8
 
0.9%
게스트하우스 7
 
0.8%
미용실 7
 
0.8%
모텔 6
 
0.7%
뷰티 5
 
0.6%
부산 5
 
0.6%
Other values (759) 809
90.5%
2024-03-15T02:27:00.224110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
228
 
5.3%
어 130
 
3.0%
헤 126
 
3.0%
스 112
 
2.6%
미 101
 
2.4%
이 98
 
2.3%
텔 88
 
2.1%
용 85
 
2.0%
) 77
 
1.8%
( 77
 
1.8%
Other values (449) 3147
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3437
80.5%
Space Separator 228
 
5.3%
Lowercase Letter 199
 
4.7%
Uppercase Letter 198
 
4.6%
Close Punctuation 77
 
1.8%
Open Punctuation 77
 
1.8%
Decimal Number 29
 
0.7%
Other Punctuation 21
 
0.5%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 130
 
3.8%
헤 126
 
3.7%
스 112
 
3.3%
미 101
 
2.9%
이 98
 
2.9%
텔 88
 
2.6%
용 85
 
2.5%
실 72
 
2.1%
호 70
 
2.0%
리 56
 
1.6%
Other values (386) 2499
72.7%
Uppercase Letter
ValueCountFrequency (%)
N 20
 
10.1%
A 18
 
9.1%
H 16
 
8.1%
T 15
 
7.6%
E 15
 
7.6%
M 14
 
7.1%
I 14
 
7.1%
O 12
 
6.1%
S 11
 
5.6%
B 9
 
4.5%
Other values (13) 54
27.3%
Lowercase Letter
ValueCountFrequency (%)
a 26
13.1%
i 22
11.1%
e 19
9.5%
r 19
9.5%
l 18
9.0%
o 18
9.0%
n 11
 
5.5%
u 10
 
5.0%
y 8
 
4.0%
s 7
 
3.5%
Other values (12) 41
20.6%
Decimal Number
ValueCountFrequency (%)
7 5
17.2%
2 5
17.2%
9 5
17.2%
0 4
13.8%
1 3
10.3%
4 2
 
6.9%
5 2
 
6.9%
3 1
 
3.4%
8 1
 
3.4%
6 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 7
33.3%
. 6
28.6%
& 6
28.6%
: 2
 
9.5%
Space Separator
ValueCountFrequency (%)
228
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3437
80.5%
Common 435
 
10.2%
Latin 397
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 130
 
3.8%
헤 126
 
3.7%
스 112
 
3.3%
미 101
 
2.9%
이 98
 
2.9%
텔 88
 
2.6%
용 85
 
2.5%
실 72
 
2.1%
호 70
 
2.0%
리 56
 
1.6%
Other values (386) 2499
72.7%
Latin
ValueCountFrequency (%)
a 26
 
6.5%
i 22
 
5.5%
N 20
 
5.0%
e 19
 
4.8%
r 19
 
4.8%
l 18
 
4.5%
o 18
 
4.5%
A 18
 
4.5%
H 16
 
4.0%
T 15
 
3.8%
Other values (35) 206
51.9%
Common
ValueCountFrequency (%)
228
52.4%
) 77
 
17.7%
( 77
 
17.7%
, 7
 
1.6%
. 6
 
1.4%
& 6
 
1.4%
7 5
 
1.1%
2 5
 
1.1%
9 5
 
1.1%
0 4
 
0.9%
Other values (8) 15
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3437
80.5%
ASCII 832
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
228
27.4%
) 77
 
9.3%
( 77
 
9.3%
a 26
 
3.1%
i 22
 
2.6%
N 20
 
2.4%
e 19
 
2.3%
r 19
 
2.3%
l 18
 
2.2%
o 18
 
2.2%
Other values (53) 308
37.0%
Hangul
ValueCountFrequency (%)
어 130
 
3.8%
헤 126
 
3.7%
스 112
 
3.3%
미 101
 
2.9%
이 98
 
2.9%
텔 88
 
2.6%
용 85
 
2.5%
실 72
 
2.1%
호 70
 
2.0%
리 56
 
1.6%
Other values (386) 2499
72.7%

업소도로명주소
Text

Distinct638
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-03-15T02:27:01.412608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length46
Mean length29.774775
Min length21

Characters and Unicode

Total characters19830
Distinct characters155
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

Unique612 ?
Unique (%)91.9%

Sample

1st row부산광역시 중구 초량중로6번길 17 (영주동)
2nd row부산광역시 중구 대영로242번길 18-7 (영주동)
3rd row부산광역시 중구 광복로12번길 7-4 (부평동1가)
4th row부산광역시 중구 광복로6번길 11-1 (부평동2가)
5th row부산광역시 중구 중구로62번길 6 (대청동3가)
ValueCountFrequency (%)
부산광역시 666
 
17.0%
중구 666
 
17.0%
2층 120
 
3.1%
1층 117
 
3.0%
3층 79
 
2.0%
영주동 50
 
1.3%
대청로 45
 
1.1%
광복로 43
 
1.1%
중앙동4가 43
 
1.1%
남포동5가 39
 
1.0%
Other values (576) 2053
52.4%
2024-03-15T02:27:02.810613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3255
 
16.4%
광 909
 
4.6%
중 897
 
4.5%
1 875
 
4.4%
구 786
 
4.0%
부 762
 
3.8%
동 749
 
3.8%
산 678
 
3.4%
시 675
 
3.4%
) 670
 
3.4%
Other values (145) 9574
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10933
55.1%
Decimal Number 3446
 
17.4%
Space Separator 3255
 
16.4%
Close Punctuation 670
 
3.4%
Open Punctuation 670
 
3.4%
Other Punctuation 540
 
2.7%
Dash Punctuation 290
 
1.5%
Uppercase Letter 15
 
0.1%
Math Symbol 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 909
 
8.3%
중 897
 
8.2%
구 786
 
7.2%
부 762
 
7.0%
동 749
 
6.9%
산 678
 
6.2%
시 675
 
6.2%
역 669
 
6.1%
가 630
 
5.8%
로 584
 
5.3%
Other values (117) 3594
32.9%
Decimal Number
ValueCountFrequency (%)
1 875
25.4%
2 646
18.7%
3 489
14.2%
4 389
11.3%
5 299
 
8.7%
6 191
 
5.5%
9 153
 
4.4%
7 144
 
4.2%
8 139
 
4.0%
0 121
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
20.0%
A 2
13.3%
T 2
13.3%
O 2
13.3%
L 1
 
6.7%
U 1
 
6.7%
P 1
 
6.7%
E 1
 
6.7%
G 1
 
6.7%
N 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 538
99.6%
/ 1
 
0.2%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 670
100.0%
Open Punctuation
ValueCountFrequency (%)
( 670
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 290
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10933
55.1%
Common 8882
44.8%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 909
 
8.3%
중 897
 
8.2%
구 786
 
7.2%
부 762
 
7.0%
동 749
 
6.9%
산 678
 
6.2%
시 675
 
6.2%
역 669
 
6.1%
가 630
 
5.8%
로 584
 
5.3%
Other values (117) 3594
32.9%
Common
ValueCountFrequency (%)
3255
36.6%
1 875
 
9.9%
) 670
 
7.5%
( 670
 
7.5%
2 646
 
7.3%
, 538
 
6.1%
3 489
 
5.5%
4 389
 
4.4%
5 299
 
3.4%
- 290
 
3.3%
Other values (8) 761
 
8.6%
Latin
ValueCountFrequency (%)
B 3
20.0%
A 2
13.3%
T 2
13.3%
O 2
13.3%
L 1
 
6.7%
U 1
 
6.7%
P 1
 
6.7%
E 1
 
6.7%
G 1
 
6.7%
N 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10933
55.1%
ASCII 8897
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3255
36.6%
1 875
 
9.8%
) 670
 
7.5%
( 670
 
7.5%
2 646
 
7.3%
, 538
 
6.0%
3 489
 
5.5%
4 389
 
4.4%
5 299
 
3.4%
- 290
 
3.3%
Other values (18) 776
 
8.7%
Hangul
ValueCountFrequency (%)
광 909
 
8.3%
중 897
 
8.2%
구 786
 
7.2%
부 762
 
7.0%
동 749
 
6.9%
산 678
 
6.2%
시 675
 
6.2%
역 669
 
6.1%
가 630
 
5.8%
로 584
 
5.3%
Other values (117) 3594
32.9%

업소전화번호
Text

MISSING 

Distinct465
Distinct (%)98.3%
Missing193
Missing (%)29.0%
Memory size5.3 KiB
2024-03-15T02:27:03.815088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027484
Min length12

Characters and Unicode

Total characters5689
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

Unique457 ?
Unique (%)96.6%

Sample

1st row051-469-8886
2nd row051-469-4115
3rd row051-245-6344
4th row051-245-9458
5th row051-469-6088
ValueCountFrequency (%)
051-257-3833 2
 
0.4%
051-245-7072 2
 
0.4%
051-245-4066 2
 
0.4%
051-244-4321 2
 
0.4%
070-8864-7890 2
 
0.4%
051-245-8093 2
 
0.4%
051-231-1178 2
 
0.4%
051-715-8844 2
 
0.4%
051-521-1411 1
 
0.2%
051-253-4370 1
 
0.2%
Other values (455) 455
96.2%
2024-03-15T02:27:05.241335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 946
16.6%
5 795
14.0%
0 736
12.9%
1 698
12.3%
4 588
10.3%
2 552
9.7%
6 387
6.8%
7 282
 
5.0%
3 253
 
4.4%
8 239
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4743
83.4%
Dash Punctuation 946
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 795
16.8%
0 736
15.5%
1 698
14.7%
4 588
12.4%
2 552
11.6%
6 387
8.2%
7 282
 
5.9%
3 253
 
5.3%
8 239
 
5.0%
9 213
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5689
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 946
16.6%
5 795
14.0%
0 736
12.9%
1 698
12.3%
4 588
10.3%
2 552
9.7%
6 387
6.8%
7 282
 
5.0%
3 253
 
4.4%
8 239
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5689
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 946
16.6%
5 795
14.0%
0 736
12.9%
1 698
12.3%
4 588
10.3%
2 552
9.7%
6 387
6.8%
7 282
 
5.0%
3 253
 
4.4%
8 239
 
4.2%

Missing values

2024-03-15T02:26:57.254975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:26:57.546217image/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

업종명업소명업소도로명주소업소전화번호
0숙박업(일반)양지장부산광역시 중구 초량중로6번길 17 (영주동)051-469-8886
1숙박업(일반)더로찌부산광역시 중구 대영로242번길 18-7 (영주동)051-469-4115
2숙박업(일반)유일모텔부산광역시 중구 광복로12번길 7-4 (부평동1가)051-245-6344
3숙박업(일반)부산부산광역시 중구 광복로6번길 11-1 (부평동2가)051-245-9458
4숙박업(일반)로얄장부산광역시 중구 중구로62번길 6 (대청동3가)051-469-6088
5숙박업(일반)초원그린빌부산광역시 중구 대영로242번길 20 (영주동)051-469-9766
6숙박업(일반)서울모텔부산광역시 중구 해관로 76-1 (중앙동4가, 55-4,11)051-469-7001
7숙박업(일반)에이스모텔부산광역시 중구 백산길 10-1 (동광동3가)051-246-2161
8숙박업(일반)베이호텔부산광역시 중구 광복로 56-18 (남포동2가)051-243-8254
9숙박업(일반)로즈모텔부산광역시 중구 중구로5번길 10-2 (남포동6가)051-245-8093
업종명업소명업소도로명주소업소전화번호
656일반미용업, 네일미용업, 화장ㆍ분장 미용업OLA네일(올라네일)부산광역시 중구 대청로 93, 3층 (대청동2가)<NA>
657일반미용업, 네일미용업, 화장ㆍ분장 미용업헤어셀렉션 광복점부산광역시 중구 광복로 51-1, 2층 (창선동1가)051-246-3350
658일반미용업, 네일미용업, 화장ㆍ분장 미용업서산하가발부산광역시 중구 대청로 146, 202호 (중앙동2가)051-242-2334
659일반미용업, 네일미용업, 화장ㆍ분장 미용업블랙컷트부산광역시 중구 동영로 14-2, 1층 202호 (동광동5가, 향미빌리지)<NA>
660피부미용업, 네일미용업, 화장ㆍ분장 미용업도쿄네일 앤 스튜디오(Tokyo Nail & Studio)부산광역시 중구 중앙대로 지하 17, B동 4호 (중앙동6가)<NA>
661피부미용업, 네일미용업, 화장ㆍ분장 미용업바루나 뷰티부산광역시 중구 흑교로31번길 3, 1층 (부평동3가)051-243-4144
662피부미용업, 네일미용업, 화장ㆍ분장 미용업제제언니피부미용부산광역시 중구 광복로 20-1, 3층 (부평동1가)<NA>
663피부미용업, 네일미용업, 화장ㆍ분장 미용업더끌림뷰티부산광역시 중구 구덕로34번길 7, 4층 (남포동2가)<NA>
664피부미용업, 네일미용업, 화장ㆍ분장 미용업끌레르뷰티부산광역시 중구 남포길 29-1, 4층 (남포동2가)<NA>
665피부미용업, 네일미용업, 화장ㆍ분장 미용업BOB뷰티(비오비뷰티)부산광역시 중구 흑교로 71-1, 2층 (보수동2가)<NA>

Duplicate rows

Most frequently occurring

업종명업소명업소도로명주소업소전화번호# duplicates
0종합미용업오샤레 헤어부산광역시 중구 중앙대로 35-1, 2층 (중앙동6가)051-245-70722