Overview

Dataset statistics

Number of variables4
Number of observations766
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.1 KiB
Average record size in memory32.2 B

Variable types

Categorical1
Text3

Dataset

Description울산광역시 동구 내 위치한 공중위생업 현황 데이터로 목욕업, 미용업, 세탁소 등의 위치, 연락처 정보 등을 제공합니다
Author울산광역시 동구
URLhttps://www.data.go.kr/data/15006811/fileData.do

Reproduction

Analysis started2024-03-15 00:16:42.446647
Analysis finished2024-03-15 00:16:43.266667
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct20
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
일반미용업
392 
이용업
68 
숙박업(일반)
66 
피부미용업
61 
네일미용업
45 
Other values (15)
134 

Length

Max length23
Median length5
Mean length5.4308094
Min length3

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 392
51.2%
이용업 68
 
8.9%
숙박업(일반) 66
 
8.6%
피부미용업 61
 
8.0%
네일미용업 45
 
5.9%
세탁업 40
 
5.2%
목욕장업 21
 
2.7%
건물위생관리업 17
 
2.2%
종합미용업 12
 
1.6%
피부미용업, 네일미용업 7
 
0.9%
Other values (10) 37
 
4.8%

Length

2024-03-15T09:16:43.475996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 408
49.0%
피부미용업 80
 
9.6%
네일미용업 70
 
8.4%
이용업 68
 
8.2%
숙박업(일반 66
 
7.9%
세탁업 40
 
4.8%
화장ㆍ분장 23
 
2.8%
미용업 23
 
2.8%
목욕장업 21
 
2.5%
건물위생관리업 17
 
2.0%
Other values (2) 16
 
1.9%

신고일자
Text

Distinct721
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-03-15T09:16:44.486779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters7660
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

Unique677 ?
Unique (%)88.4%

Sample

1st row1979-03-22
2nd row1979-07-18
3rd row1979-11-09
4th row1980-08-11
5th row1981-03-25
ValueCountFrequency (%)
2014-09-29 3
 
0.4%
2019-09-20 2
 
0.3%
2016-08-18 2
 
0.3%
2013-04-10 2
 
0.3%
2002-05-23 2
 
0.3%
2021-06-03 2
 
0.3%
2023-04-04 2
 
0.3%
1990-04-20 2
 
0.3%
2022-08-16 2
 
0.3%
2005-10-07 2
 
0.3%
Other values (711) 745
97.3%
2024-03-15T09:16:46.076452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1726
22.5%
- 1532
20.0%
2 1321
17.2%
1 1169
15.3%
9 480
 
6.3%
3 329
 
4.3%
8 258
 
3.4%
7 230
 
3.0%
4 209
 
2.7%
6 209
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6128
80.0%
Dash Punctuation 1532
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1726
28.2%
2 1321
21.6%
1 1169
19.1%
9 480
 
7.8%
3 329
 
5.4%
8 258
 
4.2%
7 230
 
3.8%
4 209
 
3.4%
6 209
 
3.4%
5 197
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 1532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1726
22.5%
- 1532
20.0%
2 1321
17.2%
1 1169
15.3%
9 480
 
6.3%
3 329
 
4.3%
8 258
 
3.4%
7 230
 
3.0%
4 209
 
2.7%
6 209
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1726
22.5%
- 1532
20.0%
2 1321
17.2%
1 1169
15.3%
9 480
 
6.3%
3 329
 
4.3%
8 258
 
3.4%
7 230
 
3.0%
4 209
 
2.7%
6 209
 
2.7%

업소명
Text

Distinct744
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-03-15T09:16:46.960307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length5.8916449
Min length1

Characters and Unicode

Total characters4513
Distinct characters498
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique726 ?
Unique (%)94.8%

Sample

1st row뉴 정록장
2nd row향촌
3rd row제일장
4th row고고
5th row랑랑
ValueCountFrequency (%)
헤어 9
 
1.0%
미용실 6
 
0.7%
주식회사 5
 
0.5%
salon 5
 
0.5%
hair 5
 
0.5%
남성컷트전문점 5
 
0.5%
포맨 4
 
0.4%
네일 4
 
0.4%
맨즈헤어 3
 
0.3%
호텔 3
 
0.3%
Other values (830) 863
94.6%
2024-03-15T09:16:48.755555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 253
 
5.6%
헤 241
 
5.3%
146
 
3.2%
이 115
 
2.5%
스 82
 
1.8%
미 73
 
1.6%
) 72
 
1.6%
( 72
 
1.6%
일 68
 
1.5%
리 66
 
1.5%
Other values (488) 3325
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3671
81.3%
Lowercase Letter 260
 
5.8%
Uppercase Letter 228
 
5.1%
Space Separator 146
 
3.2%
Close Punctuation 72
 
1.6%
Open Punctuation 72
 
1.6%
Other Punctuation 35
 
0.8%
Decimal Number 23
 
0.5%
Dash Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 253
 
6.9%
헤 241
 
6.6%
이 115
 
3.1%
스 82
 
2.2%
미 73
 
2.0%
일 68
 
1.9%
리 66
 
1.8%
용 59
 
1.6%
샵 51
 
1.4%
네 48
 
1.3%
Other values (419) 2615
71.2%
Uppercase Letter
ValueCountFrequency (%)
H 20
 
8.8%
A 18
 
7.9%
E 18
 
7.9%
I 17
 
7.5%
N 15
 
6.6%
B 13
 
5.7%
R 13
 
5.7%
O 12
 
5.3%
C 11
 
4.8%
T 11
 
4.8%
Other values (16) 80
35.1%
Lowercase Letter
ValueCountFrequency (%)
a 35
13.5%
e 25
9.6%
i 25
9.6%
o 24
9.2%
r 21
8.1%
n 21
8.1%
l 20
7.7%
s 18
6.9%
h 17
 
6.5%
t 11
 
4.2%
Other values (12) 43
16.5%
Decimal Number
ValueCountFrequency (%)
1 5
21.7%
7 4
17.4%
8 4
17.4%
9 3
13.0%
0 2
 
8.7%
2 2
 
8.7%
6 1
 
4.3%
3 1
 
4.3%
4 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
& 10
28.6%
, 7
20.0%
# 7
20.0%
. 7
20.0%
' 3
 
8.6%
: 1
 
2.9%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3670
81.3%
Latin 488
 
10.8%
Common 354
 
7.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 253
 
6.9%
헤 241
 
6.6%
이 115
 
3.1%
스 82
 
2.2%
미 73
 
2.0%
일 68
 
1.9%
리 66
 
1.8%
용 59
 
1.6%
샵 51
 
1.4%
네 48
 
1.3%
Other values (418) 2614
71.2%
Latin
ValueCountFrequency (%)
a 35
 
7.2%
e 25
 
5.1%
i 25
 
5.1%
o 24
 
4.9%
r 21
 
4.3%
n 21
 
4.3%
H 20
 
4.1%
l 20
 
4.1%
A 18
 
3.7%
E 18
 
3.7%
Other values (38) 261
53.5%
Common
ValueCountFrequency (%)
146
41.2%
) 72
20.3%
( 72
20.3%
& 10
 
2.8%
, 7
 
2.0%
# 7
 
2.0%
. 7
 
2.0%
1 5
 
1.4%
- 4
 
1.1%
7 4
 
1.1%
Other values (11) 20
 
5.6%
Han
ValueCountFrequency (%)
美 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3670
81.3%
ASCII 842
 
18.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 253
 
6.9%
헤 241
 
6.6%
이 115
 
3.1%
스 82
 
2.2%
미 73
 
2.0%
일 68
 
1.9%
리 66
 
1.8%
용 59
 
1.6%
샵 51
 
1.4%
네 48
 
1.3%
Other values (418) 2614
71.2%
ASCII
ValueCountFrequency (%)
146
 
17.3%
) 72
 
8.6%
( 72
 
8.6%
a 35
 
4.2%
e 25
 
3.0%
i 25
 
3.0%
o 24
 
2.9%
r 21
 
2.5%
n 21
 
2.5%
H 20
 
2.4%
Other values (59) 381
45.2%
CJK
ValueCountFrequency (%)
美 1
100.0%

영업소주소
Text

Distinct754
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-03-15T09:16:50.420321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length50
Mean length28.073107
Min length20

Characters and Unicode

Total characters21504
Distinct characters242
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique743 ?
Unique (%)97.0%

Sample

1st row울산광역시 동구 방어진순환도로 797 (전하동)
2nd row울산광역시 동구 바드래4길 19 (전하동)
3rd row울산광역시 동구 내진3길 2 (방어동, 197-1)
4th row울산광역시 동구 바드래4길 7 (전하동)
5th row울산광역시 동구 바드래2길 12 (전하동)
ValueCountFrequency (%)
울산광역시 766
 
16.6%
동구 766
 
16.6%
1층 262
 
5.7%
전하동 172
 
3.7%
방어동 165
 
3.6%
화정동 165
 
3.6%
동부동 79
 
1.7%
서부동 70
 
1.5%
일산동 70
 
1.5%
방어진순환도로 53
 
1.2%
Other values (706) 2040
44.3%
2024-03-15T09:16:52.415544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3842
17.9%
동 1694
 
7.9%
1 1049
 
4.9%
산 855
 
4.0%
( 778
 
3.6%
시 778
 
3.6%
) 778
 
3.6%
구 768
 
3.6%
광 767
 
3.6%
울 766
 
3.6%
Other values (232) 9429
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11948
55.6%
Space Separator 3842
 
17.9%
Decimal Number 3385
 
15.7%
Open Punctuation 778
 
3.6%
Close Punctuation 778
 
3.6%
Other Punctuation 589
 
2.7%
Dash Punctuation 117
 
0.5%
Uppercase Letter 47
 
0.2%
Lowercase Letter 16
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1694
 
14.2%
산 855
 
7.2%
시 778
 
6.5%
구 768
 
6.4%
광 767
 
6.4%
울 766
 
6.4%
역 766
 
6.4%
길 532
 
4.5%
층 387
 
3.2%
화 240
 
2.0%
Other values (196) 4395
36.8%
Decimal Number
ValueCountFrequency (%)
1 1049
31.0%
2 424
12.5%
3 314
 
9.3%
0 308
 
9.1%
5 286
 
8.4%
6 234
 
6.9%
4 233
 
6.9%
7 213
 
6.3%
8 171
 
5.1%
9 153
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 14
29.8%
A 7
14.9%
P 6
12.8%
K 5
 
10.6%
C 5
 
10.6%
I 4
 
8.5%
R 3
 
6.4%
D 1
 
2.1%
V 1
 
2.1%
H 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 6
37.5%
s 4
25.0%
l 1
 
6.2%
o 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
w 1
 
6.2%
a 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 584
99.2%
' 3
 
0.5%
& 2
 
0.3%
Space Separator
ValueCountFrequency (%)
3842
100.0%
Open Punctuation
ValueCountFrequency (%)
( 778
100.0%
Close Punctuation
ValueCountFrequency (%)
) 778
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11948
55.6%
Common 9493
44.1%
Latin 63
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1694
 
14.2%
산 855
 
7.2%
시 778
 
6.5%
구 768
 
6.4%
광 767
 
6.4%
울 766
 
6.4%
역 766
 
6.4%
길 532
 
4.5%
층 387
 
3.2%
화 240
 
2.0%
Other values (196) 4395
36.8%
Common
ValueCountFrequency (%)
3842
40.5%
1 1049
 
11.1%
( 778
 
8.2%
) 778
 
8.2%
, 584
 
6.2%
2 424
 
4.5%
3 314
 
3.3%
0 308
 
3.2%
5 286
 
3.0%
6 234
 
2.5%
Other values (8) 896
 
9.4%
Latin
ValueCountFrequency (%)
B 14
22.2%
A 7
11.1%
P 6
9.5%
e 6
9.5%
K 5
 
7.9%
C 5
 
7.9%
s 4
 
6.3%
I 4
 
6.3%
R 3
 
4.8%
D 1
 
1.6%
Other values (8) 8
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11948
55.6%
ASCII 9556
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3842
40.2%
1 1049
 
11.0%
( 778
 
8.1%
) 778
 
8.1%
, 584
 
6.1%
2 424
 
4.4%
3 314
 
3.3%
0 308
 
3.2%
5 286
 
3.0%
6 234
 
2.4%
Other values (26) 959
 
10.0%
Hangul
ValueCountFrequency (%)
동 1694
 
14.2%
산 855
 
7.2%
시 778
 
6.5%
구 768
 
6.4%
광 767
 
6.4%
울 766
 
6.4%
역 766
 
6.4%
길 532
 
4.5%
층 387
 
3.2%
화 240
 
2.0%
Other values (196) 4395
36.8%

Missing values

2024-03-15T09:16:43.055580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:16:43.207633image/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

업종명신고일자업소명영업소주소
0숙박업(일반)1979-03-22뉴 정록장울산광역시 동구 방어진순환도로 797 (전하동)
1숙박업(일반)1979-07-18향촌울산광역시 동구 바드래4길 19 (전하동)
2숙박업(일반)1979-11-09제일장울산광역시 동구 내진3길 2 (방어동, 197-1)
3숙박업(일반)1980-08-11고고울산광역시 동구 바드래4길 7 (전하동)
4숙박업(일반)1981-03-25랑랑울산광역시 동구 바드래2길 12 (전하동)
5숙박업(일반)1982-05-07서울장울산광역시 동구 대학길 180 (화정동)
6숙박업(일반)1982-12-01동광울산광역시 동구 방어진순환도로 927-1 (서부동)
7숙박업(일반)1983-05-14해오름모텔울산광역시 동구 내진3길 4 (방어동)
8숙박업(일반)1983-01-24주식회사 라한호텔 울산울산광역시 동구 방어진순환도로 875 (전하동)
9숙박업(일반)1983-05-14약수장울산광역시 동구 옥류3길 3-1 (서부동)
업종명신고일자업소명영업소주소
756네일미용업, 화장ㆍ분장 미용업2023-10-26네일노리(NAIL NORI)울산광역시 동구 봉수로 224, 한라타워맨션 제상가동 3호 (전하동)
757일반미용업, 피부미용업, 네일미용업2001-02-22노블리안울산광역시 동구 양지5길 2 (화정동)
758일반미용업, 피부미용업, 화장ㆍ분장 미용업2023-01-10이음울산광역시 동구 내진1길 23, 1층 (방어동)
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