Overview

Dataset statistics

Number of variables4
Number of observations186
Missing cells17
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory32.7 B

Variable types

Categorical1
Text3

Dataset

Description강진군 공중위생업소 현황에 대한 데이터로 업종명, 업소명, 업소소재지 주소, 소재지 전화번호 등에 대한 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15007218/fileData.do

Alerts

소재지전화 has 17 (9.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:34:13.763787
Analysis finished2023-12-12 18:34:14.291854
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct14
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
미용업
42 
숙박업(일반)
33 
일반미용업
22 
세탁업
20 
이용업
20 
Other values (9)
49 

Length

Max length16
Median length12
Mean length4.7096774
Min length3

Unique

Unique3 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 42
22.6%
숙박업(일반) 33
17.7%
일반미용업 22
11.8%
세탁업 20
10.8%
이용업 20
10.8%
피부미용업 12
 
6.5%
목욕장업 9
 
4.8%
종합미용업 8
 
4.3%
건물위생관리업 6
 
3.2%
숙박업(생활) 6
 
3.2%
Other values (4) 8
 
4.3%

Length

2023-12-13T03:34:14.419711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 44
23.0%
숙박업(일반 33
17.3%
일반미용업 24
12.6%
세탁업 20
10.5%
이용업 20
10.5%
피부미용업 12
 
6.3%
목욕장업 9
 
4.7%
종합미용업 8
 
4.2%
네일미용업 7
 
3.7%
건물위생관리업 6
 
3.1%
Other values (2) 8
 
4.2%

업소명
Text

Distinct182
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T03:34:15.118262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length5.7204301
Min length2

Characters and Unicode

Total characters1064
Distinct characters264
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)95.7%

Sample

1st row나은관리산업(주)
2nd row한국방역환경
3rd row다산클린
4th row전남강진지역자활센터(클린청소)
5th row(주) 인맥
ValueCountFrequency (%)
미용실 4
 
1.8%
네일 3
 
1.4%
서울세탁소 2
 
0.9%
이든호스텔 2
 
0.9%
모텔 2
 
0.9%
헤어샵 2
 
0.9%
헤어 2
 
0.9%
주)티에스파워텍 2
 
0.9%
제일세탁소 2
 
0.9%
제일이발관 2
 
0.9%
Other values (196) 196
89.5%
2023-12-13T03:34:15.798542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 39
 
3.7%
미 34
 
3.2%
33
 
3.1%
어 30
 
2.8%
실 26
 
2.4%
용 26
 
2.4%
헤 25
 
2.3%
텔 23
 
2.2%
관 22
 
2.1%
모 22
 
2.1%
Other values (254) 784
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 957
89.9%
Space Separator 33
 
3.1%
Lowercase Letter 28
 
2.6%
Uppercase Letter 21
 
2.0%
Close Punctuation 9
 
0.8%
Open Punctuation 9
 
0.8%
Other Punctuation 6
 
0.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 39
 
4.1%
미 34
 
3.6%
어 30
 
3.1%
실 26
 
2.7%
용 26
 
2.7%
헤 25
 
2.6%
텔 23
 
2.4%
관 22
 
2.3%
모 22
 
2.3%
스 20
 
2.1%
Other values (215) 690
72.1%
Lowercase Letter
ValueCountFrequency (%)
o 4
14.3%
e 3
10.7%
b 2
 
7.1%
u 2
 
7.1%
y 2
 
7.1%
n 2
 
7.1%
s 2
 
7.1%
a 2
 
7.1%
l 1
 
3.6%
r 1
 
3.6%
Other values (7) 7
25.0%
Uppercase Letter
ValueCountFrequency (%)
O 3
14.3%
B 2
9.5%
S 2
9.5%
A 2
9.5%
N 2
9.5%
J 2
9.5%
W 1
 
4.8%
H 1
 
4.8%
L 1
 
4.8%
C 1
 
4.8%
Other values (4) 4
19.0%
Other Punctuation
ValueCountFrequency (%)
& 3
50.0%
. 1
 
16.7%
# 1
 
16.7%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 956
89.8%
Common 58
 
5.5%
Latin 49
 
4.6%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 39
 
4.1%
미 34
 
3.6%
어 30
 
3.1%
실 26
 
2.7%
용 26
 
2.7%
헤 25
 
2.6%
텔 23
 
2.4%
관 22
 
2.3%
모 22
 
2.3%
스 20
 
2.1%
Other values (214) 689
72.1%
Latin
ValueCountFrequency (%)
o 4
 
8.2%
e 3
 
6.1%
O 3
 
6.1%
b 2
 
4.1%
B 2
 
4.1%
u 2
 
4.1%
y 2
 
4.1%
S 2
 
4.1%
A 2
 
4.1%
N 2
 
4.1%
Other values (21) 25
51.0%
Common
ValueCountFrequency (%)
33
56.9%
) 9
 
15.5%
( 9
 
15.5%
& 3
 
5.2%
. 1
 
1.7%
= 1
 
1.7%
# 1
 
1.7%
, 1
 
1.7%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 956
89.8%
ASCII 107
 
10.1%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 39
 
4.1%
미 34
 
3.6%
어 30
 
3.1%
실 26
 
2.7%
용 26
 
2.7%
헤 25
 
2.6%
텔 23
 
2.4%
관 22
 
2.3%
모 22
 
2.3%
스 20
 
2.1%
Other values (214) 689
72.1%
ASCII
ValueCountFrequency (%)
33
30.8%
) 9
 
8.4%
( 9
 
8.4%
o 4
 
3.7%
& 3
 
2.8%
e 3
 
2.8%
O 3
 
2.8%
b 2
 
1.9%
B 2
 
1.9%
u 2
 
1.9%
Other values (29) 37
34.6%
CJK
ValueCountFrequency (%)
愛 1
100.0%

영업소 주소(도로명)
Text

Distinct178
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T03:34:16.283952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length22.580645
Min length18

Characters and Unicode

Total characters4200
Distinct characters141
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

Unique170 ?
Unique (%)91.4%

Sample

1st row전라남도 강진군 강진읍 남포3길 8-1
2nd row전라남도 강진군 강진읍 동성로 27
3rd row전라남도 강진군 강진읍 중앙로 88, 금호상가 101동 2층 206호
4th row전라남도 강진군 강진읍 지전로 562-14
5th row전라남도 강진군 성전면 별뫼로 371-1
ValueCountFrequency (%)
전라남도 186
18.5%
강진군 186
18.5%
강진읍 125
 
12.4%
중앙로 27
 
2.7%
마량면 17
 
1.7%
1층 16
 
1.6%
탐진로 12
 
1.2%
병영면 10
 
1.0%
병영성로 9
 
0.9%
성전면 9
 
0.9%
Other values (233) 410
40.7%
2023-12-13T03:34:16.979193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
821
19.5%
진 331
 
7.9%
강 316
 
7.5%
전 207
 
4.9%
군 196
 
4.7%
도 194
 
4.6%
남 189
 
4.5%
라 187
 
4.5%
1 169
 
4.0%
로 133
 
3.2%
Other values (131) 1457
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2657
63.3%
Space Separator 821
 
19.5%
Decimal Number 604
 
14.4%
Dash Punctuation 54
 
1.3%
Other Punctuation 35
 
0.8%
Close Punctuation 13
 
0.3%
Open Punctuation 13
 
0.3%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 331
12.5%
강 316
11.9%
전 207
 
7.8%
군 196
 
7.4%
도 194
 
7.3%
남 189
 
7.1%
라 187
 
7.0%
로 133
 
5.0%
읍 125
 
4.7%
길 90
 
3.4%
Other values (112) 689
25.9%
Decimal Number
ValueCountFrequency (%)
1 169
28.0%
2 87
14.4%
3 85
14.1%
0 48
 
7.9%
7 44
 
7.3%
4 40
 
6.6%
8 38
 
6.3%
6 38
 
6.3%
9 30
 
5.0%
5 25
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
C 1
33.3%
L 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 34
97.1%
& 1
 
2.9%
Space Separator
ValueCountFrequency (%)
821
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2657
63.3%
Common 1540
36.7%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 331
12.5%
강 316
11.9%
전 207
 
7.8%
군 196
 
7.4%
도 194
 
7.3%
남 189
 
7.1%
라 187
 
7.0%
로 133
 
5.0%
읍 125
 
4.7%
길 90
 
3.4%
Other values (112) 689
25.9%
Common
ValueCountFrequency (%)
821
53.3%
1 169
 
11.0%
2 87
 
5.6%
3 85
 
5.5%
- 54
 
3.5%
0 48
 
3.1%
7 44
 
2.9%
4 40
 
2.6%
8 38
 
2.5%
6 38
 
2.5%
Other values (6) 116
 
7.5%
Latin
ValueCountFrequency (%)
S 1
33.3%
C 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2657
63.3%
ASCII 1543
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
821
53.2%
1 169
 
11.0%
2 87
 
5.6%
3 85
 
5.5%
- 54
 
3.5%
0 48
 
3.1%
7 44
 
2.9%
4 40
 
2.6%
8 38
 
2.5%
6 38
 
2.5%
Other values (9) 119
 
7.7%
Hangul
ValueCountFrequency (%)
진 331
12.5%
강 316
11.9%
전 207
 
7.8%
군 196
 
7.4%
도 194
 
7.3%
남 189
 
7.1%
라 187
 
7.0%
로 133
 
5.0%
읍 125
 
4.7%
길 90
 
3.4%
Other values (112) 689
25.9%

소재지전화
Text

MISSING 

Distinct164
Distinct (%)97.0%
Missing17
Missing (%)9.1%
Memory size1.6 KiB
2023-12-13T03:34:17.344535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.071006
Min length9

Characters and Unicode

Total characters2040
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

Unique159 ?
Unique (%)94.1%

Sample

1st row042-585-2645
2nd row061-434-1580
3rd row061-434-7002
4th row061-434-7002
5th row1577-3211
ValueCountFrequency (%)
061-433-6262 2
 
1.2%
061-432-4277 2
 
1.2%
061-433-7188 2
 
1.2%
061-432-8925 2
 
1.2%
061-434-7002 2
 
1.2%
0507-1332-3299 1
 
0.6%
042-585-2645 1
 
0.6%
1661-0117 1
 
0.6%
061-432-5018 1
 
0.6%
061-434-6606 1
 
0.6%
Other values (154) 154
91.1%
2023-12-13T03:34:17.882538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 335
16.4%
4 281
13.8%
0 270
13.2%
3 265
13.0%
1 238
11.7%
6 230
11.3%
2 127
 
6.2%
7 75
 
3.7%
8 75
 
3.7%
5 74
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1705
83.6%
Dash Punctuation 335
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 281
16.5%
0 270
15.8%
3 265
15.5%
1 238
14.0%
6 230
13.5%
2 127
7.4%
7 75
 
4.4%
8 75
 
4.4%
5 74
 
4.3%
9 70
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 335
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2040
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 335
16.4%
4 281
13.8%
0 270
13.2%
3 265
13.0%
1 238
11.7%
6 230
11.3%
2 127
 
6.2%
7 75
 
3.7%
8 75
 
3.7%
5 74
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 335
16.4%
4 281
13.8%
0 270
13.2%
3 265
13.0%
1 238
11.7%
6 230
11.3%
2 127
 
6.2%
7 75
 
3.7%
8 75
 
3.7%
5 74
 
3.6%

Missing values

2023-12-13T03:34:14.136352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:34:14.246384image/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
0건물위생관리업나은관리산업(주)전라남도 강진군 강진읍 남포3길 8-1042-585-2645
1건물위생관리업한국방역환경전라남도 강진군 강진읍 동성로 27061-434-1580
2건물위생관리업다산클린전라남도 강진군 강진읍 중앙로 88, 금호상가 101동 2층 206호061-434-7002
3건물위생관리업전남강진지역자활센터(클린청소)전라남도 강진군 강진읍 지전로 562-14061-434-7002
4건물위생관리업(주) 인맥전라남도 강진군 성전면 별뫼로 371-11577-3211
5건물위생관리업(주)바른전라남도 강진군 강진읍 평동1길 11, 1층1600-9606
6네일미용업또네일전라남도 강진군 강진읍 중앙로 53, 1층 1호0507-1369-1086
7네일미용업현주 네일전라남도 강진군 강진읍 초지길 36061-433-2331
8네일미용업네일스파전라남도 강진군 군동면 진흥로 13, 2층 204호<NA>
9네일미용업네일#전라남도 강진군 마량면 마량3길 310507-1340-7613
업종명업소명영업소 주소(도로명)소재지전화
176피부미용업닥터큐스킨케어전라남도 강진군 강진읍 신성길 24, 1층061-432-9493
177피부미용업최영재 약손전라남도 강진군 강진읍 보은로2길 30 (3층)061-432-9494
178피부미용업미스킨케어전라남도 강진군 강진읍 중앙로 91 (2층)061-433-7477
179피부미용업아름다운 피부전라남도 강진군 강진읍 보은로3길 34061-434-0234
180피부미용업미스킨앤바디전라남도 강진군 마량면 마량3길 36, 1층061-434-5402
181피부미용업피부愛물들다전라남도 강진군 강진읍 탐진로 74061-434-8225
182피부미용업서윤테라피전라남도 강진군 강진읍 삼일로 36, 2층 (천년예가)<NA>
183피부미용업BLANC skin&body(블랑)전라남도 강진군 마량면 마량5길 33, 101호 (남우천년예가)<NA>
184피부미용업플투레전라남도 강진군 강진읍 보은로2길 31<NA>
185피부미용업예지음에스테틱전라남도 강진군 강진읍 서성3길 21, 1층0507-1376-9400