Overview

Dataset statistics

Number of variables4
Number of observations76
Missing cells21
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory33.7 B

Variable types

Categorical1
Text3

Dataset

Description아산시 관내 위생관리용역업소 현황으로 업종명, 주소, 전화번호 등의 자료를 제공합니다.---------------------------------------
URLhttps://www.data.go.kr/data/3078526/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 21 (27.6%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:40:33.404287
Analysis finished2023-12-12 14:40:33.946709
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
건물위생관리업
76 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 76
100.0%

Length

2023-12-12T23:40:34.028806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:40:34.139847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 76
100.0%

업소명
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-12T23:40:34.422926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length12
Mean length7.3947368
Min length1

Characters and Unicode

Total characters562
Distinct characters161
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)100.0%

Sample

1st row애니크린
2nd row(주)청명환경시스템
3rd row대정위생관리용역
4th row(주)씨 월드
5th row(주)에이치티인력
ValueCountFrequency (%)
주식회사 12
 
12.8%
애니크린 1
 
1.1%
주)클린앤케어 1
 
1.1%
청소그룹 1
 
1.1%
동기산업 1
 
1.1%
창조크린 1
 
1.1%
주)다솜 1
 
1.1%
나눔다우리사회적협동조합 1
 
1.1%
에코플러스 1
 
1.1%
푸른청소 1
 
1.1%
Other values (73) 73
77.7%
2023-12-12T23:40:34.907818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 38
 
6.8%
) 28
 
5.0%
( 28
 
5.0%
스 20
 
3.6%
에 18
 
3.2%
18
 
3.2%
이 17
 
3.0%
사 16
 
2.8%
린 15
 
2.7%
회 14
 
2.5%
Other values (151) 350
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 456
81.1%
Close Punctuation 28
 
5.0%
Open Punctuation 28
 
5.0%
Lowercase Letter 23
 
4.1%
Space Separator 18
 
3.2%
Decimal Number 5
 
0.9%
Uppercase Letter 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 38
 
8.3%
스 20
 
4.4%
에 18
 
3.9%
이 17
 
3.7%
사 16
 
3.5%
린 15
 
3.3%
회 14
 
3.1%
식 12
 
2.6%
크 12
 
2.6%
리 11
 
2.4%
Other values (130) 283
62.1%
Lowercase Letter
ValueCountFrequency (%)
t 3
13.0%
m 3
13.0%
r 3
13.0%
a 3
13.0%
e 3
13.0%
p 2
8.7%
n 2
8.7%
y 1
 
4.3%
s 1
 
4.3%
o 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
O 1
25.0%
K 1
25.0%
R 1
25.0%
H 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
9 1
 
20.0%
2 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 456
81.1%
Common 79
 
14.1%
Latin 27
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 38
 
8.3%
스 20
 
4.4%
에 18
 
3.9%
이 17
 
3.7%
사 16
 
3.5%
린 15
 
3.3%
회 14
 
3.1%
식 12
 
2.6%
크 12
 
2.6%
리 11
 
2.4%
Other values (130) 283
62.1%
Latin
ValueCountFrequency (%)
t 3
11.1%
m 3
11.1%
r 3
11.1%
a 3
11.1%
e 3
11.1%
p 2
 
7.4%
n 2
 
7.4%
y 1
 
3.7%
s 1
 
3.7%
O 1
 
3.7%
Other values (5) 5
18.5%
Common
ValueCountFrequency (%)
) 28
35.4%
( 28
35.4%
18
22.8%
1 3
 
3.8%
9 1
 
1.3%
2 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 456
81.1%
ASCII 106
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 38
 
8.3%
스 20
 
4.4%
에 18
 
3.9%
이 17
 
3.7%
사 16
 
3.5%
린 15
 
3.3%
회 14
 
3.1%
식 12
 
2.6%
크 12
 
2.6%
리 11
 
2.4%
Other values (130) 283
62.1%
ASCII
ValueCountFrequency (%)
) 28
26.4%
( 28
26.4%
18
17.0%
t 3
 
2.8%
m 3
 
2.8%
1 3
 
2.8%
r 3
 
2.8%
a 3
 
2.8%
e 3
 
2.8%
p 2
 
1.9%
Other values (11) 12
11.3%

영업소 주소(도로명)
Text

Distinct74
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-12T23:40:35.196216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length30.026316
Min length20

Characters and Unicode

Total characters2282
Distinct characters129
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

Unique73 ?
Unique (%)96.1%

Sample

1st row충청남도 아산시 온여고길9번길 8-12 (용화동)
2nd row충청남도 아산시 탕정면 탕정면로 434
3rd row충청남도 아산시 권곡로 47, 301동 상가1호 (권곡동,더샾퍼스트@(1층))
4th row충청남도 아산시 음봉면 충무로 647, 2층 204호
5th row충청남도 아산시 남부로 312 (풍기동)
ValueCountFrequency (%)
충청남도 76
 
15.3%
아산시 76
 
15.3%
1층 39
 
7.9%
배방읍 16
 
3.2%
2층 12
 
2.4%
온천동 12
 
2.4%
용화동 7
 
1.4%
3층 7
 
1.4%
탕정면 6
 
1.2%
102호 6
 
1.2%
Other values (169) 239
48.2%
2023-12-12T23:40:35.662809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
420
 
18.4%
1 124
 
5.4%
2 83
 
3.6%
시 82
 
3.6%
충 81
 
3.5%
아 80
 
3.5%
산 80
 
3.5%
청 79
 
3.5%
남 79
 
3.5%
도 76
 
3.3%
Other values (119) 1098
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1237
54.2%
Decimal Number 422
 
18.5%
Space Separator 420
 
18.4%
Other Punctuation 71
 
3.1%
Open Punctuation 53
 
2.3%
Close Punctuation 53
 
2.3%
Dash Punctuation 22
 
1.0%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 82
 
6.6%
충 81
 
6.5%
아 80
 
6.5%
산 80
 
6.5%
청 79
 
6.4%
남 79
 
6.4%
도 76
 
6.1%
로 68
 
5.5%
층 67
 
5.4%
동 56
 
4.5%
Other values (102) 489
39.5%
Decimal Number
ValueCountFrequency (%)
1 124
29.4%
2 83
19.7%
0 46
 
10.9%
4 45
 
10.7%
3 39
 
9.2%
6 23
 
5.5%
7 22
 
5.2%
8 14
 
3.3%
9 14
 
3.3%
5 12
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 70
98.6%
@ 1
 
1.4%
Space Separator
ValueCountFrequency (%)
420
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1237
54.2%
Common 1041
45.6%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 82
 
6.6%
충 81
 
6.5%
아 80
 
6.5%
산 80
 
6.5%
청 79
 
6.4%
남 79
 
6.4%
도 76
 
6.1%
로 68
 
5.5%
층 67
 
5.4%
동 56
 
4.5%
Other values (102) 489
39.5%
Common
ValueCountFrequency (%)
420
40.3%
1 124
 
11.9%
2 83
 
8.0%
, 70
 
6.7%
( 53
 
5.1%
) 53
 
5.1%
0 46
 
4.4%
4 45
 
4.3%
3 39
 
3.7%
6 23
 
2.2%
Other values (6) 85
 
8.2%
Latin
ValueCountFrequency (%)
A 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1237
54.2%
ASCII 1045
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
420
40.2%
1 124
 
11.9%
2 83
 
7.9%
, 70
 
6.7%
( 53
 
5.1%
) 53
 
5.1%
0 46
 
4.4%
4 45
 
4.3%
3 39
 
3.7%
6 23
 
2.2%
Other values (7) 89
 
8.5%
Hangul
ValueCountFrequency (%)
시 82
 
6.6%
충 81
 
6.5%
아 80
 
6.5%
산 80
 
6.5%
청 79
 
6.4%
남 79
 
6.4%
도 76
 
6.1%
로 68
 
5.5%
층 67
 
5.4%
동 56
 
4.5%
Other values (102) 489
39.5%

소재지전화
Text

MISSING 

Distinct55
Distinct (%)100.0%
Missing21
Missing (%)27.6%
Memory size740.0 B
2023-12-12T23:40:35.959328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length9

Characters and Unicode

Total characters660
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

Unique55 ?
Unique (%)100.0%

Sample

1st row041-531-7731
2nd row041-542-8032
3rd row041-549-4905
4th row041-547-7226
5th row041-547-8884
ValueCountFrequency (%)
041-531-7731 1
 
1.8%
041-424-0016 1
 
1.8%
041-546-1814 1
 
1.8%
041-546-5660 1
 
1.8%
041-533-6300 1
 
1.8%
031-433-9770 1
 
1.8%
041-545-7536 1
 
1.8%
041-543-2757 1
 
1.8%
041-544-3400 1
 
1.8%
041-560-3956 1
 
1.8%
Other values (45) 45
81.8%
2023-12-12T23:40:36.398914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 117
17.7%
- 109
16.5%
0 102
15.5%
1 80
12.1%
5 77
11.7%
3 45
 
6.8%
2 29
 
4.4%
7 28
 
4.2%
9 26
 
3.9%
6 24
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 551
83.5%
Dash Punctuation 109
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 117
21.2%
0 102
18.5%
1 80
14.5%
5 77
14.0%
3 45
 
8.2%
2 29
 
5.3%
7 28
 
5.1%
9 26
 
4.7%
6 24
 
4.4%
8 23
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 117
17.7%
- 109
16.5%
0 102
15.5%
1 80
12.1%
5 77
11.7%
3 45
 
6.8%
2 29
 
4.4%
7 28
 
4.2%
9 26
 
3.9%
6 24
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 117
17.7%
- 109
16.5%
0 102
15.5%
1 80
12.1%
5 77
11.7%
3 45
 
6.8%
2 29
 
4.4%
7 28
 
4.2%
9 26
 
3.9%
6 24
 
3.6%

Correlations

2023-12-12T23:40:36.546895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화
업소명1.0001.0001.000
영업소 주소(도로명)1.0001.0001.000
소재지전화1.0001.0001.000

Missing values

2023-12-12T23:40:33.798409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:40:33.902848image/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
0건물위생관리업애니크린충청남도 아산시 온여고길9번길 8-12 (용화동)041-531-7731
1건물위생관리업(주)청명환경시스템충청남도 아산시 탕정면 탕정면로 434041-542-8032
2건물위생관리업대정위생관리용역충청남도 아산시 권곡로 47, 301동 상가1호 (권곡동,더샾퍼스트@(1층))041-549-4905
3건물위생관리업(주)씨 월드충청남도 아산시 음봉면 충무로 647, 2층 204호041-547-7226
4건물위생관리업(주)에이치티인력충청남도 아산시 남부로 312 (풍기동)041-547-8884
5건물위생관리업주식회사 한빛티엠충청남도 아산시 배방읍 고불로 615041-547-6969
6건물위생관리업에버크린충청남도 아산시 온천대로 1120 (득산동)041-542-2352
7건물위생관리업(주)나너그린충청남도 아산시 시민로 415, 2층 (온천동)041-545-5004
8건물위생관리업(주)경진충청남도 아산시 온중로 60-3, 1층 101호 (용화동)041-549-0123
9건물위생관리업충무개발충청남도 아산시 삼동로 72 (모종동,(2층))041-534-4472
업종명업소명영업소 주소(도로명)소재지전화
66건물위생관리업스마일클린충청남도 아산시 탕정면 탕정면로 223, 1동 1층 102호 (태화오피스텔)<NA>
67건물위생관리업오케이크린(OK크린)충청남도 아산시 남부로 312, 2층 (풍기동)<NA>
68건물위생관리업퍼스트에코아산충청남도 아산시 음봉면 음봉로 807, 2층 203호041-532-3645
69건물위생관리업에스웜충청남도 아산시 탕정면 한들물빛2로 42, 402호041-533-1542
70건물위생관리업(주)중앙무인항공방역충청남도 아산시 배방읍 고불로 554, 1층<NA>
71건물위생관리업정원클린충청남도 아산시 둔포면 둔포중앙로 144, 3층<NA>
72건물위생관리업디엠코리아충청남도 아산시 탕정면 탕정면로 223, 1동 1층 103호 (태화오피스텔)031-332-1114
73건물위생관리업(주)홍윤충청남도 아산시 배방읍 광장로 177-10, 펜타폴리스 1층 102호041-540-7035
74건물위생관리업빛나라 광나라충청남도 아산시 번영로69번길 32-7, 1층 (온천동)<NA>
75건물위생관리업온양원도심 마을관리사회적협동조합충청남도 아산시 아산로 13-1, 1층 (온천동)<NA>