Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory42.2 B

Variable types

Text4
Categorical1

Dataset

Description충청남도 논산시 세탁업에 대한 데이터로 업소명, 행정동, 소재지도로명주소, 소재지지번주소, 전화번호 정보를 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=390&beforeMenuCd=DOM_000000201001001000&publicdatapk=15054219

Alerts

전화 has 2 (3.3%) missing valuesMissing
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 11:50:07.960558
Analysis finished2024-03-13 11:50:08.863996
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct58
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-13T20:50:09.123386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.5
Min length4

Characters and Unicode

Total characters330
Distinct characters86
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)93.3%

Sample

1st row창영기계세탁
2nd row대창세탁소
3rd row세광세탁소
4th row부산컴퓨터세탁소
5th row신광세탁소
ValueCountFrequency (%)
형제세탁소 2
 
3.1%
금강세탁소 2
 
3.1%
내동세탁나라 1
 
1.6%
창영기계세탁 1
 
1.6%
하나세탁소 1
 
1.6%
부광세탁소 1
 
1.6%
아주세탁소 1
 
1.6%
동신세탁소 1
 
1.6%
조흥세탁소 1
 
1.6%
귀공자세탁소 1
 
1.6%
Other values (52) 52
81.2%
2024-03-13T20:50:09.590594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 56
17.0%
탁 54
16.4%
소 47
 
14.2%
대 8
 
2.4%
산 7
 
2.1%
신 6
 
1.8%
동 5
 
1.5%
광 5
 
1.5%
사 4
 
1.2%
부 4
 
1.2%
Other values (76) 134
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
97.9%
Space Separator 4
 
1.2%
Decimal Number 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 56
17.3%
탁 54
16.7%
소 47
 
14.6%
대 8
 
2.5%
산 7
 
2.2%
신 6
 
1.9%
동 5
 
1.5%
광 5
 
1.5%
사 4
 
1.2%
부 4
 
1.2%
Other values (73) 127
39.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
97.9%
Common 7
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 56
17.3%
탁 54
16.7%
소 47
 
14.6%
대 8
 
2.5%
산 7
 
2.2%
신 6
 
1.9%
동 5
 
1.5%
광 5
 
1.5%
사 4
 
1.2%
부 4
 
1.2%
Other values (73) 127
39.3%
Common
ValueCountFrequency (%)
4
57.1%
1 2
28.6%
9 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
97.9%
ASCII 7
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 56
17.3%
탁 54
16.7%
소 47
 
14.6%
대 8
 
2.5%
산 7
 
2.2%
신 6
 
1.9%
동 5
 
1.5%
광 5
 
1.5%
사 4
 
1.2%
부 4
 
1.2%
Other values (73) 127
39.3%
ASCII
ValueCountFrequency (%)
4
57.1%
1 2
28.6%
9 1
 
14.3%

행정동
Categorical

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
취암동
28 
강경읍
13 
부창동
7 
연무읍
6 
연산면
3 
Other values (3)
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
취암동 28
46.7%
강경읍 13
21.7%
부창동 7
 
11.7%
연무읍 6
 
10.0%
연산면 3
 
5.0%
양촌면 1
 
1.7%
은진면 1
 
1.7%
노성면 1
 
1.7%

Length

2024-03-13T20:50:09.772843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:09.912693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취암동 28
46.7%
강경읍 13
21.7%
부창동 7
 
11.7%
연무읍 6
 
10.0%
연산면 3
 
5.0%
양촌면 1
 
1.7%
은진면 1
 
1.7%
노성면 1
 
1.7%

소재지도로명주소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-13T20:50:10.251727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length23.866667
Min length19

Characters and Unicode

Total characters1432
Distinct characters89
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row충청남도 논산시 시민로 344 (취암동)
2nd row충청남도 논산시 시민로360번길 12-1 (취암동)
3rd row충청남도 논산시 관촉로 268 (취암동)
4th row충청남도 논산시 해월로179번길 14 (화지동)
5th row충청남도 논산시 중앙로492번길 15 (화지동)
ValueCountFrequency (%)
충청남도 60
19.5%
논산시 60
19.5%
강경읍 13
 
4.2%
취암동 10
 
3.3%
내동 8
 
2.6%
화지동 7
 
2.3%
연무읍 6
 
2.0%
시민로 5
 
1.6%
계백로 4
 
1.3%
1층 4
 
1.3%
Other values (107) 130
42.3%
2024-03-13T20:50:10.777610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
17.2%
산 73
 
5.1%
시 71
 
5.0%
논 62
 
4.3%
충 60
 
4.2%
청 60
 
4.2%
남 60
 
4.2%
도 60
 
4.2%
로 54
 
3.8%
1 50
 
3.5%
Other values (79) 635
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 844
58.9%
Space Separator 247
 
17.2%
Decimal Number 242
 
16.9%
Open Punctuation 35
 
2.4%
Close Punctuation 35
 
2.4%
Dash Punctuation 22
 
1.5%
Other Punctuation 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 73
 
8.6%
시 71
 
8.4%
논 62
 
7.3%
충 60
 
7.1%
청 60
 
7.1%
남 60
 
7.1%
도 60
 
7.1%
로 54
 
6.4%
동 36
 
4.3%
길 30
 
3.6%
Other values (64) 278
32.9%
Decimal Number
ValueCountFrequency (%)
1 50
20.7%
2 34
14.0%
4 30
12.4%
5 23
9.5%
0 19
 
7.9%
3 19
 
7.9%
6 19
 
7.9%
8 17
 
7.0%
7 16
 
6.6%
9 15
 
6.2%
Space Separator
ValueCountFrequency (%)
247
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 844
58.9%
Common 588
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 73
 
8.6%
시 71
 
8.4%
논 62
 
7.3%
충 60
 
7.1%
청 60
 
7.1%
남 60
 
7.1%
도 60
 
7.1%
로 54
 
6.4%
동 36
 
4.3%
길 30
 
3.6%
Other values (64) 278
32.9%
Common
ValueCountFrequency (%)
247
42.0%
1 50
 
8.5%
( 35
 
6.0%
) 35
 
6.0%
2 34
 
5.8%
4 30
 
5.1%
5 23
 
3.9%
- 22
 
3.7%
0 19
 
3.2%
3 19
 
3.2%
Other values (5) 74
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 844
58.9%
ASCII 588
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
42.0%
1 50
 
8.5%
( 35
 
6.0%
) 35
 
6.0%
2 34
 
5.8%
4 30
 
5.1%
5 23
 
3.9%
- 22
 
3.7%
0 19
 
3.2%
3 19
 
3.2%
Other values (5) 74
 
12.6%
Hangul
ValueCountFrequency (%)
산 73
 
8.6%
시 71
 
8.4%
논 62
 
7.3%
충 60
 
7.1%
청 60
 
7.1%
남 60
 
7.1%
도 60
 
7.1%
로 54
 
6.4%
동 36
 
4.3%
길 30
 
3.6%
Other values (64) 278
32.9%

소재지지번주소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-13T20:50:11.136618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length27
Mean length21.716667
Min length16

Characters and Unicode

Total characters1303
Distinct characters78
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

Unique60 ?
Unique (%)100.0%

Sample

1st row충청남도 논산시 취암동 444-10
2nd row충청남도 논산시 취암동 370-13
3rd row충청남도 논산시 취암동 296-28 다동 7호
4th row충청남도 논산시 화지동 54
5th row충청남도 논산시 화지동 45-5
ValueCountFrequency (%)
충청남도 60
21.0%
논산시 60
21.0%
강경읍 13
 
4.5%
취암동 10
 
3.5%
내동 8
 
2.8%
화지동 7
 
2.4%
연무읍 6
 
2.1%
대흥리 5
 
1.7%
연산면 3
 
1.0%
연산리 3
 
1.0%
Other values (99) 111
38.8%
2024-03-13T20:50:11.664055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
280
21.5%
산 77
 
5.9%
남 61
 
4.7%
논 61
 
4.7%
청 61
 
4.7%
충 60
 
4.6%
도 60
 
4.6%
시 60
 
4.6%
1 46
 
3.5%
- 45
 
3.5%
Other values (68) 492
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 732
56.2%
Space Separator 280
 
21.5%
Decimal Number 246
 
18.9%
Dash Punctuation 45
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 77
 
10.5%
남 61
 
8.3%
논 61
 
8.3%
청 61
 
8.3%
충 60
 
8.2%
도 60
 
8.2%
시 60
 
8.2%
동 41
 
5.6%
리 25
 
3.4%
읍 19
 
2.6%
Other values (56) 207
28.3%
Decimal Number
ValueCountFrequency (%)
1 46
18.7%
2 33
13.4%
3 30
12.2%
4 24
9.8%
9 23
9.3%
5 23
9.3%
0 22
8.9%
8 17
 
6.9%
6 14
 
5.7%
7 14
 
5.7%
Space Separator
ValueCountFrequency (%)
280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 732
56.2%
Common 571
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 77
 
10.5%
남 61
 
8.3%
논 61
 
8.3%
청 61
 
8.3%
충 60
 
8.2%
도 60
 
8.2%
시 60
 
8.2%
동 41
 
5.6%
리 25
 
3.4%
읍 19
 
2.6%
Other values (56) 207
28.3%
Common
ValueCountFrequency (%)
280
49.0%
1 46
 
8.1%
- 45
 
7.9%
2 33
 
5.8%
3 30
 
5.3%
4 24
 
4.2%
9 23
 
4.0%
5 23
 
4.0%
0 22
 
3.9%
8 17
 
3.0%
Other values (2) 28
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 732
56.2%
ASCII 571
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
280
49.0%
1 46
 
8.1%
- 45
 
7.9%
2 33
 
5.8%
3 30
 
5.3%
4 24
 
4.2%
9 23
 
4.0%
5 23
 
4.0%
0 22
 
3.9%
8 17
 
3.0%
Other values (2) 28
 
4.9%
Hangul
ValueCountFrequency (%)
산 77
 
10.5%
남 61
 
8.3%
논 61
 
8.3%
청 61
 
8.3%
충 60
 
8.2%
도 60
 
8.2%
시 60
 
8.2%
동 41
 
5.6%
리 25
 
3.4%
읍 19
 
2.6%
Other values (56) 207
28.3%

전화
Text

MISSING 

Distinct58
Distinct (%)100.0%
Missing2
Missing (%)3.3%
Memory size612.0 B
2024-03-13T20:50:11.976442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters696
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

Unique58 ?
Unique (%)100.0%

Sample

1st row041-732-3440
2nd row041-735-6496
3rd row041-735-7046
4th row041-732-0320
5th row041-732-1610
ValueCountFrequency (%)
041-735-2605 1
 
1.7%
041-733-6530 1
 
1.7%
041-745-0430 1
 
1.7%
041-735-9261 1
 
1.7%
041-732-0056 1
 
1.7%
041-741-8466 1
 
1.7%
041-736-4276 1
 
1.7%
041-745-6668 1
 
1.7%
041-745-7227 1
 
1.7%
041-735-3713 1
 
1.7%
Other values (48) 48
82.8%
2024-03-13T20:50:12.520995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 116
16.7%
4 101
14.5%
1 92
13.2%
0 90
12.9%
7 79
11.4%
3 65
9.3%
5 51
7.3%
2 33
 
4.7%
6 30
 
4.3%
9 22
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 580
83.3%
Dash Punctuation 116
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 101
17.4%
1 92
15.9%
0 90
15.5%
7 79
13.6%
3 65
11.2%
5 51
8.8%
2 33
 
5.7%
6 30
 
5.2%
9 22
 
3.8%
8 17
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 696
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 116
16.7%
4 101
14.5%
1 92
13.2%
0 90
12.9%
7 79
11.4%
3 65
9.3%
5 51
7.3%
2 33
 
4.7%
6 30
 
4.3%
9 22
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 116
16.7%
4 101
14.5%
1 92
13.2%
0 90
12.9%
7 79
11.4%
3 65
9.3%
5 51
7.3%
2 33
 
4.7%
6 30
 
4.3%
9 22
 
3.2%

Correlations

2024-03-13T20:50:12.629078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명행정동소재지도로명주소소재지지번주소전화
업소명1.0000.0001.0001.0001.000
행정동0.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.000
전화1.0001.0001.0001.0001.000

Missing values

2024-03-13T20:50:08.678061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:50:08.803515image/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

업소명행정동소재지도로명주소소재지지번주소전화
0창영기계세탁취암동충청남도 논산시 시민로 344 (취암동)충청남도 논산시 취암동 444-10041-732-3440
1대창세탁소취암동충청남도 논산시 시민로360번길 12-1 (취암동)충청남도 논산시 취암동 370-13041-735-6496
2세광세탁소취암동충청남도 논산시 관촉로 268 (취암동)충청남도 논산시 취암동 296-28 다동 7호041-735-7046
3부산컴퓨터세탁소취암동충청남도 논산시 해월로179번길 14 (화지동)충청남도 논산시 화지동 54041-732-0320
4신광세탁소취암동충청남도 논산시 중앙로492번길 15 (화지동)충청남도 논산시 화지동 45-5041-732-1610
5리벤하임세탁취암동충청남도 논산시 대학로65번길 46, 201호 (내동, 상가동)충청남도 논산시 내동 1113 상가동 201호041-742-0445
6시온세탁소연무읍충청남도 논산시 연무읍 안심로 137, 1층충청남도 논산시 연무읍 안심리 1-94041-741-3669
7백양세탁소강경읍충청남도 논산시 강경읍 계백로167번길 37충청남도 논산시 강경읍 태평리 12-15041-745-5913
8현대세탁소강경읍충청남도 논산시 강경읍 계백로167번길 61-2충청남도 논산시 강경읍 서창리 20-13041-745-0820
9대광세탁소강경읍충청남도 논산시 강경읍 옥녀봉로 58충청남도 논산시 강경읍 중앙리 1-3041-745-4430
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50클린케이운동화빨래방취암동충청남도 논산시 시민로 315-1 (취암동)충청남도 논산시 취암동 990041-734-3931
51클린케이세탁 논산내동점취암동충청남도 논산시 시민로 271 (내동)충청남도 논산시 내동 314-4041-735-8283
52연산새소망세탁연산면충청남도 논산시 연산면 연산1길 5-1충청남도 논산시 연산면 연산리 492041-735-7995
53주식회사 중부크린산업강경읍충청남도 논산시 강경읍 계백로 184충청남도 논산시 강경읍 남교리 63-2041-742-8200
54영창세탁소취암동충청남도 논산시 시민로258번길 12, 제이파크아파트상가 (내동)충청남도 논산시 내동 272-7 제이파크아파트상가041-735-4065
55엘지엘주식회사연무읍충청남도 논산시 연무읍 감바위로 20충청남도 논산시 연무읍 양지리 531-3<NA>
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58빛나는 세탁부창동충청남도 논산시 부창로100번길 19-2, 1층 (강산동)충청남도 논산시 강산동 570041-734-5859
59신일상사노성면충청남도 논산시 노성면 노성로 430충청남도 논산시 노성면 송당리 산 23-8041-735-7961