Overview

Dataset statistics

Number of variables5
Number of observations61
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 11:50:29.516039
Analysis finished2024-03-13 11:50:30.071417
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct59
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-13T20:50:30.285451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.5901639
Min length4

Characters and Unicode

Total characters341
Distinct characters89
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

Unique57 ?
Unique (%)93.4%

Sample

1st row창영기계세탁
2nd row대창세탁소
3rd row세광세탁소
4th row부산컴퓨터세탁소
5th row신광세탁소
ValueCountFrequency (%)
형제세탁소 2
 
3.1%
금강세탁소 2
 
3.1%
영창세탁소 1
 
1.5%
중부크린산업 1
 
1.5%
창영기계세탁 1
 
1.5%
중앙라사 1
 
1.5%
세탁소 1
 
1.5%
부광세탁소 1
 
1.5%
아주세탁소 1
 
1.5%
동신세탁소 1
 
1.5%
Other values (53) 53
81.5%
2024-03-13T20:50:30.896806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 58
17.0%
탁 56
16.4%
소 49
 
14.4%
대 8
 
2.3%
산 7
 
2.1%
동 6
 
1.8%
부 5
 
1.5%
광 5
 
1.5%
신 5
 
1.5%
주 4
 
1.2%
Other values (79) 138
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 334
97.9%
Space Separator 4
 
1.2%
Decimal Number 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 58
17.4%
탁 56
16.8%
소 49
 
14.7%
대 8
 
2.4%
산 7
 
2.1%
동 6
 
1.8%
부 5
 
1.5%
광 5
 
1.5%
신 5
 
1.5%
주 4
 
1.2%
Other values (76) 131
39.2%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 334
97.9%
Common 7
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 58
17.4%
탁 56
16.8%
소 49
 
14.7%
대 8
 
2.4%
산 7
 
2.1%
동 6
 
1.8%
부 5
 
1.5%
광 5
 
1.5%
신 5
 
1.5%
주 4
 
1.2%
Other values (76) 131
39.2%
Common
ValueCountFrequency (%)
4
57.1%
1 2
28.6%
9 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 334
97.9%
ASCII 7
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 58
17.4%
탁 56
16.8%
소 49
 
14.7%
대 8
 
2.4%
산 7
 
2.1%
동 6
 
1.8%
부 5
 
1.5%
광 5
 
1.5%
신 5
 
1.5%
주 4
 
1.2%
Other values (76) 131
39.2%
ASCII
ValueCountFrequency (%)
4
57.1%
1 2
28.6%
9 1
 
14.3%

행정동
Categorical

Distinct7
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size620.0 B
취암동
29 
강경읍
13 
부창동
7 
연무읍
6 
연산면
3 
Other values (2)
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
취암동 29
47.5%
강경읍 13
21.3%
부창동 7
 
11.5%
연무읍 6
 
9.8%
연산면 3
 
4.9%
양촌면 2
 
3.3%
은진면 1
 
1.6%

Length

2024-03-13T20:50:31.043407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:31.172405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취암동 29
47.5%
강경읍 13
21.3%
부창동 7
 
11.5%
연무읍 6
 
9.8%
연산면 3
 
4.9%
양촌면 2
 
3.3%
은진면 1
 
1.6%

소재지도로명주소
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-13T20:50:31.496449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length23.704918
Min length19

Characters and Unicode

Total characters1446
Distinct characters86
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

Unique61 ?
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 61
19.8%
논산시 61
19.8%
강경읍 13
 
4.2%
취암동 11
 
3.6%
내동 8
 
2.6%
화지동 7
 
2.3%
연무읍 6
 
1.9%
시민로 5
 
1.6%
계백로 4
 
1.3%
해월로 3
 
1.0%
Other values (104) 129
41.9%
2024-03-13T20:50:31.995734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
17.1%
산 73
 
5.0%
시 73
 
5.0%
논 63
 
4.4%
충 61
 
4.2%
남 61
 
4.2%
도 61
 
4.2%
청 61
 
4.2%
로 55
 
3.8%
1 48
 
3.3%
Other values (76) 643
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 856
59.2%
Space Separator 247
 
17.1%
Decimal Number 244
 
16.9%
Close Punctuation 36
 
2.5%
Open Punctuation 36
 
2.5%
Dash Punctuation 24
 
1.7%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 73
 
8.5%
시 73
 
8.5%
논 63
 
7.4%
충 61
 
7.1%
남 61
 
7.1%
도 61
 
7.1%
청 61
 
7.1%
로 55
 
6.4%
동 37
 
4.3%
길 31
 
3.6%
Other values (61) 280
32.7%
Decimal Number
ValueCountFrequency (%)
1 48
19.7%
2 33
13.5%
4 31
12.7%
5 24
9.8%
6 20
8.2%
3 20
8.2%
9 19
 
7.8%
0 17
 
7.0%
8 17
 
7.0%
7 15
 
6.1%
Space Separator
ValueCountFrequency (%)
247
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 856
59.2%
Common 590
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 73
 
8.5%
시 73
 
8.5%
논 63
 
7.4%
충 61
 
7.1%
남 61
 
7.1%
도 61
 
7.1%
청 61
 
7.1%
로 55
 
6.4%
동 37
 
4.3%
길 31
 
3.6%
Other values (61) 280
32.7%
Common
ValueCountFrequency (%)
247
41.9%
1 48
 
8.1%
) 36
 
6.1%
( 36
 
6.1%
2 33
 
5.6%
4 31
 
5.3%
- 24
 
4.1%
5 24
 
4.1%
6 20
 
3.4%
3 20
 
3.4%
Other values (5) 71
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 856
59.2%
ASCII 590
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
41.9%
1 48
 
8.1%
) 36
 
6.1%
( 36
 
6.1%
2 33
 
5.6%
4 31
 
5.3%
- 24
 
4.1%
5 24
 
4.1%
6 20
 
3.4%
3 20
 
3.4%
Other values (5) 71
 
12.0%
Hangul
ValueCountFrequency (%)
산 73
 
8.5%
시 73
 
8.5%
논 63
 
7.4%
충 61
 
7.1%
남 61
 
7.1%
도 61
 
7.1%
청 61
 
7.1%
로 55
 
6.4%
동 37
 
4.3%
길 31
 
3.6%
Other values (61) 280
32.7%

소재지지번주소
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-13T20:50:32.304087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length24
Mean length21.672131
Min length17

Characters and Unicode

Total characters1322
Distinct characters65
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

Unique61 ?
Unique (%)100.0%

Sample

1st row충청남도 논산시 취암동 444-10번지
2nd row충청남도 논산시 취암동 370-13번지
3rd row충청남도 논산시 취암동 296-28번지
4th row충청남도 논산시 화지동 54번지
5th row충청남도 논산시 화지동 45-5번지
ValueCountFrequency (%)
충청남도 61
22.5%
논산시 61
22.5%
강경읍 13
 
4.8%
취암동 11
 
4.1%
내동 8
 
3.0%
화지동 7
 
2.6%
연무읍 6
 
2.2%
대흥리 6
 
2.2%
연산면 3
 
1.1%
부창동 3
 
1.1%
Other values (78) 92
33.9%
2024-03-13T20:50:32.862678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
18.7%
산 75
 
5.7%
지 69
 
5.2%
충 61
 
4.6%
남 61
 
4.6%
도 61
 
4.6%
논 61
 
4.6%
시 61
 
4.6%
청 61
 
4.6%
번 61
 
4.6%
Other values (55) 504
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 808
61.1%
Space Separator 247
 
18.7%
Decimal Number 223
 
16.9%
Dash Punctuation 44
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 75
 
9.3%
지 69
 
8.5%
충 61
 
7.5%
남 61
 
7.5%
도 61
 
7.5%
논 61
 
7.5%
시 61
 
7.5%
청 61
 
7.5%
번 61
 
7.5%
동 38
 
4.7%
Other values (43) 199
24.6%
Decimal Number
ValueCountFrequency (%)
1 41
18.4%
2 30
13.5%
3 28
12.6%
5 23
10.3%
9 22
9.9%
4 20
9.0%
6 16
 
7.2%
8 16
 
7.2%
0 15
 
6.7%
7 12
 
5.4%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 808
61.1%
Common 514
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 75
 
9.3%
지 69
 
8.5%
충 61
 
7.5%
남 61
 
7.5%
도 61
 
7.5%
논 61
 
7.5%
시 61
 
7.5%
청 61
 
7.5%
번 61
 
7.5%
동 38
 
4.7%
Other values (43) 199
24.6%
Common
ValueCountFrequency (%)
247
48.1%
- 44
 
8.6%
1 41
 
8.0%
2 30
 
5.8%
3 28
 
5.4%
5 23
 
4.5%
9 22
 
4.3%
4 20
 
3.9%
6 16
 
3.1%
8 16
 
3.1%
Other values (2) 27
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 808
61.1%
ASCII 514
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
48.1%
- 44
 
8.6%
1 41
 
8.0%
2 30
 
5.8%
3 28
 
5.4%
5 23
 
4.5%
9 22
 
4.3%
4 20
 
3.9%
6 16
 
3.1%
8 16
 
3.1%
Other values (2) 27
 
5.3%
Hangul
ValueCountFrequency (%)
산 75
 
9.3%
지 69
 
8.5%
충 61
 
7.5%
남 61
 
7.5%
도 61
 
7.5%
논 61
 
7.5%
시 61
 
7.5%
청 61
 
7.5%
번 61
 
7.5%
동 38
 
4.7%
Other values (43) 199
24.6%

전화
Text

MISSING 

Distinct59
Distinct (%)100.0%
Missing2
Missing (%)3.3%
Memory size620.0 B
2024-03-13T20:50:33.211993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters708
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

Unique59 ?
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 (%)
041-732-3440 1
 
1.7%
041-742-1189 1
 
1.7%
041-745-2524 1
 
1.7%
041-733-7712 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%
Other values (49) 49
83.1%
2024-03-13T20:50:33.631423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 118
16.7%
4 103
14.5%
1 92
13.0%
0 91
12.9%
7 79
11.2%
3 65
9.2%
5 53
7.5%
2 36
 
5.1%
6 31
 
4.4%
9 20
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 590
83.3%
Dash Punctuation 118
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 103
17.5%
1 92
15.6%
0 91
15.4%
7 79
13.4%
3 65
11.0%
5 53
9.0%
2 36
 
6.1%
6 31
 
5.3%
9 20
 
3.4%
8 20
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 708
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 118
16.7%
4 103
14.5%
1 92
13.0%
0 91
12.9%
7 79
11.2%
3 65
9.2%
5 53
7.5%
2 36
 
5.1%
6 31
 
4.4%
9 20
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 708
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 118
16.7%
4 103
14.5%
1 92
13.0%
0 91
12.9%
7 79
11.2%
3 65
9.2%
5 53
7.5%
2 36
 
5.1%
6 31
 
4.4%
9 20
 
2.8%

Correlations

2024-03-13T20:50:33.755131image/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

2024-03-13T20:50:29.901260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:50:30.025684image/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 444-10번지041-732-3440
1대창세탁소취암동충청남도 논산시 시민로360번길 12-1 (취암동)충청남도 논산시 취암동 370-13번지041-735-6496
2세광세탁소취암동충청남도 논산시 관촉로 268 (취암동)충청남도 논산시 취암동 296-28번지041-735-7046
3부산컴퓨터세탁소취암동충청남도 논산시 해월로179번길 14 (화지동)충청남도 논산시 화지동 54번지041-732-0320
4신광세탁소취암동충청남도 논산시 중앙로492번길 15 (화지동)충청남도 논산시 화지동 45-5번지041-732-1610
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