Overview

Dataset statistics

Number of variables5
Number of observations61
Missing cells0
Missing cells (%)0.0%
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

소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-13 11:50:34.388477
Analysis finished2024-03-13 11:50:34.961533
Duration0.57 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
2024-03-13T20:50:35.252796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.3770492
Min length4

Characters and Unicode

Total characters328
Distinct characters81
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 row119세탁소
2nd row귀공자세탁소
3rd row금강세탁소
4th row금강세탁소
5th row기신세탁소
ValueCountFrequency (%)
금강세탁소 2
 
3.2%
형제세탁소 2
 
3.2%
하나세탁소 1
 
1.6%
119세탁소 1
 
1.6%
조흥세탁소 1
 
1.6%
신광컴퓨터세탁소 1
 
1.6%
신성세탁소 1
 
1.6%
아주세탁 1
 
1.6%
에덴세탁소 1
 
1.6%
연산새소망세탁 1
 
1.6%
Other values (50) 50
80.6%
2024-03-13T20:50:35.724891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 57
17.4%
탁 55
16.8%
소 43
 
13.1%
산 9
 
2.7%
대 8
 
2.4%
부 5
 
1.5%
광 5
 
1.5%
동 5
 
1.5%
신 5
 
1.5%
미 4
 
1.2%
Other values (71) 132
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
98.8%
Decimal Number 3
 
0.9%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 57
17.6%
탁 55
17.0%
소 43
 
13.3%
산 9
 
2.8%
대 8
 
2.5%
부 5
 
1.5%
광 5
 
1.5%
동 5
 
1.5%
신 5
 
1.5%
미 4
 
1.2%
Other values (68) 128
39.5%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 324
98.8%
Common 4
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 57
17.6%
탁 55
17.0%
소 43
 
13.3%
산 9
 
2.8%
대 8
 
2.5%
부 5
 
1.5%
광 5
 
1.5%
동 5
 
1.5%
신 5
 
1.5%
미 4
 
1.2%
Other values (68) 128
39.5%
Common
ValueCountFrequency (%)
1 2
50.0%
9 1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 324
98.8%
ASCII 4
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 57
17.6%
탁 55
17.0%
소 43
 
13.3%
산 9
 
2.8%
대 8
 
2.5%
부 5
 
1.5%
광 5
 
1.5%
동 5
 
1.5%
신 5
 
1.5%
미 4
 
1.2%
Other values (68) 128
39.5%
ASCII
ValueCountFrequency (%)
1 2
50.0%
9 1
25.0%
1
25.0%

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 row은진면
2nd row강경읍
3rd row취암동
4th row강경읍
5th row강경읍

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

2024-03-13T20:50:35.892847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:36.035612image/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
2024-03-13T20:50:36.324344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.967213
Min length14

Characters and Unicode

Total characters1218
Distinct characters64
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 은진면 대학로 144
2nd row충청남도 논산시 강경읍 옥녀봉로51번길 12
3rd row충청남도 논산시 관촉로 274-1
4th row충청남도 논산시 강경읍 잣디길 13-2
5th row충청남도 논산시 강경읍 황산길 5-2
ValueCountFrequency (%)
충청남도 61
22.7%
논산시 61
22.7%
강경읍 13
 
4.8%
연무읍 6
 
2.2%
시민로 5
 
1.9%
계백로 4
 
1.5%
해월로 3
 
1.1%
연산면 3
 
1.1%
5-1 2
 
0.7%
47 2
 
0.7%
Other values (95) 109
40.5%
2024-03-13T20:50:36.809909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
17.1%
시 72
 
5.9%
산 71
 
5.8%
논 63
 
5.2%
충 61
 
5.0%
남 61
 
5.0%
도 61
 
5.0%
청 61
 
5.0%
로 55
 
4.5%
1 48
 
3.9%
Other values (54) 457
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 745
61.2%
Decimal Number 240
 
19.7%
Space Separator 208
 
17.1%
Dash Punctuation 25
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 72
 
9.7%
산 71
 
9.5%
논 63
 
8.5%
충 61
 
8.2%
남 61
 
8.2%
도 61
 
8.2%
청 61
 
8.2%
로 55
 
7.4%
길 32
 
4.3%
번 26
 
3.5%
Other values (42) 182
24.4%
Decimal Number
ValueCountFrequency (%)
1 48
20.0%
2 31
12.9%
4 30
12.5%
5 25
10.4%
3 22
9.2%
9 20
8.3%
6 19
 
7.9%
8 18
 
7.5%
0 14
 
5.8%
7 13
 
5.4%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 745
61.2%
Common 473
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 72
 
9.7%
산 71
 
9.5%
논 63
 
8.5%
충 61
 
8.2%
남 61
 
8.2%
도 61
 
8.2%
청 61
 
8.2%
로 55
 
7.4%
길 32
 
4.3%
번 26
 
3.5%
Other values (42) 182
24.4%
Common
ValueCountFrequency (%)
208
44.0%
1 48
 
10.1%
2 31
 
6.6%
4 30
 
6.3%
5 25
 
5.3%
- 25
 
5.3%
3 22
 
4.7%
9 20
 
4.2%
6 19
 
4.0%
8 18
 
3.8%
Other values (2) 27
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 745
61.2%
ASCII 473
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
44.0%
1 48
 
10.1%
2 31
 
6.6%
4 30
 
6.3%
5 25
 
5.3%
- 25
 
5.3%
3 22
 
4.7%
9 20
 
4.2%
6 19
 
4.0%
8 18
 
3.8%
Other values (2) 27
 
5.7%
Hangul
ValueCountFrequency (%)
시 72
 
9.7%
산 71
 
9.5%
논 63
 
8.5%
충 61
 
8.2%
남 61
 
8.2%
도 61
 
8.2%
청 61
 
8.2%
로 55
 
7.4%
길 32
 
4.3%
번 26
 
3.5%
Other values (42) 182
24.4%

소재지지번주소
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-13T20:50:37.104314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length18.885246
Min length15

Characters and Unicode

Total characters1152
Distinct characters57
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 은진면 와야리 128-7
2nd row충청남도 논산시 강경읍 중앙리 19-3
3rd row충청남도 논산시 취암동 1037-5
4th row충청남도 논산시 강경읍 산양리 255-3
5th row충청남도 논산시 강경읍 대흥리 52-11
ValueCountFrequency (%)
충청남도 61
22.6%
논산시 61
22.6%
강경읍 13
 
4.8%
취암동 12
 
4.4%
화지동 7
 
2.6%
내동 7
 
2.6%
대흥리 6
 
2.2%
연무읍 6
 
2.2%
부창동 3
 
1.1%
반월동 3
 
1.1%
Other values (78) 91
33.7%
2024-03-13T20:50:37.714068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
209
18.1%
산 75
 
6.5%
충 61
 
5.3%
남 61
 
5.3%
도 61
 
5.3%
논 61
 
5.3%
시 61
 
5.3%
청 61
 
5.3%
- 46
 
4.0%
1 40
 
3.5%
Other values (47) 416
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 679
58.9%
Decimal Number 218
 
18.9%
Space Separator 209
 
18.1%
Dash Punctuation 46
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 75
11.0%
충 61
 
9.0%
남 61
 
9.0%
도 61
 
9.0%
논 61
 
9.0%
시 61
 
9.0%
청 61
 
9.0%
동 38
 
5.6%
리 25
 
3.7%
읍 19
 
2.8%
Other values (35) 156
23.0%
Decimal Number
ValueCountFrequency (%)
1 40
18.3%
3 31
14.2%
2 25
11.5%
5 23
10.6%
9 23
10.6%
4 22
10.1%
8 16
 
7.3%
6 15
 
6.9%
0 14
 
6.4%
7 9
 
4.1%
Space Separator
ValueCountFrequency (%)
209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 679
58.9%
Common 473
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 75
11.0%
충 61
 
9.0%
남 61
 
9.0%
도 61
 
9.0%
논 61
 
9.0%
시 61
 
9.0%
청 61
 
9.0%
동 38
 
5.6%
리 25
 
3.7%
읍 19
 
2.8%
Other values (35) 156
23.0%
Common
ValueCountFrequency (%)
209
44.2%
- 46
 
9.7%
1 40
 
8.5%
3 31
 
6.6%
2 25
 
5.3%
5 23
 
4.9%
9 23
 
4.9%
4 22
 
4.7%
8 16
 
3.4%
6 15
 
3.2%
Other values (2) 23
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 679
58.9%
ASCII 473
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
209
44.2%
- 46
 
9.7%
1 40
 
8.5%
3 31
 
6.6%
2 25
 
5.3%
5 23
 
4.9%
9 23
 
4.9%
4 22
 
4.7%
8 16
 
3.4%
6 15
 
3.2%
Other values (2) 23
 
4.9%
Hangul
ValueCountFrequency (%)
산 75
11.0%
충 61
 
9.0%
남 61
 
9.0%
도 61
 
9.0%
논 61
 
9.0%
시 61
 
9.0%
청 61
 
9.0%
동 38
 
5.6%
리 25
 
3.7%
읍 19
 
2.8%
Other values (35) 156
23.0%

전화번호
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-13T20:50:37.981773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters732
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

Unique61 ?
Unique (%)100.0%

Sample

1st row041-741-0129
2nd row041-745-7227
3rd row041-732-0885
4th row041-745-0430
5th row041-745-1728
ValueCountFrequency (%)
041-741-0129 1
 
1.6%
041-741-8312 1
 
1.6%
041-732-1610 1
 
1.6%
041-745-1359 1
 
1.6%
041-732-0056 1
 
1.6%
041-732-1772 1
 
1.6%
041-735-7995 1
 
1.6%
041-733-0137 1
 
1.6%
041-735-4065 1
 
1.6%
041-736-8285 1
 
1.6%
Other values (51) 51
83.6%
2024-03-13T20:50:38.408666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.7%
4 107
14.6%
1 95
13.0%
0 93
12.7%
7 82
11.2%
3 66
9.0%
5 57
7.8%
2 38
 
5.2%
6 32
 
4.4%
9 20
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 610
83.3%
Dash Punctuation 122
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 107
17.5%
1 95
15.6%
0 93
15.2%
7 82
13.4%
3 66
10.8%
5 57
9.3%
2 38
 
6.2%
6 32
 
5.2%
9 20
 
3.3%
8 20
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.7%
4 107
14.6%
1 95
13.0%
0 93
12.7%
7 82
11.2%
3 66
9.0%
5 57
7.8%
2 38
 
5.2%
6 32
 
4.4%
9 20
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.7%
4 107
14.6%
1 95
13.0%
0 93
12.7%
7 82
11.2%
3 66
9.0%
5 57
7.8%
2 38
 
5.2%
6 32
 
4.4%
9 20
 
2.7%

Correlations

2024-03-13T20:50:38.881063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명행정동소재지도로명주소소재지지번주소전화번호
업소명1.0000.0001.0001.0001.000
행정동0.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-03-13T20:50:34.765834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:50:34.892751image/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

업소명행정동소재지도로명주소소재지지번주소전화번호
0119세탁소은진면충청남도 논산시 은진면 대학로 144충청남도 논산시 은진면 와야리 128-7041-741-0129
1귀공자세탁소강경읍충청남도 논산시 강경읍 옥녀봉로51번길 12충청남도 논산시 강경읍 중앙리 19-3041-745-7227
2금강세탁소취암동충청남도 논산시 관촉로 274-1충청남도 논산시 취암동 1037-5041-732-0885
3금강세탁소강경읍충청남도 논산시 강경읍 잣디길 13-2충청남도 논산시 강경읍 산양리 255-3041-745-0430
4기신세탁소강경읍충청남도 논산시 강경읍 황산길 5-2충청남도 논산시 강경읍 대흥리 52-11041-745-1728
5나래세탁소취암동충청남도 논산시 논산대로348번길 7충청남도 논산시 취암동 95041-735-3019
6남양세탁소취암동충청남도 논산시 시민로 318충청남도 논산시 취암동 460-8041-736-0751
7내동세탁나라취암동충청남도 논산시 시민로194번길 23충청남도 논산시 내동 805041-736-0119
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