Overview

Dataset statistics

Number of variables6
Number of observations60
Missing cells2
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory50.2 B

Variable types

Text4
Categorical2

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

기준일자 has constant value ""Constant
전화 has 2 (3.3%) missing valuesMissing
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 11:50:18.492843
Analysis finished2024-03-13 11:50:19.086620
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct58
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-13T20:50:19.353601image/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%
2024-03-13T20:50:19.900974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
17.0%
54
16.4%
47
 
14.2%
8
 
2.4%
7
 
2.1%
6
 
1.8%
5
 
1.5%
5
 
1.5%
4
 
1.2%
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 (%)
56
17.3%
54
16.7%
47
 
14.6%
8
 
2.5%
7
 
2.2%
6
 
1.9%
5
 
1.5%
5
 
1.5%
4
 
1.2%
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 (%)
56
17.3%
54
16.7%
47
 
14.6%
8
 
2.5%
7
 
2.2%
6
 
1.9%
5
 
1.5%
5
 
1.5%
4
 
1.2%
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 (%)
56
17.3%
54
16.7%
47
 
14.6%
8
 
2.5%
7
 
2.2%
6
 
1.9%
5
 
1.5%
5
 
1.5%
4
 
1.2%
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
연무읍
연산면
Other values (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

2024-03-13T20:50:20.087982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:20.245366image/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%
Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-13T20:50:20.544061image/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%
2024-03-13T20:50:21.001710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
17.2%
73
 
5.1%
71
 
5.0%
62
 
4.3%
60
 
4.2%
60
 
4.2%
60
 
4.2%
60
 
4.2%
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 (%)
73
 
8.6%
71
 
8.4%
62
 
7.3%
60
 
7.1%
60
 
7.1%
60
 
7.1%
60
 
7.1%
54
 
6.4%
36
 
4.3%
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 (%)
73
 
8.6%
71
 
8.4%
62
 
7.3%
60
 
7.1%
60
 
7.1%
60
 
7.1%
60
 
7.1%
54
 
6.4%
36
 
4.3%
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 (%)
73
 
8.6%
71
 
8.4%
62
 
7.3%
60
 
7.1%
60
 
7.1%
60
 
7.1%
60
 
7.1%
54
 
6.4%
36
 
4.3%
30
 
3.6%
Other values (64) 278
32.9%
Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-13T20:50:21.289402image/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%
2024-03-13T20:50:21.742939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/