Overview

Dataset statistics

Number of variables6
Number of observations110
Missing cells19
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory50.2 B

Variable types

Text4
Categorical2

Dataset

Description1. 충청남도 홍성군에서 제공하는 대기배출시설 사업장 현황으로, 업체명, 도로명주소, 전화번호, 업종, 종별, 데이터기준일자로 구성되어 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=339&beforeMenuCd=DOM_000000201001001000&publicdatapk=15083590

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 19 (17.3%) missing valuesMissing

Reproduction

Analysis started2024-01-09 20:31:11.871424
Analysis finished2024-01-09 20:31:12.682384
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct109
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-01-10T05:31:12.848122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length141
Median length16
Mean length8.8909091
Min length3

Characters and Unicode

Total characters978
Distinct characters177
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)98.2%

Sample

1st row홍주정미소
2nd row홍성축산업협동조합배합사료공장
3rd row㈜한솔
4th row(유)태광타이어
5th row현대공업사
ValueCountFrequency (%)
원강금속㈜ 2
 
1.6%
홍성공장 2
 
1.6%
주식회사 2
 
1.6%
건강한사람들㈜ 2
 
1.6%
㈜수천중공업 1
 
0.8%
경원컴포싱㈜ 1
 
0.8%
㈜삼조생명과학 1
 
0.8%
㈜광일테크 1
 
0.8%
토임에이취에스티㈜ 1
 
0.8%
천마레미콘주식회사 1
 
0.8%
Other values (114) 114
89.1%
2024-01-10T05:31:13.192146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153
 
15.6%
㈜ 67
 
6.9%
업 35
 
3.6%
사 27
 
2.8%
공 21
 
2.1%
성 20
 
2.0%
홍 19
 
1.9%
스 16
 
1.6%
산 16
 
1.6%
농 15
 
1.5%
Other values (167) 589
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 738
75.5%
Space Separator 153
 
15.6%
Other Symbol 67
 
6.9%
Close Punctuation 8
 
0.8%
Open Punctuation 8
 
0.8%
Decimal Number 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 35
 
4.7%
사 27
 
3.7%
공 21
 
2.8%
성 20
 
2.7%
홍 19
 
2.6%
스 16
 
2.2%
산 16
 
2.2%
농 15
 
2.0%
동 14
 
1.9%
미 14
 
1.9%
Other values (161) 541
73.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
153
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 805
82.3%
Common 173
 
17.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 67
 
8.3%
업 35
 
4.3%
사 27
 
3.4%
공 21
 
2.6%
성 20
 
2.5%
홍 19
 
2.4%
스 16
 
2.0%
산 16
 
2.0%
농 15
 
1.9%
동 14
 
1.7%
Other values (162) 555
68.9%
Common
ValueCountFrequency (%)
153
88.4%
) 8
 
4.6%
( 8
 
4.6%
2 2
 
1.2%
1 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 738
75.5%
ASCII 173
 
17.7%
None 67
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
153
88.4%
) 8
 
4.6%
( 8
 
4.6%
2 2
 
1.2%
1 2
 
1.2%
None
ValueCountFrequency (%)
㈜ 67
100.0%
Hangul
ValueCountFrequency (%)
업 35
 
4.7%
사 27
 
3.7%
공 21
 
2.8%
성 20
 
2.7%
홍 19
 
2.6%
스 16
 
2.2%
산 16
 
2.2%
농 15
 
2.0%
동 14
 
1.9%
미 14
 
1.9%
Other values (161) 541
73.3%

도로명주소
Text

Distinct103
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-01-10T05:31:13.503630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.409091
Min length16

Characters and Unicode

Total characters2355
Distinct characters68
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)87.3%

Sample

1st row충남 홍성군 홍성읍 문화로 8
2nd row충남 홍성군 홍성읍 구항길 389
3rd row충남 홍성군 홍동면 광금남로 891
4th row충남 홍성군 결성면 홍남서로 651
5th row충남 홍성군 광천읍 광천로 185
ValueCountFrequency (%)
충남 110
19.9%
홍성군 110
19.9%
갈산면 23
 
4.2%
결성면 14
 
2.5%
금마면 14
 
2.5%
홍성읍 13
 
2.4%
은하면 12
 
2.2%
충서로 11
 
2.0%
구항면 10
 
1.8%
내포로 10
 
1.8%
Other values (161) 226
40.9%
2024-01-10T05:31:13.942160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
450
19.1%
홍 144
 
6.1%
성 140
 
5.9%
충 128
 
5.4%
1 125
 
5.3%
남 123
 
5.2%
군 110
 
4.7%
로 98
 
4.2%
면 82
 
3.5%
길 57
 
2.4%
Other values (58) 898
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1331
56.5%
Decimal Number 531
 
22.5%
Space Separator 450
 
19.1%
Dash Punctuation 41
 
1.7%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 144
 
10.8%
성 140
 
10.5%
충 128
 
9.6%
남 123
 
9.2%
군 110
 
8.3%
로 98
 
7.4%
면 82
 
6.2%
길 57
 
4.3%
번 47
 
3.5%
산 41
 
3.1%
Other values (44) 361
27.1%
Decimal Number
ValueCountFrequency (%)
1 125
23.5%
2 57
10.7%
6 55
10.4%
4 54
10.2%
3 51
9.6%
8 43
 
8.1%
0 42
 
7.9%
5 40
 
7.5%
7 37
 
7.0%
9 27
 
5.1%
Space Separator
ValueCountFrequency (%)
450
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1331
56.5%
Common 1024
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 144
 
10.8%
성 140
 
10.5%
충 128
 
9.6%
남 123
 
9.2%
군 110
 
8.3%
로 98
 
7.4%
면 82
 
6.2%
길 57
 
4.3%
번 47
 
3.5%
산 41
 
3.1%
Other values (44) 361
27.1%
Common
ValueCountFrequency (%)
450
43.9%
1 125
 
12.2%
2 57
 
5.6%
6 55
 
5.4%
4 54
 
5.3%
3 51
 
5.0%
8 43
 
4.2%
0 42
 
4.1%
- 41
 
4.0%
5 40
 
3.9%
Other values (4) 66
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1331
56.5%
ASCII 1024
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
450
43.9%
1 125
 
12.2%
2 57
 
5.6%
6 55
 
5.4%
4 54
 
5.3%
3 51
 
5.0%
8 43
 
4.2%
0 42
 
4.1%
- 41
 
4.0%
5 40
 
3.9%
Other values (4) 66
 
6.4%
Hangul
ValueCountFrequency (%)
홍 144
 
10.8%
성 140
 
10.5%
충 128
 
9.6%
남 123
 
9.2%
군 110
 
8.3%
로 98
 
7.4%
면 82
 
6.2%
길 57
 
4.3%
번 47
 
3.5%
산 41
 
3.1%
Other values (44) 361
27.1%

전화번호
Text

MISSING 

Distinct87
Distinct (%)95.6%
Missing19
Missing (%)17.3%
Memory size1012.0 B
2024-01-10T05:31:14.161376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.087912
Min length12

Characters and Unicode

Total characters1100
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)91.2%

Sample

1st row041-632-2252
2nd row041-634-4624
3rd row041-634-3690
4th row041-642-2333
5th row041-642-2211
ValueCountFrequency (%)
041-642-7611 2
 
2.2%
041-633-7977 2
 
2.2%
041-630-8000 2
 
2.2%
041-632-3820 2
 
2.2%
041-634-3900 1
 
1.1%
041-633-7780 1
 
1.1%
041-635-0601~4 1
 
1.1%
041-642-6050 1
 
1.1%
041-641-0031 1
 
1.1%
041-641-4222 1
 
1.1%
Other values (77) 77
84.6%
2024-01-10T05:31:14.520051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 182
16.5%
0 165
15.0%
4 158
14.4%
1 147
13.4%
6 129
11.7%
3 117
10.6%
2 67
 
6.1%
7 35
 
3.2%
9 34
 
3.1%
5 33
 
3.0%
Other values (2) 33
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 914
83.1%
Dash Punctuation 182
 
16.5%
Math Symbol 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 165
18.1%
4 158
17.3%
1 147
16.1%
6 129
14.1%
3 117
12.8%
2 67
7.3%
7 35
 
3.8%
9 34
 
3.7%
5 33
 
3.6%
8 29
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 182
16.5%
0 165
15.0%
4 158
14.4%
1 147
13.4%
6 129
11.7%
3 117
10.6%
2 67
 
6.1%
7 35
 
3.2%
9 34
 
3.1%
5 33
 
3.0%
Other values (2) 33
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 182
16.5%
0 165
15.0%
4 158
14.4%
1 147
13.4%
6 129
11.7%
3 117
10.6%
2 67
 
6.1%
7 35
 
3.2%
9 34
 
3.1%
5 33
 
3.0%
Other values (2) 33
 
3.0%

업종
Text

Distinct72
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-01-10T05:31:14.752883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length30
Mean length13.272727
Min length3

Characters and Unicode

Total characters1460
Distinct characters165
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)52.7%

Sample

1st row곡물도정업
2nd row동물성사료및조제식품제조업
3rd row레미콘제조업
4th row타이어재생업
5th row자동차종합수리업
ValueCountFrequency (%)
및 21
 
9.4%
제조업 14
 
6.3%
자동차종합수리업 13
 
5.8%
곡물도정업 8
 
3.6%
기타 7
 
3.1%
레미콘제조업 5
 
2.2%
구조용 4
 
1.8%
그외 4
 
1.8%
자동차종합수리업(95211 3
 
1.3%
그외기타분류안된비금속광물제품제조업 3
 
1.3%
Other values (114) 141
63.2%
2024-01-10T05:31:15.118169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
7.7%
업 109
 
7.5%
제 100
 
6.8%
조 98
 
6.7%
및 38
 
2.6%
기 37
 
2.5%
물 34
 
2.3%
품 32
 
2.2%
동 30
 
2.1%
차 30
 
2.1%
Other values (155) 839
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1206
82.6%
Space Separator 113
 
7.7%
Decimal Number 90
 
6.2%
Open Punctuation 18
 
1.2%
Close Punctuation 18
 
1.2%
Other Punctuation 15
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 109
 
9.0%
제 100
 
8.3%
조 98
 
8.1%
및 38
 
3.2%
기 37
 
3.1%
물 34
 
2.8%
품 32
 
2.7%
동 30
 
2.5%
차 30
 
2.5%
리 30
 
2.5%
Other values (143) 668
55.4%
Decimal Number
ValueCountFrequency (%)
2 20
22.2%
9 19
21.1%
3 16
17.8%
1 15
16.7%
0 9
10.0%
5 7
 
7.8%
8 3
 
3.3%
6 1
 
1.1%
Space Separator
ValueCountFrequency (%)
113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1206
82.6%
Common 254
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 109
 
9.0%
제 100
 
8.3%
조 98
 
8.1%
및 38
 
3.2%
기 37
 
3.1%
물 34
 
2.8%
품 32
 
2.7%
동 30
 
2.5%
차 30
 
2.5%
리 30
 
2.5%
Other values (143) 668
55.4%
Common
ValueCountFrequency (%)
113
44.5%
2 20
 
7.9%
9 19
 
7.5%
( 18
 
7.1%
) 18
 
7.1%
3 16
 
6.3%
1 15
 
5.9%
, 15
 
5.9%
0 9
 
3.5%
5 7
 
2.8%
Other values (2) 4
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1206
82.6%
ASCII 254
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
44.5%
2 20
 
7.9%
9 19
 
7.5%
( 18
 
7.1%
) 18
 
7.1%
3 16
 
6.3%
1 15
 
5.9%
, 15
 
5.9%
0 9
 
3.5%
5 7
 
2.8%
Other values (2) 4
 
1.6%
Hangul
ValueCountFrequency (%)
업 109
 
9.0%
제 100
 
8.3%
조 98
 
8.1%
및 38
 
3.2%
기 37
 
3.1%
물 34
 
2.8%
품 32
 
2.7%
동 30
 
2.5%
차 30
 
2.5%
리 30
 
2.5%
Other values (143) 668
55.4%

종별
Categorical

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1012.0 B
4
54 
5
50 
3
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row3
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 54
49.1%
5 50
45.5%
3 6
 
5.5%

Length

2024-01-10T05:31:15.231755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:31:15.315427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 54
49.1%
5 50
45.5%
3 6
 
5.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2021-05-31
110 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-31
2nd row2021-05-31
3rd row2021-05-31
4th row2021-05-31
5th row2021-05-31

Common Values

ValueCountFrequency (%)
2021-05-31 110
100.0%

Length

2024-01-10T05:31:15.404644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:31:15.481975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-31 110
100.0%

Correlations

2024-01-10T05:31:15.533196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전화번호업종종별
전화번호1.0000.9950.611
업종0.9951.0000.737
종별0.6110.7371.000

Missing values

2024-01-10T05:31:12.560962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:31:12.647804image/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

업체명도로명주소전화번호업종종별데이터기준일자
0홍주정미소충남 홍성군 홍성읍 문화로 8041-632-2252곡물도정업52021-05-31
1홍성축산업협동조합배합사료공장충남 홍성군 홍성읍 구항길 389041-634-4624동물성사료및조제식품제조업32021-05-31
2㈜한솔충남 홍성군 홍동면 광금남로 891041-634-3690레미콘제조업42021-05-31
3(유)태광타이어충남 홍성군 결성면 홍남서로 651041-642-2333타이어재생업42021-05-31
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