Overview

Dataset statistics

Number of variables6
Number of observations61
Missing cells4
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory51.2 B

Variable types

Text4
Categorical2

Dataset

Description충청남도 부여군에 소재하는 대기배출시설 현황 정보(업체명, 종수, 사업장 도로명주소, 업종, 전화번호, 데이터기준일자 등)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=339&beforeMenuCd=DOM_000000201001001000&publicdatapk=15082968

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 4 (6.6%) missing valuesMissing
사업장 도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:47:01.601202
Analysis finished2024-01-09 21:47:02.084668
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-01-10T06:47:02.218492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.4918033
Min length3

Characters and Unicode

Total characters457
Distinct characters137
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)96.7%

Sample

1st row㈜제일산업
2nd row㈜대오
3rd row선진기업㈜
4th row부여레미콘㈜
5th row대한레미콘㈜
ValueCountFrequency (%)
㈜뉴제일이엘이씨 2
 
3.0%
농업회사법인 2
 
3.0%
주식회사 2
 
3.0%
㈜제일산업 1
 
1.5%
㈜대오 1
 
1.5%
라이스영농조합법인 1
 
1.5%
주)우리면 1
 
1.5%
부여군농협쌀조합공동사업법인 1
 
1.5%
㈜)정우소재 1
 
1.5%
동인화학㈜부여공장 1
 
1.5%
Other values (54) 54
80.6%
2024-01-10T06:47:02.517881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 30
 
6.6%
인 13
 
2.8%
농 12
 
2.6%
이 12
 
2.6%
업 12
 
2.6%
산 11
 
2.4%
스 11
 
2.4%
합 11
 
2.4%
제 10
 
2.2%
부 9
 
2.0%
Other values (127) 326
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 406
88.8%
Other Symbol 30
 
6.6%
Space Separator 6
 
1.3%
Uppercase Letter 6
 
1.3%
Close Punctuation 5
 
1.1%
Open Punctuation 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 13
 
3.2%
농 12
 
3.0%
이 12
 
3.0%
업 12
 
3.0%
산 11
 
2.7%
스 11
 
2.7%
합 11
 
2.7%
제 10
 
2.5%
부 9
 
2.2%
영 9
 
2.2%
Other values (118) 296
72.9%
Uppercase Letter
ValueCountFrequency (%)
R 2
33.3%
M 1
16.7%
T 1
16.7%
P 1
16.7%
C 1
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 30
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
95.4%
Common 15
 
3.3%
Latin 6
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 30
 
6.9%
인 13
 
3.0%
농 12
 
2.8%
이 12
 
2.8%
업 12
 
2.8%
산 11
 
2.5%
스 11
 
2.5%
합 11
 
2.5%
제 10
 
2.3%
부 9
 
2.1%
Other values (119) 305
70.0%
Latin
ValueCountFrequency (%)
R 2
33.3%
M 1
16.7%
T 1
16.7%
P 1
16.7%
C 1
16.7%
Common
ValueCountFrequency (%)
6
40.0%
) 5
33.3%
( 4
26.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 406
88.8%
None 30
 
6.6%
ASCII 21
 
4.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 30
100.0%
Hangul
ValueCountFrequency (%)
인 13
 
3.2%
농 12
 
3.0%
이 12
 
3.0%
업 12
 
3.0%
산 11
 
2.7%
스 11
 
2.7%
합 11
 
2.7%
제 10
 
2.5%
부 9
 
2.2%
영 9
 
2.2%
Other values (118) 296
72.9%
ASCII
ValueCountFrequency (%)
6
28.6%
) 5
23.8%
( 4
19.0%
R 2
 
9.5%
M 1
 
4.8%
T 1
 
4.8%
P 1
 
4.8%
C 1
 
4.8%

종수
Categorical

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
5
33 
4
24 
3
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
5 33
54.1%
4 24
39.3%
3 4
 
6.6%

Length

2024-01-10T06:47:02.623917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:47:02.696765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 33
54.1%
4 24
39.3%
3 4
 
6.6%

사업장 도로명주소
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-01-10T06:47:02.903953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.704918
Min length18

Characters and Unicode

Total characters1324
Distinct characters81
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 부여군 홍산면 비홍로 59-10
2nd row충청남도 부여군 초촌면 금백로 1007
3rd row충청남도 부여군 석성면 선사로 12
4th row충청남도 부여군 규암면 충절로2599번길 15
5th row충청남도 부여군 석성면 왕릉로 619
ValueCountFrequency (%)
충청남도 61
20.0%
부여군 61
20.0%
초촌면 11
 
3.6%
은산면 10
 
3.3%
규암면 9
 
3.0%
석성면 8
 
2.6%
흥수로 6
 
2.0%
임천면 6
 
2.0%
금백로 6
 
2.0%
장암면 5
 
1.6%
Other values (101) 122
40.0%
2024-01-10T06:47:03.229899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
244
18.4%
충 73
 
5.5%
부 68
 
5.1%
여 66
 
5.0%
남 64
 
4.8%
도 61
 
4.6%
군 61
 
4.6%
청 61
 
4.6%
로 59
 
4.5%
면 56
 
4.2%
Other values (71) 511
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 832
62.8%
Space Separator 244
 
18.4%
Decimal Number 231
 
17.4%
Dash Punctuation 17
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 73
 
8.8%
부 68
 
8.2%
여 66
 
7.9%
남 64
 
7.7%
도 61
 
7.3%
군 61
 
7.3%
청 61
 
7.3%
로 59
 
7.1%
면 56
 
6.7%
암 19
 
2.3%
Other values (59) 244
29.3%
Decimal Number
ValueCountFrequency (%)
1 42
18.2%
2 34
14.7%
0 27
11.7%
6 26
11.3%
3 23
10.0%
4 21
9.1%
5 19
8.2%
8 15
 
6.5%
7 13
 
5.6%
9 11
 
4.8%
Space Separator
ValueCountFrequency (%)
244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 832
62.8%
Common 492
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 73
 
8.8%
부 68
 
8.2%
여 66
 
7.9%
남 64
 
7.7%
도 61
 
7.3%
군 61
 
7.3%
청 61
 
7.3%
로 59
 
7.1%
면 56
 
6.7%
암 19
 
2.3%
Other values (59) 244
29.3%
Common
ValueCountFrequency (%)
244
49.6%
1 42
 
8.5%
2 34
 
6.9%
0 27
 
5.5%
6 26
 
5.3%
3 23
 
4.7%
4 21
 
4.3%
5 19
 
3.9%
- 17
 
3.5%
8 15
 
3.0%
Other values (2) 24
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 832
62.8%
ASCII 492
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
244
49.6%
1 42
 
8.5%
2 34
 
6.9%
0 27
 
5.5%
6 26
 
5.3%
3 23
 
4.7%
4 21
 
4.3%
5 19
 
3.9%
- 17
 
3.5%
8 15
 
3.0%
Other values (2) 24
 
4.9%
Hangul
ValueCountFrequency (%)
충 73
 
8.8%
부 68
 
8.2%
여 66
 
7.9%
남 64
 
7.7%
도 61
 
7.3%
군 61
 
7.3%
청 61
 
7.3%
로 59
 
7.1%
면 56
 
6.7%
암 19
 
2.3%
Other values (59) 244
29.3%

전화번호
Text

MISSING 

Distinct56
Distinct (%)98.2%
Missing4
Missing (%)6.6%
Memory size620.0 B
2024-01-10T06:47:03.426818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.017544
Min length12

Characters and Unicode

Total characters685
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

Unique55 ?
Unique (%)96.5%

Sample

1st row041-836-8077
2nd row041-832-7900
3rd row041-834-6556
4th row041-834-6636
5th row041-836-3131
ValueCountFrequency (%)
041-836-0181 2
 
3.5%
041-835-5401 1
 
1.8%
041-830-9400 1
 
1.8%
041-836-8077 1
 
1.8%
041-836-4470 1
 
1.8%
041-835-3292 1
 
1.8%
041-832-1571 1
 
1.8%
041-834-6778 1
 
1.8%
041-833-0977 1
 
1.8%
041-837-7370 1
 
1.8%
Other values (46) 46
80.7%
2024-01-10T06:47:03.723476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 114
16.6%
0 102
14.9%
4 84
12.3%
1 84
12.3%
8 79
11.5%
3 78
11.4%
7 42
 
6.1%
5 33
 
4.8%
6 29
 
4.2%
2 28
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 571
83.4%
Dash Punctuation 114
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102
17.9%
4 84
14.7%
1 84
14.7%
8 79
13.8%
3 78
13.7%
7 42
7.4%
5 33
 
5.8%
6 29
 
5.1%
2 28
 
4.9%
9 12
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 685
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 114
16.6%
0 102
14.9%
4 84
12.3%
1 84
12.3%
8 79
11.5%
3 78
11.4%
7 42
 
6.1%
5 33
 
4.8%
6 29
 
4.2%
2 28
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 114
16.6%
0 102
14.9%
4 84
12.3%
1 84
12.3%
8 79
11.5%
3 78
11.4%
7 42
 
6.1%
5 33
 
4.8%
6 29
 
4.2%
2 28
 
4.1%

업종
Text

Distinct41
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-01-10T06:47:03.929110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length8.9344262
Min length3

Characters and Unicode

Total characters545
Distinct characters114
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)55.7%

Sample

1st row비금속광물제품제조
2nd row식료품제조
3rd row비금속광물제품제조
4th row비금속광물제품제조
5th row비금속광물제품제조
ValueCountFrequency (%)
비금속광물제품제조 12
 
15.8%
및 4
 
5.3%
곡물도정업 3
 
3.9%
음식료품제조업 3
 
3.9%
도정업 3
 
3.9%
공통시설 2
 
2.6%
레미콘제조업 2
 
2.6%
기타 2
 
2.6%
나무제품제조 2
 
2.6%
목재 2
 
2.6%
Other values (41) 41
53.9%
2024-01-10T06:47:04.226582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 67
 
12.3%
조 46
 
8.4%
업 40
 
7.3%
품 30
 
5.5%
물 22
 
4.0%
비 18
 
3.3%
속 16
 
2.9%
금 16
 
2.9%
15
 
2.8%
광 12
 
2.2%
Other values (104) 263
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 525
96.3%
Space Separator 15
 
2.8%
Other Punctuation 3
 
0.6%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 67
 
12.8%
조 46
 
8.8%
업 40
 
7.6%
품 30
 
5.7%
물 22
 
4.2%
비 18
 
3.4%
속 16
 
3.0%
금 16
 
3.0%
광 12
 
2.3%
기 12
 
2.3%
Other values (100) 246
46.9%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 525
96.3%
Common 20
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 67
 
12.8%
조 46
 
8.8%
업 40
 
7.6%
품 30
 
5.7%
물 22
 
4.2%
비 18
 
3.4%
속 16
 
3.0%
금 16
 
3.0%
광 12
 
2.3%
기 12
 
2.3%
Other values (100) 246
46.9%
Common
ValueCountFrequency (%)
15
75.0%
, 3
 
15.0%
) 1
 
5.0%
( 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 525
96.3%
ASCII 20
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 67
 
12.8%
조 46
 
8.8%
업 40
 
7.6%
품 30
 
5.7%
물 22
 
4.2%
비 18
 
3.4%
속 16
 
3.0%
금 16
 
3.0%
광 12
 
2.3%
기 12
 
2.3%
Other values (100) 246
46.9%
ASCII
ValueCountFrequency (%)
15
75.0%
, 3
 
15.0%
) 1
 
5.0%
( 1
 
5.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
2021-06-01
61 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-06-01
2nd row2021-06-01
3rd row2021-06-01
4th row2021-06-01
5th row2021-06-01

Common Values

ValueCountFrequency (%)
2021-06-01 61
100.0%

Length

2024-01-10T06:47:04.331164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:47:04.401481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-01 61
100.0%

Correlations

2024-01-10T06:47:04.448517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명종수사업장 도로명주소전화번호업종
업체명1.0001.0001.0000.9970.960
종수1.0001.0001.0001.0000.000
사업장 도로명주소1.0001.0001.0001.0001.000
전화번호0.9971.0001.0001.0001.000
업종0.9600.0001.0001.0001.000

Missing values

2024-01-10T06:47:01.975484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:47:02.053251image/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

업체명종수사업장 도로명주소전화번호업종데이터기준일자
0㈜제일산업4충청남도 부여군 홍산면 비홍로 59-10041-836-8077비금속광물제품제조2021-06-01
1㈜대오5충청남도 부여군 초촌면 금백로 1007041-832-7900식료품제조2021-06-01
2선진기업㈜5충청남도 부여군 석성면 선사로 12041-834-6556비금속광물제품제조2021-06-01
3부여레미콘㈜5충청남도 부여군 규암면 충절로2599번길 15041-834-6636비금속광물제품제조2021-06-01
4대한레미콘㈜4충청남도 부여군 석성면 왕릉로 619041-836-3131비금속광물제품제조2021-06-01
5㈜한길5충청남도 부여군 초촌면 신암로 412041-834-0537비금속광물제품제조2021-06-01
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