Overview

Dataset statistics

Number of variables7
Number of observations76
Missing cells15
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory58.7 B

Variable types

Text4
Categorical2
DateTime1

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
중질유 사용량(시간당) is highly imbalanced (87.3%)Imbalance
전화번호 has 15 (19.7%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:46:57.313722
Analysis finished2024-01-09 21:46:58.253595
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct75
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-01-10T06:46:58.369069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.4342105
Min length3

Characters and Unicode

Total characters565
Distinct characters156
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

Unique74 ?
Unique (%)97.4%

Sample

1st row㈜제일산업
2nd row㈜대오
3rd row선진기업㈜
4th row부여레미콘㈜
5th row대한레미콘㈜
ValueCountFrequency (%)
농업회사법인 4
 
4.7%
㈜뉴제일이엘이씨 2
 
2.4%
주식회사 2
 
2.4%
㈜케이지콘크리트 1
 
1.2%
영바이오 1
 
1.2%
대한폴리텍 1
 
1.2%
꿈에영농조합법인 1
 
1.2%
대명자원 1
 
1.2%
㈜삼성콘슬라트 1
 
1.2%
㈜현호산업 1
 
1.2%
Other values (70) 70
82.4%
2024-01-10T06:46:58.639853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 43
 
7.6%
업 20
 
3.5%
이 18
 
3.2%
농 16
 
2.8%
인 15
 
2.7%
사 14
 
2.5%
산 14
 
2.5%
스 12
 
2.1%
법 11
 
1.9%
콘 11
 
1.9%
Other values (146) 391
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 498
88.1%
Other Symbol 43
 
7.6%
Space Separator 9
 
1.6%
Uppercase Letter 6
 
1.1%
Close Punctuation 5
 
0.9%
Open Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 20
 
4.0%
이 18
 
3.6%
농 16
 
3.2%
인 15
 
3.0%
사 14
 
2.8%
산 14
 
2.8%
스 12
 
2.4%
법 11
 
2.2%
콘 11
 
2.2%
제 10
 
2.0%
Other values (137) 357
71.7%
Uppercase Letter
ValueCountFrequency (%)
R 2
33.3%
T 1
16.7%
M 1
16.7%
P 1
16.7%
C 1
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 43
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 541
95.8%
Common 18
 
3.2%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 43
 
7.9%
업 20
 
3.7%
이 18
 
3.3%
농 16
 
3.0%
인 15
 
2.8%
사 14
 
2.6%
산 14
 
2.6%
스 12
 
2.2%
법 11
 
2.0%
콘 11
 
2.0%
Other values (138) 367
67.8%
Latin
ValueCountFrequency (%)
R 2
33.3%
T 1
16.7%
M 1
16.7%
P 1
16.7%
C 1
16.7%
Common
ValueCountFrequency (%)
9
50.0%
) 5
27.8%
( 4
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 498
88.1%
None 43
 
7.6%
ASCII 24
 
4.2%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 43
100.0%
Hangul
ValueCountFrequency (%)
업 20
 
4.0%
이 18
 
3.6%
농 16
 
3.2%
인 15
 
3.0%
사 14
 
2.8%
산 14
 
2.8%
스 12
 
2.4%
법 11
 
2.2%
콘 11
 
2.2%
제 10
 
2.0%
Other values (137) 357
71.7%
ASCII
ValueCountFrequency (%)
9
37.5%
) 5
20.8%
( 4
16.7%
R 2
 
8.3%
T 1
 
4.2%
M 1
 
4.2%
P 1
 
4.2%
C 1
 
4.2%

종수
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
5
42 
4
29 
3
5 

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 42
55.3%
4 29
38.2%
3 5
 
6.6%

Length

2024-01-10T06:46:58.744928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:46:58.821726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 42
55.3%
4 29
38.2%
3 5
 
6.6%

사업장 도로명주소
Text

Distinct75
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-01-10T06:46:59.055612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length21.789474
Min length18

Characters and Unicode

Total characters1656
Distinct characters88
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

Unique74 ?
Unique (%)97.4%

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 76
19.7%
부여군 76
19.7%
석성면 14
 
3.6%
초촌면 13
 
3.4%
은산면 10
 
2.6%
규암면 8
 
2.1%
임천면 8
 
2.1%
금백로 6
 
1.6%
장암면 6
 
1.6%
부여읍 6
 
1.6%
Other values (128) 163
42.2%
2024-01-10T06:46:59.415420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
18.7%
충 90
 
5.4%
부 84
 
5.1%
여 82
 
5.0%
남 79
 
4.8%
도 77
 
4.6%
군 77
 
4.6%
청 76
 
4.6%
면 70
 
4.2%
로 66
 
4.0%
Other values (78) 645
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1031
62.3%
Space Separator 310
 
18.7%
Decimal Number 288
 
17.4%
Dash Punctuation 25
 
1.5%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 90
 
8.7%
부 84
 
8.1%
여 82
 
8.0%
남 79
 
7.7%
도 77
 
7.5%
군 77
 
7.5%
청 76
 
7.4%
면 70
 
6.8%
로 66
 
6.4%
산 23
 
2.2%
Other values (65) 307
29.8%
Decimal Number
ValueCountFrequency (%)
1 54
18.8%
2 36
12.5%
6 35
12.2%
3 32
11.1%
0 31
10.8%
4 24
8.3%
5 24
8.3%
8 19
 
6.6%
7 17
 
5.9%
9 16
 
5.6%
Space Separator
ValueCountFrequency (%)
310
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1031
62.3%
Common 625
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 90
 
8.7%
부 84
 
8.1%
여 82
 
8.0%
남 79
 
7.7%
도 77
 
7.5%
군 77
 
7.5%
청 76
 
7.4%
면 70
 
6.8%
로 66
 
6.4%
산 23
 
2.2%
Other values (65) 307
29.8%
Common
ValueCountFrequency (%)
310
49.6%
1 54
 
8.6%
2 36
 
5.8%
6 35
 
5.6%
3 32
 
5.1%
0 31
 
5.0%
- 25
 
4.0%
4 24
 
3.8%
5 24
 
3.8%
8 19
 
3.0%
Other values (3) 35
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1031
62.3%
ASCII 625
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
49.6%
1 54
 
8.6%
2 36
 
5.8%
6 35
 
5.6%
3 32
 
5.1%
0 31
 
5.0%
- 25
 
4.0%
4 24
 
3.8%
5 24
 
3.8%
8 19
 
3.0%
Other values (3) 35
 
5.6%
Hangul
ValueCountFrequency (%)
충 90
 
8.7%
부 84
 
8.1%
여 82
 
8.0%
남 79
 
7.7%
도 77
 
7.5%
군 77
 
7.5%
청 76
 
7.4%
면 70
 
6.8%
로 66
 
6.4%
산 23
 
2.2%
Other values (65) 307
29.8%

전화번호
Text

MISSING 

Distinct60
Distinct (%)98.4%
Missing15
Missing (%)19.7%
Memory size740.0 B
2024-01-10T06:46:59.622240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016393
Min length12

Characters and Unicode

Total characters733
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 (%)96.7%

Sample

1st row041-836-8077
2nd row041-832-7900
3rd row041-834-6556
4th row041-834-6636
5th row041-836-3131
ValueCountFrequency (%)
041-837-9904 2
 
3.3%
041-834-8036 1
 
1.6%
041-834-1010 1
 
1.6%
041-939-1024 1
 
1.6%
041-834-6778 1
 
1.6%
041-833-0977 1
 
1.6%
041-837-7370 1
 
1.6%
041-836-8055 1
 
1.6%
041-835-0770 1
 
1.6%
041-832-7288 1
 
1.6%
Other values (50) 50
82.0%
2024-01-10T06:46:59.907222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.6%
0 106
14.5%
4 90
12.3%
3 86
11.7%
1 85
11.6%
8 83
11.3%
7 44
 
6.0%
5 37
 
5.0%
6 30
 
4.1%
2 29
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 611
83.4%
Dash Punctuation 122
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
17.3%
4 90
14.7%
3 86
14.1%
1 85
13.9%
8 83
13.6%
7 44
7.2%
5 37
 
6.1%
6 30
 
4.9%
2 29
 
4.7%
9 21
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 733
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.6%
0 106
14.5%
4 90
12.3%
3 86
11.7%
1 85
11.6%
8 83
11.3%
7 44
 
6.0%
5 37
 
5.0%
6 30
 
4.1%
2 29
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.6%
0 106
14.5%
4 90
12.3%
3 86
11.7%
1 85
11.6%
8 83
11.3%
7 44
 
6.0%
5 37
 
5.0%
6 30
 
4.1%
2 29
 
4.0%

업종
Text

Distinct50
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-01-10T06:47:00.096745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length9.3947368
Min length3

Characters and Unicode

Total characters714
Distinct characters130
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

Unique40 ?
Unique (%)52.6%

Sample

1st row비금속광물제품제조
2nd row식료품제조
3rd row비금속광물제품제조
4th row비금속광물제품제조
5th row비금속광물제품제조
ValueCountFrequency (%)
비금속광물제품제조 12
 
11.1%
및 7
 
6.5%
폐기물종합재활용업 5
 
4.6%
콘크리트 4
 
3.7%
콘크리트제품제조업 3
 
2.8%
음식료품제조업 3
 
2.8%
도정업 3
 
2.8%
곡물도정업 3
 
2.8%
제조업 2
 
1.9%
나무제품제조 2
 
1.9%
Other values (57) 64
59.3%
2024-01-10T06:47:00.377863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 74
 
10.4%
업 56
 
7.8%
조 54
 
7.6%
32
 
4.5%
품 32
 
4.5%
물 26
 
3.6%
기 21
 
2.9%
비 19
 
2.7%
금 16
 
2.2%
속 16
 
2.2%
Other values (120) 368
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 671
94.0%
Space Separator 32
 
4.5%
Other Punctuation 5
 
0.7%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 74
 
11.0%
업 56
 
8.3%
조 54
 
8.0%
품 32
 
4.8%
물 26
 
3.9%
기 21
 
3.1%
비 19
 
2.8%
금 16
 
2.4%
속 16
 
2.4%
및 15
 
2.2%
Other values (116) 342
51.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 671
94.0%
Common 43
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 74
 
11.0%
업 56
 
8.3%
조 54
 
8.0%
품 32
 
4.8%
물 26
 
3.9%
기 21
 
3.1%
비 19
 
2.8%
금 16
 
2.4%
속 16
 
2.4%
및 15
 
2.2%
Other values (116) 342
51.0%
Common
ValueCountFrequency (%)
32
74.4%
, 5
 
11.6%
) 3
 
7.0%
( 3
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 671
94.0%
ASCII 43
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 74
 
11.0%
업 56
 
8.3%
조 54
 
8.0%
품 32
 
4.8%
물 26
 
3.9%
기 21
 
3.1%
비 19
 
2.8%
금 16
 
2.4%
속 16
 
2.4%
및 15
 
2.2%
Other values (116) 342
51.0%
ASCII
ValueCountFrequency (%)
32
74.4%
, 5
 
11.6%
) 3
 
7.0%
( 3
 
7.0%

중질유 사용량(시간당)
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
미사용
74 
220
 
1
637.5
 
1

Length

Max length5
Median length3
Mean length3.0263158
Min length3

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row220
2nd row미사용
3rd row미사용
4th row미사용
5th row미사용

Common Values

ValueCountFrequency (%)
미사용 74
97.4%
220 1
 
1.3%
637.5 1
 
1.3%

Length

2024-01-10T06:47:00.490370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:47:00.591523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미사용 74
97.4%
220 1
 
1.3%
637.5 1
 
1.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2024-01-10T06:47:00.676918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:47:00.774208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-01-10T06:47:00.848575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명종수사업장 도로명주소전화번호업종중질유 사용량(시간당)
업체명1.0001.0000.9980.9980.9711.000
종수1.0001.0001.0001.0000.0000.617
사업장 도로명주소0.9981.0001.0001.0001.0001.000
전화번호0.9981.0001.0001.0001.0001.000
업종0.9710.0001.0001.0001.0000.000
중질유 사용량(시간당)1.0000.6171.0001.0000.0001.000
2024-01-10T06:47:00.954594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종수중질유 사용량(시간당)
종수1.0000.284
중질유 사용량(시간당)0.2841.000
2024-01-10T06:47:01.037154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종수중질유 사용량(시간당)
종수1.0000.284
중질유 사용량(시간당)0.2841.000

Missing values

2024-01-10T06:46:58.133537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:46:58.218352image/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

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