Overview

Dataset statistics

Number of variables7
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory61.3 B

Variable types

Categorical3
Text3
DateTime1

Dataset

Description본 공공데이터는 폐기물처리업현황을 제공하는 공공데이터로 업종, 업체명, 소재지, 전화번호, 관리부서, 관리부서 전화번호 의 정보를 담고 있습니다.
Author전라북도 완주군
URLhttps://www.data.go.kr/data/3076576/fileData.do

Alerts

관리부서 has constant value ""Constant
관리부서 연락처 has constant value ""Constant
데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-13 00:50:21.523857
Analysis finished2023-12-13 00:50:21.892958
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업 종
Categorical

Distinct7
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
폐기물 재활용 신고업소
7 
사업장배출시설계 수집운반업
6 
사업장폐기물중간처리업
6 
건설폐기물수집운반업
3 
사업장일반폐기물최종처리업
1 
Other values (2)
2 

Length

Max length14
Median length13
Mean length11.8
Min length8

Unique

Unique3 ?
Unique (%)12.0%

Sample

1st row사업장일반폐기물최종처리업
2nd row사업장배출시설계 수집운반업
3rd row사업장폐기물중간처리업
4th row사업장배출시설계 수집운반업
5th row폐기물 재활용 신고업소

Common Values

ValueCountFrequency (%)
폐기물 재활용 신고업소 7
28.0%
사업장배출시설계 수집운반업 6
24.0%
사업장폐기물중간처리업 6
24.0%
건설폐기물수집운반업 3
12.0%
사업장일반폐기물최종처리업 1
 
4.0%
건설폐기물중간처리업 1
 
4.0%
생활계수집운반업 1
 
4.0%

Length

2023-12-13T09:50:22.158441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:50:22.244968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐기물 7
15.6%
재활용 7
15.6%
신고업소 7
15.6%
사업장배출시설계 6
13.3%
수집운반업 6
13.3%
사업장폐기물중간처리업 6
13.3%
건설폐기물수집운반업 3
6.7%
사업장일반폐기물최종처리업 1
 
2.2%
건설폐기물중간처리업 1
 
2.2%
생활계수집운반업 1
 
2.2%

업 체 명
Text

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T09:50:22.389937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.68
Min length3

Characters and Unicode

Total characters167
Distinct characters61
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st row㈜케이엠그린
2nd row(유)풍남특수운송사
3rd row영진약품공업㈜
4th row(주)동진환경
5th row봉동영농조합법인
ValueCountFrequency (%)
유)완주환경토건 3
 
12.0%
유)전일환경 2
 
8.0%
유)신동진산업 2
 
8.0%
유)풍남특수운송사 1
 
4.0%
㈜케이엠그린 1
 
4.0%
현풍산업 1
 
4.0%
유)태현환경 1
 
4.0%
완주상사 1
 
4.0%
광희농가 1
 
4.0%
유)은진산업 1
 
4.0%
Other values (11) 11
44.0%
2023-12-13T09:50:22.663124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 12
 
7.2%
) 12
 
7.2%
유 11
 
6.6%
환 8
 
4.8%
경 8
 
4.8%
업 7
 
4.2%
산 7
 
4.2%
주 6
 
3.6%
진 5
 
3.0%
동 5
 
3.0%
Other values (51) 86
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
83.2%
Open Punctuation 12
 
7.2%
Close Punctuation 12
 
7.2%
Other Symbol 4
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 11
 
7.9%
환 8
 
5.8%
경 8
 
5.8%
업 7
 
5.0%
산 7
 
5.0%
주 6
 
4.3%
진 5
 
3.6%
동 5
 
3.6%
농 4
 
2.9%
완 4
 
2.9%
Other values (48) 74
53.2%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143
85.6%
Common 24
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 11
 
7.7%
환 8
 
5.6%
경 8
 
5.6%
업 7
 
4.9%
산 7
 
4.9%
주 6
 
4.2%
진 5
 
3.5%
동 5
 
3.5%
농 4
 
2.8%
㈜ 4
 
2.8%
Other values (49) 78
54.5%
Common
ValueCountFrequency (%)
( 12
50.0%
) 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
83.2%
ASCII 24
 
14.4%
None 4
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 12
50.0%
) 12
50.0%
Hangul
ValueCountFrequency (%)
유 11
 
7.9%
환 8
 
5.8%
경 8
 
5.8%
업 7
 
5.0%
산 7
 
5.0%
주 6
 
4.3%
진 5
 
3.6%
동 5
 
3.6%
농 4
 
2.9%
완 4
 
2.9%
Other values (48) 74
53.2%
None
ValueCountFrequency (%)
㈜ 4
100.0%

소 재 지
Text

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T09:50:22.837197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length21.44
Min length19

Characters and Unicode

Total characters536
Distinct characters62
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

Unique18 ?
Unique (%)72.0%

Sample

1st row전라북도 완주군 봉동읍 완주산단6로 83
2nd row전라북도 완주군 봉동읍 용화길 15
3rd row전라북도 완주군 봉동읍 완주산단5로 21
4th row전라북도 완주군 봉동읍 역전만로 47
5th row전라북도 완주군 봉동읍 무관길 61
ValueCountFrequency (%)
전라북도 25
20.0%
완주군 25
20.0%
봉동읍 8
 
6.4%
소양면 7
 
5.6%
비봉면 3
 
2.4%
삼례읍 3
 
2.4%
원암로 3
 
2.4%
소양로 3
 
2.4%
209 3
 
2.4%
봉동로 3
 
2.4%
Other values (37) 42
33.6%
2023-12-13T09:50:23.096033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
18.7%
완 27
 
5.0%
주 27
 
5.0%
전 26
 
4.9%
도 26
 
4.9%
북 25
 
4.7%
군 25
 
4.7%
라 25
 
4.7%
로 18
 
3.4%
1 16
 
3.0%
Other values (52) 221
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
63.4%
Space Separator 100
 
18.7%
Decimal Number 86
 
16.0%
Dash Punctuation 10
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
완 27
 
7.9%
주 27
 
7.9%
전 26
 
7.6%
도 26
 
7.6%
북 25
 
7.4%
군 25
 
7.4%
라 25
 
7.4%
로 18
 
5.3%
봉 15
 
4.4%
면 14
 
4.1%
Other values (40) 112
32.9%
Decimal Number
ValueCountFrequency (%)
1 16
18.6%
6 13
15.1%
2 12
14.0%
9 9
10.5%
7 8
9.3%
5 8
9.3%
0 6
 
7.0%
3 6
 
7.0%
4 5
 
5.8%
8 3
 
3.5%
Space Separator
ValueCountFrequency (%)
100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 340
63.4%
Common 196
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
완 27
 
7.9%
주 27
 
7.9%
전 26
 
7.6%
도 26
 
7.6%
북 25
 
7.4%
군 25
 
7.4%
라 25
 
7.4%
로 18
 
5.3%
봉 15
 
4.4%
면 14
 
4.1%
Other values (40) 112
32.9%
Common
ValueCountFrequency (%)
100
51.0%
1 16
 
8.2%
6 13
 
6.6%
2 12
 
6.1%
- 10
 
5.1%
9 9
 
4.6%
7 8
 
4.1%
5 8
 
4.1%
0 6
 
3.1%
3 6
 
3.1%
Other values (2) 8
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
63.4%
ASCII 196
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
51.0%
1 16
 
8.2%
6 13
 
6.6%
2 12
 
6.1%
- 10
 
5.1%
9 9
 
4.6%
7 8
 
4.1%
5 8
 
4.1%
0 6
 
3.1%
3 6
 
3.1%
Other values (2) 8
 
4.1%
Hangul
ValueCountFrequency (%)
완 27
 
7.9%
주 27
 
7.9%
전 26
 
7.6%
도 26
 
7.6%
북 25
 
7.4%
군 25
 
7.4%
라 25
 
7.4%
로 18
 
5.3%
봉 15
 
4.4%
면 14
 
4.1%
Other values (40) 112
32.9%

전화번호
Text

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T09:50:23.247332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters300
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

Unique19 ?
Unique (%)76.0%

Sample

1st row063-262-8816
2nd row063-278-4212
3rd row063-263-0246
4th row063-245-4000
5th row063-263-6705
ValueCountFrequency (%)
063-243-6872 2
 
8.0%
063-232-7272 2
 
8.0%
063-263-3800 2
 
8.0%
063-213-2000 1
 
4.0%
063-262-8816 1
 
4.0%
063-278-4212 1
 
4.0%
063-241-7909 1
 
4.0%
063-243-6873 1
 
4.0%
063-291-0904 1
 
4.0%
063-261-8542 1
 
4.0%
Other values (12) 12
48.0%
2023-12-13T09:50:23.480818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 50
16.7%
0 45
15.0%
6 44
14.7%
3 43
14.3%
2 43
14.3%
1 18
 
6.0%
4 16
 
5.3%
7 13
 
4.3%
8 12
 
4.0%
5 8
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 250
83.3%
Dash Punctuation 50
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
18.0%
6 44
17.6%
3 43
17.2%
2 43
17.2%
1 18
 
7.2%
4 16
 
6.4%
7 13
 
5.2%
8 12
 
4.8%
5 8
 
3.2%
9 8
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 50
16.7%
0 45
15.0%
6 44
14.7%
3 43
14.3%
2 43
14.3%
1 18
 
6.0%
4 16
 
5.3%
7 13
 
4.3%
8 12
 
4.0%
5 8
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 50
16.7%
0 45
15.0%
6 44
14.7%
3 43
14.3%
2 43
14.3%
1 18
 
6.0%
4 16
 
5.3%
7 13
 
4.3%
8 12
 
4.0%
5 8
 
2.7%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
환경과 폐기물관리팀
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row환경과 폐기물관리팀
2nd row환경과 폐기물관리팀
3rd row환경과 폐기물관리팀
4th row환경과 폐기물관리팀
5th row환경과 폐기물관리팀

Common Values

ValueCountFrequency (%)
환경과 폐기물관리팀 25
100.0%

Length

2023-12-13T09:50:23.581793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:50:23.647044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경과 25
50.0%
폐기물관리팀 25
50.0%

관리부서 연락처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
063-290-2669
25 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row063-290-2669
2nd row063-290-2669
3rd row063-290-2669
4th row063-290-2669
5th row063-290-2669

Common Values

ValueCountFrequency (%)
063-290-2669 25
100.0%

Length

2023-12-13T09:50:23.730241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:50:23.796560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
063-290-2669 25
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2022-11-08 00:00:00
Maximum2022-11-08 00:00:00
2023-12-13T09:50:23.853841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:50:23.921229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T09:50:23.970592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업 종업 체 명소 재 지전화번호
업 종1.0000.0000.0000.000
업 체 명0.0001.0001.0001.000
소 재 지0.0001.0001.0001.000
전화번호0.0001.0001.0001.000

Missing values

2023-12-13T09:50:21.766362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:50:21.859759image/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

업 종업 체 명소 재 지전화번호관리부서관리부서 연락처데이터기준일자
0사업장일반폐기물최종처리업㈜케이엠그린전라북도 완주군 봉동읍 완주산단6로 83063-262-8816환경과 폐기물관리팀063-290-26692022-11-08
1사업장배출시설계 수집운반업(유)풍남특수운송사전라북도 완주군 봉동읍 용화길 15063-278-4212환경과 폐기물관리팀063-290-26692022-11-08
2사업장폐기물중간처리업영진약품공업㈜전라북도 완주군 봉동읍 완주산단5로 21063-263-0246환경과 폐기물관리팀063-290-26692022-11-08
3사업장배출시설계 수집운반업(주)동진환경전라북도 완주군 봉동읍 역전만로 47063-245-4000환경과 폐기물관리팀063-290-26692022-11-08
4폐기물 재활용 신고업소봉동영농조합법인전라북도 완주군 봉동읍 무관길 61063-263-6705환경과 폐기물관리팀063-290-26692022-11-08
5사업장폐기물중간처리업㈜농우전라북도 완주군 비봉면 이수백로 274-5063-261-0123환경과 폐기물관리팀063-290-26692022-11-08
6사업장배출시설계 수집운반업한국바이오영농조합법인전라북도 완주군 비봉면 백도리 363063-263-1711환경과 폐기물관리팀063-290-26692022-11-08
7사업장폐기물중간처리업삼우산업전라북도 완주군 비봉면 율백로 183-7063-263-8356환경과 폐기물관리팀063-290-26692022-11-08
8건설폐기물수집운반업(유)부성건설중기전라북도 완주군 삼례읍 삼례나들목로 95063-291-0050환경과 폐기물관리팀063-290-26692022-11-08
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