Overview

Dataset statistics

Number of variables8
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory68.6 B

Variable types

Categorical6
Text1
Numeric1

Dataset

Description광주환경공단 분뇨수거회사 현황에 대한 데이터로 분뇨수거회사의 업체명, 전화번호, fax번호, 소재지, 총인원, 차량번호, 적재량 항목을 제공합니다.
Author광주환경공단
URLhttps://www.data.go.kr/data/15007277/fileData.do

Alerts

팩스 is highly overall correlated with 구청 and 4 other fieldsHigh correlation
소재지 is highly overall correlated with 구청 and 4 other fieldsHigh correlation
전화번호 is highly overall correlated with 구청 and 4 other fieldsHigh correlation
업체명 is highly overall correlated with 구청 and 4 other fieldsHigh correlation
총인원(현장종사자) is highly overall correlated with 구청 and 4 other fieldsHigh correlation
구청 is highly overall correlated with 업체명 and 4 other fieldsHigh correlation
차량번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:02:07.830610
Analysis finished2024-03-14 16:02:09.428259
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구청
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size416.0 B
동구
11 
서구
8 
북구
7 
광산구
6 
남구
4 

Length

Max length3
Median length2
Mean length2.1666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동구
2nd row동구
3rd row동구
4th row동구
5th row동구

Common Values

ValueCountFrequency (%)
동구 11
30.6%
서구 8
22.2%
북구 7
19.4%
광산구 6
16.7%
남구 4
 
11.1%

Length

2024-03-15T01:02:09.741267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:02:10.085228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동구 11
30.6%
서구 8
22.2%
북구 7
19.4%
광산구 6
16.7%
남구 4
 
11.1%

업체명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size416.0 B
원일정화(유)
7 
㈜자양
4 
남도위생합자회사
4 
㈜명진정화
4 
(주)광북위생
4 
Other values (6)
13 

Length

Max length8
Median length7
Mean length6
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row원일정화(유)
2nd row원일정화(유)
3rd row원일정화(유)
4th row원일정화(유)
5th row원일정화(유)

Common Values

ValueCountFrequency (%)
원일정화(유) 7
19.4%
㈜자양 4
11.1%
남도위생합자회사 4
11.1%
㈜명진정화 4
11.1%
(주)광북위생 4
11.1%
㈜남구위생산업 3
8.3%
㈜청류환경 3
8.3%
(유)광산위생 2
 
5.6%
㈜가나위생 2
 
5.6%
㈜어등위생 2
 
5.6%

Length

2024-03-15T01:02:10.503612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
원일정화(유 7
19.4%
㈜자양 4
11.1%
남도위생합자회사 4
11.1%
㈜명진정화 4
11.1%
주)광북위생 4
11.1%
㈜남구위생산업 3
8.3%
㈜청류환경 3
8.3%
유)광산위생 2
 
5.6%
㈜가나위생 2
 
5.6%
㈜어등위생 2
 
5.6%

전화번호
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size416.0 B
062-226-0044
7 
062-385-1035
4 
062-373-9001
4 
062-373-0122
4 
062-515-0100
4 
Other values (6)
13 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row062-226-0044
2nd row062-226-0044
3rd row062-226-0044
4th row062-226-0044
5th row062-226-0044

Common Values

ValueCountFrequency (%)
062-226-0044 7
19.4%
062-385-1035 4
11.1%
062-373-9001 4
11.1%
062-373-0122 4
11.1%
062-515-0100 4
11.1%
062-653-8208 3
8.3%
062-261-8585 3
8.3%
062-944-0670 2
 
5.6%
062-941-5291 2
 
5.6%
062-941-5292 2
 
5.6%

Length

2024-03-15T01:02:10.901251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
062-226-0044 7
19.4%
062-385-1035 4
11.1%
062-373-9001 4
11.1%
062-373-0122 4
11.1%
062-515-0100 4
11.1%
062-653-8208 3
8.3%
062-261-8585 3
8.3%
062-944-0670 2
 
5.6%
062-941-5291 2
 
5.6%
062-941-5292 2
 
5.6%

팩스
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size416.0 B
062-373-6604
15 
062-226-4433
7 
062-945-0670
6 
062-385-1036
4 
062-371-8208
4 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row062-226-4433
2nd row062-226-4433
3rd row062-226-4433
4th row062-226-4433
5th row062-226-4433

Common Values

ValueCountFrequency (%)
062-373-6604 15
41.7%
062-226-4433 7
19.4%
062-945-0670 6
 
16.7%
062-385-1036 4
 
11.1%
062-371-8208 4
 
11.1%

Length

2024-03-15T01:02:11.287097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:02:11.569832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
062-373-6604 15
41.7%
062-226-4433 7
19.4%
062-945-0670 6
 
16.7%
062-385-1036 4
 
11.1%
062-371-8208 4
 
11.1%

소재지
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
광주광역시 학동길 5
7 
광주광역시 송도로 114번길 68(황룡동)
6 
광주광역시 천변우로 453, 407호
4 
광주광역시 천변우하로 171-1번지(덕흥동)
4 
광주광역시 화운로 304번길 15-25
4 
Other values (4)
11 

Length

Max length25
Median length23
Mean length19.25
Min length11

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row광주광역시 학동길 5
2nd row광주광역시 학동길 5
3rd row광주광역시 학동길 5
4th row광주광역시 학동길 5
5th row광주광역시 학동길 5

Common Values

ValueCountFrequency (%)
광주광역시 학동길 5 7
19.4%
광주광역시 송도로 114번길 68(황룡동) 6
16.7%
광주광역시 천변우로 453, 407호 4
11.1%
광주광역시 천변우하로 171-1번지(덕흥동) 4
11.1%
광주광역시 화운로 304번길 15-25 4
11.1%
광주광역시 무등로 271-1(중흥동) 4
11.1%
광주광역시 군분로 89번길 32 3
8.3%
광주광역시 안산로 70 3층 301호(오치동) 3
8.3%
광주광역시 월산로 72 1
 
2.8%

Length

2024-03-15T01:02:11.996193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:02:12.370235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 36
27.5%
5 7
 
5.3%
학동길 7
 
5.3%
송도로 6
 
4.6%
114번길 6
 
4.6%
68(황룡동 6
 
4.6%
화운로 4
 
3.1%
271-1(중흥동 4
 
3.1%
무등로 4
 
3.1%
15-25 4
 
3.1%
Other values (15) 47
35.9%

총인원(현장종사자)
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size416.0 B
9(6)
7 
5(4)
6 
7(6)
4 
7(4)
4 
12(10)
4 
Other values (5)
11 

Length

Max length6
Median length4
Mean length4.2222222
Min length4

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row9(6)
2nd row9(6)
3rd row9(6)
4th row9(6)
5th row9(6)

Common Values

ValueCountFrequency (%)
9(6) 7
19.4%
5(4) 6
16.7%
7(6) 4
11.1%
7(4) 4
11.1%
12(10) 4
11.1%
5(3) 3
8.3%
4(4) 3
8.3%
3(2) 2
 
5.6%
3(3) 2
 
5.6%
2(1) 1
 
2.8%

Length

2024-03-15T01:02:12.801683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:02:13.060579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9(6 7
19.4%
5(4 6
16.7%
7(6 4
11.1%
7(4 4
11.1%
12(10 4
11.1%
5(3 3
8.3%
4(4 3
8.3%
3(2 2
 
5.6%
3(3 2
 
5.6%
2(1 1
 
2.8%

차량번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-15T01:02:13.993457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2222222
Min length7

Characters and Unicode

Total characters296
Distinct characters27
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

Unique36 ?
Unique (%)100.0%

Sample

1st row82마6166
2nd row광주91가2022
3rd row82머9069
4th row87머 9066
5th row87머 9074
ValueCountFrequency (%)
84머 2
 
3.1%
광주90가 2
 
3.1%
81고 2
 
3.1%
87머 2
 
3.1%
86누 2
 
3.1%
87서 2
 
3.1%
광주8고 2
 
3.1%
광주88가 2
 
3.1%
5471 1
 
1.6%
0779 1
 
1.6%
Other values (46) 46
71.9%
2024-03-15T01:02:15.181589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 43
14.5%
28
9.5%
9 27
9.1%
1 26
 
8.8%
7 24
 
8.1%
2 19
 
6.4%
0 19
 
6.4%
4 16
 
5.4%
6 15
 
5.1%
5 14
 
4.7%
Other values (17) 65
22.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 214
72.3%
Other Letter 54
 
18.2%
Space Separator 28
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 10
18.5%
광 9
16.7%
고 7
13.0%
가 7
13.0%
머 6
11.1%
더 2
 
3.7%
루 2
 
3.7%
누 2
 
3.7%
서 2
 
3.7%
저 1
 
1.9%
Other values (6) 6
11.1%
Decimal Number
ValueCountFrequency (%)
8 43
20.1%
9 27
12.6%
1 26
12.1%
7 24
11.2%
2 19
8.9%
0 19
8.9%
4 16
 
7.5%
6 15
 
7.0%
5 14
 
6.5%
3 11
 
5.1%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242
81.8%
Hangul 54
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 10
18.5%
광 9
16.7%
고 7
13.0%
가 7
13.0%
머 6
11.1%
더 2
 
3.7%
루 2
 
3.7%
누 2
 
3.7%
서 2
 
3.7%
저 1
 
1.9%
Other values (6) 6
11.1%
Common
ValueCountFrequency (%)
8 43
17.8%
28
11.6%
9 27
11.2%
1 26
10.7%
7 24
9.9%
2 19
7.9%
0 19
7.9%
4 16
 
6.6%
6 15
 
6.2%
5 14
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242
81.8%
Hangul 54
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 43
17.8%
28
11.6%
9 27
11.2%
1 26
10.7%
7 24
9.9%
2 19
7.9%
0 19
7.9%
4 16
 
6.6%
6 15
 
6.2%
5 14
 
5.8%
Hangul
ValueCountFrequency (%)
주 10
18.5%
광 9
16.7%
고 7
13.0%
가 7
13.0%
머 6
11.1%
더 2
 
3.7%
루 2
 
3.7%
누 2
 
3.7%
서 2
 
3.7%
저 1
 
1.9%
Other values (6) 6
11.1%

적재량(톤)
Real number (ℝ)

Distinct19
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.291667
Minimum2.5
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-15T01:02:15.449676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile4.5
Q15
median8
Q316.125
95-th percentile23.375
Maximum25
Range22.5
Interquartile range (IQR)11.125

Descriptive statistics

Standard deviation6.8487069
Coefficient of variation (CV)0.60652755
Kurtosis-0.92194704
Mean11.291667
Median Absolute Deviation (MAD)3
Skewness0.71507124
Sum406.5
Variance46.904786
MonotonicityNot monotonic
2024-03-15T01:02:15.777858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
8.0 9
25.0%
5.0 8
22.2%
20.0 2
 
5.6%
21.0 2
 
5.6%
10.0 1
 
2.8%
25.0 1
 
2.8%
9.0 1
 
2.8%
15.3 1
 
2.8%
23.0 1
 
2.8%
3.0 1
 
2.8%
Other values (9) 9
25.0%
ValueCountFrequency (%)
2.5 1
 
2.8%
3.0 1
 
2.8%
5.0 8
22.2%
7.6 1
 
2.8%
7.9 1
 
2.8%
8.0 9
25.0%
9.0 1
 
2.8%
10.0 1
 
2.8%
14.6 1
 
2.8%
15.0 1
 
2.8%
ValueCountFrequency (%)
25.0 1
2.8%
24.5 1
2.8%
23.0 1
2.8%
21.6 1
2.8%
21.0 2
5.6%
20.0 2
5.6%
18.0 1
2.8%
15.5 1
2.8%
15.3 1
2.8%
15.0 1
2.8%

Interactions

2024-03-15T01:02:08.500688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:02:15.922906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구청업체명전화번호팩스소재지총인원(현장종사자)차량번호적재량(톤)
구청1.0001.0001.0000.9891.0000.9981.0000.000
업체명1.0001.0001.0001.0001.0001.0001.0000.000
전화번호1.0001.0001.0001.0001.0001.0001.0000.000
팩스0.9891.0001.0001.0001.0000.9991.0000.000
소재지1.0001.0001.0001.0001.0000.9861.0000.000
총인원(현장종사자)0.9981.0001.0000.9990.9861.0001.0000.000
차량번호1.0001.0001.0001.0001.0001.0001.0001.000
적재량(톤)0.0000.0000.0000.0000.0000.0001.0001.000
2024-03-15T01:02:16.224197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
팩스소재지전화번호업체명총인원(현장종사자)구청
팩스1.0000.9330.8980.8980.8670.847
소재지0.9331.0000.9620.9620.9340.933
전화번호0.8980.9621.0001.0000.9810.898
업체명0.8980.9621.0001.0000.9810.898
총인원(현장종사자)0.8670.9340.9810.9811.0000.854
구청0.8470.9330.8980.8980.8541.000
2024-03-15T01:02:16.508384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적재량(톤)구청업체명전화번호팩스소재지총인원(현장종사자)
적재량(톤)1.0000.0000.0000.0000.0000.0000.000
구청0.0001.0000.8980.8980.8470.9330.854
업체명0.0000.8981.0001.0000.8980.9620.981
전화번호0.0000.8981.0001.0000.8980.9620.981
팩스0.0000.8470.8980.8981.0000.9330.867
소재지0.0000.9330.9620.9620.9331.0000.934
총인원(현장종사자)0.0000.8540.9810.9810.8670.9341.000

Missing values

2024-03-15T01:02:08.847329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:02:09.266859image/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

구청업체명전화번호팩스소재지총인원(현장종사자)차량번호적재량(톤)
0동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)82마616610.0
1동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)광주91가20225.0
2동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)82머90695.0
3동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)87머 906615.0
4동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)87머 90747.6
5동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)87더 987918.0
6동구원일정화(유)062-226-0044062-226-4433광주광역시 학동길 59(6)82주 208320.0
7동구㈜자양062-385-1035062-385-1036광주광역시 천변우로 453, 407호7(6)90저 859820.0
8동구㈜자양062-385-1035062-385-1036광주광역시 천변우로 453, 407호7(6)94고 14138.0
9동구㈜자양062-385-1035062-385-1036광주광역시 천변우로 453, 407호7(6)91루 816721.0
구청업체명전화번호팩스소재지총인원(현장종사자)차량번호적재량(톤)
26북구(주)광북위생062-515-0100062-373-6604광주광역시 무등로 271-1(중흥동)12(10)86누 077925.0
27북구㈜청류환경062-261-8585062-373-6604광주광역시 안산로 70 3층 301호(오치동)4(4)81고 549014.6
28북구㈜청류환경062-261-8585062-373-6604광주광역시 안산로 70 3층 301호(오치동)4(4)84루 28598.0
29북구㈜청류환경062-261-8585062-373-6604광주광역시 안산로 70 3층 301호(오치동)4(4)92오 68922.5
30광산구(유)광산위생062-944-0670062-945-0670광주광역시 송도로 114번길 68(황룡동)5(4)87러 25383.0
31광산구(유)광산위생062-944-0670062-945-0670광주광역시 송도로 114번길 68(황룡동)5(4)81고187023.0
32광산구㈜가나위생062-941-5291062-945-0670광주광역시 송도로 114번길 68(황룡동)3(2)87서 130315.3
33광산구㈜가나위생062-941-5291062-945-0670광주광역시 송도로 114번길 68(황룡동)3(2)89노 74755.0
34광산구㈜어등위생062-941-5292062-945-0670광주광역시 송도로 114번길 68(황룡동)3(3)87더98689.0
35광산구㈜어등위생062-941-5292062-945-0670광주광역시 송도로 114번길 68(황룡동)3(3)87머90695.0