Overview

Dataset statistics

Number of variables5
Number of observations157
Missing cells0
Missing cells (%)0.0%
Duplicate rows35
Duplicate rows (%)22.3%
Total size in memory6.6 KiB
Average record size in memory42.8 B

Variable types

Numeric1
Categorical4

Dataset

Description폐기물처분부담금관리시스템 내 등록되어진 데이터로 재활용 및 폐기물처분부담금 신고한 내역에 대한 정보를 제공합니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15092762/fileData.do

Alerts

처분방법 has constant value ""Constant
처리방법 has constant value ""Constant
Dataset has 35 (22.3%) duplicate rowsDuplicates
폐기물코드 is highly overall correlated with 실적년도High correlation
실적년도 is highly overall correlated with 폐기물코드High correlation
폐기물코드 is highly imbalanced (62.3%)Imbalance

Reproduction

Analysis started2023-12-12 18:00:01.596084
Analysis finished2023-12-12 18:00:01.978076
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

Distinct20
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.8025478
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T03:00:02.036528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median9
Q313
95-th percentile21
Maximum35
Range34
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.2760932
Coefficient of variation (CV)0.74226552
Kurtosis1.0432235
Mean9.8025478
Median Absolute Deviation (MAD)5
Skewness0.84249203
Sum1539
Variance52.941532
MonotonicityIncreasing
2023-12-13T03:00:02.174117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 23
14.6%
9 16
10.2%
12 16
10.2%
13 14
 
8.9%
2 13
 
8.3%
19 9
 
5.7%
3 9
 
5.7%
14 7
 
4.5%
5 6
 
3.8%
11 6
 
3.8%
Other values (10) 38
24.2%
ValueCountFrequency (%)
1 23
14.6%
2 13
8.3%
3 9
 
5.7%
4 5
 
3.2%
5 6
 
3.8%
6 4
 
2.5%
8 3
 
1.9%
9 16
10.2%
10 4
 
2.5%
11 6
 
3.8%
ValueCountFrequency (%)
35 3
 
1.9%
23 4
 
2.5%
21 3
 
1.9%
20 4
 
2.5%
19 9
5.7%
18 4
 
2.5%
15 4
 
2.5%
14 7
4.5%
13 14
8.9%
12 16
10.2%

폐기물코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
51-13-03
126 
51-02-19
 
7
51-08-03
 
5
51-04-99
 
5
51-02-01
 
5
Other values (6)
 
9

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique4 ?
Unique (%)2.5%

Sample

1st row 51-13-03
2nd row 51-13-03
3rd row 51-13-03
4th row 51-01-04
5th row 51-21-01

Common Values

ValueCountFrequency (%)
51-13-03 126
80.3%
51-02-19 7
 
4.5%
51-08-03 5
 
3.2%
51-04-99 5
 
3.2%
51-02-01 5
 
3.2%
51-02-06 3
 
1.9%
09-02-00 2
 
1.3%
51-01-04 1
 
0.6%
51-21-01 1
 
0.6%
51-03-01 1
 
0.6%

Length

2023-12-13T03:00:02.305846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
51-13-03 126
80.3%
51-02-19 7
 
4.5%
51-08-03 5
 
3.2%
51-04-99 5
 
3.2%
51-02-01 5
 
3.2%
51-02-06 3
 
1.9%
09-02-00 2
 
1.3%
51-01-04 1
 
0.6%
51-21-01 1
 
0.6%
51-03-01 1
 
0.6%

실적년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2019
59 
2021
42 
2020
37 
2018
17 
2014
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2019
3rd row2019
4th row2018
5th row2019

Common Values

ValueCountFrequency (%)
2019 59
37.6%
2021 42
26.8%
2020 37
23.6%
2018 17
 
10.8%
2014 2
 
1.3%

Length

2023-12-13T03:00:02.447737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:00:02.913532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 59
37.6%
2021 42
26.8%
2020 37
23.6%
2018 17
 
10.8%
2014 2
 
1.3%

처분방법
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
자가
157 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가 157
100.0%

Length

2023-12-13T03:00:03.047360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:00:03.158750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가 157
100.0%

처리방법
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
매립
157 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매립 157
100.0%

Length

2023-12-13T03:00:03.272362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:00:03.388525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매립 157
100.0%

Interactions

2023-12-13T03:00:01.712961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:00:03.453954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번폐기물코드실적년도
순번1.0000.2320.513
폐기물코드0.2321.0000.741
실적년도0.5130.7411.000
2023-12-13T03:00:03.571970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물코드실적년도
폐기물코드1.0000.516
실적년도0.5161.000
2023-12-13T03:00:03.669040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번폐기물코드실적년도
순번1.0000.1080.306
폐기물코드0.1081.0000.516
실적년도0.3060.5161.000

Missing values

2023-12-13T03:00:01.838075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:00:01.933913image/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

순번폐기물코드실적년도처분방법처리방법
0151-13-032018자가매립
1151-13-032019자가매립
2151-13-032019자가매립
3151-01-042018자가매립
4151-21-012019자가매립
5151-13-032019자가매립
6151-13-032019자가매립
7151-13-032019자가매립
8151-13-032018자가매립
9151-13-032018자가매립
순번폐기물코드실적년도처분방법처리방법
1472151-13-032021자가매립
1482151-13-032021자가매립
1492151-13-032021자가매립
1502351-13-032020자가매립
1512351-13-032020자가매립
1522351-13-032020자가매립
1532351-13-032020자가매립
1543551-13-032020자가매립
1553551-13-032020자가매립
1563551-13-032020자가매립

Duplicate rows

Most frequently occurring

순번폐기물코드실적년도처분방법처리방법# duplicates
231351-13-032019자가매립14
16951-13-032019자가매립10
211251-13-032020자가매립8
291951-13-032021자가매립7
3151-13-032019자가매립6
17951-13-032020자가매립6
191151-13-032021자가매립6
2151-13-032018자가매립5
5251-04-992019자가매립5
6251-13-032019자가매립5