Overview

Dataset statistics

Number of variables10
Number of observations3000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory252.1 KiB
Average record size in memory86.0 B

Variable types

Categorical7
Numeric3

Dataset

Description제주도 인근 해양에서 발견된 해안쓰레기에 대해 조사한 데이터입니다.해양폐기물의 발생 및 이동현황에 대한 모니터링을 통해 오염수준 및 발생원인을 파악할 목적으로 조사되었습니다.출처는 해양환경공단입니다. (데이터 미집계로 인하여 일부 데이터값에 공란이 존재할 수 있습니다.)**추가 정보**플라스틱은 재질별 특성에 따른 개수와 무게를 산정하지 않아 해당 재질의 전체 무게를 표시함
Author제주특별자치도
URLhttps://www.data.go.kr/data/15110788/fileData.do

Alerts

쓰레기 유형 대분류 is highly overall correlated with 쓰레기 유형 중분류 and 1 other fieldsHigh correlation
정점명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 정점명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 정점명 and 1 other fieldsHigh correlation
쓰레기 유형 소분류 is highly overall correlated with 쓰레기 유형 대분류 and 1 other fieldsHigh correlation
쓰레기 유형 중분류 is highly overall correlated with 쓰레기 유형 대분류 and 1 other fieldsHigh correlation
개수 has 2158 (71.9%) zerosZeros
무게 has 1227 (40.9%) zerosZeros

Reproduction

Analysis started2023-12-12 09:10:40.516151
Analysis finished2023-12-12 09:10:42.928187
Duration2.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정 연도
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2021
966 
2018
678 
2019
678 
2020
678 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 966
32.2%
2018 678
22.6%
2019 678
22.6%
2020 678
22.6%

Length

2023-12-12T18:10:43.002427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:43.123944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 966
32.2%
2018 678
22.6%
2019 678
22.6%
2020 678
22.6%

측정 차수
Real number (ℝ)

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2023-12-12T18:10:43.244808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3.5
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7081098
Coefficient of variation (CV)0.48803138
Kurtosis-1.2686856
Mean3.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum10500
Variance2.9176392
MonotonicityNot monotonic
2023-12-12T18:10:43.382893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 500
16.7%
2 500
16.7%
3 500
16.7%
4 500
16.7%
5 500
16.7%
6 500
16.7%
ValueCountFrequency (%)
1 500
16.7%
2 500
16.7%
3 500
16.7%
4 500
16.7%
5 500
16.7%
6 500
16.7%
ValueCountFrequency (%)
6 500
16.7%
5 500
16.7%
4 500
16.7%
3 500
16.7%
2 500
16.7%
1 500
16.7%

정점명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
제주 사계리
1368 
제주 김녕리
1344 
제주 위미
288 

Length

Max length6
Median length6
Mean length5.904
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주 사계리
2nd row제주 사계리
3rd row제주 사계리
4th row제주 사계리
5th row제주 사계리

Common Values

ValueCountFrequency (%)
제주 사계리 1368
45.6%
제주 김녕리 1344
44.8%
제주 위미 288
 
9.6%

Length

2023-12-12T18:10:43.516382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:43.632596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주 3000
50.0%
사계리 1368
22.8%
김녕리 1344
22.4%
위미 288
 
4.8%

위도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
33.222638
1368 
33.565625
1344 
33.26946
288 

Length

Max length9
Median length9
Mean length8.904
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row33.222638
2nd row33.222638
3rd row33.222638
4th row33.222638
5th row33.222638

Common Values

ValueCountFrequency (%)
33.222638 1368
45.6%
33.565625 1344
44.8%
33.26946 288
 
9.6%

Length

2023-12-12T18:10:43.753301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:43.872075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
33.222638 1368
45.6%
33.565625 1344
44.8%
33.26946 288
 
9.6%

경도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
126.296772
1368 
126.76504
1344 
126.652471
288 

Length

Max length10
Median length10
Mean length9.552
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row126.296772
2nd row126.296772
3rd row126.296772
4th row126.296772
5th row126.296772

Common Values

ValueCountFrequency (%)
126.296772 1368
45.6%
126.76504 1344
44.8%
126.652471 288
 
9.6%

Length

2023-12-12T18:10:43.983156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:44.078821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
126.296772 1368
45.6%
126.76504 1344
44.8%
126.652471 288
 
9.6%

쓰레기 유형 대분류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
플라스틱
1998 
외국기인
624 
천연섬유
 
54
종이
 
54
유리
 
54
Other values (4)
216 

Length

Max length4
Median length4
Mean length3.82
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
플라스틱 1998
66.6%
외국기인 624
 
20.8%
천연섬유 54
 
1.8%
종이 54
 
1.8%
유리 54
 
1.8%
목재 54
 
1.8%
기타재질 54
 
1.8%
금속 54
 
1.8%
고무 54
 
1.8%

Length

2023-12-12T18:10:44.180395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:10:44.291125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
플라스틱 1998
66.6%
외국기인 624
 
20.8%
천연섬유 54
 
1.8%
종이 54
 
1.8%
유리 54
 
1.8%
목재 54
 
1.8%
기타재질 54
 
1.8%
금속 54
 
1.8%
고무 54
 
1.8%

쓰레기 유형 중분류
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
경질형
864 
섬유형
378 
발포형
378 
<NA>
378 
필름형
270 
Other values (18)
732 

Length

Max length13
Median length3
Mean length3.942
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경질형 864
28.8%
섬유형 378
12.6%
발포형 378
12.6%
<NA> 378
12.6%
필름형 270
 
9.0%
기타 108
 
3.6%
각종 비닐포장 54
 
1.8%
부표(막대형 주황) 54
 
1.8%
음료수병, 병뚜껑 등 54
 
1.8%
라이터 48
 
1.6%
Other values (13) 414
13.8%

Length

2023-12-12T18:10:44.401939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경질형 918
26.3%
발포형 378
10.8%
na 378
10.8%
섬유형 378
10.8%
필름형 270
 
7.7%
기타 186
 
5.3%
파랑 96
 
2.8%
등 78
 
2.2%
음료수병 54
 
1.5%
병뚜껑 54
 
1.5%
Other values (17) 696
20.0%

쓰레기 유형 소분류
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
1002 
낚싯줄
 
54
담배꽁초
 
54
비닐포장(빙과류, 과자봉지 등)
 
54
비닐봉지
 
54
Other values (34)
1782 

Length

Max length35
Median length28
Mean length8.72
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row필름형 풍선
2nd row필름형 풍선
3rd row필름형 풍선
4th row필름형 풍선
5th row필름형 풍선

Common Values

ValueCountFrequency (%)
<NA> 1002
33.4%
낚싯줄 54
 
1.8%
담배꽁초 54
 
1.8%
비닐포장(빙과류, 과자봉지 등) 54
 
1.8%
비닐봉지 54
 
1.8%
옷, 천, 장갑, 양말, 이불 등(합성섬유만 해당) 54
 
1.8%
섬유형 파편 54
 
1.8%
섬유형 기타 54
 
1.8%
밧줄(꼬인 것, 어업용) 54
 
1.8%
끈(노끈, 포장용 끈) 54
 
1.8%
Other values (29) 1512
50.4%

Length

2023-12-12T18:10:44.521148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1002
 
15.8%
등 432
 
6.8%
파편 270
 
4.3%
스티로폼 216
 
3.4%
기타 216
 
3.4%
포장용 162
 
2.6%
필름형 138
 
2.2%
섬유형 108
 
1.7%
경질형 108
 
1.7%
미끼통 108
 
1.7%
Other values (62) 3564
56.4%

개수
Real number (ℝ)

ZEROS 

Distinct63
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3626667
Minimum0
Maximum396
Zeros2158
Zeros (%)71.9%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2023-12-12T18:10:44.652300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile9
Maximum396
Range396
Interquartile range (IQR)1

Descriptive statistics

Standard deviation13.295114
Coefficient of variation (CV)5.6271646
Kurtosis351.69348
Mean2.3626667
Median Absolute Deviation (MAD)0
Skewness15.765332
Sum7088
Variance176.76006
MonotonicityNot monotonic
2023-12-12T18:10:44.767663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2158
71.9%
1 306
 
10.2%
2 158
 
5.3%
3 80
 
2.7%
4 44
 
1.5%
5 32
 
1.1%
6 29
 
1.0%
7 21
 
0.7%
8 15
 
0.5%
10 12
 
0.4%
Other values (53) 145
 
4.8%
ValueCountFrequency (%)
0 2158
71.9%
1 306
 
10.2%
2 158
 
5.3%
3 80
 
2.7%
4 44
 
1.5%
5 32
 
1.1%
6 29
 
1.0%
7 21
 
0.7%
8 15
 
0.5%
9 11
 
0.4%
ValueCountFrequency (%)
396 1
< 0.1%
268 1
< 0.1%
183 1
< 0.1%
168 1
< 0.1%
163 1
< 0.1%
152 1
< 0.1%
121 1
< 0.1%
116 1
< 0.1%
112 1
< 0.1%
111 2
0.1%

무게
Real number (ℝ)

ZEROS 

Distinct63
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2169333
Minimum0
Maximum75.7
Zeros1227
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2023-12-12T18:10:44.889176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.2
Q35
95-th percentile14.91
Maximum75.7
Range75.7
Interquartile range (IQR)5

Descriptive statistics

Standard deviation10.799438
Coefficient of variation (CV)2.5609697
Kurtosis25.314425
Mean4.2169333
Median Absolute Deviation (MAD)0.2
Skewness4.7286002
Sum12650.8
Variance116.62787
MonotonicityNot monotonic
2023-12-12T18:10:45.043926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1227
40.9%
0.2 272
 
9.1%
0.1 170
 
5.7%
0.4 80
 
2.7%
0.3 80
 
2.7%
0.8 42
 
1.4%
0.7 39
 
1.3%
1.7 38
 
1.3%
4.0 38
 
1.3%
5.8 38
 
1.3%
Other values (53) 976
32.5%
ValueCountFrequency (%)
0.0 1227
40.9%
0.1 170
 
5.7%
0.2 272
 
9.1%
0.3 80
 
2.7%
0.4 80
 
2.7%
0.5 5
 
0.2%
0.6 8
 
0.3%
0.7 39
 
1.3%
0.8 42
 
1.4%
0.9 38
 
1.3%
ValueCountFrequency (%)
75.7 37
1.2%
60.0 1
 
< 0.1%
49.7 37
1.2%
30.1 37
1.2%
15.2 1
 
< 0.1%
15.1 37
1.2%
14.9 1
 
< 0.1%
13.7 37
1.2%
13.4 1
 
< 0.1%
12.8 37
1.2%

Interactions

2023-12-12T18:10:42.195341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:41.391694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:41.820023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:42.322795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:41.533249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:41.926485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:42.466321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:41.700289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:10:42.072577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:10:45.150855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정 연도측정 차수정점명위도경도쓰레기 유형 대분류쓰레기 유형 중분류쓰레기 유형 소분류개수무게
측정 연도1.0000.0000.3440.3440.3440.0000.0000.0000.0000.301
측정 차수0.0001.0000.0000.0000.0000.0000.0000.0000.0160.340
정점명0.3440.0001.0001.0001.0000.1140.3850.0000.1280.342
위도0.3440.0001.0001.0001.0000.1140.3850.0000.1280.342
경도0.3440.0001.0001.0001.0000.1140.3850.0000.1280.342
쓰레기 유형 대분류0.0000.0000.1140.1140.1141.0001.000NaN0.3270.257
쓰레기 유형 중분류0.0000.0000.3850.3850.3851.0001.0001.0000.0000.196
쓰레기 유형 소분류0.0000.0000.0000.0000.000NaN1.0001.0000.2840.000
개수0.0000.0160.1280.1280.1280.3270.0000.2841.0000.000
무게0.3010.3400.3420.3420.3420.2570.1960.0000.0001.000
2023-12-12T18:10:45.280620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
쓰레기 유형 대분류정점명경도측정 연도위도쓰레기 유형 소분류쓰레기 유형 중분류
쓰레기 유형 대분류1.0000.0500.0500.0000.0501.0000.996
정점명0.0501.0001.0000.3331.0000.0000.217
경도0.0501.0001.0000.3331.0000.0000.217
측정 연도0.0000.3330.3331.0000.3330.0000.000
위도0.0501.0001.0000.3331.0000.0000.217
쓰레기 유형 소분류1.0000.0000.0000.0000.0001.0000.992
쓰레기 유형 중분류0.9960.2170.2170.0000.2170.9921.000
2023-12-12T18:10:45.439054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정 차수개수무게측정 연도정점명위도경도쓰레기 유형 대분류쓰레기 유형 중분류쓰레기 유형 소분류
측정 차수1.000-0.0120.0770.0000.0000.0000.0000.0000.0000.000
개수-0.0121.0000.3020.0000.0860.0860.0860.1790.0000.147
무게0.0770.3021.0000.2110.2450.2450.2450.1380.0980.000
측정 연도0.0000.0000.2111.0000.3330.3330.3330.0000.0000.000
정점명0.0000.0860.2450.3331.0001.0001.0000.0500.2170.000
위도0.0000.0860.2450.3331.0001.0001.0000.0500.2170.000
경도0.0000.0860.2450.3331.0001.0001.0000.0500.2170.000
쓰레기 유형 대분류0.0000.1790.1380.0000.0500.0500.0501.0000.9961.000
쓰레기 유형 중분류0.0000.0000.0980.0000.2170.2170.2170.9961.0000.992
쓰레기 유형 소분류0.0000.1470.0000.0000.0000.0000.0001.0000.9921.000

Missing values

2023-12-12T18:10:42.628883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:10:42.841303image/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

측정 연도측정 차수정점명위도경도쓰레기 유형 대분류쓰레기 유형 중분류쓰레기 유형 소분류개수무게
020181제주 사계리33.222638126.296772플라스틱필름형필름형 풍선00.0
120182제주 사계리33.222638126.296772플라스틱필름형필름형 풍선00.0
220183제주 사계리33.222638126.296772플라스틱필름형필름형 풍선00.0
320184제주 사계리33.222638126.296772플라스틱필름형필름형 풍선01.3
420185제주 사계리33.222638126.296772플라스틱필름형필름형 풍선00.8
520186제주 사계리33.222638126.296772플라스틱필름형필름형 풍선00.0
620181제주 사계리33.222638126.296772플라스틱필름형필름형 파편00.0
720182제주 사계리33.222638126.296772플라스틱필름형필름형 파편00.0
820183제주 사계리33.222638126.296772플라스틱필름형필름형 파편00.0
920184제주 사계리33.222638126.296772플라스틱필름형필름형 파편01.3
측정 연도측정 차수정점명위도경도쓰레기 유형 대분류쓰레기 유형 중분류쓰레기 유형 소분류개수무게
299020213제주 김녕리33.565625126.76504플라스틱필름형필름형 파편04.0
299120214제주 김녕리33.565625126.76504플라스틱필름형필름형 파편00.7
299220215제주 김녕리33.565625126.76504플라스틱필름형필름형 파편10.4
299320216제주 김녕리33.565625126.76504플라스틱필름형필름형 파편05.6
299420211제주 김녕리33.565625126.76504플라스틱필름형필름형 풍선275.7
299520212제주 김녕리33.565625126.76504플라스틱필름형필름형 풍선011.3
299620213제주 김녕리33.565625126.76504플라스틱필름형필름형 풍선04.0
299720214제주 김녕리33.565625126.76504플라스틱필름형필름형 풍선00.7
299820215제주 김녕리33.565625126.76504플라스틱필름형필름형 풍선00.4
299920216제주 김녕리33.565625126.76504플라스틱필름형필름형 풍선05.6