Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells1724
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory732.4 KiB
Average record size in memory75.0 B

Variable types

Numeric2
Categorical5
Text1

Dataset

Description전국, 지역별 정점별 해양쓰레기의 양과 종류 파악을 통해 정책 수립, 외국기인 해양쓰레기 분석 등 과학적 대응의 근거를 마련하기 위한 조사 자료(2008~2017)
Author해양환경공단
URLhttps://www.data.go.kr/data/15044009/fileData.do

Alerts

단체 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 단체High correlation
번호 is highly overall correlated with 연도High correlation
연도 is highly overall correlated with 번호High correlation
개수 has 1724 (17.2%) missing valuesMissing
개수 is highly skewed (γ1 = 22.65185745)Skewed
개수 has 5405 (54.0%) zerosZeros

Reproduction

Analysis started2023-12-12 23:29:55.412346
Analysis finished2023-12-12 23:29:56.970771
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION 

Distinct953
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1132.7773
Minimum603
Maximum1692
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:29:57.092596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum603
5-th percentile680
Q1892
median1140
Q31376
95-th percentile1566
Maximum1692
Range1089
Interquartile range (IQR)484

Descriptive statistics

Standard deviation282.77276
Coefficient of variation (CV)0.24962785
Kurtosis-1.1489656
Mean1132.7773
Median Absolute Deviation (MAD)242
Skewness-0.053663438
Sum11327773
Variance79960.436
MonotonicityNot monotonic
2023-12-13T08:29:57.246415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
848 22
 
0.2%
1567 21
 
0.2%
1077 20
 
0.2%
936 20
 
0.2%
682 19
 
0.2%
1148 19
 
0.2%
1397 19
 
0.2%
993 18
 
0.2%
780 18
 
0.2%
859 18
 
0.2%
Other values (943) 9806
98.1%
ValueCountFrequency (%)
603 12
0.1%
604 10
0.1%
605 12
0.1%
606 15
0.1%
607 11
0.1%
609 16
0.2%
612 12
0.1%
615 16
0.2%
616 6
 
0.1%
617 7
0.1%
ValueCountFrequency (%)
1692 13
0.1%
1691 10
0.1%
1614 6
 
0.1%
1613 14
0.1%
1612 10
0.1%
1611 12
0.1%
1610 9
0.1%
1609 11
0.1%
1608 15
0.1%
1607 6
 
0.1%

연도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2017
2557 
2016
2536 
2015
2456 
2014
1684 
2013
767 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2015
3rd row2017
4th row2016
5th row2015

Common Values

ValueCountFrequency (%)
2017 2557
25.6%
2016 2536
25.4%
2015 2456
24.6%
2014 1684
16.8%
2013 767
 
7.7%

Length

2023-12-13T08:29:57.397977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:29:57.503669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 2557
25.6%
2016 2536
25.4%
2015 2456
24.6%
2014 1684
16.8%
2013 767
 
7.7%

단체
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
구조단 보령지역대
1062 
자연사랑메아리
934 
구조단 고흥지역대
 
542
제주환경운동연합
 
521
광양만권 환경연구소
 
518
Other values (22)
6423 

Length

Max length14
Median length12
Mean length8.6578
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해양소년단 경남남부연맹
2nd row광양만권 환경연구소
3rd row울진바다지킴이
4th row신안섬갯벌연구소
5th row해양구조협회 진주사천지역대

Common Values

ValueCountFrequency (%)
구조단 보령지역대 1062
 
10.6%
자연사랑메아리 934
 
9.3%
구조단 고흥지역대 542
 
5.4%
제주환경운동연합 521
 
5.2%
광양만권 환경연구소 518
 
5.2%
구조단 본부대 501
 
5.0%
포항환경감시연합 491
 
4.9%
시흥환경운동연합 481
 
4.8%
강화도시민연대 457
 
4.6%
신안섬갯벌연구소 451
 
4.5%
Other values (17) 4042
40.4%

Length

2023-12-13T08:29:57.631593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구조단 3187
21.7%
보령지역대 1062
 
7.2%
자연사랑메아리 934
 
6.4%
해양구조협회 673
 
4.6%
고흥지역대 542
 
3.7%
제주환경운동연합 521
 
3.6%
광양만권 518
 
3.5%
환경연구소 518
 
3.5%
본부대 501
 
3.4%
포항환경감시연합 491
 
3.3%
Other values (21) 5725
39.0%

지역
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
울진 후정
 
359
마산 봉암갯벌
 
334
고흥 신흥
 
321
부산 해양대
 
315
사천 아두도
 
310
Other values (36)
8361 

Length

Max length13
Median length11
Mean length7.0071
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row통영 망일봉
2nd row여수 백야도해변
3rd row울진 후정
4th row신안 고장리해변
5th row남해 유구해변

Common Values

ValueCountFrequency (%)
울진 후정 359
 
3.6%
마산 봉암갯벌 334
 
3.3%
고흥 신흥 321
 
3.2%
부산 해양대 315
 
3.1%
사천 아두도 310
 
3.1%
포항 칠포 300
 
3.0%
강릉 송정 300
 
3.0%
울산 대왕암 299
 
3.0%
순천 반월 299
 
3.0%
통영 망일봉 294
 
2.9%
Other values (31) 6869
68.7%

Length

2023-12-13T08:29:57.778630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해남 704
 
3.3%
인천 618
 
2.9%
고흥 542
 
2.6%
제주 521
 
2.5%
포항 491
 
2.3%
태안 473
 
2.3%
신안 451
 
2.1%
후정 359
 
1.7%
울진 359
 
1.7%
마산 334
 
1.6%
Other values (67) 16165
76.9%

차수
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
5차
1826 
6차
1718 
1차
1653 
3차
1643 
2차
1633 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4차
2nd row1차
3rd row5차
4th row1차
5th row6차

Common Values

ValueCountFrequency (%)
5차 1826
18.3%
6차 1718
17.2%
1차 1653
16.5%
3차 1643
16.4%
2차 1633
16.3%
4차 1527
15.3%

Length

2023-12-13T08:29:57.973702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:29:58.100894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5차 1826
18.3%
6차 1718
17.2%
1차 1653
16.5%
3차 1643
16.4%
2차 1633
16.3%
4차 1527
15.3%

유형
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
플라스틱류
3242 
외국기인
1200 
금속
1031 
나무
807 
기타
791 
Other values (7)
2929 

Length

Max length10
Median length9
Mean length4.0452
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고무
2nd row유리
3rd row플라스틱류
4th row플라스틱류
5th row기타

Common Values

ValueCountFrequency (%)
플라스틱류 3242
32.4%
외국기인 1200
 
12.0%
금속 1031
 
10.3%
나무 807
 
8.1%
기타 791
 
7.9%
스티로폼 571
 
5.7%
유리 492
 
4.9%
의류 및 천 434
 
4.3%
고무 398
 
4.0%
흡연 / 불꽃 놀이 373
 
3.7%
Other values (2) 661
 
6.6%

Length

2023-12-13T08:29:58.268112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
플라스틱류 3242
25.5%
외국기인 1200
 
9.5%
금속 1031
 
8.1%
나무 807
 
6.4%
기타 791
 
6.2%
및 786
 
6.2%
스티로폼 571
 
4.5%
유리 492
 
3.9%
천 434
 
3.4%
의류 434
 
3.4%
Other values (8) 2903
22.9%

상세유형
Text

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T08:29:58.624841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length23
Mean length12.2738
Min length2

Characters and Unicode

Total characters122738
Distinct characters237
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고무장갑(가정용)
2nd row전구,형광등(일반형)
3rd row어망 (50cm 이상)
4th row6개들이 포장고리
5th row가전(냉장고, TV..)
ValueCountFrequency (%)
등 2218
 
9.1%
기타 924
 
3.8%
이상 710
 
2.9%
50cm 615
 
2.5%
2.5~50cm 466
 
1.9%
플라스틱 424
 
1.7%
플라스틱부표 401
 
1.6%
부표 288
 
1.2%
스티로폼 270
 
1.1%
포함 212
 
0.9%
Other values (166) 17914
73.3%
2023-12-13T08:29:59.081210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14742
 
12.0%
, 6872
 
5.6%
( 4103
 
3.3%
) 4103
 
3.3%
용 3267
 
2.7%
장 2541
 
2.1%
기 2465
 
2.0%
이 2415
 
2.0%
등 2403
 
2.0%
스 2401
 
2.0%
Other values (227) 77426
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83087
67.7%
Space Separator 14742
 
12.0%
Other Punctuation 9391
 
7.7%
Open Punctuation 4103
 
3.3%
Close Punctuation 4103
 
3.3%
Decimal Number 3918
 
3.2%
Lowercase Letter 2538
 
2.1%
Math Symbol 559
 
0.5%
Uppercase Letter 206
 
0.2%
Dash Punctuation 91
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 3267
 
3.9%
장 2541
 
3.1%
기 2465
 
3.0%
이 2415
 
2.9%
등 2403
 
2.9%
스 2401
 
2.9%
라 1704
 
2.1%
포 1511
 
1.8%
틱 1312
 
1.6%
플 1312
 
1.6%
Other values (210) 61756
74.3%
Decimal Number
ValueCountFrequency (%)
5 1828
46.7%
0 1174
30.0%
2 753
19.2%
1 85
 
2.2%
6 78
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 6872
73.2%
/ 1562
 
16.6%
. 957
 
10.2%
Lowercase Letter
ValueCountFrequency (%)
m 1269
50.0%
c 1269
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 103
50.0%
V 103
50.0%
Space Separator
ValueCountFrequency (%)
14742
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4103
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4103
100.0%
Math Symbol
ValueCountFrequency (%)
~ 559
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83087
67.7%
Common 36907
30.1%
Latin 2744
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 3267
 
3.9%
장 2541
 
3.1%
기 2465
 
3.0%
이 2415
 
2.9%
등 2403
 
2.9%
스 2401
 
2.9%
라 1704
 
2.1%
포 1511
 
1.8%
틱 1312
 
1.6%
플 1312
 
1.6%
Other values (210) 61756
74.3%
Common
ValueCountFrequency (%)
14742
39.9%
, 6872
18.6%
( 4103
 
11.1%
) 4103
 
11.1%
5 1828
 
5.0%
/ 1562
 
4.2%
0 1174
 
3.2%
. 957
 
2.6%
2 753
 
2.0%
~ 559
 
1.5%
Other values (3) 254
 
0.7%
Latin
ValueCountFrequency (%)
m 1269
46.2%
c 1269
46.2%
T 103
 
3.8%
V 103
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83087
67.7%
ASCII 39651
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14742
37.2%
, 6872
17.3%
( 4103
 
10.3%
) 4103
 
10.3%
5 1828
 
4.6%
/ 1562
 
3.9%
m 1269
 
3.2%
c 1269
 
3.2%
0 1174
 
3.0%
. 957
 
2.4%
Other values (7) 1772
 
4.5%
Hangul
ValueCountFrequency (%)
용 3267
 
3.9%
장 2541
 
3.1%
기 2465
 
3.0%
이 2415
 
2.9%
등 2403
 
2.9%
스 2401
 
2.9%
라 1704
 
2.1%
포 1511
 
1.8%
틱 1312
 
1.6%
플 1312
 
1.6%
Other values (210) 61756
74.3%

개수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct119
Distinct (%)1.4%
Missing1724
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean3.6951426
Minimum0
Maximum810
Zeros5405
Zeros (%)54.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:29:59.260903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile16
Maximum810
Range810
Interquartile range (IQR)2

Descriptive statistics

Standard deviation19.7861
Coefficient of variation (CV)5.3546243
Kurtosis761.28616
Mean3.6951426
Median Absolute Deviation (MAD)0
Skewness22.651857
Sum30581
Variance391.48977
MonotonicityNot monotonic
2023-12-13T08:29:59.442278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5405
54.0%
1 733
 
7.3%
2 469
 
4.7%
3 324
 
3.2%
4 177
 
1.8%
5 171
 
1.7%
6 105
 
1.1%
7 90
 
0.9%
8 86
 
0.9%
10 61
 
0.6%
Other values (109) 655
 
6.6%
(Missing) 1724
 
17.2%
ValueCountFrequency (%)
0 5405
54.0%
1 733
 
7.3%
2 469
 
4.7%
3 324
 
3.2%
4 177
 
1.8%
5 171
 
1.7%
6 105
 
1.1%
7 90
 
0.9%
8 86
 
0.9%
9 51
 
0.5%
ValueCountFrequency (%)
810 1
< 0.1%
800 1
< 0.1%
500 1
< 0.1%
436 1
< 0.1%
356 1
< 0.1%
312 1
< 0.1%
261 1
< 0.1%
242 1
< 0.1%
210 1
< 0.1%
205 1
< 0.1%

Interactions

2023-12-13T08:29:56.521667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:29:56.341223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:29:56.613469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:29:56.422239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:29:59.553539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호연도단체지역차수유형상세유형개수
번호1.0000.9970.4360.4910.6370.0000.0000.049
연도0.9971.0000.4200.4580.0960.0000.0000.026
단체0.4360.4201.0000.9990.0430.0000.0000.109
지역0.4910.4580.9991.0000.0540.0000.0000.061
차수0.6370.0960.0430.0541.0000.0000.0000.000
유형0.0000.0000.0000.0000.0001.0000.9990.020
상세유형0.0000.0000.0000.0000.0000.9991.0000.177
개수0.0490.0260.1090.0610.0000.0200.1771.000
2023-12-13T08:29:59.677779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차수단체연도지역유형
차수1.0000.0190.0650.0230.000
단체0.0191.0000.2150.9640.000
연도0.0650.2151.0000.2300.000
지역0.0230.9640.2301.0000.000
유형0.0000.0000.0000.0001.000
2023-12-13T08:30:00.122157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호개수연도단체지역차수유형
번호1.0000.1640.9200.1740.1910.4020.000
개수0.1641.0000.0160.0430.0220.0000.008
연도0.9200.0161.0000.2150.2300.0650.000
단체0.1740.0430.2151.0000.9640.0190.000
지역0.1910.0220.2300.9641.0000.0230.000
차수0.4020.0000.0650.0190.0231.0000.000
유형0.0000.0080.0000.0000.0000.0001.000

Missing values

2023-12-13T08:29:56.766445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:29:56.908010image/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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번호연도단체지역차수유형상세유형개수
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6854011202015신안섬갯벌연구소신안 임자도5차의류 및 천옷,신발, 모자, 장갑(목장갑 제외), 양말, 구두3
223714262017동해환경지킴이운동본부동해 노봉해변2차의류 및 천기타<NA>
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