Overview

Dataset statistics

Number of variables17
Number of observations4425
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory622.4 KiB
Average record size in memory144.0 B

Variable types

Numeric4
Categorical13

Dataset

DescriptionSample
Author(사)동아시아바다공동체오션
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT08OSN004

Alerts

DNF_SRC_NM has constant value ""Constant
CST_NM has constant value ""Constant
ADM_ZN_NM is highly overall correlated with INVS_AREA_NM and 4 other fieldsHigh correlation
STR_LA is highly overall correlated with INVS_AREA_NM and 4 other fieldsHigh correlation
QTMT_CD is highly overall correlated with QTMT_NM and 2 other fieldsHigh correlation
IEM_NM is highly overall correlated with QTMT_NM and 2 other fieldsHigh correlation
INVS_AREA_NM is highly overall correlated with ADM_ZN_NM and 4 other fieldsHigh correlation
END_LA is highly overall correlated with INVS_AREA_NM and 4 other fieldsHigh correlation
END_LO is highly overall correlated with INVS_AREA_NM and 4 other fieldsHigh correlation
IEM_CD is highly overall correlated with QTMT_NM and 2 other fieldsHigh correlation
QTMT_NM is highly overall correlated with IEM_NM and 2 other fieldsHigh correlation
STR_LO is highly overall correlated with INVS_AREA_NM and 4 other fieldsHigh correlation
INVS_YR is highly overall correlated with INVS_YMDHigh correlation
IEM_CNT is highly overall correlated with METER_PER_IEM_CNTHigh correlation
METER_PER_IEM_CNT is highly overall correlated with IEM_CNTHigh correlation
INVS_YMD is highly overall correlated with INVS_YRHigh correlation
IEM_CNT has 2737 (61.9%) zerosZeros
METER_PER_IEM_CNT has 2737 (61.9%) zerosZeros

Reproduction

Analysis started2024-03-13 12:46:57.011093
Analysis finished2024-03-13 12:47:02.115073
Duration5.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

INVS_YR
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.5763
Minimum2008
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2024-03-13T21:47:02.177867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12010
median2013
Q32015
95-th percentile2017
Maximum2017
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8359496
Coefficient of variation (CV)0.0014091141
Kurtosis-1.2094062
Mean2012.5763
Median Absolute Deviation (MAD)2
Skewness-0.012977445
Sum8905650
Variance8.0426104
MonotonicityIncreasing
2024-03-13T21:47:02.351887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2009 450
10.2%
2010 450
10.2%
2011 450
10.2%
2012 450
10.2%
2013 450
10.2%
2014 450
10.2%
2015 450
10.2%
2016 450
10.2%
2017 450
10.2%
2008 375
8.5%
ValueCountFrequency (%)
2008 375
8.5%
2009 450
10.2%
2010 450
10.2%
2011 450
10.2%
2012 450
10.2%
2013 450
10.2%
2014 450
10.2%
2015 450
10.2%
2016 450
10.2%
2017 450
10.2%
ValueCountFrequency (%)
2017 450
10.2%
2016 450
10.2%
2015 450
10.2%
2014 450
10.2%
2013 450
10.2%
2012 450
10.2%
2011 450
10.2%
2010 450
10.2%
2009 450
10.2%
2008 375
8.5%

INVS_DSRT
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
2차
750 
3차
750 
4차
750 
5차
750 
6차
750 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2차
2nd row2차
3rd row2차
4th row2차
5th row2차

Common Values

ValueCountFrequency (%)
2차 750
16.9%
3차 750
16.9%
4차 750
16.9%
5차 750
16.9%
6차 750
16.9%
1차 675
15.3%

Length

2024-03-13T21:47:02.518387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:02.697393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2차 750
16.9%
3차 750
16.9%
4차 750
16.9%
5차 750
16.9%
6차 750
16.9%
1차 675
15.3%

INVS_AREA_NM
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
울산 대왕암
885 
포항 칠포
885 
울진 후정
885 
강릉 송정
885 
속초 청초
885 

Length

Max length6
Median length5
Mean length5.2
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산 대왕암
2nd row울산 대왕암
3rd row울산 대왕암
4th row울산 대왕암
5th row울산 대왕암

Common Values

ValueCountFrequency (%)
울산 대왕암 885
20.0%
포항 칠포 885
20.0%
울진 후정 885
20.0%
강릉 송정 885
20.0%
속초 청초 885
20.0%

Length

2024-03-13T21:47:02.930757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:03.139346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산 885
10.0%
대왕암 885
10.0%
포항 885
10.0%
칠포 885
10.0%
울진 885
10.0%
후정 885
10.0%
강릉 885
10.0%
송정 885
10.0%
속초 885
10.0%
청초 885
10.0%

DNF_SRC_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
국내기인
4425 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내기인 4425
100.0%

Length

2024-03-13T21:47:03.372006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:03.528952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내기인 4425
100.0%

QTMT_NM
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
플라스틱류
3245 
금속
590 
고무
 
295
의료 및 개인위생
 
295

Length

Max length9
Median length5
Mean length4.6666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
플라스틱류 3245
73.3%
금속 590
 
13.3%
고무 295
 
6.7%
의료 및 개인위생 295
 
6.7%

Length

2024-03-13T21:47:04.092548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:04.290878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
플라스틱류 3245
64.7%
금속 590
 
11.8%
고무 295
 
5.9%
의료 295
 
5.9%
및 295
 
5.9%
개인위생 295
 
5.9%

IEM_NM
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
비닐봉투, 비닐쇼핑백 등
 
295
6개들이 포장고리
 
295
장어/문어 통발
 
295
어망(2.5~50cm)
 
295
어망 (50cm 이상)
 
295
Other values (10)
2950 

Length

Max length22
Median length15
Mean length11.133333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비닐봉투, 비닐쇼핑백 등
2nd row6개들이 포장고리
3rd row장어/문어 통발
4th row어망(2.5~50cm)
5th row어망 (50cm 이상)

Common Values

ValueCountFrequency (%)
비닐봉투, 비닐쇼핑백 등 295
 
6.7%
6개들이 포장고리 295
 
6.7%
장어/문어 통발 295
 
6.7%
어망(2.5~50cm) 295
 
6.7%
어망 (50cm 이상) 295
 
6.7%
밧줄/로프 (2.5~50cm) 295
 
6.7%
밧줄/로프 (50cm 이상) 295
 
6.7%
끈(플라스틱, 노끈) (2.5~50cm) 295
 
6.7%
끈(플라스틱, 노끈) (50cm 이상) 295
 
6.7%
낚시줄 295
 
6.7%
Other values (5) 1475
33.3%

Length

2024-03-13T21:47:04.506554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
50cm 885
 
9.4%
이상 885
 
9.4%
2.5~50cm 590
 
6.2%
노끈 590
 
6.2%
밧줄/로프 590
 
6.2%
끈(플라스틱 590
 
6.2%
풍선 295
 
3.1%
스프링통발(그물포함 295
 
3.1%
낚싯바늘 295
 
3.1%
낚시추 295
 
3.1%
Other values (14) 4130
43.8%

IEM_CNT
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct110
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0662147
Minimum0
Maximum312
Zeros2737
Zeros (%)61.9%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2024-03-13T21:47:04.725386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile32
Maximum312
Range312
Interquartile range (IQR)3

Descriptive statistics

Standard deviation19.297739
Coefficient of variation (CV)3.1811829
Kurtosis70.51576
Mean6.0662147
Median Absolute Deviation (MAD)0
Skewness6.9822395
Sum26843
Variance372.40271
MonotonicityNot monotonic
2024-03-13T21:47:04.939917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2737
61.9%
1 305
 
6.9%
2 200
 
4.5%
3 159
 
3.6%
5 110
 
2.5%
4 82
 
1.9%
7 62
 
1.4%
10 59
 
1.3%
8 54
 
1.2%
6 53
 
1.2%
Other values (100) 604
 
13.6%
ValueCountFrequency (%)
0 2737
61.9%
1 305
 
6.9%
2 200
 
4.5%
3 159
 
3.6%
4 82
 
1.9%
5 110
 
2.5%
6 53
 
1.2%
7 62
 
1.4%
8 54
 
1.2%
9 25
 
0.6%
ValueCountFrequency (%)
312 1
< 0.1%
310 1
< 0.1%
306 1
< 0.1%
226 1
< 0.1%
210 1
< 0.1%
206 1
< 0.1%
192 1
< 0.1%
190 1
< 0.1%
188 1
< 0.1%
169 1
< 0.1%

METER_PER_IEM_CNT
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct110
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.060662147
Minimum0
Maximum3.12
Zeros2737
Zeros (%)61.9%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2024-03-13T21:47:05.162625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.03
95-th percentile0.32
Maximum3.12
Range3.12
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.19297739
Coefficient of variation (CV)3.1811829
Kurtosis70.51576
Mean0.060662147
Median Absolute Deviation (MAD)0
Skewness6.9822395
Sum268.43
Variance0.037240271
MonotonicityNot monotonic
2024-03-13T21:47:05.382205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2737
61.9%
0.01 305
 
6.9%
0.02 200
 
4.5%
0.03 159
 
3.6%
0.05 110
 
2.5%
0.04 82
 
1.9%
0.07 62
 
1.4%
0.1 59
 
1.3%
0.08 54
 
1.2%
0.06 53
 
1.2%
Other values (100) 604
 
13.6%
ValueCountFrequency (%)
0.0 2737
61.9%
0.01 305
 
6.9%
0.02 200
 
4.5%
0.03 159
 
3.6%
0.04 82
 
1.9%
0.05 110
 
2.5%
0.06 53
 
1.2%
0.07 62
 
1.4%
0.08 54
 
1.2%
0.09 25
 
0.6%
ValueCountFrequency (%)
3.12 1
< 0.1%
3.1 1
< 0.1%
3.06 1
< 0.1%
2.26 1
< 0.1%
2.1 1
< 0.1%
2.06 1
< 0.1%
1.92 1
< 0.1%
1.9 1
< 0.1%
1.88 1
< 0.1%
1.69 1
< 0.1%

ADM_ZN_NM
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
경북
1770 
강원
1770 
울산
885 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경북 1770
40.0%
강원 1770
40.0%
울산 885
20.0%

Length

2024-03-13T21:47:05.671248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:05.835333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경북 1770
40.0%
강원 1770
40.0%
울산 885
20.0%

QTMT_CD
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
PL
3245 
ME
590 
RB
 
295
MH
 
295

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PL 3245
73.3%
ME 590
 
13.3%
RB 295
 
6.7%
MH 295
 
6.7%

Length

2024-03-13T21:47:05.992099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:06.122433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pl 3245
73.3%
me 590
 
13.3%
rb 295
 
6.7%
mh 295
 
6.7%

IEM_CD
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
PL_1_01
 
295
PL_1_07
 
295
PL_1_15
 
295
PL_1_16
 
295
PL_1_17
 
295
Other values (10)
2950 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPL_1_01
2nd rowPL_1_07
3rd rowPL_1_15
4th rowPL_1_16
5th rowPL_1_17

Common Values

ValueCountFrequency (%)
PL_1_01 295
 
6.7%
PL_1_07 295
 
6.7%
PL_1_15 295
 
6.7%
PL_1_16 295
 
6.7%
PL_1_17 295
 
6.7%
PL_1_20 295
 
6.7%
PL_1_21 295
 
6.7%
PL_1_22 295
 
6.7%
PL_1_23 295
 
6.7%
PL_1_30 295
 
6.7%
Other values (5) 1475
33.3%

Length

2024-03-13T21:47:06.295612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pl_1_01 295
 
6.7%
pl_1_07 295
 
6.7%
pl_1_15 295
 
6.7%
pl_1_16 295
 
6.7%
pl_1_17 295
 
6.7%
pl_1_20 295
 
6.7%
pl_1_21 295
 
6.7%
pl_1_22 295
 
6.7%
pl_1_23 295
 
6.7%
pl_1_30 295
 
6.7%
Other values (5) 1475
33.3%

INVS_YMD
Real number (ℝ)

HIGH CORRELATION 

Distinct223
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20126428
Minimum20080328
Maximum20171126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2024-03-13T21:47:06.461598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080328
5-th percentile20080802
Q120100801
median20130203
Q320150725
95-th percentile20170724
Maximum20171126
Range90798
Interquartile range (IQR)49924

Descriptive statistics

Standard deviation28345.308
Coefficient of variation (CV)0.0014083625
Kurtosis-1.210916
Mean20126428
Median Absolute Deviation (MAD)20925
Skewness-0.012085302
Sum8.9059446 × 1010
Variance8.0345647 × 108
MonotonicityNot monotonic
2024-03-13T21:47:06.689263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080926 45
 
1.0%
20160326 45
 
1.0%
20120602 45
 
1.0%
20120729 45
 
1.0%
20170730 45
 
1.0%
20090926 45
 
1.0%
20140330 45
 
1.0%
20170205 45
 
1.0%
20100131 45
 
1.0%
20100529 45
 
1.0%
Other values (213) 3975
89.8%
ValueCountFrequency (%)
20080328 30
0.7%
20080401 15
0.3%
20080403 15
0.3%
20080405 15
0.3%
20080529 15
0.3%
20080530 15
0.3%
20080601 30
0.7%
20080604 15
0.3%
20080726 15
0.3%
20080731 15
0.3%
ValueCountFrequency (%)
20171126 30
0.7%
20171125 30
0.7%
20171120 15
 
0.3%
20171001 15
 
0.3%
20170930 15
 
0.3%
20170924 15
 
0.3%
20170923 15
 
0.3%
20170921 15
 
0.3%
20170826 15
 
0.3%
20170730 45
1.0%

CST_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
동해안
4425 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동해안 4425
100.0%

Length

2024-03-13T21:47:06.872675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:07.004679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동해안 4425
100.0%

STR_LA
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
35.490138
885 
36.133848
885 
37.070654
885 
37.780347
885 
38.200627
885 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35.490138
2nd row35.490138
3rd row35.490138
4th row35.490138
5th row35.490138

Common Values

ValueCountFrequency (%)
35.490138 885
20.0%
36.133848 885
20.0%
37.070654 885
20.0%
37.780347 885
20.0%
38.200627 885
20.0%

Length

2024-03-13T21:47:07.150980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:07.329418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
35.490138 885
20.0%
36.133848 885
20.0%
37.070654 885
20.0%
37.780347 885
20.0%
38.200627 885
20.0%

STR_LO
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
129.439721
885 
129.398305
885 
129.415776
885 
128.937288
885 
128.597016
885 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row129.439721
2nd row129.439721
3rd row129.439721
4th row129.439721
5th row129.439721

Common Values

ValueCountFrequency (%)
129.439721 885
20.0%
129.398305 885
20.0%
129.415776 885
20.0%
128.937288 885
20.0%
128.597016 885
20.0%

Length

2024-03-13T21:47:07.509518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:07.639916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
129.439721 885
20.0%
129.398305 885
20.0%
129.415776 885
20.0%
128.937288 885
20.0%
128.597016 885
20.0%

END_LA
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
35.490602
885 
36.134681
885 
37.07136
885 
37.780843
885 
38.198843
885 

Length

Max length9
Median length9
Mean length8.8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35.490602
2nd row35.490602
3rd row35.490602
4th row35.490602
5th row35.490602

Common Values

ValueCountFrequency (%)
35.490602 885
20.0%
36.134681 885
20.0%
37.07136 885
20.0%
37.780843 885
20.0%
38.198843 885
20.0%

Length

2024-03-13T21:47:07.880641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:08.118457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
35.490602 885
20.0%
36.134681 885
20.0%
37.07136 885
20.0%
37.780843 885
20.0%
38.198843 885
20.0%

END_LO
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
129.440027
885 
129.397533
885 
129.414542
885 
128.936559
885 
128.597144
885 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row129.440027
2nd row129.440027
3rd row129.440027
4th row129.440027
5th row129.440027

Common Values

ValueCountFrequency (%)
129.440027 885
20.0%
129.397533 885
20.0%
129.414542 885
20.0%
128.936559 885
20.0%
128.597144 885
20.0%

Length

2024-03-13T21:47:08.286587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:08.449484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
129.440027 885
20.0%
129.397533 885
20.0%
129.414542 885
20.0%
128.936559 885
20.0%
128.597144 885
20.0%

Interactions

2024-03-13T21:47:01.045908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:46:59.414887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:46:59.983312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.441203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:01.205932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:46:59.538579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.085901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.588189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:01.329981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:46:59.679754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.193765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.725148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:01.465369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:46:59.863796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.328285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:00.870533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:47:08.570114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
INVS_YRINVS_DSRTINVS_AREA_NMQTMT_NMIEM_NMIEM_CNTMETER_PER_IEM_CNTADM_ZN_NMQTMT_CDIEM_CDINVS_YMDSTR_LASTR_LOEND_LAEND_LO
INVS_YR1.0000.0000.0000.0000.0000.0890.0840.0000.0000.0001.0000.0000.0000.0000.000
INVS_DSRT0.0001.0000.0000.0000.0000.0070.0000.0000.0000.0000.0750.0000.0000.0000.000
INVS_AREA_NM0.0000.0001.0000.0000.0000.1310.1311.0000.0000.0000.0001.0001.0001.0001.000
QTMT_NM0.0000.0000.0001.0001.0000.1080.1080.0001.0001.0000.0000.0000.0000.0000.000
IEM_NM0.0000.0000.0001.0001.0000.3520.3520.0001.0001.0000.0000.0000.0000.0000.000
IEM_CNT0.0890.0070.1310.1080.3521.0001.0000.0890.1080.3520.0600.1310.1310.1310.131
METER_PER_IEM_CNT0.0840.0000.1310.1080.3521.0001.0000.0880.1080.3520.0570.1310.1310.1310.131
ADM_ZN_NM0.0000.0001.0000.0000.0000.0890.0881.0000.0000.0000.0001.0001.0001.0001.000
QTMT_CD0.0000.0000.0001.0001.0000.1080.1080.0001.0001.0000.0000.0000.0000.0000.000
IEM_CD0.0000.0000.0001.0001.0000.3520.3520.0001.0001.0000.0000.0000.0000.0000.000
INVS_YMD1.0000.0750.0000.0000.0000.0600.0570.0000.0000.0001.0000.0000.0000.0000.000
STR_LA0.0000.0001.0000.0000.0000.1310.1311.0000.0000.0000.0001.0001.0001.0001.000
STR_LO0.0000.0001.0000.0000.0000.1310.1311.0000.0000.0000.0001.0001.0001.0001.000
END_LA0.0000.0001.0000.0000.0000.1310.1311.0000.0000.0000.0001.0001.0001.0001.000
END_LO0.0000.0001.0000.0000.0000.1310.1311.0000.0000.0000.0001.0001.0001.0001.000
2024-03-13T21:47:08.762476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ADM_ZN_NMSTR_LAQTMT_CDIEM_NMINVS_AREA_NMEND_LAEND_LOIEM_CDQTMT_NMSTR_LOINVS_DSRT
ADM_ZN_NM1.0001.0000.0000.0001.0001.0001.0000.0000.0001.0000.000
STR_LA1.0001.0000.0000.0001.0001.0001.0000.0000.0001.0000.000
QTMT_CD0.0000.0001.0000.9990.0000.0000.0000.9991.0000.0000.000
IEM_NM0.0000.0000.9991.0000.0000.0000.0001.0000.9990.0000.000
INVS_AREA_NM1.0001.0000.0000.0001.0001.0001.0000.0000.0001.0000.000
END_LA1.0001.0000.0000.0001.0001.0001.0000.0000.0001.0000.000
END_LO1.0001.0000.0000.0001.0001.0001.0000.0000.0001.0000.000
IEM_CD0.0000.0000.9991.0000.0000.0000.0001.0000.9990.0000.000
QTMT_NM0.0000.0001.0000.9990.0000.0000.0000.9991.0000.0000.000
STR_LO1.0001.0000.0000.0001.0001.0001.0000.0000.0001.0000.000
INVS_DSRT0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000
2024-03-13T21:47:08.985778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
INVS_YRIEM_CNTMETER_PER_IEM_CNTINVS_YMDINVS_DSRTINVS_AREA_NMQTMT_NMIEM_NMADM_ZN_NMQTMT_CDIEM_CDSTR_LASTR_LOEND_LAEND_LO
INVS_YR1.0000.0290.0290.9950.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
IEM_CNT0.0291.0001.0000.0310.0030.0760.0690.1510.0390.0690.1510.0760.0760.0760.076
METER_PER_IEM_CNT0.0291.0001.0000.0310.0030.0760.0690.1510.0390.0690.1510.0760.0760.0760.076
INVS_YMD0.9950.0310.0311.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
INVS_DSRT0.0360.0030.0030.0361.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
INVS_AREA_NM0.0000.0760.0760.0000.0001.0000.0000.0001.0000.0000.0001.0001.0001.0001.000
QTMT_NM0.0000.0690.0690.0000.0000.0001.0000.9990.0001.0000.9990.0000.0000.0000.000
IEM_NM0.0000.1510.1510.0000.0000.0000.9991.0000.0000.9991.0000.0000.0000.0000.000
ADM_ZN_NM0.0000.0390.0390.0000.0001.0000.0000.0001.0000.0000.0001.0001.0001.0001.000
QTMT_CD0.0000.0690.0690.0000.0000.0001.0000.9990.0001.0000.9990.0000.0000.0000.000
IEM_CD0.0000.1510.1510.0000.0000.0000.9991.0000.0000.9991.0000.0000.0000.0000.000
STR_LA0.0000.0760.0760.0000.0001.0000.0000.0001.0000.0000.0001.0001.0001.0001.000
STR_LO0.0000.0760.0760.0000.0001.0000.0000.0001.0000.0000.0001.0001.0001.0001.000
END_LA0.0000.0760.0760.0000.0001.0000.0000.0001.0000.0000.0001.0001.0001.0001.000
END_LO0.0000.0760.0760.0000.0001.0000.0000.0001.0000.0000.0001.0001.0001.0001.000

Missing values

2024-03-13T21:47:01.654520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:47:01.972878image/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

INVS_YRINVS_DSRTINVS_AREA_NMDNF_SRC_NMQTMT_NMIEM_NMIEM_CNTMETER_PER_IEM_CNTADM_ZN_NMQTMT_CDIEM_CDINVS_YMDCST_NMSTR_LASTR_LOEND_LAEND_LO
020082차울산 대왕암국내기인플라스틱류비닐봉투, 비닐쇼핑백 등470.47울산PLPL_1_0120080328동해안35.490138129.43972135.490602129.440027
120082차울산 대왕암국내기인플라스틱류6개들이 포장고리00.0울산PLPL_1_0720080328동해안35.490138129.43972135.490602129.440027
220082차울산 대왕암국내기인플라스틱류장어/문어 통발00.0울산PLPL_1_1520080328동해안35.490138129.43972135.490602129.440027
320082차울산 대왕암국내기인플라스틱류어망(2.5~50cm)00.0울산PLPL_1_1620080328동해안35.490138129.43972135.490602129.440027
420082차울산 대왕암국내기인플라스틱류어망 (50cm 이상)00.0울산PLPL_1_1720080328동해안35.490138129.43972135.490602129.440027
520082차울산 대왕암국내기인플라스틱류밧줄/로프 (2.5~50cm)20.02울산PLPL_1_2020080328동해안35.490138129.43972135.490602129.440027
620082차울산 대왕암국내기인플라스틱류밧줄/로프 (50cm 이상)00.0울산PLPL_1_2120080328동해안35.490138129.43972135.490602129.440027
720082차울산 대왕암국내기인플라스틱류끈(플라스틱, 노끈) (2.5~50cm)10.01울산PLPL_1_2220080328동해안35.490138129.43972135.490602129.440027
820082차울산 대왕암국내기인플라스틱류끈(플라스틱, 노끈) (50cm 이상)00.0울산PLPL_1_2320080328동해안35.490138129.43972135.490602129.440027
920082차울산 대왕암국내기인플라스틱류낚시줄50.05울산PLPL_1_3020080328동해안35.490138129.43972135.490602129.440027
INVS_YRINVS_DSRTINVS_AREA_NMDNF_SRC_NMQTMT_NMIEM_NMIEM_CNTMETER_PER_IEM_CNTADM_ZN_NMQTMT_CDIEM_CDINVS_YMDCST_NMSTR_LASTR_LOEND_LAEND_LO
441520176차속초 청초국내기인플라스틱류밧줄/로프 (2.5~50cm)120.12강원PLPL_1_2020171126동해안38.200627128.59701638.198843128.597144
441620176차속초 청초국내기인플라스틱류밧줄/로프 (50cm 이상)00.0강원PLPL_1_2120171126동해안38.200627128.59701638.198843128.597144
441720176차속초 청초국내기인플라스틱류끈(플라스틱, 노끈) (2.5~50cm)00.0강원PLPL_1_2220171126동해안38.200627128.59701638.198843128.597144
441820176차속초 청초국내기인플라스틱류끈(플라스틱, 노끈) (50cm 이상)00.0강원PLPL_1_2320171126동해안38.200627128.59701638.198843128.597144
441920176차속초 청초국내기인플라스틱류낚시줄00.0강원PLPL_1_3020171126동해안38.200627128.59701638.198843128.597144
442020176차속초 청초국내기인플라스틱류가짜미끼, 형광찌130.13강원PLPL_1_3120171126동해안38.200627128.59701638.198843128.597144
442120176차속초 청초국내기인금속납 낚시추, 낚싯바늘00.0강원MEME_1_0620171126동해안38.200627128.59701638.198843128.597144
442220176차속초 청초국내기인금속스프링통발(그물포함)00.0강원MEME_1_0720171126동해안38.200627128.59701638.198843128.597144
442320176차속초 청초국내기인고무풍선00.0강원RBRB_1_0220171126동해안38.200627128.59701638.198843128.597144
442420176차속초 청초국내기인의료 및 개인위생주사기00.0강원MHMH_1_0220171126동해안38.200627128.59701638.198843128.597144