Overview

Dataset statistics

Number of variables4
Number of observations830
Missing cells20
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.3 KiB
Average record size in memory36.2 B

Variable types

Numeric4

Dataset

DescriptionSample
Author㈜해양정보기술
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT04MIT006

Alerts

WTCH_WVHGH is highly overall correlated with WTCH_WVPDHigh correlation
WTCH_WVPD is highly overall correlated with WTCH_WVHGHHigh correlation
WTCH_WVHGH has 10 (1.2%) missing valuesMissing
WTCH_WVPD has 10 (1.2%) missing valuesMissing
OVT_OCCR_YMDHMS has unique valuesUnique
OVT_CNTE_MIN has 697 (84.0%) zerosZeros

Reproduction

Analysis started2024-03-13 12:30:07.642733
Analysis finished2024-03-13 12:30:11.737391
Duration4.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

OVT_OCCR_YMDHMS
Real number (ℝ)

UNIQUE 

Distinct830
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0220156 × 1013
Minimum2.0220104 × 1013
Maximum2.0220308 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.4 KiB
2024-03-13T21:30:11.844186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0220104 × 1013
5-th percentile2.0220106 × 1013
Q12.0220113 × 1013
median2.0220121 × 1013
Q32.022013 × 1013
95-th percentile2.0220306 × 1013
Maximum2.0220308 × 1013
Range2.0389 × 108
Interquartile range (IQR)17065000

Descriptive statistics

Standard deviation75730772
Coefficient of variation (CV)3.7453109 × 10-6
Kurtosis0.083149538
Mean2.0220156 × 1013
Median Absolute Deviation (MAD)8870000
Skewness1.424639
Sum1.678273 × 1016
Variance5.7351499 × 1015
MonotonicityStrictly increasing
2024-03-13T21:30:12.119582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20220104130000 1
 
0.1%
20220127190000 1
 
0.1%
20220127090000 1
 
0.1%
20220127100000 1
 
0.1%
20220127110000 1
 
0.1%
20220127120000 1
 
0.1%
20220127130000 1
 
0.1%
20220127140000 1
 
0.1%
20220127150000 1
 
0.1%
20220127160000 1
 
0.1%
Other values (820) 820
98.8%
ValueCountFrequency (%)
20220104130000 1
0.1%
20220104140000 1
0.1%
20220104150000 1
0.1%
20220104160000 1
0.1%
20220104170000 1
0.1%
20220104180000 1
0.1%
20220104190000 1
0.1%
20220104200000 1
0.1%
20220104210000 1
0.1%
20220104220000 1
0.1%
ValueCountFrequency (%)
20220308020000 1
0.1%
20220308010000 1
0.1%
20220308000000 1
0.1%
20220307230000 1
0.1%
20220307220000 1
0.1%
20220307210000 1
0.1%
20220307200000 1
0.1%
20220307190000 1
0.1%
20220307180000 1
0.1%
20220307170000 1
0.1%

OVT_CNTE_MIN
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5024096
Minimum0
Maximum35
Zeros697
Zeros (%)84.0%
Negative0
Negative (%)0.0%
Memory size7.4 KiB
2024-03-13T21:30:12.389220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile11
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.0246071
Coefficient of variation (CV)3.3443656
Kurtosis18.649096
Mean1.5024096
Median Absolute Deviation (MAD)0
Skewness4.2223626
Sum1247
Variance25.246677
MonotonicityNot monotonic
2024-03-13T21:30:12.604835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 697
84.0%
2 24
 
2.9%
1 18
 
2.2%
5 9
 
1.1%
6 9
 
1.1%
3 8
 
1.0%
8 6
 
0.7%
7 6
 
0.7%
11 6
 
0.7%
22 4
 
0.5%
Other values (22) 43
 
5.2%
ValueCountFrequency (%)
0 697
84.0%
1 18
 
2.2%
2 24
 
2.9%
3 8
 
1.0%
4 4
 
0.5%
5 9
 
1.1%
6 9
 
1.1%
7 6
 
0.7%
8 6
 
0.7%
9 4
 
0.5%
ValueCountFrequency (%)
35 1
 
0.1%
34 1
 
0.1%
32 2
0.2%
31 1
 
0.1%
30 2
0.2%
29 1
 
0.1%
28 1
 
0.1%
27 3
0.4%
26 1
 
0.1%
23 2
0.2%

WTCH_WVHGH
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct226
Distinct (%)27.6%
Missing10
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean1.2460854
Minimum0.3
Maximum3.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.4 KiB
2024-03-13T21:30:12.844328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.4195
Q10.7875
median1.18
Q31.62
95-th percentile2.441
Maximum3.77
Range3.47
Interquartile range (IQR)0.8325

Descriptive statistics

Standard deviation0.62739352
Coefficient of variation (CV)0.50349161
Kurtosis1.1372593
Mean1.2460854
Median Absolute Deviation (MAD)0.41
Skewness0.94310734
Sum1021.79
Variance0.39362263
MonotonicityNot monotonic
2024-03-13T21:30:13.578540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.21 12
 
1.4%
0.92 11
 
1.3%
1.15 10
 
1.2%
1.09 10
 
1.2%
1.27 9
 
1.1%
1.07 9
 
1.1%
1.29 9
 
1.1%
0.94 8
 
1.0%
1.08 8
 
1.0%
1.72 8
 
1.0%
Other values (216) 726
87.5%
(Missing) 10
 
1.2%
ValueCountFrequency (%)
0.3 5
0.6%
0.31 7
0.8%
0.32 5
0.6%
0.33 6
0.7%
0.34 1
 
0.1%
0.35 2
 
0.2%
0.36 3
0.4%
0.37 2
 
0.2%
0.38 1
 
0.1%
0.39 3
0.4%
ValueCountFrequency (%)
3.77 1
0.1%
3.57 1
0.1%
3.5 1
0.1%
3.48 1
0.1%
3.29 1
0.1%
3.28 1
0.1%
3.26 1
0.1%
3.24 1
0.1%
3.19 2
0.2%
3.18 2
0.2%

WTCH_WVPD
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct469
Distinct (%)57.2%
Missing10
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean7.8472195
Minimum2.33
Maximum12.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.4 KiB
2024-03-13T21:30:13.888770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.33
5-th percentile5.179
Q16.7
median7.78
Q38.8025
95-th percentile11.1105
Maximum12.54
Range10.21
Interquartile range (IQR)2.1025

Descriptive statistics

Standard deviation1.7134487
Coefficient of variation (CV)0.21835106
Kurtosis0.12517913
Mean7.8472195
Median Absolute Deviation (MAD)1.06
Skewness0.25272891
Sum6434.72
Variance2.9359065
MonotonicityNot monotonic
2024-03-13T21:30:14.141677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.7 7
 
0.8%
7.24 6
 
0.7%
7.67 6
 
0.7%
8.06 5
 
0.6%
8.12 5
 
0.6%
8.29 5
 
0.6%
5.93 5
 
0.6%
8.46 5
 
0.6%
6.67 5
 
0.6%
7.8 5
 
0.6%
Other values (459) 766
92.3%
(Missing) 10
 
1.2%
ValueCountFrequency (%)
2.33 1
0.1%
3.39 1
0.1%
3.54 1
0.1%
3.7 1
0.1%
3.96 1
0.1%
3.99 1
0.1%
4.0 1
0.1%
4.09 1
0.1%
4.12 1
0.1%
4.17 1
0.1%
ValueCountFrequency (%)
12.54 1
0.1%
12.41 1
0.1%
12.36 1
0.1%
12.34 1
0.1%
12.31 1
0.1%
12.28 1
0.1%
12.22 1
0.1%
12.16 2
0.2%
12.1 2
0.2%
12.05 1
0.1%

Interactions

2024-03-13T21:30:10.547496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:07.905023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:08.882703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:09.774986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:10.747269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:08.132427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:09.200866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:09.996060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:10.914273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:08.389410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:09.436497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:10.180795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:11.092368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:08.628610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:09.606518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:30:10.360652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:30:14.313809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
OVT_OCCR_YMDHMSOVT_CNTE_MINWTCH_WVHGHWTCH_WVPD
OVT_OCCR_YMDHMS1.0000.2700.5830.636
OVT_CNTE_MIN0.2701.0000.6710.470
WTCH_WVHGH0.5830.6711.0000.780
WTCH_WVPD0.6360.4700.7801.000
2024-03-13T21:30:14.481966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
OVT_OCCR_YMDHMSOVT_CNTE_MINWTCH_WVHGHWTCH_WVPD
OVT_OCCR_YMDHMS1.000-0.264-0.400-0.404
OVT_CNTE_MIN-0.2641.0000.4500.404
WTCH_WVHGH-0.4000.4501.0000.705
WTCH_WVPD-0.4040.4040.7051.000

Missing values

2024-03-13T21:30:11.296547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:30:11.473846image/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.
2024-03-13T21:30:11.665008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

OVT_OCCR_YMDHMSOVT_CNTE_MINWTCH_WVHGHWTCH_WVPD
02022010413000001.186.85
12022010414000001.257.17
22022010415000001.216.35
32022010416000001.077.08
42022010417000000.986.93
52022010418000001.047.02
62022010419000001.377.1
72022010420000001.538.88
82022010421000001.548.36
92022010422000001.478.12
OVT_OCCR_YMDHMSOVT_CNTE_MINWTCH_WVHGHWTCH_WVPD
8202022030717000000.787.9
8212022030718000000.8510.55
8222022030719000000.9610.71
8232022030720000000.9710.58
8242022030721000000.9910.9
8252022030722000001.0611.43
8262022030723000001.0811.62
8272022030800000001.1511.21
8282022030801000001.1511.24
8292022030802000001.2411.63