Overview

Dataset statistics

Number of variables8
Number of observations98
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory71.3 B

Variable types

Categorical2
DateTime1
Numeric5

Dataset

DescriptionSample
Author한국해양대학교 산학협력단
URLhttp://www.bigdata-sea.kr/datasearch/base/view.do?prodId=PROD_000780

Alerts

441273000 has constant value ""Constant
HANNARA has constant value ""Constant
2021-09-12 0:00 has constant value ""Constant
2.37976 is highly overall correlated with 0.797837High correlation
0.797837 is highly overall correlated with 2.37976High correlation
0.809688216 has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:17:00.315806
Analysis finished2023-12-10 14:17:07.513007
Duration7.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

441273000
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
441273000
98 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row441273000
2nd row441273000
3rd row441273000
4th row441273000
5th row441273000

Common Values

ValueCountFrequency (%)
441273000 98
100.0%

Length

2023-12-10T23:17:07.619606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:07.742656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
441273000 98
100.0%

HANNARA
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
HANNARA
98 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
HANNARA 98
100.0%

Length

2023-12-10T23:17:07.863680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:07.999917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hannara 98
100.0%

2021-09-12 0:00
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
Minimum2021-09-12 00:00:00
Maximum2021-09-12 00:00:00
2023-12-10T23:17:08.120542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.267147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

2.37976
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3777089
Minimum2.37434
Maximum2.38178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-10T23:17:08.487119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.37434
5-th percentile2.3747005
Q12.3755325
median2.377615
Q32.37961
95-th percentile2.3812415
Maximum2.38178
Range0.00744
Interquartile range (IQR)0.0040775

Descriptive statistics

Standard deviation0.0022280387
Coefficient of variation (CV)0.00093705278
Kurtosis-1.2453414
Mean2.3777089
Median Absolute Deviation (MAD)0.002035
Skewness0.13908969
Sum233.01547
Variance4.9641565 × 10-6
MonotonicityNot monotonic
2023-12-10T23:17:08.736238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.37746 2
 
2.0%
2.37498 2
 
2.0%
2.37961 2
 
2.0%
2.3784 1
 
1.0%
2.3788 1
 
1.0%
2.38002 1
 
1.0%
2.37905 1
 
1.0%
2.3793 1
 
1.0%
2.37964 1
 
1.0%
2.37999 1
 
1.0%
Other values (85) 85
86.7%
ValueCountFrequency (%)
2.37434 1
1.0%
2.37438 1
1.0%
2.37454 1
1.0%
2.37455 1
1.0%
2.37459 1
1.0%
2.37472 1
1.0%
2.37473 1
1.0%
2.37477 1
1.0%
2.37479 1
1.0%
2.37484 1
1.0%
ValueCountFrequency (%)
2.38178 1
1.0%
2.38146 1
1.0%
2.38145 1
1.0%
2.38135 1
1.0%
2.38125 1
1.0%
2.38124 1
1.0%
2.38119 1
1.0%
2.38111 1
1.0%
2.3811 1
1.0%
2.38105 1
1.0%

0.797521
Real number (ℝ)

Distinct82
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.79792924
Minimum0.796991
Maximum0.798663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-10T23:17:09.002913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.796991
5-th percentile0.7974007
Q10.79773975
median0.7979215
Q30.79811825
95-th percentile0.79847185
Maximum0.798663
Range0.001672
Interquartile range (IQR)0.0003785

Descriptive statistics

Standard deviation0.00032672123
Coefficient of variation (CV)0.00040946141
Kurtosis0.31986093
Mean0.79792924
Median Absolute Deviation (MAD)0.0001915
Skewness-0.2455434
Sum78.197066
Variance1.0674676 × 10-7
MonotonicityNot monotonic
2023-12-10T23:17:09.255276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.79773 3
 
3.1%
0.797876 2
 
2.0%
0.797905 2
 
2.0%
0.797987 2
 
2.0%
0.797832 2
 
2.0%
0.797871 2
 
2.0%
0.797997 2
 
2.0%
0.797846 2
 
2.0%
0.797686 2
 
2.0%
0.797769 2
 
2.0%
Other values (72) 77
78.6%
ValueCountFrequency (%)
0.796991 1
1.0%
0.797079 1
1.0%
0.797239 1
1.0%
0.797278 1
1.0%
0.797297 1
1.0%
0.797419 1
1.0%
0.797443 1
1.0%
0.797453 1
1.0%
0.797472 1
1.0%
0.797497 1
1.0%
ValueCountFrequency (%)
0.798663 1
1.0%
0.798565 1
1.0%
0.798551 1
1.0%
0.798541 1
1.0%
0.798522 1
1.0%
0.798463 1
1.0%
0.798405 1
1.0%
0.79839 1
1.0%
0.798386 1
1.0%
0.798356 1
1.0%

0.797837
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.79750102
Minimum0.796059
Maximum0.79876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-10T23:17:09.519414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.796059
5-th percentile0.79651915
Q10.79700225
median0.7975115
Q30.7979415
95-th percentile0.79857435
Maximum0.79876
Range0.002701
Interquartile range (IQR)0.00093925

Descriptive statistics

Standard deviation0.00063210556
Coefficient of variation (CV)0.00079260784
Kurtosis-0.80359101
Mean0.79750102
Median Absolute Deviation (MAD)0.0005005
Skewness0.03623565
Sum78.1551
Variance3.9955744 × 10-7
MonotonicityNot monotonic
2023-12-10T23:17:09.823577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.797793 2
 
2.0%
0.797628 2
 
2.0%
0.797526 2
 
2.0%
0.797215 2
 
2.0%
0.797817 2
 
2.0%
0.797123 2
 
2.0%
0.798434 1
 
1.0%
0.797613 1
 
1.0%
0.797982 1
 
1.0%
0.79755 1
 
1.0%
Other values (82) 82
83.7%
ValueCountFrequency (%)
0.796059 1
1.0%
0.79637 1
1.0%
0.796418 1
1.0%
0.796438 1
1.0%
0.796486 1
1.0%
0.796525 1
1.0%
0.796593 1
1.0%
0.796598 1
1.0%
0.796637 1
1.0%
0.796642 1
1.0%
ValueCountFrequency (%)
0.79876 1
1.0%
0.798731 1
1.0%
0.798633 1
1.0%
0.798624 1
1.0%
0.798599 1
1.0%
0.79857 1
1.0%
0.798434 1
1.0%
0.798424 1
1.0%
0.79841 1
1.0%
0.79839 1
1.0%

0.809688216
Real number (ℝ)

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.80944855
Minimum0.80907605
Maximum0.80978778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-10T23:17:10.158178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.80907605
5-th percentile0.80920138
Q10.80935573
median0.80944828
Q30.80954296
95-th percentile0.80967077
Maximum0.80978778
Range0.000711725
Interquartile range (IQR)0.00018722975

Descriptive statistics

Standard deviation0.00014247854
Coefficient of variation (CV)0.00017601926
Kurtosis0.05806892
Mean0.80944855
Median Absolute Deviation (MAD)9.35095 × 10-5
Skewness-0.092039237
Sum79.325958
Variance2.0300134 × 10-8
MonotonicityNot monotonic
2023-12-10T23:17:10.448606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.809370895 1
 
1.0%
0.809354694 1
 
1.0%
0.809634894 1
 
1.0%
0.809390103 1
 
1.0%
0.809341324 1
 
1.0%
0.809076052 1
 
1.0%
0.809605414 1
 
1.0%
0.809576352 1
 
1.0%
0.809261452 1
 
1.0%
0.80939744 1
 
1.0%
Other values (88) 88
89.8%
ValueCountFrequency (%)
0.809076052 1
1.0%
0.809112216 1
1.0%
0.809157099 1
1.0%
0.80918312 1
1.0%
0.809200959 1
1.0%
0.809201458 1
1.0%
0.809203266 1
1.0%
0.8092315 1
1.0%
0.809241071 1
1.0%
0.809261452 1
1.0%
ValueCountFrequency (%)
0.809787777 1
1.0%
0.809761603 1
1.0%
0.8097328 1
1.0%
0.809732469 1
1.0%
0.809716956 1
1.0%
0.809662614 1
1.0%
0.809652745 1
1.0%
0.809640192 1
1.0%
0.809634894 1
1.0%
0.809634891 1
1.0%

0.805735
Real number (ℝ)

Distinct79
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.80569279
Minimum0.805036
Maximum0.806323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-10T23:17:10.712450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.805036
5-th percentile0.80517625
Q10.805497
median0.8057305
Q30.8059275
95-th percentile0.8062035
Maximum0.806323
Range0.001287
Interquartile range (IQR)0.0004305

Descriptive statistics

Standard deviation0.00030311592
Coefficient of variation (CV)0.00037621775
Kurtosis-0.58954331
Mean0.80569279
Median Absolute Deviation (MAD)0.0002285
Skewness-0.11427409
Sum78.957893
Variance9.1879263 × 10-8
MonotonicityNot monotonic
2023-12-10T23:17:10.984865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.805784 3
 
3.1%
0.805794 2
 
2.0%
0.805818 2
 
2.0%
0.805274 2
 
2.0%
0.805755 2
 
2.0%
0.805629 2
 
2.0%
0.805993 2
 
2.0%
0.806119 2
 
2.0%
0.805502 2
 
2.0%
0.806017 2
 
2.0%
Other values (69) 77
78.6%
ValueCountFrequency (%)
0.805036 1
1.0%
0.805041 1
1.0%
0.80508 1
1.0%
0.805162 1
1.0%
0.805172 1
1.0%
0.805177 1
1.0%
0.805235 1
1.0%
0.80524 1
1.0%
0.805259 1
1.0%
0.805274 2
2.0%
ValueCountFrequency (%)
0.806323 1
1.0%
0.806265 1
1.0%
0.80626 1
1.0%
0.806236 1
1.0%
0.806212 1
1.0%
0.806202 1
1.0%
0.806119 2
2.0%
0.80609 1
1.0%
0.806066 1
1.0%
0.806051 2
2.0%

Interactions

2023-12-10T23:17:06.210003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:02.300196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.329126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.108497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.953811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.427520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:02.613204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.498184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.325518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.126410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.591537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:02.835225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.626110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.488863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.660540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.756604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:02.984460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.776875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.634998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.832135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.928824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.181407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.946532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.798141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.008328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:17:11.204128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2.379760.7975210.7978370.8096882160.805735
2.379761.0000.0000.6750.0000.264
0.7975210.0001.0000.0000.0000.000
0.7978370.6750.0001.0000.0000.000
0.8096882160.0000.0000.0001.0000.000
0.8057350.2640.0000.0000.0001.000
2023-12-10T23:17:11.391404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2.379760.7975210.7978370.8096882160.805735
2.379761.0000.1410.796-0.018-0.054
0.7975210.1411.0000.1810.1270.326
0.7978370.7960.1811.000-0.0140.127
0.809688216-0.0180.127-0.0141.0000.005
0.805735-0.0540.3260.1270.0051.000

Missing values

2023-12-10T23:17:07.181938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:17:07.423748image/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

441273000HANNARA2021-09-12 0:002.379760.7975210.7978370.8096882160.805735
0441273000HANNARA2021-09-12 0:002.379780.7978510.7984340.8093710.806202
1441273000HANNARA2021-09-12 0:002.379730.7976180.7977350.8095360.805765
2441273000HANNARA2021-09-12 0:002.379040.7979190.7972630.8096630.80575
3441273000HANNARA2021-09-12 0:002.378090.7979480.7984240.8095780.805527
4441273000HANNARA2021-09-12 0:002.378370.798070.7979340.8095060.80609
5441273000HANNARA2021-09-12 0:002.37790.7975840.7973990.8094670.805769
6441273000HANNARA2021-09-12 0:002.37830.7980840.7972830.8095090.806212
7441273000HANNARA2021-09-12 0:002.378020.7978610.7983080.8094290.806323
8441273000HANNARA2021-09-12 0:002.377950.7982740.7977440.8093580.80626
9441273000HANNARA2021-09-12 0:002.377830.7979820.7973120.8093180.805862
441273000HANNARA2021-09-12 0:002.379760.7975210.7978370.8096882160.805735
88441273000HANNARA2021-09-12 0:002.374550.7980460.7964380.8095140.805041
89441273000HANNARA2021-09-12 0:002.374980.7978610.7975260.8097330.806051
90441273000HANNARA2021-09-12 0:002.375120.7982010.7976280.8093550.805998
91441273000HANNARA2021-09-12 0:002.375210.797730.7965930.8094660.805434
92441273000HANNARA2021-09-12 0:002.374590.7978710.79670.8091570.806119
93441273000HANNARA2021-09-12 0:002.374730.7981620.7960590.8094450.805259
94441273000HANNARA2021-09-12 0:002.3750.7974720.7972150.8094220.805497
95441273000HANNARA2021-09-12 0:002.375690.7983420.7974140.8095310.80592
96441273000HANNARA2021-09-12 0:002.375350.7978560.7968460.8095450.805784
97441273000HANNARA2021-09-12 0:002.374540.7975550.7969670.8095890.805735