Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory80.3 B

Variable types

Categorical7
Numeric2

Dataset

DescriptionSample
Author㈜일렉오션
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT08ELO004

Alerts

CLMT_AVG_MNTH_DD has constant value ""Constant
YY30_AVG_SYMD has constant value ""Constant
YY30_AVG_EYMD has constant value ""Constant
SRC_DATA_NM has constant value ""Constant
SRC_DATA_INTV has constant value ""Constant
WTCH_RELM_NM has constant value ""Constant
LO is highly overall correlated with CLMT_AVGHigh correlation
CLMT_AVG is highly overall correlated with LOHigh correlation

Reproduction

Analysis started2024-03-13 12:50:33.612038
Analysis finished2024-03-13 12:50:34.763721
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

LA
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
39.0
33 
38.75
33 
38.5
33 
38.25
 
1

Length

Max length5
Median length4
Mean length4.34
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row39.0
2nd row39.0
3rd row39.0
4th row39.0
5th row39.0

Common Values

ValueCountFrequency (%)
39.0 33
33.0%
38.75 33
33.0%
38.5 33
33.0%
38.25 1
 
1.0%

Length

2024-03-13T21:50:34.881735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:35.031792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
39.0 33
33.0%
38.75 33
33.0%
38.5 33
33.0%
38.25 1
 
1.0%

LO
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.96
Minimum124
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:50:35.190299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124
5-th percentile124.25
Q1125.9375
median128
Q3130
95-th percentile131.75
Maximum132
Range8
Interquartile range (IQR)4.0625

Descriptive statistics

Standard deviation2.4138489
Coefficient of variation (CV)0.01886409
Kurtosis-1.2069907
Mean127.96
Median Absolute Deviation (MAD)2
Skewness0.0038306951
Sum12796
Variance5.8266667
MonotonicityNot monotonic
2024-03-13T21:50:35.412450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
124.0 4
 
4.0%
130.25 3
 
3.0%
128.75 3
 
3.0%
129.0 3
 
3.0%
129.25 3
 
3.0%
129.5 3
 
3.0%
129.75 3
 
3.0%
130.0 3
 
3.0%
130.5 3
 
3.0%
124.25 3
 
3.0%
Other values (23) 69
69.0%
ValueCountFrequency (%)
124.0 4
4.0%
124.25 3
3.0%
124.5 3
3.0%
124.75 3
3.0%
125.0 3
3.0%
125.25 3
3.0%
125.5 3
3.0%
125.75 3
3.0%
126.0 3
3.0%
126.25 3
3.0%
ValueCountFrequency (%)
132.0 3
3.0%
131.75 3
3.0%
131.5 3
3.0%
131.25 3
3.0%
131.0 3
3.0%
130.75 3
3.0%
130.5 3
3.0%
130.25 3
3.0%
130.0 3
3.0%
129.75 3
3.0%

CLMT_AVG_MNTH_DD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
101
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row101
2nd row101
3rd row101
4th row101
5th row101

Common Values

ValueCountFrequency (%)
101 100
100.0%

Length

2024-03-13T21:50:35.598120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:35.731770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
101 100
100.0%

CLMT_AVG
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.1654
Minimum-3.6
Maximum-0.8
Zeros0
Zeros (%)0.0%
Negative100
Negative (%)100.0%
Memory size1.0 KiB
2024-03-13T21:50:36.405218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.6
5-th percentile-3.4005
Q1-3.0775
median-2.115
Q3-1.24
95-th percentile-0.9485
Maximum-0.8
Range2.8
Interquartile range (IQR)1.8375

Descriptive statistics

Standard deviation0.9120799
Coefficient of variation (CV)-0.4212062
Kurtosis-1.612042
Mean-2.1654
Median Absolute Deviation (MAD)0.895
Skewness-0.045467266
Sum-216.54
Variance0.83188974
MonotonicityNot monotonic
2024-03-13T21:50:36.649088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.22 3
 
3.0%
-1.07 2
 
2.0%
-1.08 2
 
2.0%
-3.24 2
 
2.0%
-1.5 2
 
2.0%
-2.34 2
 
2.0%
-2.41 2
 
2.0%
-1.23 2
 
2.0%
-1.77 2
 
2.0%
-2.3 2
 
2.0%
Other values (72) 79
79.0%
ValueCountFrequency (%)
-3.6 1
1.0%
-3.5 1
1.0%
-3.46 1
1.0%
-3.42 1
1.0%
-3.41 1
1.0%
-3.4 1
1.0%
-3.39 1
1.0%
-3.38 1
1.0%
-3.34 1
1.0%
-3.33 1
1.0%
ValueCountFrequency (%)
-0.8 1
1.0%
-0.83 1
1.0%
-0.88 1
1.0%
-0.91 1
1.0%
-0.92 1
1.0%
-0.95 1
1.0%
-0.96 1
1.0%
-1.01 1
1.0%
-1.04 1
1.0%
-1.06 1
1.0%

YY30_AVG_SYMD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
19810101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19810101
2nd row19810101
3rd row19810101
4th row19810101
5th row19810101

Common Values

ValueCountFrequency (%)
19810101 100
100.0%

Length

2024-03-13T21:50:36.833454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:36.969763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19810101 100
100.0%

YY30_AVG_EYMD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20101231
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20101231
2nd row20101231
3rd row20101231
4th row20101231
5th row20101231

Common Values

ValueCountFrequency (%)
20101231 100
100.0%

Length

2024-03-13T21:50:37.121268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:37.275976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20101231 100
100.0%

SRC_DATA_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
ERA5 Reanalysis Data
100 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowERA5 Reanalysis Data
2nd rowERA5 Reanalysis Data
3rd rowERA5 Reanalysis Data
4th rowERA5 Reanalysis Data
5th rowERA5 Reanalysis Data

Common Values

ValueCountFrequency (%)
ERA5 Reanalysis Data 100
100.0%

Length

2024-03-13T21:50:37.426940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:37.594383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
era5 100
33.3%
reanalysis 100
33.3%
data 100
33.3%

SRC_DATA_INTV
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.25
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.25
2nd row0.25
3rd row0.25
4th row0.25
5th row0.25

Common Values

ValueCountFrequency (%)
0.25 100
100.0%

Length

2024-03-13T21:50:37.741204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:37.882353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.25 100
100.0%

WTCH_RELM_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KOREA
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KOREA 100
100.0%

Length

2024-03-13T21:50:38.016833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:50:38.191071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
korea 100
100.0%

Interactions

2024-03-13T21:50:34.089650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:33.809094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:34.238603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:33.958020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:50:38.314626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LALOCLMT_AVG
LA1.0000.0000.302
LO0.0001.0000.845
CLMT_AVG0.3020.8451.000
2024-03-13T21:50:38.463912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LOCLMT_AVGLA
LO1.0000.8880.000
CLMT_AVG0.8881.0000.176
LA0.0000.1761.000

Missing values

2024-03-13T21:50:34.444393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:50:34.668390image/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

LALOCLMT_AVG_MNTH_DDCLMT_AVGYY30_AVG_SYMDYY30_AVG_EYMDSRC_DATA_NMSRC_DATA_INTVWTCH_RELM_NM
039.0124.0101-3.381981010120101231ERA5 Reanalysis Data0.25KOREA
139.0124.25101-3.291981010120101231ERA5 Reanalysis Data0.25KOREA
239.0124.5101-3.181981010120101231ERA5 Reanalysis Data0.25KOREA
339.0124.75101-3.071981010120101231ERA5 Reanalysis Data0.25KOREA
439.0125.0101-3.01981010120101231ERA5 Reanalysis Data0.25KOREA
539.0125.25101-2.971981010120101231ERA5 Reanalysis Data0.25KOREA
639.0125.5101-2.971981010120101231ERA5 Reanalysis Data0.25KOREA
739.0125.75101-3.011981010120101231ERA5 Reanalysis Data0.25KOREA
839.0126.0101-3.031981010120101231ERA5 Reanalysis Data0.25KOREA
939.0126.25101-3.01981010120101231ERA5 Reanalysis Data0.25KOREA
LALOCLMT_AVG_MNTH_DDCLMT_AVGYY30_AVG_SYMDYY30_AVG_EYMDSRC_DATA_NMSRC_DATA_INTVWTCH_RELM_NM
9038.5130.0101-1.431981010120101231ERA5 Reanalysis Data0.25KOREA
9138.5130.25101-1.391981010120101231ERA5 Reanalysis Data0.25KOREA
9238.5130.5101-1.291981010120101231ERA5 Reanalysis Data0.25KOREA
9338.5130.75101-1.241981010120101231ERA5 Reanalysis Data0.25KOREA
9438.5131.0101-1.251981010120101231ERA5 Reanalysis Data0.25KOREA
9538.5131.25101-1.241981010120101231ERA5 Reanalysis Data0.25KOREA
9638.5131.5101-1.231981010120101231ERA5 Reanalysis Data0.25KOREA
9738.5131.75101-1.221981010120101231ERA5 Reanalysis Data0.25KOREA
9838.5132.0101-1.251981010120101231ERA5 Reanalysis Data0.25KOREA
9938.25124.0101-3.61981010120101231ERA5 Reanalysis Data0.25KOREA