Overview

Dataset statistics

Number of variables18
Number of observations100
Missing cells900
Missing cells (%)50.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.9 KiB
Average record size in memory163.3 B

Variable types

Categorical6
Numeric3
Unsupported9

Dataset

DescriptionSample
Author인천항만공사
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT03IPA004

Alerts

WTCH_YR has constant value ""Constant
WTCH_MNTH has constant value ""Constant
WTCH_DD has constant value ""Constant
WTCH_HHS has constant value ""Constant
WTCH_MIN has constant value ""Constant
WTCH_SEC has constant value ""Constant
WTCH_LA is highly overall correlated with WTCH_LO and 1 other fieldsHigh correlation
WTCH_LO is highly overall correlated with WTCH_LA and 1 other fieldsHigh correlation
WTCH_SLNTY is highly overall correlated with WTCH_LA and 1 other fieldsHigh correlation
WTCH_WTRLV has 100 (100.0%) missing valuesMissing
WTCH_WTDP has 100 (100.0%) missing valuesMissing
WTCH_CRSPD has 100 (100.0%) missing valuesMissing
WTCH_CRDRC has 100 (100.0%) missing valuesMissing
WTCH_WTEM has 100 (100.0%) missing valuesMissing
SSC_CCTR has 100 (100.0%) missing valuesMissing
MVMN_DRC has 100 (100.0%) missing valuesMissing
MVMN_VE has 100 (100.0%) missing valuesMissing
WTDP_VARTION_QY has 100 (100.0%) missing valuesMissing
WTCH_LA has unique valuesUnique
WTCH_LO has unique valuesUnique
WTCH_WTRLV is an unsupported type, check if it needs cleaning or further analysisUnsupported
WTCH_WTDP is an unsupported type, check if it needs cleaning or further analysisUnsupported
WTCH_CRSPD is an unsupported type, check if it needs cleaning or further analysisUnsupported
WTCH_CRDRC is an unsupported type, check if it needs cleaning or further analysisUnsupported
WTCH_WTEM is an unsupported type, check if it needs cleaning or further analysisUnsupported
SSC_CCTR is an unsupported type, check if it needs cleaning or further analysisUnsupported
MVMN_DRC is an unsupported type, check if it needs cleaning or further analysisUnsupported
MVMN_VE is an unsupported type, check if it needs cleaning or further analysisUnsupported
WTDP_VARTION_QY is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 12:48:03.659122
Analysis finished2024-03-13 12:48:05.813785
Duration2.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

WTCH_YR
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 100
100.0%

Length

2024-03-13T21:48:05.909292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:06.076959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
100.0%

WTCH_MNTH
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 100
100.0%

Length

2024-03-13T21:48:06.283527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:06.457118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 100
100.0%

WTCH_DD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
15
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15
2nd row15
3rd row15
4th row15
5th row15

Common Values

ValueCountFrequency (%)
15 100
100.0%

Length

2024-03-13T21:48:06.651889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:06.803682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15 100
100.0%

WTCH_HHS
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2024-03-13T21:48:06.961558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:07.113213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

WTCH_MIN
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2024-03-13T21:48:07.231830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:07.386460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

WTCH_SEC
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2024-03-13T21:48:07.550736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:07.671887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

WTCH_LA
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.431632
Minimum37.42686
Maximum37.434527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:48:07.878018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.42686
5-th percentile37.428209
Q137.430439
median37.431834
Q337.433156
95-th percentile37.434097
Maximum37.434527
Range0.0076666525
Interquartile range (IQR)0.0027167744

Descriptive statistics

Standard deviation0.001889337
Coefficient of variation (CV)5.0474341 × 10-5
Kurtosis-0.57252817
Mean37.431632
Median Absolute Deviation (MAD)0.0013613808
Skewness-0.50292329
Sum3743.1632
Variance3.5695941 × 10-6
MonotonicityNot monotonic
2024-03-13T21:48:08.165162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.43310536814136 1
 
1.0%
37.43228157244353 1
 
1.0%
37.43002456270184 1
 
1.0%
37.42957076886899 1
 
1.0%
37.42911697499608 1
 
1.0%
37.428663181083095 1
 
1.0%
37.428209387130075 1
 
1.0%
37.427755593136986 1
 
1.0%
37.434096745792985 1
 
1.0%
37.43364295251572 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
37.42685995877804 1
1.0%
37.42731375304621 1
1.0%
37.427755593136986 1
1.0%
37.42776754727431 1
1.0%
37.428197430063456 1
1.0%
37.428209387130075 1
1.0%
37.428221341462326 1
1.0%
37.42865122382149 1
1.0%
37.428663181083095 1
1.0%
37.42867513561031 1
1.0%
ValueCountFrequency (%)
37.43452661123181 1
1.0%
37.434514643230166 1
1.0%
37.43450267249355 1
1.0%
37.43449069902199 1
1.0%
37.4341087053947 1
1.0%
37.434096745792985 1
1.0%
37.43408478345636 1
1.0%
37.434072818384784 1
1.0%
37.43406085057829 1
1.0%
37.43404888003689 1
1.0%

WTCH_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.51579
Minimum126.51245
Maximum126.51778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:48:08.362930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.51245
5-th percentile126.51352
Q1126.51474
median126.51593
Q3126.51705
95-th percentile126.5177
Maximum126.51778
Range0.0053300835
Interquartile range (IQR)0.0023131206

Descriptive statistics

Standard deviation0.0014261437
Coefficient of variation (CV)1.1272456 × 10-5
Kurtosis-0.90079346
Mean126.51579
Median Absolute Deviation (MAD)0.0011602933
Skewness-0.37883547
Sum12651.579
Variance2.0338859 × 10-6
MonotonicityNot monotonic
2024-03-13T21:48:08.571887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.51244891840336 1
 
1.0%
126.5164612768433 1
 
1.0%
126.51710516886013 1
 
1.0%
126.51712016583504 1
 
1.0%
126.51713516247372 1
 
1.0%
126.5171501587762 1
 
1.0%
126.51716515474244 1
 
1.0%
126.51718015037245 1
 
1.0%
126.516401265143 1
 
1.0%
126.51641626857264 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.51244891840336 1
1.0%
126.5130028013408 1
1.0%
126.51301782500272 1
1.0%
126.51303284832778 1
1.0%
126.513047871316 1
1.0%
126.51354167022696 1
1.0%
126.51355669113433 1
1.0%
126.51357171170493 1
1.0%
126.51358673193872 1
1.0%
126.51360175183576 1
1.0%
ValueCountFrequency (%)
126.5177790019284 1
1.0%
126.51776401039784 1
1.0%
126.5177490185312 1
1.0%
126.51773402632838 1
1.0%
126.51771903378943 1
1.0%
126.51770404091435 1
1.0%
126.51768904770312 1
1.0%
126.51767405415572 1
1.0%
126.51765906027212 1
1.0%
126.5176440660524 1
1.0%

WTCH_WTRLV
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

WTCH_WTDP
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

WTCH_CRSPD
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

WTCH_CRDRC
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

WTCH_WTEM
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

WTCH_SLNTY
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.6549
Minimum30.26
Maximum31.045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:48:08.838494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30.26
5-th percentile30.3216
Q130.4545
median30.6395
Q330.8505
95-th percentile30.98645
Maximum31.045
Range0.785
Interquartile range (IQR)0.396

Descriptive statistics

Standard deviation0.22568341
Coefficient of variation (CV)0.0073620663
Kurtosis-1.2486042
Mean30.6549
Median Absolute Deviation (MAD)0.203
Skewness0.083033758
Sum3065.49
Variance0.050933
MonotonicityNot monotonic
2024-03-13T21:48:09.087909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31.014 2
 
2.0%
30.673 2
 
2.0%
30.421 2
 
2.0%
30.366 2
 
2.0%
30.852 2
 
2.0%
30.441 2
 
2.0%
30.733 2
 
2.0%
30.785 2
 
2.0%
30.432 1
 
1.0%
30.544 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
30.26 1
1.0%
30.27 1
1.0%
30.286 1
1.0%
30.302 1
1.0%
30.314 1
1.0%
30.322 1
1.0%
30.337 1
1.0%
30.353 1
1.0%
30.366 2
2.0%
30.368 1
1.0%
ValueCountFrequency (%)
31.045 1
1.0%
31.042 1
1.0%
31.015 1
1.0%
31.014 2
2.0%
30.985 1
1.0%
30.983 1
1.0%
30.982 1
1.0%
30.981 1
1.0%
30.978 1
1.0%
30.969 1
1.0%

SSC_CCTR
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

MVMN_DRC
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

MVMN_VE
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

WTDP_VARTION_QY
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

Interactions

2024-03-13T21:48:04.840847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:03.869456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:04.337946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:04.991638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:04.022635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:04.532588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:05.129289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:04.179525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:04.690164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:48:09.244269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOWTCH_SLNTY
WTCH_LA1.0000.0000.956
WTCH_LO0.0001.0000.000
WTCH_SLNTY0.9560.0001.000
2024-03-13T21:48:09.380161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOWTCH_SLNTY
WTCH_LA1.000-0.517-0.984
WTCH_LO-0.5171.0000.618
WTCH_SLNTY-0.9840.6181.000

Missing values

2024-03-13T21:48:05.338726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:48:05.679027image/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

WTCH_YRWTCH_MNTHWTCH_DDWTCH_HHSWTCH_MINWTCH_SECWTCH_LAWTCH_LOWTCH_WTRLVWTCH_WTDPWTCH_CRSPDWTCH_CRDRCWTCH_WTEMWTCH_SLNTYSSC_CCTRMVMN_DRCMVMN_VEWTDP_VARTION_QY
0202021500037.433105126.512449<NA><NA><NA><NA><NA>30.432<NA><NA><NA><NA>
1202021500037.43221126.513048<NA><NA><NA><NA><NA>30.552<NA><NA><NA><NA>
2202021500037.432664126.513033<NA><NA><NA><NA><NA>30.488<NA><NA><NA><NA>
3202021500037.433117126.513018<NA><NA><NA><NA><NA>30.426<NA><NA><NA><NA>
4202021500037.433571126.513003<NA><NA><NA><NA><NA>30.368<NA><NA><NA><NA>
5202021500037.431768126.513632<NA><NA><NA><NA><NA>30.624<NA><NA><NA><NA>
6202021500037.432222126.513617<NA><NA><NA><NA><NA>30.554<NA><NA><NA><NA>
7202021500037.432676126.513602<NA><NA><NA><NA><NA>30.486<NA><NA><NA><NA>
8202021500037.433129126.513587<NA><NA><NA><NA><NA>30.421<NA><NA><NA><NA>
9202021500037.433583126.513572<NA><NA><NA><NA><NA>30.366<NA><NA><NA><NA>
WTCH_YRWTCH_MNTHWTCH_DDWTCH_HHSWTCH_MINWTCH_SECWTCH_LAWTCH_LOWTCH_WTRLVWTCH_WTDPWTCH_CRSPDWTCH_CRDRCWTCH_WTEMWTCH_SLNTYSSC_CCTRMVMN_DRCMVMN_VEWTDP_VARTION_QY
90202021500037.429583126.517689<NA><NA><NA><NA><NA>30.885<NA><NA><NA><NA>
91202021500037.430037126.517674<NA><NA><NA><NA><NA>30.852<NA><NA><NA><NA>
92202021500037.43049126.517659<NA><NA><NA><NA><NA>30.819<NA><NA><NA><NA>
93202021500037.430944126.517644<NA><NA><NA><NA><NA>30.785<NA><NA><NA><NA>
94202021500037.431398126.517629<NA><NA><NA><NA><NA>30.733<NA><NA><NA><NA>
95202021500037.431852126.517614<NA><NA><NA><NA><NA>30.673<NA><NA><NA><NA>
96202021500037.432305126.517599<NA><NA><NA><NA><NA>30.612<NA><NA><NA><NA>
97202021500037.432759126.517584<NA><NA><NA><NA><NA>30.551<NA><NA><NA><NA>
98202021500037.433213126.517569<NA><NA><NA><NA><NA>30.495<NA><NA><NA><NA>
99202021500037.433667126.517554<NA><NA><NA><NA><NA>30.441<NA><NA><NA><NA>