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=CT03IPA002

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 WTDP_VARTION_QYHigh correlation
WTDP_VARTION_QY is highly overall correlated with WTCH_LAHigh 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
WTCH_SLNTY 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
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
WTCH_SLNTY 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

Reproduction

Analysis started2024-03-13 12:48:10.413381
Analysis finished2024-03-13 12:48:12.290644
Duration1.88 second
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

2024-03-13T21:48:12.395114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:12.567422image/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

2024-03-13T21:48:12.774315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:12.932670image/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

2024-03-13T21:48:13.085840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:13.250424image/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

2024-03-13T21:48:13.375335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:13.519646image/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

2024-03-13T21:48:13.629116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:13.775270image/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

2024-03-13T21:48:13.915901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:48:14.057279image/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%
Mean37.405548
Minimum37.393921
Maximum37.420819
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:48:14.201838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.393921
5-th percentile37.394844
Q137.399398
median37.405092
Q337.410785
95-th percentile37.418563
Maximum37.420819
Range0.026897053
Interquartile range (IQR)0.011386185

Descriptive statistics

Standard deviation0.0073472957
Coefficient of variation (CV)0.00019642262
Kurtosis-0.87796256
Mean37.405548
Median Absolute Deviation (MAD)0.0056960371
Skewness0.28393607
Sum3740.5548
Variance5.3982754 × 10-5
MonotonicityNot monotonic
2024-03-13T21:48:14.410677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.393921463023446 1
 
1.0%
37.40486963576858 1
 
1.0%
37.40942646362188 1
 
1.0%
37.40897078101765 1
 
1.0%
37.40851509837315 1
 
1.0%
37.40805941568843 1
 
1.0%
37.407603732963445 1
 
1.0%
37.407148050198245 1
 
1.0%
37.40669236739281 1
 
1.0%
37.40623668454709 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
37.393921463023446 1
1.0%
37.39393323250321 1
1.0%
37.394377146762736 1
1.0%
37.3943889164353 1
1.0%
37.39483283046183 1
1.0%
37.39484460032717 1
1.0%
37.39528851412064 1
1.0%
37.39530028417881 1
1.0%
37.39574419773925 1
1.0%
37.395755967990205 1
1.0%
ValueCountFrequency (%)
37.42081851564812 1
1.0%
37.420362834050046 1
1.0%
37.41990715241172 1
1.0%
37.41945147073314 1
1.0%
37.418995789014325 1
1.0%
37.41854010725524 1
1.0%
37.41808442545592 1
1.0%
37.41762874361634 1
1.0%
37.41717306173653 1
1.0%
37.41671737981646 1
1.0%

WTCH_LO
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.55109
Minimum126.55055
Maximum126.5517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:48:14.638942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55055
5-th percentile126.55063
Q1126.55087
median126.55105
Q3126.55133
95-th percentile126.55163
Maximum126.5517
Range0.0011467975
Interquartile range (IQR)0.00046488293

Descriptive statistics

Standard deviation0.00030755046
Coefficient of variation (CV)2.4302473 × 10-6
Kurtosis-0.86446995
Mean126.55109
Median Absolute Deviation (MAD)0.0002172802
Skewness0.26705578
Sum12655.109
Variance9.4587282 × 10-8
MonotonicityNot monotonic
2024-03-13T21:48:14.942859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5511319018889 1
 
1.0%
126.5513439197535 1
 
1.0%
126.55119552201396 1
 
1.0%
126.55121036329132 1
 
1.0%
126.55122520423458 1
 
1.0%
126.55124004484372 1
 
1.0%
126.55125488511878 1
 
1.0%
126.55126972505975 1
 
1.0%
126.55128456466664 1
 
1.0%
126.55129940393944 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.550553140528 1
1.0%
126.55056798691145 1
1.0%
126.5505828329606 1
1.0%
126.55059767867554 1
1.0%
126.55061252405628 1
1.0%
126.55062736910283 1
1.0%
126.55064221381517 1
1.0%
126.5506570581933 1
1.0%
126.55067190223724 1
1.0%
126.55068674594706 1
1.0%
ValueCountFrequency (%)
126.55169993805445 1
1.0%
126.55168510779863 1
1.0%
126.55167027720896 1
1.0%
126.55165544628542 1
1.0%
126.551640615028 1
1.0%
126.55162578343668 1
1.0%
126.55161095151148 1
1.0%
126.5515961192524 1
1.0%
126.5515812866594 1
1.0%
126.55156645373248 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
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

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
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01982
Minimum0.017
Maximum0.022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:48:15.148530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.017
5-th percentile0.018
Q10.019
median0.02
Q30.021
95-th percentile0.022
Maximum0.022
Range0.005
Interquartile range (IQR)0.002

Descriptive statistics

Standard deviation0.0012008415
Coefficient of variation (CV)0.060587359
Kurtosis-0.45313718
Mean0.01982
Median Absolute Deviation (MAD)0.001
Skewness0.17662491
Sum1.982
Variance1.4420202 × 10-6
MonotonicityNot monotonic
2024-03-13T21:48:15.344303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.019 35
35.0%
0.02 27
27.0%
0.021 17
17.0%
0.022 11
 
11.0%
0.018 8
 
8.0%
0.017 2
 
2.0%
ValueCountFrequency (%)
0.017 2
 
2.0%
0.018 8
 
8.0%
0.019 35
35.0%
0.02 27
27.0%
0.021 17
17.0%
0.022 11
 
11.0%
ValueCountFrequency (%)
0.022 11
 
11.0%
0.021 17
17.0%
0.02 27
27.0%
0.019 35
35.0%
0.018 8
 
8.0%
0.017 2
 
2.0%

Interactions

2024-03-13T21:48:11.480287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:10.658191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:11.026825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:11.613837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:10.768301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:11.144813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:11.729080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:10.883862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:11.357746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:48:15.451921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOWTDP_VARTION_QY
WTCH_LA1.0000.9270.842
WTCH_LO0.9271.0000.672
WTDP_VARTION_QY0.8420.6721.000
2024-03-13T21:48:15.609828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOWTDP_VARTION_QY
WTCH_LA1.000-0.4680.569
WTCH_LO-0.4681.000-0.036
WTDP_VARTION_QY0.569-0.0361.000

Missing values

2024-03-13T21:48:11.897551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:48:12.170880image/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
0202021500037.393921126.551132<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.017
1202021500037.394377126.551117<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.018
2202021500037.394833126.551102<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.018
3202021500037.395289126.551087<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.018
4202021500037.395744126.551073<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.018
5202021500037.3962126.551058<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.019
6202021500037.396656126.551043<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.019
7202021500037.397111126.551028<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.019
8202021500037.397567126.551013<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.02
9202021500037.398023126.550998<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.02
WTCH_YRWTCH_MNTHWTCH_DDWTCH_HHSWTCH_MINWTCH_SECWTCH_LAWTCH_LOWTCH_WTRLVWTCH_WTDPWTCH_CRSPDWTCH_CRDRCWTCH_WTEMWTCH_SLNTYSSC_CCTRMVMN_DRCMVMN_VEWTDP_VARTION_QY
90202021500037.416717126.550958<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
91202021500037.417173126.550943<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
92202021500037.417629126.550928<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
93202021500037.418084126.550913<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
94202021500037.41854126.550899<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
95202021500037.418996126.550884<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
96202021500037.419451126.550869<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
97202021500037.419907126.550854<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
98202021500037.420363126.550839<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022
99202021500037.420819126.550824<NA><NA><NA><NA><NA><NA><NA><NA><NA>0.022