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
Author인하대학교 산학협력단
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT03IHU013

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_CRSPD 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_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
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_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
WTDP_VARTION_QY is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-14 07:01:24.091207
Analysis finished2024-01-14 07:01:25.782893
Duration1.69 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
2022
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 100
100.0%

Length

2024-01-14T16:01:25.902868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:01:26.051763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 100
100.0%

WTCH_MNTH
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 100
100.0%

Length

2024-01-14T16:01:26.215127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:01:26.338087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 100
100.0%

WTCH_DD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 100
100.0%

Length

2024-01-14T16:01:26.435591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:01:26.525526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
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

2024-01-14T16:01:26.614772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:01:26.695586image/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

2024-01-14T16:01:26.778792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:01:26.864519image/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

2024-01-14T16:01:26.945755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T16:01:27.030312image/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%
Mean37.43353
Minimum37.379497
Maximum37.463335
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-01-14T16:01:27.133193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.379497
5-th percentile37.405306
Q137.418811
median37.435012
Q337.448494
95-th percentile37.461092
Maximum37.463335
Range0.083837981
Interquartile range (IQR)0.029683106

Descriptive statistics

Standard deviation0.019745237
Coefficient of variation (CV)0.00052747461
Kurtosis-0.66125759
Mean37.43353
Median Absolute Deviation (MAD)0.015408044
Skewness-0.35588553
Sum3743.353
Variance0.00038987437
MonotonicityStrictly increasing
2024-01-14T16:01:27.301461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.379497217684474 1
 
1.0%
37.4438486549998 1
 
1.0%
37.448380415987245 1
 
1.0%
37.4479272400684 1
 
1.0%
37.44747406410958 1
 
1.0%
37.4470208881108 1
 
1.0%
37.446567712072 1
 
1.0%
37.44611453599324 1
 
1.0%
37.445661359874514 1
 
1.0%
37.44520818371579 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
37.379497217684474 1
1.0%
37.39173311638272 1
1.0%
37.39218629725681 1
1.0%
37.39263947809096 1
1.0%
37.40487534551316 1
1.0%
37.40532852522877 1
1.0%
37.40578170490441 1
1.0%
37.40623488454012 1
1.0%
37.40668806413586 1
1.0%
37.407141243691655 1
1.0%
ValueCountFrequency (%)
37.46333519887849 1
1.0%
37.46288202427914 1
1.0%
37.4624288496398 1
1.0%
37.46197567496048 1
1.0%
37.461522500241166 1
1.0%
37.46106932548186 1
1.0%
37.46061615068256 1
1.0%
37.46016297584328 1
1.0%
37.45970980096401 1
1.0%
37.45925662604476 1
1.0%

WTCH_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.51318
Minimum126.51219
Maximum126.51496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-01-14T16:01:27.440449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.51219
5-th percentile126.51227
Q1126.51268
median126.51313
Q3126.51367
95-th percentile126.51411
Maximum126.51496
Range0.0027737834
Interquartile range (IQR)0.00098266249

Descriptive statistics

Standard deviation0.00065355289
Coefficient of variation (CV)5.1658878 × 10-6
Kurtosis-0.6641084
Mean126.51318
Median Absolute Deviation (MAD)0.00050992444
Skewness0.35412179
Sum12651.318
Variance4.2713138 × 10-7
MonotonicityStrictly decreasing
2024-01-14T16:01:27.582570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5149648019649 1
 
1.0%
126.51283676106976 1
 
1.0%
126.51268664387084 1
 
1.0%
126.51270165710336 1
 
1.0%
126.51271666999972 1
 
1.0%
126.51273168255995 1
 
1.0%
126.512746694784 1
 
1.0%
126.51276170667192 1
 
1.0%
126.51277671822373 1
 
1.0%
126.5127917294394 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.51219101855848 1
1.0%
126.51220604288883 1
1.0%
126.51222106688274 1
1.0%
126.51223609054021 1
1.0%
126.51225111386132 1
1.0%
126.512266136846 1
1.0%
126.51228115949428 1
1.0%
126.5122961818062 1
1.0%
126.51231120378172 1
1.0%
126.51232622542088 1
1.0%
ValueCountFrequency (%)
126.5149648019649 1
1.0%
126.5145606951986 1
1.0%
126.51454572358976 1
1.0%
126.51453075164572 1
1.0%
126.51412638242688 1
1.0%
126.51411140109438 1
1.0%
126.51409641942644 1
1.0%
126.5140814374231 1
1.0%
126.5140664550843 1
1.0%
126.51405147241007 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
Real number (ℝ)

HIGH CORRELATION 

Distinct86
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1594
Minimum0
Maximum0.42
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-01-14T16:01:27.738854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.001
Q10.02475
median0.146
Q30.2915
95-th percentile0.38115
Maximum0.42
Range0.42
Interquartile range (IQR)0.26675

Descriptive statistics

Standard deviation0.14282659
Coefficient of variation (CV)0.89602628
Kurtosis-1.3944466
Mean0.1594
Median Absolute Deviation (MAD)0.1345
Skewness0.37897092
Sum15.94
Variance0.020399434
MonotonicityNot monotonic
2024-01-14T16:01:27.901978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001 5
 
5.0%
0.147 2
 
2.0%
0.004 2
 
2.0%
0.012 2
 
2.0%
0.009 2
 
2.0%
0.149 2
 
2.0%
0.005 2
 
2.0%
0.003 2
 
2.0%
0.002 2
 
2.0%
0.145 2
 
2.0%
Other values (76) 77
77.0%
ValueCountFrequency (%)
0.0 1
 
1.0%
0.001 5
5.0%
0.002 2
 
2.0%
0.003 2
 
2.0%
0.004 2
 
2.0%
0.005 2
 
2.0%
0.006 1
 
1.0%
0.007 1
 
1.0%
0.008 1
 
1.0%
0.009 2
 
2.0%
ValueCountFrequency (%)
0.42 1
1.0%
0.415 2
2.0%
0.406 1
1.0%
0.384 1
1.0%
0.381 1
1.0%
0.378 1
1.0%
0.375 1
1.0%
0.373 1
1.0%
0.37 1
1.0%
0.368 1
1.0%

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
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Interactions

2024-01-14T16:01:24.915257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:24.294660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:24.567090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:25.042629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:24.384007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:24.669127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:25.157784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:24.477277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T16:01:24.777533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T16:01:28.040343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOWTCH_CRSPD
WTCH_LA1.0001.0000.920
WTCH_LO1.0001.0000.918
WTCH_CRSPD0.9200.9181.000
2024-01-14T16:01:28.173859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOWTCH_CRSPD
WTCH_LA1.000-1.000-0.999
WTCH_LO-1.0001.0000.999
WTCH_CRSPD-0.9990.9991.000

Missing values

2024-01-14T16:01:25.340814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T16:01:25.672281image/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
020223100037.379497126.514965<NA><NA>0.406<NA><NA><NA><NA><NA><NA><NA>
120223100037.391733126.514561<NA><NA>0.42<NA><NA><NA><NA><NA><NA><NA>
220223100037.392186126.514546<NA><NA>0.415<NA><NA><NA><NA><NA><NA><NA>
320223100037.392639126.514531<NA><NA>0.415<NA><NA><NA><NA><NA><NA><NA>
420223100037.404875126.514126<NA><NA>0.384<NA><NA><NA><NA><NA><NA><NA>
520223100037.405329126.514111<NA><NA>0.381<NA><NA><NA><NA><NA><NA><NA>
620223100037.405782126.514096<NA><NA>0.378<NA><NA><NA><NA><NA><NA><NA>
720223100037.406235126.514081<NA><NA>0.375<NA><NA><NA><NA><NA><NA><NA>
820223100037.406688126.514066<NA><NA>0.373<NA><NA><NA><NA><NA><NA><NA>
920223100037.407141126.514051<NA><NA>0.37<NA><NA><NA><NA><NA><NA><NA>
WTCH_YRWTCH_MNTHWTCH_DDWTCH_HHSWTCH_MINWTCH_SECWTCH_LAWTCH_LOWTCH_WTRLVWTCH_WTDPWTCH_CRSPDWTCH_CRDRCWTCH_WTEMWTCH_SLNTYSSC_CCTRMVMN_DRCMVMN_VEWTDP_VARTION_QY
9020223100037.459257126.512326<NA><NA>0.003<NA><NA><NA><NA><NA><NA><NA>
9120223100037.45971126.512311<NA><NA>0.003<NA><NA><NA><NA><NA><NA><NA>
9220223100037.460163126.512296<NA><NA>0.002<NA><NA><NA><NA><NA><NA><NA>
9320223100037.460616126.512281<NA><NA>0.002<NA><NA><NA><NA><NA><NA><NA>
9420223100037.461069126.512266<NA><NA>0.001<NA><NA><NA><NA><NA><NA><NA>
9520223100037.461523126.512251<NA><NA>0.001<NA><NA><NA><NA><NA><NA><NA>
9620223100037.461976126.512236<NA><NA>0.001<NA><NA><NA><NA><NA><NA><NA>
9720223100037.462429126.512221<NA><NA>0.001<NA><NA><NA><NA><NA><NA><NA>
9820223100037.462882126.512206<NA><NA>0.001<NA><NA><NA><NA><NA><NA><NA>
9920223100037.463335126.512191<NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA>