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=CT03IPA001

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_LO is highly overall correlated with SSC_CCTRHigh correlation
SSC_CCTR is highly overall correlated with WTCH_LOHigh 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
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
WTCH_SLNTY 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 12:27:46.393252
Analysis finished2024-03-13 12:27:48.954705
Duration2.56 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

2024-03-13T21:27:49.058798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:49.242761image/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

2024-03-13T21:27:49.452626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:49.629496image/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

2024-03-13T21:27:49.793195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:49.972737image/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

2024-03-13T21:27:50.141308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:50.409352image/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

2024-03-13T21:27:50.569178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:50.732853image/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

2024-03-13T21:27:50.925543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:51.105925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

WTCH_LA
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.485594
Minimum37.475205
Maximum37.509277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:27:51.448732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.475205
5-th percentile37.475544
Q137.476122
median37.477075
Q337.507428
95-th percentile37.509219
Maximum37.509277
Range0.034071663
Interquartile range (IQR)0.031306079

Descriptive statistics

Standard deviation0.014361787
Coefficient of variation (CV)0.00038312818
Kurtosis-1.0305663
Mean37.485594
Median Absolute Deviation (MAD)0.0013798602
Skewness0.98478585
Sum3748.5594
Variance0.00020626094
MonotonicityNot monotonic
2024-03-13T21:27:52.117630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.47555952465313 1
 
1.0%
37.476148732433074 1
 
1.0%
37.50926526461649 1
 
1.0%
37.50880531423473 1
 
1.0%
37.508345363812 1
 
1.0%
37.50788541334831 1
 
1.0%
37.50742546284364 1
 
1.0%
37.47844849847238 1
 
1.0%
37.477988545346406 1
 
1.0%
37.477528592179496 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
37.4752053501056 1
1.0%
37.47521708929571 1
1.0%
37.47522882573073 1
1.0%
37.47524055941066 1
1.0%
37.4752522903355 1
1.0%
37.47555952465313 1
1.0%
37.47557128883309 1
1.0%
37.47558305025797 1
1.0%
37.47559480892774 1
1.0%
37.47560656484246 1
1.0%
ValueCountFrequency (%)
37.5092770126484 1
1.0%
37.50926526461649 1
1.0%
37.50925351382611 1
1.0%
37.50924176027728 1
1.0%
37.50923000397003 1
1.0%
37.509218244904325 1
1.0%
37.50920648308019 1
1.0%
37.50881706207263 1
1.0%
37.50880531423473 1
1.0%
37.50879356363843 1
1.0%

WTCH_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.57103
Minimum126.56627
Maximum126.57371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:27:52.582131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56627
5-th percentile126.56797
Q1126.56969
median126.57137
Q3126.57248
95-th percentile126.57364
Maximum126.57371
Range0.0074363845
Interquartile range (IQR)0.0027874447

Descriptive statistics

Standard deviation0.0017946224
Coefficient of variation (CV)1.4178778 × 10-5
Kurtosis-0.59931648
Mean126.57103
Median Absolute Deviation (MAD)0.0011715721
Skewness-0.40165471
Sum12657.103
Variance3.2206697 × 10-6
MonotonicityNot monotonic
2024-03-13T21:27:52.973196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.56627331611575 1
 
1.0%
126.57253816281596 1
 
1.0%
126.57146550781081 1
 
1.0%
126.57148041782128 1
 
1.0%
126.57149532749283 1
 
1.0%
126.57151023682547 1
 
1.0%
126.57152514581927 1
 
1.0%
126.57246372958936 1
 
1.0%
126.57247861691138 1
 
1.0%
126.57249350389505 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.56627331611575 1
1.0%
126.56684419921513 1
1.0%
126.5674150826463 1
1.0%
126.56794122468413 1
1.0%
126.56795613893148 1
1.0%
126.56797105283984 1
1.0%
126.56798596640924 1
1.0%
126.56849720816234 1
1.0%
126.56851211925604 1
1.0%
126.56852703001088 1
1.0%
ValueCountFrequency (%)
126.5737097005749 1
1.0%
126.5736948222676 1
1.0%
126.57367994362212 1
1.0%
126.5736650646385 1
1.0%
126.57365018531668 1
1.0%
126.5736353056567 1
1.0%
126.57362042565852 1
1.0%
126.57360554532217 1
1.0%
126.57359066464755 1
1.0%
126.57357578363477 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
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.2379
Minimum90.96
Maximum127.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:27:53.237553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90.96
5-th percentile92.9845
Q194.165
median96.03
Q3100.585
95-th percentile110.949
Maximum127.82
Range36.86
Interquartile range (IQR)6.42

Descriptive statistics

Standard deviation6.3630245
Coefficient of variation (CV)0.064771586
Kurtosis5.9664931
Mean98.2379
Median Absolute Deviation (MAD)2.465
Skewness2.1644911
Sum9823.79
Variance40.488081
MonotonicityNot monotonic
2024-03-13T21:27:53.468082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103.67 2
 
2.0%
94.61 2
 
2.0%
94.15 2
 
2.0%
102.61 1
 
1.0%
95.29 1
 
1.0%
93.75 1
 
1.0%
93.02 1
 
1.0%
92.08 1
 
1.0%
98.3 1
 
1.0%
99.0 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
90.96 1
1.0%
91.45 1
1.0%
91.87 1
1.0%
92.08 1
1.0%
92.31 1
1.0%
93.02 1
1.0%
93.03 1
1.0%
93.05 1
1.0%
93.19 1
1.0%
93.24 1
1.0%
ValueCountFrequency (%)
127.82 1
1.0%
122.04 1
1.0%
116.95 1
1.0%
113.81 1
1.0%
111.31 1
1.0%
110.93 1
1.0%
109.29 1
1.0%
106.77 1
1.0%
106.5 1
1.0%
105.72 1
1.0%

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

2024-03-13T21:27:47.838331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:46.603151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:47.240349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:48.012403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:46.741531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:47.439685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:48.159808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:46.979274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:47.674290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:27:53.636211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOSSC_CCTR
WTCH_LA1.0000.4460.272
WTCH_LO0.4461.0000.586
SSC_CCTR0.2720.5861.000
2024-03-13T21:27:53.863838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WTCH_LAWTCH_LOSSC_CCTR
WTCH_LA1.0000.080-0.258
WTCH_LO0.0801.0000.661
SSC_CCTR-0.2580.6611.000

Missing values

2024-03-13T21:27:48.409131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:27:48.823059image/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
0202021500037.47556126.566273<NA><NA><NA><NA><NA><NA>97.03<NA><NA><NA>
1202021500037.475571126.566844<NA><NA><NA><NA><NA><NA>96.21<NA><NA><NA>
2202021500037.475583126.567415<NA><NA><NA><NA><NA><NA>95.4<NA><NA><NA>
3202021500037.475595126.567986<NA><NA><NA><NA><NA><NA>94.81<NA><NA><NA>
4202021500037.476055126.567971<NA><NA><NA><NA><NA><NA>94.61<NA><NA><NA>
5202021500037.476515126.567956<NA><NA><NA><NA><NA><NA>94.36<NA><NA><NA>
6202021500037.476975126.567941<NA><NA><NA><NA><NA><NA>94.09<NA><NA><NA>
7202021500037.475607126.568557<NA><NA><NA><NA><NA><NA>94.43<NA><NA><NA>
8202021500037.476067126.568542<NA><NA><NA><NA><NA><NA>94.17<NA><NA><NA>
9202021500037.476526126.568527<NA><NA><NA><NA><NA><NA>93.87<NA><NA><NA>
WTCH_YRWTCH_MNTHWTCH_DDWTCH_HHSWTCH_MINWTCH_SECWTCH_LAWTCH_LOWTCH_WTRLVWTCH_WTDPWTCH_CRSPDWTCH_CRDRCWTCH_WTEMWTCH_SLNTYSSC_CCTRMVMN_DRCMVMN_VEWTDP_VARTION_QY
90202021500037.475252126.57371<NA><NA><NA><NA><NA><NA>127.82<NA><NA><NA>
91202021500037.475712126.573695<NA><NA><NA><NA><NA><NA>113.81<NA><NA><NA>
92202021500037.476172126.57368<NA><NA><NA><NA><NA><NA>110.93<NA><NA><NA>
93202021500037.476632126.573665<NA><NA><NA><NA><NA><NA>109.29<NA><NA><NA>
94202021500037.477092126.57365<NA><NA><NA><NA><NA><NA>106.77<NA><NA><NA>
95202021500037.477552126.573635<NA><NA><NA><NA><NA><NA>104.57<NA><NA><NA>
96202021500037.478012126.57362<NA><NA><NA><NA><NA><NA>103.67<NA><NA><NA>
97202021500037.478472126.573606<NA><NA><NA><NA><NA><NA>103.0<NA><NA><NA>
98202021500037.478932126.573591<NA><NA><NA><NA><NA><NA>102.3<NA><NA><NA>
99202021500037.479392126.573576<NA><NA><NA><NA><NA><NA>101.43<NA><NA><NA>