Overview

Dataset statistics

Number of variables8
Number of observations29
Missing cells29
Missing cells (%)12.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory74.6 B

Variable types

Categorical2
Numeric5
Unsupported1

Dataset

DescriptionSample
Author㈜유에스티21
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT01UST007

Alerts

TYPHN_NM has constant value ""Constant
TYPHN_OBVP_NM has constant value ""Constant
TYPHN_WTCH_YMDHM is highly overall correlated with TYPHN_WTCH_ARCSRHigh correlation
TYPHN_WTCH_WNDRCT is highly overall correlated with TYPHN_WTCH_WNSPDHigh correlation
TYPHN_WTCH_WNSPD is highly overall correlated with TYPHN_WTCH_WNDRCTHigh correlation
TYPHN_WTCH_ARCSR is highly overall correlated with TYPHN_WTCH_YMDHMHigh correlation
TYPHN_WTCH_SGNFCT_WVHGH has 29 (100.0%) missing valuesMissing
TYPHN_WTCH_YMDHM has unique valuesUnique
TYPHN_WTCH_SGNFCT_WVHGH is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 12:48:58.298059
Analysis finished2024-03-13 12:49:02.325584
Duration4.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

TYPHN_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
제14호찬투
29 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제14호찬투
2nd row제14호찬투
3rd row제14호찬투
4th row제14호찬투
5th row제14호찬투

Common Values

ValueCountFrequency (%)
제14호찬투 29
100.0%

Length

2024-03-13T21:49:02.414850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:02.586983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제14호찬투 29
100.0%

TYPHN_OBVP_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
거문도조위관측소
29 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
거문도조위관측소 29
100.0%

Length

2024-03-13T21:49:02.738399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:02.873528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
거문도조위관측소 29
100.0%

TYPHN_WTCH_YMDHM
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0210906 × 1011
Minimum2.0210906 × 1011
Maximum2.0210906 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-13T21:49:03.014788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210906 × 1011
5-th percentile2.0210906 × 1011
Q12.0210906 × 1011
median2.0210906 × 1011
Q32.0210906 × 1011
95-th percentile2.0210906 × 1011
Maximum2.0210906 × 1011
Range1400
Interquartile range (IQR)700

Descriptive statistics

Standard deviation425.85614
Coefficient of variation (CV)2.1070611 × 10-9
Kurtosis-1.1983787
Mean2.0210906 × 1011
Median Absolute Deviation (MAD)370
Skewness0.0052143492
Sum5.8611628 × 1012
Variance181353.45
MonotonicityStrictly increasing
2024-03-13T21:49:03.223251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
202109060000 1
 
3.4%
202109060030 1
 
3.4%
202109061400 1
 
3.4%
202109061330 1
 
3.4%
202109061300 1
 
3.4%
202109061230 1
 
3.4%
202109061200 1
 
3.4%
202109061130 1
 
3.4%
202109061100 1
 
3.4%
202109061030 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
202109060000 1
3.4%
202109060030 1
3.4%
202109060100 1
3.4%
202109060130 1
3.4%
202109060200 1
3.4%
202109060230 1
3.4%
202109060300 1
3.4%
202109060330 1
3.4%
202109060400 1
3.4%
202109060430 1
3.4%
ValueCountFrequency (%)
202109061400 1
3.4%
202109061330 1
3.4%
202109061300 1
3.4%
202109061230 1
3.4%
202109061200 1
3.4%
202109061130 1
3.4%
202109061100 1
3.4%
202109061030 1
3.4%
202109061000 1
3.4%
202109060930 1
3.4%

TYPHN_WTCH_TDLV
Real number (ℝ)

Distinct17
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9482759
Minimum1
Maximum2.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-13T21:49:03.459886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.2
Q11.4
median1.9
Q32.5
95-th percentile2.9
Maximum2.9
Range1.9
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.61795786
Coefficient of variation (CV)0.31718191
Kurtosis-1.3709301
Mean1.9482759
Median Absolute Deviation (MAD)0.6
Skewness0.15770747
Sum56.5
Variance0.38187192
MonotonicityNot monotonic
2024-03-13T21:49:03.655265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1.2 4
13.8%
2.3 3
10.3%
2.9 3
10.3%
2.5 2
 
6.9%
1.7 2
 
6.9%
1.3 2
 
6.9%
1.4 2
 
6.9%
2.7 2
 
6.9%
1.0 1
 
3.4%
2.0 1
 
3.4%
Other values (7) 7
24.1%
ValueCountFrequency (%)
1.0 1
 
3.4%
1.2 4
13.8%
1.3 2
6.9%
1.4 2
6.9%
1.5 1
 
3.4%
1.6 1
 
3.4%
1.7 2
6.9%
1.8 1
 
3.4%
1.9 1
 
3.4%
2.0 1
 
3.4%
ValueCountFrequency (%)
2.9 3
10.3%
2.8 1
 
3.4%
2.7 2
6.9%
2.5 2
6.9%
2.3 3
10.3%
2.2 1
 
3.4%
2.1 1
 
3.4%
2.0 1
 
3.4%
1.9 1
 
3.4%
1.8 1
 
3.4%

TYPHN_WTCH_SGNFCT_WVHGH
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

TYPHN_WTCH_WNDRCT
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.748276
Minimum65
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-13T21:49:03.858023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.68
Q172.2
median81.8
Q385.4
95-th percentile93.78
Maximum107
Range42
Interquartile range (IQR)13.2

Descriptive statistics

Standard deviation9.2893803
Coefficient of variation (CV)0.11504122
Kurtosis1.0123388
Mean80.748276
Median Absolute Deviation (MAD)4.2
Skewness0.44217379
Sum2341.7
Variance86.292586
MonotonicityNot monotonic
2024-03-13T21:49:04.037376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
81.8 2
 
6.9%
83.8 2
 
6.9%
81.4 2
 
6.9%
107.0 1
 
3.4%
88.9 1
 
3.4%
84.6 1
 
3.4%
86.0 1
 
3.4%
77.1 1
 
3.4%
69.0 1
 
3.4%
68.6 1
 
3.4%
Other values (16) 16
55.2%
ValueCountFrequency (%)
65.0 1
3.4%
65.4 1
3.4%
68.6 1
3.4%
69.0 1
3.4%
69.8 1
3.4%
71.1 1
3.4%
71.9 1
3.4%
72.2 1
3.4%
77.1 1
3.4%
78.7 1
3.4%
ValueCountFrequency (%)
107.0 1
3.4%
95.3 1
3.4%
91.5 1
3.4%
88.9 1
3.4%
86.5 1
3.4%
86.0 1
3.4%
85.7 1
3.4%
85.4 1
3.4%
84.9 1
3.4%
84.8 1
3.4%

TYPHN_WTCH_WNSPD
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4827586
Minimum2.1
Maximum6.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-13T21:49:04.221268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.1
5-th percentile2.44
Q14
median4.4
Q35.2
95-th percentile6.02
Maximum6.6
Range4.5
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.1234732
Coefficient of variation (CV)0.25062095
Kurtosis-0.17423125
Mean4.4827586
Median Absolute Deviation (MAD)0.7
Skewness-0.33031924
Sum130
Variance1.2621921
MonotonicityNot monotonic
2024-03-13T21:49:04.438523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4.3 3
 
10.3%
4.1 2
 
6.9%
4.5 2
 
6.9%
5.9 2
 
6.9%
5.2 2
 
6.9%
3.8 1
 
3.4%
4.4 1
 
3.4%
4.2 1
 
3.4%
5.1 1
 
3.4%
5.0 1
 
3.4%
Other values (13) 13
44.8%
ValueCountFrequency (%)
2.1 1
3.4%
2.4 1
3.4%
2.5 1
3.4%
2.9 1
3.4%
3.4 1
3.4%
3.8 1
3.4%
3.9 1
3.4%
4.0 1
3.4%
4.1 2
6.9%
4.2 1
3.4%
ValueCountFrequency (%)
6.6 1
3.4%
6.1 1
3.4%
5.9 2
6.9%
5.7 1
3.4%
5.5 1
3.4%
5.4 1
3.4%
5.2 2
6.9%
5.1 1
3.4%
5.0 1
3.4%
4.7 1
3.4%

TYPHN_WTCH_ARCSR
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1015.9759
Minimum1014.6
Maximum1017.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-13T21:49:04.594615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1014.6
5-th percentile1015.06
Q11015.5
median1015.9
Q31016.2
95-th percentile1017.36
Maximum1017.4
Range2.8
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.69418769
Coefficient of variation (CV)0.00068327184
Kurtosis0.25669578
Mean1015.9759
Median Absolute Deviation (MAD)0.4
Skewness0.5983988
Sum29463.3
Variance0.48189655
MonotonicityNot monotonic
2024-03-13T21:49:04.797579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1015.5 4
13.8%
1016.0 3
 
10.3%
1016.1 3
 
10.3%
1015.6 3
 
10.3%
1017.4 2
 
6.9%
1015.7 2
 
6.9%
1014.6 1
 
3.4%
1014.9 1
 
3.4%
1015.3 1
 
3.4%
1016.2 1
 
3.4%
Other values (8) 8
27.6%
ValueCountFrequency (%)
1014.6 1
 
3.4%
1014.9 1
 
3.4%
1015.3 1
 
3.4%
1015.4 1
 
3.4%
1015.5 4
13.8%
1015.6 3
10.3%
1015.7 2
6.9%
1015.8 1
 
3.4%
1015.9 1
 
3.4%
1016.0 3
10.3%
ValueCountFrequency (%)
1017.4 2
6.9%
1017.3 1
 
3.4%
1017.1 1
 
3.4%
1016.8 1
 
3.4%
1016.4 1
 
3.4%
1016.3 1
 
3.4%
1016.2 1
 
3.4%
1016.1 3
10.3%
1016.0 3
10.3%
1015.9 1
 
3.4%

Interactions

2024-03-13T21:49:01.403670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:58.550331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.353996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.987205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.619463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:01.539246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:58.761650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.511852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.123526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.755815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:01.655044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:58.963070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.647595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.259685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.969199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:01.766160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.105438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.764538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.350225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:01.133457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:01.893692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.229114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:48:59.865238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:00.483939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:49:01.260554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:49:04.949922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
TYPHN_WTCH_YMDHMTYPHN_WTCH_TDLVTYPHN_WTCH_WNDRCTTYPHN_WTCH_WNSPDTYPHN_WTCH_ARCSR
TYPHN_WTCH_YMDHM1.0000.5070.3800.8300.701
TYPHN_WTCH_TDLV0.5071.0000.3710.7140.675
TYPHN_WTCH_WNDRCT0.3800.3711.0000.8090.657
TYPHN_WTCH_WNSPD0.8300.7140.8091.0000.908
TYPHN_WTCH_ARCSR0.7010.6750.6570.9081.000
2024-03-13T21:49:05.179273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
TYPHN_WTCH_YMDHMTYPHN_WTCH_TDLVTYPHN_WTCH_WNDRCTTYPHN_WTCH_WNSPDTYPHN_WTCH_ARCSR
TYPHN_WTCH_YMDHM1.0000.171-0.1960.389-0.553
TYPHN_WTCH_TDLV0.1711.000-0.1080.1720.411
TYPHN_WTCH_WNDRCT-0.196-0.1081.000-0.8910.259
TYPHN_WTCH_WNSPD0.3890.172-0.8911.000-0.271
TYPHN_WTCH_ARCSR-0.5530.4110.259-0.2711.000

Missing values

2024-03-13T21:49:02.072895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:49:02.246487image/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

TYPHN_NMTYPHN_OBVP_NMTYPHN_WTCH_YMDHMTYPHN_WTCH_TDLVTYPHN_WTCH_SGNFCT_WVHGHTYPHN_WTCH_WNDRCTTYPHN_WTCH_WNSPDTYPHN_WTCH_ARCSR
0제14호찬투거문도조위관측소2021090600002.3<NA>107.02.11017.4
1제14호찬투거문도조위관측소2021090600302.2<NA>91.52.51017.4
2제14호찬투거문도조위관측소2021090601001.9<NA>85.42.41017.3
3제14호찬투거문도조위관측소2021090601301.7<NA>95.32.91017.1
4제14호찬투거문도조위관측소2021090602001.5<NA>84.93.91016.8
5제14호찬투거문도조위관측소2021090602301.3<NA>85.73.41016.4
6제14호찬투거문도조위관측소2021090603001.2<NA>81.44.31016.1
7제14호찬투거문도조위관측소2021090603301.2<NA>71.15.71015.9
8제14호찬투거문도조위관측소2021090604001.2<NA>65.45.91015.5
9제14호찬투거문도조위관측소2021090604301.3<NA>69.85.41015.6
TYPHN_NMTYPHN_OBVP_NMTYPHN_WTCH_YMDHMTYPHN_WTCH_TDLVTYPHN_WTCH_SGNFCT_WVHGHTYPHN_WTCH_WNDRCTTYPHN_WTCH_WNSPDTYPHN_WTCH_ARCSR
19제14호찬투거문도조위관측소2021090609302.9<NA>81.84.71016.1
20제14호찬투거문도조위관측소2021090610002.8<NA>68.65.91016.1
21제14호찬투거문도조위관측소2021090610302.7<NA>69.06.11016.3
22제14호찬투거문도조위관측소2021090611002.5<NA>77.15.51016.2
23제14호찬투거문도조위관측소2021090611302.3<NA>83.85.01016.0
24제14호찬투거문도조위관측소2021090612002.0<NA>86.05.11015.7
25제14호찬투거문도조위관측소2021090612301.7<NA>84.64.21015.5
26제14호찬투거문도조위관측소2021090613001.4<NA>83.84.31015.3
27제14호찬투거문도조위관측소2021090613301.2<NA>81.44.41014.9
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