Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory113.0 B

Variable types

DateTime1
Categorical2
Numeric9

Dataset

Description한국동서발전의 영광백수풍력발전단지 1호기 10분 평균 발전량 데이터 정보입니다. 영광백수풍력발전단지 1호기 10분 평균 발전량 데이터는 일시, 발전기명(WTG), 발전기(Serial), 발전량(kWh), 최저풍속(m-s), 평균풍속(m-s), 최대풍속(m-s), 최소발전량(kW), 평균발전량(kW), 최대발전량(kW), 이용률(백분율), 가동율(백분율)의 항목으로 구성됩니다.
Author한국동서발전(주)
URLhttps://www.data.go.kr/data/15091978/fileData.do

Alerts

발전기명(WTG) has constant value ""Constant
발전기(Serial) has constant value ""Constant
발전량(kWh) is highly overall correlated with 최저풍속(m-s) and 6 other fieldsHigh correlation
최저풍속(m-s) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
평균풍속(m-s) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
최대풍속(m-s) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
최소발전량(kW) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
평균발전량(kW) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
최대발전량(kW) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
이용률(백분율) is highly overall correlated with 발전량(kWh) and 6 other fieldsHigh correlation
일시 has unique valuesUnique
발전량(kWh) has 2900 (29.0%) zerosZeros
최소발전량(kW) has 1715 (17.2%) zerosZeros
평균발전량(kW) has 1695 (17.0%) zerosZeros
최대발전량(kW) has 2831 (28.3%) zerosZeros
이용률(백분율) has 2900 (29.0%) zerosZeros
가동율(백분율) has 174 (1.7%) zerosZeros

Reproduction

Analysis started2023-12-12 21:32:48.869019
Analysis finished2023-12-12 21:33:00.184220
Duration11.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일시
Date

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-01-01 00:00:00
Maximum2020-12-31 23:20:00
2023-12-13T06:33:00.251518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:00.437002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발전기명(WTG)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
WTG01
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWTG01
2nd rowWTG01
3rd rowWTG01
4th rowWTG01
5th rowWTG01

Common Values

ValueCountFrequency (%)
WTG01 10000
100.0%

Length

2023-12-13T06:33:00.588254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:33:00.692392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
wtg01 10000
100.0%

발전기(Serial)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
U113-001
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU113-001
2nd rowU113-001
3rd rowU113-001
4th rowU113-001
5th rowU113-001

Common Values

ValueCountFrequency (%)
U113-001 10000
100.0%

Length

2023-12-13T06:33:00.806450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:33:00.924030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u113-001 10000
100.0%

발전량(kWh)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct787
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.161533
Minimum0
Maximum391.602
Zeros2900
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:01.040173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median29.297
Q3135.254
95-th percentile384.766
Maximum391.602
Range391.602
Interquartile range (IQR)135.254

Descriptive statistics

Standard deviation121.80121
Coefficient of variation (CV)1.3509221
Kurtosis0.55213057
Mean90.161533
Median Absolute Deviation (MAD)29.297
Skewness1.3708786
Sum901615.33
Variance14835.534
MonotonicityNot monotonic
2023-12-13T06:33:01.213628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2900
29.0%
387.695 230
 
2.3%
7.813 69
 
0.7%
12.695 68
 
0.7%
9.766 64
 
0.6%
388.184 61
 
0.6%
388.672 60
 
0.6%
17.578 58
 
0.6%
8.789 55
 
0.5%
4.883 53
 
0.5%
Other values (777) 6382
63.8%
ValueCountFrequency (%)
0.0 2900
29.0%
0.488 33
 
0.3%
0.977 38
 
0.4%
1.465 30
 
0.3%
1.953 34
 
0.3%
2.441 26
 
0.3%
2.93 33
 
0.3%
3.418 19
 
0.2%
3.906 45
 
0.4%
4.395 29
 
0.3%
ValueCountFrequency (%)
391.602 2
 
< 0.1%
390.625 2
 
< 0.1%
390.137 1
 
< 0.1%
389.648 5
 
0.1%
389.16 3
 
< 0.1%
388.672 60
 
0.6%
388.184 61
 
0.6%
387.695 230
2.3%
387.207 45
 
0.4%
386.719 42
 
0.4%

최저풍속(m-s)
Real number (ℝ)

HIGH CORRELATION 

Distinct5699
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4899647
Minimum0
Maximum15.541
Zeros65
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:01.397477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.163
Q11.372
median2.746
Q34.843
95-th percentile9.6484
Maximum15.541
Range15.541
Interquartile range (IQR)3.471

Descriptive statistics

Standard deviation2.8578782
Coefficient of variation (CV)0.81888455
Kurtosis1.0337825
Mean3.4899647
Median Absolute Deviation (MAD)1.6005
Skewness1.185198
Sum34899.647
Variance8.1674676
MonotonicityNot monotonic
2023-12-13T06:33:01.539779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 65
 
0.7%
0.033 30
 
0.3%
0.035 23
 
0.2%
0.032 23
 
0.2%
0.034 22
 
0.2%
0.036 21
 
0.2%
0.037 20
 
0.2%
7.616 18
 
0.2%
0.028 17
 
0.2%
0.031 16
 
0.2%
Other values (5689) 9745
97.5%
ValueCountFrequency (%)
0.0 65
0.7%
0.025 2
 
< 0.1%
0.026 4
 
< 0.1%
0.027 9
 
0.1%
0.028 17
 
0.2%
0.029 13
 
0.1%
0.03 16
 
0.2%
0.031 16
 
0.2%
0.032 23
 
0.2%
0.033 30
0.3%
ValueCountFrequency (%)
15.541 1
< 0.1%
15.178 1
< 0.1%
15.127 1
< 0.1%
15.106 1
< 0.1%
15.099 1
< 0.1%
15.042 1
< 0.1%
14.823 1
< 0.1%
14.816 1
< 0.1%
14.702 1
< 0.1%
14.589 1
< 0.1%

평균풍속(m-s)
Real number (ℝ)

HIGH CORRELATION 

Distinct6716
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3416605
Minimum0
Maximum22.851
Zeros33
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:01.695282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.85085
Q12.462
median4.4365
Q37.35475
95-th percentile12.8066
Maximum22.851
Range22.851
Interquartile range (IQR)4.89275

Descriptive statistics

Standard deviation3.7254155
Coefficient of variation (CV)0.69742648
Kurtosis0.63978726
Mean5.3416605
Median Absolute Deviation (MAD)2.2525
Skewness1.0078116
Sum53416.605
Variance13.878721
MonotonicityNot monotonic
2023-12-13T06:33:01.829994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 33
 
0.3%
7.616 19
 
0.2%
2.239 8
 
0.1%
2.165 7
 
0.1%
2.244 6
 
0.1%
2.096 6
 
0.1%
3.673 6
 
0.1%
3.855 6
 
0.1%
1.937 6
 
0.1%
3.304 6
 
0.1%
Other values (6706) 9897
99.0%
ValueCountFrequency (%)
0.0 33
0.3%
0.032 2
 
< 0.1%
0.034 1
 
< 0.1%
0.04 1
 
< 0.1%
0.041 1
 
< 0.1%
0.042 1
 
< 0.1%
0.044 1
 
< 0.1%
0.048 1
 
< 0.1%
0.053 1
 
< 0.1%
0.054 1
 
< 0.1%
ValueCountFrequency (%)
22.851 1
< 0.1%
22.255 1
< 0.1%
22.18 1
< 0.1%
21.839 1
< 0.1%
21.661 1
< 0.1%
20.982 1
< 0.1%
20.506 1
< 0.1%
20.407 1
< 0.1%
20.266 1
< 0.1%
19.858 1
< 0.1%

최대풍속(m-s)
Real number (ℝ)

HIGH CORRELATION 

Distinct7148
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1787977
Minimum0
Maximum35.183
Zeros33
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:01.984182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.48695
Q13.662
median6.149
Q39.83075
95-th percentile15.93005
Maximum35.183
Range35.183
Interquartile range (IQR)6.16875

Descriptive statistics

Standard deviation4.5849473
Coefficient of variation (CV)0.638679
Kurtosis0.99372518
Mean7.1787977
Median Absolute Deviation (MAD)2.871
Skewness1.0018066
Sum71787.977
Variance21.021742
MonotonicityNot monotonic
2023-12-13T06:33:02.110486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 33
 
0.3%
7.616 20
 
0.2%
3.867 7
 
0.1%
3.94 6
 
0.1%
4.241 6
 
0.1%
3.43 5
 
0.1%
7.786 5
 
0.1%
4.206 5
 
0.1%
12.175 5
 
0.1%
2.051 5
 
0.1%
Other values (7138) 9903
99.0%
ValueCountFrequency (%)
0.0 33
0.3%
0.034 1
 
< 0.1%
0.061 1
 
< 0.1%
0.062 1
 
< 0.1%
0.092 1
 
< 0.1%
0.098 1
 
< 0.1%
0.111 1
 
< 0.1%
0.151 1
 
< 0.1%
0.155 1
 
< 0.1%
0.158 1
 
< 0.1%
ValueCountFrequency (%)
35.183 1
< 0.1%
31.648 1
< 0.1%
31.048 1
< 0.1%
28.993 1
< 0.1%
28.739 1
< 0.1%
28.729 1
< 0.1%
28.116 1
< 0.1%
28.096 1
< 0.1%
27.984 1
< 0.1%
27.869 1
< 0.1%

최소발전량(kW)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3679
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean368.36227
Minimum-552.811
Maximum2323.564
Zeros1715
Zeros (%)17.2%
Negative1915
Negative (%)19.1%
Memory size166.0 KiB
2023-12-13T06:33:02.251353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-552.811
5-th percentile-19.084
Q10
median86.65
Q3468.573
95-th percentile1837.9777
Maximum2323.564
Range2876.375
Interquartile range (IQR)468.573

Descriptive statistics

Standard deviation588.21478
Coefficient of variation (CV)1.5968377
Kurtosis3.0557762
Mean368.36227
Median Absolute Deviation (MAD)86.869
Skewness1.9513133
Sum3683622.7
Variance345996.62
MonotonicityNot monotonic
2023-12-13T06:33:02.362513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1715
 
17.2%
-0.219 1098
 
11.0%
-29.614 30
 
0.3%
-30.711 26
 
0.3%
-30.492 24
 
0.2%
-29.833 23
 
0.2%
-30.053 22
 
0.2%
-31.15 22
 
0.2%
-28.956 21
 
0.2%
-29.395 21
 
0.2%
Other values (3669) 6998
70.0%
ValueCountFrequency (%)
-552.811 1
< 0.1%
-200.942 1
< 0.1%
-40.363 1
< 0.1%
-36.853 1
< 0.1%
-36.634 1
< 0.1%
-35.098 1
< 0.1%
-34.879 1
< 0.1%
-34.66 1
< 0.1%
-33.563 2
< 0.1%
-32.905 1
< 0.1%
ValueCountFrequency (%)
2323.564 1
 
< 0.1%
2323.125 1
 
< 0.1%
2322.247 1
 
< 0.1%
2319.615 1
 
< 0.1%
2318.079 1
 
< 0.1%
2317.86 1
 
< 0.1%
2317.422 1
 
< 0.1%
2316.982 1
 
< 0.1%
2316.544 3
< 0.1%
2316.324 2
< 0.1%

평균발전량(kW)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7219
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean543.84758
Minimum-17.616
Maximum2357.924
Zeros1695
Zeros (%)17.0%
Negative1246
Negative (%)12.5%
Memory size166.0 KiB
2023-12-13T06:33:02.475869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-17.616
5-th percentile-0.219
Q10
median177.1465
Q3812.604
95-th percentile2316.137
Maximum2357.924
Range2375.54
Interquartile range (IQR)812.604

Descriptive statistics

Standard deviation733.1386
Coefficient of variation (CV)1.3480589
Kurtosis0.5463692
Mean543.84758
Median Absolute Deviation (MAD)177.3625
Skewness1.3673618
Sum5438475.8
Variance537492.2
MonotonicityNot monotonic
2023-12-13T06:33:02.865100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1695
 
17.0%
-0.218 481
 
4.8%
-0.219 362
 
3.6%
-0.217 79
 
0.8%
-0.215 38
 
0.4%
-0.216 35
 
0.4%
750.463 18
 
0.2%
-0.212 12
 
0.1%
-0.001 8
 
0.1%
-0.213 6
 
0.1%
Other values (7209) 7266
72.7%
ValueCountFrequency (%)
-17.616 1
< 0.1%
-17.172 1
< 0.1%
-16.69 1
< 0.1%
-16.5 1
< 0.1%
-16.241 1
< 0.1%
-15.606 1
< 0.1%
-13.907 1
< 0.1%
-13.758 1
< 0.1%
-13.367 1
< 0.1%
-13.325 1
< 0.1%
ValueCountFrequency (%)
2357.924 1
< 0.1%
2353.38 1
< 0.1%
2349.236 1
< 0.1%
2348.38 1
< 0.1%
2348.289 1
< 0.1%
2347.196 1
< 0.1%
2345.428 1
< 0.1%
2343.981 1
< 0.1%
2343.945 1
< 0.1%
2343.904 1
< 0.1%

최대발전량(kW)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4117
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean716.14821
Minimum0
Maximum2440.269
Zeros2831
Zeros (%)28.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:02.993479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median281.451
Q31236.586
95-th percentile2378.187
Maximum2440.269
Range2440.269
Interquartile range (IQR)1236.586

Descriptive statistics

Standard deviation860.7202
Coefficient of variation (CV)1.2018744
Kurtosis-0.57710786
Mean716.14821
Median Absolute Deviation (MAD)281.451
Skewness0.98830695
Sum7161482.1
Variance740839.27
MonotonicityNot monotonic
2023-12-13T06:33:03.115547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2831
28.3%
750.463 18
 
0.2%
2377.09 13
 
0.1%
2367.657 13
 
0.1%
102.664 13
 
0.1%
2366.779 12
 
0.1%
2364.366 12
 
0.1%
2376.213 12
 
0.1%
103.103 12
 
0.1%
2369.193 12
 
0.1%
Other values (4107) 7052
70.5%
ValueCountFrequency (%)
0.0 2831
28.3%
0.877 1
 
< 0.1%
1.535 1
 
< 0.1%
1.754 1
 
< 0.1%
1.974 1
 
< 0.1%
2.193 1
 
< 0.1%
2.632 2
 
< 0.1%
3.29 1
 
< 0.1%
3.729 1
 
< 0.1%
3.948 1
 
< 0.1%
ValueCountFrequency (%)
2440.269 1
< 0.1%
2438.294 1
< 0.1%
2433.029 1
< 0.1%
2428.642 1
< 0.1%
2426.667 1
< 0.1%
2425.351 1
< 0.1%
2424.474 1
< 0.1%
2423.815 1
< 0.1%
2422.719 1
< 0.1%
2421.403 2
< 0.1%

이용률(백분율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct787
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.520403
Minimum0
Maximum102.157
Zeros2900
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:03.238580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7.643
Q335.284
95-th percentile100.374
Maximum102.157
Range102.157
Interquartile range (IQR)35.284

Descriptive statistics

Standard deviation31.774233
Coefficient of variation (CV)1.3509222
Kurtosis0.55213414
Mean23.520403
Median Absolute Deviation (MAD)7.643
Skewness1.3708796
Sum235204.03
Variance1009.6019
MonotonicityNot monotonic
2023-12-13T06:33:03.381318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2900
29.0%
101.138 230
 
2.3%
2.038 69
 
0.7%
3.312 68
 
0.7%
2.548 64
 
0.6%
101.265 61
 
0.6%
101.393 60
 
0.6%
4.586 58
 
0.6%
2.293 55
 
0.5%
1.274 53
 
0.5%
Other values (777) 6382
63.8%
ValueCountFrequency (%)
0.0 2900
29.0%
0.127 33
 
0.3%
0.255 38
 
0.4%
0.382 30
 
0.3%
0.51 34
 
0.3%
0.637 26
 
0.3%
0.764 33
 
0.3%
0.892 19
 
0.2%
1.019 45
 
0.4%
1.146 29
 
0.3%
ValueCountFrequency (%)
102.157 2
 
< 0.1%
101.902 2
 
< 0.1%
101.775 1
 
< 0.1%
101.647 5
 
0.1%
101.52 3
 
< 0.1%
101.393 60
 
0.6%
101.265 61
 
0.6%
101.138 230
2.3%
101.011 45
 
0.4%
100.883 42
 
0.4%

가동율(백분율)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.16461
Minimum0
Maximum100
Zeros174
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:33:03.502988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.331336
Coefficient of variation (CV)0.13580593
Kurtosis49.851236
Mean98.16461
Median Absolute Deviation (MAD)0
Skewness-7.1911214
Sum981646.1
Variance177.72452
MonotonicityNot monotonic
2023-12-13T06:33:03.617042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
100.0 9802
98.0%
0.0 174
 
1.7%
82.3 2
 
< 0.1%
88.7 2
 
< 0.1%
0.7 2
 
< 0.1%
92.3 2
 
< 0.1%
89.7 2
 
< 0.1%
96.3 1
 
< 0.1%
1.0 1
 
< 0.1%
13.7 1
 
< 0.1%
Other values (11) 11
 
0.1%
ValueCountFrequency (%)
0.0 174
1.7%
0.7 2
 
< 0.1%
1.0 1
 
< 0.1%
1.2 1
 
< 0.1%
4.7 1
 
< 0.1%
13.7 1
 
< 0.1%
27.7 1
 
< 0.1%
50.5 1
 
< 0.1%
53.0 1
 
< 0.1%
53.7 1
 
< 0.1%
ValueCountFrequency (%)
100.0 9802
98.0%
99.4 1
 
< 0.1%
97.7 1
 
< 0.1%
96.3 1
 
< 0.1%
93.7 1
 
< 0.1%
92.3 2
 
< 0.1%
89.7 2
 
< 0.1%
88.7 2
 
< 0.1%
82.7 1
 
< 0.1%
82.3 2
 
< 0.1%

Interactions

2023-12-13T06:32:59.072494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.200655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.201660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.301162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.297747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.282959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.261106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.150794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.231980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.177922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.302388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.363285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.424359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.432884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.421382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.377457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.249633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.325726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.265038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.405166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.489637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.551397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.541664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.545209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.515269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.605059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.442729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.348660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.492163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.582337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.662989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.635586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.638765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.601516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.694696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.536500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.436368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.592436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.716790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.763319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.749954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.767900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.691776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.781928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.632719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.514840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.701678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.815590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.858571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.868440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.867719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.807367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.882267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.741802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.590369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.832642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.929774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.960383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.960820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.953315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.891348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.980461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.818787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.684961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:51.941047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.042336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.074578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.076128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.050905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.969336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.080844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.908596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:59.772544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:52.071896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:53.153829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:54.193379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:55.176608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:56.171389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:57.059677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.156985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:32:58.988668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:33:03.694782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전량(kWh)최저풍속(m-s)평균풍속(m-s)최대풍속(m-s)최소발전량(kW)평균발전량(kW)최대발전량(kW)이용률(백분율)가동율(백분율)
발전량(kWh)1.0000.8860.9310.8770.8381.0000.9321.0000.085
최저풍속(m-s)0.8861.0000.9490.8980.8520.8870.8380.8860.119
평균풍속(m-s)0.9310.9491.0000.9660.8190.9330.8930.9310.201
최대풍속(m-s)0.8770.8980.9661.0000.7490.8790.8830.8770.245
최소발전량(kW)0.8380.8520.8190.7491.0000.8400.7640.8380.120
평균발전량(kW)1.0000.8870.9330.8790.8401.0000.9341.0000.089
최대발전량(kW)0.9320.8380.8930.8830.7640.9341.0000.9320.110
이용률(백분율)1.0000.8860.9310.8770.8381.0000.9321.0000.085
가동율(백분율)0.0850.1190.2010.2450.1200.0890.1100.0851.000
2023-12-13T06:33:03.817546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전량(kWh)최저풍속(m-s)평균풍속(m-s)최대풍속(m-s)최소발전량(kW)평균발전량(kW)최대발전량(kW)이용률(백분율)가동율(백분율)
발전량(kWh)1.0000.9240.9550.9470.9220.9830.9891.0000.170
최저풍속(m-s)0.9241.0000.9670.9300.8970.9220.9090.9240.054
평균풍속(m-s)0.9550.9671.0000.9860.8940.9470.9510.9550.035
최대풍속(m-s)0.9470.9300.9861.0000.8690.9350.9520.9470.026
최소발전량(kW)0.9220.8970.8940.8691.0000.9410.9020.9220.145
평균발전량(kW)0.9830.9220.9470.9350.9411.0000.9780.9830.165
최대발전량(kW)0.9890.9090.9510.9520.9020.9781.0000.9890.167
이용률(백분율)1.0000.9240.9550.9470.9220.9830.9891.0000.170
가동율(백분율)0.1700.0540.0350.0260.1450.1650.1670.1701.000

Missing values

2023-12-13T06:32:59.906149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:33:00.093177image/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

일시발전기명(WTG)발전기(Serial)발전량(kWh)최저풍속(m-s)평균풍속(m-s)최대풍속(m-s)최소발전량(kW)평균발전량(kW)최대발전량(kW)이용률(백분율)가동율(백분율)
335562020-08-24 15:00WTG01U113-0010.00.00.00.00.00.00.00.00.0
227772020-06-10 08:00WTG01U113-00121.9732.5174.1896.13426.982133.092224.6345.732100.0
490112020-12-14 02:50WTG01U113-001388.67212.56916.29219.7152303.3822334.7552380.161101.393100.0
218612020-06-03 23:20WTG01U113-00155.6643.9735.6376.708230.338337.373432.15814.521100.0
140942020-04-11 00:50WTG01U113-0010.00.3631.0011.9080.00.00.00.0100.0
313282020-08-08 23:40WTG01U113-001353.0277.94611.64316.3811251.0652121.7072384.98792.094100.0
477562020-12-05 09:40WTG01U113-00112.6951.4643.063.968-12.06475.775108.5883.312100.0
103292020-03-15 21:20WTG01U113-001387.20713.24818.42222.312301.4082334.292382.135101.011100.0
329202020-08-20 05:00WTG01U113-0010.00.0341.0192.216-0.219-0.2180.00.0100.0
444012020-11-12 02:30WTG01U113-0010.01.4462.3113.250.00.00.00.0100.0
일시발전기명(WTG)발전기(Serial)발전량(kWh)최저풍속(m-s)평균풍속(m-s)최대풍속(m-s)최소발전량(kW)평균발전량(kW)최대발전량(kW)이용률(백분율)가동율(백분율)
132342020-04-05 01:30WTG01U113-001377.939.52611.73113.7941697.0442276.3582399.68598.59100.0
420062020-10-26 11:20WTG01U113-00119.0432.3723.9465.0924.569114.745168.9144.968100.0
202782020-05-23 23:30WTG01U113-001114.7465.5216.9958.329546.01690.874859.92929.934100.0
102082020-03-15 01:10WTG01U113-001240.7236.9819.1810.6511003.3961447.0191689.80462.797100.0
398202020-10-11 07:00WTG01U113-0010.00.6131.3892.5610.00.00.00.0100.0
360352020-09-10 22:40WTG01U113-0010.00.1540.9682.014-0.219-0.2180.00.0100.0
35502020-01-28 19:30WTG01U113-0015.3712.0342.9153.575.48434.81366.2491.401100.0
257902020-07-01 06:10WTG01U113-001123.0476.0417.0498.259574.309742.204969.83332.099100.0
270212020-07-10 01:50WTG01U113-00167.8714.8635.937.121250.739405.611565.97317.706100.0
410132020-10-19 13:50WTG01U113-001102.0514.6896.7548.915421.848615.045906.21626.622100.0