Overview

Dataset statistics

Number of variables7
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory63.4 B

Variable types

DateTime1
Numeric6

Dataset

Description제주에너지공사가 소유한 태양광발전단지에서 계측되는 전력생산량 데이터 전체 총합량(19년도에는 발전단지별로 구분되어 있지 않습니다.)
Author제주에너지공사
URLhttps://www.data.go.kr/data/15038930/fileData.do

Alerts

교래태양광 is highly overall correlated with 종합경기장 태양광 and 4 other fieldsHigh correlation
종합경기장 태양광 is highly overall correlated with 교래태양광 and 4 other fieldsHigh correlation
행원태양광 is highly overall correlated with 교래태양광 and 4 other fieldsHigh correlation
홍보관주차장 태양광 is highly overall correlated with 교래태양광 and 4 other fieldsHigh correlation
수산태양광 is highly overall correlated with 교래태양광 and 4 other fieldsHigh correlation
태양광전체 is highly overall correlated with 교래태양광 and 4 other fieldsHigh correlation
일시 has unique valuesUnique
교래태양광 has unique valuesUnique
종합경기장 태양광 has unique valuesUnique
행원태양광 has unique valuesUnique
수산태양광 has unique valuesUnique
태양광전체 has unique valuesUnique
교래태양광 has 1 (1.1%) zerosZeros

Reproduction

Analysis started2024-03-15 00:13:26.490466
Analysis finished2024-03-15 00:13:36.297750
Duration9.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일시
Date

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size864.0 B
Minimum2023-10-01 00:00:00
Maximum2023-12-31 00:00:00
2024-03-15T09:13:36.516230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:36.893425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

교래태양광
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1338.6891
Minimum0
Maximum2937.8
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T09:13:37.158674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile66.64
Q1568.9
median1412.4
Q32021.5
95-th percentile2581.08
Maximum2937.8
Range2937.8
Interquartile range (IQR)1452.6

Descriptive statistics

Standard deviation840.25017
Coefficient of variation (CV)0.62766639
Kurtosis-1.1630262
Mean1338.6891
Median Absolute Deviation (MAD)663.4
Skewness-0.038566474
Sum123159.4
Variance706020.35
MonotonicityNot monotonic
2024-03-15T09:13:37.501305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2565.6 1
 
1.1%
946.6 1
 
1.1%
1954.0 1
 
1.1%
2032.0 1
 
1.1%
1198.4 1
 
1.1%
1928.2 1
 
1.1%
1666.4 1
 
1.1%
1367.6 1
 
1.1%
875.8 1
 
1.1%
190.2 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
0.0 1
1.1%
0.2 1
1.1%
1.4 1
1.1%
18.0 1
1.1%
48.6 1
1.1%
81.4 1
1.1%
100.8 1
1.1%
105.0 1
1.1%
149.6 1
1.1%
186.6 1
1.1%
ValueCountFrequency (%)
2937.8 1
1.1%
2792.2 1
1.1%
2745.0 1
1.1%
2721.2 1
1.1%
2600.0 1
1.1%
2565.6 1
1.1%
2547.4 1
1.1%
2492.8 1
1.1%
2467.2 1
1.1%
2409.6 1
1.1%

종합경기장 태양광
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean959.7433
Minimum6.112
Maximum1924.192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T09:13:38.019517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.112
5-th percentile137.9648
Q1329.608
median1021.248
Q31584.888
95-th percentile1827.9088
Maximum1924.192
Range1918.08
Interquartile range (IQR)1255.28

Descriptive statistics

Standard deviation608.48255
Coefficient of variation (CV)0.63400552
Kurtosis-1.5056638
Mean959.7433
Median Absolute Deviation (MAD)596.56
Skewness-0.045871881
Sum88296.384
Variance370251.02
MonotonicityNot monotonic
2024-03-15T09:13:38.566253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1817.728 1
 
1.1%
803.04 1
 
1.1%
1373.536 1
 
1.1%
1409.792 1
 
1.1%
940.64 1
 
1.1%
1417.568 1
 
1.1%
1241.76 1
 
1.1%
633.216 1
 
1.1%
248.0 1
 
1.1%
127.2 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
6.112 1
1.1%
83.712 1
1.1%
121.792 1
1.1%
127.2 1
1.1%
135.36 1
1.1%
140.096 1
1.1%
147.872 1
1.1%
152.576 1
1.1%
176.928 1
1.1%
184.448 1
1.1%
ValueCountFrequency (%)
1924.192 1
1.1%
1903.616 1
1.1%
1889.856 1
1.1%
1865.6 1
1.1%
1840.352 1
1.1%
1817.728 1
1.1%
1813.952 1
1.1%
1704.544 1
1.1%
1688.032 1
1.1%
1681.216 1
1.1%

행원태양광
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.59826
Minimum0.216
Maximum660.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T09:13:39.072944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.216
5-th percentile23.1192
Q181.018
median272.448
Q3472.68
95-th percentile578.4624
Maximum660.6
Range660.384
Interquartile range (IQR)391.662

Descriptive statistics

Standard deviation201.84883
Coefficient of variation (CV)0.69459751
Kurtosis-1.3570244
Mean290.59826
Median Absolute Deviation (MAD)193.212
Skewness0.094069962
Sum26735.04
Variance40742.95
MonotonicityNot monotonic
2024-03-15T09:13:39.621127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
333.72 1
 
1.1%
135.072 1
 
1.1%
465.768 1
 
1.1%
496.728 1
 
1.1%
255.888 1
 
1.1%
494.712 1
 
1.1%
444.168 1
 
1.1%
229.824 1
 
1.1%
58.248 1
 
1.1%
31.536 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
0.216 1
1.1%
0.432 1
1.1%
16.704 1
1.1%
20.376 1
1.1%
21.456 1
1.1%
24.48 1
1.1%
24.912 1
1.1%
26.928 1
1.1%
30.168 1
1.1%
31.248 1
1.1%
ValueCountFrequency (%)
660.6 1
1.1%
652.752 1
1.1%
634.752 1
1.1%
598.608 1
1.1%
584.64 1
1.1%
573.408 1
1.1%
572.04 1
1.1%
570.888 1
1.1%
567.36 1
1.1%
563.76 1
1.1%

홍보관주차장 태양광
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205.97957
Minimum1.28
Maximum432.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T09:13:40.119498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.28
5-th percentile29.412
Q185.24
median189.04
Q3313.33
95-th percentile405.174
Maximum432.12
Range430.84
Interquartile range (IQR)228.09

Descriptive statistics

Standard deviation127.40202
Coefficient of variation (CV)0.61851778
Kurtosis-1.3087624
Mean205.97957
Median Absolute Deviation (MAD)119.66
Skewness0.086014738
Sum18950.12
Variance16231.276
MonotonicityNot monotonic
2024-03-15T09:13:40.626183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.8 2
 
2.2%
423.24 1
 
1.1%
100.52 1
 
1.1%
152.48 1
 
1.1%
274.96 1
 
1.1%
241.72 1
 
1.1%
144.4 1
 
1.1%
64.64 1
 
1.1%
45.72 1
 
1.1%
60.08 1
 
1.1%
Other values (81) 81
88.0%
ValueCountFrequency (%)
1.28 1
1.1%
3.8 1
1.1%
6.8 2
2.2%
26.64 1
1.1%
31.68 1
1.1%
37.84 1
1.1%
45.72 1
1.1%
47.32 1
1.1%
49.36 1
1.1%
51.44 1
1.1%
ValueCountFrequency (%)
432.12 1
1.1%
430.68 1
1.1%
423.24 1
1.1%
417.0 1
1.1%
411.4 1
1.1%
400.08 1
1.1%
397.88 1
1.1%
382.12 1
1.1%
368.0 1
1.1%
365.28 1
1.1%

수산태양광
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2940.3912
Minimum161.263
Maximum6000.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T09:13:41.123339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum161.263
5-th percentile469.6904
Q11595.8275
median3142.1215
Q33885.1647
95-th percentile5421.2971
Maximum6000.04
Range5838.777
Interquartile range (IQR)2289.3372

Descriptive statistics

Standard deviation1507.3296
Coefficient of variation (CV)0.51262893
Kurtosis-0.85207986
Mean2940.3912
Median Absolute Deviation (MAD)980.24
Skewness-0.029389119
Sum270515.99
Variance2272042.4
MonotonicityNot monotonic
2024-03-15T09:13:41.598896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3253.486 1
 
1.1%
2562.872 1
 
1.1%
4132.124 1
 
1.1%
4903.732 1
 
1.1%
2847.072 1
 
1.1%
4760.548 1
 
1.1%
3957.12 1
 
1.1%
3236.13 1
 
1.1%
1718.946 1
 
1.1%
603.836 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
161.263 1
1.1%
218.395 1
1.1%
352.177 1
1.1%
419.433 1
1.1%
425.939 1
1.1%
505.487 1
1.1%
585.757 1
1.1%
603.836 1
1.1%
799.089 1
1.1%
898.884 1
1.1%
ValueCountFrequency (%)
6000.04 1
1.1%
5650.033 1
1.1%
5598.687 1
1.1%
5473.582 1
1.1%
5423.683 1
1.1%
5419.345 1
1.1%
5330.397 1
1.1%
5248.68 1
1.1%
4968.818 1
1.1%
4957.97 1
1.1%

태양광전체
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5735.4014
Minimum404.439
Maximum11728.864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T09:13:41.918599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum404.439
5-th percentile895.0728
Q12827.915
median6251.0735
Q38200.638
95-th percentile9994.5742
Maximum11728.864
Range11324.425
Interquartile range (IQR)5372.723

Descriptive statistics

Standard deviation3085.8577
Coefficient of variation (CV)0.53803693
Kurtosis-1.2112442
Mean5735.4014
Median Absolute Deviation (MAD)2522.843
Skewness-0.19482618
Sum527656.93
Variance9522518
MonotonicityNot monotonic
2024-03-15T09:13:42.181009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8393.774 1
 
1.1%
4677.144 1
 
1.1%
8173.668 1
 
1.1%
9113.932 1
 
1.1%
5394.48 1
 
1.1%
8875.988 1
 
1.1%
7551.168 1
 
1.1%
5611.17 1
 
1.1%
2965.634 1
 
1.1%
998.492 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
404.439 1
1.1%
557.161 1
1.1%
571.465 1
1.1%
776.971 1
1.1%
835.631 1
1.1%
943.707 1
1.1%
998.492 1
1.1%
1002.213 1
1.1%
1112.988 1
1.1%
1241.801 1
1.1%
ValueCountFrequency (%)
11728.864 1
1.1%
10818.449 1
1.1%
10469.719 1
1.1%
10354.094 1
1.1%
10041.394 1
1.1%
9956.267 1
1.1%
9793.977 1
1.1%
9749.716 1
1.1%
9572.539 1
1.1%
9116.249 1
1.1%

Interactions

2024-03-15T09:13:34.185118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:26.798642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:28.622159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:30.395750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:31.697567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:33.080221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:34.430643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:27.123899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:28.914527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:30.707352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:31.947083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:33.314924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:34.696009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:27.455533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:29.226628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:30.907755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:32.171502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:33.519614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:34.847842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:27.776809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:29.527480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:31.155621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:32.397531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:33.745674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:34.988747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:28.046599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:29.807308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:31.394128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:32.630676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:33.886651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:35.139258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:28.348335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:30.102181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:31.546002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:32.882399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:13:34.034400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:13:42.366386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일시교래태양광종합경기장 태양광행원태양광홍보관주차장 태양광수산태양광태양광전체
일시1.0001.0001.0001.0001.0001.0001.000
교래태양광1.0001.0000.8930.7730.8640.8540.912
종합경기장 태양광1.0000.8931.0000.8300.8850.7710.838
행원태양광1.0000.7730.8301.0000.9170.8520.882
홍보관주차장 태양광1.0000.8640.8850.9171.0000.7870.867
수산태양광1.0000.8540.7710.8520.7871.0000.941
태양광전체1.0000.9120.8380.8820.8670.9411.000
2024-03-15T09:13:42.587429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교래태양광종합경기장 태양광행원태양광홍보관주차장 태양광수산태양광태양광전체
교래태양광1.0000.9230.8080.9260.8080.935
종합경기장 태양광0.9231.0000.8390.9440.7510.893
행원태양광0.8080.8391.0000.8710.9100.923
홍보관주차장 태양광0.9260.9440.8711.0000.7660.898
수산태양광0.8080.7510.9100.7661.0000.946
태양광전체0.9350.8930.9230.8980.9461.000

Missing values

2024-03-15T09:13:35.746711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:13:36.141376image/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

일시교래태양광종합경기장 태양광행원태양광홍보관주차장 태양광수산태양광태양광전체
02023-10-012565.61817.728333.72423.243253.4868393.774
12023-10-022721.21924.192652.752430.686000.0411728.864
22023-10-03559.6389.7693.16899.21143.3122285.04
32023-10-042547.41813.952448.56368.04571.8049749.716
42023-10-052937.81865.6177.192359.121632.1676971.879
52023-10-061414.21139.584363.384251.723168.1556337.043
62023-10-07454.4345.05675.31282.84919.8551877.463
72023-10-08497.4750.68847.66460.61458.6092814.961
82023-10-091104.01008.768428.112292.842683.645517.36
92023-10-102492.81636.512380.88397.883299.0468207.118
일시교래태양광종합경기장 태양광행원태양광홍보관주차장 태양광수산태양광태양광전체
822023-12-220.06.11267.53664.08419.433557.161
832023-12-2348.6202.65681.57685.01433.2991851.131
842023-12-24197.683.7120.4321.281521.5251804.549
852023-12-2581.4225.18466.16869.96799.0891241.801
862023-12-261063.0422.94431.24854.882171.6443743.716
872023-12-271147.41055.84373.176188.43400.2886165.104
882023-12-28954.6797.632253.584156.42719.7974882.013
892023-12-291568.0771.328350.64188.043859.4936737.501
902023-12-301454.41026.752335.016189.683644.7166650.564
912023-12-31222.6176.92836.86454.481196.8261687.698