Overview

Dataset statistics

Number of variables8
Number of observations126
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory68.0 B

Variable types

Categorical5
Numeric3

Dataset

Description한국지역난방공사에서 운영하는 RPS태양광 연도별 운영현황 자료 (태양광명, 연도, 용량, 단위, 사업구분, 형식, 발전량)
Author한국지역난방공사
URLhttps://www.data.go.kr/data/15044218/fileData.do

Alerts

용량단위 has constant value ""Constant
발전량단위 has constant value ""Constant
태양광명 is highly overall correlated with 용량 and 3 other fieldsHigh correlation
형식 is highly overall correlated with 용량 and 3 other fieldsHigh correlation
사업구분 is highly overall correlated with 용량 and 2 other fieldsHigh correlation
용량 is highly overall correlated with 발전량 and 3 other fieldsHigh correlation
발전량 is highly overall correlated with 용량 and 2 other fieldsHigh correlation
발전량 has 2 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-12 22:45:24.380721
Analysis finished2023-12-12 22:45:25.625760
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

태양광명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
판교가압장태양광
12 
수원장안태양광
12 
경남태양광
12 
분당주차장태양광
12 
신안태양광
12 
Other values (17)
66 

Length

Max length13
Median length9
Mean length6.5396825
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row판교가압장태양광
2nd row수원영통태양광
3rd row수원장안태양광
4th row경남태양광
5th row분당주차장태양광

Common Values

ValueCountFrequency (%)
판교가압장태양광 12
9.5%
수원장안태양광 12
9.5%
경남태양광 12
9.5%
분당주차장태양광 12
9.5%
신안태양광 12
9.5%
수원영통태양광 12
9.5%
청주태양광 11
8.7%
대구태양광 11
8.7%
분당 제2호 주차장태양광 4
 
3.2%
함백태양광 4
 
3.2%
Other values (12) 24
19.0%

Length

2023-12-13T07:45:25.701022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
판교가압장태양광 12
 
8.2%
수원장안태양광 12
 
8.2%
경남태양광 12
 
8.2%
분당주차장태양광 12
 
8.2%
신안태양광 12
 
8.2%
수원영통태양광 12
 
8.2%
청주태양광 11
 
7.5%
대구태양광 11
 
7.5%
강릉태양광 6
 
4.1%
광양항태양광 6
 
4.1%
Other values (14) 40
27.4%

연도
Real number (ℝ)

Distinct12
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.619
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T07:45:25.812009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12015.25
median2019
Q32022
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation3.6548207
Coefficient of variation (CV)0.0018105549
Kurtosis-1.2210348
Mean2018.619
Median Absolute Deviation (MAD)3
Skewness-0.39842359
Sum254346
Variance13.357714
MonotonicityDecreasing
2023-12-13T07:45:25.936058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2022 22
17.5%
2023 20
15.9%
2021 10
7.9%
2020 10
7.9%
2019 8
 
6.3%
2018 8
 
6.3%
2017 8
 
6.3%
2016 8
 
6.3%
2015 8
 
6.3%
2014 8
 
6.3%
Other values (2) 16
12.7%
ValueCountFrequency (%)
2012 8
6.3%
2013 8
6.3%
2014 8
6.3%
2015 8
6.3%
2016 8
6.3%
2017 8
6.3%
2018 8
6.3%
2019 8
6.3%
2020 10
7.9%
2021 10
7.9%
ValueCountFrequency (%)
2023 20
15.9%
2022 22
17.5%
2021 10
7.9%
2020 10
7.9%
2019 8
 
6.3%
2018 8
 
6.3%
2017 8
 
6.3%
2016 8
 
6.3%
2015 8
 
6.3%
2014 8
 
6.3%

용량
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.96246
Minimum45.5
Maximum997.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T07:45:26.032775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45.5
5-th percentile45.5
Q170
median99.96
Q3396
95-th percentile992
Maximum997.6
Range952.1
Interquartile range (IQR)326

Descriptive statistics

Standard deviation314.18363
Coefficient of variation (CV)1.1902588
Kurtosis0.40080001
Mean263.96246
Median Absolute Deviation (MAD)43.96
Skewness1.4040859
Sum33259.27
Variance98711.355
MonotonicityNot monotonic
2023-12-13T07:45:26.463011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
99.96 24
19.0%
70.0 23
18.3%
56.0 12
9.5%
45.5 12
9.5%
806.4 12
9.5%
110.43 11
8.7%
997.6 6
 
4.8%
992.0 4
 
3.2%
81.6 4
 
3.2%
309.6 2
 
1.6%
Other values (8) 16
12.7%
ValueCountFrequency (%)
45.5 12
9.5%
56.0 12
9.5%
70.0 23
18.3%
81.6 4
 
3.2%
99.96 24
19.0%
110.43 11
8.7%
216.0 2
 
1.6%
259.2 2
 
1.6%
270.0 2
 
1.6%
309.6 2
 
1.6%
ValueCountFrequency (%)
997.6 6
4.8%
992.0 4
 
3.2%
806.4 12
9.5%
499.95 2
 
1.6%
498.0 2
 
1.6%
496.8 2
 
1.6%
456.0 2
 
1.6%
424.8 2
 
1.6%
309.6 2
 
1.6%
270.0 2
 
1.6%

용량단위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
kWp
126 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kWp 126
100.0%

Length

2023-12-13T07:45:26.592918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:45:26.704242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kwp 126
100.0%

사업구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
RPS
103 
발전차액지원
23 

Length

Max length6
Median length3
Mean length3.547619
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
RPS 103
81.7%
발전차액지원 23
 
18.3%

Length

2023-12-13T07:45:26.834442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:45:26.932135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
rps 103
81.7%
발전차액지원 23
 
18.3%

형식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
고정
103 
고정, 단축, 양축
12 
고정, 가변고정
11 

Length

Max length10
Median length2
Mean length3.2857143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고정 103
81.7%
고정, 단축, 양축 12
 
9.5%
고정, 가변고정 11
 
8.7%

Length

2023-12-13T07:45:27.045694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:45:27.149371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정 126
78.3%
단축 12
 
7.5%
양축 12
 
7.5%
가변고정 11
 
6.8%

발전량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct103
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266.87579
Minimum0
Maximum1344.11
Zeros2
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T07:45:27.280515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38.75525
Q168.038
median112
Q3350.33
95-th percentile995.06
Maximum1344.11
Range1344.11
Interquartile range (IQR)282.292

Descriptive statistics

Standard deviation323.81685
Coefficient of variation (CV)1.2133617
Kurtosis1.1330941
Mean266.87579
Median Absolute Deviation (MAD)51.86
Skewness1.5665872
Sum33626.35
Variance104857.36
MonotonicityNot monotonic
2023-12-13T07:45:27.455616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.14 2
 
1.6%
762.3 2
 
1.6%
80.39 2
 
1.6%
112.0 2
 
1.6%
80.0 2
 
1.6%
517.49 2
 
1.6%
163.62 2
 
1.6%
227.4 2
 
1.6%
267.32 2
 
1.6%
454.16 2
 
1.6%
Other values (93) 106
84.1%
ValueCountFrequency (%)
0.0 2
1.6%
35.7 1
0.8%
36.97 2
1.6%
38.14 2
1.6%
40.601 1
0.8%
50.0 1
0.8%
52.724 1
0.8%
54.093 1
0.8%
54.252 1
0.8%
55.196 1
0.8%
ValueCountFrequency (%)
1344.11 1
0.8%
1126.0 1
0.8%
1036.62 1
0.8%
1030.0 1
0.8%
1022.888 1
0.8%
998.0 2
1.6%
986.24 1
0.8%
972.617 1
0.8%
968.0 1
0.8%
966.054 1
0.8%

발전량단위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
MWh
126 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
MWh 126
100.0%

Length

2023-12-13T07:45:27.598694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:45:27.707918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mwh 126
100.0%

Interactions

2023-12-13T07:45:25.090273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:24.632121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:24.853329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:25.209142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:24.713348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:24.928485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:25.291913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:24.776762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:45:24.999035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:45:27.772120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
태양광명연도용량사업구분형식발전량
태양광명1.0000.0001.0001.0001.0000.930
연도0.0001.0000.0980.0000.0000.318
용량1.0000.0981.0000.6320.7650.921
사업구분1.0000.0000.6321.0001.0000.501
형식1.0000.0000.7651.0001.0000.841
발전량0.9300.3180.9210.5010.8411.000
2023-12-13T07:45:27.883689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
태양광명형식사업구분
태양광명1.0000.9200.916
형식0.9201.0000.996
사업구분0.9160.9961.000
2023-12-13T07:45:27.982398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도용량발전량태양광명사업구분형식
연도1.0000.3510.1690.0000.0000.000
용량0.3511.0000.9070.9350.6670.691
발전량0.1690.9071.0000.6730.4880.541
태양광명0.0000.9350.6731.0000.9160.920
사업구분0.0000.6670.4880.9161.0000.996
형식0.0000.6910.5410.9200.9961.000

Missing values

2023-12-13T07:45:25.408624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:45:25.582870image/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

태양광명연도용량용량단위사업구분형식발전량발전량단위
0판교가압장태양광202356.0kWpRPS고정38.14MWh
1수원영통태양광202399.96kWpRPS고정80.39MWh
2수원장안태양광202345.5kWpRPS고정36.97MWh
3경남태양광202399.96kWpRPS고정90.09MWh
4분당주차장태양광202370.0kWpRPS고정58.3MWh
5신안태양광2023806.4kWp발전차액지원고정, 단축, 양축693.63MWh
6함백태양광2023992.0kWpRPS고정998.0MWh
7분당 제2호 주차장태양광202381.6kWpRPS고정56.65MWh
8광양항태양광 1호2023456.0kWpRPS고정435.0MWh
9광양항태양광 2호2023498.0kWpRPS고정469.0MWh
태양광명연도용량용량단위사업구분형식발전량발전량단위
116대구태양광2013110.43kWp발전차액지원고정, 가변고정128.0MWh
117신안태양광2013806.4kWp발전차액지원고정, 단축, 양축1126.0MWh
118판교가압장태양광201256.0kWpRPS고정79.08MWh
119수원영통태양광201299.96kWpRPS고정128.43MWh
120수원장안태양광201245.5kWpRPS고정57.15MWh
121청주태양광201270.0kWpRPS고정86.22MWh
122경남태양광201299.96kWpRPS고정133.33MWh
123분당주차장태양광201270.0kWpRPS고정35.7MWh
124대구태양광2012110.43kWp발전차액지원고정, 가변고정123.1MWh
125신안태양광2012806.4kWp발전차액지원고정, 단축, 양축1036.62MWh