Overview

Dataset statistics

Number of variables8
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory73.4 B

Variable types

Numeric2
Categorical5
DateTime1

Dataset

Description샘플 데이터
Author한국생산기술연구원
URLhttps://www.bigdata-region.kr/#/dataset/6c1bf739-d62e-499a-a127-695086fa19a0

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
외부기온 is highly overall correlated with 예측발전량 and 1 other fieldsHigh correlation
일사량 is highly overall correlated with 예측발전량 and 1 other fieldsHigh correlation
예측발전량 is highly overall correlated with 인버터번호 and 2 other fieldsHigh correlation
인버터번호 is highly overall correlated with 예측발전량High correlation

Reproduction

Analysis started2023-12-10 14:10:11.523304
Analysis finished2023-12-10 14:10:13.429690
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발전소번호
Real number (ℝ)

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean497
Minimum1
Maximum961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:13.521688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q1201
median481
Q3801
95-th percentile961
Maximum961
Range960
Interquartile range (IQR)600

Descriptive statistics

Standard deviation320.96407
Coefficient of variation (CV)0.64580295
Kurtosis-1.2301516
Mean497
Median Absolute Deviation (MAD)320
Skewness-0.11917823
Sum14910
Variance103017.93
MonotonicityNot monotonic
2023-12-10T23:10:13.685151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
641 5
16.7%
801 5
16.7%
481 4
13.3%
321 4
13.3%
961 4
13.3%
1 4
13.3%
161 4
13.3%
ValueCountFrequency (%)
1 4
13.3%
161 4
13.3%
321 4
13.3%
481 4
13.3%
641 5
16.7%
801 5
16.7%
961 4
13.3%
ValueCountFrequency (%)
961 4
13.3%
801 5
16.7%
641 5
16.7%
481 4
13.3%
321 4
13.3%
161 4
13.3%
1 4
13.3%

인버터번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
15 
2
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 15
50.0%
2 15
50.0%

Length

2023-12-10T23:10:13.863756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:14.017503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 15
50.0%
2 15
50.0%

생성일시
Date

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2016-06-01 10:00:00
Maximum2016-06-01 12:00:00
2023-12-10T23:10:14.135303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:14.343400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

예측발전량
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean288.63333
Minimum269
Maximum318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:14.544916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum269
5-th percentile269
Q1277
median298
Q3303
95-th percentile307.95
Maximum318
Range49
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.661249
Coefficient of variation (CV)0.054260014
Kurtosis-1.5306305
Mean288.63333
Median Absolute Deviation (MAD)17
Skewness0.0057394837
Sum8659
Variance245.27471
MonotonicityNot monotonic
2023-12-10T23:10:14.743787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
269 7
23.3%
277 7
23.3%
298 7
23.3%
303 7
23.3%
318 1
 
3.3%
312 1
 
3.3%
ValueCountFrequency (%)
269 7
23.3%
277 7
23.3%
298 7
23.3%
303 7
23.3%
312 1
 
3.3%
318 1
 
3.3%
ValueCountFrequency (%)
318 1
 
3.3%
312 1
 
3.3%
303 7
23.3%
298 7
23.3%
277 7
23.3%
269 7
23.3%

일사량
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
712.7
14 
796.2
14 
846.6
2 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row712.7
2nd row712.7
3rd row712.7
4th row712.7
5th row712.7

Common Values

ValueCountFrequency (%)
712.7 14
46.7%
796.2 14
46.7%
846.6 2
 
6.7%

Length

2023-12-10T23:10:14.949159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:15.135009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
712.7 14
46.7%
796.2 14
46.7%
846.6 2
 
6.7%

외부기온
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
38.6
14 
40.0
14 
40.7
2 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38.6
2nd row38.6
3rd row38.6
4th row38.6
5th row38.6

Common Values

ValueCountFrequency (%)
38.6 14
46.7%
40.0 14
46.7%
40.7 2
 
6.7%

Length

2023-12-10T23:10:15.426442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:15.593954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38.6 14
46.7%
40.0 14
46.7%
40.7 2
 
6.7%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
전라북도
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 30
100.0%

Length

2023-12-10T23:10:15.905736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:16.217391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 30
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
익산시
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
익산시 30
100.0%

Length

2023-12-10T23:10:16.507271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:16.651057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
익산시 30
100.0%

Interactions

2023-12-10T23:10:12.707665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:12.430742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:12.947053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:12.566801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:10:16.753174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전소번호인버터번호생성일시예측발전량일사량외부기온
발전소번호1.0000.0000.0000.0000.0000.000
인버터번호0.0001.0000.0001.0000.0000.000
생성일시0.0000.0001.0001.0001.0001.000
예측발전량0.0001.0001.0001.0001.0001.000
일사량0.0000.0001.0001.0001.0001.000
외부기온0.0000.0001.0001.0001.0001.000
2023-12-10T23:10:16.934293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인버터번호외부기온일사량
인버터번호1.0000.0000.000
외부기온0.0001.0001.000
일사량0.0001.0001.000
2023-12-10T23:10:17.160917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전소번호예측발전량인버터번호일사량외부기온
발전소번호1.0000.0820.0000.0000.000
예측발전량0.0821.0000.9260.9430.943
인버터번호0.0000.9261.0000.0000.000
일사량0.0000.9430.0001.0001.000
외부기온0.0000.9430.0001.0001.000

Missing values

2023-12-10T23:10:13.139992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:10:13.348358image/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

발전소번호인버터번호생성일시예측발전량일사량외부기온시도명시군구명
048112016-06-01 10:00269712.738.6전라북도익산시
132122016-06-01 10:00277712.738.6전라북도익산시
296122016-06-01 10:00277712.738.6전라북도익산시
3112016-06-01 10:00269712.738.6전라북도익산시
464112016-06-01 10:00269712.738.6전라북도익산시
564122016-06-01 10:00277712.738.6전라북도익산시
616112016-06-01 10:00269712.738.6전라북도익산시
796112016-06-01 10:00269712.738.6전라북도익산시
816122016-06-01 10:00277712.738.6전라북도익산시
932112016-06-01 10:00269712.738.6전라북도익산시
발전소번호인버터번호생성일시예측발전량일사량외부기온시도명시군구명
2096112016-06-01 11:00298796.240.0전라북도익산시
2148122016-06-01 11:00303796.240.0전라북도익산시
22122016-06-01 11:00303796.240.0전라북도익산시
2316112016-06-01 11:00298796.240.0전라북도익산시
2480122016-06-01 11:00303796.240.0전라북도익산시
2564122016-06-01 11:00303796.240.0전라북도익산시
2680112016-06-01 11:00298796.240.0전라북도익산시
2716122016-06-01 11:00303796.240.0전라북도익산시
2864122016-06-01 12:00318846.640.7전라북도익산시
2980112016-06-01 12:00312846.640.7전라북도익산시