Overview

Dataset statistics

Number of variables14
Number of observations34
Missing cells3
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory128.9 B

Variable types

Categorical8
Text1
Numeric5

Dataset

Description한국동서발전의 월간 태양광 발전량 정보입니다. 월간 태양광 발전량은 연도, 발전기명, 1월(Wh)~12월(Wh) 항목으로 구성됩니다.
Author한국동서발전(주)
URLhttps://www.data.go.kr/data/15088647/fileData.do

Alerts

연도 has constant value ""Constant
6월(Wh) has constant value ""Constant
7월(Wh) has constant value ""Constant
8월(Wh) has constant value ""Constant
9월(Wh) has constant value ""Constant
10월(Wh) has constant value ""Constant
11월(Wh) has constant value ""Constant
12월(Wh) has constant value ""Constant
1월(Wh) is highly overall correlated with 2월(Wh) and 3 other fieldsHigh correlation
2월(Wh) is highly overall correlated with 1월(Wh) and 3 other fieldsHigh correlation
3월(Wh) is highly overall correlated with 1월(Wh) and 3 other fieldsHigh correlation
4월(Wh) is highly overall correlated with 1월(Wh) and 3 other fieldsHigh correlation
5월(Wh) is highly overall correlated with 1월(Wh) and 3 other fieldsHigh correlation
1월(Wh) has 3 (8.8%) missing valuesMissing
발전기명 has unique valuesUnique
5월(Wh) has unique valuesUnique
1월(Wh) has 10 (29.4%) zerosZeros
2월(Wh) has 5 (14.7%) zerosZeros
3월(Wh) has 3 (8.8%) zerosZeros
4월(Wh) has 2 (5.9%) zerosZeros

Reproduction

Analysis started2023-12-12 15:14:31.300098
Analysis finished2023-12-12 15:14:34.810301
Duration3.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
2021
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 34
100.0%

Length

2023-12-13T00:14:34.874238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:34.965580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 34
100.0%

발전기명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-13T00:14:35.123366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12.5
Mean length10.294118
Min length5

Characters and Unicode

Total characters350
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row광양항어울림태양광
2nd row광양항광양냉장태양광
3rd row광양항태양광
4th row광양항황금물류센터태양광
5th row당진매립장태양광
ValueCountFrequency (%)
태양광 13
25.0%
발전설비 5
 
9.6%
광양항어울림태양광 1
 
1.9%
광양항광양냉장태양광 1
 
1.9%
한공건설 1
 
1.9%
티에스엠텍 1
 
1.9%
테라테크 1
 
1.9%
창신인터내셔날 1
 
1.9%
정일울산 1
 
1.9%
이레테크(2 1
 
1.9%
Other values (26) 26
50.0%
2023-12-13T00:14:35.489274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 41
 
11.7%
광 39
 
11.1%
태 34
 
9.7%
18
 
5.1%
당 9
 
2.6%
진 9
 
2.6%
장 7
 
2.0%
산 6
 
1.7%
설 6
 
1.7%
수 6
 
1.7%
Other values (92) 175
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 308
88.0%
Space Separator 18
 
5.1%
Decimal Number 12
 
3.4%
Open Punctuation 4
 
1.1%
Close Punctuation 4
 
1.1%
Uppercase Letter 2
 
0.6%
Other Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 41
 
13.3%
광 39
 
12.7%
태 34
 
11.0%
당 9
 
2.9%
진 9
 
2.9%
장 7
 
2.3%
산 6
 
1.9%
설 6
 
1.9%
수 6
 
1.9%
발 5
 
1.6%
Other values (83) 146
47.4%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
2 4
33.3%
4 1
 
8.3%
3 1
 
8.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%
Other Punctuation
ValueCountFrequency (%)
# 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 308
88.0%
Common 40
 
11.4%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 41
 
13.3%
광 39
 
12.7%
태 34
 
11.0%
당 9
 
2.9%
진 9
 
2.9%
장 7
 
2.3%
산 6
 
1.9%
설 6
 
1.9%
수 6
 
1.9%
발 5
 
1.6%
Other values (83) 146
47.4%
Common
ValueCountFrequency (%)
18
45.0%
1 6
 
15.0%
( 4
 
10.0%
2 4
 
10.0%
) 4
 
10.0%
# 2
 
5.0%
4 1
 
2.5%
3 1
 
2.5%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 308
88.0%
ASCII 42
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 41
 
13.3%
광 39
 
12.7%
태 34
 
11.0%
당 9
 
2.9%
진 9
 
2.9%
장 7
 
2.3%
산 6
 
1.9%
설 6
 
1.9%
수 6
 
1.9%
발 5
 
1.6%
Other values (83) 146
47.4%
ASCII
ValueCountFrequency (%)
18
42.9%
1 6
 
14.3%
( 4
 
9.5%
2 4
 
9.5%
) 4
 
9.5%
C 2
 
4.8%
# 2
 
4.8%
4 1
 
2.4%
3 1
 
2.4%

1월(Wh)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct22
Distinct (%)71.0%
Missing3
Missing (%)8.8%
Infinite0
Infinite (%)0.0%
Mean1.2829051 × 108
Minimum0
Maximum2.2449533 × 109
Zeros10
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T00:14:35.661427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median43004112
Q391682400
95-th percentile2.6093124 × 108
Maximum2.2449533 × 109
Range2.2449533 × 109
Interquartile range (IQR)91682400

Descriptive statistics

Standard deviation3.9967776 × 108
Coefficient of variation (CV)3.1154117
Kurtosis28.715767
Mean1.2829051 × 108
Median Absolute Deviation (MAD)43004112
Skewness5.2787276
Sum3.9770058 × 109
Variance1.5974231 × 1017
MonotonicityNot monotonic
2023-12-13T00:14:35.824201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 10
29.4%
73250640 1
 
2.9%
18589820 1
 
2.9%
17402600 1
 
2.9%
11534560 1
 
2.9%
43004112 1
 
2.9%
32762520 1
 
2.9%
10105715 1
 
2.9%
134202000 1
 
2.9%
216550800 1
 
2.9%
Other values (12) 12
35.3%
(Missing) 3
 
8.8%
ValueCountFrequency (%)
0 10
29.4%
10105715 1
 
2.9%
11534560 1
 
2.9%
17402600 1
 
2.9%
18589820 1
 
2.9%
32762520 1
 
2.9%
43004112 1
 
2.9%
45909600 1
 
2.9%
46925716 1
 
2.9%
48748368 1
 
2.9%
ValueCountFrequency (%)
2244953286 1
2.9%
305311680 1
2.9%
216550800 1
2.9%
185335200 1
2.9%
134202000 1
2.9%
126451800 1
2.9%
122117400 1
2.9%
106760928 1
2.9%
76603872 1
2.9%
73250640 1
2.9%

2월(Wh)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7531361 × 108
Minimum0
Maximum2.7584135 × 109
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T00:14:35.954453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131723785
median70522560
Q31.541808 × 108
95-th percentile3.3568878 × 108
Maximum2.7584135 × 109
Range2.7584135 × 109
Interquartile range (IQR)1.2245702 × 108

Descriptive statistics

Standard deviation4.6596053 × 108
Coefficient of variation (CV)2.6578685
Kurtosis31.047119
Mean1.7531361 × 108
Median Absolute Deviation (MAD)52743461
Skewness5.4695521
Sum5.9606629 × 109
Variance2.1711921 × 1017
MonotonicityNot monotonic
2023-12-13T00:14:36.100119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 5
 
14.7%
64750560 1
 
2.9%
201306000 1
 
2.9%
32533080 1
 
2.9%
31454020 1
 
2.9%
203550504 1
 
2.9%
53888044 1
 
2.9%
27326440 1
 
2.9%
4567540 1
 
2.9%
54850438 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
0 5
14.7%
4567540 1
 
2.9%
11135990 1
 
2.9%
27326440 1
 
2.9%
31454020 1
 
2.9%
32533080 1
 
2.9%
33443280 1
 
2.9%
45247152 1
 
2.9%
53888044 1
 
2.9%
54850438 1
 
2.9%
ValueCountFrequency (%)
2758413481 1
2.9%
389835600 1
2.9%
306532800 1
2.9%
250648200 1
2.9%
213163200 1
2.9%
203550504 1
2.9%
201306000 1
2.9%
158380200 1
2.9%
154375200 1
2.9%
153597600 1
2.9%

3월(Wh)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.179884 × 108
Minimum0
Maximum3.3835292 × 109
Zeros3
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T00:14:36.276803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q139669530
median1.0051907 × 108
Q31.894599 × 108
95-th percentile4.2317269 × 108
Maximum3.3835292 × 109
Range3.3835292 × 109
Interquartile range (IQR)1.4979037 × 108

Descriptive statistics

Standard deviation5.7097088 × 108
Coefficient of variation (CV)2.6192718
Kurtosis31.059974
Mean2.179884 × 108
Median Absolute Deviation (MAD)63835716
Skewness5.4711762
Sum7.4116056 × 109
Variance3.2600774 × 1017
MonotonicityNot monotonic
2023-12-13T00:14:36.435218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 3
 
8.8%
50720112 1
 
2.9%
213440400 1
 
2.9%
191505600 1
 
2.9%
12884850 1
 
2.9%
116612821 1
 
2.9%
118567440 1
 
2.9%
38772360 1
 
2.9%
85226400 1
 
2.9%
329712000 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
0 3
8.8%
3304488 1
 
2.9%
8035576 1
 
2.9%
12884850 1
 
2.9%
35677960 1
 
2.9%
37688740 1
 
2.9%
38772360 1
 
2.9%
42361040 1
 
2.9%
50631100 1
 
2.9%
50720112 1
 
2.9%
ValueCountFrequency (%)
3383529244 1
2.9%
459475920 1
2.9%
403624800 1
2.9%
329712000 1
2.9%
278798400 1
2.9%
236054290 1
2.9%
221913000 1
2.9%
213440400 1
2.9%
191505600 1
2.9%
183322800 1
2.9%

4월(Wh)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4250607 × 108
Minimum0
Maximum3.5437449 × 109
Zeros2
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T00:14:36.584426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8044602.8
Q156243010
median1.1728774 × 108
Q32.1513075 × 108
95-th percentile4.701814 × 108
Maximum3.5437449 × 109
Range3.5437449 × 109
Interquartile range (IQR)1.5888774 × 108

Descriptive statistics

Standard deviation5.9587607 × 108
Coefficient of variation (CV)2.4571594
Kurtosis30.961375
Mean2.4250607 × 108
Median Absolute Deviation (MAD)66712412
Skewness5.4589242
Sum8.2452063 × 109
Variance3.5506829 × 1017
MonotonicityNot monotonic
2023-12-13T00:14:36.717819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 2
 
5.9%
96456960 1
 
2.9%
60847680 1
 
2.9%
203823600 1
 
2.9%
16183535 1
 
2.9%
124662290 1
 
2.9%
129556800 1
 
2.9%
54708120 1
 
2.9%
112917563 1
 
2.9%
101030400 1
 
2.9%
Other values (23) 23
67.6%
ValueCountFrequency (%)
0 2
5.9%
12376312 1
2.9%
16183535 1
2.9%
27787888 1
2.9%
46935580 1
2.9%
47445640 1
2.9%
53705020 1
2.9%
54708120 1
2.9%
60847680 1
2.9%
61377700 1
2.9%
ValueCountFrequency (%)
3543744871 1
2.9%
474878400 1
2.9%
467652240 1
2.9%
333703200 1
2.9%
321307200 1
2.9%
307059351 1
2.9%
255922200 1
2.9%
223292400 1
2.9%
218899800 1
2.9%
203823600 1
2.9%

5월(Wh)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2979578 × 108
Minimum12208280
Maximum3.1353776 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T00:14:36.910383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12208280
5-th percentile22457435
Q154667989
median1.060858 × 108
Q32.051103 × 108
95-th percentile4.5878372 × 108
Maximum3.1353776 × 109
Range3.1231693 × 109
Interquartile range (IQR)1.5044231 × 108

Descriptive statistics

Standard deviation5.2637869 × 108
Coefficient of variation (CV)2.2906369
Kurtosis30.466524
Mean2.2979578 × 108
Median Absolute Deviation (MAD)54322744
Skewness5.4002307
Sum7.8130566 × 109
Variance2.7707452 × 1017
MonotonicityNot monotonic
2023-12-13T00:14:37.046444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
95080800 1
 
2.9%
96710723 1
 
2.9%
181056000 1
 
2.9%
15346575 1
 
2.9%
117926086 1
 
2.9%
121065120 1
 
2.9%
49258440 1
 
2.9%
54113712 1
 
2.9%
51891620 1
 
2.9%
213128400 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
12208280 1
2.9%
15346575 1
2.9%
26286360 1
2.9%
44685140 1
2.9%
45139280 1
2.9%
49258440 1
2.9%
51634500 1
2.9%
51891620 1
2.9%
54113712 1
2.9%
56330820 1
2.9%
ValueCountFrequency (%)
3135377608 1
2.9%
477904800 1
2.9%
448487760 1
2.9%
333386400 1
2.9%
303010200 1
2.9%
288433512 1
2.9%
267237000 1
2.9%
221400000 1
2.9%
213128400 1
2.9%
181056000 1
2.9%

6월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:37.205362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:37.332765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

7월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:37.480727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:37.595176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

8월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:37.709595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:37.806397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

9월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:37.926856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:38.023687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

10월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:38.120369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:38.222147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

11월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:38.334185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:38.452145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

12월(Wh)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
100.0%

Length

2023-12-13T00:14:38.568415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:14:38.675151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

Interactions

2023-12-13T00:14:33.885840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:31.601527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.116322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.779752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.448025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.957877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:31.698642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.239202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.880857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.548647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:34.025759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:31.782498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.368619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.002756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.627923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:34.101706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:31.876919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.525647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.131437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.717211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:34.181314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:31.995836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:32.660291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.270680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:33.808224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:14:38.748917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전기명1월(Wh)2월(Wh)3월(Wh)4월(Wh)5월(Wh)
발전기명1.0001.0001.0001.0001.0001.000
1월(Wh)1.0001.0001.0000.9850.9850.985
2월(Wh)1.0001.0001.0000.9630.9630.993
3월(Wh)1.0000.9850.9631.0001.0000.993
4월(Wh)1.0000.9850.9631.0001.0000.993
5월(Wh)1.0000.9850.9930.9930.9931.000
2023-12-13T00:14:38.861839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1월(Wh)2월(Wh)3월(Wh)4월(Wh)5월(Wh)
1월(Wh)1.0000.7450.7560.7210.674
2월(Wh)0.7451.0000.9890.9550.918
3월(Wh)0.7560.9891.0000.9630.921
4월(Wh)0.7210.9550.9631.0000.967
5월(Wh)0.6740.9180.9210.9671.000

Missing values

2023-12-13T00:14:34.557688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:14:34.741619image/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

연도발전기명1월(Wh)2월(Wh)3월(Wh)4월(Wh)5월(Wh)6월(Wh)7월(Wh)8월(Wh)9월(Wh)10월(Wh)11월(Wh)12월(Wh)
02021광양항어울림태양광45909600647505608522640096456960950808000000000
12021광양항광양냉장태양광0001010304001012858470000000
22021광양항태양광1221174001583802002219130002559222002672370000000000
32021광양항황금물류센터태양광1067609281166229121430157121560799681480029120000000
42021당진매립장태양광49454160762945601095658801381666801461270000000000
52021당진신행정동옥상태양광4692571663958972914722511022617531000915540000000
62021당진옥내저탄장지붕태양광3053116803898356004594759204676522404484877600000000
72021당진자재창고태양광48748368638621767398307287660432844662240000000
82021당진제1회처리장태양광224495328627584134813383529244354374487131353776080000000
92021당진제2회처리장수상태양광1853352002131632004036248004748784004779048000000000
연도발전기명1월(Wh)2월(Wh)3월(Wh)4월(Wh)5월(Wh)6월(Wh)7월(Wh)8월(Wh)9월(Wh)10월(Wh)11월(Wh)12월(Wh)
242021울산#4CC건물옥상태양광32762520334432803877236054708120492584400000000
252021울산태양광#143004112452471525072011260847680541137120000000
262021이레테크 태양광 발전설비<NA>5485043868290050112917563967107230000000
272021이레테크(2) 태양광 발전설비0000518916200000000
282021정일울산 태양광045675405063110061377700563308200000000
292021창신인터내셔날 태양광11534560273264403567796046935580446851400000000
302021테라테크 태양광0538880446501675982966215790546540000000
312021티에스엠텍 태양광02035505042360542903070593512884335120000000
322021한공건설 태양광17402600314540203768874047445640451392800000000
332021한국몰드(1) 태양광18589820325330804236104053705020516345000000000