Overview

Dataset statistics

Number of variables6
Number of observations3550
Missing cells1825
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory173.5 KiB
Average record size in memory50.0 B

Variable types

Numeric2
Text4

Dataset

Description전라북도 임실군 태양광 전기사업 데이터 입니다. 데이터 세부내역에는 발전소명, 설치장소소재지, 설비용량, 발전사업허가일자, 사업개시일을 포함하여 제공하고 있습니다.
Author전북특별자치도 임실군
URLhttps://www.data.go.kr/data/15042064/fileData.do

Alerts

사업개시일 has 1825 (51.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:29:38.182732
Analysis finished2024-04-29 22:29:40.100145
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct3550
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1775.5
Minimum1
Maximum3550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2024-04-30T07:29:40.165213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile178.45
Q1888.25
median1775.5
Q32662.75
95-th percentile3372.55
Maximum3550
Range3549
Interquartile range (IQR)1774.5

Descriptive statistics

Standard deviation1024.9411
Coefficient of variation (CV)0.57726897
Kurtosis-1.2
Mean1775.5
Median Absolute Deviation (MAD)887.5
Skewness0
Sum6303025
Variance1050504.2
MonotonicityStrictly increasing
2024-04-30T07:29:40.288140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2373 1
 
< 0.1%
2362 1
 
< 0.1%
2363 1
 
< 0.1%
2364 1
 
< 0.1%
2365 1
 
< 0.1%
2366 1
 
< 0.1%
2367 1
 
< 0.1%
2368 1
 
< 0.1%
2369 1
 
< 0.1%
Other values (3540) 3540
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3550 1
< 0.1%
3549 1
< 0.1%
3548 1
< 0.1%
3547 1
< 0.1%
3546 1
< 0.1%
3545 1
< 0.1%
3544 1
< 0.1%
3543 1
< 0.1%
3542 1
< 0.1%
3541 1
< 0.1%

발전소명
Text

Distinct3213
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-04-30T07:29:40.509854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length9.2059155
Min length3

Characters and Unicode

Total characters32681
Distinct characters467
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2970 ?
Unique (%)83.7%

Sample

1st row다우태양광㈜
2nd row선진태양광발전소
3rd row선진2호태양광발전소
4th row㈜서해에너지(오수태양광)
5th row승선태양광발전소
ValueCountFrequency (%)
상월에너지스테이션 21
 
0.6%
행복태양광발전소 8
 
0.2%
태양광발전소 8
 
0.2%
청웅태양광발전소 6
 
0.2%
에너지 6
 
0.2%
희망태양광발전소 5
 
0.1%
호암태양광발전소 5
 
0.1%
은혜태양광발전소 5
 
0.1%
써니태양광발전소 5
 
0.1%
양지2호태양광발전소 4
 
0.1%
Other values (3212) 3522
98.0%
2024-04-30T07:29:40.867732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 3288
 
10.1%
광 3237
 
9.9%
소 3228
 
9.9%
발 3219
 
9.8%
태 3200
 
9.8%
양 3189
 
9.8%
호 1791
 
5.5%
2 602
 
1.8%
1 599
 
1.8%
지 461
 
1.4%
Other values (457) 9867
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30356
92.9%
Decimal Number 2022
 
6.2%
Uppercase Letter 154
 
0.5%
Space Separator 45
 
0.1%
Lowercase Letter 25
 
0.1%
Close Punctuation 24
 
0.1%
Open Punctuation 24
 
0.1%
Dash Punctuation 22
 
0.1%
Other Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 3288
10.8%
광 3237
10.7%
소 3228
10.6%
발 3219
 
10.6%
태 3200
 
10.5%
양 3189
 
10.5%
호 1791
 
5.9%
지 461
 
1.5%
에 362
 
1.2%
너 326
 
1.1%
Other values (412) 8055
26.5%
Uppercase Letter
ValueCountFrequency (%)
S 26
16.9%
B 20
13.0%
J 16
10.4%
H 13
 
8.4%
K 9
 
5.8%
D 8
 
5.2%
A 8
 
5.2%
Y 7
 
4.5%
E 7
 
4.5%
N 6
 
3.9%
Other values (12) 34
22.1%
Decimal Number
ValueCountFrequency (%)
2 602
29.8%
1 599
29.6%
3 314
15.5%
4 155
 
7.7%
5 121
 
6.0%
6 68
 
3.4%
7 54
 
2.7%
8 45
 
2.2%
9 34
 
1.7%
0 30
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
o 6
24.0%
s 5
20.0%
r 3
12.0%
p 3
12.0%
w 3
12.0%
e 3
12.0%
y 1
 
4.0%
j 1
 
4.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30365
92.9%
Common 2137
 
6.5%
Latin 179
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 3288
10.8%
광 3237
10.7%
소 3228
10.6%
발 3219
 
10.6%
태 3200
 
10.5%
양 3189
 
10.5%
호 1791
 
5.9%
지 461
 
1.5%
에 362
 
1.2%
너 326
 
1.1%
Other values (413) 8064
26.6%
Latin
ValueCountFrequency (%)
S 26
14.5%
B 20
 
11.2%
J 16
 
8.9%
H 13
 
7.3%
K 9
 
5.0%
D 8
 
4.5%
A 8
 
4.5%
Y 7
 
3.9%
E 7
 
3.9%
N 6
 
3.4%
Other values (20) 59
33.0%
Common
ValueCountFrequency (%)
2 602
28.2%
1 599
28.0%
3 314
14.7%
4 155
 
7.3%
5 121
 
5.7%
6 68
 
3.2%
7 54
 
2.5%
8 45
 
2.1%
45
 
2.1%
9 34
 
1.6%
Other values (4) 100
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30356
92.9%
ASCII 2316
 
7.1%
None 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 3288
10.8%
광 3237
10.7%
소 3228
10.6%
발 3219
 
10.6%
태 3200
 
10.5%
양 3189
 
10.5%
호 1791
 
5.9%
지 461
 
1.5%
에 362
 
1.2%
너 326
 
1.1%
Other values (412) 8055
26.5%
ASCII
ValueCountFrequency (%)
2 602
26.0%
1 599
25.9%
3 314
13.6%
4 155
 
6.7%
5 121
 
5.2%
6 68
 
2.9%
7 54
 
2.3%
8 45
 
1.9%
45
 
1.9%
9 34
 
1.5%
Other values (34) 279
12.0%
None
ValueCountFrequency (%)
㈜ 9
100.0%

설치장소소재지
Text

Distinct2831
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-04-30T07:29:41.156582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length145
Median length73
Mean length16.981408
Min length9

Characters and Unicode

Total characters60284
Distinct characters151
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2453 ?
Unique (%)69.1%

Sample

1st row삼계면 오지리 511
2nd row삼계면 세심리 608-1, 외1건
3rd row삼계면 세심리608-3
4th row오수면 금암리 산34, 839, 840
5th row삼계면 세심리 605외1건
ValueCountFrequency (%)
관촌면 565
 
4.4%
임실읍 512
 
4.0%
삼계면 440
 
3.4%
오수면 375
 
2.9%
지사면 302
 
2.4%
임실군 286
 
2.2%
청웅면 267
 
2.1%
성수면 254
 
2.0%
강진면 197
 
1.5%
신덕면 191
 
1.5%
Other values (3266) 9368
73.4%
2024-04-30T07:29:41.611619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9266
 
15.4%
1 3928
 
6.5%
- 3598
 
6.0%
리 3512
 
5.8%
면 3038
 
5.0%
2 2713
 
4.5%
3 2215
 
3.7%
4 1957
 
3.2%
, 1897
 
3.1%
7 1723
 
2.9%
Other values (141) 26437
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24667
40.9%
Decimal Number 19875
33.0%
Space Separator 9266
 
15.4%
Dash Punctuation 3598
 
6.0%
Other Punctuation 1902
 
3.2%
Open Punctuation 474
 
0.8%
Close Punctuation 474
 
0.8%
Math Symbol 12
 
< 0.1%
Uppercase Letter 6
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 3512
 
14.2%
면 3038
 
12.3%
임 801
 
3.2%
실 798
 
3.2%
수 739
 
3.0%
관 663
 
2.7%
계 636
 
2.6%
삼 636
 
2.6%
덕 617
 
2.5%
오 608
 
2.5%
Other values (113) 12619
51.2%
Decimal Number
ValueCountFrequency (%)
1 3928
19.8%
2 2713
13.7%
3 2215
11.1%
4 1957
9.8%
7 1723
8.7%
5 1715
8.6%
6 1623
8.2%
8 1545
 
7.8%
9 1233
 
6.2%
0 1223
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 1897
99.7%
. 3
 
0.2%
: 1
 
0.1%
* 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
W 4
66.7%
A 1
 
16.7%
B 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 473
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 473
99.8%
] 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 11
91.7%
+ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
9266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3598
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 4
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35607
59.1%
Hangul 24667
40.9%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 3512
 
14.2%
면 3038
 
12.3%
임 801
 
3.2%
실 798
 
3.2%
수 739
 
3.0%
관 663
 
2.7%
계 636
 
2.6%
삼 636
 
2.6%
덕 617
 
2.5%
오 608
 
2.5%
Other values (113) 12619
51.2%
Common
ValueCountFrequency (%)
9266
26.0%
1 3928
11.0%
- 3598
 
10.1%
2 2713
 
7.6%
3 2215
 
6.2%
4 1957
 
5.5%
, 1897
 
5.3%
7 1723
 
4.8%
5 1715
 
4.8%
6 1623
 
4.6%
Other values (14) 4972
14.0%
Latin
ValueCountFrequency (%)
k 4
40.0%
W 4
40.0%
A 1
 
10.0%
B 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35617
59.1%
Hangul 24663
40.9%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9266
26.0%
1 3928
11.0%
- 3598
 
10.1%
2 2713
 
7.6%
3 2215
 
6.2%
4 1957
 
5.5%
, 1897
 
5.3%
7 1723
 
4.8%
5 1715
 
4.8%
6 1623
 
4.6%
Other values (18) 4982
14.0%
Hangul
ValueCountFrequency (%)
리 3512
 
14.2%
면 3038
 
12.3%
임 801
 
3.2%
실 798
 
3.2%
수 739
 
3.0%
관 663
 
2.7%
계 636
 
2.6%
삼 636
 
2.6%
덕 617
 
2.5%
오 608
 
2.5%
Other values (111) 12615
51.1%
Compat Jamo
ValueCountFrequency (%)
ㄱ 2
50.0%
ㄴ 2
50.0%

설비용량(KW)
Real number (ℝ)

Distinct609
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.03484
Minimum5.88
Maximum1500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.3 KiB
2024-04-30T07:29:41.748570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.88
5-th percentile30
Q199
median99.36
Q399.84
95-th percentile450.514
Maximum1500
Range1494.12
Interquartile range (IQR)0.84

Descriptive statistics

Standard deviation153.51857
Coefficient of variation (CV)1.1453632
Kurtosis20.176755
Mean134.03484
Median Absolute Deviation (MAD)0.39
Skewness4.3215909
Sum475823.7
Variance23567.952
MonotonicityNot monotonic
2024-04-30T07:29:41.882295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 562
 
15.8%
99.9 177
 
5.0%
99.96 159
 
4.5%
99.45 150
 
4.2%
99.2 137
 
3.9%
99.75 133
 
3.7%
99.4 116
 
3.3%
99.6 112
 
3.2%
99.36 94
 
2.6%
99.84 94
 
2.6%
Other values (599) 1816
51.2%
ValueCountFrequency (%)
5.88 1
< 0.1%
6.0 1
< 0.1%
7.0 1
< 0.1%
9.44 1
< 0.1%
9.52 2
0.1%
10.0 1
< 0.1%
10.71 1
< 0.1%
11.31 1
< 0.1%
11.6 1
< 0.1%
11.83 1
< 0.1%
ValueCountFrequency (%)
1500.0 1
 
< 0.1%
999.9 1
 
< 0.1%
999.75 2
 
0.1%
999.7 2
 
0.1%
999.68 1
 
< 0.1%
999.6 8
0.2%
999.45 3
 
0.1%
999.36 1
 
< 0.1%
999.24 1
 
< 0.1%
999.04 1
 
< 0.1%

허가일자
Text

Distinct663
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-04-30T07:29:42.136817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length10
Mean length10.003944
Min length10

Characters and Unicode

Total characters35514
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)5.0%

Sample

1st row2007-09-10
2nd row2007-10-29
3rd row2008-02-27
4th row2008-03-07
5th row2008-03-31
ValueCountFrequency (%)
2018-07-05 47
 
1.3%
2017-06-22 38
 
1.1%
2023-07-11 37
 
1.0%
2018-01-02 36
 
1.0%
2018-07-18 32
 
0.9%
2017-08-14 32
 
0.9%
2018-05-04 30
 
0.8%
2013-09-03 29
 
0.8%
2023-11-17 28
 
0.8%
2017-09-11 26
 
0.7%
Other values (653) 3216
90.6%
2024-04-30T07:29:42.494897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8000
22.5%
2 7587
21.4%
- 7102
20.0%
1 5198
14.6%
3 1529
 
4.3%
7 1432
 
4.0%
8 1336
 
3.8%
4 1086
 
3.1%
9 860
 
2.4%
5 738
 
2.1%
Other values (5) 646
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28408
80.0%
Dash Punctuation 7102
 
20.0%
Other Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8000
28.2%
2 7587
26.7%
1 5198
18.3%
3 1529
 
5.4%
7 1432
 
5.0%
8 1336
 
4.7%
4 1086
 
3.8%
9 860
 
3.0%
5 738
 
2.6%
6 642
 
2.3%
Other Letter
ValueCountFrequency (%)
증 1
50.0%
설 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7102
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35512
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8000
22.5%
2 7587
21.4%
- 7102
20.0%
1 5198
14.6%
3 1529
 
4.3%
7 1432
 
4.0%
8 1336
 
3.8%
4 1086
 
3.1%
9 860
 
2.4%
5 738
 
2.1%
Other values (3) 644
 
1.8%
Hangul
ValueCountFrequency (%)
증 1
50.0%
설 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35512
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8000
22.5%
2 7587
21.4%
- 7102
20.0%
1 5198
14.6%
3 1529
 
4.3%
7 1432
 
4.0%
8 1336
 
3.8%
4 1086
 
3.1%
9 860
 
2.4%
5 738
 
2.1%
Other values (3) 644
 
1.8%
Hangul
ValueCountFrequency (%)
증 1
50.0%
설 1
50.0%

사업개시일
Text

MISSING 

Distinct592
Distinct (%)34.3%
Missing1825
Missing (%)51.4%
Memory size27.9 KiB
2024-04-30T07:29:42.766472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length10
Mean length10.046377
Min length10

Characters and Unicode

Total characters17330
Distinct characters20
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)14.6%

Sample

1st row2008-08-28
2nd row2007-12-04
3rd row2008-05-19
4th row2009-08-16
5th row2008-05-19
ValueCountFrequency (%)
2021-01-06 32
 
1.8%
2020-09-04 25
 
1.4%
2018-12-11 24
 
1.4%
2014-11-24 20
 
1.2%
2020-03-31 19
 
1.1%
2020-01-07 17
 
1.0%
2023-09-26 16
 
0.9%
2020-11-04 13
 
0.8%
2012-07-27 13
 
0.8%
2018-06-15 13
 
0.8%
Other values (582) 1538
88.9%
2024-04-30T07:29:43.164765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4132
23.8%
2 3724
21.5%
- 3437
19.8%
1 2782
16.1%
3 629
 
3.6%
8 504
 
2.9%
9 463
 
2.7%
6 418
 
2.4%
4 414
 
2.4%
7 410
 
2.4%
Other values (10) 417
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13840
79.9%
Dash Punctuation 3437
 
19.8%
Other Punctuation 26
 
0.2%
Other Letter 12
 
0.1%
Control 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4132
29.9%
2 3724
26.9%
1 2782
20.1%
3 629
 
4.5%
8 504
 
3.6%
9 463
 
3.3%
6 418
 
3.0%
4 414
 
3.0%
7 410
 
3.0%
5 364
 
2.6%
Other Letter
ValueCountFrequency (%)
한 3
25.0%
전 3
25.0%
체 3
25.0%
결 3
25.0%
Other Punctuation
ValueCountFrequency (%)
. 23
88.5%
: 3
 
11.5%
Dash Punctuation
ValueCountFrequency (%)
- 3437
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17318
99.9%
Hangul 12
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4132
23.9%
2 3724
21.5%
- 3437
19.8%
1 2782
16.1%
3 629
 
3.6%
8 504
 
2.9%
9 463
 
2.7%
6 418
 
2.4%
4 414
 
2.4%
7 410
 
2.4%
Other values (6) 405
 
2.3%
Hangul
ValueCountFrequency (%)
한 3
25.0%
전 3
25.0%
체 3
25.0%
결 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17318
99.9%
Hangul 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4132
23.9%
2 3724
21.5%
- 3437
19.8%
1 2782
16.1%
3 629
 
3.6%
8 504
 
2.9%
9 463
 
2.7%
6 418
 
2.4%
4 414
 
2.4%
7 410
 
2.4%
Other values (6) 405
 
2.3%
Hangul
ValueCountFrequency (%)
한 3
25.0%
전 3
25.0%
체 3
25.0%
결 3
25.0%

Interactions

2024-04-30T07:29:39.769365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:29:39.549001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:29:39.855583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:29:39.685510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:29:43.255451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번설비용량(KW)
순번1.0000.380
설비용량(KW)0.3801.000
2024-04-30T07:29:43.323290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번설비용량(KW)
순번1.0000.144
설비용량(KW)0.1441.000

Missing values

2024-04-30T07:29:39.964746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:29:40.058551image/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

순번발전소명설치장소소재지설비용량(KW)허가일자사업개시일
01다우태양광㈜삼계면 오지리 511851.252007-09-102008-08-28
12선진태양광발전소삼계면 세심리 608-1, 외1건29.162007-10-292007-12-04
23선진2호태양광발전소삼계면 세심리608-329.162008-02-272008-05-19
34㈜서해에너지(오수태양광)오수면 금암리 산34, 839, 840993.62008-03-072009-08-16
45승선태양광발전소삼계면 세심리 605외1건29.42008-03-312008-05-19
56(유)관촌에너지태양광관촌면 신전리 산223-1676.22008-05-072009-10-01
67㈜케이에스컴퍼니관촌면 슬치리 92-1, 92-3, 92-5989.22008-05-152009-08-26
78가정1호태양광삼계면 세심리 679, 680, 682-129.982008-05-232008-07-02
89가정2호태양광삼계면 세심리 682-1, 683-128.982008-07-072008-09-30
910박사골정보화마을태양광발전소삼계면 봉현리27614.72008-09-052008-09-29
순번발전소명설치장소소재지설비용량(KW)허가일자사업개시일
35403541둔덕24호태양광발전소오수면 둔덕리 753-199.42024-04-15<NA>
35413542둔덕25호태양광발전소오수면 둔덕리 753-199.42024-04-15<NA>
35423543둔덕26호태양광발전소오수면 둔덕리 753-199.42024-04-15<NA>
35433544둔덕27호태양광발전소오수면 둔덕리 753-199.42024-04-15<NA>
35443545둔덕28호태양광발전소오수면 둔덕리 753-199.42024-04-15<NA>
35453546성문안발전소삼계면 학정리 82-299.682024-04-15<NA>
35463547병석태양광발전소성수면 봉강리 1050-651.02024-04-16<NA>
35473548계월태양광발전소성수면 봉강리 1050-699.752024-04-16<NA>
35483549봉강태양광발전소성수면 봉강리 25295.252024-04-16<NA>
35493550둔덕23호태양광발전소오수면 둔덕리 753-199.42024-04-16<NA>