Overview

Dataset statistics

Number of variables9
Number of observations334
Missing cells151
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.3 KiB
Average record size in memory74.4 B

Variable types

Text3
Categorical3
Numeric2
DateTime1

Dataset

Description경상북도 포항시 태양광 발전소 현황에 관한 데이터로 발전소명, 설비용량, 발전소주소, 최초허가일, 사업개시일 등의 정보를 제공합니다.
Author경상북도 포항시
URLhttps://www.data.go.kr/data/15033889/fileData.do

Alerts

데이터기준일 has constant value ""Constant
설비용량(kW) is highly overall correlated with 부지면적(m2)High correlation
부지면적(m2) is highly overall correlated with 설비용량(kW)High correlation
구분 is highly overall correlated with 설치지 지목High correlation
설치지 지목 is highly overall correlated with 구분High correlation
설치지 지목 is highly imbalanced (57.0%)Imbalance
부지면적(m2) has 20 (6.0%) missing valuesMissing
사업개시일 has 131 (39.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 04:47:59.127915
Analysis finished2023-12-12 04:48:00.775263
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호(시설명)
Text

Distinct332
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T13:48:01.170643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19.5
Mean length8.257485
Min length2

Characters and Unicode

Total characters2758
Distinct characters274
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

Unique330 ?
Unique (%)98.8%

Sample

1st row와이케이2호
2nd row와이케이3호
3rd row나라
4th row구룡
5th row채영
ValueCountFrequency (%)
태양광발전소 102
 
20.9%
주식회사 15
 
3.1%
발전소 11
 
2.2%
수상태양광 6
 
1.2%
상옥 4
 
0.8%
희망빛 3
 
0.6%
흥곡 2
 
0.4%
태양광 2
 
0.4%
이인리 2
 
0.4%
1호 2
 
0.4%
Other values (338) 340
69.5%
2023-12-12T13:48:01.842290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 213
 
7.7%
전 213
 
7.7%
발 209
 
7.6%
태 198
 
7.2%
광 196
 
7.1%
양 190
 
6.9%
176
 
6.4%
호 57
 
2.1%
에 42
 
1.5%
라 41
 
1.5%
Other values (264) 1223
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2436
88.3%
Space Separator 176
 
6.4%
Decimal Number 79
 
2.9%
Uppercase Letter 23
 
0.8%
Other Symbol 17
 
0.6%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%
Lowercase Letter 8
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 213
 
8.7%
전 213
 
8.7%
발 209
 
8.6%
태 198
 
8.1%
광 196
 
8.0%
양 190
 
7.8%
호 57
 
2.3%
에 42
 
1.7%
라 41
 
1.7%
이 40
 
1.6%
Other values (232) 1037
42.6%
Uppercase Letter
ValueCountFrequency (%)
S 5
21.7%
B 3
13.0%
H 3
13.0%
J 2
 
8.7%
G 2
 
8.7%
K 2
 
8.7%
M 1
 
4.3%
I 1
 
4.3%
E 1
 
4.3%
N 1
 
4.3%
Other values (2) 2
 
8.7%
Decimal Number
ValueCountFrequency (%)
1 29
36.7%
2 28
35.4%
3 11
 
13.9%
4 4
 
5.1%
7 2
 
2.5%
0 2
 
2.5%
8 1
 
1.3%
6 1
 
1.3%
5 1
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
r 2
25.0%
a 2
25.0%
k 1
12.5%
p 1
12.5%
l 1
12.5%
o 1
12.5%
Space Separator
ValueCountFrequency (%)
176
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2453
88.9%
Common 274
 
9.9%
Latin 31
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 213
 
8.7%
전 213
 
8.7%
발 209
 
8.5%
태 198
 
8.1%
광 196
 
8.0%
양 190
 
7.7%
호 57
 
2.3%
에 42
 
1.7%
라 41
 
1.7%
이 40
 
1.6%
Other values (233) 1054
43.0%
Latin
ValueCountFrequency (%)
S 5
16.1%
B 3
 
9.7%
H 3
 
9.7%
J 2
 
6.5%
G 2
 
6.5%
K 2
 
6.5%
r 2
 
6.5%
a 2
 
6.5%
M 1
 
3.2%
k 1
 
3.2%
Other values (8) 8
25.8%
Common
ValueCountFrequency (%)
176
64.2%
1 29
 
10.6%
2 28
 
10.2%
3 11
 
4.0%
( 9
 
3.3%
) 9
 
3.3%
4 4
 
1.5%
7 2
 
0.7%
0 2
 
0.7%
8 1
 
0.4%
Other values (3) 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2436
88.3%
ASCII 305
 
11.1%
None 17
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 213
 
8.7%
전 213
 
8.7%
발 209
 
8.6%
태 198
 
8.1%
광 196
 
8.0%
양 190
 
7.8%
호 57
 
2.3%
에 42
 
1.7%
라 41
 
1.7%
이 40
 
1.6%
Other values (232) 1037
42.6%
ASCII
ValueCountFrequency (%)
176
57.7%
1 29
 
9.5%
2 28
 
9.2%
3 11
 
3.6%
( 9
 
3.0%
) 9
 
3.0%
S 5
 
1.6%
4 4
 
1.3%
B 3
 
1.0%
H 3
 
1.0%
Other values (21) 28
 
9.2%
None
ValueCountFrequency (%)
㈜ 17
100.0%

시설 지번주소
Text

Distinct285
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T13:48:02.170127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length29.311377
Min length19

Characters and Unicode

Total characters9790
Distinct characters146
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

Unique255 ?
Unique (%)76.3%

Sample

1st row경상북도 포항시 남구 괴동동 590-1(건물 위)
2nd row경상북도 포항시 남구 괴동동 911-6(건물 위)
3rd row경상북도 포항시 남구 구룡포읍 구룡포리 318-2
4th row경상북도 포항시 남구 구룡포읍 땅끝마을길 81(건물 위)
5th row경상북도 포항시 남구 구룡포읍 병포리 104-4
ValueCountFrequency (%)
포항시 356
 
15.3%
경상북도 334
 
14.3%
북구 227
 
9.7%
남구 144
 
6.2%
산 92
 
3.9%
신광면 52
 
2.2%
위 50
 
2.1%
청하면 50
 
2.1%
장기면 28
 
1.2%
호미곶면 28
 
1.2%
Other values (499) 969
41.6%
2023-12-12T13:48:02.687584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1999
20.4%
북 575
 
5.9%
구 392
 
4.0%
1 376
 
3.8%
포 368
 
3.8%
상 364
 
3.7%
항 356
 
3.6%
시 356
 
3.6%
도 337
 
3.4%
경 334
 
3.4%
Other values (136) 4333
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5555
56.7%
Space Separator 1999
 
20.4%
Decimal Number 1648
 
16.8%
Dash Punctuation 284
 
2.9%
Other Punctuation 133
 
1.4%
Open Punctuation 82
 
0.8%
Close Punctuation 82
 
0.8%
Uppercase Letter 6
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 575
 
10.4%
구 392
 
7.1%
포 368
 
6.6%
상 364
 
6.6%
항 356
 
6.4%
시 356
 
6.4%
도 337
 
6.1%
경 334
 
6.0%
리 291
 
5.2%
면 245
 
4.4%
Other values (116) 1937
34.9%
Decimal Number
ValueCountFrequency (%)
1 376
22.8%
2 191
11.6%
3 163
9.9%
5 162
9.8%
6 151
9.2%
8 144
 
8.7%
4 130
 
7.9%
7 126
 
7.6%
9 105
 
6.4%
0 100
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
L 2
33.3%
A 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 131
98.5%
. 2
 
1.5%
Space Separator
ValueCountFrequency (%)
1999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 284
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5555
56.7%
Common 4229
43.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 575
 
10.4%
구 392
 
7.1%
포 368
 
6.6%
상 364
 
6.6%
항 356
 
6.4%
시 356
 
6.4%
도 337
 
6.1%
경 334
 
6.0%
리 291
 
5.2%
면 245
 
4.4%
Other values (116) 1937
34.9%
Common
ValueCountFrequency (%)
1999
47.3%
1 376
 
8.9%
- 284
 
6.7%
2 191
 
4.5%
3 163
 
3.9%
5 162
 
3.8%
6 151
 
3.6%
8 144
 
3.4%
, 131
 
3.1%
4 130
 
3.1%
Other values (7) 498
 
11.8%
Latin
ValueCountFrequency (%)
B 3
50.0%
L 2
33.3%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5555
56.7%
ASCII 4234
43.2%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1999
47.2%
1 376
 
8.9%
- 284
 
6.7%
2 191
 
4.5%
3 163
 
3.8%
5 162
 
3.8%
6 151
 
3.6%
8 144
 
3.4%
, 131
 
3.1%
4 130
 
3.1%
Other values (9) 503
 
11.9%
Hangul
ValueCountFrequency (%)
북 575
 
10.4%
구 392
 
7.1%
포 368
 
6.6%
상 364
 
6.6%
항 356
 
6.4%
시 356
 
6.4%
도 337
 
6.1%
경 334
 
6.0%
리 291
 
5.2%
면 245
 
4.4%
Other values (116) 1937
34.9%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

구분
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
건물
132 
토지
120 
<NA>
17 
토지 위
 
11
토지위
 
10
Other values (18)
44 

Length

Max length6
Median length2
Mean length2.4101796
Min length1

Unique

Unique9 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
건물 132
39.5%
토지 120
35.9%
<NA> 17
 
5.1%
토지 위 11
 
3.3%
토지위 10
 
3.0%
건물 위 6
 
1.8%
수상 6
 
1.8%
건물위 5
 
1.5%
임야 5
 
1.5%
농지위 3
 
0.9%
Other values (13) 19
 
5.7%

Length

2023-12-12T13:48:02.878567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건물 142
40.0%
토지 132
37.2%
위 20
 
5.6%
na 17
 
4.8%
토지위 10
 
2.8%
건물위 8
 
2.3%
수상 6
 
1.7%
임야 5
 
1.4%
농지 3
 
0.8%
농지위 3
 
0.8%
Other values (8) 9
 
2.5%

설치지 지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct25
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
<NA>
239 
답
 
15
전
 
13
목장용지
 
9
대
 
8
Other values (20)
50 

Length

Max length5
Median length4
Mean length3.3562874
Min length1

Unique

Unique11 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row잡
4th row<NA>
5th row전

Common Values

ValueCountFrequency (%)
<NA> 239
71.6%
답 15
 
4.5%
전 13
 
3.9%
목장용지 9
 
2.7%
대 8
 
2.4%
임 7
 
2.1%
유 6
 
1.8%
공장용지 6
 
1.8%
장 4
 
1.2%
공장 4
 
1.2%
Other values (15) 23
 
6.9%

Length

2023-12-12T13:48:03.049526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 239
71.3%
답 15
 
4.5%
전 14
 
4.2%
목장용지 9
 
2.7%
대 8
 
2.4%
임 7
 
2.1%
공장용지 7
 
2.1%
유 6
 
1.8%
장 4
 
1.2%
공장 4
 
1.2%
Other values (14) 22
 
6.6%

설비용량(kW)
Real number (ℝ)

HIGH CORRELATION 

Distinct201
Distinct (%)60.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean363.02627
Minimum3
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T13:48:03.199227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile18.137
Q195.6625
median99.93
Q3700.6725
95-th percentile997.92
Maximum2000
Range1997
Interquartile range (IQR)605.01

Descriptive statistics

Standard deviation390.99381
Coefficient of variation (CV)1.07704
Kurtosis-0.2890965
Mean363.02627
Median Absolute Deviation (MAD)80.49
Skewness0.97955498
Sum121250.77
Variance152876.16
MonotonicityNot monotonic
2023-12-12T13:48:03.364207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
997.92 21
 
6.3%
99.0 15
 
4.5%
996.48 11
 
3.3%
98.28 9
 
2.7%
99.2 8
 
2.4%
99.9 8
 
2.4%
99.75 6
 
1.8%
9.92 6
 
1.8%
99.36 5
 
1.5%
97.2 5
 
1.5%
Other values (191) 240
71.9%
ValueCountFrequency (%)
3.0 1
 
0.3%
9.855 1
 
0.3%
9.92 6
1.8%
10.0 1
 
0.3%
10.53 1
 
0.3%
14.18 1
 
0.3%
15.0 2
 
0.6%
15.54 1
 
0.3%
16.32 1
 
0.3%
17.28 1
 
0.3%
ValueCountFrequency (%)
2000.0 1
 
0.3%
1143.18 1
 
0.3%
1100.0 1
 
0.3%
1051.05 1
 
0.3%
1000.0 1
 
0.3%
999.81 4
1.2%
999.6 1
 
0.3%
999.305 1
 
0.3%
999.0 2
0.6%
998.58 1
 
0.3%

부지면적(m2)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct264
Distinct (%)84.1%
Missing20
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean4288.259
Minimum5.1
Maximum27769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T13:48:03.563756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.1
5-th percentile107.895
Q1551.15
median1660.5
Q36249.25
95-th percentile14850
Maximum27769
Range27763.9
Interquartile range (IQR)5698.1

Descriptive statistics

Standard deviation5221.4644
Coefficient of variation (CV)1.2176187
Kurtosis1.0956944
Mean4288.259
Median Absolute Deviation (MAD)1437.1
Skewness1.3838079
Sum1346513.3
Variance27263690
MonotonicityNot monotonic
2023-12-12T13:48:03.740996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14850.0 11
 
3.3%
9900.0 6
 
1.8%
6088.0 4
 
1.2%
990.0 4
 
1.2%
16520.0 3
 
0.9%
15000.0 3
 
0.9%
11000.0 3
 
0.9%
550.0 3
 
0.9%
540.0 3
 
0.9%
110.0 3
 
0.9%
Other values (254) 271
81.1%
(Missing) 20
 
6.0%
ValueCountFrequency (%)
5.1 1
0.3%
11.5 1
0.3%
54.4 1
0.3%
61.5 1
0.3%
61.9 1
0.3%
82.0 1
0.3%
84.8 1
0.3%
91.0 1
0.3%
95.6 1
0.3%
96.1 1
0.3%
ValueCountFrequency (%)
27769.0 1
 
0.3%
18290.0 1
 
0.3%
18173.0 1
 
0.3%
18132.0 1
 
0.3%
17242.0 1
 
0.3%
17058.0 1
 
0.3%
16520.0 3
0.9%
15835.0 2
0.6%
15000.0 3
0.9%
14961.0 1
 
0.3%

발전사업허가일
Date

Distinct168
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2005-10-05 00:00:00
Maximum2020-03-26 00:00:00
2023-12-12T13:48:03.886831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:04.039576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업개시일
Text

MISSING 

Distinct140
Distinct (%)69.0%
Missing131
Missing (%)39.2%
Memory size2.7 KiB
2023-12-12T13:48:04.420226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.955665
Min length1

Characters and Unicode

Total characters2021
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)50.7%

Sample

1st row2018-07-25
2nd row2018-09-11
3rd row2018-08-29
4th row2006-06-20
5th row2015-08-17
ValueCountFrequency (%)
2020-10-21 5
 
2.5%
2019-11-27 5
 
2.5%
2019-01-11 5
 
2.5%
2013-12-06 4
 
2.0%
2017-12-21 4
 
2.0%
2018-09-10 4
 
2.0%
2018-07-04 4
 
2.0%
2013-04-09 3
 
1.5%
2018-11-22 3
 
1.5%
2019-04-22 3
 
1.5%
Other values (129) 162
80.2%
2023-12-12T13:48:04.888047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 482
23.8%
- 404
20.0%
2 372
18.4%
1 359
17.8%
9 95
 
4.7%
3 58
 
2.9%
8 58
 
2.9%
7 55
 
2.7%
6 52
 
2.6%
5 49
 
2.4%
Other values (2) 37
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1616
80.0%
Dash Punctuation 404
 
20.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 482
29.8%
2 372
23.0%
1 359
22.2%
9 95
 
5.9%
3 58
 
3.6%
8 58
 
3.6%
7 55
 
3.4%
6 52
 
3.2%
5 49
 
3.0%
4 36
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 404
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2021
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 482
23.8%
- 404
20.0%
2 372
18.4%
1 359
17.8%
9 95
 
4.7%
3 58
 
2.9%
8 58
 
2.9%
7 55
 
2.7%
6 52
 
2.6%
5 49
 
2.4%
Other values (2) 37
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 482
23.8%
- 404
20.0%
2 372
18.4%
1 359
17.8%
9 95
 
4.7%
3 58
 
2.9%
8 58
 
2.9%
7 55
 
2.7%
6 52
 
2.6%
5 49
 
2.4%
Other values (2) 37
 
1.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2021-09-27
334 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-27
2nd row2021-09-27
3rd row2021-09-27
4th row2021-09-27
5th row2021-09-27

Common Values

ValueCountFrequency (%)
2021-09-27 334
100.0%

Length

2023-12-12T13:48:05.042495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:05.148052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-27 334
100.0%

Interactions

2023-12-12T13:47:59.772353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:47:59.561258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:47:59.899688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:47:59.670701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:48:05.221993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분설치지 지목설비용량(kW)부지면적(m2)
구분1.0000.9020.3270.499
설치지 지목0.9021.0000.7490.809
설비용량(kW)0.3270.7491.0000.674
부지면적(m2)0.4990.8090.6741.000
2023-12-12T13:48:05.323725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분설치지 지목
구분1.0000.566
설치지 지목0.5661.000
2023-12-12T13:48:05.421373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설비용량(kW)부지면적(m2)구분설치지 지목
설비용량(kW)1.0000.8840.1420.360
부지면적(m2)0.8841.0000.2230.420
구분0.1420.2231.0000.566
설치지 지목0.3600.4200.5661.000

Missing values

2023-12-12T13:48:00.072021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:48:00.231364image/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.
2023-12-12T13:48:00.699088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

상호(시설명)시설 지번주소구분설치지 지목설비용량(kW)부지면적(m2)발전사업허가일사업개시일데이터기준일
0와이케이2호경상북도 포항시 남구 괴동동 590-1(건물 위)건물<NA>631.123367.02017-10-242018-07-252021-09-27
1와이케이3호경상북도 포항시 남구 괴동동 911-6(건물 위)건물<NA>452.762476.02017-10-242018-09-112021-09-27
2나라경상북도 포항시 남구 구룡포읍 구룡포리 318-2건물잡15.5499.02019-10-18<NA>2021-09-27
3구룡경상북도 포항시 남구 구룡포읍 땅끝마을길 81(건물 위)건물<NA>19.88171.02017-08-142018-08-292021-09-27
4채영경상북도 포항시 남구 구룡포읍 병포리 104-4건물전18.48178.62019-12-19<NA>2021-09-27
5포철산기 태양광발전소경상북도 포항시 남구 구룡포읍 삼정리 99-1<NA><NA>3.0<NA>2005-10-052006-06-202021-09-27
6민수네 태양광발전소경상북도 포항시 남구 구룡포읍 석병리 920-1건물<NA>99.0778.22014-11-042015-08-172021-09-27
7구룡포 태양광발전소경상북도 포항시 남구 구룡포읍 성동리 754,751,760,760-1토지<NA>498.428378.02016-06-272019-04-222021-09-27
8구룡태양광발전소경상북도 포항시 남구 구룡포읍 일출로 308-41(건물 위)건물<NA>45.9263.02017-11-302018-05-242021-09-27
9협동 스포츠랜드 주차장 태양광발전소경상북도 포항시 남구 남구 동촌동 16-3.716-13,716-15,716-16,산33-6건물<NA>468.052618.02018-04-062018-12-262021-09-27
상호(시설명)시설 지번주소구분설치지 지목설비용량(kW)부지면적(m2)발전사업허가일사업개시일데이터기준일
324고종대 태양광발전소경상북도 포항시 북구 신광면 토성리 470건물<NA>9.9282.02017-04-062017-12-212021-09-27
325스마일경상북도 포항시 북구 신광면 토성리 614-3건물답99.9973.62019-09-052020-09-242021-09-27
326태식솔라경상북도 포항시 북구 신광면 호리 727, 626-3(건물 위)건물<NA>81.12396.02017-06-142018-11-152021-09-27
327주식회사 케이피코리아경상북도 포항시 북구 신광면 흥곡리 264-1(건물 위)건물<NA>229.951660.02018-10-30<NA>2021-09-27
328훈성성계태양광발전소경상북도 포항시 북구 신광면 흥곡리 282-1, 282-3,산 25, 산 25-3, 산 25-4토지<NA>997.9211460.02018-10-02<NA>2021-09-27
329흥곡성계태양광발전소경상북도 포항시 북구 신광면 흥곡리 282-1, 산 25, 산 25-2토지<NA>997.9211.52018-10-02<NA>2021-09-27
330흥곡경상북도 포항시 북구 신광면 흥곡리 697, 696(축사 위)건물<NA>198.81344.02017-09-042018-03-172021-09-27
331흥곡 태양광발전소경상북도 포항시 북구 신광면 흥곡리 706-1답<NA>99.01672.02015-03-27<NA>2021-09-27
332양덕정수장 태양광발전소경상북도 포항시 북구 양덕동 산 180-1 외 4필지건물 위<NA>495.68010.02013-10-232013-12-272021-09-27
333영남에너지태양광발전소경상북도 포항시 북구 양덕로 30번길 42-12건물 위<NA>15.095.62014-10-012015-02-262021-09-27