Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells41929
Missing cells (%)23.3%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.5 MiB
Average record size in memory159.0 B

Variable types

Text5
Numeric6
Categorical5
DateTime2

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털&gt;정보공유&gt;자료실)
Author지방자치단체
URLhttps://www.data.go.kr/data/15107742/standard.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
주파수 is highly overall correlated with 설치면적 and 1 other fieldsHigh correlation
설치상세위치구분명 is highly overall correlated with 주파수High correlation
위도 is highly overall correlated with 제공기관코드High correlation
경도 is highly overall correlated with 세부용도High correlation
설비용량 is highly overall correlated with 설치면적High correlation
설치면적 is highly overall correlated with 설비용량 and 1 other fieldsHigh correlation
제공기관코드 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
세부용도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
설치상세위치구분명 is highly imbalanced (72.3%)Imbalance
가동상태구분명 is highly imbalanced (61.4%)Imbalance
공급전압 is highly imbalanced (84.2%)Imbalance
주파수 is highly imbalanced (99.7%)Imbalance
세부용도 is highly imbalanced (55.0%)Imbalance
소재지도로명주소 has 6204 (62.0%) missing valuesMissing
소재지지번주소 has 2327 (23.3%) missing valuesMissing
위도 has 8609 (86.1%) missing valuesMissing
경도 has 8609 (86.1%) missing valuesMissing
허가일자 has 3169 (31.7%) missing valuesMissing
허가기관 has 4199 (42.0%) missing valuesMissing
설치면적 has 8812 (88.1%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:14:43.214421
Analysis finished2024-05-11 10:15:02.136858
Duration18.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct9117
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:15:02.758105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.3044
Min length2

Characters and Unicode

Total characters103044
Distinct characters747
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8483 ?
Unique (%)84.8%

Sample

1st row한성 태양광발전소
2nd row주식회사 부산태양광1호(트렉스타 본사
3rd row옥당태양광발전소
4th row명보4호 태양광발전소
5th row대흥3호 태양광발전소
ValueCountFrequency (%)
태양광발전소 5211
31.2%
발전소 241
 
1.4%
태양광 184
 
1.1%
2호 65
 
0.4%
1호 61
 
0.4%
주식회사 59
 
0.4%
3호 36
 
0.2%
태양광발 32
 
0.2%
㈜강원학교태양광 28
 
0.2%
태양 22
 
0.1%
Other values (9260) 10769
64.5%
2024-05-11T10:15:04.080283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9280
 
9.0%
9250
 
9.0%
9222
 
8.9%
9208
 
8.9%
9193
 
8.9%
9193
 
8.9%
6730
 
6.5%
3374
 
3.3%
1 1680
 
1.6%
2 1489
 
1.4%
Other values (737) 34425
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88886
86.3%
Space Separator 6730
 
6.5%
Decimal Number 5162
 
5.0%
Uppercase Letter 736
 
0.7%
Open Punctuation 452
 
0.4%
Close Punctuation 373
 
0.4%
Lowercase Letter 264
 
0.3%
Dash Punctuation 192
 
0.2%
Other Punctuation 131
 
0.1%
Other Symbol 115
 
0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9280
 
10.4%
9250
 
10.4%
9222
 
10.4%
9208
 
10.4%
9193
 
10.3%
9193
 
10.3%
3374
 
3.8%
860
 
1.0%
773
 
0.9%
689
 
0.8%
Other values (665) 27844
31.3%
Uppercase Letter
ValueCountFrequency (%)
S 125
17.0%
E 69
 
9.4%
J 53
 
7.2%
K 53
 
7.2%
H 47
 
6.4%
N 43
 
5.8%
C 39
 
5.3%
M 38
 
5.2%
G 31
 
4.2%
P 30
 
4.1%
Other values (14) 208
28.3%
Lowercase Letter
ValueCountFrequency (%)
o 91
34.5%
k 27
 
10.2%
p 26
 
9.8%
c 24
 
9.1%
e 23
 
8.7%
n 11
 
4.2%
a 10
 
3.8%
r 10
 
3.8%
l 9
 
3.4%
s 8
 
3.0%
Other values (11) 25
 
9.5%
Decimal Number
ValueCountFrequency (%)
1 1680
32.5%
2 1489
28.8%
3 709
13.7%
4 361
 
7.0%
5 276
 
5.3%
6 190
 
3.7%
7 125
 
2.4%
0 120
 
2.3%
9 113
 
2.2%
8 99
 
1.9%
Other Punctuation
ValueCountFrequency (%)
* 115
87.8%
. 7
 
5.3%
/ 5
 
3.8%
& 3
 
2.3%
, 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 435
96.2%
[ 14
 
3.1%
{ 3
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 370
99.2%
] 2
 
0.5%
} 1
 
0.3%
Space Separator
ValueCountFrequency (%)
6730
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%
Other Symbol
ValueCountFrequency (%)
115
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88998
86.4%
Common 13042
 
12.7%
Latin 1001
 
1.0%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9280
 
10.4%
9250
 
10.4%
9222
 
10.4%
9208
 
10.3%
9193
 
10.3%
9193
 
10.3%
3374
 
3.8%
860
 
1.0%
773
 
0.9%
689
 
0.8%
Other values (663) 27956
31.4%
Latin
ValueCountFrequency (%)
S 125
 
12.5%
o 91
 
9.1%
E 69
 
6.9%
J 53
 
5.3%
K 53
 
5.3%
H 47
 
4.7%
N 43
 
4.3%
C 39
 
3.9%
M 38
 
3.8%
G 31
 
3.1%
Other values (36) 412
41.2%
Common
ValueCountFrequency (%)
6730
51.6%
1 1680
 
12.9%
2 1489
 
11.4%
3 709
 
5.4%
( 435
 
3.3%
) 370
 
2.8%
4 361
 
2.8%
5 276
 
2.1%
- 192
 
1.5%
6 190
 
1.5%
Other values (15) 610
 
4.7%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88849
86.2%
ASCII 14042
 
13.6%
None 115
 
0.1%
Compat Jamo 34
 
< 0.1%
CJK 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9280
 
10.4%
9250
 
10.4%
9222
 
10.4%
9208
 
10.4%
9193
 
10.3%
9193
 
10.3%
3374
 
3.8%
860
 
1.0%
773
 
0.9%
689
 
0.8%
Other values (661) 27807
31.3%
ASCII
ValueCountFrequency (%)
6730
47.9%
1 1680
 
12.0%
2 1489
 
10.6%
3 709
 
5.0%
( 435
 
3.1%
) 370
 
2.6%
4 361
 
2.6%
5 276
 
2.0%
- 192
 
1.4%
6 190
 
1.4%
Other values (60) 1610
 
11.5%
None
ValueCountFrequency (%)
115
100.0%
Compat Jamo
ValueCountFrequency (%)
34
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct3403
Distinct (%)89.6%
Missing6204
Missing (%)62.0%
Memory size156.2 KiB
2024-05-11T10:15:04.897933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length63
Mean length24.637513
Min length11

Characters and Unicode

Total characters93524
Distinct characters540
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3109 ?
Unique (%)81.9%

Sample

1st row충청북도 청주시 청원구 오창읍 두릉1길 63-22
2nd row부산광역시 강서구 녹산산업중로192번길 23(송정동)
3rd row충청남도 서산시 부석면 대두리 501-28, 501-29, 501-34
4th row부산광역시 강서구 과학산단로333번길 32 (지사동)
5th row경상남도 합천군 율곡면 임북1길 45
ValueCountFrequency (%)
경기도 689
 
3.4%
충청남도 648
 
3.2%
충청북도 481
 
2.4%
경상남도 459
 
2.3%
강원도 452
 
2.2%
경상북도 437
 
2.2%
서산시 390
 
1.9%
인제군 257
 
1.3%
경산시 213
 
1.0%
천안시 204
 
1.0%
Other values (5819) 16094
79.2%
2024-05-11T10:15:08.924325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16533
 
17.7%
3752
 
4.0%
1 3338
 
3.6%
2478
 
2.6%
2 2366
 
2.5%
2109
 
2.3%
- 1979
 
2.1%
1970
 
2.1%
1893
 
2.0%
3 1884
 
2.0%
Other values (530) 55222
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55912
59.8%
Decimal Number 16737
 
17.9%
Space Separator 16533
 
17.7%
Dash Punctuation 1979
 
2.1%
Other Punctuation 980
 
1.0%
Open Punctuation 655
 
0.7%
Close Punctuation 654
 
0.7%
Uppercase Letter 59
 
0.1%
Lowercase Letter 10
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3752
 
6.7%
2478
 
4.4%
2109
 
3.8%
1970
 
3.5%
1893
 
3.4%
1812
 
3.2%
1796
 
3.2%
1705
 
3.0%
1543
 
2.8%
1510
 
2.7%
Other values (482) 35344
63.2%
Uppercase Letter
ValueCountFrequency (%)
C 11
18.6%
K 7
11.9%
E 7
11.9%
S 5
8.5%
A 5
8.5%
T 4
 
6.8%
M 3
 
5.1%
B 3
 
5.1%
P 2
 
3.4%
G 2
 
3.4%
Other values (7) 10
16.9%
Decimal Number
ValueCountFrequency (%)
1 3338
19.9%
2 2366
14.1%
3 1884
11.3%
4 1573
9.4%
5 1418
8.5%
6 1358
8.1%
7 1273
 
7.6%
8 1196
 
7.1%
0 1196
 
7.1%
9 1135
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
m 2
20.0%
c 2
20.0%
e 1
10.0%
a 1
10.0%
i 1
10.0%
t 1
10.0%
l 1
10.0%
u 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 976
99.6%
. 3
 
0.3%
· 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 637
97.3%
[ 18
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 636
97.2%
] 18
 
2.8%
Other Symbol
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
16533
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1979
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55914
59.8%
Common 37540
40.1%
Latin 70
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3752
 
6.7%
2478
 
4.4%
2109
 
3.8%
1970
 
3.5%
1893
 
3.4%
1812
 
3.2%
1796
 
3.2%
1705
 
3.0%
1543
 
2.8%
1510
 
2.7%
Other values (483) 35346
63.2%
Latin
ValueCountFrequency (%)
C 11
15.7%
K 7
 
10.0%
E 7
 
10.0%
S 5
 
7.1%
A 5
 
7.1%
T 4
 
5.7%
M 3
 
4.3%
B 3
 
4.3%
P 2
 
2.9%
G 2
 
2.9%
Other values (16) 21
30.0%
Common
ValueCountFrequency (%)
16533
44.0%
1 3338
 
8.9%
2 2366
 
6.3%
- 1979
 
5.3%
3 1884
 
5.0%
4 1573
 
4.2%
5 1418
 
3.8%
6 1358
 
3.6%
7 1273
 
3.4%
8 1196
 
3.2%
Other values (11) 4622
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55912
59.8%
ASCII 37607
40.2%
None 3
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16533
44.0%
1 3338
 
8.9%
2 2366
 
6.3%
- 1979
 
5.3%
3 1884
 
5.0%
4 1573
 
4.2%
5 1418
 
3.8%
6 1358
 
3.6%
7 1273
 
3.4%
8 1196
 
3.2%
Other values (34) 4689
 
12.5%
Hangul
ValueCountFrequency (%)
3752
 
6.7%
2478
 
4.4%
2109
 
3.8%
1970
 
3.5%
1893
 
3.4%
1812
 
3.2%
1796
 
3.2%
1705
 
3.0%
1543
 
2.8%
1510
 
2.7%
Other values (482) 35344
63.2%
None
ValueCountFrequency (%)
2
66.7%
· 1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

소재지지번주소
Text

MISSING 

Distinct6111
Distinct (%)79.6%
Missing2327
Missing (%)23.3%
Memory size156.2 KiB
2024-05-11T10:15:10.029843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length205
Median length82
Mean length24.404666
Min length8

Characters and Unicode

Total characters187257
Distinct characters470
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5523 ?
Unique (%)72.0%

Sample

1st row경기도 안성시 대덕면 무능리 309,314,315
2nd row전북특별자치도 완주군 소양면 대흥리 887(답)(토지위)
3rd row전북특별자치도 완주군 용진읍 간중리 877번지 건물상부
4th row경상남도 합천군 율곡면 임북리 555번지 8호
5th row충청북도 청주시 흥덕구 옥산면 호죽리 산 10번지 1호
ValueCountFrequency (%)
강원도 1323
 
3.2%
경상북도 931
 
2.3%
전라북도 929
 
2.3%
경기도 910
 
2.2%
전북특별자치도 782
 
1.9%
완주군 764
 
1.9%
충청북도 682
 
1.7%
전라남도 658
 
1.6%
652
 
1.6%
충청남도 529
 
1.3%
Other values (8622) 32933
80.1%
2024-05-11T10:15:12.308949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33567
 
17.9%
8093
 
4.3%
1 6893
 
3.7%
6525
 
3.5%
5688
 
3.0%
- 4883
 
2.6%
2 4621
 
2.5%
4524
 
2.4%
3 3628
 
1.9%
3618
 
1.9%
Other values (460) 105217
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109016
58.2%
Space Separator 33567
 
17.9%
Decimal Number 33539
 
17.9%
Dash Punctuation 4883
 
2.6%
Other Punctuation 2697
 
1.4%
Close Punctuation 1726
 
0.9%
Open Punctuation 1726
 
0.9%
Uppercase Letter 61
 
< 0.1%
Other Symbol 26
 
< 0.1%
Lowercase Letter 11
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8093
 
7.4%
6525
 
6.0%
5688
 
5.2%
4524
 
4.1%
3618
 
3.3%
3317
 
3.0%
2873
 
2.6%
2775
 
2.5%
2646
 
2.4%
2477
 
2.3%
Other values (413) 66480
61.0%
Uppercase Letter
ValueCountFrequency (%)
A 15
24.6%
C 11
18.0%
B 8
13.1%
K 6
 
9.8%
W 5
 
8.2%
E 3
 
4.9%
T 2
 
3.3%
S 2
 
3.3%
I 2
 
3.3%
P 2
 
3.3%
Other values (5) 5
 
8.2%
Decimal Number
ValueCountFrequency (%)
1 6893
20.6%
2 4621
13.8%
3 3628
10.8%
5 3230
9.6%
4 3148
9.4%
6 2636
 
7.9%
8 2466
 
7.4%
7 2445
 
7.3%
9 2243
 
6.7%
0 2229
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
m 2
18.2%
k 2
18.2%
c 1
9.1%
e 1
9.1%
a 1
9.1%
l 1
9.1%
t 1
9.1%
i 1
9.1%
u 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 2680
99.4%
. 16
 
0.6%
/ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 1672
96.9%
] 54
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 1672
96.9%
[ 54
 
3.1%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
~ 2
50.0%
Space Separator
ValueCountFrequency (%)
33567
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4883
100.0%
Other Symbol
ValueCountFrequency (%)
26
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109006
58.2%
Common 78168
41.7%
Latin 73
 
< 0.1%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8093
 
7.4%
6525
 
6.0%
5688
 
5.2%
4524
 
4.2%
3618
 
3.3%
3317
 
3.0%
2873
 
2.6%
2775
 
2.5%
2646
 
2.4%
2477
 
2.3%
Other values (409) 66470
61.0%
Latin
ValueCountFrequency (%)
A 15
20.5%
C 11
15.1%
B 8
11.0%
K 6
 
8.2%
W 5
 
6.8%
E 3
 
4.1%
T 2
 
2.7%
S 2
 
2.7%
m 2
 
2.7%
k 2
 
2.7%
Other values (15) 17
23.3%
Common
ValueCountFrequency (%)
33567
42.9%
1 6893
 
8.8%
- 4883
 
6.2%
2 4621
 
5.9%
3 3628
 
4.6%
5 3230
 
4.1%
4 3148
 
4.0%
, 2680
 
3.4%
6 2636
 
3.4%
8 2466
 
3.2%
Other values (12) 10416
 
13.3%
Han
ValueCountFrequency (%)
4
40.0%
4
40.0%
1
 
10.0%
1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109006
58.2%
ASCII 78214
41.8%
CJK Compat 26
 
< 0.1%
CJK 10
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33567
42.9%
1 6893
 
8.8%
- 4883
 
6.2%
2 4621
 
5.9%
3 3628
 
4.6%
5 3230
 
4.1%
4 3148
 
4.0%
, 2680
 
3.4%
6 2636
 
3.4%
8 2466
 
3.2%
Other values (35) 10462
 
13.4%
Hangul
ValueCountFrequency (%)
8093
 
7.4%
6525
 
6.0%
5688
 
5.2%
4524
 
4.2%
3618
 
3.3%
3317
 
3.0%
2873
 
2.6%
2775
 
2.5%
2646
 
2.4%
2477
 
2.3%
Other values (409) 66470
61.0%
CJK Compat
ValueCountFrequency (%)
26
100.0%
CJK
ValueCountFrequency (%)
4
40.0%
4
40.0%
1
 
10.0%
1
 
10.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1234
Distinct (%)88.7%
Missing8609
Missing (%)86.1%
Infinite0
Infinite (%)0.0%
Mean36.776659
Minimum34.866278
Maximum38.311596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:15:13.340172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.866278
5-th percentile35.093602
Q136.292681
median37.160814
Q337.438328
95-th percentile37.99421
Maximum38.311596
Range3.4453175
Interquartile range (IQR)1.1456468

Descriptive statistics

Standard deviation0.93852394
Coefficient of variation (CV)0.025519554
Kurtosis-0.84336411
Mean36.776659
Median Absolute Deviation (MAD)0.72774526
Skewness-0.49602995
Sum51156.332
Variance0.88082719
MonotonicityNot monotonic
2024-05-11T10:15:13.959510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.22129654 9
 
0.1%
37.2178561 8
 
0.1%
37.31945268 5
 
0.1%
38.047818 5
 
0.1%
36.41925461 4
 
< 0.1%
37.35529654 4
 
< 0.1%
37.16081374 4
 
< 0.1%
37.98635 4
 
< 0.1%
37.28973476 4
 
< 0.1%
36.43969932 3
 
< 0.1%
Other values (1224) 1341
 
13.4%
(Missing) 8609
86.1%
ValueCountFrequency (%)
34.86627846 1
< 0.1%
34.86824956 1
< 0.1%
34.87405348 1
< 0.1%
34.87429276 1
< 0.1%
34.88871641 1
< 0.1%
34.90861635 1
< 0.1%
34.91766575 1
< 0.1%
34.91961994 1
< 0.1%
34.92060559 1
< 0.1%
34.92101756 1
< 0.1%
ValueCountFrequency (%)
38.311596 1
< 0.1%
38.281012 2
< 0.1%
38.241223 1
< 0.1%
38.225867 1
< 0.1%
38.215928 1
< 0.1%
38.214371 1
< 0.1%
38.209311 1
< 0.1%
38.209282 1
< 0.1%
38.206978 1
< 0.1%
38.189886 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1237
Distinct (%)88.9%
Missing8609
Missing (%)86.1%
Infinite0
Infinite (%)0.0%
Mean127.84818
Minimum126.57316
Maximum129.26999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:15:14.667912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.57316
5-th percentile126.9488
Q1127.60386
median127.7653
Q3127.98537
95-th percentile128.9764
Maximum129.26999
Range2.696828
Interquartile range (IQR)0.38151505

Descriptive statistics

Standard deviation0.54910044
Coefficient of variation (CV)0.0042949412
Kurtosis0.33976375
Mean127.84818
Median Absolute Deviation (MAD)0.17995307
Skewness0.60395617
Sum177836.82
Variance0.30151129
MonotonicityNot monotonic
2024-05-11T10:15:15.339720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.0989254 9
 
0.1%
127.7718335 8
 
0.1%
127.874619 5
 
0.1%
127.620875 5
 
0.1%
127.8316158 4
 
< 0.1%
127.897696 4
 
< 0.1%
127.6725079 4
 
< 0.1%
127.8885005 4
 
< 0.1%
127.8238527 4
 
< 0.1%
127.692372 3
 
< 0.1%
Other values (1227) 1341
 
13.4%
(Missing) 8609
86.1%
ValueCountFrequency (%)
126.5731623 1
< 0.1%
126.5754495 1
< 0.1%
126.5775382 1
< 0.1%
126.5826558 1
< 0.1%
126.5903708 1
< 0.1%
126.5918804 1
< 0.1%
126.5973411 1
< 0.1%
126.6301821 1
< 0.1%
126.7115803 1
< 0.1%
126.7214758 1
< 0.1%
ValueCountFrequency (%)
129.2699903 1
 
< 0.1%
129.2632819 1
 
< 0.1%
129.2605443 1
 
< 0.1%
129.2595635 1
 
< 0.1%
129.2580962 1
 
< 0.1%
129.2576334 3
< 0.1%
129.2571183 1
 
< 0.1%
129.2484379515 1
 
< 0.1%
129.2482968 1
 
< 0.1%
129.2207147 1
 
< 0.1%

설치상세위치구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8623 
옥상
 
704
옥외
 
519
기타
 
139
옥상+옥외
 
10
Other values (2)
 
5

Length

Max length5
Median length4
Mean length3.7283
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8623
86.2%
옥상 704
 
7.0%
옥외 519
 
5.2%
기타 139
 
1.4%
옥상+옥외 10
 
0.1%
주차장 4
 
< 0.1%
건물일체형 1
 
< 0.1%

Length

2024-05-11T10:15:15.980831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:15:16.359544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8623
86.2%
옥상 704
 
7.0%
옥외 519
 
5.2%
기타 139
 
1.4%
옥상+옥외 10
 
0.1%
주차장 4
 
< 0.1%
건물일체형 1
 
< 0.1%

가동상태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상가동
8888 
가동중단
 
668
폐기
 
444

Length

Max length4
Median length4
Mean length3.9112
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상가동
2nd row정상가동
3rd row정상가동
4th row가동중단
5th row정상가동

Common Values

ValueCountFrequency (%)
정상가동 8888
88.9%
가동중단 668
 
6.7%
폐기 444
 
4.4%

Length

2024-05-11T10:15:16.955457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:15:17.484711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상가동 8888
88.9%
가동중단 668
 
6.7%
폐기 444
 
4.4%

설비용량
Real number (ℝ)

HIGH CORRELATION 

Distinct2371
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.11736
Minimum0
Maximum3000
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:15:18.021677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.44
Q182.4625
median99
Q399.9
95-th percentile904.405
Maximum3000
Range3000
Interquartile range (IQR)17.4375

Descriptive statistics

Standard deviation282.53559
Coefficient of variation (CV)1.6320465
Kurtosis28.258504
Mean173.11736
Median Absolute Deviation (MAD)1.8
Skewness4.5716103
Sum1731173.6
Variance79826.357
MonotonicityNot monotonic
2024-05-11T10:15:18.636427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 898
 
9.0%
99.96 277
 
2.8%
99.9 266
 
2.7%
99.84 248
 
2.5%
99.36 244
 
2.4%
99.6 221
 
2.2%
97.92 193
 
1.9%
99.2 188
 
1.9%
99.45 156
 
1.6%
98.28 148
 
1.5%
Other values (2361) 7161
71.6%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
0.32 1
 
< 0.1%
3.0 2
 
< 0.1%
3.08 1
 
< 0.1%
3.5 1
 
< 0.1%
3.96 1
 
< 0.1%
4.0 1
 
< 0.1%
4.04 2
 
< 0.1%
5.0 8
0.1%
5.3 1
 
< 0.1%
ValueCountFrequency (%)
3000.0 5
0.1%
2999.1 1
 
< 0.1%
2997.68 1
 
< 0.1%
2996.91 2
 
< 0.1%
2995.2 1
 
< 0.1%
2992.0 1
 
< 0.1%
2980.8 1
 
< 0.1%
2706.0 1
 
< 0.1%
2673.0 1
 
< 0.1%
2600.0 1
 
< 0.1%

공급전압
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
380
8853 
22900
 
801
220
 
135
220380
 
104
220+380
 
53
Other values (16)
 
54

Length

Max length8
Median length3
Mean length3.2277
Min length1

Unique

Unique10 ?
Unique (%)0.1%

Sample

1st row380
2nd row380
3rd row22900
4th row380
5th row220380

Common Values

ValueCountFrequency (%)
380 8853
88.5%
22900 801
 
8.0%
220 135
 
1.4%
220380 104
 
1.0%
220+380 53
 
0.5%
380+220 26
 
0.3%
154000 8
 
0.1%
360 3
 
< 0.1%
12900 3
 
< 0.1%
229000 2
 
< 0.1%
Other values (11) 12
 
0.1%

Length

2024-05-11T10:15:19.396818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
380 8853
88.5%
22900 801
 
8.0%
220 135
 
1.4%
220380 104
 
1.0%
220+380 53
 
0.5%
380+220 26
 
0.3%
154000 8
 
0.1%
360 3
 
< 0.1%
12900 3
 
< 0.1%
22.9 2
 
< 0.1%
Other values (11) 12
 
0.1%

주파수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
60
9996 
30
 
2
220
 
1
62
 
1

Length

Max length3
Median length2
Mean length2.0001
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row60
2nd row60
3rd row60
4th row60
5th row60

Common Values

ValueCountFrequency (%)
60 9996
> 99.9%
30 2
 
< 0.1%
220 1
 
< 0.1%
62 1
 
< 0.1%

Length

2024-05-11T10:15:19.798912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:15:20.231365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 9996
> 99.9%
30 2
 
< 0.1%
220 1
 
< 0.1%
62 1
 
< 0.1%

설치연도
Real number (ℝ)

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.388
Minimum1900
Maximum2029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:15:20.741724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile2012
Q12017
median2020
Q32021
95-th percentile2023
Maximum2029
Range129
Interquartile range (IQR)4

Descriptive statistics

Standard deviation13.08441
Coefficient of variation (CV)0.0064858171
Kurtosis70.948144
Mean2017.388
Median Absolute Deviation (MAD)2
Skewness-8.2510001
Sum20173880
Variance171.20178
MonotonicityNot monotonic
2024-05-11T10:15:21.249536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2021 1619
16.2%
2020 1547
15.5%
2022 1159
11.6%
2019 1122
11.2%
2018 1075
10.8%
2017 820
8.2%
2023 661
6.6%
2014 482
 
4.8%
2015 424
 
4.2%
2016 407
 
4.1%
Other values (18) 684
6.8%
ValueCountFrequency (%)
1900 114
1.1%
1998 1
 
< 0.1%
2000 99
1.0%
2002 1
 
< 0.1%
2003 1
 
< 0.1%
2005 1
 
< 0.1%
2006 10
 
0.1%
2007 11
 
0.1%
2008 53
0.5%
2009 51
0.5%
ValueCountFrequency (%)
2029 1
 
< 0.1%
2026 1
 
< 0.1%
2025 4
 
< 0.1%
2024 11
 
0.1%
2023 661
6.6%
2022 1159
11.6%
2021 1619
16.2%
2020 1547
15.5%
2019 1122
11.2%
2018 1075
10.8%

세부용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6533 
발전사업용
2844 
전기사업
 
380
사업용
 
120
태양광
 
90
Other values (2)
 
33

Length

Max length7
Median length4
Mean length4.2669
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row전기사업
2nd row발전사업용
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6533
65.3%
발전사업용 2844
28.4%
전기사업 380
 
3.8%
사업용 120
 
1.2%
태양광 90
 
0.9%
전기사업용 32
 
0.3%
가스엔진발전기 1
 
< 0.1%

Length

2024-05-11T10:15:21.800056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:15:22.255568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6533
65.3%
발전사업용 2844
28.4%
전기사업 380
 
3.8%
사업용 120
 
1.2%
태양광 90
 
0.9%
전기사업용 32
 
0.3%
가스엔진발전기 1
 
< 0.1%

허가일자
Date

MISSING 

Distinct2228
Distinct (%)32.6%
Missing3169
Missing (%)31.7%
Memory size156.2 KiB
Minimum2002-01-10 00:00:00
Maximum2024-01-16 00:00:00
2024-05-11T10:15:22.734541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:15:23.233579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

허가기관
Text

MISSING 

Distinct52
Distinct (%)0.9%
Missing4199
Missing (%)42.0%
Memory size156.2 KiB
2024-05-11T10:15:23.960715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.1911739
Min length3

Characters and Unicode

Total characters47517
Distinct characters64
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row부산광역시청
2nd row충청남도 서산시청
3rd row경기도 안성시청
4th row부산광역시청
5th row경상남도 합천군청
ValueCountFrequency (%)
강원도 998
 
9.2%
경기도 956
 
8.8%
경상북도 665
 
6.1%
경상남도 662
 
6.1%
화성시청 442
 
4.1%
강원도청 405
 
3.7%
충청남도 390
 
3.6%
서산시청 390
 
3.6%
강원특별자치도 375
 
3.5%
전라북도 361
 
3.3%
Other values (46) 5171
47.8%
2024-05-11T10:15:25.166701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5617
 
11.8%
5014
 
10.6%
4837
 
10.2%
2911
 
6.1%
2563
 
5.4%
2364
 
5.0%
2107
 
4.4%
1914
 
4.0%
1562
 
3.3%
1401
 
2.9%
Other values (54) 17227
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42503
89.4%
Space Separator 5014
 
10.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5617
 
13.2%
4837
 
11.4%
2911
 
6.8%
2563
 
6.0%
2364
 
5.6%
2107
 
5.0%
1914
 
4.5%
1562
 
3.7%
1401
 
3.3%
1327
 
3.1%
Other values (53) 15900
37.4%
Space Separator
ValueCountFrequency (%)
5014
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42503
89.4%
Common 5014
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5617
 
13.2%
4837
 
11.4%
2911
 
6.8%
2563
 
6.0%
2364
 
5.6%
2107
 
5.0%
1914
 
4.5%
1562
 
3.7%
1401
 
3.3%
1327
 
3.1%
Other values (53) 15900
37.4%
Common
ValueCountFrequency (%)
5014
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42503
89.4%
ASCII 5014
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5617
 
13.2%
4837
 
11.4%
2911
 
6.8%
2563
 
6.0%
2364
 
5.6%
2107
 
5.0%
1914
 
4.5%
1562
 
3.7%
1401
 
3.3%
1327
 
3.1%
Other values (53) 15900
37.4%
ASCII
ValueCountFrequency (%)
5014
100.0%

설치면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct938
Distinct (%)79.0%
Missing8812
Missing (%)88.1%
Infinite0
Infinite (%)0.0%
Mean1308.2633
Minimum8.78
Maximum44297
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:15:25.813494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.78
5-th percentile101.308
Q1407.6
median596
Q31281.5
95-th percentile5003.9
Maximum44297
Range44288.22
Interquartile range (IQR)873.9

Descriptive statistics

Standard deviation2563.7611
Coefficient of variation (CV)1.9596675
Kurtosis94.777454
Mean1308.2633
Median Absolute Deviation (MAD)395.5
Skewness7.818429
Sum1554216.8
Variance6572870.9
MonotonicityNot monotonic
2024-05-11T10:15:26.439268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500.0 12
 
0.1%
1650.0 8
 
0.1%
480.0 6
 
0.1%
482.0 6
 
0.1%
598.0 5
 
0.1%
1200.0 5
 
0.1%
453.44 5
 
0.1%
991.5 5
 
0.1%
574.0 5
 
0.1%
990.0 4
 
< 0.1%
Other values (928) 1127
 
11.3%
(Missing) 8812
88.1%
ValueCountFrequency (%)
8.78 1
< 0.1%
37.0 1
< 0.1%
42.0 1
< 0.1%
48.0 2
< 0.1%
48.17 1
< 0.1%
48.172 1
< 0.1%
50.0 1
< 0.1%
51.36 1
< 0.1%
52.93 1
< 0.1%
54.14 1
< 0.1%
ValueCountFrequency (%)
44297.0 1
< 0.1%
29600.0 1
< 0.1%
29157.0 1
< 0.1%
14786.0 1
< 0.1%
14688.0 1
< 0.1%
14092.0 1
< 0.1%
13855.0 1
< 0.1%
13817.0 1
< 0.1%
13498.0 1
< 0.1%
12932.48 1
< 0.1%
Distinct54
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-11-08 00:00:00
Maximum2024-02-27 00:00:00
2024-05-11T10:15:27.043567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:15:27.639666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4860478.1
Minimum3620000
Maximum6420000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:15:28.049511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3620000
5-th percentile4080000
Q14420000
median4731000
Q35230000
95-th percentile6260000
Maximum6420000
Range2800000
Interquartile range (IQR)810000

Descriptive statistics

Standard deviation608936.2
Coefficient of variation (CV)0.12528319
Kurtosis0.081447315
Mean4860478.1
Median Absolute Deviation (MAD)401000
Skewness0.72610313
Sum4.8604781 × 1010
Variance3.708033 × 1011
MonotonicityNot monotonic
2024-05-11T10:15:28.514563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4721000 467
 
4.7%
5530000 442
 
4.4%
4530000 390
 
3.9%
5710000 380
 
3.8%
6420000 360
 
3.6%
4820000 318
 
3.2%
4490000 310
 
3.1%
4780000 305
 
3.0%
4720000 294
 
2.9%
4430000 272
 
2.7%
Other values (65) 6462
64.6%
ValueCountFrequency (%)
3620000 63
0.6%
3780000 11
 
0.1%
3820000 2
 
< 0.1%
3830000 2
 
< 0.1%
3860000 2
 
< 0.1%
3900000 5
 
0.1%
3930000 33
0.3%
3940000 62
0.6%
3990000 39
0.4%
4010000 32
0.3%
ValueCountFrequency (%)
6420000 360
3.6%
6280000 107
 
1.1%
6260000 122
 
1.2%
5710000 380
3.8%
5670000 78
 
0.8%
5540000 94
 
0.9%
5530000 442
4.4%
5480000 213
2.1%
5450000 207
2.1%
5440000 159
 
1.6%
Distinct75
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:15:29.044277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.04
Min length3

Characters and Unicode

Total characters80400
Distinct characters73
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청북도 청주시
2nd row부산광역시
3rd row충청남도 서산시
4th row경기도 안성시
5th row전북특별자치도 완주군
ValueCountFrequency (%)
경기도 1278
 
6.6%
경상북도 1195
 
6.2%
충청남도 1175
 
6.1%
강원도 1099
 
5.7%
전라북도 960
 
4.9%
경상남도 869
 
4.5%
충청북도 846
 
4.4%
강원특별자치도 812
 
4.2%
전북특별자치도 809
 
4.2%
완주군 761
 
3.9%
Other values (64) 9607
49.5%
2024-05-11T10:15:30.080541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9889
 
12.3%
9411
 
11.7%
4888
 
6.1%
4784
 
6.0%
3873
 
4.8%
3801
 
4.7%
2850
 
3.5%
2653
 
3.3%
2434
 
3.0%
2348
 
2.9%
Other values (63) 33469
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70989
88.3%
Space Separator 9411
 
11.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9889
 
13.9%
4888
 
6.9%
4784
 
6.7%
3873
 
5.5%
3801
 
5.4%
2850
 
4.0%
2653
 
3.7%
2434
 
3.4%
2348
 
3.3%
2240
 
3.2%
Other values (62) 31229
44.0%
Space Separator
ValueCountFrequency (%)
9411
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70989
88.3%
Common 9411
 
11.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9889
 
13.9%
4888
 
6.9%
4784
 
6.7%
3873
 
5.5%
3801
 
5.4%
2850
 
4.0%
2653
 
3.7%
2434
 
3.4%
2348
 
3.3%
2240
 
3.2%
Other values (62) 31229
44.0%
Common
ValueCountFrequency (%)
9411
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70989
88.3%
ASCII 9411
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9889
 
13.9%
4888
 
6.9%
4784
 
6.7%
3873
 
5.5%
3801
 
5.4%
2850
 
4.0%
2653
 
3.7%
2434
 
3.4%
2348
 
3.3%
2240
 
3.2%
Other values (62) 31229
44.0%
ASCII
ValueCountFrequency (%)
9411
100.0%

Interactions

2024-05-11T10:14:58.538122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:49.445924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:51.266105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:53.153746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:54.952557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:56.761774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:58.920424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:49.810032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:51.742532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:53.380151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:55.310017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:57.079696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:59.142002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:50.035384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:52.013952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:53.711826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:55.614115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:57.428431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:59.433994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:50.397663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:52.276633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:54.043524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:55.907869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:57.698873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:59.673432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:50.721414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:52.638544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:54.335380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:56.198637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:57.980914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:59.982097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:50.997581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:52.964236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:54.628560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:56.464856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:14:58.238241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:15:30.401755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치상세위치구분명가동상태구분명설비용량공급전압주파수설치연도세부용도허가기관설치면적데이터기준일자제공기관코드제공기관명
위도1.0000.7790.5400.6580.0000.0320.0000.1440.7240.9230.3860.9300.8190.930
경도0.7791.0000.6620.4250.1570.1340.0770.2240.7540.9820.0000.9570.9000.957
설치상세위치구분명0.5400.6621.0000.4040.0710.355NaN0.0780.2430.8180.0460.8550.5520.855
가동상태구분명0.6580.4250.4041.0000.2520.3490.0000.6080.2400.7600.0750.7640.5000.807
설비용량0.0000.1570.0710.2521.0000.5660.0000.1380.0990.4000.6850.4030.2610.412
공급전압0.0320.1340.3550.3490.5661.0000.0000.4020.3620.6410.5040.6390.5610.667
주파수0.0000.077NaN0.0000.0000.0001.0000.0000.0000.000NaN0.0000.0000.000
설치연도0.1440.2240.0780.6080.1380.4020.0001.0000.1200.6480.1490.8100.5640.828
세부용도0.7240.7540.2430.2400.0990.3620.0000.1201.0000.9690.1380.9800.7700.980
허가기관0.9230.9820.8180.7600.4000.6410.0000.6480.9691.0000.2101.0000.9990.999
설치면적0.3860.0000.0460.0750.6850.504NaN0.1490.1380.2101.0000.0710.0530.040
데이터기준일자0.9300.9570.8550.7640.4030.6390.0000.8100.9801.0000.0711.0000.9891.000
제공기관코드0.8190.9000.5520.5000.2610.5610.0000.5640.7700.9990.0530.9891.0001.000
제공기관명0.9300.9570.8550.8070.4120.6670.0000.8280.9800.9990.0401.0001.0001.000
2024-05-11T10:15:30.814197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주파수가동상태구분명공급전압설치상세위치구분명세부용도
주파수1.0000.0000.0001.0000.000
가동상태구분명0.0001.0000.1720.1830.102
공급전압0.0000.1721.0000.2490.200
설치상세위치구분명1.0000.1830.2491.0000.158
세부용도0.0000.1020.2000.1581.000
2024-05-11T10:15:31.392864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설비용량설치연도설치면적제공기관코드설치상세위치구분명가동상태구분명공급전압주파수세부용도
위도1.000-0.152-0.042-0.2030.224-0.7550.3680.3710.0200.0000.428
경도-0.1521.0000.067-0.0870.0380.3010.4580.2820.0800.0460.624
설비용량-0.0420.0671.0000.0440.663-0.0150.0260.1550.2470.0000.052
설치연도-0.203-0.0870.0441.000-0.294-0.1010.1720.3630.1640.0000.082
설치면적0.2240.0380.663-0.2941.000-0.1400.0370.0310.3481.0000.055
제공기관코드-0.7550.301-0.015-0.101-0.1401.0000.3460.2550.2460.0000.514
설치상세위치구분명0.3680.4580.0260.1720.0370.3461.0000.1830.2491.0000.158
가동상태구분명0.3710.2820.1550.3630.0310.2550.1831.0000.1720.0000.102
공급전압0.0200.0800.2470.1640.3480.2460.2490.1721.0000.0000.200
주파수0.0000.0460.0000.0001.0000.0001.0000.0000.0001.0000.000
세부용도0.4280.6240.0520.0820.0550.5140.1580.1020.2000.0001.000

Missing values

2024-05-11T10:15:00.449414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:15:01.246495image/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.
2024-05-11T10:15:01.808140image/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

태양광발전시설명소재지도로명주소소재지지번주소위도경도설치상세위치구분명가동상태구분명설비용량공급전압주파수설치연도세부용도허가일자허가기관설치면적데이터기준일자제공기관코드제공기관명
45242한성 태양광발전소충청북도 청주시 청원구 오창읍 두릉1길 63-22<NA><NA><NA><NA>정상가동199.82380602023전기사업2022-06-23<NA><NA>2023-08-075710000충청북도 청주시
3193주식회사 부산태양광1호(트렉스타 본사부산광역시 강서구 녹산산업중로192번길 23(송정동)<NA>35.091512128.841492<NA>정상가동194.4380602022발전사업용2021-09-13부산광역시청<NA>2022-11-296260000부산광역시
30420옥당태양광발전소충청남도 서산시 부석면 대두리 501-28, 501-29, 501-34<NA><NA><NA><NA>정상가동999.622900602023<NA>2023-05-15충청남도 서산시청<NA>2023-07-124530000충청남도 서산시
34973명보4호 태양광발전소<NA>경기도 안성시 대덕면 무능리 309,314,315<NA><NA><NA>가동중단99.68380602020<NA>2020-09-21경기도 안성시청<NA>2023-07-064080000경기도 안성시
6873대흥3호 태양광발전소<NA>전북특별자치도 완주군 소양면 대흥리 887(답)(토지위)<NA><NA><NA>정상가동50.0220380602017<NA>2017-08-28<NA>1339.02024-01-294721000전북특별자치도 완주군
3266한국대동지공업3 태양광발전소부산광역시 강서구 과학산단로333번길 32 (지사동)<NA>35.146289128.832674<NA>정상가동91.8380602021발전사업용2021-03-04부산광역시청<NA>2022-11-296260000부산광역시
36242유정태양광발전소<NA>전북특별자치도 완주군 용진읍 간중리 877번지 건물상부<NA><NA><NA>정상가동19.0380602014<NA>2014-02-25<NA>96.02024-01-294721000전북특별자치도 완주군
12749선택한우발전소3호경상남도 합천군 율곡면 임북1길 45경상남도 합천군 율곡면 임북리 555번지 8호<NA><NA><NA>정상가동99.9380602020발전사업용2019-11-26경상남도 합천군청<NA>2023-10-255480000경상남도 합천군
31395서산54호 태양광발전소충청남도 서산시 부석면 지산리 150-10<NA><NA><NA><NA>정상가동98.8380602018<NA>2018-07-12충청남도 서산시청<NA>2023-07-124530000충청남도 서산시
11183153선교태양광발전소경상남도 김해시 인제로 190, 선교빌딩 (어방동)<NA><NA><NA><NA>정상가동59.78380602016<NA>2015-11-04경상남도 김해시청<NA>2022-11-295350000경상남도 김해시
태양광발전시설명소재지도로명주소소재지지번주소위도경도설치상세위치구분명가동상태구분명설비용량공급전압주파수설치연도세부용도허가일자허가기관설치면적데이터기준일자제공기관코드제공기관명
18900파란하늘1호태양광발전소<NA>전라북도 완주군 경천면<NA><NA><NA>정상가동90.675380602022<NA><NA><NA><NA>2022-11-224720000전라북도 완주군
9580새봄1호 태양광발전소충청남도 천안시 서북구 성환읍 양령2길 184<NA><NA><NA><NA>정상가동99.96380602023<NA><NA><NA><NA>2023-07-044490000충청남도 천안시
34740우리5호 태양광발전소<NA>경기도 안성시 미양면 고지리 48-1,43,44-1,48,51 마동<NA><NA><NA>가동중단98.88380602022<NA>2022-08-18경기도 안성시청<NA>2023-07-064080000경기도 안성시
24546구현 태양광발전소강원도 인제군 남면 관대리 산 106번지 3호<NA><NA><NA><NA>정상가동99.23380602017<NA>2016-11-08강원도 인제군청<NA>2022-12-014331000강원특별자치도 인제군
33555병철태양광발전소<NA>전라북도 고창군 성내면 옥제리 산1-1<NA><NA><NA>정상가동297.022900602015<NA><NA><NA><NA>2023-07-104780000전라북도 고창군
14710통해제9태양광충청남도 부여군 초촌면 국사로129번길 118<NA><NA><NA><NA>정상가동999.0380602018<NA>2016-11-17<NA><NA>2023-03-204570000충청남도 부여군
3879금평1호 태앙광발전소<NA>충청남도 천안시 서북구 성환읍 신가리 503-8 ,9(건물 위)<NA><NA><NA>정상가동99.96380602020<NA><NA><NA><NA>2023-07-044490000충청남도 천안시
47498성우에너지<NA>경상북도 영주시 이산면 두월리<NA><NA>옥외정상가동98.28380602008<NA>2007-11-27<NA><NA>2023-08-185090000경상북도 영주시
1749보라매1호 태양광발전소<NA>강원도 강릉시 구정면<NA><NA><NA>정상가동20.0380602021발전사업용<NA>강원도 강릉시청<NA>2022-11-254200000강원도 강릉시
49182마전2호 태양광발전소<NA>경상북도 예천군 지보면 마전리 754번지 1호 750<NA><NA><NA>정상가동99.36380602021발전사업용2019-05-31경상북도 예천군청<NA>2023-10-125230000경상북도 예천군

Duplicate rows

Most frequently occurring

태양광발전시설명소재지도로명주소소재지지번주소위도경도설치상세위치구분명가동상태구분명설비용량공급전압주파수설치연도세부용도허가일자허가기관설치면적데이터기준일자제공기관코드제공기관명# duplicates
0성은에너지 태양광발전소경기도 고양시 일산서구 이산포길 364-60<NA><NA><NA><NA>정상가동99.0380602015발전사업용<NA><NA><NA>2022-11-213940000경기도 고양시2