Overview

Dataset statistics

Number of variables18
Number of observations80
Missing cells109
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory152.7 B

Variable types

Text3
Numeric5
DateTime5
Categorical5

Dataset

Description경상남도 거제시 태양광 사업 현황에 대한 데이터로 허가번호, 발전소명,허가용량, 주소, 설비용량, 공급전압 등의 자료를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033873

Alerts

주파수 has constant value ""Constant
기준일자 has constant value ""Constant
허가용량(킬로와트) is highly overall correlated with 설치면적(제곱미터) and 1 other fieldsHigh correlation
설치면적(제곱미터) is highly overall correlated with 허가용량(킬로와트) and 3 other fieldsHigh correlation
설비용량 is highly overall correlated with 허가용량(킬로와트) and 1 other fieldsHigh correlation
상태 is highly overall correlated with 지목High correlation
설치위치 is highly overall correlated with 설치면적(제곱미터) and 1 other fieldsHigh correlation
지목 is highly overall correlated with 설치면적(제곱미터) and 2 other fieldsHigh correlation
공급전압 is highly imbalanced (57.2%)Imbalance
사업개시일 has 16 (20.0%) missing valuesMissing
완공개시일 has 16 (20.0%) missing valuesMissing
공사준공예정일 has 77 (96.2%) missing valuesMissing
허가번호 has unique valuesUnique
발전소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:03:59.975867
Analysis finished2023-12-10 23:04:03.719137
Duration3.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T08:04:03.928103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters1840
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row2008-5370000-38-5-00001
2nd row2010-5370000-38-5-00002
3rd row2012-5370000-38-5-00005
4th row2012-5370000-38-5-00006
5th row2012-5370000-38-5-00007
ValueCountFrequency (%)
2008-5370000-38-5-00001 1
 
1.2%
2010-5370000-38-5-00002 1
 
1.2%
2020-5370000-38-5-00006 1
 
1.2%
2020-5370000-38-5-00005 1
 
1.2%
2020-5370000-38-5-00004 1
 
1.2%
2020-5370000-38-5-00003 1
 
1.2%
2020-5370000-38-5-00002 1
 
1.2%
2020-5370000-38-5-00001 1
 
1.2%
2019-5370000-38-5-00020 1
 
1.2%
2020-5370000-38-5-00008 1
 
1.2%
Other values (70) 70
87.5%
2023-12-11T08:04:04.346712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 700
38.0%
- 320
17.4%
5 175
 
9.5%
3 174
 
9.5%
2 127
 
6.9%
1 106
 
5.8%
8 104
 
5.7%
7 89
 
4.8%
6 16
 
0.9%
4 15
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1520
82.6%
Dash Punctuation 320
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 700
46.1%
5 175
 
11.5%
3 174
 
11.4%
2 127
 
8.4%
1 106
 
7.0%
8 104
 
6.8%
7 89
 
5.9%
6 16
 
1.1%
4 15
 
1.0%
9 14
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 700
38.0%
- 320
17.4%
5 175
 
9.5%
3 174
 
9.5%
2 127
 
6.9%
1 106
 
5.8%
8 104
 
5.7%
7 89
 
4.8%
6 16
 
0.9%
4 15
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 700
38.0%
- 320
17.4%
5 175
 
9.5%
3 174
 
9.5%
2 127
 
6.9%
1 106
 
5.8%
8 104
 
5.7%
7 89
 
4.8%
6 16
 
0.9%
4 15
 
0.8%

발전소명
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T08:04:04.677042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.7125
Min length5

Characters and Unicode

Total characters857
Distinct characters149
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row광열발전소
2nd row드비치골프클럽태양광발전소
3rd row미인태양광발전소
4th row사등모터월드태양광발전소
5th row(주)유성기업태양광발전소
ValueCountFrequency (%)
태양광발전소 32
 
23.4%
발전소 6
 
4.4%
태양광 4
 
2.9%
원홍수산 2
 
1.5%
수상태양광 2
 
1.5%
한국카본솔렉트 2
 
1.5%
모햇태양광발전소 2
 
1.5%
와우펜션 2
 
1.5%
주차장 2
 
1.5%
광열발전소 1
 
0.7%
Other values (82) 82
59.9%
2023-12-11T08:04:05.200598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
발 80
 
9.3%
전 77
 
9.0%
소 77
 
9.0%
양 73
 
8.5%
광 72
 
8.4%
태 66
 
7.7%
57
 
6.7%
제 24
 
2.8%
거 19
 
2.2%
호 15
 
1.8%
Other values (139) 297
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 758
88.4%
Space Separator 57
 
6.7%
Decimal Number 27
 
3.2%
Uppercase Letter 7
 
0.8%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 80
 
10.6%
전 77
 
10.2%
소 77
 
10.2%
양 73
 
9.6%
광 72
 
9.5%
태 66
 
8.7%
제 24
 
3.2%
거 19
 
2.5%
호 15
 
2.0%
동 10
 
1.3%
Other values (122) 245
32.3%
Decimal Number
ValueCountFrequency (%)
1 10
37.0%
2 7
25.9%
8 4
 
14.8%
4 2
 
7.4%
3 2
 
7.4%
9 1
 
3.7%
5 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
14.3%
N 1
14.3%
P 1
14.3%
A 1
14.3%
G 1
14.3%
S 1
14.3%
L 1
14.3%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 758
88.4%
Common 92
 
10.7%
Latin 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
발 80
 
10.6%
전 77
 
10.2%
소 77
 
10.2%
양 73
 
9.6%
광 72
 
9.5%
태 66
 
8.7%
제 24
 
3.2%
거 19
 
2.5%
호 15
 
2.0%
동 10
 
1.3%
Other values (122) 245
32.3%
Common
ValueCountFrequency (%)
57
62.0%
1 10
 
10.9%
2 7
 
7.6%
) 4
 
4.3%
( 4
 
4.3%
8 4
 
4.3%
4 2
 
2.2%
3 2
 
2.2%
9 1
 
1.1%
5 1
 
1.1%
Latin
ValueCountFrequency (%)
B 1
14.3%
N 1
14.3%
P 1
14.3%
A 1
14.3%
G 1
14.3%
S 1
14.3%
L 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 758
88.4%
ASCII 99
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
발 80
 
10.6%
전 77
 
10.2%
소 77
 
10.2%
양 73
 
9.6%
광 72
 
9.5%
태 66
 
8.7%
제 24
 
3.2%
거 19
 
2.5%
호 15
 
2.0%
동 10
 
1.3%
Other values (122) 245
32.3%
ASCII
ValueCountFrequency (%)
57
57.6%
1 10
 
10.1%
2 7
 
7.1%
) 4
 
4.0%
( 4
 
4.0%
8 4
 
4.0%
4 2
 
2.0%
3 2
 
2.0%
B 1
 
1.0%
N 1
 
1.0%
Other values (7) 7
 
7.1%

허가용량(킬로와트)
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.70912
Minimum5
Maximum499.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T08:04:05.366392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile17.91
Q129.6
median97.77
Q399.61
95-th percentile466.196
Maximum499.95
Range494.95
Interquartile range (IQR)70.01

Descriptive statistics

Standard deviation124.08127
Coefficient of variation (CV)1.0912164
Kurtosis3.4139345
Mean113.70912
Median Absolute Deviation (MAD)52.575
Skewness2.0144452
Sum9096.73
Variance15396.161
MonotonicityNot monotonic
2023-12-11T08:04:05.513056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.6 6
 
7.5%
99.36 6
 
7.5%
20.0 4
 
5.0%
99.0 3
 
3.8%
18.0 2
 
2.5%
29.6 2
 
2.5%
29.58 2
 
2.5%
499.95 2
 
2.5%
99.64 2
 
2.5%
48.6 2
 
2.5%
Other values (48) 49
61.3%
ValueCountFrequency (%)
5.0 1
 
1.2%
9.01 1
 
1.2%
15.0 1
 
1.2%
16.2 1
 
1.2%
18.0 2
2.5%
18.38 1
 
1.2%
19.2 1
 
1.2%
19.8 1
 
1.2%
20.0 4
5.0%
24.36 1
 
1.2%
ValueCountFrequency (%)
499.95 2
2.5%
493.68 1
1.2%
490.44 1
1.2%
464.92 1
1.2%
370.98 1
1.2%
334.08 1
1.2%
300.0 1
1.2%
299.3 1
1.2%
289.44 1
1.2%
261.45 1
1.2%

설치면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean880.49042
Minimum34
Maximum6100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T08:04:05.661475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile96.874
Q1160
median493.25
Q31113.75
95-th percentile2661.28
Maximum6100
Range6066
Interquartile range (IQR)953.75

Descriptive statistics

Standard deviation1168.5403
Coefficient of variation (CV)1.327147
Kurtosis9.432024
Mean880.49042
Median Absolute Deviation (MAD)347.75
Skewness2.884108
Sum70439.234
Variance1365486.3
MonotonicityNot monotonic
2023-12-11T08:04:05.810710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
581.0 5
 
6.2%
145.0 2
 
2.5%
516.177 2
 
2.5%
943.0 2
 
2.5%
489.5 2
 
2.5%
130.0 2
 
2.5%
287.16 2
 
2.5%
496.5 1
 
1.2%
98.7 1
 
1.2%
247.0 1
 
1.2%
Other values (60) 60
75.0%
ValueCountFrequency (%)
34.0 1
1.2%
52.8 1
1.2%
70.0 1
1.2%
78.14 1
1.2%
97.86 1
1.2%
98.6 1
1.2%
98.7 1
1.2%
98.8 1
1.2%
102.54 1
1.2%
109.4 1
1.2%
ValueCountFrequency (%)
6100.0 1
1.2%
5800.0 1
1.2%
5121.0 1
1.2%
3179.6 1
1.2%
2634.0 1
1.2%
2488.0 1
1.2%
2182.0 1
1.2%
2079.0 1
1.2%
2047.64 1
1.2%
1812.0 1
1.2%

설치장소
Text

Distinct67
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T08:04:06.073582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length35.5
Mean length26.1375
Min length16

Characters and Unicode

Total characters2091
Distinct characters105
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)76.2%

Sample

1st row경상남도 거제시 일운면 지세포3길 21 (건물옥상)
2nd row경상남도 거제시 장목면 송진포리 산 77번지 3호 외 5필지
3rd row경상남도 거제시 거제면 동상명진길 61
4th row경상남도 거제시 사등면 지석2길 20
5th row경상남도 거제시 장평3로 80 (장평동)
ValueCountFrequency (%)
경상남도 80
20.2%
거제시 80
20.2%
둔덕면 18
 
4.5%
학산리 11
 
2.8%
동부면 10
 
2.5%
연초면 9
 
2.3%
하청면 7
 
1.8%
거제면 7
 
1.8%
사등면 6
 
1.5%
산9-1 5
 
1.3%
Other values (130) 164
41.3%
2023-12-11T08:04:06.433821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
 
15.2%
1 96
 
4.6%
거 90
 
4.3%
제 89
 
4.3%
상 83
 
4.0%
남 82
 
3.9%
경 80
 
3.8%
도 80
 
3.8%
시 80
 
3.8%
- 71
 
3.4%
Other values (95) 1023
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1155
55.2%
Decimal Number 432
 
20.7%
Space Separator 317
 
15.2%
Dash Punctuation 71
 
3.4%
Other Punctuation 48
 
2.3%
Close Punctuation 34
 
1.6%
Open Punctuation 34
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 90
 
7.8%
제 89
 
7.7%
상 83
 
7.2%
남 82
 
7.1%
경 80
 
6.9%
도 80
 
6.9%
시 80
 
6.9%
면 66
 
5.7%
리 44
 
3.8%
산 30
 
2.6%
Other values (80) 431
37.3%
Decimal Number
ValueCountFrequency (%)
1 96
22.2%
2 69
16.0%
8 43
10.0%
4 43
10.0%
5 38
 
8.8%
3 36
 
8.3%
0 35
 
8.1%
6 27
 
6.2%
9 27
 
6.2%
7 18
 
4.2%
Space Separator
ValueCountFrequency (%)
317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Other Punctuation
ValueCountFrequency (%)
， 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1155
55.2%
Common 936
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 90
 
7.8%
제 89
 
7.7%
상 83
 
7.2%
남 82
 
7.1%
경 80
 
6.9%
도 80
 
6.9%
시 80
 
6.9%
면 66
 
5.7%
리 44
 
3.8%
산 30
 
2.6%
Other values (80) 431
37.3%
Common
ValueCountFrequency (%)
317
33.9%
1 96
 
10.3%
- 71
 
7.6%
2 69
 
7.4%
， 48
 
5.1%
8 43
 
4.6%
4 43
 
4.6%
5 38
 
4.1%
3 36
 
3.8%
0 35
 
3.7%
Other values (5) 140
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1155
55.2%
ASCII 888
42.5%
None 48
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
35.7%
1 96
 
10.8%
- 71
 
8.0%
2 69
 
7.8%
8 43
 
4.8%
4 43
 
4.8%
5 38
 
4.3%
3 36
 
4.1%
0 35
 
3.9%
) 34
 
3.8%
Other values (4) 106
 
11.9%
Hangul
ValueCountFrequency (%)
거 90
 
7.8%
제 89
 
7.7%
상 83
 
7.2%
남 82
 
7.1%
경 80
 
6.9%
도 80
 
6.9%
시 80
 
6.9%
면 66
 
5.7%
리 44
 
3.8%
산 30
 
2.6%
Other values (80) 431
37.3%
None
ValueCountFrequency (%)
， 48
100.0%

위도
Real number (ℝ)

Distinct66
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.863717
Minimum34.35578
Maximum35.016486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T08:04:06.588253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.35578
5-th percentile34.772535
Q134.835825
median34.872881
Q334.903817
95-th percentile34.955405
Maximum35.016486
Range0.66070675
Interquartile range (IQR)0.067991805

Descriptive statistics

Standard deviation0.077560839
Coefficient of variation (CV)0.0022246865
Kurtosis22.667543
Mean34.863717
Median Absolute Deviation (MAD)0.033882055
Skewness-3.5232846
Sum2789.0974
Variance0.0060156837
MonotonicityNot monotonic
2023-12-11T08:04:07.021717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.87323281 5
 
6.2%
34.87288057 5
 
6.2%
34.83324668 3
 
3.8%
34.91769656 2
 
2.5%
34.84845001 2
 
2.5%
34.7933254 2
 
2.5%
34.88293674 2
 
2.5%
34.89008192 1
 
1.2%
34.85844676 1
 
1.2%
34.77254482 1
 
1.2%
Other values (56) 56
70.0%
ValueCountFrequency (%)
34.35577958 1
1.2%
34.76789563 1
1.2%
34.7680845 1
1.2%
34.77234173 1
1.2%
34.77254482 1
1.2%
34.77693099 1
1.2%
34.77970325 1
1.2%
34.77975478 1
1.2%
34.78440557 1
1.2%
34.7933254 2
2.5%
ValueCountFrequency (%)
35.01648633 1
1.2%
34.96039601 1
1.2%
34.95859898 1
1.2%
34.95826315 1
1.2%
34.95525433 1
1.2%
34.95347696 1
1.2%
34.95071081 1
1.2%
34.94959813 1
1.2%
34.94728416 1
1.2%
34.92379871 1
1.2%

경도
Real number (ℝ)

Distinct66
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59769
Minimum128.47809
Maximum128.73127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T08:04:07.190965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.47809
5-th percentile128.48235
Q1128.53325
median128.61201
Q3128.64778
95-th percentile128.70112
Maximum128.73127
Range0.2531834
Interquartile range (IQR)0.11452607

Descriptive statistics

Standard deviation0.070100349
Coefficient of variation (CV)0.00054511358
Kurtosis-1.0310501
Mean128.59769
Median Absolute Deviation (MAD)0.04319705
Skewness-0.29757542
Sum10287.815
Variance0.0049140589
MonotonicityNot monotonic
2023-12-11T08:04:07.382438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.4866964 5
 
6.2%
128.4823518 5
 
6.2%
128.5078344 3
 
3.8%
128.6184983 2
 
2.5%
128.5402084 2
 
2.5%
128.5734069 2
 
2.5%
128.5724549 2
 
2.5%
128.627809 1
 
1.2%
128.4780895 1
 
1.2%
128.5979861 1
 
1.2%
Other values (56) 56
70.0%
ValueCountFrequency (%)
128.4780895 1
 
1.2%
128.4823518 5
6.2%
128.4866964 5
6.2%
128.5078344 3
3.8%
128.5106713 1
 
1.2%
128.5150218 1
 
1.2%
128.5162904 1
 
1.2%
128.5163605 1
 
1.2%
128.5242845 1
 
1.2%
128.5299975 1
 
1.2%
ValueCountFrequency (%)
128.7312729 1
1.2%
128.7138361 1
1.2%
128.7018883 1
1.2%
128.7016253 1
1.2%
128.7010912 1
1.2%
128.6944557 1
1.2%
128.6898539 1
1.2%
128.6886891 1
1.2%
128.6829233 1
1.2%
128.6814561 1
1.2%

허가일시
Date

Distinct51
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum2008-08-22 00:00:00
Maximum2022-08-31 00:00:00
2023-12-11T08:04:07.542703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:07.685620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업개시일
Date

MISSING 

Distinct47
Distinct (%)73.4%
Missing16
Missing (%)20.0%
Memory size772.0 B
Minimum2008-10-08 00:00:00
Maximum2022-08-05 00:00:00
2023-12-11T08:04:07.823023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:07.976568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

상태
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
사업개시
64 
인허가
13 
공사계획
 
3

Length

Max length4
Median length4
Mean length3.8375
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사업개시 64
80.0%
인허가 13
 
16.2%
공사계획 3
 
3.8%

Length

2023-12-11T08:04:08.141595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:08.261757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업개시 64
80.0%
인허가 13
 
16.2%
공사계획 3
 
3.8%

완공개시일
Date

MISSING 

Distinct46
Distinct (%)71.9%
Missing16
Missing (%)20.0%
Memory size772.0 B
Minimum2008-10-08 00:00:00
Maximum2021-12-08 00:00:00
2023-12-11T08:04:08.393566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:08.551806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

공사준공예정일
Date

MISSING 

Distinct3
Distinct (%)100.0%
Missing77
Missing (%)96.2%
Memory size772.0 B
Minimum2022-11-15 00:00:00
Maximum2023-01-02 00:00:00
2023-12-11T08:04:08.669218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:08.772143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

설치위치
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
건물
49 
토지
21 
주차장
5 
수상
 
2
건물，주차장
 
2

Length

Max length6
Median length2
Mean length2.1625
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
건물 49
61.3%
토지 21
26.2%
주차장 5
 
6.2%
수상 2
 
2.5%
건물，주차장 2
 
2.5%
해상 1
 
1.2%

Length

2023-12-11T08:04:08.911060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:09.043673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물 49
61.3%
토지 21
26.2%
주차장 5
 
6.2%
수상 2
 
2.5%
건물，주차장 2
 
2.5%
해상 1
 
1.2%

설비용량
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.70912
Minimum5
Maximum499.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T08:04:09.167439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile17.91
Q129.6
median97.77
Q399.61
95-th percentile466.196
Maximum499.95
Range494.95
Interquartile range (IQR)70.01

Descriptive statistics

Standard deviation124.08127
Coefficient of variation (CV)1.0912164
Kurtosis3.4139345
Mean113.70912
Median Absolute Deviation (MAD)52.575
Skewness2.0144452
Sum9096.73
Variance15396.161
MonotonicityNot monotonic
2023-12-11T08:04:09.330736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.6 6
 
7.5%
99.36 6
 
7.5%
20.0 4
 
5.0%
99.0 3
 
3.8%
18.0 2
 
2.5%
29.6 2
 
2.5%
29.58 2
 
2.5%
499.95 2
 
2.5%
99.64 2
 
2.5%
48.6 2
 
2.5%
Other values (48) 49
61.3%
ValueCountFrequency (%)
5.0 1
 
1.2%
9.01 1
 
1.2%
15.0 1
 
1.2%
16.2 1
 
1.2%
18.0 2
2.5%
18.38 1
 
1.2%
19.2 1
 
1.2%
19.8 1
 
1.2%
20.0 4
5.0%
24.36 1
 
1.2%
ValueCountFrequency (%)
499.95 2
2.5%
493.68 1
1.2%
490.44 1
1.2%
464.92 1
1.2%
370.98 1
1.2%
334.08 1
1.2%
300.0 1
1.2%
299.3 1
1.2%
289.44 1
1.2%
261.45 1
1.2%

공급전압
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
380
73 
220
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row220
2nd row380
3rd row380
4th row380
5th row380

Common Values

ValueCountFrequency (%)
380 73
91.2%
220 7
 
8.8%

Length

2023-12-11T08:04:09.457599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:09.577705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
380 73
91.2%
220 7
 
8.8%

주파수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
60
80 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
60 80
100.0%

Length

2023-12-11T08:04:09.666476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:09.752058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 80
100.0%

지목
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
대
25 
잡종지
14 
답
10 
임야
5 
공장
4 
Other values (14)
22 

Length

Max length15
Median length11
Mean length2.5375
Min length1

Unique

Unique8 ?
Unique (%)10.0%

Sample

1st row대
2nd row체육용지
3rd row대
4th row대
5th row대

Common Values

ValueCountFrequency (%)
대 25
31.2%
잡종지 14
17.5%
답 10
 
12.5%
임야 5
 
6.2%
공장 4
 
5.0%
창고용지 3
 
3.8%
체육용지 3
 
3.8%
대지 2
 
2.5%
답/답/답 2
 
2.5%
전 2
 
2.5%
Other values (9) 10
 
12.5%

Length

2023-12-11T08:04:09.853995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 25
30.5%
잡종지 15
18.3%
답 10
 
12.2%
임야 5
 
6.1%
공장 4
 
4.9%
창고용지 4
 
4.9%
체육용지 3
 
3.7%
공장용지 2
 
2.4%
전 2
 
2.4%
답/답/답 2
 
2.4%
Other values (9) 10
 
12.2%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum2022-11-29 00:00:00
Maximum2022-11-29 00:00:00
2023-12-11T08:04:09.950752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:10.056514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T08:04:02.693000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:00.773704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.180691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.608034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.193137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.794269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:00.854216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.268262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.703158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.286782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.895583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:00.937263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.358366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.814270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.416894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.995678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.026146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.444179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.977948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.513352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:03.078267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.104694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:01.529455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.100285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:02.598195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:04:10.172239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가번호발전소명허가용량(킬로와트)설치면적(제곱미터)설치장소위도경도허가일시사업개시일상태완공개시일공사준공예정일설치위치설비용량공급전압지목
허가번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
발전소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
허가용량(킬로와트)1.0001.0001.0000.8051.0000.7000.3820.7830.8980.7880.0001.0000.5991.0000.2020.846
설치면적(제곱미터)1.0001.0000.8051.0000.9930.0000.3220.9470.9650.4800.9521.0000.7480.8050.0000.860
설치장소1.0001.0001.0000.9931.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0001.0000.7000.0001.0001.0000.5330.8300.9650.5390.9481.0000.1610.7000.0720.603
경도1.0001.0000.3820.3221.0000.5331.0000.9760.9860.4860.981NaN0.5070.3820.1520.574
허가일시1.0001.0000.7830.9471.0000.8300.9761.0000.9990.9760.9991.0000.9500.7831.0000.972
사업개시일1.0001.0000.8980.9651.0000.9650.9860.9991.000NaN1.000NaN1.0000.8981.0000.995
상태1.0001.0000.7880.4801.0000.5390.4860.976NaN1.000NaNNaN0.7590.7880.0000.807
완공개시일1.0001.0000.0000.9521.0000.9480.9810.9991.000NaN1.000NaN1.0000.0001.0000.985
공사준공예정일1.0001.0001.0001.0001.0001.000NaN1.000NaNNaNNaN1.0001.0001.000NaN1.000
설치위치1.0001.0000.5990.7481.0000.1610.5070.9501.0000.7591.0001.0001.0000.5990.0000.927
설비용량1.0001.0001.0000.8051.0000.7000.3820.7830.8980.7880.0001.0000.5991.0000.2020.846
공급전압1.0001.0000.2020.0001.0000.0720.1521.0001.0000.0001.000NaN0.0000.2021.0000.000
지목1.0001.0000.8460.8601.0000.6030.5740.9720.9950.8070.9851.0000.9270.8460.0001.000
2023-12-11T08:04:10.312107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치상태지목공급전압
설치위치1.0000.4280.6880.000
상태0.4281.0000.5610.000
지목0.6880.5611.0000.000
공급전압0.0000.0000.0001.000
2023-12-11T08:04:10.395399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가용량(킬로와트)설치면적(제곱미터)위도경도설비용량상태설치위치공급전압지목
허가용량(킬로와트)1.0000.885-0.067-0.1561.0000.4730.3390.1890.497
설치면적(제곱미터)0.8851.0000.027-0.1560.8850.3350.5330.0000.543
위도-0.0670.0271.0000.168-0.0670.4730.1040.0830.313
경도-0.156-0.1560.1681.000-0.1560.2850.2660.1150.219
설비용량1.0000.885-0.067-0.1561.0000.4730.3390.1890.497
상태0.4730.3350.4730.2850.4731.0000.4280.0000.561
설치위치0.3390.5330.1040.2660.3390.4281.0000.0000.688
공급전압0.1890.0000.0830.1150.1890.0000.0001.0000.000
지목0.4970.5430.3130.2190.4970.5610.6880.0001.000

Missing values

2023-12-11T08:04:03.224804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:04:03.479462image/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.
2023-12-11T08:04:03.647028image/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

허가번호발전소명허가용량(킬로와트)설치면적(제곱미터)설치장소위도경도허가일시사업개시일상태완공개시일공사준공예정일설치위치설비용량공급전압주파수지목기준일자
02008-5370000-38-5-00001광열발전소19.270.0경상남도 거제시 일운면 지세포3길 21 (건물옥상)34.827371128.7010912008-08-222008-10-08사업개시2008-10-08<NA>건물19.222060대2022-11-29
12010-5370000-38-5-00002드비치골프클럽태양광발전소75.0400.0경상남도 거제시 장목면 송진포리 산 77번지 3호 외 5필지35.016486128.6743692010-06-152010-11-22사업개시2010-11-22<NA>주차장75.038060체육용지2022-11-29
22012-5370000-38-5-00005미인태양광발전소24.3698.6경상남도 거제시 거제면 동상명진길 6134.848047128.59922012-04-022012-07-30사업개시2012-07-30<NA>건물24.3638060대2022-11-29
32012-5370000-38-5-00006사등모터월드태양광발전소36.48253.0경상남도 거제시 사등면 지석2길 2034.907408128.5150222012-09-192013-01-14사업개시2013-01-14<NA>건물36.4838060대2022-11-29
42012-5370000-38-5-00007(주)유성기업태양광발전소26.25186.0경상남도 거제시 장평3로 80 (장평동)34.897131128.6102142012-10-242013-01-30사업개시2013-01-30<NA>건물26.2538060대2022-11-29
52013-5370000-38-5-00008학동자동차야영장태양광발전소5.034.0경상남도 거제시 동부면 학동리 252번지34.776931128.6411962013-04-122013-06-26사업개시2013-06-26<NA>토지5.022060답2022-11-29
62013-5370000-38-5-00009제1호연초농협태양광발전소20.0130.0경상남도 거제시 연초면 거제북로 2634.913529128.6550732013-07-262013-12-18사업개시2013-12-18<NA>건물20.022060대2022-11-29
72013-5370000-38-5-00010제2호연초농협태양광발전소20.0130.0경상남도 거제시 연초면 거제북로 26-134.913482128.6553472013-07-262013-12-18사업개시2013-12-18<NA>건물20.022060대2022-11-29
82013-5370000-38-5-00011외포태양광발전소9.0152.8경상남도 거제시 장목면 외포대금산길 50-234.949598128.7138362013-08-272014-02-18사업개시2014-02-18<NA>건물9.0122060잡종지2022-11-29
92014-5370000-38-5-00014거제해양관광개발제1발전소48.6287.16경상남도 거제시 일운면 지세포해안로 4134.833695128.7018882014-03-312014-06-30사업개시2014-06-30<NA>건물48.638060잡종지2022-11-29
허가번호발전소명허가용량(킬로와트)설치면적(제곱미터)설치장소위도경도허가일시사업개시일상태완공개시일공사준공예정일설치위치설비용량공급전압주파수지목기준일자
702021-5370000-38-5-00011경남테크 태양광발전소29.58145.0경상남도 거제시 사등면 사곡리 415-1(건물지붕)34.882937128.5724552021-07-192021-12-01사업개시2021-12-01<NA>건물29.5838060대2022-11-29
712021-5370000-38-5-00012양정2 태양광발전소213.41045.0경상남도 거제시 양정동 27，27-10，432(건물지붕)34.873024128.6554292021-07-192022-08-05사업개시2021-12-08<NA>건물213.438060창고용지, 잡종지2022-11-29
722021-5370000-38-5-00013와우펜션 A동 태양광발전소44.16256.0경상남도 거제시 동부면 고촌길 34(건물위)34.779755128.6475872021-09-012021-12-08사업개시2021-12-08<NA>건물44.1638060대2022-11-29
732021-5370000-38-5-00014와우펜션 B동 태양광발전소29.44157.0경상남도 거제시 동부면 고촌길 34-1(건물위)34.779703128.6471062021-09-012021-12-08사업개시2021-12-08<NA>건물29.4438060대2022-11-29
742021-5370000-38-5-00015모햇태양광발전소 88호99.19489.5경상남도 거제시 둔덕면 방하리 9-1(건물 지붕)34.84845128.5402082021-10-26<NA>인허가<NA><NA>건물99.1938060잡종지2022-11-29
752021-5370000-38-5-00016모햇태양광발전소 89호99.19489.5경상남도 거제시 둔덕면 방하리 9-1(건물 지붕)34.84845128.5402082021-10-26<NA>인허가<NA><NA>건물99.1938060잡종지2022-11-29
762022-5370000-38-5-00001한국카본솔렉트 거제1호 발전소202.86465.0경상남도 거제시 하청면 유계리661(가동)34.35578128.6383252022-06-28<NA>공사계획<NA>2022-11-15건물202.8638060공장2022-11-29
772022-5370000-38-5-00002한국카본솔렉트 거제2호 발전소99.96943.0경상남도 거제시 하청면 유계리661(나동)34.955254128.6384922022-06-28<NA>공사계획<NA>2022-11-16건물99.9638060공장2022-11-29
782022-5370000-38-5-00003거제도 해상 태양광 연구발전소493.682488.0경상남도 거제시 하청면 하청리 628-29일원 (공유수면)34.960396128.6504092022-08-31<NA>공사계획<NA>2023-01-02해상493.6838060공유수면2022-11-29
792022-5370000-38-5-00004효성거제PNL 태양광발전소370.98943.0경상남도 거제시 연초면 오비리 760-16(건물 위)34.923799128.6177412022-08-31<NA>인허가<NA><NA>건물370.9838060공장2022-11-29