Overview

Dataset statistics

Number of variables17
Number of observations82
Missing cells18
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory144.6 B

Variable types

Text3
Numeric5
DateTime3
Categorical6

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 2 other fieldsHigh correlation
설비용량 is highly overall correlated with 허가용량(킬로와트) and 1 other fieldsHigh correlation
상태 is highly overall correlated with 설치위치High correlation
설치위치 is highly overall correlated with 상태 and 1 other fieldsHigh correlation
지목 is highly overall correlated with 설치면적(제곱미터) and 1 other fieldsHigh correlation
상태 is highly imbalanced (65.0%)Imbalance
공급전압 is highly imbalanced (57.9%)Imbalance
사업개시일 has 9 (11.0%) missing valuesMissing
완공개시일 has 9 (11.0%) missing valuesMissing
허가번호 has unique valuesUnique
발전소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:03:48.546652
Analysis finished2023-12-10 23:03:52.008591
Duration3.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-11T08:03:52.172011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters1886
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

Unique82 ?
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%
2021-5370000-38-5-00008 1
 
1.2%
2021-5370000-38-5-00004 1
 
1.2%
2021-5370000-38-5-00003 1
 
1.2%
2021-5370000-38-5-00001 1
 
1.2%
2020-5370000-38-5-00013 1
 
1.2%
2020-5370000-38-5-00012 1
 
1.2%
2020-5370000-38-5-00011 1
 
1.2%
2020-5370000-38-5-00008 1
 
1.2%
2020-5370000-38-5-00006 1
 
1.2%
Other values (72) 72
87.8%
2023-12-11T08:03:52.814497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 724
38.4%
- 328
17.4%
3 184
 
9.8%
5 181
 
9.6%
2 141
 
7.5%
8 103
 
5.5%
7 93
 
4.9%
1 93
 
4.9%
6 15
 
0.8%
4 15
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1558
82.6%
Dash Punctuation 328
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 724
46.5%
3 184
 
11.8%
5 181
 
11.6%
2 141
 
9.1%
8 103
 
6.6%
7 93
 
6.0%
1 93
 
6.0%
6 15
 
1.0%
4 15
 
1.0%
9 9
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 328
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 724
38.4%
- 328
17.4%
3 184
 
9.8%
5 181
 
9.6%
2 141
 
7.5%
8 103
 
5.5%
7 93
 
4.9%
1 93
 
4.9%
6 15
 
0.8%
4 15
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 724
38.4%
- 328
17.4%
3 184
 
9.8%
5 181
 
9.6%
2 141
 
7.5%
8 103
 
5.5%
7 93
 
4.9%
1 93
 
4.9%
6 15
 
0.8%
4 15
 
0.8%

발전소명
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-11T08:03:53.181685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.756098
Min length5

Characters and Unicode

Total characters882
Distinct characters152
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

Unique82 ?
Unique (%)100.0%

Sample

1st row광열발전소
2nd row드비치골프클럽태양광발전소
3rd row미인태양광발전소
4th row사등모터월드태양광발전소
5th row(주)유성기업태양광발전소
ValueCountFrequency (%)
태양광발전소 35
23.8%
발전소 9
 
6.1%
태양광 6
 
4.1%
와우펜션 2
 
1.4%
수상태양광 2
 
1.4%
모햇태양광발전소 2
 
1.4%
한국카본솔렉트 2
 
1.4%
원홍수산 2
 
1.4%
주차장 2
 
1.4%
옥포운동장 1
 
0.7%
Other values (84) 84
57.1%
2023-12-11T08:03:53.701096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
발 82
 
9.3%
전 79
 
9.0%
소 79
 
9.0%
양 75
 
8.5%
광 74
 
8.4%
태 68
 
7.7%
65
 
7.4%
제 22
 
2.5%
거 17
 
1.9%
호 17
 
1.9%
Other values (142) 304
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 775
87.9%
Space Separator 65
 
7.4%
Decimal Number 27
 
3.1%
Uppercase Letter 7
 
0.8%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 82
 
10.6%
전 79
 
10.2%
소 79
 
10.2%
양 75
 
9.7%
광 74
 
9.5%
태 68
 
8.8%
제 22
 
2.8%
거 17
 
2.2%
호 17
 
2.2%
동 13
 
1.7%
Other values (125) 249
32.1%
Decimal Number
ValueCountFrequency (%)
1 10
37.0%
2 7
25.9%
8 4
 
14.8%
3 3
 
11.1%
9 1
 
3.7%
5 1
 
3.7%
4 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
L 1
14.3%
B 1
14.3%
N 1
14.3%
P 1
14.3%
G 1
14.3%
S 1
14.3%
A 1
14.3%
Space Separator
ValueCountFrequency (%)
65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 775
87.9%
Common 100
 
11.3%
Latin 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
발 82
 
10.6%
전 79
 
10.2%
소 79
 
10.2%
양 75
 
9.7%
광 74
 
9.5%
태 68
 
8.8%
제 22
 
2.8%
거 17
 
2.2%
호 17
 
2.2%
동 13
 
1.7%
Other values (125) 249
32.1%
Common
ValueCountFrequency (%)
65
65.0%
1 10
 
10.0%
2 7
 
7.0%
8 4
 
4.0%
) 4
 
4.0%
( 4
 
4.0%
3 3
 
3.0%
9 1
 
1.0%
5 1
 
1.0%
4 1
 
1.0%
Latin
ValueCountFrequency (%)
L 1
14.3%
B 1
14.3%
N 1
14.3%
P 1
14.3%
G 1
14.3%
S 1
14.3%
A 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 775
87.9%
ASCII 107
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
발 82
 
10.6%
전 79
 
10.2%
소 79
 
10.2%
양 75
 
9.7%
광 74
 
9.5%
태 68
 
8.8%
제 22
 
2.8%
거 17
 
2.2%
호 17
 
2.2%
동 13
 
1.7%
Other values (125) 249
32.1%
ASCII
ValueCountFrequency (%)
65
60.7%
1 10
 
9.3%
2 7
 
6.5%
8 4
 
3.7%
) 4
 
3.7%
( 4
 
3.7%
3 3
 
2.8%
L 1
 
0.9%
B 1
 
0.9%
N 1
 
0.9%
Other values (7) 7
 
6.5%

허가용량(킬로와트)
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.35037
Minimum5
Maximum668.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T08:03:53.869860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile16.594
Q129.585
median97.625
Q399.71
95-th percentile489.164
Maximum668.5
Range663.5
Interquartile range (IQR)70.125

Descriptive statistics

Standard deviation139.25288
Coefficient of variation (CV)1.1475275
Kurtosis3.7966814
Mean121.35037
Median Absolute Deviation (MAD)64.505
Skewness2.043461
Sum9950.73
Variance19391.365
MonotonicityNot monotonic
2023-12-11T08:03:54.026197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.6 6
 
7.3%
99.36 6
 
7.3%
20.0 4
 
4.9%
99.0 3
 
3.7%
18.0 2
 
2.4%
499.95 2
 
2.4%
29.6 2
 
2.4%
29.58 2
 
2.4%
99.19 2
 
2.4%
48.6 2
 
2.4%
Other values (50) 51
62.2%
ValueCountFrequency (%)
5.0 1
1.2%
9.01 1
1.2%
15.0 1
1.2%
16.2 1
1.2%
16.52 1
1.2%
18.0 2
2.4%
18.38 1
1.2%
19.2 1
1.2%
19.5 1
1.2%
19.8 1
1.2%
ValueCountFrequency (%)
668.5 1
1.2%
499.95 2
2.4%
493.68 1
1.2%
490.44 1
1.2%
464.92 1
1.2%
370.98 1
1.2%
332.0 1
1.2%
300.0 1
1.2%
299.3 1
1.2%
299.13 1
1.2%

설치면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean836.79676
Minimum34
Maximum6100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T08:03:54.195367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile78.93
Q1158
median489.5
Q31030.75
95-th percentile2626.7
Maximum6100
Range6066
Interquartile range (IQR)872.75

Descriptive statistics

Standard deviation1088.6469
Coefficient of variation (CV)1.3009693
Kurtosis10.806826
Mean836.79676
Median Absolute Deviation (MAD)344
Skewness2.9647773
Sum68617.334
Variance1185152.1
MonotonicityNot monotonic
2023-12-11T08:03:54.412870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
581.0 5
 
6.1%
145.0 2
 
2.4%
489.5 2
 
2.4%
130.0 2
 
2.4%
488.0 2
 
2.4%
287.16 2
 
2.4%
943.0 2
 
2.4%
516.177 2
 
2.4%
448.0 1
 
1.2%
399.0 1
 
1.2%
Other values (61) 61
74.4%
ValueCountFrequency (%)
34.0 1
1.2%
52.8 1
1.2%
70.0 1
1.2%
77.33 1
1.2%
78.14 1
1.2%
93.94 1
1.2%
98.6 1
1.2%
98.7 1
1.2%
98.8 1
1.2%
102.54 1
1.2%
ValueCountFrequency (%)
6100.0 1
1.2%
5800.0 1
1.2%
3191.0 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

Distinct71
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-11T08:03:54.631392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length35
Mean length26.195122
Min length16

Characters and Unicode

Total characters2148
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

Unique66 ?
Unique (%)80.5%

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 82
19.6%
거제시 82
19.6%
연초면 14
 
3.3%
둔덕면 13
 
3.1%
학산리 10
 
2.4%
동부면 10
 
2.4%
위 10
 
2.4%
거제면 8
 
1.9%
하청면 7
 
1.7%
사등면 6
 
1.4%
Other values (136) 176
42.1%
2023-12-11T08:03:54.968789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
336
 
15.6%
1 103
 
4.8%
거 93
 
4.3%
제 92
 
4.3%
상 86
 
4.0%
시 82
 
3.8%
경 82
 
3.8%
도 82
 
3.8%
남 82
 
3.8%
- 68
 
3.2%
Other values (95) 1042
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1194
55.6%
Decimal Number 430
 
20.0%
Space Separator 336
 
15.6%
Dash Punctuation 68
 
3.2%
Other Punctuation 44
 
2.0%
Open Punctuation 38
 
1.8%
Close Punctuation 38
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 93
 
7.8%
제 92
 
7.7%
상 86
 
7.2%
시 82
 
6.9%
경 82
 
6.9%
도 82
 
6.9%
남 82
 
6.9%
면 65
 
5.4%
리 44
 
3.7%
산 30
 
2.5%
Other values (80) 456
38.2%
Decimal Number
ValueCountFrequency (%)
1 103
24.0%
2 65
15.1%
5 43
10.0%
4 41
 
9.5%
0 35
 
8.1%
8 34
 
7.9%
3 32
 
7.4%
9 30
 
7.0%
6 26
 
6.0%
7 21
 
4.9%
Space Separator
ValueCountFrequency (%)
336
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Other Punctuation
ValueCountFrequency (%)
， 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1194
55.6%
Common 954
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 93
 
7.8%
제 92
 
7.7%
상 86
 
7.2%
시 82
 
6.9%
경 82
 
6.9%
도 82
 
6.9%
남 82
 
6.9%
면 65
 
5.4%
리 44
 
3.7%
산 30
 
2.5%
Other values (80) 456
38.2%
Common
ValueCountFrequency (%)
336
35.2%
1 103
 
10.8%
- 68
 
7.1%
2 65
 
6.8%
， 44
 
4.6%
5 43
 
4.5%
4 41
 
4.3%
( 38
 
4.0%
) 38
 
4.0%
0 35
 
3.7%
Other values (5) 143
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1194
55.6%
ASCII 910
42.4%
None 44
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
336
36.9%
1 103
 
11.3%
- 68
 
7.5%
2 65
 
7.1%
5 43
 
4.7%
4 41
 
4.5%
( 38
 
4.2%
) 38
 
4.2%
0 35
 
3.8%
8 34
 
3.7%
Other values (4) 109
 
12.0%
Hangul
ValueCountFrequency (%)
거 93
 
7.8%
제 92
 
7.7%
상 86
 
7.2%
시 82
 
6.9%
경 82
 
6.9%
도 82
 
6.9%
남 82
 
6.9%
면 65
 
5.4%
리 44
 
3.7%
산 30
 
2.5%
Other values (80) 456
38.2%
None
ValueCountFrequency (%)
， 44
100.0%

위도
Real number (ℝ)

Distinct70
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.871914
Minimum34.35578
Maximum35.016486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T08:03:55.123700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.35578
5-th percentile34.779706
Q134.849271
median34.873233
Q334.912137
95-th percentile34.955165
Maximum35.016486
Range0.66070675
Interquartile range (IQR)0.062866067

Descriptive statistics

Standard deviation0.076002206
Coefficient of variation (CV)0.0021794676
Kurtosis25.756941
Mean34.871914
Median Absolute Deviation (MAD)0.031350935
Skewness-3.9000892
Sum2859.497
Variance0.0057763354
MonotonicityNot monotonic
2023-12-11T08:03:55.278800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.87288057 5
 
6.1%
34.87323281 5
 
6.1%
34.7933254 2
 
2.4%
34.84845001 2
 
2.4%
34.88293674 2
 
2.4%
34.91769656 2
 
2.4%
34.78440557 1
 
1.2%
34.81127791 1
 
1.2%
34.92118126 1
 
1.2%
34.87086721 1
 
1.2%
Other values (60) 60
73.2%
ValueCountFrequency (%)
34.35577958 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
2.4%
34.81127791 1
1.2%
34.81195709 1
1.2%
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%
34.9276 1
1.2%

경도
Real number (ℝ)

Distinct70
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.60732
Minimum128.48235
Maximum128.73127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T08:03:55.442193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.48235
5-th percentile128.48257
Q1128.57245
median128.61869
Q3128.65186
95-th percentile128.70076
Maximum128.73127
Range0.2489211
Interquartile range (IQR)0.0794088

Descriptive statistics

Standard deviation0.067085318
Coefficient of variation (CV)0.00052162908
Kurtosis-0.67306663
Mean128.60732
Median Absolute Deviation (MAD)0.0369488
Skewness-0.50650887
Sum10545.8
Variance0.0045004399
MonotonicityNot monotonic
2023-12-11T08:03:55.576059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.4823518 5
 
6.1%
128.4866964 5
 
6.1%
128.5734069 2
 
2.4%
128.5402084 2
 
2.4%
128.5724549 2
 
2.4%
128.6184983 2
 
2.4%
128.5685374 1
 
1.2%
128.5162904 1
 
1.2%
128.6814561 1
 
1.2%
128.5946955 1
 
1.2%
Other values (60) 60
73.2%
ValueCountFrequency (%)
128.4823518 5
6.1%
128.4866964 5
6.1%
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%
128.5343399 1
 
1.2%
128.5402084 2
 
2.4%
128.5633095 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%
128.6933 1
1.2%
128.6898539 1
1.2%
128.6886891 1
1.2%
128.6818 1
1.2%

허가일시
Date

Distinct51
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2008-08-22 00:00:00
Maximum2023-10-25 00:00:00
2023-12-11T08:03:55.705707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:55.838176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업개시일
Date

MISSING 

Distinct54
Distinct (%)74.0%
Missing9
Missing (%)11.0%
Memory size788.0 B
Minimum2008-10-08 00:00:00
Maximum2023-07-18 00:00:00
2023-12-11T08:03:55.965967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:56.087500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
사업개시
73 
인허가
8 
공사계획
 
1

Length

Max length4
Median length4
Mean length3.902439
Min length3

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
사업개시 73
89.0%
인허가 8
 
9.8%
공사계획 1
 
1.2%

Length

2023-12-11T08:03:56.214232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:03:56.308609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업개시 73
89.0%
인허가 8
 
9.8%
공사계획 1
 
1.2%

완공개시일
Date

MISSING 

Distinct53
Distinct (%)72.6%
Missing9
Missing (%)11.0%
Memory size788.0 B
Minimum2008-10-08 00:00:00
Maximum2023-07-18 00:00:00
2023-12-11T08:03:56.427270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:56.557540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

설치위치
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
건물
44 
토지
19 
건물지붕
6 
주차장
5 
주차장위
 
3
Other values (3)
5 

Length

Max length6
Median length2
Mean length2.3780488
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
건물 44
53.7%
토지 19
23.2%
건물지붕 6
 
7.3%
주차장 5
 
6.1%
주차장위 3
 
3.7%
수상 2
 
2.4%
건물，주차장 2
 
2.4%
해상 1
 
1.2%

Length

2023-12-11T08:03:56.675151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:03:56.783169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물 44
53.7%
토지 19
23.2%
건물지붕 6
 
7.3%
주차장 5
 
6.1%
주차장위 3
 
3.7%
수상 2
 
2.4%
건물，주차장 2
 
2.4%
해상 1
 
1.2%

설비용량
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.35037
Minimum5
Maximum668.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T08:03:56.891115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile16.594
Q129.585
median97.625
Q399.71
95-th percentile489.164
Maximum668.5
Range663.5
Interquartile range (IQR)70.125

Descriptive statistics

Standard deviation139.25288
Coefficient of variation (CV)1.1475275
Kurtosis3.7966814
Mean121.35037
Median Absolute Deviation (MAD)64.505
Skewness2.043461
Sum9950.73
Variance19391.365
MonotonicityNot monotonic
2023-12-11T08:03:57.029669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.6 6
 
7.3%
99.36 6
 
7.3%
20.0 4
 
4.9%
99.0 3
 
3.7%
18.0 2
 
2.4%
499.95 2
 
2.4%
29.6 2
 
2.4%
29.58 2
 
2.4%
99.19 2
 
2.4%
48.6 2
 
2.4%
Other values (50) 51
62.2%
ValueCountFrequency (%)
5.0 1
1.2%
9.01 1
1.2%
15.0 1
1.2%
16.2 1
1.2%
16.52 1
1.2%
18.0 2
2.4%
18.38 1
1.2%
19.2 1
1.2%
19.5 1
1.2%
19.8 1
1.2%
ValueCountFrequency (%)
668.5 1
1.2%
499.95 2
2.4%
493.68 1
1.2%
490.44 1
1.2%
464.92 1
1.2%
370.98 1
1.2%
332.0 1
1.2%
300.0 1
1.2%
299.3 1
1.2%
299.13 1
1.2%

공급전압
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
380
75 
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 75
91.5%
220 7
 
8.5%

Length

2023-12-11T08:03:57.169148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:03:57.257204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
380 75
91.5%
220 7
 
8.5%

주파수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
60
82 

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 82
100.0%

Length

2023-12-11T08:03:57.363682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:03:57.453471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 82
100.0%

지목
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
대
27 
잡종지
13 
답
6 
공장
6 
임야
6 
Other values (14)
24 

Length

Max length15
Median length11
Mean length2.597561
Min length1

Unique

Unique8 ?
Unique (%)9.8%

Sample

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

Common Values

ValueCountFrequency (%)
대 27
32.9%
잡종지 13
15.9%
답 6
 
7.3%
공장 6
 
7.3%
임야 6
 
7.3%
창고용지 4
 
4.9%
체육용지 3
 
3.7%
대(건물) 3
 
3.7%
전 2
 
2.4%
대지 2
 
2.4%
Other values (9) 10
 
12.2%

Length

2023-12-11T08:03:57.551201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 27
32.1%
잡종지 14
16.7%
답 6
 
7.1%
공장 6
 
7.1%
임야 6
 
7.1%
창고용지 5
 
6.0%
체육용지 3
 
3.6%
대(건물 3
 
3.6%
공장용지 2
 
2.4%
대지 2
 
2.4%
Other values (9) 10
 
11.9%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-11-22
82 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-22
2nd row2023-11-22
3rd row2023-11-22
4th row2023-11-22
5th row2023-11-22

Common Values

ValueCountFrequency (%)
2023-11-22 82
100.0%

Length

2023-12-11T08:03:57.669810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:03:57.772421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-22 82
100.0%

Interactions

2023-12-11T08:03:51.021475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.234864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.640666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.115509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.549890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.117098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.307693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.770100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.216210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.629724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.200323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.383467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.876661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.304240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.734663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.304068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.462417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.957960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.381126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.863526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.430732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:49.539173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.031708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.455747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.937683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:03:57.843647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가번호발전소명허가용량(킬로와트)설치면적(제곱미터)설치장소위도경도허가일시사업개시일상태완공개시일설치위치설비용량공급전압지목
허가번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
발전소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
허가용량(킬로와트)1.0001.0001.0000.8071.0000.3430.0560.0000.8950.7390.7920.6231.0000.1760.790
설치면적(제곱미터)1.0001.0000.8071.0000.9880.0000.3780.8480.9710.4760.9500.7120.8070.0000.879
설치장소1.0001.0001.0000.9881.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0001.0000.3430.0001.0001.0000.4770.8560.8070.1200.7760.2820.3430.0000.485
경도1.0001.0000.0560.3781.0000.4771.0000.9680.9900.2760.9910.3910.0560.1250.000
허가일시1.0001.0000.0000.8481.0000.8560.9681.0000.9990.0000.9990.9450.0001.0000.959
사업개시일1.0001.0000.8950.9711.0000.8070.9900.9991.000NaN1.0001.0000.8951.0000.996
상태1.0001.0000.7390.4761.0000.1200.2760.000NaN1.000NaN0.6920.7390.0000.333
완공개시일1.0001.0000.7920.9501.0000.7760.9910.9991.000NaN1.0001.0000.7921.0000.989
설치위치1.0001.0000.6230.7121.0000.2820.3910.9451.0000.6921.0001.0000.6230.0000.906
설비용량1.0001.0001.0000.8071.0000.3430.0560.0000.8950.7390.7920.6231.0000.1760.790
공급전압1.0001.0000.1760.0001.0000.0000.1251.0001.0000.0001.0000.0000.1761.0000.000
지목1.0001.0000.7900.8791.0000.4850.0000.9590.9960.3330.9890.9060.7900.0001.000
2023-12-11T08:03:57.981109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치상태지목공급전압
설치위치1.0000.5570.6310.000
상태0.5571.0000.1590.000
지목0.6310.1591.0000.000
공급전압0.0000.0000.0001.000
2023-12-11T08:03:58.498274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가용량(킬로와트)설치면적(제곱미터)위도경도설비용량상태설치위치공급전압지목
허가용량(킬로와트)1.0000.8880.096-0.1241.0000.4260.3620.1640.423
설치면적(제곱미터)0.8881.0000.096-0.2310.8880.3530.4800.0000.592
위도0.0960.0961.0000.1820.0960.0850.1700.0000.235
경도-0.124-0.2310.1821.000-0.1240.1890.2580.1390.109
설비용량1.0000.8880.096-0.1241.0000.4260.3620.1640.423
상태0.4260.3530.0850.1890.4261.0000.5570.0000.159
설치위치0.3620.4800.1700.2580.3620.5571.0000.0000.631
공급전압0.1640.0000.0000.1390.1640.0000.0001.0000.000
지목0.4230.5920.2350.1090.4230.1590.6310.0001.000

Missing values

2023-12-11T08:03:51.593755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:03:51.836960image/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.
2023-12-11T08:03:51.958606image/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)설치장소위도경도허가일시사업개시일상태완공개시일설치위치설비용량공급전압주파수지목기준일자
02008-5370000-38-5-00001광열발전소19.270.0경상남도 거제시 일운면 지세포3길 21 (건물옥상)34.827371128.7010912008-08-222008-10-08사업개시2008-10-08건물19.222060대2023-11-22
12010-5370000-38-5-00002드비치골프클럽태양광발전소75.0400.0경상남도 거제시 장목면 송진포리 산 77번지 3호 외 5필지35.016486128.6743692010-06-152010-11-22사업개시2010-11-22주차장75.038060체육용지2023-11-22
22012-5370000-38-5-00005미인태양광발전소24.3698.6경상남도 거제시 거제면 동상명진길 6134.848047128.59922012-04-022012-07-30사업개시2012-07-30건물24.3638060대2023-11-22
32012-5370000-38-5-00006사등모터월드태양광발전소36.48253.0경상남도 거제시 사등면 지석2길 2034.907408128.5150222012-09-192013-01-14사업개시2013-01-14건물36.4838060대2023-11-22
42012-5370000-38-5-00007(주)유성기업태양광발전소26.25186.0경상남도 거제시 장평3로 80 (장평동)34.897131128.6102142012-10-242013-01-30사업개시2013-01-30건물26.2538060대2023-11-22
52013-5370000-38-5-00008학동자동차야영장태양광발전소5.034.0경상남도 거제시 동부면 학동리 252번지34.776931128.6411962013-04-122013-06-26사업개시2013-06-26토지5.022060답2023-11-22
62013-5370000-38-5-00009제1호연초농협태양광발전소20.0130.0경상남도 거제시 연초면 거제북로 2634.913529128.6550732013-07-262013-12-18사업개시2013-12-18건물20.022060대2023-11-22
72013-5370000-38-5-00010제2호연초농협태양광발전소20.0130.0경상남도 거제시 연초면 거제북로 26-134.913482128.6553472013-07-262013-12-18사업개시2013-12-18건물20.022060대2023-11-22
82013-5370000-38-5-00011외포태양광발전소9.0152.8경상남도 거제시 장목면 외포대금산길 50-234.949598128.7138362013-08-272014-02-18사업개시2014-02-18건물9.0122060잡종지2023-11-22
92014-5370000-38-5-00014거제해양관광개발제1발전소48.6287.16경상남도 거제시 일운면 지세포해안로 4134.833695128.7018882014-03-312014-06-30사업개시2014-06-30건물48.638060잡종지2023-11-22
허가번호발전소명허가용량(킬로와트)설치면적(제곱미터)설치장소위도경도허가일시사업개시일상태완공개시일설치위치설비용량공급전압주파수지목기준일자
722022-5370000-38-5-00005장평 태양광발전소181.72988.0경상남도 거제시 장평동 1110-9(건물 위)34.90253128.58412022-11-282023-07-18사업개시2023-07-18건물지붕181.7238060창고용지2023-11-22
732022-5370000-38-5-00006동산3호 태양광발전소299.131338.0경상남도 거제시 연초면 송정리 산53-1(토지 위)34.9203128.68172022-11-28<NA>인허가<NA>토지299.1338060임야2023-11-22
742022-5370000-38-5-00007디케이 태양광발전소99.74478.15경상남도 거제시 연초면 연사리 56-3(건물 위)34.9081128.65222022-11-282023-05-15사업개시2023-05-15건물지붕99.7438060대(건물)2023-11-22
752022-5370000-38-5-00008섬섬 발전소19.593.94경상남도 거제시 거제면 동상리 29-2(건물 위)34.8471128.60272022-12-132023-04-28사업개시2023-04-28건물지붕19.538060대(건물)2023-11-22
762023-5370000-38-5-00001동산1호 태양광발전소99.71488.0경상남도 거제시 연초면 송정리 512-2(주차장 위)34.9207128.68182023-01-13<NA>인허가<NA>주차장위99.7138060대2023-11-22
772023-5370000-38-5-00002동산2호 태양광발전소99.71488.0경상남도 거제시 연초면 송정리 512-1(주차장 위)34.9211128.68142023-01-13<NA>인허가<NA>주차장위99.7138060대2023-11-22
782023-5370000-38-5-00003메카짐쏠라 태양광 발전소16.5277.33경상남도 거제시 옥포로 22길 2734.8954128.69332023-01-132023-06-21사업개시2023-06-21건물지붕16.5238060대(건물)2023-11-22
792023-5370000-38-5-00004삼녹1호 태양광발전소668.53191.0경상남도 거제시 연초면 오비리 779-3 외 4필지(건물 위)34.9196128.61352023-02-01<NA>인허가<NA>건물지붕668.538060공장2023-11-22
802023-5370000-38-5-00005삼녹2호 태양광발전소332.01492.5경상남도 거제시 연초면 한내리 161 외 2필지(건물 위)34.9276128.60412023-02-01<NA>공사계획<NA>건물지붕332.038060공장2023-11-22
812023-5370000-38-5-00007거제세일마트 태양광 발전소50.4235.0경상남도 거제시 고현동 987-5(주차장 위)34.8967128.62872023-10-25<NA>인허가<NA>주차장위50.438060대2023-11-22