Overview

Dataset statistics

Number of variables5
Number of observations503
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.8 KiB
Average record size in memory42.3 B

Variable types

Numeric2
Text2
DateTime1

Dataset

Description-공유 데이터명: 대전광역시 태양광발전소 현황-공유 데이터 내용: 태양광발전소 현황/ 발전소명, 설비용량, 설치장소, 사업개시일
Author대전광역시
URLhttps://www.data.go.kr/data/15122159/fileData.do

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:12:53.206704
Analysis finished2023-12-12 01:12:54.305141
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct503
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean252
Minimum1
Maximum503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T10:12:54.416387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.1
Q1126.5
median252
Q3377.5
95-th percentile477.9
Maximum503
Range502
Interquartile range (IQR)251

Descriptive statistics

Standard deviation145.34786
Coefficient of variation (CV)0.57677722
Kurtosis-1.2
Mean252
Median Absolute Deviation (MAD)126
Skewness0
Sum126756
Variance21126
MonotonicityStrictly increasing
2023-12-12T10:12:54.577831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
332 1
 
0.2%
345 1
 
0.2%
344 1
 
0.2%
343 1
 
0.2%
342 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
338 1
 
0.2%
Other values (493) 493
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
503 1
0.2%
502 1
0.2%
501 1
0.2%
500 1
0.2%
499 1
0.2%
498 1
0.2%
497 1
0.2%
496 1
0.2%
495 1
0.2%
494 1
0.2%

발전소명
Text

Distinct492
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T10:12:55.149476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length10.218688
Min length3

Characters and Unicode

Total characters5140
Distinct characters359
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique481 ?
Unique (%)95.6%

Sample

1st row대전대덕 태양광발전소 2
2nd row대전대덕 태양광발전소 1
3rd row우성 태양광발전소
4th row웅진에너지 태양광발전소 1호
5th row서울 태양광발전소
ValueCountFrequency (%)
태양광발전소 409
41.6%
발전소 15
 
1.5%
태양광 14
 
1.4%
햇빛발전소 8
 
0.8%
1호 6
 
0.6%
2호 4
 
0.4%
은혜 3
 
0.3%
한빛 3
 
0.3%
동양 2
 
0.2%
웅진에너지 2
 
0.2%
Other values (498) 517
52.6%
2023-12-12T10:12:55.924698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 517
 
10.1%
발 498
 
9.7%
소 497
 
9.7%
양 497
 
9.7%
광 494
 
9.6%
태 488
 
9.5%
480
 
9.3%
호 63
 
1.2%
대 53
 
1.0%
이 51
 
1.0%
Other values (349) 1502
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4512
87.8%
Space Separator 480
 
9.3%
Decimal Number 84
 
1.6%
Uppercase Letter 34
 
0.7%
Lowercase Letter 17
 
0.3%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Other Punctuation 4
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 517
 
11.5%
발 498
 
11.0%
소 497
 
11.0%
양 497
 
11.0%
광 494
 
10.9%
태 488
 
10.8%
호 63
 
1.4%
대 53
 
1.2%
이 51
 
1.1%
동 38
 
0.8%
Other values (308) 1316
29.2%
Uppercase Letter
ValueCountFrequency (%)
K 7
20.6%
S 5
14.7%
L 4
11.8%
E 4
11.8%
H 2
 
5.9%
Y 2
 
5.9%
M 1
 
2.9%
G 1
 
2.9%
N 1
 
2.9%
P 1
 
2.9%
Other values (6) 6
17.6%
Lowercase Letter
ValueCountFrequency (%)
o 3
17.6%
a 2
11.8%
r 2
11.8%
e 2
11.8%
c 1
 
5.9%
d 1
 
5.9%
p 1
 
5.9%
l 1
 
5.9%
s 1
 
5.9%
g 1
 
5.9%
Other values (2) 2
11.8%
Decimal Number
ValueCountFrequency (%)
1 43
51.2%
2 27
32.1%
3 5
 
6.0%
5 4
 
4.8%
6 2
 
2.4%
0 1
 
1.2%
9 1
 
1.2%
4 1
 
1.2%
Space Separator
ValueCountFrequency (%)
480
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4512
87.8%
Common 577
 
11.2%
Latin 51
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 517
 
11.5%
발 498
 
11.0%
소 497
 
11.0%
양 497
 
11.0%
광 494
 
10.9%
태 488
 
10.8%
호 63
 
1.4%
대 53
 
1.2%
이 51
 
1.1%
동 38
 
0.8%
Other values (308) 1316
29.2%
Latin
ValueCountFrequency (%)
K 7
 
13.7%
S 5
 
9.8%
L 4
 
7.8%
E 4
 
7.8%
o 3
 
5.9%
H 2
 
3.9%
Y 2
 
3.9%
a 2
 
3.9%
r 2
 
3.9%
e 2
 
3.9%
Other values (18) 18
35.3%
Common
ValueCountFrequency (%)
480
83.2%
1 43
 
7.5%
2 27
 
4.7%
3 5
 
0.9%
) 4
 
0.7%
( 4
 
0.7%
. 4
 
0.7%
5 4
 
0.7%
6 2
 
0.3%
0 1
 
0.2%
Other values (3) 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4512
87.8%
ASCII 628
 
12.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 517
 
11.5%
발 498
 
11.0%
소 497
 
11.0%
양 497
 
11.0%
광 494
 
10.9%
태 488
 
10.8%
호 63
 
1.4%
대 53
 
1.2%
이 51
 
1.1%
동 38
 
0.8%
Other values (308) 1316
29.2%
ASCII
ValueCountFrequency (%)
480
76.4%
1 43
 
6.8%
2 27
 
4.3%
K 7
 
1.1%
3 5
 
0.8%
S 5
 
0.8%
) 4
 
0.6%
L 4
 
0.6%
E 4
 
0.6%
( 4
 
0.6%
Other values (31) 45
 
7.2%

설치장소
Text

Distinct483
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T10:12:56.287848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length25.950298
Min length17

Characters and Unicode

Total characters13053
Distinct characters248
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique464 ?
Unique (%)92.2%

Sample

1st row대전광역시 대덕구 석봉로43번길 16 (석봉동)
2nd row대전광역시 대덕구 남경마을로1번길 16 (신탄진동)
3rd row대전광역시 서구 중반6길 72 (변동)
4th row대전광역시 유성구 테크노2로 37 (관평동)
5th row대전광역시 동구 송촌남로11번길 109 (용전동)
ValueCountFrequency (%)
대전광역시 503
 
20.4%
대덕구 152
 
6.2%
유성구 110
 
4.5%
서구 103
 
4.2%
동구 80
 
3.2%
중구 58
 
2.4%
오정동 37
 
1.5%
가양동 17
 
0.7%
테크노2로 15
 
0.6%
갈마동 14
 
0.6%
Other values (867) 1375
55.8%
2023-12-12T10:12:56.860757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1961
 
15.0%
대 789
 
6.0%
동 648
 
5.0%
전 549
 
4.2%
구 520
 
4.0%
광 508
 
3.9%
역 503
 
3.9%
시 503
 
3.9%
( 480
 
3.7%
) 480
 
3.7%
Other values (238) 6112
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7756
59.4%
Decimal Number 2119
 
16.2%
Space Separator 1961
 
15.0%
Open Punctuation 480
 
3.7%
Close Punctuation 480
 
3.7%
Dash Punctuation 156
 
1.2%
Other Punctuation 91
 
0.7%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 789
 
10.2%
동 648
 
8.4%
전 549
 
7.1%
구 520
 
6.7%
광 508
 
6.5%
역 503
 
6.5%
시 503
 
6.5%
로 414
 
5.3%
길 264
 
3.4%
번 243
 
3.1%
Other values (220) 2815
36.3%
Decimal Number
ValueCountFrequency (%)
1 446
21.0%
2 291
13.7%
3 237
11.2%
5 195
9.2%
4 189
8.9%
0 183
8.6%
7 167
 
7.9%
6 166
 
7.8%
8 129
 
6.1%
9 116
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 5
50.0%
B 3
30.0%
C 2
 
20.0%
Space Separator
ValueCountFrequency (%)
1961
100.0%
Open Punctuation
ValueCountFrequency (%)
( 480
100.0%
Close Punctuation
ValueCountFrequency (%)
) 480
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7756
59.4%
Common 5287
40.5%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 789
 
10.2%
동 648
 
8.4%
전 549
 
7.1%
구 520
 
6.7%
광 508
 
6.5%
역 503
 
6.5%
시 503
 
6.5%
로 414
 
5.3%
길 264
 
3.4%
번 243
 
3.1%
Other values (220) 2815
36.3%
Common
ValueCountFrequency (%)
1961
37.1%
( 480
 
9.1%
) 480
 
9.1%
1 446
 
8.4%
2 291
 
5.5%
3 237
 
4.5%
5 195
 
3.7%
4 189
 
3.6%
0 183
 
3.5%
7 167
 
3.2%
Other values (5) 658
 
12.4%
Latin
ValueCountFrequency (%)
A 5
50.0%
B 3
30.0%
C 2
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7756
59.4%
ASCII 5297
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1961
37.0%
( 480
 
9.1%
) 480
 
9.1%
1 446
 
8.4%
2 291
 
5.5%
3 237
 
4.5%
5 195
 
3.7%
4 189
 
3.6%
0 183
 
3.5%
7 167
 
3.2%
Other values (8) 668
 
12.6%
Hangul
ValueCountFrequency (%)
대 789
 
10.2%
동 648
 
8.4%
전 549
 
7.1%
구 520
 
6.7%
광 508
 
6.5%
역 503
 
6.5%
시 503
 
6.5%
로 414
 
5.3%
길 264
 
3.4%
번 243
 
3.1%
Other values (220) 2815
36.3%

설비용량(kW)
Real number (ℝ)

Distinct328
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.642107
Minimum3
Maximum2530.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T10:12:57.046028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile12.808
Q119.22
median29.96
Q387.255
95-th percentile245.508
Maximum2530.8
Range2527.8
Interquartile range (IQR)68.035

Descriptive statistics

Standard deviation224.82006
Coefficient of variation (CV)2.5652061
Kurtosis62.255665
Mean87.642107
Median Absolute Deviation (MAD)14.96
Skewness7.1968783
Sum44083.98
Variance50544.061
MonotonicityNot monotonic
2023-12-12T10:12:57.250372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.5 13
 
2.6%
19.8 12
 
2.4%
18.0 10
 
2.0%
99.0 8
 
1.6%
20.0 7
 
1.4%
18.72 7
 
1.4%
15.0 6
 
1.2%
19.0 6
 
1.2%
28.8 6
 
1.2%
30.0 6
 
1.2%
Other values (318) 422
83.9%
ValueCountFrequency (%)
3.0 2
0.4%
6.04 1
0.2%
8.0 2
0.4%
9.0 2
0.4%
9.99 1
0.2%
10.0 2
0.4%
10.08 1
0.2%
10.12 1
0.2%
10.36 1
0.2%
11.25 1
0.2%
ValueCountFrequency (%)
2530.8 1
0.2%
2356.2 1
0.2%
2008.8 1
0.2%
1300.0 1
0.2%
999.0 2
0.4%
998.4 1
0.2%
993.45 1
0.2%
990.0 1
0.2%
885.6 2
0.4%
825.44 1
0.2%

사업개시일
Date

Distinct340
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Minimum2008-08-25 00:00:00
Maximum2023-08-20 00:00:00
2023-12-12T10:12:57.414425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:12:57.584885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T10:12:53.804738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:12:53.615714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:12:53.931288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:12:53.709141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:12:57.687561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)
연번1.0000.057
설비용량(kW)0.0571.000
2023-12-12T10:12:57.774544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)
연번1.0000.056
설비용량(kW)0.0561.000

Missing values

2023-12-12T10:12:54.117521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:12:54.239786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번발전소명설치장소설비용량(kW)사업개시일
01대전대덕 태양광발전소 2대전광역시 대덕구 석봉로43번길 16 (석봉동)3.02008-08-25
12대전대덕 태양광발전소 1대전광역시 대덕구 남경마을로1번길 16 (신탄진동)12.02008-08-25
23우성 태양광발전소대전광역시 서구 중반6길 72 (변동)6.042008-09-03
34웅진에너지 태양광발전소 1호대전광역시 유성구 테크노2로 37 (관평동)200.02008-12-23
45서울 태양광발전소대전광역시 동구 송촌남로11번길 109 (용전동)3.02009-09-16
56롯데마트서대전점 태양광발전소대전광역시 유성구 유성대로 26-37 (원내동)99.02009-12-01
67플러스원 태양광발전소대전광역시 동구 계족로 413-7 (홍도동)22.082010-10-08
78웅진에너지 태양광발전소 2호대전광역시 유성구 테크노2로 37 (관평동)129.62010-11-01
89K-Water 본사 태양광발전소대전광역시 대덕구 신탄진로 200 (연축동)97.42011-12-23
910대원개발 태양광발전소대전광역시 서구 벌곡로 1095 (괴곡동)30.02011-12-29
연번발전소명설치장소설비용량(kW)사업개시일
493494해신 태양광발전소대전광역시 유성구 갑천로 362-1(탑립동)99.912023-05-16
494495불휘12호 햇빛발전소대전광역시 서구 구봉로 11(관저동)19.322023-05-22
495496보성 태양광발전소대전광역시 중구 보문산로177번안길 50, 0동(문화동, 보성빌라)35.42023-05-24
496497한밭냉동기 태양광 발전소대전광역시 대덕구 오정로78번길 75(오정동)20.02023-05-30
497498경국3 태양광발전소대전광역시 유성구 원내동 100-330.02023-06-07
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