Overview

Dataset statistics

Number of variables5
Number of observations1476
Missing cells4003
Missing cells (%)54.2%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory59.2 KiB
Average record size in memory41.1 B

Variable types

Text2
Numeric1
DateTime2

Dataset

Description경상북도 봉화군 태양광발전설치현황(발전소명, 설비용량, 발전소주소, 최초허가일, 데이터기준일자)을 제공합니다.
Author경상북도 봉화군
URLhttps://www.data.go.kr/data/15033937/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
발전소명 has 799 (54.1%) missing valuesMissing
설비용량 has 799 (54.1%) missing valuesMissing
설치장소 has 799 (54.1%) missing valuesMissing
허가일자 has 799 (54.1%) missing valuesMissing
데이터기준일자 has 807 (54.7%) missing valuesMissing

Reproduction

Analysis started2024-04-21 01:04:24.808000
Analysis finished2024-04-21 01:04:25.712831
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발전소명
Text

MISSING 

Distinct675
Distinct (%)99.7%
Missing799
Missing (%)54.1%
Memory size11.7 KiB
2024-04-21T10:04:25.951830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length10.423929
Min length4

Characters and Unicode

Total characters7057
Distinct characters321
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique673 ?
Unique (%)99.4%

Sample

1st row정순옥 태양광발전소
2nd row돌집 태양광발전소
3rd row어지1리마을회관 태양광발전소
4th row교동빌딩 태양광발전소
5th row두현2태양광발전소
ValueCountFrequency (%)
태양광발전소 319
30.2%
주식회사 9
 
0.9%
태양광 9
 
0.9%
발전소 6
 
0.6%
봉화 6
 
0.6%
님터 3
 
0.3%
봉래 3
 
0.3%
쏠라포스 3
 
0.3%
주민발전소 3
 
0.3%
유림 2
 
0.2%
Other values (689) 693
65.6%
2024-04-21T10:04:26.363806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 623
 
8.8%
소 620
 
8.8%
발 611
 
8.7%
양 602
 
8.5%
광 588
 
8.3%
태 581
 
8.2%
379
 
5.4%
호 174
 
2.5%
2 123
 
1.7%
1 107
 
1.5%
Other values (311) 2649
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6000
85.0%
Decimal Number 419
 
5.9%
Space Separator 379
 
5.4%
Open Punctuation 92
 
1.3%
Close Punctuation 92
 
1.3%
Uppercase Letter 44
 
0.6%
Other Symbol 23
 
0.3%
Dash Punctuation 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 623
 
10.4%
소 620
 
10.3%
발 611
 
10.2%
양 602
 
10.0%
광 588
 
9.8%
태 581
 
9.7%
호 174
 
2.9%
화 100
 
1.7%
지 83
 
1.4%
봉 74
 
1.2%
Other values (283) 1944
32.4%
Decimal Number
ValueCountFrequency (%)
2 123
29.4%
1 107
25.5%
3 58
13.8%
4 25
 
6.0%
5 24
 
5.7%
0 23
 
5.5%
7 20
 
4.8%
8 15
 
3.6%
6 12
 
2.9%
9 12
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
C 9
20.5%
S 8
18.2%
B 6
13.6%
K 5
11.4%
F 4
9.1%
P 4
9.1%
L 2
 
4.5%
M 2
 
4.5%
H 2
 
4.5%
Y 2
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 79
85.9%
[ 13
 
14.1%
Close Punctuation
ValueCountFrequency (%)
) 79
85.9%
] 13
 
14.1%
Space Separator
ValueCountFrequency (%)
379
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
" 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6023
85.3%
Common 990
 
14.0%
Latin 44
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 623
 
10.3%
소 620
 
10.3%
발 611
 
10.1%
양 602
 
10.0%
광 588
 
9.8%
태 581
 
9.6%
호 174
 
2.9%
화 100
 
1.7%
지 83
 
1.4%
봉 74
 
1.2%
Other values (284) 1967
32.7%
Common
ValueCountFrequency (%)
379
38.3%
2 123
 
12.4%
1 107
 
10.8%
( 79
 
8.0%
) 79
 
8.0%
3 58
 
5.9%
4 25
 
2.5%
5 24
 
2.4%
0 23
 
2.3%
7 20
 
2.0%
Other values (7) 73
 
7.4%
Latin
ValueCountFrequency (%)
C 9
20.5%
S 8
18.2%
B 6
13.6%
K 5
11.4%
F 4
9.1%
P 4
9.1%
L 2
 
4.5%
M 2
 
4.5%
H 2
 
4.5%
Y 2
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6000
85.0%
ASCII 1034
 
14.7%
None 23
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 623
 
10.4%
소 620
 
10.3%
발 611
 
10.2%
양 602
 
10.0%
광 588
 
9.8%
태 581
 
9.7%
호 174
 
2.9%
화 100
 
1.7%
지 83
 
1.4%
봉 74
 
1.2%
Other values (283) 1944
32.4%
ASCII
ValueCountFrequency (%)
379
36.7%
2 123
 
11.9%
1 107
 
10.3%
( 79
 
7.6%
) 79
 
7.6%
3 58
 
5.6%
4 25
 
2.4%
5 24
 
2.3%
0 23
 
2.2%
7 20
 
1.9%
Other values (17) 117
 
11.3%
None
ValueCountFrequency (%)
㈜ 23
100.0%

설비용량
Real number (ℝ)

MISSING 

Distinct226
Distinct (%)33.4%
Missing799
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean193.9084
Minimum9.96
Maximum1422.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2024-04-21T10:04:26.484366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.96
5-th percentile30
Q198.56
median99.36
Q399.9
95-th percentile996.12
Maximum1422.51
Range1412.55
Interquartile range (IQR)1.34

Descriptive statistics

Standard deviation250.64761
Coefficient of variation (CV)1.2926083
Kurtosis5.2467795
Mean193.9084
Median Absolute Deviation (MAD)0.54
Skewness2.484366
Sum131275.99
Variance62824.222
MonotonicityNot monotonic
2024-04-21T10:04:26.594188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.9 62
 
4.2%
99.28 51
 
3.5%
99.0 38
 
2.6%
99.2 29
 
2.0%
99.45 26
 
1.8%
99.36 25
 
1.7%
99.6 18
 
1.2%
99.68 17
 
1.2%
99.18 16
 
1.1%
98.28 13
 
0.9%
Other values (216) 382
25.9%
(Missing) 799
54.1%
ValueCountFrequency (%)
9.96 1
0.1%
10.8 1
0.1%
13.64 1
0.1%
14.62 1
0.1%
15.47 1
0.1%
16.66 1
0.1%
17.0 1
0.1%
18.0 1
0.1%
18.72 1
0.1%
19.14 1
0.1%
ValueCountFrequency (%)
1422.51 1
 
0.1%
1300.0 1
 
0.1%
1000.0 10
0.7%
999.6 3
 
0.2%
999.0 1
 
0.1%
998.82 4
 
0.3%
998.73 1
 
0.1%
998.64 5
0.3%
998.4 3
 
0.2%
998.13 1
 
0.1%

설치장소
Text

MISSING 

Distinct527
Distinct (%)77.8%
Missing799
Missing (%)54.1%
Memory size11.7 KiB
2024-04-21T10:04:26.859427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length54
Mean length26.376662
Min length18

Characters and Unicode

Total characters17857
Distinct characters149
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique456 ?
Unique (%)67.4%

Sample

1st row경상북도 봉화군 재산면 상리 402-8
2nd row경상북도 봉화군 봉화읍 건정길 24
3rd row경상북도 봉화군 법전면 어지리 338-1, 336-1
4th row경상북도 봉화군 봉화읍 내성리 232-10, 232-22, 232-33, 232-48
5th row경상북도 봉화군 봉성면 금봉리 571-20
ValueCountFrequency (%)
경상북도 677
 
16.6%
봉화군 677
 
16.6%
봉화읍 178
 
4.4%
1호 106
 
2.6%
물야면 102
 
2.5%
산 101
 
2.5%
법전면 98
 
2.4%
봉성면 90
 
2.2%
명호면 69
 
1.7%
화천리 52
 
1.3%
Other values (781) 1925
47.2%
2024-04-21T10:04:27.250235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3400
19.0%
봉 992
 
5.6%
화 910
 
5.1%
1 851
 
4.8%
도 722
 
4.0%
상 719
 
4.0%
북 687
 
3.8%
경 678
 
3.8%
군 677
 
3.8%
리 632
 
3.5%
Other values (139) 7589
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10196
57.1%
Decimal Number 3476
 
19.5%
Space Separator 3400
 
19.0%
Other Punctuation 324
 
1.8%
Dash Punctuation 321
 
1.8%
Close Punctuation 70
 
0.4%
Open Punctuation 70
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 992
 
9.7%
화 910
 
8.9%
도 722
 
7.1%
상 719
 
7.1%
북 687
 
6.7%
경 678
 
6.6%
군 677
 
6.6%
리 632
 
6.2%
면 506
 
5.0%
지 425
 
4.2%
Other values (121) 3248
31.9%
Decimal Number
ValueCountFrequency (%)
1 851
24.5%
2 390
11.2%
7 326
 
9.4%
3 326
 
9.4%
4 318
 
9.1%
5 313
 
9.0%
6 251
 
7.2%
0 235
 
6.8%
9 235
 
6.8%
8 231
 
6.6%
Other Punctuation
ValueCountFrequency (%)
, 323
99.7%
* 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 69
98.6%
] 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 69
98.6%
[ 1
 
1.4%
Space Separator
ValueCountFrequency (%)
3400
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10196
57.1%
Common 7661
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 992
 
9.7%
화 910
 
8.9%
도 722
 
7.1%
상 719
 
7.1%
북 687
 
6.7%
경 678
 
6.6%
군 677
 
6.6%
리 632
 
6.2%
면 506
 
5.0%
지 425
 
4.2%
Other values (121) 3248
31.9%
Common
ValueCountFrequency (%)
3400
44.4%
1 851
 
11.1%
2 390
 
5.1%
7 326
 
4.3%
3 326
 
4.3%
, 323
 
4.2%
- 321
 
4.2%
4 318
 
4.2%
5 313
 
4.1%
6 251
 
3.3%
Other values (8) 842
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10196
57.1%
ASCII 7661
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3400
44.4%
1 851
 
11.1%
2 390
 
5.1%
7 326
 
4.3%
3 326
 
4.3%
, 323
 
4.2%
- 321
 
4.2%
4 318
 
4.2%
5 313
 
4.1%
6 251
 
3.3%
Other values (8) 842
 
11.0%
Hangul
ValueCountFrequency (%)
봉 992
 
9.7%
화 910
 
8.9%
도 722
 
7.1%
상 719
 
7.1%
북 687
 
6.7%
경 678
 
6.6%
군 677
 
6.6%
리 632
 
6.2%
면 506
 
5.0%
지 425
 
4.2%
Other values (121) 3248
31.9%

허가일자
Date

MISSING 

Distinct235
Distinct (%)34.7%
Missing799
Missing (%)54.1%
Memory size11.7 KiB
Minimum2007-05-01 00:00:00
Maximum2023-07-24 00:00:00
2024-04-21T10:04:27.387300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:04:27.520267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing807
Missing (%)54.7%
Memory size11.7 KiB
Minimum2024-02-29 00:00:00
Maximum2024-02-29 00:00:00
2024-04-21T10:04:27.608180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:04:27.685240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T10:04:25.385416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-21T10:04:25.487211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:04:25.561192image/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.
2024-04-21T10:04:25.649889image/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

발전소명설비용량설치장소허가일자데이터기준일자
0정순옥 태양광발전소14.62경상북도 봉화군 재산면 상리 402-82023-07-242024-02-29
1돌집 태양광발전소19.64경상북도 봉화군 봉화읍 건정길 242023-07-122024-02-29
2어지1리마을회관 태양광발전소18.0경상북도 봉화군 법전면 어지리 338-1, 336-12023-04-142024-02-29
3교동빌딩 태양광발전소19.72경상북도 봉화군 봉화읍 내성리 232-10, 232-22, 232-33, 232-482023-04-142024-02-29
4두현2태양광발전소16.66경상북도 봉화군 봉성면 금봉리 571-202023-03-302024-02-29
5선진 태양광발전소19.68경상북도 봉화군 봉화읍 예봉로 1710-2102023-02-242024-02-29
6국화 태양광발전소23.04경상북도 봉화군 재산면 명재로 619-52023-02-082024-02-29
7동양태양광발전소44.1경상북도 봉화군 봉화읍 해저리 613-1 (건물위)2022-10-052024-02-29
8투게더태양광발전소39.44경상북도 봉화군 봉화읍 내성리 364 (건물위)2022-10-052024-02-29
9서벽3리마을회관태양광발전소41.23경상북도 봉화군 춘양면 서벽리 1318-3 (건물위)2022-08-082024-02-29
발전소명설비용량설치장소허가일자데이터기준일자
1466<NA><NA><NA><NA><NA>
1467<NA><NA><NA><NA><NA>
1468<NA><NA><NA><NA><NA>
1469<NA><NA><NA><NA><NA>
1470<NA><NA><NA><NA><NA>
1471<NA><NA><NA><NA><NA>
1472<NA><NA><NA><NA><NA>
1473<NA><NA><NA><NA><NA>
1474<NA><NA><NA><NA><NA>
1475<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

발전소명설비용량설치장소허가일자데이터기준일자# duplicates
0<NA><NA><NA><NA><NA>799