Overview

Dataset statistics

Number of variables8
Number of observations589
Missing cells495
Missing cells (%)10.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.1 KiB
Average record size in memory66.2 B

Variable types

Numeric2
Text2
Categorical1
DateTime3

Dataset

Description2023년 4월 18일 기준, 경상남도 산청군 태양광발전허가정보입니다. (상호, 설치장소, 설비용량(kW), 허가일자, 사업개시일자 순 제공)
Author경상남도 산청군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15042031

Alerts

데이터기준일자 has constant value ""Constant
지목 is highly imbalanced (50.1%)Imbalance
사업개시 has 494 (83.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:18:54.807685
Analysis finished2023-12-11 00:18:55.865567
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct589
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295
Minimum1
Maximum589
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T09:18:55.933765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30.4
Q1148
median295
Q3442
95-th percentile559.6
Maximum589
Range588
Interquartile range (IQR)294

Descriptive statistics

Standard deviation170.17393
Coefficient of variation (CV)0.57686078
Kurtosis-1.2
Mean295
Median Absolute Deviation (MAD)147
Skewness0
Sum173755
Variance28959.167
MonotonicityStrictly increasing
2023-12-11T09:18:56.059654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
406 1
 
0.2%
390 1
 
0.2%
391 1
 
0.2%
392 1
 
0.2%
393 1
 
0.2%
394 1
 
0.2%
395 1
 
0.2%
396 1
 
0.2%
397 1
 
0.2%
Other values (579) 579
98.3%
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 (%)
589 1
0.2%
588 1
0.2%
587 1
0.2%
586 1
0.2%
585 1
0.2%
584 1
0.2%
583 1
0.2%
582 1
0.2%
581 1
0.2%
580 1
0.2%

상호
Text

Distinct564
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-11T09:18:56.322958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length10.485569
Min length3

Characters and Unicode

Total characters6176
Distinct characters258
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

Unique541 ?
Unique (%)91.9%

Sample

1st row특리솔라
2nd row시우전력일(주) 태양광발전소
3rd row덕수태양광발전소
4th row백광태양광발전소
5th row그린태양광발전소
ValueCountFrequency (%)
태양광발전소 112
 
14.5%
주식회사 30
 
3.9%
주)다한이엔지 5
 
0.6%
진주.산청지사 4
 
0.5%
한국농어촌공사 4
 
0.5%
청솔 3
 
0.4%
나무리태양광발전소 2
 
0.3%
누리태양광발전소 2
 
0.3%
차탄태양광발전소 2
 
0.3%
관정태양광발전소 2
 
0.3%
Other values (578) 605
78.5%
2023-12-11T09:18:56.814409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 591
 
9.6%
양 577
 
9.3%
광 572
 
9.3%
소 567
 
9.2%
발 566
 
9.2%
태 549
 
8.9%
호 191
 
3.1%
183
 
3.0%
1 123
 
2.0%
2 88
 
1.4%
Other values (248) 2169
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5527
89.5%
Decimal Number 364
 
5.9%
Space Separator 183
 
3.0%
Close Punctuation 48
 
0.8%
Open Punctuation 48
 
0.8%
Other Punctuation 4
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 591
 
10.7%
양 577
 
10.4%
광 572
 
10.3%
소 567
 
10.3%
발 566
 
10.2%
태 549
 
9.9%
호 191
 
3.5%
주 76
 
1.4%
산 62
 
1.1%
지 62
 
1.1%
Other values (233) 1714
31.0%
Decimal Number
ValueCountFrequency (%)
1 123
33.8%
2 88
24.2%
3 44
 
12.1%
0 32
 
8.8%
4 21
 
5.8%
5 19
 
5.2%
6 17
 
4.7%
7 9
 
2.5%
8 6
 
1.6%
9 5
 
1.4%
Space Separator
ValueCountFrequency (%)
183
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5527
89.5%
Common 649
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 591
 
10.7%
양 577
 
10.4%
광 572
 
10.3%
소 567
 
10.3%
발 566
 
10.2%
태 549
 
9.9%
호 191
 
3.5%
주 76
 
1.4%
산 62
 
1.1%
지 62
 
1.1%
Other values (233) 1714
31.0%
Common
ValueCountFrequency (%)
183
28.2%
1 123
19.0%
2 88
13.6%
) 48
 
7.4%
( 48
 
7.4%
3 44
 
6.8%
0 32
 
4.9%
4 21
 
3.2%
5 19
 
2.9%
6 17
 
2.6%
Other values (5) 26
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5527
89.5%
ASCII 649
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 591
 
10.7%
양 577
 
10.4%
광 572
 
10.3%
소 567
 
10.3%
발 566
 
10.2%
태 549
 
9.9%
호 191
 
3.5%
주 76
 
1.4%
산 62
 
1.1%
지 62
 
1.1%
Other values (233) 1714
31.0%
ASCII
ValueCountFrequency (%)
183
28.2%
1 123
19.0%
2 88
13.6%
) 48
 
7.4%
( 48
 
7.4%
3 44
 
6.8%
0 32
 
4.9%
4 21
 
3.2%
5 19
 
2.9%
6 17
 
2.6%
Other values (5) 26
 
4.0%

설비용량(kW)
Real number (ℝ)

Distinct232
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean362.4807
Minimum8.1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T09:18:57.009870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.1
5-th percentile29.324
Q198.28
median100
Q3499.64
95-th percentile999.192
Maximum1000
Range991.9
Interquartile range (IQR)401.36

Descriptive statistics

Standard deviation371.63087
Coefficient of variation (CV)1.0252432
Kurtosis-0.86258138
Mean362.4807
Median Absolute Deviation (MAD)81.4
Skewness0.92971831
Sum213501.13
Variance138109.5
MonotonicityNot monotonic
2023-12-11T09:18:57.154030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 48
 
8.1%
97.2 30
 
5.1%
99.9 18
 
3.1%
99.96 17
 
2.9%
997.56 17
 
2.9%
992.0 15
 
2.5%
97.92 13
 
2.2%
999.75 13
 
2.2%
997.92 12
 
2.0%
995.52 11
 
1.9%
Other values (222) 395
67.1%
ValueCountFrequency (%)
8.1 1
0.2%
10.08 2
0.3%
11.03 1
0.2%
12.0 1
0.2%
12.96 1
0.2%
13.0 2
0.3%
13.5 1
0.2%
15.3 1
0.2%
16.38 1
0.2%
16.56 1
0.2%
ValueCountFrequency (%)
1000.0 4
 
0.7%
999.96 2
 
0.3%
999.85 1
 
0.2%
999.8 6
1.0%
999.75 13
2.2%
999.72 1
 
0.2%
999.6 1
 
0.2%
999.24 2
 
0.3%
999.12 1
 
0.2%
999.0 4
 
0.7%

설치장소
Text

Distinct383
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-11T09:18:57.489269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length64
Mean length25.404075
Min length10

Characters and Unicode

Total characters14963
Distinct characters149
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

Unique298 ?
Unique (%)50.6%

Sample

1st row경상남도 산청군 금서면 특리 36-9
2nd row경상남도 산청군 차황면 상법리 산 108번지
3rd row경상남도 산청군 시천면 원리 산 92-5
4th row경상남도 산청군 생초면 하촌리 142-4, 153-1
5th row경상남도 산청군 생초면 상촌리 153
ValueCountFrequency (%)
산청군 563
 
16.5%
경상남도 482
 
14.1%
산 137
 
4.0%
단성면 132
 
3.9%
신안면 76
 
2.2%
산청읍 68
 
2.0%
금서면 67
 
2.0%
신등면 60
 
1.8%
오부면 49
 
1.4%
차황면 48
 
1.4%
Other values (628) 1731
50.7%
2023-12-11T09:18:58.025668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2824
18.9%
산 1001
 
6.7%
1 772
 
5.2%
청 645
 
4.3%
리 571
 
3.8%
군 570
 
3.8%
면 521
 
3.5%
도 495
 
3.3%
상 494
 
3.3%
남 491
 
3.3%
Other values (139) 6579
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8153
54.5%
Decimal Number 3200
 
21.4%
Space Separator 2824
 
18.9%
Dash Punctuation 450
 
3.0%
Other Punctuation 329
 
2.2%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 1001
 
12.3%
청 645
 
7.9%
리 571
 
7.0%
군 570
 
7.0%
면 521
 
6.4%
도 495
 
6.1%
상 494
 
6.1%
남 491
 
6.0%
경 485
 
5.9%
지 265
 
3.3%
Other values (123) 2615
32.1%
Decimal Number
ValueCountFrequency (%)
1 772
24.1%
2 418
13.1%
3 316
9.9%
0 281
 
8.8%
6 273
 
8.5%
4 247
 
7.7%
8 243
 
7.6%
7 229
 
7.2%
5 225
 
7.0%
9 196
 
6.1%
Space Separator
ValueCountFrequency (%)
2824
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 450
100.0%
Other Punctuation
ValueCountFrequency (%)
, 329
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8153
54.5%
Common 6809
45.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 1001
 
12.3%
청 645
 
7.9%
리 571
 
7.0%
군 570
 
7.0%
면 521
 
6.4%
도 495
 
6.1%
상 494
 
6.1%
남 491
 
6.0%
경 485
 
5.9%
지 265
 
3.3%
Other values (123) 2615
32.1%
Common
ValueCountFrequency (%)
2824
41.5%
1 772
 
11.3%
- 450
 
6.6%
2 418
 
6.1%
, 329
 
4.8%
3 316
 
4.6%
0 281
 
4.1%
6 273
 
4.0%
4 247
 
3.6%
8 243
 
3.6%
Other values (5) 656
 
9.6%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8153
54.5%
ASCII 6810
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2824
41.5%
1 772
 
11.3%
- 450
 
6.6%
2 418
 
6.1%
, 329
 
4.8%
3 316
 
4.6%
0 281
 
4.1%
6 273
 
4.0%
4 247
 
3.6%
8 243
 
3.6%
Other values (6) 657
 
9.6%
Hangul
ValueCountFrequency (%)
산 1001
 
12.3%
청 645
 
7.9%
리 571
 
7.0%
군 570
 
7.0%
면 521
 
6.4%
도 495
 
6.1%
상 494
 
6.1%
남 491
 
6.0%
경 485
 
5.9%
지 265
 
3.3%
Other values (123) 2615
32.1%

지목
Categorical

IMBALANCE 

Distinct35
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
임야
320 
답
107 
토지
35 
전
 
21
창고
 
14
Other values (30)
92 

Length

Max length9
Median length2
Mean length2.0135823
Min length1

Unique

Unique15 ?
Unique (%)2.5%

Sample

1st row전
2nd row임야
3rd row임야
4th row대
5th row대

Common Values

ValueCountFrequency (%)
임야 320
54.3%
답 107
 
18.2%
토지 35
 
5.9%
전 21
 
3.6%
창고 14
 
2.4%
과수원 11
 
1.9%
대지 11
 
1.9%
목장용지 10
 
1.7%
대 7
 
1.2%
건물 7
 
1.2%
Other values (25) 46
 
7.8%

Length

2023-12-11T09:18:58.211622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
임야 321
52.2%
답 123
 
20.0%
토지 35
 
5.7%
전 22
 
3.6%
창고 15
 
2.4%
건물위 14
 
2.3%
대지 12
 
2.0%
과수원 11
 
1.8%
목장용지 11
 
1.8%
토지위 10
 
1.6%
Other values (13) 41
 
6.7%

사업개시
Date

MISSING 

Distinct63
Distinct (%)66.3%
Missing494
Missing (%)83.9%
Memory size4.7 KiB
Minimum2013-09-03 00:00:00
Maximum2019-12-05 00:00:00
2023-12-11T09:18:58.385327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:18:58.555441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

허가일자
Date

Distinct147
Distinct (%)25.0%
Missing1
Missing (%)0.2%
Memory size4.7 KiB
Minimum2017-01-20 00:00:00
Maximum2019-10-18 00:00:00
2023-12-11T09:18:58.713076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:18:58.842547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
Minimum2019-12-13 00:00:00
Maximum2019-12-13 00:00:00
2023-12-11T09:18:58.945739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:18:59.038510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:18:55.402225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:18:55.191599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:18:55.485122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:18:55.327655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:18:59.103579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)지목사업개시
연번1.0000.3820.6060.991
설비용량(kW)0.3821.0000.2860.922
지목0.6060.2861.0000.919
사업개시0.9910.9220.9191.000
2023-12-11T09:18:59.184335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)지목
연번1.000-0.3080.256
설비용량(kW)-0.3081.0000.107
지목0.2560.1071.000

Missing values

2023-12-11T09:18:55.597299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:18:55.706769image/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.
2023-12-11T09:18:55.809022image/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

연번상호설비용량(kW)설치장소지목사업개시허가일자데이터기준일자
01특리솔라95.04경상남도 산청군 금서면 특리 36-9전2017-07-212017-01-202019-12-13
12시우전력일(주) 태양광발전소998.82경상남도 산청군 차황면 상법리 산 108번지임야<NA>2017-02-012019-12-13
23덕수태양광발전소201.0경상남도 산청군 시천면 원리 산 92-5임야<NA>2017-02-072019-12-13
34백광태양광발전소18.6경상남도 산청군 생초면 하촌리 142-4, 153-1대2017-03-162017-02-072019-12-13
45그린태양광발전소18.6경상남도 산청군 생초면 상촌리 153대2017-03-162017-02-072019-12-13
56늘푸른발전소132.3경상남도 산청군 산청읍 부리 291,286목장2018-08-102017-02-222019-12-13
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