Overview

Dataset statistics

Number of variables11
Number of observations1923
Missing cells718
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory167.3 KiB
Average record size in memory89.1 B

Variable types

Numeric1
Categorical4
Text5
Boolean1

Dataset

Description2023년도 9월 신재생에너지 보급현황입니다.광주광역시의 신재생에너지 보급현황에 대한 정보로 에너지원 종류, 발전소명, 발전소 위치, 용량, 허가일자, 사업개시 여부 등의 항목을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15054767/fileData.do

Alerts

시도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 시군구High correlation
시군구 is highly overall correlated with 연번High correlation
원동력종류 is highly imbalanced (97.7%)Imbalance
사업개시여부 is highly imbalanced (76.0%)Imbalance
사업개시일자 has 386 (20.1%) missing valuesMissing
사업개시여부 has 331 (17.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-06 12:45:12.660744
Analysis finished2024-01-06 12:45:15.645485
Duration2.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1923
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean962
Minimum1
Maximum1923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.0 KiB
2024-01-06T12:45:15.874895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile97.1
Q1481.5
median962
Q31442.5
95-th percentile1826.9
Maximum1923
Range1922
Interquartile range (IQR)961

Descriptive statistics

Standard deviation555.2666
Coefficient of variation (CV)0.57720021
Kurtosis-1.2
Mean962
Median Absolute Deviation (MAD)481
Skewness0
Sum1849926
Variance308321
MonotonicityStrictly increasing
2024-01-06T12:45:16.427610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1204 1
 
0.1%
1292 1
 
0.1%
1291 1
 
0.1%
1290 1
 
0.1%
1289 1
 
0.1%
1288 1
 
0.1%
1287 1
 
0.1%
1286 1
 
0.1%
1285 1
 
0.1%
Other values (1913) 1913
99.5%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1923 1
0.1%
1922 1
0.1%
1921 1
0.1%
1920 1
0.1%
1919 1
0.1%
1918 1
0.1%
1917 1
0.1%
1916 1
0.1%
1915 1
0.1%
1914 1
0.1%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
광주광역시
1923 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시 1923
100.0%

Length

2024-01-06T12:45:16.852092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:45:17.162991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 1923
100.0%

시군구
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
광산구
1270 
북구
380 
서구
177 
남구
 
67
동구
 
29

Length

Max length3
Median length3
Mean length2.6604264
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광산구 1270
66.0%
북구 380
 
19.8%
서구 177
 
9.2%
남구 67
 
3.5%
동구 29
 
1.5%

Length

2024-01-06T12:45:17.550349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:45:17.872562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광산구 1270
66.0%
북구 380
 
19.8%
서구 177
 
9.2%
남구 67
 
3.5%
동구 29
 
1.5%

원동력종류
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
태양광
1912 
연료전지
 
4
소수력
 
3
기력발전
 
1
매립가스(LFG)
 
1
Other values (2)
 
2

Length

Max length17
Median length3
Mean length3.0161206
Min length3

Unique

Unique4 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
태양광 1912
99.4%
연료전지 4
 
0.2%
소수력 3
 
0.2%
기력발전 1
 
0.1%
매립가스(LFG) 1
 
0.1%
실증사업(ESS) 1
 
0.1%
가스터빈(수전해수소가스엔진발전) 1
 
0.1%

Length

2024-01-06T12:45:18.256203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:45:18.646537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태양광 1912
99.4%
연료전지 4
 
0.2%
소수력 3
 
0.2%
기력발전 1
 
0.1%
매립가스(lfg 1
 
0.1%
실증사업(ess 1
 
0.1%
가스터빈(수전해수소가스엔진발전 1
 
0.1%

발전소명
Text

Distinct1861
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2024-01-06T12:45:19.284458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length10.171087
Min length2

Characters and Unicode

Total characters19559
Distinct characters484
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1803 ?
Unique (%)93.8%

Sample

1st row새한병원
2nd row문빈정사태양광발전
3rd row우당 태양광발전소
4th row빛고을햇빛 태양광발전 2호
5th row빛고을햇빛 태양광발전 3호
ValueCountFrequency (%)
태양광발전소 519
 
20.2%
발전소 10
 
0.4%
주식회사 8
 
0.3%
햇빛발전소 7
 
0.3%
진곡산단 7
 
0.3%
주차장 6
 
0.2%
전자공고 6
 
0.2%
빛고을햇빛 6
 
0.2%
1호기 5
 
0.2%
2호 5
 
0.2%
Other values (1879) 1992
77.5%
2024-01-06T12:45:20.447743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 1918
 
9.8%
전 1848
 
9.4%
태 1822
 
9.3%
양 1816
 
9.3%
소 1814
 
9.3%
발 1814
 
9.3%
649
 
3.3%
호 397
 
2.0%
이 262
 
1.3%
에 223
 
1.1%
Other values (474) 6996
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17867
91.3%
Space Separator 649
 
3.3%
Decimal Number 551
 
2.8%
Uppercase Letter 190
 
1.0%
Other Symbol 147
 
0.8%
Open Punctuation 43
 
0.2%
Close Punctuation 43
 
0.2%
Lowercase Letter 32
 
0.2%
Dash Punctuation 26
 
0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 1918
 
10.7%
전 1848
 
10.3%
태 1822
 
10.2%
양 1816
 
10.2%
소 1814
 
10.2%
발 1814
 
10.2%
호 397
 
2.2%
이 262
 
1.5%
에 223
 
1.2%
지 189
 
1.1%
Other values (425) 5764
32.3%
Uppercase Letter
ValueCountFrequency (%)
S 21
11.1%
C 17
8.9%
E 16
8.4%
G 16
8.4%
N 15
 
7.9%
J 15
 
7.9%
M 15
 
7.9%
K 14
 
7.4%
H 12
 
6.3%
T 10
 
5.3%
Other values (11) 39
20.5%
Decimal Number
ValueCountFrequency (%)
2 200
36.3%
1 185
33.6%
3 69
 
12.5%
4 42
 
7.6%
5 25
 
4.5%
6 9
 
1.6%
0 8
 
1.5%
7 7
 
1.3%
9 5
 
0.9%
8 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
o 7
21.9%
k 4
12.5%
c 4
12.5%
p 4
12.5%
e 4
12.5%
r 3
9.4%
a 3
9.4%
l 3
9.4%
Other Punctuation
ValueCountFrequency (%)
. 3
42.9%
& 2
28.6%
? 1
 
14.3%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
649
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18014
92.1%
Common 1323
 
6.8%
Latin 222
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 1918
 
10.6%
전 1848
 
10.3%
태 1822
 
10.1%
양 1816
 
10.1%
소 1814
 
10.1%
발 1814
 
10.1%
호 397
 
2.2%
이 262
 
1.5%
에 223
 
1.2%
지 189
 
1.0%
Other values (426) 5911
32.8%
Latin
ValueCountFrequency (%)
S 21
 
9.5%
C 17
 
7.7%
E 16
 
7.2%
G 16
 
7.2%
N 15
 
6.8%
J 15
 
6.8%
M 15
 
6.8%
K 14
 
6.3%
H 12
 
5.4%
T 10
 
4.5%
Other values (19) 71
32.0%
Common
ValueCountFrequency (%)
649
49.1%
2 200
 
15.1%
1 185
 
14.0%
3 69
 
5.2%
( 43
 
3.3%
) 43
 
3.3%
4 42
 
3.2%
- 26
 
2.0%
5 25
 
1.9%
6 9
 
0.7%
Other values (9) 32
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17867
91.3%
ASCII 1545
 
7.9%
None 147
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 1918
 
10.7%
전 1848
 
10.3%
태 1822
 
10.2%
양 1816
 
10.2%
소 1814
 
10.2%
발 1814
 
10.2%
호 397
 
2.2%
이 262
 
1.5%
에 223
 
1.2%
지 189
 
1.1%
Other values (425) 5764
32.3%
ASCII
ValueCountFrequency (%)
649
42.0%
2 200
 
12.9%
1 185
 
12.0%
3 69
 
4.5%
( 43
 
2.8%
) 43
 
2.8%
4 42
 
2.7%
- 26
 
1.7%
5 25
 
1.6%
S 21
 
1.4%
Other values (38) 242
 
15.7%
None
ValueCountFrequency (%)
㈜ 147
100.0%

발전소위치
Text

Distinct1735
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2024-01-06T12:45:21.073140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length188
Median length62
Mean length21.764951
Min length9

Characters and Unicode

Total characters41854
Distinct characters242
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1611 ?
Unique (%)83.8%

Sample

1st row광주광역시 동구 학동 44-18
2nd row광주광역시 동구 운림동 96
3rd row광주광역시 동구 선교동 227-5
4th row광주광역시 동구 용연동 591
5th row광주광역시 동구 소태동 470
ValueCountFrequency (%)
광주광역시 1747
21.4%
광산구 1273
 
15.6%
북구 381
 
4.7%
서구 179
 
2.2%
남구 67
 
0.8%
상부 47
 
0.6%
평동산단7번로 43
 
0.5%
43
 
0.5%
평동산단로 36
 
0.4%
평동로803번길 35
 
0.4%
Other values (2032) 4326
52.9%
2024-01-06T12:45:22.309922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6273
 
15.0%
광 4775
 
11.4%
산 1958
 
4.7%
구 1934
 
4.6%
주 1836
 
4.4%
1 1753
 
4.2%
시 1749
 
4.2%
역 1747
 
4.2%
로 1523
 
3.6%
2 1180
 
2.8%
Other values (232) 17126
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24927
59.6%
Decimal Number 8529
 
20.4%
Space Separator 6273
 
15.0%
Dash Punctuation 945
 
2.3%
Other Punctuation 450
 
1.1%
Open Punctuation 323
 
0.8%
Close Punctuation 322
 
0.8%
Uppercase Letter 73
 
0.2%
Control 8
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 4775
19.2%
산 1958
 
7.9%
구 1934
 
7.8%
주 1836
 
7.4%
시 1749
 
7.0%
역 1747
 
7.0%
로 1523
 
6.1%
동 1070
 
4.3%
번 935
 
3.8%
단 724
 
2.9%
Other values (203) 6676
26.8%
Decimal Number
ValueCountFrequency (%)
1 1753
20.6%
2 1180
13.8%
3 1014
11.9%
5 759
8.9%
4 686
 
8.0%
6 685
 
8.0%
7 651
 
7.6%
8 628
 
7.4%
0 599
 
7.0%
9 574
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
A 29
39.7%
B 22
30.1%
C 13
17.8%
D 5
 
6.8%
E 2
 
2.7%
K 1
 
1.4%
H 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 357
79.3%
/ 92
 
20.4%
: 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 321
99.4%
[ 2
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 320
99.4%
] 2
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
6273
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 945
100.0%
Control
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24927
59.6%
Common 16854
40.3%
Latin 73
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 4775
19.2%
산 1958
 
7.9%
구 1934
 
7.8%
주 1836
 
7.4%
시 1749
 
7.0%
역 1747
 
7.0%
로 1523
 
6.1%
동 1070
 
4.3%
번 935
 
3.8%
단 724
 
2.9%
Other values (203) 6676
26.8%
Common
ValueCountFrequency (%)
6273
37.2%
1 1753
 
10.4%
2 1180
 
7.0%
3 1014
 
6.0%
- 945
 
5.6%
5 759
 
4.5%
4 686
 
4.1%
6 685
 
4.1%
7 651
 
3.9%
8 628
 
3.7%
Other values (12) 2280
 
13.5%
Latin
ValueCountFrequency (%)
A 29
39.7%
B 22
30.1%
C 13
17.8%
D 5
 
6.8%
E 2
 
2.7%
K 1
 
1.4%
H 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24927
59.6%
ASCII 16927
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6273
37.1%
1 1753
 
10.4%
2 1180
 
7.0%
3 1014
 
6.0%
- 945
 
5.6%
5 759
 
4.5%
4 686
 
4.1%
6 685
 
4.0%
7 651
 
3.8%
8 628
 
3.7%
Other values (19) 2353
 
13.9%
Hangul
ValueCountFrequency (%)
광 4775
19.2%
산 1958
 
7.9%
구 1934
 
7.8%
주 1836
 
7.4%
시 1749
 
7.0%
역 1747
 
7.0%
로 1523
 
6.1%
동 1070
 
4.3%
번 935
 
3.8%
단 724
 
2.9%
Other values (203) 6676
26.8%

용량(kW)
Text

Distinct1104
Distinct (%)57.4%
Missing1
Missing (%)0.1%
Memory size15.2 KiB
2024-01-06T12:45:24.508954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.5983351
Min length1

Characters and Unicode

Total characters8838
Distinct characters12
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

Unique838 ?
Unique (%)43.6%

Sample

1st row10
2nd row8.28
3rd row98
4th row999
5th row265
ValueCountFrequency (%)
99 79
 
4.1%
99.96 29
 
1.5%
97.92 25
 
1.3%
99.84 24
 
1.2%
99.18 20
 
1.0%
97.2 16
 
0.8%
99.2 15
 
0.8%
99.9 14
 
0.7%
99.36 14
 
0.7%
29.25 13
 
0.7%
Other values (1094) 1673
87.0%
2024-01-06T12:45:26.230808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1676
19.0%
. 1575
17.8%
2 866
9.8%
4 733
8.3%
1 725
8.2%
5 702
7.9%
8 663
 
7.5%
6 600
 
6.8%
7 454
 
5.1%
3 435
 
4.9%
Other values (2) 409
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7247
82.0%
Other Punctuation 1591
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 1676
23.1%
2 866
11.9%
4 733
10.1%
1 725
10.0%
5 702
9.7%
8 663
 
9.1%
6 600
 
8.3%
7 454
 
6.3%
3 435
 
6.0%
0 393
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 1575
99.0%
, 16
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8838
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 1676
19.0%
. 1575
17.8%
2 866
9.8%
4 733
8.3%
1 725
8.2%
5 702
7.9%
8 663
 
7.5%
6 600
 
6.8%
7 454
 
5.1%
3 435
 
4.9%
Other values (2) 409
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 1676
19.0%
. 1575
17.8%
2 866
9.8%
4 733
8.3%
1 725
8.2%
5 702
7.9%
8 663
 
7.5%
6 600
 
6.8%
7 454
 
5.1%
3 435
 
4.9%
Other values (2) 409
 
4.6%

허가일자
Text

Distinct935
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2024-01-06T12:45:27.232329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length11
Mean length10.777431
Min length8

Characters and Unicode

Total characters20725
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique487 ?
Unique (%)25.3%

Sample

1st row2006-06-01
2nd row2011-01-13
3rd row2011-10-27
4th row2014-05-01
5th row2014-05-01
ValueCountFrequency (%)
2022.04.27 21
 
1.1%
2022.04.06 11
 
0.6%
2018.07.16 10
 
0.5%
2023.03.21 10
 
0.5%
2023.08.11 9
 
0.5%
2023.06.27 9
 
0.5%
2014.09.02 9
 
0.5%
2017.09.04 8
 
0.4%
2018.06.21 8
 
0.4%
2020.08.11 8
 
0.4%
Other values (912) 1821
94.6%
2024-01-06T12:45:28.917372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4798
23.2%
0 4491
21.7%
2 4245
20.5%
1 2819
13.6%
3 742
 
3.6%
8 602
 
2.9%
7 555
 
2.7%
- 546
 
2.6%
4 541
 
2.6%
9 522
 
2.5%
Other values (6) 864
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15377
74.2%
Other Punctuation 4799
 
23.2%
Dash Punctuation 546
 
2.6%
Control 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4491
29.2%
2 4245
27.6%
1 2819
18.3%
3 742
 
4.8%
8 602
 
3.9%
7 555
 
3.6%
4 541
 
3.5%
9 522
 
3.4%
6 441
 
2.9%
5 419
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 4798
> 99.9%
? 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 546
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20725
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4798
23.2%
0 4491
21.7%
2 4245
20.5%
1 2819
13.6%
3 742
 
3.6%
8 602
 
2.9%
7 555
 
2.7%
- 546
 
2.6%
4 541
 
2.6%
9 522
 
2.5%
Other values (6) 864
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20725
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4798
23.2%
0 4491
21.7%
2 4245
20.5%
1 2819
13.6%
3 742
 
3.6%
8 602
 
2.9%
7 555
 
2.7%
- 546
 
2.6%
4 541
 
2.6%
9 522
 
2.5%
Other values (6) 864
 
4.2%

사업개시일자
Text

MISSING 

Distinct1067
Distinct (%)69.4%
Missing386
Missing (%)20.1%
Memory size15.2 KiB
2024-01-06T12:45:29.847179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length11
Mean length10.73715
Min length1

Characters and Unicode

Total characters16503
Distinct characters19
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique776 ?
Unique (%)50.5%

Sample

1st row2008-06-31
2nd row2011-04-21
3rd row2014-10-26
4th row2015-02-02
5th row2014-12-18
ValueCountFrequency (%)
2020.01.15 9
 
0.6%
9
 
0.6%
2021.10.27 7
 
0.5%
2022.09.30 7
 
0.5%
2021.01.17 7
 
0.5%
2021.12.30 6
 
0.4%
2022.11.01 6
 
0.4%
2014.10.30 6
 
0.4%
2023.04.19 6
 
0.4%
2014.12.15 5
 
0.3%
Other values (1053) 1478
95.6%
2024-01-06T12:45:31.070048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3788
23.0%
0 3436
20.8%
2 3300
20.0%
1 2493
15.1%
9 507
 
3.1%
- 507
 
3.1%
3 500
 
3.0%
4 462
 
2.8%
8 430
 
2.6%
7 402
 
2.4%
Other values (9) 678
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12190
73.9%
Other Punctuation 3788
 
23.0%
Dash Punctuation 507
 
3.1%
Space Separator 10
 
0.1%
Control 3
 
< 0.1%
Other Letter 3
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3436
28.2%
2 3300
27.1%
1 2493
20.5%
9 507
 
4.2%
3 500
 
4.1%
4 462
 
3.8%
8 430
 
3.5%
7 402
 
3.3%
5 362
 
3.0%
6 298
 
2.4%
Other Letter
ValueCountFrequency (%)
재 1
33.3%
공 1
33.3%
사 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 3788
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 507
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16500
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3788
23.0%
0 3436
20.8%
2 3300
20.0%
1 2493
15.1%
9 507
 
3.1%
- 507
 
3.1%
3 500
 
3.0%
4 462
 
2.8%
8 430
 
2.6%
7 402
 
2.4%
Other values (6) 675
 
4.1%
Hangul
ValueCountFrequency (%)
재 1
33.3%
공 1
33.3%
사 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16500
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3788
23.0%
0 3436
20.8%
2 3300
20.0%
1 2493
15.1%
9 507
 
3.1%
- 507
 
3.1%
3 500
 
3.0%
4 462
 
2.8%
8 430
 
2.6%
7 402
 
2.4%
Other values (6) 675
 
4.1%
Hangul
ValueCountFrequency (%)
재 1
33.3%
공 1
33.3%
사 1
33.3%

사업개시여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing331
Missing (%)17.2%
Memory size3.9 KiB
True
1529 
False
 
63
(Missing)
331 
ValueCountFrequency (%)
True 1529
79.5%
False 63
 
3.3%
(Missing) 331
 
17.2%
2024-01-06T12:45:31.490614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2023-09-21
1923 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-21
2nd row2023-09-21
3rd row2023-09-21
4th row2023-09-21
5th row2023-09-21

Common Values

ValueCountFrequency (%)
2023-09-21 1923
100.0%

Length

2024-01-06T12:45:32.006501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:45:32.324414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-21 1923
100.0%

Interactions

2024-01-06T12:45:14.118769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T12:45:32.511359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구원동력종류사업개시여부
연번1.0000.9550.0480.439
시군구0.9551.0000.1580.206
원동력종류0.0480.1581.0000.231
사업개시여부0.4390.2060.2311.000
2024-01-06T12:45:32.766290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구원동력종류사업개시여부
시군구1.0000.1010.252
원동력종류0.1011.0000.166
사업개시여부0.2520.1661.000
2024-01-06T12:45:33.087037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구원동력종류사업개시여부
연번1.0000.7070.0240.336
시군구0.7071.0000.1010.252
원동력종류0.0240.1011.0000.166
사업개시여부0.3360.2520.1661.000

Missing values

2024-01-06T12:45:14.543452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T12:45:15.130328image/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.
2024-01-06T12:45:15.490054image/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

연번시도시군구원동력종류발전소명발전소위치용량(kW)허가일자사업개시일자사업개시여부데이터기준일자
01광주광역시동구태양광새한병원광주광역시 동구 학동 44-18102006-06-012008-06-31Y2023-09-21
12광주광역시동구태양광문빈정사태양광발전광주광역시 동구 운림동 968.282011-01-132011-04-21Y2023-09-21
23광주광역시동구태양광우당 태양광발전소광주광역시 동구 선교동 227-5982011-10-272014-10-26Y2023-09-21
34광주광역시동구태양광빛고을햇빛 태양광발전 2호광주광역시 동구 용연동 5919992014-05-012015-02-02Y2023-09-21
45광주광역시동구태양광빛고을햇빛 태양광발전 3호광주광역시 동구 소태동 4702652014-05-012014-12-18Y2023-09-21
56광주광역시동구태양광빛고을햇빛 태양광발전 5호광주광역시 동구 산수동 113-7992014-05-012014-12-18Y2023-09-21
67광주광역시동구태양광우리미래3 태양광발전소광주광역시 동구 필문대로145번길 8152014-08-282016-07-25Y2023-09-21
78광주광역시동구태양광우리미래4 태양광발전소광주광역시 동구 필문대로145번길 10152014-08-282016-07-25Y2023-09-21
89광주광역시동구소수력용연 소수력발전소광주광역시 동구 용연동 572,576번지7602016-10-122016-11-10Y2023-09-21
910광주광역시동구태양광풍경채에너지 태양광발전소광주광역시 동구 동명로 25번길 1018.552016-11-282017-07-26Y2023-09-21
연번시도시군구원동력종류발전소명발전소위치용량(kW)허가일자사업개시일자사업개시여부데이터기준일자
19131914광주광역시광산구태양광테폴이현미태양광발전소광주광역시 광산구 풍영정길 39153.552023.08.22.<NA><NA>2023-09-21
19141915광주광역시광산구태양광테폴법인태양광발전소광주광역시 광산구 풍영정길 39199.3652023.08.22.<NA><NA>2023-09-21
19151916광주광역시광산구태양광희망2호태양광발전소광주광역시 광산구 평동산단7번로 92752023.08.22.<NA><NA>2023-09-21
19161917광주광역시광산구태양광코리아1호태양광발전소광주광역시 광산구 하남산단천변우로 126-499.962023.08.22.<NA><NA>2023-09-21
19171918광주광역시광산구태양광코리아2호태양광발전소광주광역시 광산구 하남산단천변우로 126-462.4752023.08.22.<NA><NA>2023-09-21
19181919광주광역시광산구태양광위너스 태양광발전소광주광역시 광산구 신가매결길 88-29 (신창동) 1, 2 동112.22023.08.28.<NA><NA>2023-09-21
19191920광주광역시광산구태양광지구별햇빛발전소1호광주광역시 광산구 하남산단8번로 17770.72023.08.29.<NA><NA>2023-09-21
19201921광주광역시광산구태양광지구별햇빛발전소2호광주광역시 광산구 하남산단8번로 17770.72023.08.29.<NA><NA>2023-09-21
19211922광주광역시광산구태양광지구별햇빛발전소3호광주광역시 광산구 하남산단8번로 17795.952023.08.29.<NA><NA>2023-09-21
19221923광주광역시광산구태양광지구별햇빛발전소4호광주광역시 광산구 하남산단8번로 17763.632023.08.29.<NA><NA>2023-09-21