Overview

Dataset statistics

Number of variables5
Number of observations323
Missing cells88
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.1 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description2023년 8월 기준 경상남도 소재 태양광 발전기를 보유한 전력거래소 회원사 현황입니다. * 발전기 미등록 회원사 제외
URLhttps://www.data.go.kr/data/15118330/fileData.do

Alerts

대표자명 has 44 (13.6%) missing valuesMissing
사업자번호 has 44 (13.6%) missing valuesMissing
연번 has unique valuesUnique
회원명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:16:15.827336
Analysis finished2023-12-12 21:16:16.581303
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162
Minimum1
Maximum323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-13T06:16:16.689736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.1
Q181.5
median162
Q3242.5
95-th percentile306.9
Maximum323
Range322
Interquartile range (IQR)161

Descriptive statistics

Standard deviation93.386294
Coefficient of variation (CV)0.57645861
Kurtosis-1.2
Mean162
Median Absolute Deviation (MAD)81
Skewness0
Sum52326
Variance8721
MonotonicityStrictly increasing
2023-12-13T06:16:16.856066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
204 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
215 1
 
0.3%
Other values (313) 313
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%
315 1
0.3%
314 1
0.3%

회원명
Text

UNIQUE 

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T06:16:17.162347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length9.9195046
Min length3

Characters and Unicode

Total characters3204
Distinct characters269
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique323 ?
Unique (%)100.0%

Sample

1st row한국수력원자력(주)
2nd row한국남동발전(주)
3rd row한국서부발전(주)
4th row한국남부발전(주)
5th row한국동서발전(주)
ValueCountFrequency (%)
주식회사 116
 
24.3%
유한회사 18
 
3.8%
태양광발전소 12
 
2.5%
주 2
 
0.4%
금아스틸 1
 
0.2%
케이솔라이호 1
 
0.2%
김해시민햇빛발전협동조합 1
 
0.2%
주식회사호산 1
 
0.2%
소호솔라에너지 1
 
0.2%
모다에너지 1
 
0.2%
Other values (323) 323
67.7%
2023-12-13T06:16:17.614731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 256
 
8.0%
사 160
 
5.0%
159
 
5.0%
회 152
 
4.7%
식 132
 
4.1%
( 122
 
3.8%
) 122
 
3.8%
광 113
 
3.5%
태 112
 
3.5%
양 108
 
3.4%
Other values (259) 1768
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2735
85.4%
Space Separator 159
 
5.0%
Open Punctuation 122
 
3.8%
Close Punctuation 122
 
3.8%
Decimal Number 53
 
1.7%
Uppercase Letter 12
 
0.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 256
 
9.4%
사 160
 
5.9%
회 152
 
5.6%
식 132
 
4.8%
광 113
 
4.1%
태 112
 
4.1%
양 108
 
3.9%
전 107
 
3.9%
발 105
 
3.8%
에 104
 
3.8%
Other values (239) 1386
50.7%
Decimal Number
ValueCountFrequency (%)
2 16
30.2%
1 13
24.5%
3 6
 
11.3%
0 5
 
9.4%
5 4
 
7.5%
4 4
 
7.5%
6 2
 
3.8%
8 2
 
3.8%
7 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
33.3%
G 2
16.7%
P 2
16.7%
K 1
 
8.3%
H 1
 
8.3%
E 1
 
8.3%
B 1
 
8.3%
Space Separator
ValueCountFrequency (%)
159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2735
85.4%
Common 457
 
14.3%
Latin 12
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 256
 
9.4%
사 160
 
5.9%
회 152
 
5.6%
식 132
 
4.8%
광 113
 
4.1%
태 112
 
4.1%
양 108
 
3.9%
전 107
 
3.9%
발 105
 
3.8%
에 104
 
3.8%
Other values (239) 1386
50.7%
Common
ValueCountFrequency (%)
159
34.8%
( 122
26.7%
) 122
26.7%
2 16
 
3.5%
1 13
 
2.8%
3 6
 
1.3%
0 5
 
1.1%
5 4
 
0.9%
4 4
 
0.9%
6 2
 
0.4%
Other values (3) 4
 
0.9%
Latin
ValueCountFrequency (%)
S 4
33.3%
G 2
16.7%
P 2
16.7%
K 1
 
8.3%
H 1
 
8.3%
E 1
 
8.3%
B 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2735
85.4%
ASCII 469
 
14.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 256
 
9.4%
사 160
 
5.9%
회 152
 
5.6%
식 132
 
4.8%
광 113
 
4.1%
태 112
 
4.1%
양 108
 
3.9%
전 107
 
3.9%
발 105
 
3.8%
에 104
 
3.8%
Other values (239) 1386
50.7%
ASCII
ValueCountFrequency (%)
159
33.9%
( 122
26.0%
) 122
26.0%
2 16
 
3.4%
1 13
 
2.8%
3 6
 
1.3%
0 5
 
1.1%
5 4
 
0.9%
4 4
 
0.9%
S 4
 
0.9%
Other values (10) 14
 
3.0%

법인(개인)여부
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
법인
279 
개인
44 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 279
86.4%
개인 44
 
13.6%

Length

2023-12-13T06:16:17.791674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:16:18.220994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 279
86.4%
개인 44
 
13.6%

대표자명
Text

MISSING 

Distinct251
Distinct (%)90.0%
Missing44
Missing (%)13.6%
Memory size2.7 KiB
2023-12-13T06:16:18.572753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.1218638
Min length2

Characters and Unicode

Total characters871
Distinct characters158
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)82.1%

Sample

1st row황주호
2nd row김회천
3rd row박형덕
4th row이승우
5th row김영문
ValueCountFrequency (%)
이대영 4
 
1.4%
권대용 4
 
1.4%
이대호 3
 
1.1%
전완수 3
 
1.1%
안병준 2
 
0.7%
송영순 2
 
0.7%
박정화 2
 
0.7%
이동년 2
 
0.7%
이성준 2
 
0.7%
서대호 2
 
0.7%
Other values (245) 258
90.8%
2023-12-13T06:16:19.129999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 60
 
6.9%
이 56
 
6.4%
정 31
 
3.6%
박 25
 
2.9%
영 24
 
2.8%
대 22
 
2.5%
성 20
 
2.3%
수 19
 
2.2%
종 17
 
2.0%
재 17
 
2.0%
Other values (148) 580
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 852
97.8%
Space Separator 12
 
1.4%
Other Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 60
 
7.0%
이 56
 
6.6%
정 31
 
3.6%
박 25
 
2.9%
영 24
 
2.8%
대 22
 
2.6%
성 20
 
2.3%
수 19
 
2.2%
종 17
 
2.0%
재 17
 
2.0%
Other values (146) 561
65.8%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 852
97.8%
Common 19
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 60
 
7.0%
이 56
 
6.6%
정 31
 
3.6%
박 25
 
2.9%
영 24
 
2.8%
대 22
 
2.6%
성 20
 
2.3%
수 19
 
2.2%
종 17
 
2.0%
재 17
 
2.0%
Other values (146) 561
65.8%
Common
ValueCountFrequency (%)
12
63.2%
, 7
36.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 852
97.8%
ASCII 19
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 60
 
7.0%
이 56
 
6.6%
정 31
 
3.6%
박 25
 
2.9%
영 24
 
2.8%
대 22
 
2.6%
성 20
 
2.3%
수 19
 
2.2%
종 17
 
2.0%
재 17
 
2.0%
Other values (146) 561
65.8%
ASCII
ValueCountFrequency (%)
12
63.2%
, 7
36.8%

사업자번호
Text

MISSING 

Distinct279
Distinct (%)100.0%
Missing44
Missing (%)13.6%
Memory size2.7 KiB
2023-12-13T06:16:19.449302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3348
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

Unique279 ?
Unique (%)100.0%

Sample

1st row120-86-18943
2nd row120-86-19151
3rd row120-86-19205
4th row120-86-19165
5th row120-86-19199
ValueCountFrequency (%)
116-81-71167 1
 
0.4%
609-81-51019 1
 
0.4%
685-87-00480 1
 
0.4%
650-88-00948 1
 
0.4%
779-86-00681 1
 
0.4%
475-81-00561 1
 
0.4%
498-88-00618 1
 
0.4%
808-81-01829 1
 
0.4%
525-86-01399 1
 
0.4%
387-81-02035 1
 
0.4%
Other values (269) 269
96.4%
2023-12-13T06:16:19.815847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 558
16.7%
8 505
15.1%
0 437
13.1%
1 427
12.8%
6 293
8.8%
2 208
 
6.2%
5 207
 
6.2%
7 200
 
6.0%
3 186
 
5.6%
9 166
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2790
83.3%
Dash Punctuation 558
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 505
18.1%
0 437
15.7%
1 427
15.3%
6 293
10.5%
2 208
7.5%
5 207
7.4%
7 200
 
7.2%
3 186
 
6.7%
9 166
 
5.9%
4 161
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 558
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 558
16.7%
8 505
15.1%
0 437
13.1%
1 427
12.8%
6 293
8.8%
2 208
 
6.2%
5 207
 
6.2%
7 200
 
6.0%
3 186
 
5.6%
9 166
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 558
16.7%
8 505
15.1%
0 437
13.1%
1 427
12.8%
6 293
8.8%
2 208
 
6.2%
5 207
 
6.2%
7 200
 
6.0%
3 186
 
5.6%
9 166
 
5.0%

Interactions

2023-12-13T06:16:16.173879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:16:19.922133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법인(개인)여부
연번1.0000.255
법인(개인)여부0.2551.000
2023-12-13T06:16:20.002246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법인(개인)여부
연번1.0000.193
법인(개인)여부0.1931.000

Missing values

2023-12-13T06:16:16.311033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:16:16.424142image/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.
2023-12-13T06:16:16.514129image/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

연번회원명법인(개인)여부대표자명사업자번호
01한국수력원자력(주)법인황주호120-86-18943
12한국남동발전(주)법인김회천120-86-19151
23한국서부발전(주)법인박형덕120-86-19205
34한국남부발전(주)법인이승우120-86-19165
45한국동서발전(주)법인김영문120-86-19199
56지에스파워(주)법인조효제123-81-57770
67GS EPS(주)법인정찬수311-81-08518
78한국수자원공사법인윤석대306-82-00471
89에스케이이엔에스(주)법인추형욱116-81-71167
910한국농어촌공사법인이양희407-82-05070
연번회원명법인(개인)여부대표자명사업자번호
313314도개리태양광발전소개인<NA><NA>
314315주식회사 상상11호법인박상근240-86-02371
315316대경8호태양광발전소개인<NA><NA>
316317주식회사 대경이피법인정영이261-88-00995
317318(주)에이치케이에스법인김국주889-86-00955
318319김해시상하수도사업소법인강삼성615-83-04117
319320주식회사 궁류태양광발전소법인김정혜812-88-00570
320321유한회사 한울에너지5호법인장영화804-87-01907
321322에코시스템개인<NA><NA>
322323주식회사 진영에이치앤에스법인김영규609-81-89169