Overview

Dataset statistics

Number of variables6
Number of observations1004
Missing cells181
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.2 KiB
Average record size in memory49.1 B

Variable types

Text2
Numeric1
DateTime2
Categorical1

Dataset

Description충청남도 공주시 신재생에너지 정보현황에 대한 데이터로 (설비용량,설치위치,허가일,사업개시일,데이터기준일)등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=385&beforeMenuCd=DOM_000000201001001000&publicdatapk=15033981

Alerts

데이터기준일 has constant value ""Constant
허가일 has 20 (2.0%) missing valuesMissing
사업개시일 has 160 (15.9%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:44:08.881421
Analysis finished2024-01-09 22:44:09.514679
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발전소명
Text

Distinct967
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-01-10T07:44:09.740159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length5.6972112
Min length1

Characters and Unicode

Total characters5720
Distinct characters361
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique937 ?
Unique (%)93.3%

Sample

1st row구당태양광발전소
2nd row만년태양광발전소
3rd row도천태양광발전소
4th row우성태양광발전소
5th row천일태양광발전소
ValueCountFrequency (%)
블루빌 21
 
1.9%
봉현리 13
 
1.2%
2호 11
 
1.0%
1호 8
 
0.7%
부엉이 7
 
0.6%
3호 7
 
0.6%
원동 6
 
0.5%
공주 6
 
0.5%
4호 5
 
0.5%
앤에이치팩토리 5
 
0.5%
Other values (938) 1016
91.9%
2024-01-10T07:44:10.187792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
태 369
 
6.5%
호 365
 
6.4%
양 350
 
6.1%
광 345
 
6.0%
전 344
 
6.0%
소 340
 
5.9%
발 334
 
5.8%
2 158
 
2.8%
1 122
 
2.1%
102
 
1.8%
Other values (351) 2891
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5119
89.5%
Decimal Number 433
 
7.6%
Space Separator 102
 
1.8%
Uppercase Letter 44
 
0.8%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Other Symbol 3
 
0.1%
Connector Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
태 369
 
7.2%
호 365
 
7.1%
양 350
 
6.8%
광 345
 
6.7%
전 344
 
6.7%
소 340
 
6.6%
발 334
 
6.5%
주 58
 
1.1%
이 57
 
1.1%
에 54
 
1.1%
Other values (315) 2503
48.9%
Uppercase Letter
ValueCountFrequency (%)
S 8
18.2%
K 3
 
6.8%
O 3
 
6.8%
E 3
 
6.8%
N 3
 
6.8%
J 3
 
6.8%
H 3
 
6.8%
W 2
 
4.5%
Y 2
 
4.5%
F 2
 
4.5%
Other values (9) 12
27.3%
Decimal Number
ValueCountFrequency (%)
2 158
36.5%
1 122
28.2%
3 67
15.5%
4 28
 
6.5%
5 22
 
5.1%
6 17
 
3.9%
7 7
 
1.6%
8 6
 
1.4%
9 4
 
0.9%
0 2
 
0.5%
Space Separator
ValueCountFrequency (%)
102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5122
89.5%
Common 554
 
9.7%
Latin 44
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
태 369
 
7.2%
호 365
 
7.1%
양 350
 
6.8%
광 345
 
6.7%
전 344
 
6.7%
소 340
 
6.6%
발 334
 
6.5%
주 58
 
1.1%
이 57
 
1.1%
에 54
 
1.1%
Other values (316) 2506
48.9%
Latin
ValueCountFrequency (%)
S 8
18.2%
K 3
 
6.8%
O 3
 
6.8%
E 3
 
6.8%
N 3
 
6.8%
J 3
 
6.8%
H 3
 
6.8%
W 2
 
4.5%
Y 2
 
4.5%
F 2
 
4.5%
Other values (9) 12
27.3%
Common
ValueCountFrequency (%)
2 158
28.5%
1 122
22.0%
102
18.4%
3 67
12.1%
4 28
 
5.1%
5 22
 
4.0%
6 17
 
3.1%
( 7
 
1.3%
) 7
 
1.3%
7 7
 
1.3%
Other values (6) 17
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5119
89.5%
ASCII 598
 
10.5%
None 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
태 369
 
7.2%
호 365
 
7.1%
양 350
 
6.8%
광 345
 
6.7%
전 344
 
6.7%
소 340
 
6.6%
발 334
 
6.5%
주 58
 
1.1%
이 57
 
1.1%
에 54
 
1.1%
Other values (315) 2503
48.9%
ASCII
ValueCountFrequency (%)
2 158
26.4%
1 122
20.4%
102
17.1%
3 67
11.2%
4 28
 
4.7%
5 22
 
3.7%
6 17
 
2.8%
S 8
 
1.3%
( 7
 
1.2%
) 7
 
1.2%
Other values (25) 60
 
10.0%
None
ValueCountFrequency (%)
㈜ 3
100.0%

설비용량(kW)
Real number (ℝ)

Distinct344
Distinct (%)34.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean106.53644
Minimum9.92
Maximum998.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:44:10.311121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.92
5-th percentile19.55
Q175.705
median99
Q399.6
95-th percentile289.1445
Maximum998.76
Range988.84
Interquartile range (IQR)23.895

Descriptive statistics

Standard deviation114.37533
Coefficient of variation (CV)1.0735795
Kurtosis34.291166
Mean106.53644
Median Absolute Deviation (MAD)0.88
Skewness5.2895714
Sum106856.05
Variance13081.716
MonotonicityNot monotonic
2024-01-10T07:44:10.450901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 150
 
14.9%
99.6 49
 
4.9%
99.84 36
 
3.6%
99.68 22
 
2.2%
99.75 22
 
2.2%
99.645 22
 
2.2%
97.92 16
 
1.6%
99.96 14
 
1.4%
97.44 14
 
1.4%
98.28 14
 
1.4%
Other values (334) 644
64.1%
ValueCountFrequency (%)
9.92 2
0.2%
10.0 1
0.1%
11.2 1
0.1%
12.0 1
0.1%
12.2 1
0.1%
13.65 1
0.1%
14.08 1
0.1%
14.25 1
0.1%
14.625 2
0.2%
14.8 1
0.1%
ValueCountFrequency (%)
998.76 1
 
0.1%
997.92 4
0.4%
997.56 2
0.2%
994.5 1
 
0.1%
991.44 1
 
0.1%
803.25 1
 
0.1%
499.8 3
0.3%
499.2 1
 
0.1%
498.75 1
 
0.1%
498.42 2
0.2%

설치위치
Text

Distinct730
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-01-10T07:44:11.038732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length17.967131
Min length6

Characters and Unicode

Total characters18039
Distinct characters155
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

Unique568 ?
Unique (%)56.6%

Sample

1st row충청남도 공주시 정안면 운궁리 산6-1
2nd row충청남도 공주시 유구읍 만천리 195-2외 1
3rd row충청남도 공주시 우성면 도천리 311
4th row충청남도 공주시 우성면 도천리 311-1
5th row충청남도 공주시 정안면 인풍리 66-1
ValueCountFrequency (%)
공주시 327
 
8.2%
충청남도 325
 
8.2%
정안면 140
 
3.5%
탄천면 138
 
3.5%
이인면 116
 
2.9%
우성면 109
 
2.7%
계룡면 100
 
2.5%
신풍면 83
 
2.1%
의당면 81
 
2.0%
유구읍 73
 
1.8%
Other values (1032) 2473
62.4%
2024-01-10T07:44:11.497566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2974
 
16.5%
- 1085
 
6.0%
1 1004
 
5.6%
리 911
 
5.1%
면 850
 
4.7%
2 775
 
4.3%
5 581
 
3.2%
3 556
 
3.1%
4 548
 
3.0%
6 545
 
3.0%
Other values (145) 8210
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8202
45.5%
Decimal Number 5289
29.3%
Space Separator 2974
 
16.5%
Dash Punctuation 1085
 
6.0%
Other Punctuation 487
 
2.7%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 911
 
11.1%
면 850
 
10.4%
남 393
 
4.8%
청 354
 
4.3%
도 341
 
4.2%
주 331
 
4.0%
공 328
 
4.0%
시 327
 
4.0%
충 325
 
4.0%
천 239
 
2.9%
Other values (130) 3803
46.4%
Decimal Number
ValueCountFrequency (%)
1 1004
19.0%
2 775
14.7%
5 581
11.0%
3 556
10.5%
4 548
10.4%
6 545
10.3%
7 441
8.3%
0 288
 
5.4%
8 287
 
5.4%
9 264
 
5.0%
Space Separator
ValueCountFrequency (%)
2974
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1085
100.0%
Other Punctuation
ValueCountFrequency (%)
, 487
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9837
54.5%
Hangul 8202
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 911
 
11.1%
면 850
 
10.4%
남 393
 
4.8%
청 354
 
4.3%
도 341
 
4.2%
주 331
 
4.0%
공 328
 
4.0%
시 327
 
4.0%
충 325
 
4.0%
천 239
 
2.9%
Other values (130) 3803
46.4%
Common
ValueCountFrequency (%)
2974
30.2%
- 1085
 
11.0%
1 1004
 
10.2%
2 775
 
7.9%
5 581
 
5.9%
3 556
 
5.7%
4 548
 
5.6%
6 545
 
5.5%
, 487
 
5.0%
7 441
 
4.5%
Other values (5) 841
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9837
54.5%
Hangul 8202
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2974
30.2%
- 1085
 
11.0%
1 1004
 
10.2%
2 775
 
7.9%
5 581
 
5.9%
3 556
 
5.7%
4 548
 
5.6%
6 545
 
5.5%
, 487
 
5.0%
7 441
 
4.5%
Other values (5) 841
 
8.5%
Hangul
ValueCountFrequency (%)
리 911
 
11.1%
면 850
 
10.4%
남 393
 
4.8%
청 354
 
4.3%
도 341
 
4.2%
주 331
 
4.0%
공 328
 
4.0%
시 327
 
4.0%
충 325
 
4.0%
천 239
 
2.9%
Other values (130) 3803
46.4%

허가일
Date

MISSING 

Distinct350
Distinct (%)35.6%
Missing20
Missing (%)2.0%
Memory size8.0 KiB
Minimum2007-01-09 00:00:00
Maximum2022-08-02 00:00:00
2024-01-10T07:44:11.620734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:44:11.739626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업개시일
Date

MISSING 

Distinct366
Distinct (%)43.4%
Missing160
Missing (%)15.9%
Memory size8.0 KiB
Minimum2007-08-07 00:00:00
Maximum2022-07-28 00:00:00
2024-01-10T07:44:11.859479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:44:11.998303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2022-08-09
1004 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-09
2nd row2022-08-09
3rd row2022-08-09
4th row2022-08-09
5th row2022-08-09

Common Values

ValueCountFrequency (%)
2022-08-09 1004
100.0%

Length

2024-01-10T07:44:12.098683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:44:12.173032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-09 1004
100.0%

Interactions

2024-01-10T07:44:09.168104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-01-10T07:44:09.272142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:44:09.362158image/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.
2024-01-10T07:44:09.458273image/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

발전소명설비용량(kW)설치위치허가일사업개시일데이터기준일
0구당태양광발전소96.0충청남도 공주시 정안면 운궁리 산6-12007-01-092007-08-072022-08-09
1만년태양광발전소99.0충청남도 공주시 유구읍 만천리 195-2외 12008-11-032009-09-022022-08-09
2도천태양광발전소29.0충청남도 공주시 우성면 도천리 3112008-12-042009-08-182022-08-09
3우성태양광발전소29.0충청남도 공주시 우성면 도천리 311-12008-12-302009-08-182022-08-09
4천일태양광발전소99.0충청남도 공주시 정안면 인풍리 66-12009-02-182009-09-082022-08-09
5차령1호태양광발전소99.0충청남도 공주시 정안면 인풍리 산11-5외 12009-06-232010-06-282022-08-09
6차령2호태양광발전소99.0충청남도 공주시 정안면 인풍리 산11-5외 12009-06-232010-06-282022-08-09
7차령3호태양광발전소99.0충청남도 공주시 정안면 인풍리 산11-52009-06-232010-06-282022-08-09
8차령4호태양광발전소99.0충청남도 공주시 정안면 인풍리 산11-52009-06-232010-06-282022-08-09
9대원당태양광발전소96.0충청남도 공주시 우성면 반촌리 산13-12009-06-262012-08-302022-08-09
발전소명설비용량(kW)설치위치허가일사업개시일데이터기준일
994삼이건업24.99사곡면 차동로 1169-16, 2동<NA><NA>2022-08-09
995정금선99.48의당면 도신리 318<NA><NA>2022-08-09
996김종묵99.48의당면 도신리 317, 318<NA><NA>2022-08-09
997김지종99.48의당면 도신리 317, 318<NA><NA>2022-08-09
998김준기99.48의당면 도신리 317<NA><NA>2022-08-09
999김한숙99.48의당면 도신리 318<NA><NA>2022-08-09
1000김영순99.48의당면 도신리 318<NA><NA>2022-08-09
1001전하용1호95.7이인면 반송리 421-9<NA><NA>2022-08-09
1002전하용2호95.7이인면 반송리 421-9<NA><NA>2022-08-09
1003정애98.0의당면 오인리 45-27<NA><NA>2022-08-09