Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory70.9 B

Variable types

Text2
Numeric2
Categorical4

Dataset

Description서울특별시 성동구_신재생에너지 설치현황 자료입니다. 설치위치, 설치용량(태양광 kW, 태양열 ㎡, 지열 RT), 설치연도, 용도 등의 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15095493/fileData.do

Alerts

용도 has constant value ""Constant
설치목적 is highly overall correlated with 태양광 용량 and 1 other fieldsHigh correlation
태양열 용량 is highly overall correlated with 태양광 용량 and 2 other fieldsHigh correlation
태양광 용량 is highly overall correlated with 태양열 용량 and 1 other fieldsHigh correlation
설치연도 is highly overall correlated with 태양열 용량High correlation
태양열 용량 is highly imbalanced (81.0%)Imbalance
지열 용량 is highly imbalanced (84.9%)Imbalance

Reproduction

Analysis started2023-12-12 10:35:24.409841
Analysis finished2023-12-12 10:35:25.554192
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치장소
Text

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-12T19:35:25.746263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.3695652
Min length4

Characters and Unicode

Total characters431
Distinct characters109
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

Unique44 ?
Unique (%)95.7%

Sample

1st row뚝섬빗물펌프장
2nd row응봉빗물펌프장
3rd row옥수빗물펌프장
4th row성수문화복지회관
5th row구립왕십리어린이집
ValueCountFrequency (%)
공영주차장 5
 
7.7%
공공복합청사 3
 
4.6%
뚝섬빗물펌프장 2
 
3.1%
사근동 2
 
3.1%
용답제2공영주차장 2
 
3.1%
응봉산 1
 
1.5%
성동안심상가 1
 
1.5%
성동종합사회복지관 1
 
1.5%
송정빗물펌프장 1
 
1.5%
행당빗물펌프장 1
 
1.5%
Other values (46) 46
70.8%
2023-12-12T19:35:26.134603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
 
5.3%
공 21
 
4.9%
19
 
4.4%
장 19
 
4.4%
성 15
 
3.5%
주 11
 
2.6%
사 10
 
2.3%
영 9
 
2.1%
차 9
 
2.1%
센 9
 
2.1%
Other values (99) 286
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 400
92.8%
Space Separator 19
 
4.4%
Decimal Number 12
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
 
5.8%
공 21
 
5.2%
장 19
 
4.8%
성 15
 
3.8%
주 11
 
2.8%
사 10
 
2.5%
영 9
 
2.2%
차 9
 
2.2%
센 9
 
2.2%
터 9
 
2.2%
Other values (95) 265
66.2%
Decimal Number
ValueCountFrequency (%)
2 7
58.3%
1 4
33.3%
3 1
 
8.3%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 400
92.8%
Common 31
 
7.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
 
5.8%
공 21
 
5.2%
장 19
 
4.8%
성 15
 
3.8%
주 11
 
2.8%
사 10
 
2.5%
영 9
 
2.2%
차 9
 
2.2%
센 9
 
2.2%
터 9
 
2.2%
Other values (95) 265
66.2%
Common
ValueCountFrequency (%)
19
61.3%
2 7
 
22.6%
1 4
 
12.9%
3 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 400
92.8%
ASCII 31
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
 
5.8%
공 21
 
5.2%
장 19
 
4.8%
성 15
 
3.8%
주 11
 
2.8%
사 10
 
2.5%
영 9
 
2.2%
차 9
 
2.2%
센 9
 
2.2%
터 9
 
2.2%
Other values (95) 265
66.2%
ASCII
ValueCountFrequency (%)
19
61.3%
2 7
 
22.6%
1 4
 
12.9%
3 1
 
3.2%

주소
Text

Distinct43
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-12T19:35:26.394242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21.5
Mean length18.565217
Min length10

Characters and Unicode

Total characters854
Distinct characters62
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)87.0%

Sample

1st row서울특별시 성동구 성수동1가 671-19
2nd row서울특별시 성동구 금호4가동 56-3
3rd row서울특별시 성동구 뚝섬로 41-1
4th row서울특별시 성동구 뚝섬로1길 43
5th row서울특별시 성동구 고산자로 262
ValueCountFrequency (%)
서울특별시 46
25.4%
성동구 46
25.4%
성수동1가 4
 
2.2%
9 4
 
2.2%
6 3
 
1.7%
천호대로78길 2
 
1.1%
행당로 2
 
1.1%
금호동1가 2
 
1.1%
독서당로 2
 
1.1%
청계천로 2
 
1.1%
Other values (65) 68
37.6%
2023-12-12T19:35:26.778473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
16.0%
동 60
 
7.0%
성 54
 
6.3%
서 50
 
5.9%
울 46
 
5.4%
특 46
 
5.4%
별 46
 
5.4%
시 46
 
5.4%
구 46
 
5.4%
1 35
 
4.1%
Other values (52) 288
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 542
63.5%
Decimal Number 161
 
18.9%
Space Separator 137
 
16.0%
Dash Punctuation 14
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 60
11.1%
성 54
10.0%
서 50
9.2%
울 46
8.5%
특 46
8.5%
별 46
8.5%
시 46
8.5%
구 46
8.5%
길 23
 
4.2%
로 21
 
3.9%
Other values (40) 104
19.2%
Decimal Number
ValueCountFrequency (%)
1 35
21.7%
2 24
14.9%
6 21
13.0%
3 17
10.6%
4 16
9.9%
7 12
 
7.5%
5 12
 
7.5%
0 9
 
5.6%
9 9
 
5.6%
8 6
 
3.7%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 542
63.5%
Common 312
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 60
11.1%
성 54
10.0%
서 50
9.2%
울 46
8.5%
특 46
8.5%
별 46
8.5%
시 46
8.5%
구 46
8.5%
길 23
 
4.2%
로 21
 
3.9%
Other values (40) 104
19.2%
Common
ValueCountFrequency (%)
137
43.9%
1 35
 
11.2%
2 24
 
7.7%
6 21
 
6.7%
3 17
 
5.4%
4 16
 
5.1%
- 14
 
4.5%
7 12
 
3.8%
5 12
 
3.8%
0 9
 
2.9%
Other values (2) 15
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 542
63.5%
ASCII 312
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
43.9%
1 35
 
11.2%
2 24
 
7.7%
6 21
 
6.7%
3 17
 
5.4%
4 16
 
5.1%
- 14
 
4.5%
7 12
 
3.8%
5 12
 
3.8%
0 9
 
2.9%
Other values (2) 15
 
4.8%
Hangul
ValueCountFrequency (%)
동 60
11.1%
성 54
10.0%
서 50
9.2%
울 46
8.5%
특 46
8.5%
별 46
8.5%
시 46
8.5%
구 46
8.5%
길 23
 
4.2%
로 21
 
3.9%
Other values (40) 104
19.2%

태양광 용량
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.152565
Minimum2
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T19:35:26.903235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q15.2125
median11.625
Q324.25
95-th percentile45.155
Maximum46
Range44
Interquartile range (IQR)19.0375

Descriptive statistics

Standard deviation13.024469
Coefficient of variation (CV)0.80634061
Kurtosis0.032614291
Mean16.152565
Median Absolute Deviation (MAD)6.57
Skewness1.0555204
Sum743.018
Variance169.6368
MonotonicityNot monotonic
2023-12-12T19:35:27.024263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5.0 5
 
10.9%
3.0 4
 
8.7%
10.0 3
 
6.5%
15.6 2
 
4.3%
15.4 2
 
4.3%
5.25 1
 
2.2%
7.0 1
 
2.2%
6.0 1
 
2.2%
22.0 1
 
2.2%
8.9 1
 
2.2%
Other values (25) 25
54.3%
ValueCountFrequency (%)
2.0 1
 
2.2%
3.0 4
8.7%
5.0 5
10.9%
5.11 1
 
2.2%
5.2 1
 
2.2%
5.25 1
 
2.2%
6.0 1
 
2.2%
7.0 1
 
2.2%
8.0 1
 
2.2%
8.9 1
 
2.2%
ValueCountFrequency (%)
46.0 1
2.2%
45.6 1
2.2%
45.54 1
2.2%
44.0 1
2.2%
36.75 1
2.2%
32.76 1
2.2%
32.13 1
2.2%
31.5 1
2.2%
30.0 1
2.2%
29.548 1
2.2%

태양열 용량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
44 
56
 
1
73
 
1

Length

Max length4
Median length4
Mean length3.9130435
Min length2

Unique

Unique2 ?
Unique (%)4.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row56
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 44
95.7%
56 1
 
2.2%
73 1
 
2.2%

Length

2023-12-12T19:35:27.170357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:35:27.397351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
95.7%
56 1
 
2.2%
73 1
 
2.2%

지열 용량
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
45 
30
 
1

Length

Max length4
Median length4
Mean length3.9565217
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row30
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 45
97.8%
30 1
 
2.2%

Length

2023-12-12T19:35:27.597471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:35:27.761136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
97.8%
30 1
 
2.2%

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.8043
Minimum2010
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T19:35:27.886024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2010.5
Q12015
median2018
Q32019
95-th percentile2020.75
Maximum2022
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0449927
Coefficient of variation (CV)0.0015098107
Kurtosis-0.21597141
Mean2016.8043
Median Absolute Deviation (MAD)1.5
Skewness-0.71899053
Sum92773
Variance9.2719807
MonotonicityIncreasing
2023-12-12T19:35:28.031166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2019 11
23.9%
2018 8
17.4%
2014 4
 
8.7%
2015 4
 
8.7%
2017 4
 
8.7%
2010 3
 
6.5%
2020 3
 
6.5%
2012 2
 
4.3%
2013 2
 
4.3%
2016 2
 
4.3%
Other values (2) 3
 
6.5%
ValueCountFrequency (%)
2010 3
 
6.5%
2012 2
 
4.3%
2013 2
 
4.3%
2014 4
 
8.7%
2015 4
 
8.7%
2016 2
 
4.3%
2017 4
 
8.7%
2018 8
17.4%
2019 11
23.9%
2020 3
 
6.5%
ValueCountFrequency (%)
2022 1
 
2.2%
2021 2
 
4.3%
2020 3
 
6.5%
2019 11
23.9%
2018 8
17.4%
2017 4
 
8.7%
2016 2
 
4.3%
2015 4
 
8.7%
2014 4
 
8.7%
2013 2
 
4.3%

설치목적
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
신재생에너지 보급확대
28 
공공기관 신축건물 설치의무화
14 
시자체보급사업
 
2
자체설치
 
2

Length

Max length15
Median length11
Mean length11.73913
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신재생에너지 보급확대
2nd row신재생에너지 보급확대
3rd row신재생에너지 보급확대
4th row공공기관 신축건물 설치의무화
5th row공공기관 신축건물 설치의무화

Common Values

ValueCountFrequency (%)
신재생에너지 보급확대 28
60.9%
공공기관 신축건물 설치의무화 14
30.4%
시자체보급사업 2
 
4.3%
자체설치 2
 
4.3%

Length

2023-12-12T19:35:28.233642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:35:28.390487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신재생에너지 28
27.5%
보급확대 28
27.5%
공공기관 14
13.7%
신축건물 14
13.7%
설치의무화 14
13.7%
시자체보급사업 2
 
2.0%
자체설치 2
 
2.0%

용도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
발전전기 자체소비
46 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row발전전기 자체소비
2nd row발전전기 자체소비
3rd row발전전기 자체소비
4th row발전전기 자체소비
5th row발전전기 자체소비

Common Values

ValueCountFrequency (%)
발전전기 자체소비 46
100.0%

Length

2023-12-12T19:35:28.529810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:35:28.654733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
발전전기 46
50.0%
자체소비 46
50.0%

Interactions

2023-12-12T19:35:25.061341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:35:24.835015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:35:25.172305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:35:24.935421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:35:28.734446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치장소주소태양광 용량태양열 용량설치연도설치목적
설치장소1.0001.0000.0000.0001.0000.000
주소1.0001.0000.0000.0001.0000.000
태양광 용량0.0000.0001.0000.0000.5930.720
태양열 용량0.0000.0000.0001.0000.000NaN
설치연도1.0001.0000.5930.0001.0000.685
설치목적0.0000.0000.720NaN0.6851.000
2023-12-12T19:35:28.884076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적지열 용량태양열 용량
설치목적1.000NaN1.000
지열 용량NaN1.000NaN
태양열 용량1.000NaN1.000
2023-12-12T19:35:29.027626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
태양광 용량설치연도태양열 용량지열 용량설치목적
태양광 용량1.0000.1731.000NaN0.513
설치연도0.1731.0001.000NaN0.477
태양열 용량1.0001.0001.000NaN1.000
지열 용량NaNNaNNaN1.000NaN
설치목적0.5130.4771.000NaN1.000

Missing values

2023-12-12T19:35:25.307645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:35:25.478706image/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.

Sample

설치장소주소태양광 용량태양열 용량지열 용량설치연도설치목적용도
0뚝섬빗물펌프장서울특별시 성동구 성수동1가 671-1910.0<NA><NA>2010신재생에너지 보급확대발전전기 자체소비
1응봉빗물펌프장서울특별시 성동구 금호4가동 56-310.0<NA><NA>2010신재생에너지 보급확대발전전기 자체소비
2옥수빗물펌프장서울특별시 성동구 뚝섬로 41-110.0<NA><NA>2010신재생에너지 보급확대발전전기 자체소비
3성수문화복지회관서울특별시 성동구 뚝섬로1길 4336.7556302012공공기관 신축건물 설치의무화발전전기 자체소비
4구립왕십리어린이집서울특별시 성동구 고산자로 2623.0<NA><NA>2012공공기관 신축건물 설치의무화발전전기 자체소비
5성동구청서울특별시 성동구 고산자로 27015.36<NA><NA>2013신재생에너지 보급확대발전전기 자체소비
6왕십리도선동 주민센터서울특별시 성동구 홍익동 36725.073<NA>2013공공기관 신축건물 설치의무화발전전기 자체소비
7성수1가1동 경로당서울특별시 성동구 성수동1가 271-23.0<NA><NA>2014신재생에너지 보급확대발전전기 자체소비
8뚝섬실버문화센터서울특별시 성동구 성수동2가 744-15.0<NA><NA>2014신재생에너지 보급확대발전전기 자체소비
9금일경로당대현경로복지관서울특별시 성동구 금호동1가 1-725.0<NA><NA>2014신재생에너지 보급확대발전전기 자체소비
설치장소주소태양광 용량태양열 용량지열 용량설치연도설치목적용도
36강변공영주차장서울특별시 성동구 둘레길 47-512.0<NA><NA>2019신재생에너지 보급확대발전전기 자체소비
37성동구도시관리공단서울특별시 성동구 청계천로 5465.25<NA><NA>2019신재생에너지 보급확대발전전기 자체소비
38용답제2공영주차장서울특별시 성동구 천호대로78길 99.0<NA><NA>2019신재생에너지 보급확대발전전기 자체소비
39대현산체육관서울특별시 성동구 독서당로63길 4445.6<NA><NA>2019시자체보급사업발전전기 자체소비
40성동나눔공유센터서울특별시 성동구 행당로 6길 103.0<NA><NA>2020자체설치발전전기 자체소비
41옥수동공공복합청사서울특별시 성동구 독서당로 20332.13<NA><NA>2020공공기관 신축건물 설치의무화발전전기 자체소비
42사근동 도시재생지원센터서울특별시 성동구 사근동길 415.0<NA><NA>2020자체설치발전전기 자체소비
43행당2동주민센터서울특별시 성동구 행당로9길 911.25<NA><NA>2021신재생에너지 보급확대발전전기 자체소비
44성동아이사랑복합문화센터서울특별시 성동구 금호동1가 63332.76<NA><NA>2021공공기관 신축건물 설치의무화발전전기 자체소비
45왕십리제2동 공공복합청사서울특별시 성동구 무학봉15길 631.5<NA><NA>2022공공기관 신축건물 설치의무화발전전기 자체소비