Overview

Dataset statistics

Number of variables7
Number of observations35
Missing cells4
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory62.8 B

Variable types

Text2
Numeric3
Categorical2

Dataset

Description서대문구 공공시설 태양광 설치현황 정보 (시설 개소수, 시설명, 소재지, 설치용량, 설치년도)에 관한 정보를 안내합니다.
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15096603/fileData.do

Alerts

발전유형 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
설치년도 is highly overall correlated with 누적 발전량(MWh)High correlation
설치용량(kW) is highly overall correlated with 누적 발전량(MWh)High correlation
누적 발전량(MWh) is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
누적 발전량(MWh) has 4 (11.4%) missing valuesMissing
시설명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:21:04.802047
Analysis finished2024-01-14 13:21:06.414142
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-14T22:21:06.612428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.1714286
Min length5

Characters and Unicode

Total characters321
Distinct characters96
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

Unique35 ?
Unique (%)100.0%

Sample

1st row자연사 박물관
2nd row문화체육회관
3rd row서대문 노인종합복지관
4th row남가좌2동 주민센터
5th row서대문 보건소
ValueCountFrequency (%)
경로당 4
 
5.7%
주민센터 4
 
5.7%
홍은 4
 
5.7%
서대문 3
 
4.3%
남가좌2동 3
 
4.3%
홍은1동 3
 
4.3%
자치회관 2
 
2.9%
제1공영주차장 2
 
2.9%
청소년 2
 
2.9%
서대문구 2
 
2.9%
Other values (40) 41
58.6%
2024-01-14T22:21:07.092475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
10.9%
관 11
 
3.4%
문 10
 
3.1%
동 10
 
3.1%
서 9
 
2.8%
터 9
 
2.8%
센 8
 
2.5%
주 8
 
2.5%
공 7
 
2.2%
은 7
 
2.2%
Other values (86) 207
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 272
84.7%
Space Separator 35
 
10.9%
Decimal Number 14
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 11
 
4.0%
문 10
 
3.7%
동 10
 
3.7%
서 9
 
3.3%
터 9
 
3.3%
센 8
 
2.9%
주 8
 
2.9%
공 7
 
2.6%
은 7
 
2.6%
대 7
 
2.6%
Other values (81) 186
68.4%
Decimal Number
ValueCountFrequency (%)
1 7
50.0%
2 4
28.6%
4 2
 
14.3%
3 1
 
7.1%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 272
84.7%
Common 49
 
15.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 11
 
4.0%
문 10
 
3.7%
동 10
 
3.7%
서 9
 
3.3%
터 9
 
3.3%
센 8
 
2.9%
주 8
 
2.9%
공 7
 
2.6%
은 7
 
2.6%
대 7
 
2.6%
Other values (81) 186
68.4%
Common
ValueCountFrequency (%)
35
71.4%
1 7
 
14.3%
2 4
 
8.2%
4 2
 
4.1%
3 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 272
84.7%
ASCII 49
 
15.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
71.4%
1 7
 
14.3%
2 4
 
8.2%
4 2
 
4.1%
3 1
 
2.0%
Hangul
ValueCountFrequency (%)
관 11
 
4.0%
문 10
 
3.7%
동 10
 
3.7%
서 9
 
3.3%
터 9
 
3.3%
센 8
 
2.9%
주 8
 
2.9%
공 7
 
2.6%
은 7
 
2.6%
대 7
 
2.6%
Other values (81) 186
68.4%

소재지
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-14T22:21:07.371826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.5142857
Min length7

Characters and Unicode

Total characters333
Distinct characters58
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

Unique35 ?
Unique (%)100.0%

Sample

1st row연희동 산5-58
2nd row홍은동 산26-155
3rd row천연동 117-3
4th row남가좌동 342-7
5th row연희동 165-2
ValueCountFrequency (%)
홍은동 4
 
5.6%
연희로 3
 
4.2%
연희동 2
 
2.8%
연희로11마길 2
 
2.8%
남가좌동 2
 
2.8%
홍은중앙로 2
 
2.8%
북가좌동 2
 
2.8%
125 1
 
1.4%
1012-2 1
 
1.4%
39나길 1
 
1.4%
Other values (51) 51
71.8%
2024-01-14T22:21:07.813427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
11.1%
1 29
 
8.7%
2 18
 
5.4%
4 18
 
5.4%
로 18
 
5.4%
길 16
 
4.8%
- 16
 
4.8%
5 14
 
4.2%
동 12
 
3.6%
8 11
 
3.3%
Other values (48) 144
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150
45.0%
Decimal Number 130
39.0%
Space Separator 37
 
11.1%
Dash Punctuation 16
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 18
 
12.0%
길 16
 
10.7%
동 12
 
8.0%
연 10
 
6.7%
홍 8
 
5.3%
희 8
 
5.3%
은 7
 
4.7%
가 5
 
3.3%
좌 4
 
2.7%
대 4
 
2.7%
Other values (36) 58
38.7%
Decimal Number
ValueCountFrequency (%)
1 29
22.3%
2 18
13.8%
4 18
13.8%
5 14
10.8%
8 11
 
8.5%
0 11
 
8.5%
3 10
 
7.7%
7 9
 
6.9%
6 6
 
4.6%
9 4
 
3.1%
Space Separator
ValueCountFrequency (%)
37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 183
55.0%
Hangul 150
45.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 18
 
12.0%
길 16
 
10.7%
동 12
 
8.0%
연 10
 
6.7%
홍 8
 
5.3%
희 8
 
5.3%
은 7
 
4.7%
가 5
 
3.3%
좌 4
 
2.7%
대 4
 
2.7%
Other values (36) 58
38.7%
Common
ValueCountFrequency (%)
37
20.2%
1 29
15.8%
2 18
9.8%
4 18
9.8%
- 16
8.7%
5 14
 
7.7%
8 11
 
6.0%
0 11
 
6.0%
3 10
 
5.5%
7 9
 
4.9%
Other values (2) 10
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 183
55.0%
Hangul 150
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
20.2%
1 29
15.8%
2 18
9.8%
4 18
9.8%
- 16
8.7%
5 14
 
7.7%
8 11
 
6.0%
0 11
 
6.0%
3 10
 
5.5%
7 9
 
4.9%
Other values (2) 10
 
5.5%
Hangul
ValueCountFrequency (%)
로 18
 
12.0%
길 16
 
10.7%
동 12
 
8.0%
연 10
 
6.7%
홍 8
 
5.3%
희 8
 
5.3%
은 7
 
4.7%
가 5
 
3.3%
좌 4
 
2.7%
대 4
 
2.7%
Other values (36) 58
38.7%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.9429
Minimum2009
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-14T22:21:07.945923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2009
Q12012.5
median2016
Q32020
95-th percentile2022
Maximum2023
Range14
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation4.4321211
Coefficient of variation (CV)0.0021985351
Kurtosis-1.1414616
Mean2015.9429
Median Absolute Deviation (MAD)4
Skewness-0.17466821
Sum70558
Variance19.643697
MonotonicityNot monotonic
2024-01-14T22:21:08.076164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2009 5
14.3%
2015 5
14.3%
2020 3
8.6%
2021 3
8.6%
2022 3
8.6%
2012 2
 
5.7%
2014 2
 
5.7%
2016 2
 
5.7%
2017 2
 
5.7%
2018 2
 
5.7%
Other values (5) 6
17.1%
ValueCountFrequency (%)
2009 5
14.3%
2010 1
 
2.9%
2011 1
 
2.9%
2012 2
 
5.7%
2013 1
 
2.9%
2014 2
 
5.7%
2015 5
14.3%
2016 2
 
5.7%
2017 2
 
5.7%
2018 2
 
5.7%
ValueCountFrequency (%)
2023 1
 
2.9%
2022 3
8.6%
2021 3
8.6%
2020 3
8.6%
2019 2
 
5.7%
2018 2
 
5.7%
2017 2
 
5.7%
2016 2
 
5.7%
2015 5
14.3%
2014 2
 
5.7%

설치용량(kW)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.892286
Minimum0.6
Maximum99.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-14T22:21:08.219435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile3.178
Q18
median10
Q324.175
95-th percentile69
Maximum99.9
Range99.3
Interquartile range (IQR)16.175

Descriptive statistics

Standard deviation23.146153
Coefficient of variation (CV)1.1635743
Kurtosis5.1750308
Mean19.892286
Median Absolute Deviation (MAD)4.72
Skewness2.2824292
Sum696.23
Variance535.74441
MonotonicityNot monotonic
2024-01-14T22:21:08.354636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
10.0 11
31.4%
20.0 2
 
5.7%
8.0 2
 
5.7%
5.0 2
 
5.7%
30.0 2
 
5.7%
60.0 1
 
2.9%
46.0 1
 
2.9%
40.0 1
 
2.9%
6.4 1
 
2.9%
3.64 1
 
2.9%
Other values (11) 11
31.4%
ValueCountFrequency (%)
0.6 1
 
2.9%
2.1 1
 
2.9%
3.64 1
 
2.9%
5.0 2
 
5.7%
5.28 1
 
2.9%
5.5 1
 
2.9%
6.4 1
 
2.9%
8.0 2
 
5.7%
8.5 1
 
2.9%
10.0 11
31.4%
ValueCountFrequency (%)
99.9 1
2.9%
90.0 1
2.9%
60.0 1
2.9%
46.0 1
2.9%
40.0 1
2.9%
38.16 1
2.9%
30.0 2
5.7%
28.35 1
2.9%
20.0 2
5.7%
15.0 1
2.9%

발전유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
계통연계형
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계통연계형 35
100.0%

Length

2024-01-14T22:21:08.513225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:21:08.633191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계통연계형 35
100.0%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-21
35 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-21
2nd row2023-12-21
3rd row2023-12-21
4th row2023-12-21
5th row2023-12-21

Common Values

ValueCountFrequency (%)
2023-12-21 35
100.0%

Length

2024-01-14T22:21:08.784851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:21:08.929440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-21 35
100.0%

누적 발전량(MWh)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct31
Distinct (%)100.0%
Missing4
Missing (%)11.4%
Infinite0
Infinite (%)0.0%
Mean143.38065
Minimum8.9
Maximum754.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-14T22:21:09.050207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.9
5-th percentile13.55
Q139.15
median68.2
Q3193.85
95-th percentile398.65
Maximum754.7
Range745.8
Interquartile range (IQR)154.7

Descriptive statistics

Standard deviation163.80061
Coefficient of variation (CV)1.1424179
Kurtosis5.3720661
Mean143.38065
Median Absolute Deviation (MAD)51.2
Skewness2.0977537
Sum4444.8
Variance26830.64
MonotonicityNot monotonic
2024-01-14T22:21:09.232264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
417.7 1
 
2.9%
33.8 1
 
2.9%
14.0 1
 
2.9%
8.9 1
 
2.9%
13.1 1
 
2.9%
17.0 1
 
2.9%
56.0 1
 
2.9%
332.8 1
 
2.9%
209.8 1
 
2.9%
53.9 1
 
2.9%
Other values (21) 21
60.0%
(Missing) 4
 
11.4%
ValueCountFrequency (%)
8.9 1
2.9%
13.1 1
2.9%
14.0 1
2.9%
17.0 1
2.9%
33.8 1
2.9%
34.1 1
2.9%
34.3 1
2.9%
39.0 1
2.9%
39.3 1
2.9%
41.1 1
2.9%
ValueCountFrequency (%)
754.7 1
2.9%
417.7 1
2.9%
379.6 1
2.9%
332.8 1
2.9%
316.7 1
2.9%
303.7 1
2.9%
240.8 1
2.9%
209.8 1
2.9%
177.9 1
2.9%
165.7 1
2.9%

Interactions

2024-01-14T22:21:05.797266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.120805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.468944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.910575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.248024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.571744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:06.017363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.352605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:21:05.692861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:21:09.441050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지설치년도설치용량(kW)누적 발전량(MWh)
시설명1.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.000
설치년도1.0001.0001.0000.0000.686
설치용량(kW)1.0001.0000.0001.0000.915
누적 발전량(MWh)1.0001.0000.6860.9151.000
2024-01-14T22:21:09.616714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도설치용량(kW)누적 발전량(MWh)
설치년도1.000-0.230-0.669
설치용량(kW)-0.2301.0000.773
누적 발전량(MWh)-0.6690.7731.000

Missing values

2024-01-14T22:21:06.168382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:21:06.347305image/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

시설명소재지설치년도설치용량(kW)발전유형데이터 기준일자누적 발전량(MWh)
0자연사 박물관연희동 산5-58200960.0계통연계형2023-12-21754.7
1문화체육회관홍은동 산26-155200990.0계통연계형2023-12-21417.7
2서대문 노인종합복지관천연동 117-3200920.0계통연계형2023-12-21303.7
3남가좌2동 주민센터남가좌동 342-7200910.0계통연계형2023-12-21147.5
4서대문 보건소연희동 165-2200910.0계통연계형2023-12-21165.7
5서대문구 두바퀴환경센터홍제천로 11120208.0계통연계형2023-12-21<NA>
6홍은 종합사회복지관홍은동 48-2020105.0계통연계형2023-12-2150.6
7구청 제4별관홍은동 273-10201130.0계통연계형2023-12-21379.6
8서대문 지역 자활센터연희로11마길 86-77201215.0계통연계형2023-12-21177.9
9북가좌1동 주민센터북가좌동 144-53201228.35계통연계형2023-12-21240.8
시설명소재지설치년도설치용량(kW)발전유형데이터 기준일자누적 발전량(MWh)
25궁둥근린공원 실내체육관연희로11마길 86-47201946.0계통연계형2023-12-21209.8
26중앙근린공원북가좌동 48020202.1계통연계형2023-12-21<NA>
27북아현문화체육센터북아현동 1012-2202099.9계통연계형2023-12-21332.8
28서대문구의회연희로36길 49202120.0계통연계형2023-12-2156.0
29남가좌2동 제2공영주차장명지대5길 10-8202110.0계통연계형2023-12-2117.0
30서대문구청연희로 24820215.28계통연계형2023-12-2113.1
31신촌 경로당성산로24길 1-2020223.64계통연계형2023-12-218.9
32백련 경로당서대문구 명지대길5020226.4계통연계형2023-12-2114.0
33구청 3별관연희로 247202230.0계통연계형2023-12-2133.8
34이진아 기념 도서관독립문공원길 80202340.0계통연계형2023-12-21<NA>