Overview

Dataset statistics

Number of variables7
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory64.0 B

Variable types

Categorical2
Text2
Numeric2
DateTime1

Dataset

Description인천광역시 서구에 위치한 태양광발전설치현황에 관한 데이터셋입니다. 인천광역시 서구에 위치한 태양광발전설치현황의 기관명, 설치장소명, 소재지도로명주소, 설치연도에 관한 정보를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15090877/fileData.do

Alerts

기관명 has constant value ""Constant
발전유형 has constant value ""Constant
데이터기준일자 has constant value ""Constant
설치연도 is highly overall correlated with 설비용량(KWh)High correlation
설비용량(KWh) is highly overall correlated with 설치연도High correlation
설치장소명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:28:46.689963
Analysis finished2023-12-12 11:28:48.410863
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
인천광역시 서구
22 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 서구
2nd row인천광역시 서구
3rd row인천광역시 서구
4th row인천광역시 서구
5th row인천광역시 서구

Common Values

ValueCountFrequency (%)
인천광역시 서구 22
100.0%

Length

2023-12-12T20:28:48.494665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:28:48.672064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 22
50.0%
서구 22
50.0%

설치장소명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T20:28:48.962997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.7272727
Min length5

Characters and Unicode

Total characters148
Distinct characters60
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row서구문화회관
2nd row서구청소년센터
3rd row가좌4동분회경로당
4th row검단복지회관
5th row원당동행정복지센터
ValueCountFrequency (%)
서구문화회관 1
 
4.5%
서구청소년센터 1
 
4.5%
원창동경로당 1
 
4.5%
신현동경로당 1
 
4.5%
공촌경로당 1
 
4.5%
고현경로당 1
 
4.5%
가좌1동경로당 1
 
4.5%
서구노인문화회관 1
 
4.5%
신현어린이집 1
 
4.5%
검단어린이집 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T20:28:49.503786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 8
 
5.4%
로 7
 
4.7%
관 7
 
4.7%
경 7
 
4.7%
터 6
 
4.1%
센 6
 
4.1%
회 6
 
4.1%
동 6
 
4.1%
구 5
 
3.4%
서 5
 
3.4%
Other values (50) 85
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145
98.0%
Decimal Number 3
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 8
 
5.5%
로 7
 
4.8%
관 7
 
4.8%
경 7
 
4.8%
터 6
 
4.1%
센 6
 
4.1%
회 6
 
4.1%
동 6
 
4.1%
구 5
 
3.4%
서 5
 
3.4%
Other values (48) 82
56.6%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
98.0%
Common 3
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 8
 
5.5%
로 7
 
4.8%
관 7
 
4.8%
경 7
 
4.8%
터 6
 
4.1%
센 6
 
4.1%
회 6
 
4.1%
동 6
 
4.1%
구 5
 
3.4%
서 5
 
3.4%
Other values (48) 82
56.6%
Common
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145
98.0%
ASCII 3
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 8
 
5.5%
로 7
 
4.8%
관 7
 
4.8%
경 7
 
4.8%
터 6
 
4.1%
센 6
 
4.1%
회 6
 
4.1%
동 6
 
4.1%
구 5
 
3.4%
서 5
 
3.4%
Other values (48) 82
56.6%
ASCII
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

소재지도로명주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T20:28:49.822568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.727273
Min length15

Characters and Unicode

Total characters390
Distinct characters51
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

Unique22 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 서달로 190
2nd row인천광역시 서구 원창로 92
3rd row인천광역시 서구 장고개로280번길 15
4th row인천광역시 서구 완정로92번길 18
5th row인천광역시 서구 고산로 24
ValueCountFrequency (%)
인천광역시 22
25.0%
서구 22
25.0%
원창로 3
 
3.4%
15 2
 
2.3%
387 1
 
1.1%
경명대로 1
 
1.1%
265 1
 
1.1%
완정로188번2길 1
 
1.1%
3 1
 
1.1%
새오개로54번길 1
 
1.1%
Other values (33) 33
37.5%
2023-12-12T20:28:50.344933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
16.9%
서 23
 
5.9%
인 22
 
5.6%
광 22
 
5.6%
역 22
 
5.6%
시 22
 
5.6%
구 22
 
5.6%
천 22
 
5.6%
로 21
 
5.4%
2 14
 
3.6%
Other values (41) 134
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
62.3%
Decimal Number 78
 
20.0%
Space Separator 66
 
16.9%
Dash Punctuation 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 23
9.5%
인 22
9.1%
광 22
9.1%
역 22
9.1%
시 22
9.1%
구 22
9.1%
천 22
9.1%
로 21
8.6%
길 10
 
4.1%
번 10
 
4.1%
Other values (29) 47
19.3%
Decimal Number
ValueCountFrequency (%)
2 14
17.9%
1 13
16.7%
8 9
11.5%
4 8
10.3%
0 7
9.0%
3 7
9.0%
5 7
9.0%
7 5
 
6.4%
6 4
 
5.1%
9 4
 
5.1%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
62.3%
Common 147
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 23
9.5%
인 22
9.1%
광 22
9.1%
역 22
9.1%
시 22
9.1%
구 22
9.1%
천 22
9.1%
로 21
8.6%
길 10
 
4.1%
번 10
 
4.1%
Other values (29) 47
19.3%
Common
ValueCountFrequency (%)
66
44.9%
2 14
 
9.5%
1 13
 
8.8%
8 9
 
6.1%
4 8
 
5.4%
0 7
 
4.8%
3 7
 
4.8%
5 7
 
4.8%
7 5
 
3.4%
6 4
 
2.7%
Other values (2) 7
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
62.3%
ASCII 147
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
44.9%
2 14
 
9.5%
1 13
 
8.8%
8 9
 
6.1%
4 8
 
5.4%
0 7
 
4.8%
3 7
 
4.8%
5 7
 
4.8%
7 5
 
3.4%
6 4
 
2.7%
Other values (2) 7
 
4.8%
Hangul
ValueCountFrequency (%)
서 23
9.5%
인 22
9.1%
광 22
9.1%
역 22
9.1%
시 22
9.1%
구 22
9.1%
천 22
9.1%
로 21
8.6%
길 10
 
4.1%
번 10
 
4.1%
Other values (29) 47
19.3%

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.9545
Minimum2011
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T20:28:50.522475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2012
Q12016.25
median2019.5
Q32020
95-th percentile2021
Maximum2021
Range10
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation3.1240583
Coefficient of variation (CV)0.0015481312
Kurtosis0.13207831
Mean2017.9545
Median Absolute Deviation (MAD)1.5
Skewness-1.0772534
Sum44395
Variance9.7597403
MonotonicityIncreasing
2023-12-12T20:28:50.695846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2020 7
31.8%
2021 4
18.2%
2012 2
 
9.1%
2016 2
 
9.1%
2017 2
 
9.1%
2018 2
 
9.1%
2011 1
 
4.5%
2015 1
 
4.5%
2019 1
 
4.5%
ValueCountFrequency (%)
2011 1
 
4.5%
2012 2
 
9.1%
2015 1
 
4.5%
2016 2
 
9.1%
2017 2
 
9.1%
2018 2
 
9.1%
2019 1
 
4.5%
2020 7
31.8%
2021 4
18.2%
ValueCountFrequency (%)
2021 4
18.2%
2020 7
31.8%
2019 1
 
4.5%
2018 2
 
9.1%
2017 2
 
9.1%
2016 2
 
9.1%
2015 1
 
4.5%
2012 2
 
9.1%
2011 1
 
4.5%

발전유형
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
자가소비
22 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가소비 22
100.0%

Length

2023-12-12T20:28:50.870140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:28:51.040318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가소비 22
100.0%

설비용량(KWh)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.181818
Minimum3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T20:28:51.185612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q15
median15
Q320
95-th percentile49.6
Maximum100
Range97
Interquartile range (IQR)15

Descriptive statistics

Standard deviation22.201751
Coefficient of variation (CV)1.1574373
Kurtosis8.0909322
Mean19.181818
Median Absolute Deviation (MAD)10
Skewness2.5744661
Sum422
Variance492.91775
MonotonicityNot monotonic
2023-12-12T20:28:51.352185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 5
22.7%
20 3
13.6%
6 2
 
9.1%
19 2
 
9.1%
5 2
 
9.1%
50 1
 
4.5%
10 1
 
4.5%
30 1
 
4.5%
18 1
 
4.5%
12 1
 
4.5%
Other values (3) 3
13.6%
ValueCountFrequency (%)
3 5
22.7%
5 2
 
9.1%
6 2
 
9.1%
10 1
 
4.5%
12 1
 
4.5%
18 1
 
4.5%
19 2
 
9.1%
20 3
13.6%
25 1
 
4.5%
30 1
 
4.5%
ValueCountFrequency (%)
100 1
 
4.5%
50 1
 
4.5%
42 1
 
4.5%
30 1
 
4.5%
25 1
 
4.5%
20 3
13.6%
19 2
9.1%
18 1
 
4.5%
12 1
 
4.5%
10 1
 
4.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2022-09-06 00:00:00
Maximum2022-09-06 00:00:00
2023-12-12T20:28:51.506956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:28:51.663822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T20:28:47.282396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:28:47.012356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:28:47.412541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:28:47.141475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:28:51.787493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치장소명소재지도로명주소설치연도설비용량(KWh)
설치장소명1.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.000
설치연도1.0001.0001.0000.781
설비용량(KWh)1.0001.0000.7811.000
2023-12-12T20:28:51.953754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도설비용량(KWh)
설치연도1.000-0.685
설비용량(KWh)-0.6851.000

Missing values

2023-12-12T20:28:48.110675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:28:48.333023image/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

기관명설치장소명소재지도로명주소설치연도발전유형설비용량(KWh)데이터기준일자
0인천광역시 서구서구문화회관인천광역시 서구 서달로 1902011자가소비202022-09-06
1인천광역시 서구서구청소년센터인천광역시 서구 원창로 922012자가소비502022-09-06
2인천광역시 서구가좌4동분회경로당인천광역시 서구 장고개로280번길 152012자가소비102022-09-06
3인천광역시 서구검단복지회관인천광역시 서구 완정로92번길 182015자가소비302022-09-06
4인천광역시 서구원당동행정복지센터인천광역시 서구 고산로 242016자가소비202022-09-06
5인천광역시 서구녹청자박물관인천광역시 서구 도요지로 542016자가소비202022-09-06
6인천광역시 서구가좌1동주민센터인천광역시 서구 가정로112번길 102017자가소비182022-09-06
7인천광역시 서구인천서구지역자활센터인천광역시 서구 원창로 762017자가소비122022-09-06
8인천광역시 서구국민체육센터인천광역시 서구 승학로 5252018자가소비422022-09-06
9인천광역시 서구세어도어촌계회관인천광역시 서구 세어로 292018자가소비62022-09-06
기관명설치장소명소재지도로명주소설치연도발전유형설비용량(KWh)데이터기준일자
12인천광역시 서구견인보관소인천광역시 서구 경명대로 2652020자가소비52022-09-06
13인천광역시 서구검단어린이집인천광역시 서구 완정로188번2길 32020자가소비252022-09-06
14인천광역시 서구신현어린이집인천광역시 서구 새오개로54번길 112020자가소비62022-09-06
15인천광역시 서구서구노인문화회관인천광역시 서구 장고개로 3872020자가소비192022-09-06
16인천광역시 서구가좌1동경로당인천광역시 서구 284번길 312020자가소비52022-09-06
17인천광역시 서구고현경로당인천광역시 서구 심곡로208번길 8-72020자가소비32022-09-06
18인천광역시 서구공촌경로당인천광역시 서구 승학로402번길 152021자가소비32022-09-06
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