Overview

Dataset statistics

Number of variables7
Number of observations1169
Missing cells10
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.3 KiB
Average record size in memory58.1 B

Variable types

Numeric2
Categorical2
Text3

Dataset

Description인천광역시 지역의 공공기관 신재생에너지 보급현황 데이터입니다. 관리처, 건물명, 설치주소, 에너지원, 용량, 설치연도 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15102466/fileData.do

Alerts

연번 is highly overall correlated with 설치연도High correlation
설치연도 is highly overall correlated with 연번High correlation
에너지원 is highly imbalanced (61.9%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:24:10.274642
Analysis finished2023-12-12 16:24:11.405540
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1169
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean585
Minimum1
Maximum1169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2023-12-13T01:24:11.496460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile59.4
Q1293
median585
Q3877
95-th percentile1110.6
Maximum1169
Range1168
Interquartile range (IQR)584

Descriptive statistics

Standard deviation337.60554
Coefficient of variation (CV)0.57710349
Kurtosis-1.2
Mean585
Median Absolute Deviation (MAD)292
Skewness0
Sum683865
Variance113977.5
MonotonicityStrictly increasing
2023-12-13T01:24:11.664994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
769 1
 
0.1%
785 1
 
0.1%
784 1
 
0.1%
783 1
 
0.1%
782 1
 
0.1%
781 1
 
0.1%
780 1
 
0.1%
779 1
 
0.1%
778 1
 
0.1%
Other values (1159) 1159
99.1%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1169 1
0.1%
1168 1
0.1%
1167 1
0.1%
1166 1
0.1%
1165 1
0.1%
1164 1
0.1%
1163 1
0.1%
1162 1
0.1%
1161 1
0.1%
1160 1
0.1%

지자체명_소속
Categorical

Distinct30
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
인천광역시교육청
288 
강화군
209 
미추홀구
127 
남동구
62 
부평구
60 
Other values (25)
423 

Length

Max length11
Median length9
Mean length4.9632164
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row인천광역시
2nd row인천광역시
3rd row인천광역시교육청
4th row인천계양소방서
5th row인천계양소방서

Common Values

ValueCountFrequency (%)
인천광역시교육청 288
24.6%
강화군 209
17.9%
미추홀구 127
10.9%
남동구 62
 
5.3%
부평구 60
 
5.1%
계양구 49
 
4.2%
서구 43
 
3.7%
연수구 42
 
3.6%
옹진군 40
 
3.4%
인천교통공사 32
 
2.7%
Other values (20) 217
18.6%

Length

2023-12-13T01:24:11.821695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천광역시교육청 288
24.6%
강화군 209
17.9%
미추홀구 127
10.9%
남동구 62
 
5.3%
부평구 60
 
5.1%
계양구 49
 
4.2%
서구 43
 
3.7%
연수구 42
 
3.6%
옹진군 40
 
3.4%
인천교통공사 32
 
2.7%
Other values (20) 217
18.6%

건물명
Text

Distinct946
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2023-12-13T01:24:12.132285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length6.823781
Min length3

Characters and Unicode

Total characters7977
Distinct characters345
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique757 ?
Unique (%)64.8%

Sample

1st row상수도사업본부 남동정수사업소
2nd row상수도사업본부 수산정수사업소
3rd row문일여고
4th row계양소방서
5th row장기119안전센터
ValueCountFrequency (%)
경로당 47
 
3.3%
마을회관 33
 
2.3%
분회경로당 32
 
2.2%
주민센터 17
 
1.2%
서구 8
 
0.6%
승기사업소 7
 
0.5%
인천글로벌 7
 
0.5%
도서관 7
 
0.5%
상수도사업본부 7
 
0.5%
캠퍼스 7
 
0.5%
Other values (977) 1267
88.0%
2023-12-13T01:24:12.598369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 304
 
3.8%
로 300
 
3.8%
당 296
 
3.7%
280
 
3.5%
동 217
 
2.7%
1 188
 
2.4%
리 188
 
2.4%
터 179
 
2.2%
센 175
 
2.2%
관 152
 
1.9%
Other values (335) 5698
71.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7124
89.3%
Decimal Number 427
 
5.4%
Space Separator 280
 
3.5%
Open Punctuation 66
 
0.8%
Close Punctuation 66
 
0.8%
Other Punctuation 11
 
0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 304
 
4.3%
로 300
 
4.2%
당 296
 
4.2%
동 217
 
3.0%
리 188
 
2.6%
터 179
 
2.5%
센 175
 
2.5%
관 152
 
2.1%
초 147
 
2.1%
소 133
 
1.9%
Other values (316) 5033
70.6%
Decimal Number
ValueCountFrequency (%)
1 188
44.0%
2 99
23.2%
9 52
 
12.2%
3 34
 
8.0%
4 22
 
5.2%
6 11
 
2.6%
5 10
 
2.3%
7 6
 
1.4%
8 3
 
0.7%
0 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 5
45.5%
. 3
27.3%
· 3
27.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
G 1
33.3%
N 1
33.3%
Space Separator
ValueCountFrequency (%)
280
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7122
89.3%
Common 850
 
10.7%
Latin 3
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 304
 
4.3%
로 300
 
4.2%
당 296
 
4.2%
동 217
 
3.0%
리 188
 
2.6%
터 179
 
2.5%
센 175
 
2.5%
관 152
 
2.1%
초 147
 
2.1%
소 133
 
1.9%
Other values (315) 5031
70.6%
Common
ValueCountFrequency (%)
280
32.9%
1 188
22.1%
2 99
 
11.6%
( 66
 
7.8%
) 66
 
7.8%
9 52
 
6.1%
3 34
 
4.0%
4 22
 
2.6%
6 11
 
1.3%
5 10
 
1.2%
Other values (6) 22
 
2.6%
Latin
ValueCountFrequency (%)
L 1
33.3%
G 1
33.3%
N 1
33.3%
Han
ValueCountFrequency (%)
舊 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7122
89.3%
ASCII 850
 
10.7%
None 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 304
 
4.3%
로 300
 
4.2%
당 296
 
4.2%
동 217
 
3.0%
리 188
 
2.6%
터 179
 
2.5%
센 175
 
2.5%
관 152
 
2.1%
초 147
 
2.1%
소 133
 
1.9%
Other values (315) 5031
70.6%
ASCII
ValueCountFrequency (%)
280
32.9%
1 188
22.1%
2 99
 
11.6%
( 66
 
7.8%
) 66
 
7.8%
9 52
 
6.1%
3 34
 
4.0%
4 22
 
2.6%
6 11
 
1.3%
5 10
 
1.2%
Other values (8) 22
 
2.6%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
舊 2
100.0%

위치(주소)
Text

Distinct587
Distinct (%)50.6%
Missing10
Missing (%)0.9%
Memory size9.3 KiB
2023-12-13T01:24:12.889964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35
Mean length15.421915
Min length3

Characters and Unicode

Total characters17874
Distinct characters256
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

Unique440 ?
Unique (%)38.0%

Sample

1st row관리동 뒤
2nd row인천광역시소래로541, 송수펌프동
3rd row미집계
4th row인천 계양구 장제로 774
5th row인천 계양구 장기서로 14
ValueCountFrequency (%)
인천광역시 850
22.4%
미집계 289
 
7.6%
강화군 213
 
5.6%
미추홀구 137
 
3.6%
서구 90
 
2.4%
연수구 88
 
2.3%
남동구 88
 
2.3%
부평구 79
 
2.1%
계양구 67
 
1.8%
옹진군 49
 
1.3%
Other values (886) 1845
48.6%
2023-12-13T01:24:13.300235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2680
 
15.0%
인 917
 
5.1%
천 879
 
4.9%
시 857
 
4.8%
역 855
 
4.8%
광 853
 
4.8%
구 629
 
3.5%
동 556
 
3.1%
로 544
 
3.0%
1 466
 
2.6%
Other values (246) 8638
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12377
69.2%
Space Separator 2680
 
15.0%
Decimal Number 2404
 
13.4%
Dash Punctuation 164
 
0.9%
Close Punctuation 123
 
0.7%
Open Punctuation 123
 
0.7%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 917
 
7.4%
천 879
 
7.1%
시 857
 
6.9%
역 855
 
6.9%
광 853
 
6.9%
구 629
 
5.1%
동 556
 
4.5%
로 544
 
4.4%
미 438
 
3.5%
계 377
 
3.0%
Other values (231) 5472
44.2%
Decimal Number
ValueCountFrequency (%)
1 466
19.4%
2 310
12.9%
3 284
11.8%
4 255
10.6%
6 215
8.9%
5 209
8.7%
7 200
8.3%
9 176
 
7.3%
8 155
 
6.4%
0 134
 
5.6%
Space Separator
ValueCountFrequency (%)
2680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 123
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12377
69.2%
Common 5497
30.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 917
 
7.4%
천 879
 
7.1%
시 857
 
6.9%
역 855
 
6.9%
광 853
 
6.9%
구 629
 
5.1%
동 556
 
4.5%
로 544
 
4.4%
미 438
 
3.5%
계 377
 
3.0%
Other values (231) 5472
44.2%
Common
ValueCountFrequency (%)
2680
48.8%
1 466
 
8.5%
2 310
 
5.6%
3 284
 
5.2%
4 255
 
4.6%
6 215
 
3.9%
5 209
 
3.8%
7 200
 
3.6%
9 176
 
3.2%
- 164
 
3.0%
Other values (5) 538
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12377
69.2%
ASCII 5497
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2680
48.8%
1 466
 
8.5%
2 310
 
5.6%
3 284
 
5.2%
4 255
 
4.6%
6 215
 
3.9%
5 209
 
3.8%
7 200
 
3.6%
9 176
 
3.2%
- 164
 
3.0%
Other values (5) 538
 
9.8%
Hangul
ValueCountFrequency (%)
인 917
 
7.4%
천 879
 
7.1%
시 857
 
6.9%
역 855
 
6.9%
광 853
 
6.9%
구 629
 
5.1%
동 556
 
4.5%
로 544
 
4.4%
미 438
 
3.5%
계 377
 
3.0%
Other values (231) 5472
44.2%

에너지원
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
태양광
970 
태양열
123 
지열
 
52
연료전지
 
23
소수력
 
1

Length

Max length4
Median length3
Mean length2.9751925
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row태양광
2nd row태양광
3rd row태양광
4th row태양열
5th row태양열

Common Values

ValueCountFrequency (%)
태양광 970
83.0%
태양열 123
 
10.5%
지열 52
 
4.4%
연료전지 23
 
2.0%
소수력 1
 
0.1%

Length

2023-12-13T01:24:13.428631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:13.541815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태양광 970
83.0%
태양열 123
 
10.5%
지열 52
 
4.4%
연료전지 23
 
2.0%
소수력 1
 
0.1%

발전용량(킬로와트_제곱미터)
Text

Distinct303
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2023-12-13T01:24:13.777905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.0402053
Min length2

Characters and Unicode

Total characters4723
Distinct characters14
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

Unique208 ?
Unique (%)17.8%

Sample

1st row30kw
2nd row30kw
3rd row30kw
4th row162㎡
5th row28㎡
ValueCountFrequency (%)
3kw 282
24.1%
5kw 91
 
7.8%
10kw 44
 
3.8%
20kw 37
 
3.2%
10㎡ 34
 
2.9%
30kw 31
 
2.7%
15kw 30
 
2.6%
12kw 27
 
2.3%
33kw 24
 
2.1%
6kw 20
 
1.7%
Other values (293) 549
47.0%
2023-12-13T01:24:14.183364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 1047
22.2%
w 1047
22.2%
3 499
10.6%
1 363
 
7.7%
0 292
 
6.2%
5 289
 
6.1%
2 268
 
5.7%
. 201
 
4.3%
6 157
 
3.3%
8 137
 
2.9%
Other values (4) 423
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2306
48.8%
Lowercase Letter 2094
44.3%
Other Punctuation 201
 
4.3%
Other Symbol 122
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 499
21.6%
1 363
15.7%
0 292
12.7%
5 289
12.5%
2 268
11.6%
6 157
 
6.8%
8 137
 
5.9%
4 129
 
5.6%
9 95
 
4.1%
7 77
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
k 1047
50.0%
w 1047
50.0%
Other Punctuation
ValueCountFrequency (%)
. 201
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2629
55.7%
Latin 2094
44.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 499
19.0%
1 363
13.8%
0 292
11.1%
5 289
11.0%
2 268
10.2%
. 201
7.6%
6 157
 
6.0%
8 137
 
5.2%
4 129
 
4.9%
㎡ 122
 
4.6%
Other values (2) 172
 
6.5%
Latin
ValueCountFrequency (%)
k 1047
50.0%
w 1047
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4601
97.4%
CJK Compat 122
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 1047
22.8%
w 1047
22.8%
3 499
10.8%
1 363
 
7.9%
0 292
 
6.3%
5 289
 
6.3%
2 268
 
5.8%
. 201
 
4.4%
6 157
 
3.4%
8 137
 
3.0%
Other values (3) 301
 
6.5%
CJK Compat
ValueCountFrequency (%)
㎡ 122
100.0%

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.1668
Minimum2004
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2023-12-13T01:24:14.311639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2004
5-th percentile2009
Q12013
median2017
Q32019
95-th percentile2021
Maximum2022
Range18
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7508529
Coefficient of variation (CV)0.0018603882
Kurtosis-0.47635829
Mean2016.1668
Median Absolute Deviation (MAD)3
Skewness-0.64211726
Sum2356899
Variance14.068897
MonotonicityIncreasing
2023-12-13T01:24:14.419010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2017 172
14.7%
2019 160
13.7%
2020 136
11.6%
2018 100
8.6%
2021 92
7.9%
2012 79
6.8%
2016 77
6.6%
2011 71
6.1%
2013 67
 
5.7%
2015 52
 
4.4%
Other values (9) 163
13.9%
ValueCountFrequency (%)
2004 2
 
0.2%
2005 1
 
0.1%
2006 8
 
0.7%
2007 4
 
0.3%
2008 14
 
1.2%
2009 46
3.9%
2010 24
 
2.1%
2011 71
6.1%
2012 79
6.8%
2013 67
5.7%
ValueCountFrequency (%)
2022 15
 
1.3%
2021 92
7.9%
2020 136
11.6%
2019 160
13.7%
2018 100
8.6%
2017 172
14.7%
2016 77
6.6%
2015 52
 
4.4%
2014 49
 
4.2%
2013 67
 
5.7%

Interactions

2023-12-13T01:24:10.968970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:10.758937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:11.059341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:10.842258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:24:14.500885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지자체명_소속에너지원설치연도
연번1.0000.7810.5460.967
지자체명_소속0.7811.0000.6690.731
에너지원0.5460.6691.0000.497
설치연도0.9670.7310.4971.000
2023-12-13T01:24:14.586059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
에너지원지자체명_소속
에너지원1.0000.354
지자체명_소속0.3541.000
2023-12-13T01:24:14.675382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치연도지자체명_소속에너지원
연번1.0000.9950.3680.257
설치연도0.9951.0000.3290.228
지자체명_소속0.3680.3291.0000.354
에너지원0.2570.2280.3541.000

Missing values

2023-12-13T01:24:11.213751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:24:11.347951image/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

연번지자체명_소속건물명위치(주소)에너지원발전용량(킬로와트_제곱미터)설치연도
01인천광역시상수도사업본부 남동정수사업소관리동 뒤태양광30kw2004
12인천광역시상수도사업본부 수산정수사업소인천광역시소래로541, 송수펌프동태양광30kw2004
23인천광역시교육청문일여고미집계태양광30kw2005
34인천계양소방서계양소방서인천 계양구 장제로 774태양열162㎡2006
45인천계양소방서장기119안전센터인천 계양구 장기서로 14태양열28㎡2006
56인천계양소방서효성119안전센터인천 계양구 효서로 96-1태양열28㎡2006
67인천서부소방서서부소방서인천광역시 서구 서곶로 292태양열59.7㎡2006
78인천광역시교육청산마을고미집계지열189kw2006
89인천광역시교육청산마을고미집계태양광50kw2006
910인천광역시교육청금마초미집계태양광5kw2006
연번지자체명_소속건물명위치(주소)에너지원발전용량(킬로와트_제곱미터)설치연도
11591160서구검단노인복지관인천광역시 서구 마전동태양광45kw2022
11601161서구가좌노인문화센터인천광역시 서구 가좌동태양광19.32kw2022
11611162인천광역시한국이민사박물관인천광역시 중구 북상동태양광15.75kw2022
11621163인천공단소방서동춘119안전센터인천광역시 연수구 앵고개로 241태양열35㎡2022
11631164인천연수경찰서연수경찰서인천광역시 연수구 원인재로 138태양광106kw2022
11641165인천연수경찰서연수경찰서 어린이집인천광역시 연수구 원인재로 138태양광15.3kw2022
11651166인천환경공단승기사업소 송도지소인천광역시 연수구 송도동태양광30.8kw2022
11661167인천시설공단인천노인종합문화회관<NA>태양열100㎡2022
11671168연수구시설안전관리공단연수구청인천광역시 연수구 동춘동태양광214kw2022
11681169연수구시설안전관리공단연수구 보건소인천광역시 연수구 청학동태양광24kw2022