Overview

Dataset statistics

Number of variables3
Number of observations188
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory25.7 B

Variable types

Numeric1
Text2

Dataset

Description한국지역난방공사에서 수행한 외부 연구용역에 대한 정보입니다. (연도, 연구용역명, 수행기관에 대한 정보를 제공합니다.)
Author한국지역난방공사
URLhttps://www.data.go.kr/data/15052342/fileData.do

Reproduction

Analysis started2024-04-06 08:18:52.058806
Analysis finished2024-04-06 08:18:52.935472
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct9
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.9947
Minimum2015
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-06T17:18:53.041605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2018
Q32022
95-th percentile2023
Maximum2023
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.6538184
Coefficient of variation (CV)0.0013144257
Kurtosis-1.329127
Mean2018.9947
Median Absolute Deviation (MAD)2
Skewness0.073459942
Sum379571
Variance7.0427523
MonotonicityIncreasing
2024-04-06T17:18:53.460281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2018 43
22.9%
2022 29
15.4%
2015 22
11.7%
2021 21
11.2%
2023 21
11.2%
2017 20
10.6%
2016 17
 
9.0%
2020 8
 
4.3%
2019 7
 
3.7%
ValueCountFrequency (%)
2015 22
11.7%
2016 17
 
9.0%
2017 20
10.6%
2018 43
22.9%
2019 7
 
3.7%
2020 8
 
4.3%
2021 21
11.2%
2022 29
15.4%
2023 21
11.2%
ValueCountFrequency (%)
2023 21
11.2%
2022 29
15.4%
2021 21
11.2%
2020 8
 
4.3%
2019 7
 
3.7%
2018 43
22.9%
2017 20
10.6%
2016 17
 
9.0%
2015 22
11.7%
Distinct182
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-06T17:18:53.965307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length44
Mean length30.595745
Min length15

Characters and Unicode

Total characters5752
Distinct characters360
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)93.6%

Sample

1st row하수 처리수의 공정용수 활용을 위한 최적화 방안 도출
2nd row열손실 저감용 단열페인트의 지역난방 설비 적용방안 연구
3rd row열사용시설의 적정 효율평가 기법 수립 연구
4th row지역난방(DH) 펌프의 운영실태 분석을 통한 최적운영방안 도출 연구
5th row바이오매스 이용 열분해 바이오오일 생산 최적화 기술개발 및 활용방안 연구
ValueCountFrequency (%)
연구 145
 
10.5%
58
 
4.2%
위한 32
 
2.3%
개발 17
 
1.2%
방안 17
 
1.2%
관한 14
 
1.0%
지역난방 14
 
1.0%
수립 13
 
0.9%
열수송관 12
 
0.9%
용역 11
 
0.8%
Other values (727) 1042
75.8%
2024-04-06T17:18:54.993146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1190
 
20.7%
190
 
3.3%
183
 
3.2%
114
 
2.0%
100
 
1.7%
97
 
1.7%
96
 
1.7%
83
 
1.4%
82
 
1.4%
79
 
1.4%
Other values (350) 3538
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4210
73.2%
Space Separator 1190
 
20.7%
Uppercase Letter 156
 
2.7%
Lowercase Letter 114
 
2.0%
Decimal Number 36
 
0.6%
Other Punctuation 14
 
0.2%
Close Punctuation 13
 
0.2%
Open Punctuation 13
 
0.2%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
190
 
4.5%
183
 
4.3%
114
 
2.7%
100
 
2.4%
97
 
2.3%
96
 
2.3%
83
 
2.0%
82
 
1.9%
79
 
1.9%
73
 
1.7%
Other values (293) 3113
73.9%
Uppercase Letter
ValueCountFrequency (%)
S 22
14.1%
C 18
11.5%
H 16
10.3%
R 15
9.6%
E 10
 
6.4%
T 9
 
5.8%
I 8
 
5.1%
G 7
 
4.5%
P 7
 
4.5%
F 7
 
4.5%
Other values (12) 37
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 18
15.8%
r 12
10.5%
t 10
 
8.8%
a 10
 
8.8%
i 8
 
7.0%
o 7
 
6.1%
s 7
 
6.1%
n 6
 
5.3%
u 6
 
5.3%
g 5
 
4.4%
Other values (9) 25
21.9%
Decimal Number
ValueCountFrequency (%)
2 10
27.8%
0 9
25.0%
1 5
13.9%
5 4
 
11.1%
6 3
 
8.3%
4 2
 
5.6%
3 2
 
5.6%
8 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 9
64.3%
· 3
 
21.4%
/ 1
 
7.1%
. 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4210
73.2%
Common 1272
 
22.1%
Latin 270
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
190
 
4.5%
183
 
4.3%
114
 
2.7%
100
 
2.4%
97
 
2.3%
96
 
2.3%
83
 
2.0%
82
 
1.9%
79
 
1.9%
73
 
1.7%
Other values (293) 3113
73.9%
Latin
ValueCountFrequency (%)
S 22
 
8.1%
e 18
 
6.7%
C 18
 
6.7%
H 16
 
5.9%
R 15
 
5.6%
r 12
 
4.4%
t 10
 
3.7%
E 10
 
3.7%
a 10
 
3.7%
T 9
 
3.3%
Other values (31) 130
48.1%
Common
ValueCountFrequency (%)
1190
93.6%
) 13
 
1.0%
( 13
 
1.0%
2 10
 
0.8%
, 9
 
0.7%
0 9
 
0.7%
- 6
 
0.5%
1 5
 
0.4%
5 4
 
0.3%
6 3
 
0.2%
Other values (6) 10
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4209
73.2%
ASCII 1539
 
26.8%
None 3
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1190
77.3%
S 22
 
1.4%
e 18
 
1.2%
C 18
 
1.2%
H 16
 
1.0%
R 15
 
1.0%
) 13
 
0.8%
( 13
 
0.8%
r 12
 
0.8%
t 10
 
0.6%
Other values (46) 212
 
13.8%
Hangul
ValueCountFrequency (%)
190
 
4.5%
183
 
4.3%
114
 
2.7%
100
 
2.4%
97
 
2.3%
96
 
2.3%
83
 
2.0%
82
 
1.9%
79
 
1.9%
73
 
1.7%
Other values (292) 3112
73.9%
None
ValueCountFrequency (%)
· 3
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct139
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-06T17:18:55.388565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length28
Mean length12.430851
Min length3

Characters and Unicode

Total characters2337
Distinct characters207
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)60.1%

Sample

1st row성균관대 산학협력단, ㈜세원
2nd row서울대학교 산학협력단
3rd row수원대학교 산학협력단
4th row한국생산기술연구원
5th row생산기술연구원, 서울시립대
ValueCountFrequency (%)
산학협력단 43
 
14.1%
주식회사 28
 
9.2%
성균관대학교 10
 
3.3%
서울과학기술대학교 7
 
2.3%
한울회계법인 7
 
2.3%
에너지경제연구원 7
 
2.3%
재)한국건설생활환경시험연구원 6
 
2.0%
충남대학교 5
 
1.6%
우원엠앤이 5
 
1.6%
재단법인 5
 
1.6%
Other values (139) 183
59.8%
2024-04-06T17:18:56.454728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
 
6.6%
121
 
5.2%
75
 
3.2%
74
 
3.2%
74
 
3.2%
70
 
3.0%
69
 
3.0%
69
 
3.0%
66
 
2.8%
60
 
2.6%
Other values (197) 1505
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2049
87.7%
Space Separator 121
 
5.2%
Other Punctuation 43
 
1.8%
Open Punctuation 35
 
1.5%
Close Punctuation 35
 
1.5%
Other Symbol 31
 
1.3%
Uppercase Letter 17
 
0.7%
Decimal Number 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
154
 
7.5%
75
 
3.7%
74
 
3.6%
74
 
3.6%
70
 
3.4%
69
 
3.4%
69
 
3.4%
66
 
3.2%
60
 
2.9%
54
 
2.6%
Other values (180) 1284
62.7%
Uppercase Letter
ValueCountFrequency (%)
K 4
23.5%
S 3
17.6%
T 2
11.8%
C 2
11.8%
P 2
11.8%
H 1
 
5.9%
M 1
 
5.9%
D 1
 
5.9%
N 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
3 2
33.3%
9 2
33.3%
Space Separator
ValueCountFrequency (%)
121
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Other Symbol
ValueCountFrequency (%)
31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2080
89.0%
Common 240
 
10.3%
Latin 17
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
154
 
7.4%
75
 
3.6%
74
 
3.6%
74
 
3.6%
70
 
3.4%
69
 
3.3%
69
 
3.3%
66
 
3.2%
60
 
2.9%
54
 
2.6%
Other values (181) 1315
63.2%
Latin
ValueCountFrequency (%)
K 4
23.5%
S 3
17.6%
T 2
11.8%
C 2
11.8%
P 2
11.8%
H 1
 
5.9%
M 1
 
5.9%
D 1
 
5.9%
N 1
 
5.9%
Common
ValueCountFrequency (%)
121
50.4%
, 43
 
17.9%
( 35
 
14.6%
) 35
 
14.6%
2 2
 
0.8%
3 2
 
0.8%
9 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2049
87.7%
ASCII 257
 
11.0%
None 31
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
154
 
7.5%
75
 
3.7%
74
 
3.6%
74
 
3.6%
70
 
3.4%
69
 
3.4%
69
 
3.4%
66
 
3.2%
60
 
2.9%
54
 
2.6%
Other values (180) 1284
62.7%
ASCII
ValueCountFrequency (%)
121
47.1%
, 43
 
16.7%
( 35
 
13.6%
) 35
 
13.6%
K 4
 
1.6%
S 3
 
1.2%
T 2
 
0.8%
C 2
 
0.8%
2 2
 
0.8%
3 2
 
0.8%
Other values (6) 8
 
3.1%
None
ValueCountFrequency (%)
31
100.0%

Interactions

2024-04-06T17:18:52.459795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-06T17:18:52.698347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:18:52.868766image/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

연도연구용역명수행기관
02015하수 처리수의 공정용수 활용을 위한 최적화 방안 도출성균관대 산학협력단, ㈜세원
12015열손실 저감용 단열페인트의 지역난방 설비 적용방안 연구서울대학교 산학협력단
22015열사용시설의 적정 효율평가 기법 수립 연구수원대학교 산학협력단
32015지역난방(DH) 펌프의 운영실태 분석을 통한 최적운영방안 도출 연구한국생산기술연구원
42015바이오매스 이용 열분해 바이오오일 생산 최적화 기술개발 및 활용방안 연구생산기술연구원, 서울시립대
52015고온형 대용량 축열조 기술개발 연구에너지기술연구원
62015지역난방 2차측 자동제어시스템 표준모델 개발에 관한 연구㈜현암바씨스, 전자부품연구원
72015전과정(LCA) 기법을 통한 온실가스 배출량 분석 연구 용역솔루티스
82015광물탄산화 기술을 통한 배가스 내 CO2 제거 및 부산물 활용방안 연구공주대학교 산학협력단
920152차측 배관 보온재 사양 및 시공 개선에 관한 연구㈜피앤아이
연도연구용역명수행기관
1782023CHP 건식탈황설비 환원제 고착화 방지 대책 수립 연구고등기술연구원연구조합
1792023대구지사 매립가스 현황분석 및 안정적 관리방안 수립 연구유진에너지기술 주식회사
1802023운영 중인 열수송관의 보온재 내구성 평가방안 연구한양대학교 에리카산학협력단
18120232050 탄소중립 단계적 이행을 위한 상생형 탄소 감축사업 개발 1단계 연구 용역재단법인 한국기후변화연구원
1822023지역난방용 이중보온관 KS 표준화 연구(재)한국건설생활환경시험연구원
1832023수소도시 비즈니스 모델 개발과 수소 기반 집단에너지 플랫폼 연계방안 수립연구주식회사 더포스엣지
1842023제로에너지주택과 지역난방의 연계확대를 위한 제도개선 연구주식회사 우원엠앤이
1852023매설환경요인에 따른 열수송관의 외부부식 영향 연구성균관대학교 산학협력단
1862023SIEMENS SGT6-3000E GT Interstage Seal Housing Assembly 국산화 개발터보파워텍㈜
1872023미활용 수열에너지를 이용한 지역냉난방 공급방안 및 활용전략 연구가천대학교산학협력단, 지엔원에너지㈜