Overview

Dataset statistics

Number of variables6
Number of observations168
Missing cells29
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory48.8 B

Variable types

DateTime3
Text3

Dataset

Description한국가스공사의 연구과제 수행보고고서에 관한 데이터로 발행연월, 국문과제명, 영문과제명, 연구책임자, 시작일, 종료일의 속성정보를 포함하고 있습니다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15040811/fileData.do

Alerts

영문과제명 has 28 (16.7%) missing valuesMissing
국문과제명 has unique valuesUnique

Reproduction

Analysis started2024-01-06 13:13:06.726281
Analysis finished2024-01-06 13:13:09.645718
Duration2.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발행년월
Date

Distinct80
Distinct (%)47.9%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
Minimum2016-04-16 00:00:00
Maximum2023-12-31 00:00:00
2024-01-06T13:13:09.955241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:13:10.448184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

국문과제명
Text

UNIQUE 

Distinct168
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-06T13:13:11.641716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length46
Mean length30.047619
Min length10

Characters and Unicode

Total characters5048
Distinct characters389
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique168 ?
Unique (%)100.0%

Sample

1st row주방공간에 조리시 발생되는 유해물질 검증
2nd row5KW급 연료전지용 연료처리장치 모듈 개발 및 실증
3rd rowGTL Pilot 플랜트 운영 및 기술 고도화
4th row가스엔진을 이용한 TriGeneration 개발
5th row산업용 열량 민감 가스기기(GHP) 대응기술 현장적용 연구
ValueCountFrequency (%)
및 56
 
4.7%
연구 55
 
4.6%
개발 29
 
2.4%
위한 27
 
2.3%
lng 22
 
1.8%
방안 14
 
1.2%
천연가스 14
 
1.2%
기술개발 13
 
1.1%
분석 12
 
1.0%
기술 11
 
0.9%
Other values (697) 939
78.8%
2024-01-06T13:13:13.287922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1025
 
20.3%
기 156
 
3.1%
연 105
 
2.1%
구 90
 
1.8%
가 84
 
1.7%
스 83
 
1.6%
개 67
 
1.3%
용 67
 
1.3%
발 58
 
1.1%
한 57
 
1.1%
Other values (379) 3256
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3473
68.8%
Space Separator 1025
 
20.3%
Uppercase Letter 285
 
5.6%
Lowercase Letter 126
 
2.5%
Close Punctuation 37
 
0.7%
Open Punctuation 37
 
0.7%
Decimal Number 36
 
0.7%
Dash Punctuation 15
 
0.3%
Other Punctuation 13
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 156
 
4.5%
연 105
 
3.0%
구 90
 
2.6%
가 84
 
2.4%
스 83
 
2.4%
개 67
 
1.9%
용 67
 
1.9%
발 58
 
1.7%
한 57
 
1.6%
및 56
 
1.6%
Other values (317) 2650
76.3%
Lowercase Letter
ValueCountFrequency (%)
n 17
13.5%
e 16
12.7%
i 15
11.9%
o 12
9.5%
r 10
 
7.9%
t 9
 
7.1%
a 7
 
5.6%
s 6
 
4.8%
d 4
 
3.2%
k 4
 
3.2%
Other values (12) 26
20.6%
Uppercase Letter
ValueCountFrequency (%)
G 49
17.2%
N 46
16.1%
L 46
16.1%
S 19
 
6.7%
O 14
 
4.9%
C 13
 
4.6%
K 12
 
4.2%
T 10
 
3.5%
R 10
 
3.5%
M 9
 
3.2%
Other values (11) 57
20.0%
Decimal Number
ValueCountFrequency (%)
2 8
22.2%
1 7
19.4%
3 7
19.4%
0 4
11.1%
4 4
11.1%
6 2
 
5.6%
8 2
 
5.6%
7 1
 
2.8%
5 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 4
30.8%
# 3
23.1%
· 3
23.1%
/ 2
15.4%
: 1
 
7.7%
Space Separator
ValueCountFrequency (%)
1025
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3473
68.8%
Common 1164
 
23.1%
Latin 411
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 156
 
4.5%
연 105
 
3.0%
구 90
 
2.6%
가 84
 
2.4%
스 83
 
2.4%
개 67
 
1.9%
용 67
 
1.9%
발 58
 
1.7%
한 57
 
1.6%
및 56
 
1.6%
Other values (317) 2650
76.3%
Latin
ValueCountFrequency (%)
G 49
 
11.9%
N 46
 
11.2%
L 46
 
11.2%
S 19
 
4.6%
n 17
 
4.1%
e 16
 
3.9%
i 15
 
3.6%
O 14
 
3.4%
C 13
 
3.2%
K 12
 
2.9%
Other values (33) 164
39.9%
Common
ValueCountFrequency (%)
1025
88.1%
) 37
 
3.2%
( 37
 
3.2%
- 15
 
1.3%
2 8
 
0.7%
1 7
 
0.6%
3 7
 
0.6%
, 4
 
0.3%
0 4
 
0.3%
4 4
 
0.3%
Other values (9) 16
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3473
68.8%
ASCII 1572
31.1%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1025
65.2%
G 49
 
3.1%
N 46
 
2.9%
L 46
 
2.9%
) 37
 
2.4%
( 37
 
2.4%
S 19
 
1.2%
n 17
 
1.1%
e 16
 
1.0%
i 15
 
1.0%
Other values (51) 265
 
16.9%
Hangul
ValueCountFrequency (%)
기 156
 
4.5%
연 105
 
3.0%
구 90
 
2.6%
가 84
 
2.4%
스 83
 
2.4%
개 67
 
1.9%
용 67
 
1.9%
발 58
 
1.7%
한 57
 
1.6%
및 56
 
1.6%
Other values (317) 2650
76.3%
None
ValueCountFrequency (%)
· 3
100.0%

영문과제명
Text

MISSING 

Distinct138
Distinct (%)98.6%
Missing28
Missing (%)16.7%
Memory size1.4 KiB
2024-01-06T13:13:14.023557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length179
Median length102
Mean length82.421429
Min length27

Characters and Unicode

Total characters11539
Distinct characters74
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)97.1%

Sample

1st rowVerification of hazardous air pollutants during cooking in kitchen
2nd rowDevelopment and Demonstration of 5㎾ Fuel Processor module
3rd rowDevelopment on Improvement of Operating Technology for GTL Pilot Plant
4th rowThe development of TriGeneration system driven by Gas Engine
5th rowField supervision and applying combustion control technology for sensitive GHP from variation in gas quality
ValueCountFrequency (%)
of 141
 
8.4%
for 78
 
4.6%
the 63
 
3.7%
and 56
 
3.3%
lng 48
 
2.8%
on 45
 
2.7%
gas 43
 
2.5%
development 41
 
2.4%
a 37
 
2.2%
study 37
 
2.2%
Other values (571) 1098
65.1%
2024-01-06T13:13:15.593275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1551
13.4%
e 1039
 
9.0%
n 847
 
7.3%
o 812
 
7.0%
a 749
 
6.5%
t 734
 
6.4%
i 714
 
6.2%
r 567
 
4.9%
s 488
 
4.2%
l 429
 
3.7%
Other values (64) 3609
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8985
77.9%
Space Separator 1551
 
13.4%
Uppercase Letter 891
 
7.7%
Dash Punctuation 35
 
0.3%
Decimal Number 35
 
0.3%
Other Punctuation 19
 
0.2%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%
Other Symbol 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1039
11.6%
n 847
 
9.4%
o 812
 
9.0%
a 749
 
8.3%
t 734
 
8.2%
i 714
 
7.9%
r 567
 
6.3%
s 488
 
5.4%
l 429
 
4.8%
f 319
 
3.6%
Other values (16) 2287
25.5%
Uppercase Letter
ValueCountFrequency (%)
S 88
 
9.9%
G 85
 
9.5%
T 72
 
8.1%
N 68
 
7.6%
A 65
 
7.3%
L 64
 
7.2%
D 58
 
6.5%
P 55
 
6.2%
C 45
 
5.1%
E 41
 
4.6%
Other values (13) 250
28.1%
Decimal Number
ValueCountFrequency (%)
2 10
28.6%
3 7
20.0%
1 6
17.1%
0 4
 
11.4%
8 2
 
5.7%
6 2
 
5.7%
4 2
 
5.7%
5 1
 
2.9%
7 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
' 4
21.1%
# 3
15.8%
, 3
15.8%
/ 3
15.8%
" 2
10.5%
& 2
10.5%
· 1
 
5.3%
: 1
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 34
97.1%
― 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1551
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Symbol
ValueCountFrequency (%)
㎾ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9877
85.6%
Common 1662
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1039
 
10.5%
n 847
 
8.6%
o 812
 
8.2%
a 749
 
7.6%
t 734
 
7.4%
i 714
 
7.2%
r 567
 
5.7%
s 488
 
4.9%
l 429
 
4.3%
f 319
 
3.2%
Other values (40) 3179
32.2%
Common
ValueCountFrequency (%)
1551
93.3%
- 34
 
2.0%
( 10
 
0.6%
) 10
 
0.6%
2 10
 
0.6%
3 7
 
0.4%
1 6
 
0.4%
' 4
 
0.2%
0 4
 
0.2%
# 3
 
0.2%
Other values (14) 23
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11534
> 99.9%
CJK Compat 1
 
< 0.1%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%
Punctuation 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1551
13.4%
e 1039
 
9.0%
n 847
 
7.3%
o 812
 
7.0%
a 749
 
6.5%
t 734
 
6.4%
i 714
 
6.2%
r 567
 
4.9%
s 488
 
4.2%
l 429
 
3.7%
Other values (59) 3604
31.2%
CJK Compat
ValueCountFrequency (%)
㎾ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Punctuation
ValueCountFrequency (%)
― 1
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

연구책임자
Text

Distinct131
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-06T13:13:16.447548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length3.0595238
Min length2

Characters and Unicode

Total characters514
Distinct characters120
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)61.3%

Sample

1st row이준규
2nd row김재동
3rd row권옥배
4th row채정민
5th row이중성
ValueCountFrequency (%)
최성희 5
 
2.9%
김준휘 4
 
2.4%
손영순 3
 
1.8%
오영삼 3
 
1.8%
이철구 3
 
1.8%
고재필 3
 
1.8%
주우성 2
 
1.2%
이철진 2
 
1.2%
유휘용 2
 
1.2%
김기동 2
 
1.2%
Other values (122) 141
82.9%
2024-01-06T13:13:17.967109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 36
 
7.0%
이 33
 
6.4%
영 20
 
3.9%
성 18
 
3.5%
정 16
 
3.1%
철 15
 
2.9%
최 10
 
1.9%
호 10
 
1.9%
용 10
 
1.9%
수 10
 
1.9%
Other values (110) 336
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 500
97.3%
Lowercase Letter 9
 
1.8%
Uppercase Letter 3
 
0.6%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 36
 
7.2%
이 33
 
6.6%
영 20
 
4.0%
성 18
 
3.6%
정 16
 
3.2%
철 15
 
3.0%
최 10
 
2.0%
호 10
 
2.0%
용 10
 
2.0%
수 10
 
2.0%
Other values (101) 322
64.4%
Lowercase Letter
ValueCountFrequency (%)
n 3
33.3%
a 2
22.2%
e 1
 
11.1%
y 1
 
11.1%
u 1
 
11.1%
g 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
T 2
66.7%
N 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 500
97.3%
Latin 12
 
2.3%
Common 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 36
 
7.2%
이 33
 
6.6%
영 20
 
4.0%
성 18
 
3.6%
정 16
 
3.2%
철 15
 
3.0%
최 10
 
2.0%
호 10
 
2.0%
용 10
 
2.0%
수 10
 
2.0%
Other values (101) 322
64.4%
Latin
ValueCountFrequency (%)
n 3
25.0%
T 2
16.7%
a 2
16.7%
e 1
 
8.3%
y 1
 
8.3%
u 1
 
8.3%
g 1
 
8.3%
N 1
 
8.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 500
97.3%
ASCII 14
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 36
 
7.2%
이 33
 
6.6%
영 20
 
4.0%
성 18
 
3.6%
정 16
 
3.2%
철 15
 
3.0%
최 10
 
2.0%
호 10
 
2.0%
용 10
 
2.0%
수 10
 
2.0%
Other values (101) 322
64.4%
ASCII
ValueCountFrequency (%)
n 3
21.4%
2
14.3%
T 2
14.3%
a 2
14.3%
e 1
 
7.1%
y 1
 
7.1%
u 1
 
7.1%
g 1
 
7.1%
N 1
 
7.1%

시작일
Date

Distinct71
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2011-05-01 00:00:00
Maximum2023-05-01 00:00:00
2024-01-06T13:13:18.422528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:13:18.964813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종료일
Date

Distinct59
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2016-05-08 00:00:00
Maximum2023-12-31 00:00:00
2024-01-06T13:13:19.592452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:13:20.298909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2024-01-06T13:13:20.614292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발행년월시작일종료일
발행년월1.0000.9990.999
시작일0.9991.0000.997
종료일0.9990.9971.000

Missing values

2024-01-06T13:13:08.803207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T13:13:09.200099image/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.
2024-01-06T13:13:09.498283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

발행년월국문과제명영문과제명연구책임자시작일종료일
02017-01-03주방공간에 조리시 발생되는 유해물질 검증Verification of hazardous air pollutants during cooking in kitchen이준규2015-12-092016-05-08
12018-02-265KW급 연료전지용 연료처리장치 모듈 개발 및 실증Development and Demonstration of 5㎾ Fuel Processor module김재동2013-09-012016-08-31
22016-12-29GTL Pilot 플랜트 운영 및 기술 고도화Development on Improvement of Operating Technology for GTL Pilot Plant권옥배2014-06-012016-11-30
32017-02-15가스엔진을 이용한 TriGeneration 개발The development of TriGeneration system driven by Gas Engine채정민2013-05-012016-11-30
42017-02-09산업용 열량 민감 가스기기(GHP) 대응기술 현장적용 연구Field supervision and applying combustion control technology for sensitive GHP from variation in gas quality이중성2013-05-012016-12-30
52017-01-18가스배관 보수절차 고도화 및 최적화방안 수립Establishment of upgrade and optimum selection method for gas pipeline repair김우식2014-05-012016-12-31
62017-01-18가스설비 내진성능평가 기술 개발Development of seismic performance evaluation techniques for gas facilities김준호2012-10-012016-12-31
72017-01-18가스배관 유지관리에 신뢰도기반평가 적용 연구A study on reliability based assessment application for maintenance and protection decision in gas pipeline김철만2015-07-012016-12-31
82017-06-27KOGAS 수소 제조시스템 개발 기획 연구A Study on Development Planning for KOGAS Hydrogen Production System김형식2016-04-012017-02-28
92017-06-22육상용 LNG플랜트 Pre-FEED 기술개발 연구(1단계)A study on the technology development of Pre-FEED at onshore LNG liquefaction plant (Stage 1)이철구2016-06-012017-04-30
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