Overview

Dataset statistics

Number of variables10
Number of observations489
Missing cells1754
Missing cells (%)35.9%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory38.3 KiB
Average record size in memory80.3 B

Variable types

Text5
Categorical4
DateTime1

Dataset

Description한전 전력연구원 지식재산 정보 입니다.
Author한국전력공사
URLhttps://www.data.go.kr/data/15040225/fileData.do

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates
결재상태 is highly overall correlated with 발표국가 and 2 other fieldsHigh correlation
발표구분 is highly overall correlated with 발표국가 and 2 other fieldsHigh correlation
발표국가 is highly overall correlated with 발표구분 and 1 other fieldsHigh correlation
SCI구분 is highly overall correlated with 발표구분 and 1 other fieldsHigh correlation
관리번호 has 289 (59.1%) missing valuesMissing
논문제목 has 289 (59.1%) missing valuesMissing
주저자 has 289 (59.1%) missing valuesMissing
학술지명 has 291 (59.5%) missing valuesMissing
발표일자 has 289 (59.1%) missing valuesMissing
과제번호 has 307 (62.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 14:20:07.197972
Analysis finished2023-12-12 14:20:08.262800
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

MISSING 

Distinct200
Distinct (%)100.0%
Missing289
Missing (%)59.1%
Memory size3.9 KiB
2023-12-12T23:20:08.480766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters2200
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)100.0%

Sample

1st rowPP201500253
2nd rowPP201700049
3rd rowPP201700076
4th rowPP201800097
5th rowPP201700014
ValueCountFrequency (%)
pp201900017 1
 
0.5%
pp201600089 1
 
0.5%
pp201800091 1
 
0.5%
pp201900019 1
 
0.5%
pp201900108 1
 
0.5%
pp201700020 1
 
0.5%
pp201700096 1
 
0.5%
pp201600046 1
 
0.5%
pp201600048 1
 
0.5%
pp201600104 1
 
0.5%
Other values (190) 190
95.0%
2023-12-12T23:20:08.995610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 769
35.0%
P 400
18.2%
1 306
 
13.9%
2 241
 
11.0%
8 95
 
4.3%
7 94
 
4.3%
6 91
 
4.1%
9 75
 
3.4%
4 46
 
2.1%
5 45
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1800
81.8%
Uppercase Letter 400
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 769
42.7%
1 306
 
17.0%
2 241
 
13.4%
8 95
 
5.3%
7 94
 
5.2%
6 91
 
5.1%
9 75
 
4.2%
4 46
 
2.6%
5 45
 
2.5%
3 38
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
P 400
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1800
81.8%
Latin 400
 
18.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 769
42.7%
1 306
 
17.0%
2 241
 
13.4%
8 95
 
5.3%
7 94
 
5.2%
6 91
 
5.1%
9 75
 
4.2%
4 46
 
2.6%
5 45
 
2.5%
3 38
 
2.1%
Latin
ValueCountFrequency (%)
P 400
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 769
35.0%
P 400
18.2%
1 306
 
13.9%
2 241
 
11.0%
8 95
 
4.3%
7 94
 
4.3%
6 91
 
4.1%
9 75
 
3.4%
4 46
 
2.1%
5 45
 
2.0%

발표국가
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
289 
국내
137 
국외
63 

Length

Max length4
Median length4
Mean length3.1820041
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국외
2nd row국내
3rd row국내
4th row국내
5th row국내

Common Values

ValueCountFrequency (%)
<NA> 289
59.1%
국내 137
28.0%
국외 63
 
12.9%

Length

2023-12-12T23:20:09.157598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:09.283043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
59.1%
국내 137
28.0%
국외 63
 
12.9%

발표구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
289 
SCIE
53 
KCI
45 
SCI
36 
KEPCO 저널
32 
Other values (3)
34 

Length

Max length8
Median length4
Mean length4.0940695
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row학술지
2nd rowSCIE
3rd rowKCI
4th rowKCI
5th rowKCI

Common Values

ValueCountFrequency (%)
<NA> 289
59.1%
SCIE 53
 
10.8%
KCI 45
 
9.2%
SCI 36
 
7.4%
KEPCO 저널 32
 
6.5%
기타국내 19
 
3.9%
기타국외 14
 
2.9%
학술지 1
 
0.2%

Length

2023-12-12T23:20:09.396202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:09.499254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
55.5%
scie 53
 
10.2%
kci 45
 
8.6%
sci 36
 
6.9%
kepco 32
 
6.1%
저널 32
 
6.1%
기타국내 19
 
3.6%
기타국외 14
 
2.7%
학술지 1
 
0.2%

SCI구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
289 
SCIE
87 
일반
85 
SCI
 
21
학술대회
 
4
Other values (2)
 
3

Length

Max length4
Median length4
Mean length3.601227
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row일반
2nd rowSCIE
3rd row일반
4th rowKCI
5th row일반

Common Values

ValueCountFrequency (%)
<NA> 289
59.1%
SCIE 87
 
17.8%
일반 85
 
17.4%
SCI 21
 
4.3%
학술대회 4
 
0.8%
KCI 2
 
0.4%
기타 1
 
0.2%

Length

2023-12-12T23:20:09.624744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:09.733884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
59.1%
scie 87
 
17.8%
일반 85
 
17.4%
sci 21
 
4.3%
학술대회 4
 
0.8%
kci 2
 
0.4%
기타 1
 
0.2%

논문제목
Text

MISSING 

Distinct199
Distinct (%)99.5%
Missing289
Missing (%)59.1%
Memory size3.9 KiB
2023-12-12T23:20:10.005523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length167
Median length101
Mean length61.05
Min length11

Characters and Unicode

Total characters12210
Distinct characters420
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)99.0%

Sample

1st row국내 풍력변동성을 고려한 장기 에너지저장장치 소요용량에 관한 연구
2nd row전력용 변압기 자산관리를 위한 경년열화와 관련된 DGA 가스에 관한 연구
3rd row주파수조정용 에너지저장장치 시운전 자동화 시스템의 개발과 실증
4th row고온수소전환반응기에 관한 수치해석적 연구
5th row해상기상탑과 윈드 라이다의 높이별 풍황관측자료 비교
ValueCountFrequency (%)
of 84
 
4.1%
for 40
 
2.0%
in 26
 
1.3%
및 26
 
1.3%
and 26
 
1.3%
연구 25
 
1.2%
power 25
 
1.2%
on 23
 
1.1%
a 22
 
1.1%
the 22
 
1.1%
Other values (1133) 1730
84.4%
2023-12-12T23:20:10.446445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1864
 
15.3%
e 692
 
5.7%
o 659
 
5.4%
i 559
 
4.6%
n 547
 
4.5%
t 536
 
4.4%
r 517
 
4.2%
a 484
 
4.0%
s 375
 
3.1%
l 281
 
2.3%
Other values (410) 5696
46.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6474
53.0%
Other Letter 2650
21.7%
Space Separator 1864
 
15.3%
Uppercase Letter 966
 
7.9%
Decimal Number 131
 
1.1%
Dash Punctuation 67
 
0.5%
Other Punctuation 33
 
0.3%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%
Math Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 77
 
2.9%
의 65
 
2.5%
전 64
 
2.4%
기 58
 
2.2%
이 56
 
2.1%
에 53
 
2.0%
연 46
 
1.7%
용 46
 
1.7%
가 42
 
1.6%
성 41
 
1.5%
Other values (331) 2102
79.3%
Lowercase Letter
ValueCountFrequency (%)
e 692
10.7%
o 659
10.2%
i 559
 
8.6%
n 547
 
8.4%
t 536
 
8.3%
r 517
 
8.0%
a 484
 
7.5%
s 375
 
5.8%
l 281
 
4.3%
c 247
 
3.8%
Other values (19) 1577
24.4%
Uppercase Letter
ValueCountFrequency (%)
C 120
12.4%
S 112
11.6%
P 72
 
7.5%
D 71
 
7.3%
A 69
 
7.1%
M 57
 
5.9%
T 55
 
5.7%
E 48
 
5.0%
F 45
 
4.7%
I 44
 
4.6%
Other values (15) 273
28.3%
Decimal Number
ValueCountFrequency (%)
2 30
22.9%
0 23
17.6%
1 22
16.8%
5 18
13.7%
4 13
9.9%
3 12
 
9.2%
6 5
 
3.8%
8 4
 
3.1%
7 2
 
1.5%
9 2
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 9
27.3%
/ 8
24.2%
, 7
21.2%
: 4
12.1%
& 3
 
9.1%
* 1
 
3.0%
· 1
 
3.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
± 1
33.3%
Space Separator
ValueCountFrequency (%)
1864
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7437
60.9%
Hangul 2650
 
21.7%
Common 2120
 
17.4%
Greek 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 77
 
2.9%
의 65
 
2.5%
전 64
 
2.4%
기 58
 
2.2%
이 56
 
2.1%
에 53
 
2.0%
연 46
 
1.7%
용 46
 
1.7%
가 42
 
1.6%
성 41
 
1.5%
Other values (331) 2102
79.3%
Latin
ValueCountFrequency (%)
e 692
 
9.3%
o 659
 
8.9%
i 559
 
7.5%
n 547
 
7.4%
t 536
 
7.2%
r 517
 
7.0%
a 484
 
6.5%
s 375
 
5.0%
l 281
 
3.8%
c 247
 
3.3%
Other values (41) 2540
34.2%
Common
ValueCountFrequency (%)
1864
87.9%
- 67
 
3.2%
2 30
 
1.4%
0 23
 
1.1%
1 22
 
1.0%
5 18
 
0.8%
4 13
 
0.6%
3 12
 
0.6%
( 10
 
0.5%
) 10
 
0.5%
Other values (15) 51
 
2.4%
Greek
ValueCountFrequency (%)
δ 1
33.3%
α 1
33.3%
γ 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9553
78.2%
Hangul 2650
 
21.7%
None 5
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1864
19.5%
e 692
 
7.2%
o 659
 
6.9%
i 559
 
5.9%
n 547
 
5.7%
t 536
 
5.6%
r 517
 
5.4%
a 484
 
5.1%
s 375
 
3.9%
l 281
 
2.9%
Other values (62) 3039
31.8%
Hangul
ValueCountFrequency (%)
한 77
 
2.9%
의 65
 
2.5%
전 64
 
2.4%
기 58
 
2.2%
이 56
 
2.1%
에 53
 
2.0%
연 46
 
1.7%
용 46
 
1.7%
가 42
 
1.6%
성 41
 
1.5%
Other values (331) 2102
79.3%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
None
ValueCountFrequency (%)
δ 1
20.0%
α 1
20.0%
γ 1
20.0%
± 1
20.0%
· 1
20.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

주저자
Text

MISSING 

Distinct109
Distinct (%)54.5%
Missing289
Missing (%)59.1%
Memory size3.9 KiB
2023-12-12T23:20:10.730491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters600
Distinct characters111
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)29.0%

Sample

1st row문승필
2nd row권동진
3rd row임건표
4th row서동균
5th row김지영
ValueCountFrequency (%)
최인혁 6
 
3.0%
박수만 5
 
2.5%
김재관 5
 
2.5%
이지현 4
 
2.0%
우상균 4
 
2.0%
문승필 4
 
2.0%
임건표 4
 
2.0%
김경숙 3
 
1.5%
백점인 3
 
1.5%
장병태 3
 
1.5%
Other values (99) 159
79.5%
2023-12-12T23:20:11.138207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 50
 
8.3%
이 21
 
3.5%
영 18
 
3.0%
상 16
 
2.7%
최 15
 
2.5%
현 15
 
2.5%
태 15
 
2.5%
성 14
 
2.3%
박 13
 
2.2%
용 13
 
2.2%
Other values (101) 410
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 600
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 50
 
8.3%
이 21
 
3.5%
영 18
 
3.0%
상 16
 
2.7%
최 15
 
2.5%
현 15
 
2.5%
태 15
 
2.5%
성 14
 
2.3%
박 13
 
2.2%
용 13
 
2.2%
Other values (101) 410
68.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 600
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 50
 
8.3%
이 21
 
3.5%
영 18
 
3.0%
상 16
 
2.7%
최 15
 
2.5%
현 15
 
2.5%
태 15
 
2.5%
성 14
 
2.3%
박 13
 
2.2%
용 13
 
2.2%
Other values (101) 410
68.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 600
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 50
 
8.3%
이 21
 
3.5%
영 18
 
3.0%
상 16
 
2.7%
최 15
 
2.5%
현 15
 
2.5%
태 15
 
2.5%
성 14
 
2.3%
박 13
 
2.2%
용 13
 
2.2%
Other values (101) 410
68.3%

학술지명
Text

MISSING 

Distinct85
Distinct (%)42.9%
Missing291
Missing (%)59.5%
Memory size3.9 KiB
2023-12-12T23:20:11.480000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length65
Mean length29.212121
Min length4

Characters and Unicode

Total characters5784
Distinct characters137
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)29.3%

Sample

1st rowIEEE TRANSACTIONS ON ENERGY CONVERSION
2nd rowKEPCO Journal on Electric Power and Energy
3rd row전기학회 논문지 P권
4th row한국 수소 및 신에너지 학회 논문집
5th row한국해안·해양공학회논문집
ValueCountFrequency (%)
journal 86
 
10.2%
and 82
 
9.7%
energy 69
 
8.2%
on 66
 
7.8%
power 63
 
7.5%
electric 59
 
7.0%
kepco 58
 
6.9%
of 32
 
3.8%
engineering 20
 
2.4%
electrical 16
 
1.9%
Other values (134) 294
34.8%
2023-12-12T23:20:12.063123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
694
 
12.0%
E 402
 
7.0%
n 352
 
6.1%
r 309
 
5.3%
e 279
 
4.8%
o 233
 
4.0%
a 190
 
3.3%
l 171
 
3.0%
c 170
 
2.9%
O 169
 
2.9%
Other values (127) 2815
48.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2405
41.6%
Uppercase Letter 2044
35.3%
Space Separator 694
 
12.0%
Other Letter 604
 
10.4%
Other Punctuation 23
 
0.4%
Decimal Number 8
 
0.1%
Dash Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 61
 
10.1%
회 57
 
9.4%
지 51
 
8.4%
문 45
 
7.5%
논 45
 
7.5%
전 33
 
5.5%
기 31
 
5.1%
한 28
 
4.6%
국 24
 
4.0%
집 18
 
3.0%
Other values (66) 211
34.9%
Uppercase Letter
ValueCountFrequency (%)
E 402
19.7%
O 169
 
8.3%
C 159
 
7.8%
N 155
 
7.6%
P 146
 
7.1%
I 125
 
6.1%
R 117
 
5.7%
A 115
 
5.6%
T 98
 
4.8%
J 87
 
4.3%
Other values (15) 471
23.0%
Lowercase Letter
ValueCountFrequency (%)
n 352
14.6%
r 309
12.8%
e 279
11.6%
o 233
9.7%
a 190
7.9%
l 171
7.1%
c 170
7.1%
i 124
 
5.2%
t 106
 
4.4%
g 85
 
3.5%
Other values (12) 386
16.0%
Other Punctuation
ValueCountFrequency (%)
& 12
52.2%
· 5
21.7%
; 3
 
13.0%
, 2
 
8.7%
/ 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
2 2
25.0%
0 2
25.0%
8 1
12.5%
7 1
12.5%
Space Separator
ValueCountFrequency (%)
694
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4449
76.9%
Common 731
 
12.6%
Hangul 604
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 61
 
10.1%
회 57
 
9.4%
지 51
 
8.4%
문 45
 
7.5%
논 45
 
7.5%
전 33
 
5.5%
기 31
 
5.1%
한 28
 
4.6%
국 24
 
4.0%
집 18
 
3.0%
Other values (66) 211
34.9%
Latin
ValueCountFrequency (%)
E 402
 
9.0%
n 352
 
7.9%
r 309
 
6.9%
e 279
 
6.3%
o 233
 
5.2%
a 190
 
4.3%
l 171
 
3.8%
c 170
 
3.8%
O 169
 
3.8%
C 159
 
3.6%
Other values (37) 2015
45.3%
Common
ValueCountFrequency (%)
694
94.9%
& 12
 
1.6%
· 5
 
0.7%
; 3
 
0.4%
- 2
 
0.3%
, 2
 
0.3%
( 2
 
0.3%
) 2
 
0.3%
1 2
 
0.3%
2 2
 
0.3%
Other values (4) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5175
89.5%
Hangul 604
 
10.4%
None 5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
694
 
13.4%
E 402
 
7.8%
n 352
 
6.8%
r 309
 
6.0%
e 279
 
5.4%
o 233
 
4.5%
a 190
 
3.7%
l 171
 
3.3%
c 170
 
3.3%
O 169
 
3.3%
Other values (50) 2206
42.6%
Hangul
ValueCountFrequency (%)
학 61
 
10.1%
회 57
 
9.4%
지 51
 
8.4%
문 45
 
7.5%
논 45
 
7.5%
전 33
 
5.5%
기 31
 
5.1%
한 28
 
4.6%
국 24
 
4.0%
집 18
 
3.0%
Other values (66) 211
34.9%
None
ValueCountFrequency (%)
· 5
100.0%

발표일자
Date

MISSING 

Distinct123
Distinct (%)61.5%
Missing289
Missing (%)59.1%
Memory size3.9 KiB
Minimum2016-06-01 00:00:00
Maximum2019-10-31 00:00:00
2023-12-12T23:20:12.301610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:12.517355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

결재상태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
289 
최종승인
200 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 289
59.1%
최종승인 200
40.9%

Length

2023-12-12T23:20:12.722876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:12.872571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
59.1%
최종승인 200
40.9%

과제번호
Text

MISSING 

Distinct121
Distinct (%)66.5%
Missing307
Missing (%)62.8%
Memory size3.9 KiB
2023-12-12T23:20:13.284316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.989011
Min length6

Characters and Unicode

Total characters1272
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)44.0%

Sample

1st rowR14TG01
2nd rowR16TA30
3rd rowR16TA13
4th rowR16EG04
5th rowR16EA02
ValueCountFrequency (%)
r16ta29 6
 
3.3%
r14gg03 4
 
2.2%
r15ta23 4
 
2.2%
r15ta19 3
 
1.6%
r16ta15 3
 
1.6%
r16ta30 3
 
1.6%
r15ta08 3
 
1.6%
r15vg01 3
 
1.6%
r14tg01 3
 
1.6%
r14vg04 3
 
1.6%
Other values (111) 147
80.8%
2023-12-12T23:20:13.938534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 261
20.5%
R 178
14.0%
0 153
12.0%
A 115
9.0%
G 90
 
7.1%
6 66
 
5.2%
4 58
 
4.6%
T 55
 
4.3%
5 48
 
3.8%
2 47
 
3.7%
Other values (16) 201
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 728
57.2%
Uppercase Letter 544
42.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 178
32.7%
A 115
21.1%
G 90
16.5%
T 55
 
10.1%
V 20
 
3.7%
D 19
 
3.5%
E 17
 
3.1%
S 12
 
2.2%
F 11
 
2.0%
I 7
 
1.3%
Other values (6) 20
 
3.7%
Decimal Number
ValueCountFrequency (%)
1 261
35.9%
0 153
21.0%
6 66
 
9.1%
4 58
 
8.0%
5 48
 
6.6%
2 47
 
6.5%
3 46
 
6.3%
8 19
 
2.6%
7 18
 
2.5%
9 12
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 728
57.2%
Latin 544
42.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 178
32.7%
A 115
21.1%
G 90
16.5%
T 55
 
10.1%
V 20
 
3.7%
D 19
 
3.5%
E 17
 
3.1%
S 12
 
2.2%
F 11
 
2.0%
I 7
 
1.3%
Other values (6) 20
 
3.7%
Common
ValueCountFrequency (%)
1 261
35.9%
0 153
21.0%
6 66
 
9.1%
4 58
 
8.0%
5 48
 
6.6%
2 47
 
6.5%
3 46
 
6.3%
8 19
 
2.6%
7 18
 
2.5%
9 12
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 261
20.5%
R 178
14.0%
0 153
12.0%
A 115
9.0%
G 90
 
7.1%
6 66
 
5.2%
4 58
 
4.6%
T 55
 
4.3%
5 48
 
3.8%
2 47
 
3.7%
Other values (16) 201
15.8%

Correlations

2023-12-12T23:20:14.049911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발표국가발표구분SCI구분학술지명
발표국가1.0000.6280.6870.988
발표구분0.6281.0000.7080.960
SCI구분0.6870.7081.0001.000
학술지명0.9880.9601.0001.000
2023-12-12T23:20:14.148759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결재상태발표구분발표국가SCI구분
결재상태1.0001.0001.0001.000
발표구분1.0001.0000.6690.520
발표국가1.0000.6691.0000.499
SCI구분1.0000.5200.4991.000
2023-12-12T23:20:14.524750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발표국가발표구분SCI구분결재상태
발표국가1.0000.6690.4991.000
발표구분0.6691.0000.5201.000
SCI구분0.4990.5201.0001.000
결재상태1.0001.0001.0001.000

Missing values

2023-12-12T23:20:07.824688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:20:07.971981image/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.
2023-12-12T23:20:08.145326image/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

관리번호발표국가발표구분SCI구분논문제목주저자학술지명발표일자결재상태과제번호
0PP201500253국외학술지일반국내 풍력변동성을 고려한 장기 에너지저장장치 소요용량에 관한 연구문승필IEEE TRANSACTIONS ON ENERGY CONVERSION2016-07-18최종승인R14TG01
1PP201700049국내SCIESCIE전력용 변압기 자산관리를 위한 경년열화와 관련된 DGA 가스에 관한 연구권동진KEPCO Journal on Electric Power and Energy2017-06-30최종승인R16TA30
2PP201700076국내KCI일반주파수조정용 에너지저장장치 시운전 자동화 시스템의 개발과 실증임건표전기학회 논문지 P권2017-09-29최종승인R16TA13
3PP201800097국내KCIKCI고온수소전환반응기에 관한 수치해석적 연구서동균한국 수소 및 신에너지 학회 논문집2018-09-10최종승인R16EG04
4PP201700014국내KCI일반해상기상탑과 윈드 라이다의 높이별 풍황관측자료 비교김지영한국해안·해양공학회논문집2017-02-28최종승인R16EA02
5PP201700006국외SCIESCIEEffect of Linearized Contact Spring in Track Dynamic System김정훈INTERNATIONAL JOURNAL OF STEEL STRUCTURES2016-12-31최종승인<NA>
6PP201800154국외SCISCIFour-channel ROSA module using a TFF-based CWDM DMUX for monitoring 22.9 kV XLPE cable joints정영범OPTICAL ENGINEERING2018-10-24최종승인R16DA21
7PP201600124국내SCI일반알칼리성 폐기물과 해수를 이용한 이산화탄소 포집 및 해양저장이정현Environmental Engineering Research2017-01-30최종승인R11VA01
8PP201600125국내기타국내일반Effect of pH on UV photodegradation of N-nitrosamines in water심재구한국물환경학회지2016-07-01최종승인R14VG04
9PP201600146국내SCIESCIE크기효과를 고려한 대형앵커의 인장강도 예측김강식COMPUTERS AND CONCRETE2016-10-31최종승인I04NJ12
관리번호발표국가발표구분SCI구분논문제목주저자학술지명발표일자결재상태과제번호
479<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
480<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
481<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
482<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
483<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
484<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
485<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
486<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
487<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
488<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

관리번호발표국가발표구분SCI구분논문제목주저자학술지명발표일자결재상태과제번호# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>289