Overview

Dataset statistics

Number of variables25
Number of observations213
Missing cells2291
Missing cells (%)43.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.9 KiB
Average record size in memory201.6 B

Variable types

Text23
DateTime1
Numeric1

Dataset

Description한국항공우주연구원에서 전년도 1년 동안 작성 및 발표한 논문과 발표실적에 대한 목록입니다. 해당 데이터가 보유한 컬럼은 아래와 같습니다. 컬럼 명: 관리번호, 발행일자, 학술지 명, 제목명(국문), 제목명(영문), 주저자, 총 저자 수, 국문키워드1~9, 영문키워드 1~9
Author한국항공우주연구원
URLhttps://www.data.go.kr/data/3043484/fileData.do

Alerts

영문키워드9 has constant value ""Constant
제목명(국문) has 38 (17.8%) missing valuesMissing
제목명(영문) has 4 (1.9%) missing valuesMissing
국문키워드1 has 61 (28.6%) missing valuesMissing
국문키워드2 has 68 (31.9%) missing valuesMissing
국문키워드3 has 70 (32.9%) missing valuesMissing
국문키워드4 has 94 (44.1%) missing valuesMissing
국문키워드5 has 131 (61.5%) missing valuesMissing
국문키워드6 has 184 (86.4%) missing valuesMissing
국문키워드7 has 205 (96.2%) missing valuesMissing
국문키워드8 has 210 (98.6%) missing valuesMissing
국문키워드9 has 211 (99.1%) missing valuesMissing
영문키워드1 has 10 (4.7%) missing valuesMissing
영문키워드2 has 24 (11.3%) missing valuesMissing
영문키워드3 has 25 (11.7%) missing valuesMissing
영문키워드4 has 54 (25.4%) missing valuesMissing
영문키워드5 has 107 (50.2%) missing valuesMissing
영문키워드6 has 175 (82.2%) missing valuesMissing
영문키워드7 has 198 (93.0%) missing valuesMissing
영문키워드8 has 210 (98.6%) missing valuesMissing
영문키워드9 has 212 (99.5%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:59:57.319839
Analysis finished2023-12-12 07:59:58.877653
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct213
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T16:59:59.083102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.13615
Min length20

Characters and Unicode

Total characters4502
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)100.0%

Sample

1st rowKARI-AIRS-RP-2021-001
2nd rowKARI-AIRS-RP-2021-002
3rd rowKARI-APRD-RP-2021-001
4th rowKARI-APRD-RP-2021-002
5th rowKARI-APRD-RP-2021-005
ValueCountFrequency (%)
kari-airs-rp-2021-001 1
 
0.5%
kari-pot-rp-2021-008 1
 
0.5%
kari-sad-rp-2021-055 1
 
0.5%
kari-samt-rp-2021-006 1
 
0.5%
kari-sast-rp-2021-001 1
 
0.5%
kari-sast-rp-2021-004 1
 
0.5%
kari-sast-rp-2021-005 1
 
0.5%
kari-sefst-rp-2020-072 1
 
0.5%
kari-sefst-rp-2020-073 1
 
0.5%
kari-sefst-rp-2021-008 1
 
0.5%
Other values (203) 203
95.3%
2023-12-12T16:59:59.540998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 852
18.9%
0 550
12.2%
R 503
11.2%
2 478
10.6%
A 302
 
6.7%
1 294
 
6.5%
P 263
 
5.8%
I 243
 
5.4%
K 226
 
5.0%
S 146
 
3.2%
Other values (23) 645
14.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2153
47.8%
Decimal Number 1494
33.2%
Dash Punctuation 852
 
18.9%
Other Punctuation 3
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 503
23.4%
A 302
14.0%
P 263
12.2%
I 243
11.3%
K 226
10.5%
S 146
 
6.8%
T 128
 
5.9%
D 127
 
5.9%
E 43
 
2.0%
C 40
 
1.9%
Other values (11) 132
 
6.1%
Decimal Number
ValueCountFrequency (%)
0 550
36.8%
2 478
32.0%
1 294
19.7%
3 45
 
3.0%
4 32
 
2.1%
5 26
 
1.7%
7 22
 
1.5%
6 20
 
1.3%
8 14
 
0.9%
9 13
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 852
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2349
52.2%
Latin 2153
47.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 503
23.4%
A 302
14.0%
P 263
12.2%
I 243
11.3%
K 226
10.5%
S 146
 
6.8%
T 128
 
5.9%
D 127
 
5.9%
E 43
 
2.0%
C 40
 
1.9%
Other values (11) 132
 
6.1%
Common
ValueCountFrequency (%)
- 852
36.3%
0 550
23.4%
2 478
20.3%
1 294
 
12.5%
3 45
 
1.9%
4 32
 
1.4%
5 26
 
1.1%
7 22
 
0.9%
6 20
 
0.9%
8 14
 
0.6%
Other values (2) 16
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4502
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 852
18.9%
0 550
12.2%
R 503
11.2%
2 478
10.6%
A 302
 
6.7%
1 294
 
6.5%
P 263
 
5.8%
I 243
 
5.4%
K 226
 
5.0%
S 146
 
3.2%
Other values (23) 645
14.3%

발행일자
Date

Distinct94
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2019-07-01 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T16:59:59.718783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:59:59.893877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

학술지명
Text

Distinct89
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T17:00:00.179469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length69
Mean length27.464789
Min length6

Characters and Unicode

Total characters5850
Distinct characters119
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)27.7%

Sample

1st rowSENSORS
2nd rowMonthly Notices of the Royal Astronomical Society
3rd rowEnergies
4th rowThe KSFM Journal of Fluid Machinery
5th rowJournal of the Korean Society of Propulsion Engineers
ValueCountFrequency (%)
of 80
 
10.1%
journal 69
 
8.7%
and 59
 
7.5%
the 25
 
3.2%
aerospace 25
 
3.2%
항공우주산업기술동향 23
 
2.9%
korean 23
 
2.9%
space 23
 
2.9%
society 21
 
2.7%
sciences 16
 
2.0%
Other values (141) 426
53.9%
2023-12-12T17:00:00.602259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
577
 
9.9%
n 485
 
8.3%
e 464
 
7.9%
o 419
 
7.2%
a 375
 
6.4%
i 297
 
5.1%
r 280
 
4.8%
c 235
 
4.0%
t 228
 
3.9%
s 203
 
3.5%
Other values (109) 2287
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3887
66.4%
Other Letter 767
 
13.1%
Uppercase Letter 588
 
10.1%
Space Separator 577
 
9.9%
Other Punctuation 24
 
0.4%
Decimal Number 4
 
0.1%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 55
 
7.2%
공 54
 
7.0%
학 54
 
7.0%
한 45
 
5.9%
지 45
 
5.9%
주 45
 
5.9%
우 45
 
5.9%
항 43
 
5.6%
기 37
 
4.8%
국 35
 
4.6%
Other values (52) 309
40.3%
Lowercase Letter
ValueCountFrequency (%)
n 485
12.5%
e 464
11.9%
o 419
10.8%
a 375
9.6%
i 297
7.6%
r 280
 
7.2%
c 235
 
6.0%
t 228
 
5.9%
s 203
 
5.2%
l 177
 
4.6%
Other values (15) 724
18.6%
Uppercase Letter
ValueCountFrequency (%)
S 109
18.5%
E 76
12.9%
A 70
11.9%
J 69
11.7%
T 61
10.4%
I 43
 
7.3%
K 26
 
4.4%
R 26
 
4.4%
P 20
 
3.4%
C 19
 
3.2%
Other values (12) 69
11.7%
Other Punctuation
ValueCountFrequency (%)
, 16
66.7%
· 3
 
12.5%
; 2
 
8.3%
& 2
 
8.3%
: 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
577
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4475
76.5%
Hangul 767
 
13.1%
Common 608
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 55
 
7.2%
공 54
 
7.0%
학 54
 
7.0%
한 45
 
5.9%
지 45
 
5.9%
주 45
 
5.9%
우 45
 
5.9%
항 43
 
5.6%
기 37
 
4.8%
국 35
 
4.6%
Other values (52) 309
40.3%
Latin
ValueCountFrequency (%)
n 485
 
10.8%
e 464
 
10.4%
o 419
 
9.4%
a 375
 
8.4%
i 297
 
6.6%
r 280
 
6.3%
c 235
 
5.3%
t 228
 
5.1%
s 203
 
4.5%
l 177
 
4.0%
Other values (37) 1312
29.3%
Common
ValueCountFrequency (%)
577
94.9%
, 16
 
2.6%
· 3
 
0.5%
- 3
 
0.5%
2 2
 
0.3%
; 2
 
0.3%
& 2
 
0.3%
1 1
 
0.2%
0 1
 
0.2%
: 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5080
86.8%
Hangul 767
 
13.1%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
577
 
11.4%
n 485
 
9.5%
e 464
 
9.1%
o 419
 
8.2%
a 375
 
7.4%
i 297
 
5.8%
r 280
 
5.5%
c 235
 
4.6%
t 228
 
4.5%
s 203
 
4.0%
Other values (46) 1517
29.9%
Hangul
ValueCountFrequency (%)
회 55
 
7.2%
공 54
 
7.0%
학 54
 
7.0%
한 45
 
5.9%
지 45
 
5.9%
주 45
 
5.9%
우 45
 
5.9%
항 43
 
5.6%
기 37
 
4.8%
국 35
 
4.6%
Other values (52) 309
40.3%
None
ValueCountFrequency (%)
· 3
100.0%

제목명(국문)
Text

MISSING 

Distinct175
Distinct (%)100.0%
Missing38
Missing (%)17.8%
Memory size1.8 KiB
2023-12-12T17:00:00.988189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length55
Mean length37.531429
Min length1

Characters and Unicode

Total characters6568
Distinct characters452
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

Unique175 ?
Unique (%)100.0%

Sample

1st row공평한 헝가리안 알고리즘을 이용한 에너지 효율적인 군집 형상 변경 방법
2nd rowConstruction of a far ultraviolet all sky map from an incomplete survey: Application of a deep learn
3rd row확장형 막냉각 홀의 배열과 밀도비가 열전달계수에 미치는 영향
4th row오픈 소스 CFD 코드를 이용한 터빈 노즐의 압축성 유동 해석
5th row소형 가스터빈엔진 고장모드 모사를 통한 제어로직 연구
ValueCountFrequency (%)
연구 36
 
2.5%
및 36
 
2.5%
이용한 20
 
1.4%
위한 20
 
1.4%
개발 18
 
1.2%
동향 16
 
1.1%
분석 13
 
0.9%
관한 12
 
0.8%
기반 10
 
0.7%
대한 10
 
0.7%
Other values (968) 1265
86.9%
2023-12-12T17:00:01.568035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1293
 
19.7%
e 131
 
2.0%
a 114
 
1.7%
o 102
 
1.6%
기 102
 
1.6%
한 100
 
1.5%
의 99
 
1.5%
n 97
 
1.5%
t 97
 
1.5%
i 90
 
1.4%
Other values (442) 4343
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3682
56.1%
Space Separator 1293
 
19.7%
Lowercase Letter 1150
 
17.5%
Uppercase Letter 332
 
5.1%
Decimal Number 43
 
0.7%
Dash Punctuation 31
 
0.5%
Other Punctuation 15
 
0.2%
Close Punctuation 11
 
0.2%
Open Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 102
 
2.8%
한 100
 
2.7%
의 99
 
2.7%
성 78
 
2.1%
용 67
 
1.8%
이 65
 
1.8%
시 60
 
1.6%
위 57
 
1.5%
상 54
 
1.5%
구 52
 
1.4%
Other values (373) 2948
80.1%
Lowercase Letter
ValueCountFrequency (%)
e 131
11.4%
a 114
9.9%
o 102
 
8.9%
n 97
 
8.4%
t 97
 
8.4%
i 90
 
7.8%
r 80
 
7.0%
s 57
 
5.0%
l 57
 
5.0%
c 55
 
4.8%
Other values (15) 270
23.5%
Uppercase Letter
ValueCountFrequency (%)
S 46
13.9%
A 45
13.6%
M 25
 
7.5%
T 21
 
6.3%
R 20
 
6.0%
P 20
 
6.0%
O 17
 
5.1%
D 17
 
5.1%
I 14
 
4.2%
C 13
 
3.9%
Other values (15) 94
28.3%
Decimal Number
ValueCountFrequency (%)
2 12
27.9%
0 7
16.3%
1 6
14.0%
5 5
11.6%
4 4
 
9.3%
3 4
 
9.3%
7 2
 
4.7%
9 1
 
2.3%
6 1
 
2.3%
8 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 8
53.3%
: 3
 
20.0%
/ 2
 
13.3%
. 1
 
6.7%
· 1
 
6.7%
Space Separator
ValueCountFrequency (%)
1293
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3682
56.1%
Latin 1482
22.6%
Common 1404
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 102
 
2.8%
한 100
 
2.7%
의 99
 
2.7%
성 78
 
2.1%
용 67
 
1.8%
이 65
 
1.8%
시 60
 
1.6%
위 57
 
1.5%
상 54
 
1.5%
구 52
 
1.4%
Other values (373) 2948
80.1%
Latin
ValueCountFrequency (%)
e 131
 
8.8%
a 114
 
7.7%
o 102
 
6.9%
n 97
 
6.5%
t 97
 
6.5%
i 90
 
6.1%
r 80
 
5.4%
s 57
 
3.8%
l 57
 
3.8%
c 55
 
3.7%
Other values (40) 602
40.6%
Common
ValueCountFrequency (%)
1293
92.1%
- 31
 
2.2%
2 12
 
0.9%
) 11
 
0.8%
( 11
 
0.8%
, 8
 
0.6%
0 7
 
0.5%
1 6
 
0.4%
5 5
 
0.4%
4 4
 
0.3%
Other values (9) 16
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3682
56.1%
ASCII 2885
43.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1293
44.8%
e 131
 
4.5%
a 114
 
4.0%
o 102
 
3.5%
n 97
 
3.4%
t 97
 
3.4%
i 90
 
3.1%
r 80
 
2.8%
s 57
 
2.0%
l 57
 
2.0%
Other values (58) 767
26.6%
Hangul
ValueCountFrequency (%)
기 102
 
2.8%
한 100
 
2.7%
의 99
 
2.7%
성 78
 
2.1%
용 67
 
1.8%
이 65
 
1.8%
시 60
 
1.6%
위 57
 
1.5%
상 54
 
1.5%
구 52
 
1.4%
Other values (373) 2948
80.1%
None
ValueCountFrequency (%)
· 1
100.0%

제목명(영문)
Text

MISSING 

Distinct209
Distinct (%)100.0%
Missing4
Missing (%)1.9%
Memory size1.8 KiB
2023-12-12T17:00:01.979600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length92
Mean length81.779904
Min length28

Characters and Unicode

Total characters17092
Distinct characters95
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

Unique209 ?
Unique (%)100.0%

Sample

1st rowEnergy-Efficient Swarming Flight Formation Transitions Using the Improved Fair Hungarian Algorithm
2nd rowConstruction of a far ultraviolet all sky map from an incomplete survey: Application of a deep learn
3rd rowThe Effect of Hole Arrangement and Density Ratio on the Heat Transfer Coefficient Augmentation of Fa
4th rowCompressible flow analysis of turbine-nozzle using open source CFD code
5th rowResearch of small gas turbine engine control logic by engine failure mode simulation
ValueCountFrequency (%)
of 182
 
7.6%
for 82
 
3.4%
the 69
 
2.9%
and 65
 
2.7%
a 51
 
2.1%
on 47
 
2.0%
using 38
 
1.6%
in 31
 
1.3%
analysis 29
 
1.2%
study 26
 
1.1%
Other values (977) 1771
74.1%
2023-12-12T17:00:02.519749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2202
 
12.9%
e 1460
 
8.5%
o 1168
 
6.8%
i 1118
 
6.5%
n 1110
 
6.5%
a 1090
 
6.4%
t 1083
 
6.3%
r 877
 
5.1%
s 716
 
4.2%
l 625
 
3.7%
Other values (85) 5643
33.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12742
74.5%
Space Separator 2202
 
12.9%
Uppercase Letter 1935
 
11.3%
Dash Punctuation 116
 
0.7%
Decimal Number 40
 
0.2%
Other Punctuation 22
 
0.1%
Other Letter 21
 
0.1%
Open Punctuation 5
 
< 0.1%
Final Punctuation 5
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1460
11.5%
o 1168
 
9.2%
i 1118
 
8.8%
n 1110
 
8.7%
a 1090
 
8.6%
t 1083
 
8.5%
r 877
 
6.9%
s 716
 
5.6%
l 625
 
4.9%
c 497
 
3.9%
Other values (16) 2998
23.5%
Uppercase Letter
ValueCountFrequency (%)
S 247
12.8%
A 208
 
10.7%
T 146
 
7.5%
C 136
 
7.0%
R 114
 
5.9%
P 112
 
5.8%
D 112
 
5.8%
E 102
 
5.3%
M 101
 
5.2%
I 93
 
4.8%
Other values (16) 564
29.1%
Other Letter
ValueCountFrequency (%)
술 1
 
4.8%
향 1
 
4.8%
동 1
 
4.8%
구 1
 
4.8%
연 1
 
4.8%
우 1
 
4.8%
기 1
 
4.8%
센 1
 
4.8%
독 1
 
4.8%
일 1
 
4.8%
Other values (11) 11
52.4%
Decimal Number
ValueCountFrequency (%)
2 11
27.5%
0 9
22.5%
1 6
15.0%
5 4
 
10.0%
3 3
 
7.5%
7 2
 
5.0%
4 2
 
5.0%
6 1
 
2.5%
8 1
 
2.5%
9 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 7
31.8%
. 5
22.7%
/ 4
18.2%
& 2
 
9.1%
: 2
 
9.1%
# 1
 
4.5%
' 1
 
4.5%
Space Separator
ValueCountFrequency (%)
2202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14677
85.9%
Common 2394
 
14.0%
Hangul 21
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1460
 
9.9%
o 1168
 
8.0%
i 1118
 
7.6%
n 1110
 
7.6%
a 1090
 
7.4%
t 1083
 
7.4%
r 877
 
6.0%
s 716
 
4.9%
l 625
 
4.3%
c 497
 
3.4%
Other values (42) 4933
33.6%
Common
ValueCountFrequency (%)
2202
92.0%
- 116
 
4.8%
2 11
 
0.5%
0 9
 
0.4%
, 7
 
0.3%
1 6
 
0.3%
. 5
 
0.2%
( 5
 
0.2%
’ 5
 
0.2%
) 4
 
0.2%
Other values (12) 24
 
1.0%
Hangul
ValueCountFrequency (%)
술 1
 
4.8%
향 1
 
4.8%
동 1
 
4.8%
구 1
 
4.8%
연 1
 
4.8%
우 1
 
4.8%
기 1
 
4.8%
센 1
 
4.8%
독 1
 
4.8%
일 1
 
4.8%
Other values (11) 11
52.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17066
99.8%
Hangul 21
 
0.1%
Punctuation 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2202
 
12.9%
e 1460
 
8.6%
o 1168
 
6.8%
i 1118
 
6.6%
n 1110
 
6.5%
a 1090
 
6.4%
t 1083
 
6.3%
r 877
 
5.1%
s 716
 
4.2%
l 625
 
3.7%
Other values (63) 5617
32.9%
Punctuation
ValueCountFrequency (%)
’ 5
100.0%
Hangul
ValueCountFrequency (%)
술 1
 
4.8%
향 1
 
4.8%
동 1
 
4.8%
구 1
 
4.8%
연 1
 
4.8%
우 1
 
4.8%
기 1
 
4.8%
센 1
 
4.8%
독 1
 
4.8%
일 1
 
4.8%
Other values (11) 11
52.4%

주저자
Text

Distinct181
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T17:00:02.918352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0093897
Min length2

Characters and Unicode

Total characters641
Distinct characters131
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

Unique156 ?
Unique (%)73.2%

Sample

1st row문성태
2nd row조영수
3rd row김영서
4th row강승환
5th row이경재
ValueCountFrequency (%)
김현기 6
 
2.8%
정승택 3
 
1.4%
황도순 3
 
1.4%
윤원근 3
 
1.4%
이승재 2
 
0.9%
이명준 2
 
0.9%
이나영 2
 
0.9%
김규동 2
 
0.9%
이상우 2
 
0.9%
이보영 2
 
0.9%
Other values (172) 187
87.4%
2023-12-12T17:00:03.394404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 49
 
7.6%
이 39
 
6.1%
영 22
 
3.4%
현 20
 
3.1%
성 17
 
2.7%
원 17
 
2.7%
재 16
 
2.5%
정 15
 
2.3%
석 15
 
2.3%
승 12
 
1.9%
Other values (121) 419
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 634
98.9%
Lowercase Letter 4
 
0.6%
Uppercase Letter 2
 
0.3%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 49
 
7.7%
이 39
 
6.2%
영 22
 
3.5%
현 20
 
3.2%
성 17
 
2.7%
원 17
 
2.7%
재 16
 
2.5%
정 15
 
2.4%
석 15
 
2.4%
승 12
 
1.9%
Other values (115) 412
65.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
u 1
25.0%
i 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
50.0%
W 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 634
98.9%
Latin 6
 
0.9%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 49
 
7.7%
이 39
 
6.2%
영 22
 
3.5%
현 20
 
3.2%
성 17
 
2.7%
원 17
 
2.7%
재 16
 
2.5%
정 15
 
2.4%
석 15
 
2.4%
승 12
 
1.9%
Other values (115) 412
65.0%
Latin
ValueCountFrequency (%)
e 2
33.3%
u 1
16.7%
X 1
16.7%
i 1
16.7%
W 1
16.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 634
98.9%
ASCII 7
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 49
 
7.7%
이 39
 
6.2%
영 22
 
3.5%
현 20
 
3.2%
성 17
 
2.7%
원 17
 
2.7%
재 16
 
2.5%
정 15
 
2.4%
석 15
 
2.4%
승 12
 
1.9%
Other values (115) 412
65.0%
ASCII
ValueCountFrequency (%)
e 2
28.6%
u 1
14.3%
X 1
14.3%
1
14.3%
i 1
14.3%
W 1
14.3%

총 저자 수
Real number (ℝ)

Distinct10
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6760563
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T17:00:03.540473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile7
Maximum10
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8437143
Coefficient of variation (CV)0.50154681
Kurtosis0.067998751
Mean3.6760563
Median Absolute Deviation (MAD)1
Skewness0.53076467
Sum783
Variance3.3992825
MonotonicityNot monotonic
2023-12-12T17:00:03.667881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 48
22.5%
3 41
19.2%
2 33
15.5%
5 30
14.1%
1 28
13.1%
6 16
 
7.5%
7 11
 
5.2%
8 4
 
1.9%
10 1
 
0.5%
9 1
 
0.5%
ValueCountFrequency (%)
1 28
13.1%
2 33
15.5%
3 41
19.2%
4 48
22.5%
5 30
14.1%
6 16
 
7.5%
7 11
 
5.2%
8 4
 
1.9%
9 1
 
0.5%
10 1
 
0.5%
ValueCountFrequency (%)
10 1
 
0.5%
9 1
 
0.5%
8 4
 
1.9%
7 11
 
5.2%
6 16
 
7.5%
5 30
14.1%
4 48
22.5%
3 41
19.2%
2 33
15.5%
1 28
13.1%

국문키워드1
Text

MISSING 

Distinct144
Distinct (%)94.7%
Missing61
Missing (%)28.6%
Memory size1.8 KiB
2023-12-12T17:00:03.981246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length6.4539474
Min length1

Characters and Unicode

Total characters981
Distinct characters280
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)91.4%

Sample

1st row가스터빈
2nd row전산유체역학
3rd row소형가스터빈
4th row직렬 하이브리드 시스템
5th row전기추진비행기
ValueCountFrequency (%)
딥러닝 4
 
1.7%
달 3
 
1.2%
시스템 3
 
1.2%
가스터빈 3
 
1.2%
발사체 3
 
1.2%
블레이드 2
 
0.8%
배터리 2
 
0.8%
우주탐사 2
 
0.8%
해상도 2
 
0.8%
제어 2
 
0.8%
Other values (203) 215
89.2%
2023-12-12T17:00:04.425953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
9.1%
기 24
 
2.4%
성 20
 
2.0%
스 19
 
1.9%
시 16
 
1.6%
도 15
 
1.5%
전 15
 
1.5%
사 14
 
1.4%
터 13
 
1.3%
위 12
 
1.2%
Other values (270) 744
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 791
80.6%
Space Separator 89
 
9.1%
Lowercase Letter 58
 
5.9%
Uppercase Letter 28
 
2.9%
Decimal Number 10
 
1.0%
Dash Punctuation 4
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 24
 
3.0%
성 20
 
2.5%
스 19
 
2.4%
시 16
 
2.0%
도 15
 
1.9%
전 15
 
1.9%
사 14
 
1.8%
터 13
 
1.6%
위 12
 
1.5%
이 12
 
1.5%
Other values (225) 631
79.8%
Lowercase Letter
ValueCountFrequency (%)
t 6
10.3%
o 6
10.3%
e 6
10.3%
r 6
10.3%
i 6
10.3%
l 4
 
6.9%
a 4
 
6.9%
u 3
 
5.2%
n 3
 
5.2%
s 2
 
3.4%
Other values (8) 12
20.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
10.7%
T 3
10.7%
A 3
10.7%
G 2
 
7.1%
M 2
 
7.1%
I 2
 
7.1%
L 2
 
7.1%
K 2
 
7.1%
P 1
 
3.6%
O 1
 
3.6%
Other values (7) 7
25.0%
Decimal Number
ValueCountFrequency (%)
5 2
20.0%
0 2
20.0%
1 2
20.0%
3 1
10.0%
9 1
10.0%
2 1
10.0%
6 1
10.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
\ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 791
80.6%
Common 104
 
10.6%
Latin 86
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 24
 
3.0%
성 20
 
2.5%
스 19
 
2.4%
시 16
 
2.0%
도 15
 
1.9%
전 15
 
1.9%
사 14
 
1.8%
터 13
 
1.6%
위 12
 
1.5%
이 12
 
1.5%
Other values (225) 631
79.8%
Latin
ValueCountFrequency (%)
t 6
 
7.0%
o 6
 
7.0%
e 6
 
7.0%
r 6
 
7.0%
i 6
 
7.0%
l 4
 
4.7%
a 4
 
4.7%
S 3
 
3.5%
u 3
 
3.5%
n 3
 
3.5%
Other values (25) 39
45.3%
Common
ValueCountFrequency (%)
89
85.6%
- 4
 
3.8%
5 2
 
1.9%
0 2
 
1.9%
1 2
 
1.9%
3 1
 
1.0%
9 1
 
1.0%
2 1
 
1.0%
\ 1
 
1.0%
6 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 791
80.6%
ASCII 190
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
46.8%
t 6
 
3.2%
o 6
 
3.2%
e 6
 
3.2%
r 6
 
3.2%
i 6
 
3.2%
l 4
 
2.1%
- 4
 
2.1%
a 4
 
2.1%
S 3
 
1.6%
Other values (35) 56
29.5%
Hangul
ValueCountFrequency (%)
기 24
 
3.0%
성 20
 
2.5%
스 19
 
2.4%
시 16
 
2.0%
도 15
 
1.9%
전 15
 
1.9%
사 14
 
1.8%
터 13
 
1.6%
위 12
 
1.5%
이 12
 
1.5%
Other values (225) 631
79.8%

국문키워드2
Text

MISSING 

Distinct140
Distinct (%)96.6%
Missing68
Missing (%)31.9%
Memory size1.8 KiB
2023-12-12T17:00:04.700771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.1448276
Min length2

Characters and Unicode

Total characters891
Distinct characters278
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)93.8%

Sample

1st row막냉각
2nd row가스터빈엔진
3rd row고장탐구
4th row왕복엔진
5th row모터
ValueCountFrequency (%)
액체로켓엔진 4
 
1.9%
천리안 2
 
0.9%
무인기 2
 
0.9%
위성 2
 
0.9%
항공기 2
 
0.9%
막냉각 2
 
0.9%
위상차 2
 
0.9%
위성영상 2
 
0.9%
지상기반보강시스템 1
 
0.5%
원격측정데이터 1
 
0.5%
Other values (192) 192
90.6%
2023-12-12T17:00:05.097834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
 
7.5%
기 27
 
3.0%
성 18
 
2.0%
스 17
 
1.9%
위 14
 
1.6%
터 14
 
1.6%
진 13
 
1.5%
체 12
 
1.3%
도 11
 
1.2%
이 10
 
1.1%
Other values (268) 688
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 737
82.7%
Space Separator 67
 
7.5%
Lowercase Letter 35
 
3.9%
Uppercase Letter 35
 
3.9%
Decimal Number 12
 
1.3%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 27
 
3.7%
성 18
 
2.4%
스 17
 
2.3%
위 14
 
1.9%
터 14
 
1.9%
진 13
 
1.8%
체 12
 
1.6%
도 11
 
1.5%
이 10
 
1.4%
상 10
 
1.4%
Other values (229) 591
80.2%
Uppercase Letter
ValueCountFrequency (%)
S 7
20.0%
M 5
14.3%
T 3
8.6%
R 3
8.6%
P 2
 
5.7%
O 2
 
5.7%
L 2
 
5.7%
C 2
 
5.7%
K 2
 
5.7%
A 2
 
5.7%
Other values (5) 5
14.3%
Lowercase Letter
ValueCountFrequency (%)
e 7
20.0%
n 5
14.3%
i 4
11.4%
a 3
8.6%
s 3
8.6%
c 2
 
5.7%
t 2
 
5.7%
d 2
 
5.7%
l 2
 
5.7%
o 1
 
2.9%
Other values (4) 4
11.4%
Decimal Number
ValueCountFrequency (%)
2 2
16.7%
8 2
16.7%
4 2
16.7%
7 2
16.7%
1 1
8.3%
9 1
8.3%
5 1
8.3%
3 1
8.3%
Space Separator
ValueCountFrequency (%)
67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 737
82.7%
Common 84
 
9.4%
Latin 70
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 27
 
3.7%
성 18
 
2.4%
스 17
 
2.3%
위 14
 
1.9%
터 14
 
1.9%
진 13
 
1.8%
체 12
 
1.6%
도 11
 
1.5%
이 10
 
1.4%
상 10
 
1.4%
Other values (229) 591
80.2%
Latin
ValueCountFrequency (%)
e 7
 
10.0%
S 7
 
10.0%
n 5
 
7.1%
M 5
 
7.1%
i 4
 
5.7%
a 3
 
4.3%
T 3
 
4.3%
R 3
 
4.3%
s 3
 
4.3%
c 2
 
2.9%
Other values (19) 28
40.0%
Common
ValueCountFrequency (%)
67
79.8%
- 5
 
6.0%
2 2
 
2.4%
8 2
 
2.4%
4 2
 
2.4%
7 2
 
2.4%
1 1
 
1.2%
9 1
 
1.2%
5 1
 
1.2%
3 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 737
82.7%
ASCII 154
 
17.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67
43.5%
e 7
 
4.5%
S 7
 
4.5%
- 5
 
3.2%
n 5
 
3.2%
M 5
 
3.2%
i 4
 
2.6%
a 3
 
1.9%
T 3
 
1.9%
R 3
 
1.9%
Other values (29) 45
29.2%
Hangul
ValueCountFrequency (%)
기 27
 
3.7%
성 18
 
2.4%
스 17
 
2.3%
위 14
 
1.9%
터 14
 
1.9%
진 13
 
1.8%
체 12
 
1.6%
도 11
 
1.5%
이 10
 
1.4%
상 10
 
1.4%
Other values (229) 591
80.2%

국문키워드3
Text

MISSING 

Distinct138
Distinct (%)96.5%
Missing70
Missing (%)32.9%
Memory size1.8 KiB
2023-12-12T17:00:05.352859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length6.3286713
Min length2

Characters and Unicode

Total characters905
Distinct characters288
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)93.0%

Sample

1st row열전달계수
2nd row오픈폼
3rd row엔진제어기
4th row발전기
5th row인버터
ValueCountFrequency (%)
케로신 3
 
1.3%
엔진 3
 
1.3%
열진공시험 2
 
0.9%
재사용 2
 
0.9%
위성 2
 
0.9%
인공지능 2
 
0.9%
및 2
 
0.9%
비행 2
 
0.9%
인버터 2
 
0.9%
정하중시험 2
 
0.9%
Other values (210) 212
90.6%
2023-12-12T17:00:05.738112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
10.2%
기 18
 
2.0%
진 16
 
1.8%
전 14
 
1.5%
성 13
 
1.4%
상 13
 
1.4%
공 12
 
1.3%
시 11
 
1.2%
인 11
 
1.2%
터 10
 
1.1%
Other values (278) 695
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 721
79.7%
Space Separator 92
 
10.2%
Lowercase Letter 58
 
6.4%
Uppercase Letter 25
 
2.8%
Decimal Number 7
 
0.8%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 18
 
2.5%
진 16
 
2.2%
전 14
 
1.9%
성 13
 
1.8%
상 13
 
1.8%
공 12
 
1.7%
시 11
 
1.5%
인 11
 
1.5%
터 10
 
1.4%
사 10
 
1.4%
Other values (244) 593
82.2%
Lowercase Letter
ValueCountFrequency (%)
n 8
13.8%
o 7
12.1%
s 6
10.3%
e 6
10.3%
a 6
10.3%
l 6
10.3%
i 4
6.9%
m 4
6.9%
t 3
 
5.2%
r 2
 
3.4%
Other values (5) 6
10.3%
Uppercase Letter
ValueCountFrequency (%)
A 6
24.0%
S 3
12.0%
R 3
12.0%
M 3
12.0%
E 2
 
8.0%
C 2
 
8.0%
F 1
 
4.0%
G 1
 
4.0%
X 1
 
4.0%
U 1
 
4.0%
Other values (2) 2
 
8.0%
Decimal Number
ValueCountFrequency (%)
0 3
42.9%
2 2
28.6%
8 1
 
14.3%
1 1
 
14.3%
Space Separator
ValueCountFrequency (%)
92
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 721
79.7%
Common 101
 
11.2%
Latin 83
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 18
 
2.5%
진 16
 
2.2%
전 14
 
1.9%
성 13
 
1.8%
상 13
 
1.8%
공 12
 
1.7%
시 11
 
1.5%
인 11
 
1.5%
터 10
 
1.4%
사 10
 
1.4%
Other values (244) 593
82.2%
Latin
ValueCountFrequency (%)
n 8
 
9.6%
o 7
 
8.4%
A 6
 
7.2%
s 6
 
7.2%
e 6
 
7.2%
a 6
 
7.2%
l 6
 
7.2%
i 4
 
4.8%
m 4
 
4.8%
S 3
 
3.6%
Other values (17) 27
32.5%
Common
ValueCountFrequency (%)
92
91.1%
0 3
 
3.0%
2 2
 
2.0%
, 1
 
1.0%
8 1
 
1.0%
1 1
 
1.0%
- 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 721
79.7%
ASCII 184
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
50.0%
n 8
 
4.3%
o 7
 
3.8%
A 6
 
3.3%
s 6
 
3.3%
e 6
 
3.3%
a 6
 
3.3%
l 6
 
3.3%
i 4
 
2.2%
m 4
 
2.2%
Other values (24) 39
21.2%
Hangul
ValueCountFrequency (%)
기 18
 
2.5%
진 16
 
2.2%
전 14
 
1.9%
성 13
 
1.8%
상 13
 
1.8%
공 12
 
1.7%
시 11
 
1.5%
인 11
 
1.5%
터 10
 
1.4%
사 10
 
1.4%
Other values (244) 593
82.2%

국문키워드4
Text

MISSING 

Distinct115
Distinct (%)96.6%
Missing94
Missing (%)44.1%
Memory size1.8 KiB
2023-12-12T17:00:05.981915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length6.4705882
Min length2

Characters and Unicode

Total characters770
Distinct characters262
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)93.3%

Sample

1st row적외선열화상기법
2nd row슈퍼컴퓨터
3rd row엔진 배기가스온도
4th row배터리
5th row배터리
ValueCountFrequency (%)
배터리 2
 
1.1%
sar 2
 
1.1%
최적 2
 
1.1%
우적계 2
 
1.1%
결합 2
 
1.1%
산화제 2
 
1.1%
냉각 2
 
1.1%
시뮬레이션 2
 
1.1%
천리안위성 2
 
1.1%
엔진 2
 
1.1%
Other values (167) 170
89.5%
2023-12-12T17:00:06.344969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
9.5%
시 14
 
1.8%
성 13
 
1.7%
스 12
 
1.6%
기 12
 
1.6%
전 10
 
1.3%
정 10
 
1.3%
사 9
 
1.2%
리 9
 
1.2%
체 9
 
1.2%
Other values (252) 599
77.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
76.9%
Space Separator 73
 
9.5%
Lowercase Letter 49
 
6.4%
Uppercase Letter 43
 
5.6%
Decimal Number 6
 
0.8%
Dash Punctuation 5
 
0.6%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 14
 
2.4%
성 13
 
2.2%
스 12
 
2.0%
기 12
 
2.0%
전 10
 
1.7%
정 10
 
1.7%
사 9
 
1.5%
리 9
 
1.5%
체 9
 
1.5%
계 9
 
1.5%
Other values (209) 485
81.9%
Uppercase Letter
ValueCountFrequency (%)
P 6
14.0%
A 5
11.6%
K 4
9.3%
S 4
9.3%
T 4
9.3%
O 3
 
7.0%
M 2
 
4.7%
R 2
 
4.7%
E 2
 
4.7%
N 2
 
4.7%
Other values (9) 9
20.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
12.2%
n 5
10.2%
a 4
 
8.2%
t 4
 
8.2%
r 4
 
8.2%
l 3
 
6.1%
i 3
 
6.1%
c 3
 
6.1%
p 3
 
6.1%
o 3
 
6.1%
Other values (8) 11
22.4%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
1 2
33.3%
Space Separator
ValueCountFrequency (%)
73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 592
76.9%
Latin 92
 
11.9%
Common 86
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 14
 
2.4%
성 13
 
2.2%
스 12
 
2.0%
기 12
 
2.0%
전 10
 
1.7%
정 10
 
1.7%
사 9
 
1.5%
리 9
 
1.5%
체 9
 
1.5%
계 9
 
1.5%
Other values (209) 485
81.9%
Latin
ValueCountFrequency (%)
e 6
 
6.5%
P 6
 
6.5%
n 5
 
5.4%
A 5
 
5.4%
a 4
 
4.3%
K 4
 
4.3%
S 4
 
4.3%
T 4
 
4.3%
t 4
 
4.3%
r 4
 
4.3%
Other values (27) 46
50.0%
Common
ValueCountFrequency (%)
73
84.9%
- 5
 
5.8%
2 2
 
2.3%
/ 2
 
2.3%
0 2
 
2.3%
1 2
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 592
76.9%
ASCII 178
 
23.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
41.0%
e 6
 
3.4%
P 6
 
3.4%
n 5
 
2.8%
- 5
 
2.8%
A 5
 
2.8%
a 4
 
2.2%
K 4
 
2.2%
S 4
 
2.2%
T 4
 
2.2%
Other values (33) 62
34.8%
Hangul
ValueCountFrequency (%)
시 14
 
2.4%
성 13
 
2.2%
스 12
 
2.0%
기 12
 
2.0%
전 10
 
1.7%
정 10
 
1.7%
사 9
 
1.5%
리 9
 
1.5%
체 9
 
1.5%
계 9
 
1.5%
Other values (209) 485
81.9%

국문키워드5
Text

MISSING 

Distinct81
Distinct (%)98.8%
Missing131
Missing (%)61.5%
Memory size1.8 KiB
2023-12-12T17:00:06.626382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length11
Mean length6.6707317
Min length2

Characters and Unicode

Total characters547
Distinct characters208
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)97.6%

Sample

1st row터빈 노즐
2nd row엔진회전수
3rd row운용 제어로직
4th row냉각
5th row막냉각 효율
ValueCountFrequency (%)
기상 2
 
1.6%
엔진 2
 
1.6%
레이더 2
 
1.6%
전동기 1
 
0.8%
항공기용 1
 
0.8%
우주 1
 
0.8%
랑데부/도킹 1
 
0.8%
자율 1
 
0.8%
다중위성군 1
 
0.8%
이중주파수 1
 
0.8%
Other values (115) 115
89.8%
2023-12-12T17:00:07.000983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
 
9.0%
성 12
 
2.2%
t 11
 
2.0%
진 10
 
1.8%
사 9
 
1.6%
전 9
 
1.6%
기 9
 
1.6%
리 8
 
1.5%
터 8
 
1.5%
주 8
 
1.5%
Other values (198) 414
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 424
77.5%
Lowercase Letter 56
 
10.2%
Space Separator 49
 
9.0%
Uppercase Letter 11
 
2.0%
Dash Punctuation 3
 
0.5%
Decimal Number 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 12
 
2.8%
진 10
 
2.4%
사 9
 
2.1%
전 9
 
2.1%
기 9
 
2.1%
리 8
 
1.9%
터 8
 
1.9%
주 8
 
1.9%
이 8
 
1.9%
로 8
 
1.9%
Other values (169) 335
79.0%
Lowercase Letter
ValueCountFrequency (%)
t 11
19.6%
o 7
12.5%
n 6
10.7%
a 6
10.7%
i 5
8.9%
r 4
 
7.1%
h 3
 
5.4%
e 3
 
5.4%
c 2
 
3.6%
f 2
 
3.6%
Other values (6) 7
12.5%
Uppercase Letter
ValueCountFrequency (%)
M 2
18.2%
S 2
18.2%
I 1
9.1%
P 1
9.1%
O 1
9.1%
A 1
9.1%
E 1
9.1%
T 1
9.1%
G 1
9.1%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 424
77.5%
Latin 67
 
12.2%
Common 56
 
10.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 12
 
2.8%
진 10
 
2.4%
사 9
 
2.1%
전 9
 
2.1%
기 9
 
2.1%
리 8
 
1.9%
터 8
 
1.9%
주 8
 
1.9%
이 8
 
1.9%
로 8
 
1.9%
Other values (169) 335
79.0%
Latin
ValueCountFrequency (%)
t 11
16.4%
o 7
 
10.4%
n 6
 
9.0%
a 6
 
9.0%
i 5
 
7.5%
r 4
 
6.0%
h 3
 
4.5%
e 3
 
4.5%
M 2
 
3.0%
c 2
 
3.0%
Other values (15) 18
26.9%
Common
ValueCountFrequency (%)
49
87.5%
- 3
 
5.4%
2 3
 
5.4%
/ 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 424
77.5%
ASCII 123
 
22.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49
39.8%
t 11
 
8.9%
o 7
 
5.7%
n 6
 
4.9%
a 6
 
4.9%
i 5
 
4.1%
r 4
 
3.3%
- 3
 
2.4%
h 3
 
2.4%
e 3
 
2.4%
Other values (19) 26
21.1%
Hangul
ValueCountFrequency (%)
성 12
 
2.8%
진 10
 
2.4%
사 9
 
2.1%
전 9
 
2.1%
기 9
 
2.1%
리 8
 
1.9%
터 8
 
1.9%
주 8
 
1.9%
이 8
 
1.9%
로 8
 
1.9%
Other values (169) 335
79.0%

국문키워드6
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing184
Missing (%)86.4%
Memory size1.8 KiB
2023-12-12T17:00:07.203132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length9
Mean length5.5862069
Min length2

Characters and Unicode

Total characters162
Distinct characters103
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row열관리시스템
2nd row압력감응페인트
3rd row제어기
4th row기술적 요구도
5th row비출력
ValueCountFrequency (%)
열관리시스템 1
 
2.6%
다트 1
 
2.6%
임무분석 1
 
2.6%
atmosphere 1
 
2.6%
correction 1
 
2.6%
달 1
 
2.6%
탐사 1
 
2.6%
야스트렙 1
 
2.6%
심우주 1
 
2.6%
영상기하보정 1
 
2.6%
Other values (29) 29
74.4%
2023-12-12T17:00:07.534094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
6.2%
트 4
 
2.5%
력 4
 
2.5%
터 3
 
1.9%
기 3
 
1.9%
r 3
 
1.9%
상 3
 
1.9%
e 3
 
1.9%
제 3
 
1.9%
위 3
 
1.9%
Other values (93) 123
75.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
80.2%
Lowercase Letter 18
 
11.1%
Space Separator 10
 
6.2%
Uppercase Letter 3
 
1.9%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 4
 
3.1%
력 4
 
3.1%
터 3
 
2.3%
기 3
 
2.3%
상 3
 
2.3%
제 3
 
2.3%
위 3
 
2.3%
소 3
 
2.3%
스 3
 
2.3%
진 3
 
2.3%
Other values (77) 98
75.4%
Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
e 3
16.7%
o 3
16.7%
t 2
11.1%
h 1
 
5.6%
s 1
 
5.6%
m 1
 
5.6%
p 1
 
5.6%
c 1
 
5.6%
n 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
A 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
80.2%
Latin 21
 
13.0%
Common 11
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 4
 
3.1%
력 4
 
3.1%
터 3
 
2.3%
기 3
 
2.3%
상 3
 
2.3%
제 3
 
2.3%
위 3
 
2.3%
소 3
 
2.3%
스 3
 
2.3%
진 3
 
2.3%
Other values (77) 98
75.4%
Latin
ValueCountFrequency (%)
r 3
14.3%
e 3
14.3%
o 3
14.3%
t 2
9.5%
B 1
 
4.8%
h 1
 
4.8%
s 1
 
4.8%
m 1
 
4.8%
A 1
 
4.8%
p 1
 
4.8%
Other values (4) 4
19.0%
Common
ValueCountFrequency (%)
10
90.9%
2 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
80.2%
ASCII 32
 
19.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
31.2%
r 3
 
9.4%
e 3
 
9.4%
o 3
 
9.4%
t 2
 
6.2%
2 1
 
3.1%
B 1
 
3.1%
h 1
 
3.1%
s 1
 
3.1%
m 1
 
3.1%
Other values (6) 6
18.8%
Hangul
ValueCountFrequency (%)
트 4
 
3.1%
력 4
 
3.1%
터 3
 
2.3%
기 3
 
2.3%
상 3
 
2.3%
제 3
 
2.3%
위 3
 
2.3%
소 3
 
2.3%
스 3
 
2.3%
진 3
 
2.3%
Other values (77) 98
75.4%

국문키워드7
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing205
Missing (%)96.2%
Memory size1.8 KiB
2023-12-12T17:00:07.722693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length6
Mean length6.25
Min length2

Characters and Unicode

Total characters50
Distinct characters37
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

Unique8 ?
Unique (%)100.0%

Sample

1st row저항력
2nd row독일 항공우주센터
3rd row우주탐사
4th row푸셔 프로펠러
5th row트림분석
ValueCountFrequency (%)
저항력 1
8.3%
독일 1
8.3%
항공우주센터 1
8.3%
우주탐사 1
8.3%
푸셔 1
8.3%
프로펠러 1
8.3%
트림분석 1
8.3%
machine 1
8.3%
learning 1
8.3%
화성 1
8.3%
Other values (2) 2
16.7%
2023-12-12T17:00:08.012145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
8.0%
n 3
 
6.0%
e 2
 
4.0%
a 2
 
4.0%
항 2
 
4.0%
우 2
 
4.0%
주 2
 
4.0%
i 2
 
4.0%
탐 2
 
4.0%
사 2
 
4.0%
Other values (27) 27
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
62.0%
Lowercase Letter 13
26.0%
Space Separator 4
 
8.0%
Uppercase Letter 2
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
항 2
 
6.5%
우 2
 
6.5%
주 2
 
6.5%
탐 2
 
6.5%
사 2
 
6.5%
저 1
 
3.2%
석 1
 
3.2%
화 1
 
3.2%
성 1
 
3.2%
소 1
 
3.2%
Other values (16) 16
51.6%
Lowercase Letter
ValueCountFrequency (%)
n 3
23.1%
e 2
15.4%
a 2
15.4%
i 2
15.4%
c 1
 
7.7%
h 1
 
7.7%
r 1
 
7.7%
g 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
62.0%
Latin 15
30.0%
Common 4
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
항 2
 
6.5%
우 2
 
6.5%
주 2
 
6.5%
탐 2
 
6.5%
사 2
 
6.5%
저 1
 
3.2%
석 1
 
3.2%
화 1
 
3.2%
성 1
 
3.2%
소 1
 
3.2%
Other values (16) 16
51.6%
Latin
ValueCountFrequency (%)
n 3
20.0%
e 2
13.3%
a 2
13.3%
i 2
13.3%
c 1
 
6.7%
h 1
 
6.7%
L 1
 
6.7%
r 1
 
6.7%
g 1
 
6.7%
M 1
 
6.7%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
62.0%
ASCII 19
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
21.1%
n 3
15.8%
e 2
10.5%
a 2
10.5%
i 2
10.5%
c 1
 
5.3%
h 1
 
5.3%
L 1
 
5.3%
r 1
 
5.3%
g 1
 
5.3%
Hangul
ValueCountFrequency (%)
항 2
 
6.5%
우 2
 
6.5%
주 2
 
6.5%
탐 2
 
6.5%
사 2
 
6.5%
저 1
 
3.2%
석 1
 
3.2%
화 1
 
3.2%
성 1
 
3.2%
소 1
 
3.2%
Other values (16) 16
51.6%

국문키워드8
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing210
Missing (%)98.6%
Memory size1.8 KiB
2023-12-12T17:00:08.167602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.6666667
Min length2

Characters and Unicode

Total characters8
Distinct characters8
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

Unique3 ?
Unique (%)100.0%

Sample

1st row번들
2nd row고속
3rd row오를란
ValueCountFrequency (%)
번들 1
33.3%
고속 1
33.3%
오를란 1
33.3%
2023-12-12T17:00:08.451526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
번 1
12.5%
들 1
12.5%
1
12.5%
고 1
12.5%
속 1
12.5%
오 1
12.5%
를 1
12.5%
란 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
87.5%
Space Separator 1
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 1
14.3%
들 1
14.3%
고 1
14.3%
속 1
14.3%
오 1
14.3%
를 1
14.3%
란 1
14.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
87.5%
Common 1
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 1
14.3%
들 1
14.3%
고 1
14.3%
속 1
14.3%
오 1
14.3%
를 1
14.3%
란 1
14.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
87.5%
ASCII 1
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
번 1
14.3%
들 1
14.3%
고 1
14.3%
속 1
14.3%
오 1
14.3%
를 1
14.3%
란 1
14.3%
ASCII
ValueCountFrequency (%)
1
100.0%

국문키워드9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing211
Missing (%)99.1%
Memory size1.8 KiB
2023-12-12T17:00:08.589531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters6
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

Unique2 ?
Unique (%)100.0%

Sample

1st row장거리
2nd row페이텐
ValueCountFrequency (%)
장거리 1
50.0%
페이텐 1
50.0%
2023-12-12T17:00:08.841079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1
16.7%
거 1
16.7%
리 1
16.7%
페 1
16.7%
이 1
16.7%
텐 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1
16.7%
거 1
16.7%
리 1
16.7%
페 1
16.7%
이 1
16.7%
텐 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1
16.7%
거 1
16.7%
리 1
16.7%
페 1
16.7%
이 1
16.7%
텐 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1
16.7%
거 1
16.7%
리 1
16.7%
페 1
16.7%
이 1
16.7%
텐 1
16.7%

영문키워드1
Text

MISSING 

Distinct190
Distinct (%)93.6%
Missing10
Missing (%)4.7%
Memory size1.8 KiB
2023-12-12T17:00:09.175673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length118
Median length41
Mean length20.236453
Min length3

Characters and Unicode

Total characters4108
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)88.7%

Sample

1st rowswarming flight system; Hungarian algorithm; RTK-GPS
2nd rowimage processing
3rd rowGas turbine
4th rowCFD
5th rowSmall Gas turbine engine
ValueCountFrequency (%)
system 9
 
1.7%
satellite 9
 
1.7%
vehicle 7
 
1.4%
space 6
 
1.2%
propulsion 5
 
1.0%
and 5
 
1.0%
deep 5
 
1.0%
gas 5
 
1.0%
turbine 5
 
1.0%
electric 5
 
1.0%
Other values (356) 456
88.2%
2023-12-12T17:00:10.071789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 382
 
9.3%
315
 
7.7%
a 289
 
7.0%
t 286
 
7.0%
i 284
 
6.9%
r 261
 
6.4%
n 253
 
6.2%
o 238
 
5.8%
l 211
 
5.1%
s 157
 
3.8%
Other values (57) 1432
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3220
78.4%
Uppercase Letter 472
 
11.5%
Space Separator 315
 
7.7%
Other Punctuation 35
 
0.9%
Dash Punctuation 31
 
0.8%
Decimal Number 15
 
0.4%
Open Punctuation 10
 
0.2%
Close Punctuation 9
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 382
11.9%
a 289
9.0%
t 286
8.9%
i 284
 
8.8%
r 261
 
8.1%
n 253
 
7.9%
o 238
 
7.4%
l 211
 
6.6%
s 157
 
4.9%
c 146
 
4.5%
Other values (16) 713
22.1%
Uppercase Letter
ValueCountFrequency (%)
S 74
15.7%
A 55
11.7%
M 33
 
7.0%
R 28
 
5.9%
C 28
 
5.9%
P 28
 
5.9%
T 27
 
5.7%
E 25
 
5.3%
L 20
 
4.2%
D 19
 
4.0%
Other values (14) 135
28.6%
Decimal Number
ValueCountFrequency (%)
5 4
26.7%
0 3
20.0%
3 3
20.0%
1 2
13.3%
9 1
 
6.7%
6 1
 
6.7%
2 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
; 28
80.0%
, 4
 
11.4%
& 1
 
2.9%
. 1
 
2.9%
: 1
 
2.9%
Space Separator
ValueCountFrequency (%)
315
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3692
89.9%
Common 416
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 382
 
10.3%
a 289
 
7.8%
t 286
 
7.7%
i 284
 
7.7%
r 261
 
7.1%
n 253
 
6.9%
o 238
 
6.4%
l 211
 
5.7%
s 157
 
4.3%
c 146
 
4.0%
Other values (40) 1185
32.1%
Common
ValueCountFrequency (%)
315
75.7%
- 31
 
7.5%
; 28
 
6.7%
( 10
 
2.4%
) 9
 
2.2%
, 4
 
1.0%
5 4
 
1.0%
0 3
 
0.7%
3 3
 
0.7%
1 2
 
0.5%
Other values (7) 7
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 382
 
9.3%
315
 
7.7%
a 289
 
7.0%
t 286
 
7.0%
i 284
 
6.9%
r 261
 
6.4%
n 253
 
6.2%
o 238
 
5.8%
l 211
 
5.1%
s 157
 
3.8%
Other values (57) 1432
34.9%

영문키워드2
Text

MISSING 

Distinct183
Distinct (%)96.8%
Missing24
Missing (%)11.3%
Memory size1.8 KiB
2023-12-12T17:00:10.416262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length30
Mean length16.777778
Min length2

Characters and Unicode

Total characters3171
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)94.2%

Sample

1st rowdeep learning
2nd rowFilm cooling
3rd rowGas turbine engine
4th rowFault Diagnostic
5th rowMotor
ValueCountFrequency (%)
engine 7
 
1.8%
satellite 7
 
1.8%
liquid 5
 
1.3%
space 5
 
1.3%
system 5
 
1.3%
image 4
 
1.0%
tank 4
 
1.0%
rocket 4
 
1.0%
lunar 3
 
0.8%
interference 3
 
0.8%
Other values (303) 349
88.1%
2023-12-12T17:00:10.995170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 325
 
10.2%
i 252
 
7.9%
a 223
 
7.0%
t 219
 
6.9%
n 218
 
6.9%
208
 
6.6%
r 182
 
5.7%
o 176
 
5.6%
l 150
 
4.7%
s 141
 
4.4%
Other values (52) 1077
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2549
80.4%
Uppercase Letter 363
 
11.4%
Space Separator 208
 
6.6%
Dash Punctuation 22
 
0.7%
Decimal Number 10
 
0.3%
Close Punctuation 9
 
0.3%
Open Punctuation 9
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 325
12.8%
i 252
9.9%
a 223
8.7%
t 219
8.6%
n 218
8.6%
r 182
 
7.1%
o 176
 
6.9%
l 150
 
5.9%
s 141
 
5.5%
c 122
 
4.8%
Other values (16) 541
21.2%
Uppercase Letter
ValueCountFrequency (%)
S 44
12.1%
C 30
 
8.3%
M 29
 
8.0%
A 26
 
7.2%
R 24
 
6.6%
P 23
 
6.3%
L 21
 
5.8%
E 21
 
5.8%
T 20
 
5.5%
D 19
 
5.2%
Other values (14) 106
29.2%
Decimal Number
ValueCountFrequency (%)
8 2
20.0%
4 2
20.0%
7 2
20.0%
9 1
10.0%
1 1
10.0%
5 1
10.0%
2 1
10.0%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2912
91.8%
Common 259
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 325
 
11.2%
i 252
 
8.7%
a 223
 
7.7%
t 219
 
7.5%
n 218
 
7.5%
r 182
 
6.2%
o 176
 
6.0%
l 150
 
5.2%
s 141
 
4.8%
c 122
 
4.2%
Other values (40) 904
31.0%
Common
ValueCountFrequency (%)
208
80.3%
- 22
 
8.5%
) 9
 
3.5%
( 9
 
3.5%
8 2
 
0.8%
4 2
 
0.8%
7 2
 
0.8%
9 1
 
0.4%
1 1
 
0.4%
5 1
 
0.4%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3171
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 325
 
10.2%
i 252
 
7.9%
a 223
 
7.0%
t 219
 
6.9%
n 218
 
6.9%
208
 
6.6%
r 182
 
5.7%
o 176
 
5.6%
l 150
 
4.7%
s 141
 
4.4%
Other values (52) 1077
34.0%

영문키워드3
Text

MISSING 

Distinct181
Distinct (%)96.3%
Missing25
Missing (%)11.7%
Memory size1.8 KiB
2023-12-12T17:00:11.363686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length27.5
Mean length16.31383
Min length3

Characters and Unicode

Total characters3067
Distinct characters58
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)92.6%

Sample

1st rowISM
2nd rowHeat transfer coefficient
3rd rowOpenFOAM
4th rowECU
5th rowInverter
ValueCountFrequency (%)
test 8
 
2.0%
space 7
 
1.8%
and 5
 
1.3%
detection 4
 
1.0%
launch 4
 
1.0%
satellite 4
 
1.0%
kerosene 3
 
0.8%
fiber 3
 
0.8%
sensor 3
 
0.8%
deep 3
 
0.8%
Other values (299) 348
88.8%
2023-12-12T17:00:11.866464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 291
 
9.5%
i 233
 
7.6%
n 220
 
7.2%
a 212
 
6.9%
209
 
6.8%
t 209
 
6.8%
o 180
 
5.9%
r 179
 
5.8%
l 152
 
5.0%
c 118
 
3.8%
Other values (48) 1064
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2443
79.7%
Uppercase Letter 369
 
12.0%
Space Separator 209
 
6.8%
Dash Punctuation 28
 
0.9%
Decimal Number 8
 
0.3%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Final Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 291
11.9%
i 233
9.5%
n 220
9.0%
a 212
 
8.7%
t 209
 
8.6%
o 180
 
7.4%
r 179
 
7.3%
l 152
 
6.2%
c 118
 
4.8%
s 116
 
4.7%
Other values (15) 533
21.8%
Uppercase Letter
ValueCountFrequency (%)
S 46
12.5%
P 30
 
8.1%
E 27
 
7.3%
C 27
 
7.3%
T 27
 
7.3%
M 25
 
6.8%
I 25
 
6.8%
A 23
 
6.2%
O 17
 
4.6%
F 16
 
4.3%
Other values (14) 106
28.7%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
0 3
37.5%
5 1
 
12.5%
Space Separator
ValueCountFrequency (%)
209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2812
91.7%
Common 255
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 291
 
10.3%
i 233
 
8.3%
n 220
 
7.8%
a 212
 
7.5%
t 209
 
7.4%
o 180
 
6.4%
r 179
 
6.4%
l 152
 
5.4%
c 118
 
4.2%
s 116
 
4.1%
Other values (39) 902
32.1%
Common
ValueCountFrequency (%)
209
82.0%
- 28
 
11.0%
( 4
 
1.6%
2 4
 
1.6%
) 4
 
1.6%
0 3
 
1.2%
’ 1
 
0.4%
& 1
 
0.4%
5 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3066
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 291
 
9.5%
i 233
 
7.6%
n 220
 
7.2%
a 212
 
6.9%
209
 
6.8%
t 209
 
6.8%
o 180
 
5.9%
r 179
 
5.8%
l 152
 
5.0%
c 118
 
3.8%
Other values (47) 1063
34.7%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

영문키워드4
Text

MISSING 

Distinct153
Distinct (%)96.2%
Missing54
Missing (%)25.4%
Memory size1.8 KiB
2023-12-12T17:00:12.237657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27
Mean length15.647799
Min length2

Characters and Unicode

Total characters2488
Distinct characters60
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)92.5%

Sample

1st rowIR thermography
2nd rowSupercomputer
3rd rowEGT
4th rowBattery
5th rowStaircase Geometry
ValueCountFrequency (%)
test 5
 
1.6%
space 5
 
1.6%
load 4
 
1.3%
analysis 4
 
1.3%
battery 3
 
0.9%
remote 3
 
0.9%
design 3
 
0.9%
vehicle 3
 
0.9%
dynamics 3
 
0.9%
fluid 3
 
0.9%
Other values (256) 283
88.7%
2023-12-12T17:00:12.722910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 224
 
9.0%
i 203
 
8.2%
t 183
 
7.4%
n 171
 
6.9%
a 169
 
6.8%
o 161
 
6.5%
160
 
6.4%
r 143
 
5.7%
l 108
 
4.3%
s 94
 
3.8%
Other values (50) 872
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2000
80.4%
Uppercase Letter 296
 
11.9%
Space Separator 160
 
6.4%
Dash Punctuation 12
 
0.5%
Decimal Number 7
 
0.3%
Other Punctuation 7
 
0.3%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 224
11.2%
i 203
10.2%
t 183
9.2%
n 171
 
8.6%
a 169
 
8.5%
o 161
 
8.1%
r 143
 
7.1%
l 108
 
5.4%
s 94
 
4.7%
c 93
 
4.7%
Other values (16) 451
22.6%
Uppercase Letter
ValueCountFrequency (%)
S 39
13.2%
A 27
 
9.1%
P 25
 
8.4%
C 19
 
6.4%
M 18
 
6.1%
D 18
 
6.1%
T 18
 
6.1%
E 15
 
5.1%
R 15
 
5.1%
L 15
 
5.1%
Other values (12) 87
29.4%
Other Punctuation
ValueCountFrequency (%)
/ 2
28.6%
. 2
28.6%
, 1
14.3%
# 1
14.3%
& 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
0 2
28.6%
1 2
28.6%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2296
92.3%
Common 192
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 224
 
9.8%
i 203
 
8.8%
t 183
 
8.0%
n 171
 
7.4%
a 169
 
7.4%
o 161
 
7.0%
r 143
 
6.2%
l 108
 
4.7%
s 94
 
4.1%
c 93
 
4.1%
Other values (38) 747
32.5%
Common
ValueCountFrequency (%)
160
83.3%
- 12
 
6.2%
2 3
 
1.6%
) 3
 
1.6%
( 3
 
1.6%
0 2
 
1.0%
/ 2
 
1.0%
1 2
 
1.0%
. 2
 
1.0%
, 1
 
0.5%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 224
 
9.0%
i 203
 
8.2%
t 183
 
7.4%
n 171
 
6.9%
a 169
 
6.8%
o 161
 
6.5%
160
 
6.4%
r 143
 
5.7%
l 108
 
4.3%
s 94
 
3.8%
Other values (50) 872
35.0%

영문키워드5
Text

MISSING 

Distinct105
Distinct (%)99.1%
Missing107
Missing (%)50.2%
Memory size1.8 KiB
2023-12-12T17:00:13.018923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length23
Mean length15.650943
Min length3

Characters and Unicode

Total characters1659
Distinct characters55
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)98.1%

Sample

1st rowTurbine nozzle
2nd rowRotational speed
3rd rowCooling
4th rowFilm Cooling Effectiven
5th rowScramjet engine
ValueCountFrequency (%)
space 5
 
2.3%
test 3
 
1.4%
engine 3
 
1.4%
battery 2
 
0.9%
satellite 2
 
0.9%
artificial 2
 
0.9%
radar 2
 
0.9%
residual 2
 
0.9%
vehicle 2
 
0.9%
rocket 2
 
0.9%
Other values (186) 193
88.5%
2023-12-12T17:00:13.485707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 159
 
9.6%
i 117
 
7.1%
114
 
6.9%
o 114
 
6.9%
t 112
 
6.8%
r 109
 
6.6%
n 108
 
6.5%
a 103
 
6.2%
l 81
 
4.9%
c 59
 
3.6%
Other values (45) 583
35.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1292
77.9%
Uppercase Letter 227
 
13.7%
Space Separator 114
 
6.9%
Dash Punctuation 12
 
0.7%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Decimal Number 4
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 159
12.3%
i 117
9.1%
o 114
8.8%
t 112
8.7%
r 109
 
8.4%
n 108
 
8.4%
a 103
 
8.0%
l 81
 
6.3%
c 59
 
4.6%
s 52
 
4.0%
Other values (16) 278
21.5%
Uppercase Letter
ValueCountFrequency (%)
A 25
11.0%
S 21
 
9.3%
C 20
 
8.8%
T 19
 
8.4%
P 19
 
8.4%
M 14
 
6.2%
D 14
 
6.2%
R 13
 
5.7%
O 11
 
4.8%
F 9
 
4.0%
Other values (11) 62
27.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
3 2
50.0%
Other Punctuation
ValueCountFrequency (%)
' 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1519
91.6%
Common 140
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 159
 
10.5%
i 117
 
7.7%
o 114
 
7.5%
t 112
 
7.4%
r 109
 
7.2%
n 108
 
7.1%
a 103
 
6.8%
l 81
 
5.3%
c 59
 
3.9%
s 52
 
3.4%
Other values (37) 505
33.2%
Common
ValueCountFrequency (%)
114
81.4%
- 12
 
8.6%
) 4
 
2.9%
( 4
 
2.9%
2 2
 
1.4%
3 2
 
1.4%
' 1
 
0.7%
, 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 159
 
9.6%
i 117
 
7.1%
114
 
6.9%
o 114
 
6.9%
t 112
 
6.8%
r 109
 
6.6%
n 108
 
6.5%
a 103
 
6.2%
l 81
 
4.9%
c 59
 
3.6%
Other values (45) 583
35.1%

영문키워드6
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing175
Missing (%)82.2%
Memory size1.8 KiB
2023-12-12T17:00:13.748161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length19
Mean length14.657895
Min length3

Characters and Unicode

Total characters557
Distinct characters51
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st rowThermal Management System
2nd rowPower Management Unit
3rd rowI-CETS
4th rowSpecific Power
5th rowUnsteady
ValueCountFrequency (%)
estimation 2
 
2.8%
safety 2
 
2.8%
rotor 2
 
2.8%
deep 2
 
2.8%
power 2
 
2.8%
management 2
 
2.8%
asteroid 1
 
1.4%
redirectio 1
 
1.4%
inr 1
 
1.4%
missionanalysis 1
 
1.4%
Other values (55) 55
77.5%
2023-12-12T17:00:14.204445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 55
 
9.9%
t 40
 
7.2%
r 38
 
6.8%
i 37
 
6.6%
o 37
 
6.6%
a 34
 
6.1%
33
 
5.9%
n 32
 
5.7%
s 19
 
3.4%
l 18
 
3.2%
Other values (41) 214
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 415
74.5%
Uppercase Letter 96
 
17.2%
Space Separator 33
 
5.9%
Dash Punctuation 6
 
1.1%
Decimal Number 4
 
0.7%
Open Punctuation 2
 
0.4%
Close Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 55
13.3%
t 40
9.6%
r 38
9.2%
i 37
8.9%
o 37
8.9%
a 34
 
8.2%
n 32
 
7.7%
s 19
 
4.6%
l 18
 
4.3%
u 16
 
3.9%
Other values (14) 89
21.4%
Uppercase Letter
ValueCountFrequency (%)
S 14
14.6%
P 10
10.4%
A 9
9.4%
M 9
9.4%
T 7
 
7.3%
R 6
 
6.2%
E 5
 
5.2%
C 5
 
5.2%
D 5
 
5.2%
I 4
 
4.2%
Other values (11) 22
22.9%
Decimal Number
ValueCountFrequency (%)
5 3
75.0%
2 1
 
25.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 511
91.7%
Common 46
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 55
 
10.8%
t 40
 
7.8%
r 38
 
7.4%
i 37
 
7.2%
o 37
 
7.2%
a 34
 
6.7%
n 32
 
6.3%
s 19
 
3.7%
l 18
 
3.5%
u 16
 
3.1%
Other values (35) 185
36.2%
Common
ValueCountFrequency (%)
33
71.7%
- 6
 
13.0%
5 3
 
6.5%
( 2
 
4.3%
) 1
 
2.2%
2 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 557
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 55
 
9.9%
t 40
 
7.2%
r 38
 
6.8%
i 37
 
6.6%
o 37
 
6.6%
a 34
 
6.1%
33
 
5.9%
n 32
 
5.7%
s 19
 
3.4%
l 18
 
3.2%
Other values (41) 214
38.4%

영문키워드7
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing198
Missing (%)93.0%
Memory size1.8 KiB
2023-12-12T17:00:14.457201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length15.6
Min length5

Characters and Unicode

Total characters234
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st rowStrategic Dilemma of
2nd rowComputational Fluid Dynamics
3rd rowGerman Aerospace Center(DLR)
4th rowDelta-V (8710;V)
5th rowPusher Propeller
ValueCountFrequency (%)
analysis 2
 
6.7%
trim 1
 
3.3%
aerial 1
 
3.3%
unmanned 1
 
3.3%
glide 1
 
3.3%
batsvq 1
 
3.3%
calibration 1
 
3.3%
sokol 1
 
3.3%
exploration 1
 
3.3%
mars 1
 
3.3%
Other values (19) 19
63.3%
2023-12-12T17:00:14.859974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 22
 
9.4%
e 22
 
9.4%
i 17
 
7.3%
n 16
 
6.8%
15
 
6.4%
r 14
 
6.0%
l 14
 
6.0%
o 11
 
4.7%
s 10
 
4.3%
t 10
 
4.3%
Other values (38) 83
35.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 176
75.2%
Uppercase Letter 33
 
14.1%
Space Separator 15
 
6.4%
Decimal Number 4
 
1.7%
Close Punctuation 2
 
0.9%
Open Punctuation 2
 
0.9%
Dash Punctuation 1
 
0.4%
Other Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 22
12.5%
e 22
12.5%
i 17
9.7%
n 16
9.1%
r 14
8.0%
l 14
8.0%
o 11
 
6.2%
s 10
 
5.7%
t 10
 
5.7%
m 9
 
5.1%
Other values (13) 31
17.6%
Uppercase Letter
ValueCountFrequency (%)
D 4
12.1%
A 4
12.1%
S 3
9.1%
V 3
9.1%
C 3
9.1%
T 2
 
6.1%
P 2
 
6.1%
M 2
 
6.1%
L 2
 
6.1%
G 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
0 1
25.0%
1 1
25.0%
7 1
25.0%
8 1
25.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
; 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 209
89.3%
Common 25
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 22
 
10.5%
e 22
 
10.5%
i 17
 
8.1%
n 16
 
7.7%
r 14
 
6.7%
l 14
 
6.7%
o 11
 
5.3%
s 10
 
4.8%
t 10
 
4.8%
m 9
 
4.3%
Other values (29) 64
30.6%
Common
ValueCountFrequency (%)
15
60.0%
) 2
 
8.0%
( 2
 
8.0%
- 1
 
4.0%
; 1
 
4.0%
0 1
 
4.0%
1 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 22
 
9.4%
e 22
 
9.4%
i 17
 
7.3%
n 16
 
6.8%
15
 
6.4%
r 14
 
6.0%
l 14
 
6.0%
o 11
 
4.7%
s 10
 
4.3%
t 10
 
4.3%
Other values (38) 83
35.5%

영문키워드8
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing210
Missing (%)98.6%
Memory size1.8 KiB
2023-12-12T17:00:15.051920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length10
Mean length12.666667
Min length7

Characters and Unicode

Total characters38
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowHigh Speed
2nd rowDP-TSVQ
3rd rowanalytical redundancy
ValueCountFrequency (%)
high 1
20.0%
speed 1
20.0%
dp-tsvq 1
20.0%
analytical 1
20.0%
redundancy 1
20.0%
2023-12-12T17:00:15.411443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
 
10.5%
e 3
 
7.9%
d 3
 
7.9%
n 3
 
7.9%
c 2
 
5.3%
2
 
5.3%
S 2
 
5.3%
y 2
 
5.3%
l 2
 
5.3%
i 2
 
5.3%
Other values (13) 13
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27
71.1%
Uppercase Letter 8
 
21.1%
Space Separator 2
 
5.3%
Dash Punctuation 1
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
14.8%
e 3
11.1%
d 3
11.1%
n 3
11.1%
c 2
7.4%
y 2
7.4%
l 2
7.4%
i 2
7.4%
r 1
 
3.7%
t 1
 
3.7%
Other values (4) 4
14.8%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
H 1
12.5%
Q 1
12.5%
V 1
12.5%
T 1
12.5%
P 1
12.5%
D 1
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35
92.1%
Common 3
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
 
11.4%
e 3
 
8.6%
d 3
 
8.6%
n 3
 
8.6%
c 2
 
5.7%
S 2
 
5.7%
y 2
 
5.7%
l 2
 
5.7%
i 2
 
5.7%
H 1
 
2.9%
Other values (11) 11
31.4%
Common
ValueCountFrequency (%)
2
66.7%
- 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
 
10.5%
e 3
 
7.9%
d 3
 
7.9%
n 3
 
7.9%
c 2
 
5.3%
2
 
5.3%
S 2
 
5.3%
y 2
 
5.3%
l 2
 
5.3%
i 2
 
5.3%
Other values (13) 13
34.2%

영문키워드9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing212
Missing (%)99.5%
Memory size1.8 KiB
2023-12-12T17:00:15.557429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowLong Range
ValueCountFrequency (%)
long 1
50.0%
range 1
50.0%
2023-12-12T17:00:15.824502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2
20.0%
g 2
20.0%
L 1
10.0%
o 1
10.0%
1
10.0%
R 1
10.0%
a 1
10.0%
e 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
70.0%
Uppercase Letter 2
 
20.0%
Space Separator 1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 2
28.6%
g 2
28.6%
o 1
14.3%
a 1
14.3%
e 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
R 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
90.0%
Common 1
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 2
22.2%
g 2
22.2%
L 1
11.1%
o 1
11.1%
R 1
11.1%
a 1
11.1%
e 1
11.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 2
20.0%
g 2
20.0%
L 1
10.0%
o 1
10.0%
1
10.0%
R 1
10.0%
a 1
10.0%
e 1
10.0%

Sample

관리번호발행일자학술지명제목명(국문)제목명(영문)주저자총 저자 수국문키워드1국문키워드2국문키워드3국문키워드4국문키워드5국문키워드6국문키워드7국문키워드8국문키워드9영문키워드1영문키워드2영문키워드3영문키워드4영문키워드5영문키워드6영문키워드7영문키워드8영문키워드9
0KARI-AIRS-RP-2021-0012021-02-10SENSORS공평한 헝가리안 알고리즘을 이용한 에너지 효율적인 군집 형상 변경 방법Energy-Efficient Swarming Flight Formation Transitions Using the Improved Fair Hungarian Algorithm문성태5<NA><NA><NA><NA><NA><NA><NA><NA><NA>swarming flight system; Hungarian algorithm; RTK-GPS<NA><NA><NA><NA><NA><NA><NA><NA>
1KARI-AIRS-RP-2021-0022021-01-13Monthly Notices of the Royal Astronomical SocietyConstruction of a far ultraviolet all sky map from an incomplete survey: Application of a deep learnConstruction of a far ultraviolet all sky map from an incomplete survey: Application of a deep learn조영수6<NA><NA><NA><NA><NA><NA><NA><NA><NA>image processingdeep learningISM<NA><NA><NA><NA><NA><NA>
2KARI-APRD-RP-2021-0012021-01-01Energies확장형 막냉각 홀의 배열과 밀도비가 열전달계수에 미치는 영향The Effect of Hole Arrangement and Density Ratio on the Heat Transfer Coefficient Augmentation of Fa김영서4가스터빈막냉각열전달계수적외선열화상기법<NA><NA><NA><NA><NA>Gas turbineFilm coolingHeat transfer coefficientIR thermography<NA><NA><NA><NA><NA>
3KARI-APRD-RP-2021-0022021-02-01The KSFM Journal of Fluid Machinery오픈 소스 CFD 코드를 이용한 터빈 노즐의 압축성 유동 해석Compressible flow analysis of turbine-nozzle using open source CFD code강승환5전산유체역학가스터빈엔진오픈폼슈퍼컴퓨터터빈 노즐<NA><NA><NA><NA>CFDGas turbine engineOpenFOAMSupercomputerTurbine nozzle<NA><NA><NA><NA>
4KARI-APRD-RP-2021-0052021-04-01Journal of the Korean Society of Propulsion Engineers소형 가스터빈엔진 고장모드 모사를 통한 제어로직 연구Research of small gas turbine engine control logic by engine failure mode simulation이경재6소형가스터빈고장탐구엔진제어기엔진 배기가스온도엔진회전수<NA><NA><NA><NA>Small Gas turbine engineFault DiagnosticECUEGTRotational speed<NA><NA><NA><NA>
5KARI-APRD-RP-2021-0072021-02-28Journal of the Korean Society of Propulsion Engineers무인기용 직렬 하이브리드 동력시스템 운용 제어로직Operational Control Logic of Series Hybrid Power System for the Unmanned Aerial Vehicle이보화3직렬 하이브리드 시스템왕복엔진발전기배터리운용 제어로직<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6KARI-APRD-RP-2021-0082021-07-01Current Industrial and Technological Trends in Aerospace전기추진항공기 냉각 및 열관리 기술 동향Technical Trend of Cooling and Thermal Management for Electric Propulsion Aircraft임병준4전기추진비행기모터인버터배터리냉각열관리시스템<NA><NA><NA>Electric Propulsion AircrfatMotorInverterBatteryCoolingThermal Management System<NA><NA><NA>
7KARI-APRD-RP-2021-0222021-08-01한국유체기계학회 논문지계단 형상의 단차가 적용된 팬 형상 막냉각 홀 하류에서의 막냉각 효율에 관한 실험적 연구Experimental study on film cooling effectiveness downstream of fan-shaped film cooling holes with st김석민5가스터빈막냉각팬 형상 막냉각 홀계단형 단차막냉각 효율압력감응페인트<NA><NA><NA>Gas TurbineFilm CoolingFan-shaped Film Cooling HoleStaircase GeometryFilm Cooling Effectiven<NA><NA><NA><NA>
8KARI-APRD-RP-2021-0232021-05-22Journal of Mechanical Science and Technology스크램젯 엔진의 재생 냉각 열교환기에서 연료 유량에 따른 케로신 상 변화의 열전달 특성Heat transfer characteristics of kerosene phase change based on fuel flow rates in the regenerative이석환5연료 상 변화열교환기형광 온도계재생 냉각스크램젯 엔진<NA><NA><NA><NA>Fuel phase changeHeat exchangerPhosphor thermometryRegenerative coolingScramjet engine<NA><NA><NA><NA>
9KARI-APRD-RP-2021-0282021-10-20전력전자학회지드론용 하이브리드 동력시스템 기술<NA>김근배1드론하이브리드 동력시스템엔진발전기배터리제어기<NA><NA><NA>DroneHybrid Power SystemEngineGeneratorBatteryPower Management Unit<NA><NA><NA>
관리번호발행일자학술지명제목명(국문)제목명(영문)주저자총 저자 수국문키워드1국문키워드2국문키워드3국문키워드4국문키워드5국문키워드6국문키워드7국문키워드8국문키워드9영문키워드1영문키워드2영문키워드3영문키워드4영문키워드5영문키워드6영문키워드7영문키워드8영문키워드9
203KARI-UASRD-RP-2021-0162021-09-01한국항공우주학회지도심 지역 비행을 위한 지상 인명 피해 기반 소형무인기 고장 빈도 분석<NA>김연실2지상 피해 맵무인기 고장 빈도도심 지역 비행<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204KARI-UASRD-RP-2021-0172021-08-01한국항공우주학회지한국형 우주비행기의 기준 항력 추종 기반 재진입 유도 기법Reentry Guidance for Korean Space Plane based on Reference Drag Following윤다인5재진입 유도한국형 우주비행기기준 항력 추종우주 왕복선 유도<NA><NA><NA><NA><NA>Reentry GuidanceKorea Space PlaneReference Drag FollowingSpace Shuttle Guidance<NA><NA><NA><NA><NA>
205KARI-UASRD-RP-2021-0202021-07-01IEEE Robotics and Automation LettersState Estimation of HALE UAVs with Deep-learning-aided Virtual AOA/SSA Sensor for Analytical RedundaState Estimation of HALE UAVs with Deep-learning-aided Virtual AOA/SSA Sensor for Analytical Redunda윤원근7센서퓨전로보틱스인공지능<NA><NA><NA><NA><NA><NA>Sensor fusionaerial systemsapplicationsfield roboticsai-enabled robotics<NA><NA><NA><NA>
206KARI-UASRD-RP-2021-0222021-08-31제어·로봇·시스템학회 논문지영상기반 비상착륙영역 인식 프레임워크를 위한 심층 합성곱 신경망 기반 영상처리 알고리즘Deep Convolutional Neural Network-based Image Processing for Vision-based Safe Landing Region Recogn조성욱2UAM드론비상대책비상착륙영역인식영상처리<NA><NA><NA>UAM(urban air mobilityDroneContingency PlanEmergency LandingRegion RecognitionImage Proce<NA><NA><NA>
207KARI-UASRD-RP-2021-0292021-11-19한국항공우주학회 2021 추계학술대회모델기반설계 기법을 이용한 소형무인기 유도모드 개발Development of Small Unmanned Aerial Vehicle Guidance Modes using a Model-Based Design Method최현진5소형무인기유도모델기반설계매틀랩/시뮬링크<NA><NA><NA><NA><NA>Small Unmmaned Aerial VehicleGuidanceModel-Based DesignMATLAB/Simulink<NA><NA><NA><NA><NA>
208KARI-UASRD-RP-2021-0422021-11-25Journal of Aerospace Information Systems무인기의 항력계수 및 비행데이터 실시간 추정 기법In-Flight Estimation of Drag Parameters and Air Data for Unmanned Aircraft류한석7<NA><NA><NA><NA><NA><NA><NA><NA><NA>DragUAVIn-FlightAir DataUKFEstimationGlide<NA><NA>
209KARI-UASRD-RP-2021-0462021-12-16Journal of Positioning, Navigation, and TimingRTKLIB의 무인기 정밀항법 적용에 대한 고찰A Review on the Usage of RTKLIB for Precise Navigation of Unmanned Vehicles임철순4<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
210KARI-UASRD-RP-2022-0042021-10-01IEEE Robotics and Automation Letters무인기의 해석적 안전이중화를 위한 딥러닝 기반 temporal convolutional network의 합성 대기속도 추정기Deep Learning-aided Synthetic Airspeed Estimation of UAVs for Analytical Redundancy with a Temporal임형태9<NA><NA><NA><NA><NA><NA><NA><NA><NA>Aerial Systemsapplicationssensor fusionfield robotstemporal convolutional networkDeep learningunmanned aerial vehiclesanalytical redundancy<NA>
211KARI-USACRT-RP-2021-0012021-02-26Journal Of Aerospace System Engineering재난치안용 틸트로터 무인기 개념설계 및 성능 향상 연구Conceptual Design and Study on the Performance Enhancement of Tilt Rotor UAV for Disaster and Polici김명재2임무확장형틸트로터성능향상전산유체역학성능해석<NA><NA><NA><NA>Mission ExpandedTiltRotorEnhancement of PerformanceComputational Fluid DynamicsPerformance A<NA><NA><NA><NA>
212KARI-USACRT-RP-2021-0092021-12-01항공우주산업기술동향민간 무인항공기의 국가 공역 운용 위한 기술표준 동향Technical Standardization Trend for National Airspace Operation of Civil Unmanned Aircraft System유창선1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>