Overview

Dataset statistics

Number of variables6
Number of observations1619
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)0.1%
Total size in memory76.0 KiB
Average record size in memory48.1 B

Variable types

Categorical1
Text4
DateTime1

Dataset

Description농림식품RnD 국내 및 국제 학술발표 성과 정보와 관련된 데이터. 분류,과제관리번호,과제명,학술회의명,학술발표제목,학술발표일자 등의 항목으로 구성
Author농림식품기술기획평가원
URLhttps://www.data.go.kr/data/15097835/fileData.do

Alerts

Dataset has 2 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-15 00:12:44.859477
Analysis finished2024-03-15 00:12:46.581340
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류
Categorical

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
농림식품 기계ㆍ시스템
398 
농림식품 환경생태
315 
식품
314 
농림식품 융복합
174 
농산
161 
Other values (3)
257 

Length

Max length11
Median length9
Mean length6.2211242
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row농림식품 기계ㆍ시스템
2nd row농림식품 기계ㆍ시스템
3rd row농림식품 기계ㆍ시스템
4th row농림식품 기계ㆍ시스템
5th row농림식품 기계ㆍ시스템

Common Values

ValueCountFrequency (%)
농림식품 기계ㆍ시스템 398
24.6%
농림식품 환경생태 315
19.5%
식품 314
19.4%
농림식품 융복합 174
10.7%
농산 161
9.9%
축산 146
 
9.0%
수의 110
 
6.8%
임산 공학 1
 
0.1%

Length

2024-03-15T09:12:46.803456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:12:47.165765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농림식품 887
35.4%
기계ㆍ시스템 398
15.9%
환경생태 315
 
12.6%
식품 314
 
12.5%
융복합 174
 
6.9%
농산 161
 
6.4%
축산 146
 
5.8%
수의 110
 
4.4%
임산 1
 
< 0.1%
공학 1
 
< 0.1%

과제관리번호
Text

Distinct337
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2024-03-15T09:12:48.460084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters12952
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)5.0%

Sample

1st row120093-3
2nd row121025-3
3rd row121025-3
4th row121025-3
5th row121027-3
ValueCountFrequency (%)
321001-3 49
 
3.0%
421031-4 32
 
2.0%
321097-3 26
 
1.6%
321036-5 26
 
1.6%
321054-5 25
 
1.5%
321028-5 21
 
1.3%
421021-3 21
 
1.3%
322033-3 20
 
1.2%
322014-5 18
 
1.1%
321021-3 18
 
1.1%
Other values (327) 1363
84.2%
2024-03-15T09:12:50.086468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2724
21.0%
3 2256
17.4%
0 2049
15.8%
1 1628
12.6%
- 1619
12.5%
4 1011
 
7.8%
5 706
 
5.5%
8 297
 
2.3%
7 246
 
1.9%
9 225
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11333
87.5%
Dash Punctuation 1619
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2724
24.0%
3 2256
19.9%
0 2049
18.1%
1 1628
14.4%
4 1011
 
8.9%
5 706
 
6.2%
8 297
 
2.6%
7 246
 
2.2%
9 225
 
2.0%
6 191
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1619
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2724
21.0%
3 2256
17.4%
0 2049
15.8%
1 1628
12.6%
- 1619
12.5%
4 1011
 
7.8%
5 706
 
5.5%
8 297
 
2.3%
7 246
 
1.9%
9 225
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2724
21.0%
3 2256
17.4%
0 2049
15.8%
1 1628
12.6%
- 1619
12.5%
4 1011
 
7.8%
5 706
 
5.5%
8 297
 
2.3%
7 246
 
1.9%
9 225
 
1.7%

과제명
Text

Distinct335
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2024-03-15T09:12:51.382314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length53
Mean length35.330451
Min length7

Characters and Unicode

Total characters57200
Distinct characters539
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)4.8%

Sample

1st row태양열을 활용한 에너지 생산저장관리 및 실증모델 구축
2nd row[제한경쟁] 우수과제 후속연구 지원(분말(분체)병합살균장치 사업화
3rd row[제한경쟁] 우수과제 후속연구 지원(분말(분체)병합살균장치 사업화
4th row[제한경쟁] 우수과제 후속연구 지원(분말(분체)병합살균장치 사업화
5th row외부온도 및 적외선 감응형 농업용 특수(조광)필름 국산화 기술 개발
ValueCountFrequency (%)
개발 1147
 
7.8%
및 1053
 
7.2%
기술 473
 
3.2%
위한 309
 
2.1%
기반 301
 
2.0%
시스템 198
 
1.3%
스마트 124
 
0.8%
기술개발 107
 
0.7%
구축 95
 
0.6%
모니터링 89
 
0.6%
Other values (1397) 10822
73.5%
2024-03-15T09:12:52.868793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13121
 
22.9%
발 1584
 
2.8%
기 1581
 
2.8%
개 1498
 
2.6%
및 1053
 
1.8%
용 843
 
1.5%
스 793
 
1.4%
화 784
 
1.4%
이 778
 
1.4%
술 755
 
1.3%
Other values (529) 34410
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41665
72.8%
Space Separator 13121
 
22.9%
Uppercase Letter 605
 
1.1%
Other Punctuation 412
 
0.7%
Lowercase Letter 411
 
0.7%
Decimal Number 374
 
0.7%
Open Punctuation 279
 
0.5%
Close Punctuation 276
 
0.5%
Dash Punctuation 53
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 1584
 
3.8%
기 1581
 
3.8%
개 1498
 
3.6%
및 1053
 
2.5%
용 843
 
2.0%
스 793
 
1.9%
화 784
 
1.9%
이 778
 
1.9%
술 755
 
1.8%
제 671
 
1.6%
Other values (464) 31325
75.2%
Lowercase Letter
ValueCountFrequency (%)
l 64
15.6%
i 46
11.2%
e 40
9.7%
n 34
8.3%
t 32
 
7.8%
m 27
 
6.6%
k 27
 
6.6%
o 22
 
5.4%
u 21
 
5.1%
f 18
 
4.4%
Other values (12) 80
19.5%
Uppercase Letter
ValueCountFrequency (%)
C 103
17.0%
I 59
 
9.8%
T 56
 
9.3%
S 41
 
6.8%
A 37
 
6.1%
R 35
 
5.8%
W 33
 
5.5%
P 31
 
5.1%
M 30
 
5.0%
D 28
 
4.6%
Other values (11) 152
25.1%
Decimal Number
ValueCountFrequency (%)
1 86
23.0%
3 78
20.9%
2 68
18.2%
0 42
11.2%
4 31
 
8.3%
5 25
 
6.7%
6 16
 
4.3%
7 13
 
3.5%
9 13
 
3.5%
8 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 164
39.8%
. 113
27.4%
· 94
22.8%
/ 41
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 193
69.2%
[ 86
30.8%
Close Punctuation
ValueCountFrequency (%)
) 190
68.8%
] 86
31.2%
Space Separator
ValueCountFrequency (%)
13121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41662
72.8%
Common 14519
 
25.4%
Latin 1016
 
1.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
발 1584
 
3.8%
기 1581
 
3.8%
개 1498
 
3.6%
및 1053
 
2.5%
용 843
 
2.0%
스 793
 
1.9%
화 784
 
1.9%
이 778
 
1.9%
술 755
 
1.8%
제 671
 
1.6%
Other values (463) 31322
75.2%
Latin
ValueCountFrequency (%)
C 103
 
10.1%
l 64
 
6.3%
I 59
 
5.8%
T 56
 
5.5%
i 46
 
4.5%
S 41
 
4.0%
e 40
 
3.9%
A 37
 
3.6%
R 35
 
3.4%
n 34
 
3.3%
Other values (33) 501
49.3%
Common
ValueCountFrequency (%)
13121
90.4%
( 193
 
1.3%
) 190
 
1.3%
, 164
 
1.1%
. 113
 
0.8%
· 94
 
0.6%
1 86
 
0.6%
[ 86
 
0.6%
] 86
 
0.6%
3 78
 
0.5%
Other values (12) 308
 
2.1%
Han
ValueCountFrequency (%)
多 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41660
72.8%
ASCII 15440
 
27.0%
None 94
 
0.2%
CJK 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13121
85.0%
( 193
 
1.2%
) 190
 
1.2%
, 164
 
1.1%
. 113
 
0.7%
C 103
 
0.7%
1 86
 
0.6%
[ 86
 
0.6%
] 86
 
0.6%
3 78
 
0.5%
Other values (53) 1220
 
7.9%
Hangul
ValueCountFrequency (%)
발 1584
 
3.8%
기 1581
 
3.8%
개 1498
 
3.6%
및 1053
 
2.5%
용 843
 
2.0%
스 793
 
1.9%
화 784
 
1.9%
이 778
 
1.9%
술 755
 
1.8%
제 671
 
1.6%
Other values (462) 31320
75.2%
None
ValueCountFrequency (%)
· 94
100.0%
CJK
ValueCountFrequency (%)
多 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

학술회의명
Text

Distinct789
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2024-03-15T09:12:53.703458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length140
Median length87
Mean length27.368128
Min length4

Characters and Unicode

Total characters44309
Distinct characters335
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique486 ?
Unique (%)30.0%

Sample

1st row한국신재생에너지학회 2023년 춘계학술대회
2nd rowNext Level of Food Industry: Translation of Tailored Food to Our Diet
3rd rowNext Level of Food Industry: Translation of Tailored Food to Our Diet
4th row한국산업식품공학회 춘계학술대회
5th row2023 ACS Fall
ValueCountFrequency (%)
2023 680
 
10.4%
2023년 234
 
3.6%
international 201
 
3.1%
및 182
 
2.8%
and 148
 
2.3%
meeting 143
 
2.2%
annual 123
 
1.9%
conference 123
 
1.9%
symposium 118
 
1.8%
of 109
 
1.7%
Other values (922) 4448
68.3%
2024-03-15T09:12:55.299314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4915
 
11.1%
2 2156
 
4.9%
n 2083
 
4.7%
회 1996
 
4.5%
학 1857
 
4.2%
e 1672
 
3.8%
o 1450
 
3.3%
a 1278
 
2.9%
i 1213
 
2.7%
t 1205
 
2.7%
Other values (325) 24484
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15635
35.3%
Lowercase Letter 14571
32.9%
Space Separator 4915
 
11.1%
Decimal Number 4724
 
10.7%
Uppercase Letter 3882
 
8.8%
Close Punctuation 179
 
0.4%
Open Punctuation 178
 
0.4%
Other Punctuation 143
 
0.3%
Dash Punctuation 78
 
0.2%
Connector Punctuation 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 1996
 
12.8%
학 1857
 
11.9%
국 1150
 
7.4%
한 1052
 
6.7%
술 769
 
4.9%
계 621
 
4.0%
대 616
 
3.9%
년 325
 
2.1%
발 277
 
1.8%
표 270
 
1.7%
Other values (249) 6702
42.9%
Lowercase Letter
ValueCountFrequency (%)
n 2083
14.3%
e 1672
11.5%
o 1450
10.0%
a 1278
8.8%
i 1213
8.3%
t 1205
8.3%
r 916
 
6.3%
l 740
 
5.1%
s 605
 
4.2%
c 488
 
3.3%
Other values (15) 2921
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 627
16.2%
A 515
13.3%
I 396
10.2%
C 354
9.1%
M 238
 
6.1%
P 229
 
5.9%
E 210
 
5.4%
F 204
 
5.3%
T 196
 
5.0%
K 194
 
5.0%
Other values (15) 719
18.5%
Decimal Number
ValueCountFrequency (%)
2 2156
45.6%
0 1125
23.8%
3 1106
23.4%
1 101
 
2.1%
5 73
 
1.5%
6 47
 
1.0%
4 41
 
0.9%
8 37
 
0.8%
7 21
 
0.4%
9 17
 
0.4%
Other Punctuation
ValueCountFrequency (%)
& 41
28.7%
, 39
27.3%
: 31
21.7%
· 12
 
8.4%
" 10
 
7.0%
' 4
 
2.8%
/ 3
 
2.1%
; 2
 
1.4%
. 1
 
0.7%
Space Separator
ValueCountFrequency (%)
4915
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%
Open Punctuation
ValueCountFrequency (%)
( 178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈔ 1
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18453
41.6%
Hangul 15636
35.3%
Common 10220
23.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 1996
 
12.8%
학 1857
 
11.9%
국 1150
 
7.4%
한 1052
 
6.7%
술 769
 
4.9%
계 621
 
4.0%
대 616
 
3.9%
년 325
 
2.1%
발 277
 
1.8%
표 270
 
1.7%
Other values (250) 6703
42.9%
Latin
ValueCountFrequency (%)
n 2083
 
11.3%
e 1672
 
9.1%
o 1450
 
7.9%
a 1278
 
6.9%
i 1213
 
6.6%
t 1205
 
6.5%
r 916
 
5.0%
l 740
 
4.0%
S 627
 
3.4%
s 605
 
3.3%
Other values (40) 6664
36.1%
Common
ValueCountFrequency (%)
4915
48.1%
2 2156
21.1%
0 1125
 
11.0%
3 1106
 
10.8%
) 179
 
1.8%
( 178
 
1.7%
1 101
 
1.0%
- 78
 
0.8%
5 73
 
0.7%
6 47
 
0.5%
Other values (15) 262
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28661
64.7%
Hangul 15635
35.3%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4915
17.1%
2 2156
 
7.5%
n 2083
 
7.3%
e 1672
 
5.8%
o 1450
 
5.1%
a 1278
 
4.5%
i 1213
 
4.2%
t 1205
 
4.2%
0 1125
 
3.9%
3 1106
 
3.9%
Other values (64) 10458
36.5%
Hangul
ValueCountFrequency (%)
회 1996
 
12.8%
학 1857
 
11.9%
국 1150
 
7.4%
한 1052
 
6.7%
술 769
 
4.9%
계 621
 
4.0%
대 616
 
3.9%
년 325
 
2.1%
발 277
 
1.8%
표 270
 
1.7%
Other values (249) 6702
42.9%
None
ValueCountFrequency (%)
· 12
92.3%
㈔ 1
 
7.7%

학술발표제목
Text

Distinct1578
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2024-03-15T09:12:56.599392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length110
Mean length82.883879
Min length4

Characters and Unicode

Total characters134189
Distinct characters632
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1538 ?
Unique (%)95.0%

Sample

1st row재생에너지와 히트펌프, 계절간 열저장: 초단기~장기 운영제어 실증과 AI 제어 도입방안
2nd rowEfficacy of Different Plasma Forming Gases on Microbial Inactivation and Quality Attributes of Sesame during Cold Plasma Pasteurization
3rd rowMicrobial efficacy of different Plasma Forming Gases and their quality attributes for rice embryo during cold plasma treatment
4th rowEffect of intense pulsed light (IPL) treatment on the microbial inactivation and change of vitamin D2 content of shiitake (Lentinula edodes) pills.
5th rowManipulation of optical properties through temperature-responsive polymer photonic films
ValueCountFrequency (%)
of 1159
 
5.9%
and 605
 
3.1%
in 453
 
2.3%
the 325
 
1.6%
for 319
 
1.6%
on 239
 
1.2%
a 174
 
0.9%
using 148
 
0.7%
with 114
 
0.6%
위한 104
 
0.5%
Other values (6125) 16100
81.6%
2024-03-15T09:12:58.197891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18264
 
13.6%
e 9799
 
7.3%
i 8952
 
6.7%
a 8109
 
6.0%
o 8101
 
6.0%
t 7519
 
5.6%
n 7342
 
5.5%
r 6010
 
4.5%
s 5346
 
4.0%
l 4495
 
3.3%
Other values (622) 50252
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 93333
69.6%
Space Separator 18264
 
13.6%
Other Letter 12005
 
8.9%
Uppercase Letter 8330
 
6.2%
Dash Punctuation 761
 
0.6%
Decimal Number 684
 
0.5%
Other Punctuation 432
 
0.3%
Open Punctuation 173
 
0.1%
Close Punctuation 166
 
0.1%
Final Punctuation 18
 
< 0.1%
Other values (4) 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 328
 
2.7%
의 282
 
2.3%
기 252
 
2.1%
이 245
 
2.0%
용 225
 
1.9%
수 195
 
1.6%
에 194
 
1.6%
성 164
 
1.4%
을 162
 
1.3%
스 159
 
1.3%
Other values (530) 9799
81.6%
Lowercase Letter
ValueCountFrequency (%)
e 9799
10.5%
i 8952
 
9.6%
a 8109
 
8.7%
o 8101
 
8.7%
t 7519
 
8.1%
n 7342
 
7.9%
r 6010
 
6.4%
s 5346
 
5.7%
l 4495
 
4.8%
c 4374
 
4.7%
Other values (21) 23286
24.9%
Uppercase Letter
ValueCountFrequency (%)
C 751
 
9.0%
S 739
 
8.9%
A 685
 
8.2%
P 636
 
7.6%
E 558
 
6.7%
M 513
 
6.2%
D 472
 
5.7%
R 447
 
5.4%
T 412
 
4.9%
B 409
 
4.9%
Other values (16) 2708
32.5%
Decimal Number
ValueCountFrequency (%)
1 155
22.7%
2 146
21.3%
3 87
12.7%
0 85
12.4%
4 58
 
8.5%
7 38
 
5.6%
5 36
 
5.3%
9 29
 
4.2%
6 26
 
3.8%
8 24
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 178
41.2%
. 105
24.3%
: 80
18.5%
/ 34
 
7.9%
' 20
 
4.6%
" 9
 
2.1%
& 4
 
0.9%
· 1
 
0.2%
* 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
~ 1
25.0%
× 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 760
99.9%
－ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 167
96.5%
[ 6
 
3.5%
Close Punctuation
ValueCountFrequency (%)
) 160
96.4%
] 6
 
3.6%
Final Punctuation
ValueCountFrequency (%)
’ 15
83.3%
” 3
 
16.7%
Initial Punctuation
ValueCountFrequency (%)
‘ 13
81.2%
“ 3
 
18.8%
Space Separator
ValueCountFrequency (%)
18264
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Number
ValueCountFrequency (%)
₁ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 101648
75.7%
Common 20521
 
15.3%
Hangul 12005
 
8.9%
Greek 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 328
 
2.7%
의 282
 
2.3%
기 252
 
2.1%
이 245
 
2.0%
용 225
 
1.9%
수 195
 
1.6%
에 194
 
1.6%
성 164
 
1.4%
을 162
 
1.3%
스 159
 
1.3%
Other values (530) 9799
81.6%
Latin
ValueCountFrequency (%)
e 9799
 
9.6%
i 8952
 
8.8%
a 8109
 
8.0%
o 8101
 
8.0%
t 7519
 
7.4%
n 7342
 
7.2%
r 6010
 
5.9%
s 5346
 
5.3%
l 4495
 
4.4%
c 4374
 
4.3%
Other values (43) 31601
31.1%
Common
ValueCountFrequency (%)
18264
89.0%
- 760
 
3.7%
, 178
 
0.9%
( 167
 
0.8%
) 160
 
0.8%
1 155
 
0.8%
2 146
 
0.7%
. 105
 
0.5%
3 87
 
0.4%
0 85
 
0.4%
Other values (25) 414
 
2.0%
Greek
ValueCountFrequency (%)
γ 7
46.7%
α 5
33.3%
β 2
 
13.3%
κ 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122130
91.0%
Hangul 12005
 
8.9%
Punctuation 34
 
< 0.1%
None 20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18264
15.0%
e 9799
 
8.0%
i 8952
 
7.3%
a 8109
 
6.6%
o 8101
 
6.6%
t 7519
 
6.2%
n 7342
 
6.0%
r 6010
 
4.9%
s 5346
 
4.4%
l 4495
 
3.7%
Other values (69) 38193
31.3%
Hangul
ValueCountFrequency (%)
한 328
 
2.7%
의 282
 
2.3%
기 252
 
2.1%
이 245
 
2.0%
용 225
 
1.9%
수 195
 
1.6%
에 194
 
1.6%
성 164
 
1.4%
을 162
 
1.3%
스 159
 
1.3%
Other values (530) 9799
81.6%
Punctuation
ValueCountFrequency (%)
’ 15
44.1%
‘ 13
38.2%
” 3
 
8.8%
“ 3
 
8.8%
None
ValueCountFrequency (%)
γ 7
35.0%
α 5
25.0%
β 2
 
10.0%
· 1
 
5.0%
₁ 1
 
5.0%
κ 1
 
5.0%
ĸ 1
 
5.0%
× 1
 
5.0%
－ 1
 
5.0%

학술발표일자
Date

Distinct201
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
Minimum2023-01-13 00:00:00
Maximum2023-12-24 00:00:00
2024-03-15T09:12:58.595056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:12:59.040764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2024-03-15T09:12:46.073955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:12:46.440578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

분류과제관리번호과제명학술회의명학술발표제목학술발표일자
0농림식품 기계ㆍ시스템120093-3태양열을 활용한 에너지 생산저장관리 및 실증모델 구축한국신재생에너지학회 2023년 춘계학술대회재생에너지와 히트펌프, 계절간 열저장: 초단기~장기 운영제어 실증과 AI 제어 도입방안2023-06-01
1농림식품 기계ㆍ시스템121025-3[제한경쟁] 우수과제 후속연구 지원(분말(분체)병합살균장치 사업화Next Level of Food Industry: Translation of Tailored Food to Our DietEfficacy of Different Plasma Forming Gases on Microbial Inactivation and Quality Attributes of Sesame during Cold Plasma Pasteurization2023-04-27
2농림식품 기계ㆍ시스템121025-3[제한경쟁] 우수과제 후속연구 지원(분말(분체)병합살균장치 사업화Next Level of Food Industry: Translation of Tailored Food to Our DietMicrobial efficacy of different Plasma Forming Gases and their quality attributes for rice embryo during cold plasma treatment2023-04-27
3농림식품 기계ㆍ시스템121025-3[제한경쟁] 우수과제 후속연구 지원(분말(분체)병합살균장치 사업화한국산업식품공학회 춘계학술대회Effect of intense pulsed light (IPL) treatment on the microbial inactivation and change of vitamin D2 content of shiitake (Lentinula edodes) pills.2023-04-27
4농림식품 기계ㆍ시스템121027-3외부온도 및 적외선 감응형 농업용 특수(조광)필름 국산화 기술 개발2023 ACS FallManipulation of optical properties through temperature-responsive polymer photonic films2023-08-13
5농림식품 기계ㆍ시스템121027-3외부온도 및 적외선 감응형 농업용 특수(조광)필름 국산화 기술 개발2023 나노코리아The Manipulation of Optical Properties through Temperature-Responsive Polymer Photonic Films2023-07-07
6농림식품 기계ㆍ시스템121027-3외부온도 및 적외선 감응형 농업용 특수(조광)필름 국산화 기술 개발2023 춘계 화학공학회외부온도 감응 고분자 복합필름을 이용한 광학특성 제어2023-04-21
7농림식품 기계ㆍ시스템121027-3외부온도 및 적외선 감응형 농업용 특수(조광)필름 국산화 기술 개발2023 한국 세라믹헉회Solution-Processed high transparency ultrathin films with efficient broadband radiation and diffuse reflection2023-10-18
8농림식품 기계ㆍ시스템121027-3외부온도 및 적외선 감응형 농업용 특수(조광)필름 국산화 기술 개발2023 한국자기학회 하계학술대회Colorimetric Visualization using silica hollow nanoparticles for enhanced sensitivity in acetone gas sensors2023-05-24
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분류과제관리번호과제명학술회의명학술발표제목학술발표일자
1609축산421022-423. 축우(한우/젖소) 2세대 스마트 축산 모델 개발 및 실증한국축산환경학회스마트 장비를 활용한 반추동물의 온실가스 발생량 연구2023-09-07
1610축산421023-42세대 돼지 스마트 축산 모델 개발 및 실증2023 Annual International Conference of KSAST스마트 축산 모델 구축을 위한 돼지 생체와 환경 상호관계 조사2023-07-06
1611축산421023-42세대 돼지 스마트 축산 모델 개발 및 실증지능형 자율시스템 국제컨퍼런스The Application for Pig Face Recognition Using Transformer Model2023-07-05
1612축산421023-42세대 돼지 스마트 축산 모델 개발 및 실증지능형 자율시스템 국제컨퍼런스YOLO Algorithm Based Pig Face detection2023-07-05
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1616축산421050-3국가단위 유전능력 평가 모형 적용 및 체중체척 예측 모델 개발한국동물유전육종학회The effect of season and age on average daily gain and body weight on the performance-tested Hanwoo bulls2023-06-23
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Duplicate rows

Most frequently occurring

분류과제관리번호과제명학술회의명학술발표제목학술발표일자# duplicates
0농림식품 환경생태321107-3원예작물의 생산성 향상을 위한 잿빛곰팡이병 조기 진단 기술 개발A3 symposiumThe real-time monitoring of plant signaling molecules using surface-enhanced Raman spectroscopy2023-10-312
1식품321030-5식이관리 수요 기반 대상별 맞춤형 식사관리 솔루션 및 재가식 연구 개발2023 대한가정의학회 춘계학술대회개인맞춤 영양치료의 최신연구2023-04-142