Overview

Dataset statistics

Number of variables9
Number of observations455
Missing cells8
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.5 KiB
Average record size in memory75.3 B

Variable types

Numeric2
Categorical2
Text5

Dataset

Description농림식품 식품 R&D 논문정보의(과제번호, 과제명, 연구책임자, 논문명, 학술지 출판년도, 저자, 학술지명)
Author농림식품기술기획평가원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20191011000000001251

Alerts

분류 has constant value ""Constant
번호 is highly overall correlated with 과제번호High correlation
과제번호 is highly overall correlated with 번호High correlation
저자 has 8 (1.8%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:38:57.757302
Analysis finished2023-12-11 03:38:59.090197
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct455
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228
Minimum1
Maximum455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-11T12:38:59.157798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.7
Q1114.5
median228
Q3341.5
95-th percentile432.3
Maximum455
Range454
Interquartile range (IQR)227

Descriptive statistics

Standard deviation131.49144
Coefficient of variation (CV)0.57671686
Kurtosis-1.2
Mean228
Median Absolute Deviation (MAD)114
Skewness0
Sum103740
Variance17290
MonotonicityStrictly increasing
2023-12-11T12:38:59.281759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
314 1
 
0.2%
312 1
 
0.2%
311 1
 
0.2%
310 1
 
0.2%
309 1
 
0.2%
308 1
 
0.2%
307 1
 
0.2%
306 1
 
0.2%
305 1
 
0.2%
Other values (445) 445
97.8%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
455 1
0.2%
454 1
0.2%
453 1
0.2%
452 1
0.2%
451 1
0.2%
450 1
0.2%
449 1
0.2%
448 1
0.2%
447 1
0.2%
446 1
0.2%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
식품
455 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품 455
100.0%

Length

2023-12-11T12:38:59.427399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:38:59.808145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품 455
100.0%

과제번호
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2563341.9
Minimum1130163
Maximum3150101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-11T12:38:59.918436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1130163
5-th percentile1130213
Q11140282
median3130213
Q33130363
95-th percentile3140202
Maximum3150101
Range2019938
Interquartile range (IQR)1990081

Descriptive statistics

Standard deviation900904.76
Coefficient of variation (CV)0.35145712
Kurtosis-1.0757365
Mean2563341.9
Median Absolute Deviation (MAD)290
Skewness-0.96377589
Sum1.1663206 × 109
Variance8.1162938 × 1011
MonotonicityIncreasing
2023-12-11T12:39:00.148929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3130503 28
 
6.2%
3130103 25
 
5.5%
3120104 25
 
5.5%
3130403 24
 
5.3%
3120494 20
 
4.4%
3130213 20
 
4.4%
1130453 18
 
4.0%
1130243 18
 
4.0%
3130243 17
 
3.7%
3130363 15
 
3.3%
Other values (40) 245
53.8%
ValueCountFrequency (%)
1130163 4
 
0.9%
1130183 9
2.0%
1130203 1
 
0.2%
1130213 10
2.2%
1130233 7
 
1.5%
1130243 18
4.0%
1130273 6
 
1.3%
1130283 2
 
0.4%
1130293 8
1.8%
1130303 5
 
1.1%
ValueCountFrequency (%)
3150101 1
 
0.2%
3140552 5
 
1.1%
3140532 3
 
0.7%
3140472 11
 
2.4%
3140202 5
 
1.1%
3130503 28
6.2%
3130453 4
 
0.9%
3130443 11
 
2.4%
3130403 24
5.3%
3130373 13
2.9%

과제명
Text

Distinct52
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-11T12:39:00.510423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length47
Mean length35.942857
Min length21

Characters and Unicode

Total characters16354
Distinct characters300
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)1.5%

Sample

1st row분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발
2nd row분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발
3rd row분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발
4th row분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발
5th row마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화
ValueCountFrequency (%)
개발 338
 
8.2%
및 258
 
6.3%
위한 161
 
3.9%
기능성 75
 
1.8%
제품화 48
 
1.2%
기술 46
 
1.1%
활용한 45
 
1.1%
연구 42
 
1.0%
유래 42
 
1.0%
통한 40
 
1.0%
Other values (313) 3026
73.4%
2023-12-11T12:39:01.084529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3681
 
22.5%
개 432
 
2.6%
품 382
 
2.3%
발 378
 
2.3%
기 344
 
2.1%
한 340
 
2.1%
화 327
 
2.0%
용 273
 
1.7%
가 259
 
1.6%
식 258
 
1.6%
Other values (290) 9680
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12039
73.6%
Space Separator 3681
 
22.5%
Lowercase Letter 280
 
1.7%
Uppercase Letter 173
 
1.1%
Other Punctuation 60
 
0.4%
Open Punctuation 47
 
0.3%
Close Punctuation 47
 
0.3%
Dash Punctuation 20
 
0.1%
Decimal Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 432
 
3.6%
품 382
 
3.2%
발 378
 
3.1%
기 344
 
2.9%
한 340
 
2.8%
화 327
 
2.7%
용 273
 
2.3%
가 259
 
2.2%
식 258
 
2.1%
및 258
 
2.1%
Other values (247) 8788
73.0%
Lowercase Letter
ValueCountFrequency (%)
e 46
16.4%
a 42
15.0%
o 38
13.6%
r 30
10.7%
n 27
9.6%
h 18
 
6.4%
c 12
 
4.3%
i 12
 
4.3%
l 12
 
4.3%
s 11
 
3.9%
Other values (7) 32
11.4%
Uppercase Letter
ValueCountFrequency (%)
P 39
22.5%
M 39
22.5%
C 29
16.8%
H 16
9.2%
R 11
 
6.4%
I 6
 
3.5%
T 6
 
3.5%
K 6
 
3.5%
E 5
 
2.9%
O 5
 
2.9%
Other values (5) 11
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 30
50.0%
· 18
30.0%
/ 10
 
16.7%
% 2
 
3.3%
Decimal Number
ValueCountFrequency (%)
0 4
57.1%
1 2
28.6%
3 1
 
14.3%
Space Separator
ValueCountFrequency (%)
3681
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12038
73.6%
Common 3862
 
23.6%
Latin 453
 
2.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 432
 
3.6%
품 382
 
3.2%
발 378
 
3.1%
기 344
 
2.9%
한 340
 
2.8%
화 327
 
2.7%
용 273
 
2.3%
가 259
 
2.2%
식 258
 
2.1%
및 258
 
2.1%
Other values (246) 8787
73.0%
Latin
ValueCountFrequency (%)
e 46
 
10.2%
a 42
 
9.3%
P 39
 
8.6%
M 39
 
8.6%
o 38
 
8.4%
r 30
 
6.6%
C 29
 
6.4%
n 27
 
6.0%
h 18
 
4.0%
H 16
 
3.5%
Other values (22) 129
28.5%
Common
ValueCountFrequency (%)
3681
95.3%
( 47
 
1.2%
) 47
 
1.2%
, 30
 
0.8%
- 20
 
0.5%
· 18
 
0.5%
/ 10
 
0.3%
0 4
 
0.1%
1 2
 
0.1%
% 2
 
0.1%
Han
ValueCountFrequency (%)
高 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12038
73.6%
ASCII 4297
 
26.3%
None 18
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3681
85.7%
( 47
 
1.1%
) 47
 
1.1%
e 46
 
1.1%
a 42
 
1.0%
P 39
 
0.9%
M 39
 
0.9%
o 38
 
0.9%
, 30
 
0.7%
r 30
 
0.7%
Other values (32) 258
 
6.0%
Hangul
ValueCountFrequency (%)
개 432
 
3.6%
품 382
 
3.2%
발 378
 
3.1%
기 344
 
2.9%
한 340
 
2.8%
화 327
 
2.7%
용 273
 
2.3%
가 259
 
2.2%
식 258
 
2.1%
및 258
 
2.1%
Other values (246) 8787
73.0%
None
ValueCountFrequency (%)
· 18
100.0%
CJK
ValueCountFrequency (%)
高 1
100.0%

연구책임자
Text

Distinct52
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-11T12:39:01.369985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1365
Distinct characters78
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

Unique7 ?
Unique (%)1.5%

Sample

1st row김동호
2nd row김동호
3rd row김동호
4th row김동호
5th row지근억
ValueCountFrequency (%)
김영붕 28
 
6.2%
조형용 25
 
5.5%
오덕환 25
 
5.5%
김현진 24
 
5.3%
김상숙 20
 
4.4%
장판식 20
 
4.4%
이치호 18
 
4.0%
조향현 18
 
4.0%
이수용 17
 
3.7%
하영식 15
 
3.3%
Other values (42) 245
53.8%
2023-12-11T12:39:01.818391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 98
 
7.2%
현 64
 
4.7%
이 62
 
4.5%
영 56
 
4.1%
조 54
 
4.0%
정 47
 
3.4%
호 45
 
3.3%
용 45
 
3.3%
장 41
 
3.0%
상 38
 
2.8%
Other values (68) 815
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1365
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 98
 
7.2%
현 64
 
4.7%
이 62
 
4.5%
영 56
 
4.1%
조 54
 
4.0%
정 47
 
3.4%
호 45
 
3.3%
용 45
 
3.3%
장 41
 
3.0%
상 38
 
2.8%
Other values (68) 815
59.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1365
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 98
 
7.2%
현 64
 
4.7%
이 62
 
4.5%
영 56
 
4.1%
조 54
 
4.0%
정 47
 
3.4%
호 45
 
3.3%
용 45
 
3.3%
장 41
 
3.0%
상 38
 
2.8%
Other values (68) 815
59.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1365
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 98
 
7.2%
현 64
 
4.7%
이 62
 
4.5%
영 56
 
4.1%
조 54
 
4.0%
정 47
 
3.4%
호 45
 
3.3%
용 45
 
3.3%
장 41
 
3.0%
상 38
 
2.8%
Other values (68) 815
59.7%

논문명
Text

Distinct390
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-11T12:39:02.136600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length209
Median length134
Mean length90.8
Min length13

Characters and Unicode

Total characters41314
Distinct characters417
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)75.8%

Sample

1st rowDroplet Digital PCR을 이용한 Bacillus cereus, Staphylococcus aureus, Salmonella Typhimurium과 Escherichia coli O157:H7의 검출 및 정량
2nd row식품으로부터 식중독 세균 검출을 위한 Real-time PCR에 적합한 DNA 추출 방법 비교
3rd rowWhole genome amplification을 이용한 식중독 세균 신속 검출 기술 개발
4th rowReal-time PCR-based quantification of Shigella sonnei in beef and a modified Gompertz equation-based predictive modeling of its growth
5th rowCharacterization of soybean fermented by aflatoxin non-producing Aspergillus oryzae and γ-aminobutyric acid producing Lactobacillus brevis
ValueCountFrequency (%)
of 339
 
5.7%
and 240
 
4.0%
in 127
 
2.1%
the 85
 
1.4%
on 69
 
1.2%
with 54
 
0.9%
및 50
 
0.8%
by 48
 
0.8%
a 44
 
0.7%
from 44
 
0.7%
Other values (2101) 4837
81.5%
2023-12-11T12:39:02.590621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5489
 
13.3%
i 2906
 
7.0%
e 2898
 
7.0%
a 2560
 
6.2%
o 2379
 
5.8%
t 2364
 
5.7%
n 2154
 
5.2%
r 1664
 
4.0%
s 1629
 
3.9%
c 1453
 
3.5%
Other values (407) 15818
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28379
68.7%
Space Separator 5489
 
13.3%
Other Letter 4270
 
10.3%
Uppercase Letter 2349
 
5.7%
Dash Punctuation 280
 
0.7%
Other Punctuation 207
 
0.5%
Decimal Number 201
 
0.5%
Close Punctuation 64
 
0.2%
Open Punctuation 64
 
0.2%
Connector Punctuation 7
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 154
 
3.6%
성 128
 
3.0%
한 110
 
2.6%
분 94
 
2.2%
이 92
 
2.2%
가 78
 
1.8%
에 78
 
1.8%
질 72
 
1.7%
품 68
 
1.6%
기 67
 
1.6%
Other values (323) 3329
78.0%
Lowercase Letter
ValueCountFrequency (%)
i 2906
10.2%
e 2898
10.2%
a 2560
 
9.0%
o 2379
 
8.4%
t 2364
 
8.3%
n 2154
 
7.6%
r 1664
 
5.9%
s 1629
 
5.7%
c 1453
 
5.1%
l 1354
 
4.8%
Other values (19) 7018
24.7%
Uppercase Letter
ValueCountFrequency (%)
C 258
 
11.0%
S 220
 
9.4%
A 201
 
8.6%
P 198
 
8.4%
E 160
 
6.8%
I 139
 
5.9%
L 113
 
4.8%
M 109
 
4.6%
R 106
 
4.5%
D 104
 
4.4%
Other values (16) 741
31.5%
Decimal Number
ValueCountFrequency (%)
1 49
24.4%
2 40
19.9%
7 23
11.4%
3 22
10.9%
5 21
10.4%
0 13
 
6.5%
4 13
 
6.5%
6 10
 
5.0%
9 5
 
2.5%
8 5
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 99
47.8%
. 39
 
18.8%
: 30
 
14.5%
/ 25
 
12.1%
% 6
 
2.9%
' 3
 
1.4%
¡ 2
 
1.0%
¿ 2
 
1.0%
; 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 62
96.9%
] 2
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 62
96.9%
[ 2
 
3.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
5489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 280
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30722
74.4%
Common 6314
 
15.3%
Hangul 4270
 
10.3%
Greek 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 154
 
3.6%
성 128
 
3.0%
한 110
 
2.6%
분 94
 
2.2%
이 92
 
2.2%
가 78
 
1.8%
에 78
 
1.8%
질 72
 
1.7%
품 68
 
1.6%
기 67
 
1.6%
Other values (323) 3329
78.0%
Latin
ValueCountFrequency (%)
i 2906
 
9.5%
e 2898
 
9.4%
a 2560
 
8.3%
o 2379
 
7.7%
t 2364
 
7.7%
n 2154
 
7.0%
r 1664
 
5.4%
s 1629
 
5.3%
c 1453
 
4.7%
l 1354
 
4.4%
Other values (44) 9361
30.5%
Common
ValueCountFrequency (%)
5489
86.9%
- 280
 
4.4%
, 99
 
1.6%
) 62
 
1.0%
( 62
 
1.0%
1 49
 
0.8%
2 40
 
0.6%
. 39
 
0.6%
: 30
 
0.5%
/ 25
 
0.4%
Other values (17) 139
 
2.2%
Greek
ValueCountFrequency (%)
γ 4
50.0%
β 3
37.5%
α 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37028
89.6%
Hangul 4270
 
10.3%
None 12
 
< 0.1%
Punctuation 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5489
14.8%
i 2906
 
7.8%
e 2898
 
7.8%
a 2560
 
6.9%
o 2379
 
6.4%
t 2364
 
6.4%
n 2154
 
5.8%
r 1664
 
4.5%
s 1629
 
4.4%
c 1453
 
3.9%
Other values (66) 11532
31.1%
Hangul
ValueCountFrequency (%)
의 154
 
3.6%
성 128
 
3.0%
한 110
 
2.6%
분 94
 
2.2%
이 92
 
2.2%
가 78
 
1.8%
에 78
 
1.8%
질 72
 
1.7%
품 68
 
1.6%
기 67
 
1.6%
Other values (323) 3329
78.0%
None
ValueCountFrequency (%)
γ 4
33.3%
β 3
25.0%
¡ 2
16.7%
¿ 2
16.7%
α 1
 
8.3%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅲ 1
50.0%

학술지 출판년도
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2016
196 
2015
144 
2014
69 
2017
43 
2013
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2014

Common Values

ValueCountFrequency (%)
2016 196
43.1%
2015 144
31.6%
2014 69
 
15.2%
2017 43
 
9.5%
2013 3
 
0.7%

Length

2023-12-11T12:39:02.708778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:39:02.789858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 196
43.1%
2015 144
31.6%
2014 69
 
15.2%
2017 43
 
9.5%
2013 3
 
0.7%

저자
Text

MISSING 

Distinct325
Distinct (%)72.7%
Missing8
Missing (%)1.8%
Memory size3.7 KiB
2023-12-11T12:39:03.106224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length3
Mean length7.1185682
Min length2

Characters and Unicode

Total characters3182
Distinct characters177
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)56.2%

Sample

1st row김진희
2nd row구은정
3rd row성지영
4th row채창훈
5th rowNam Yeun Kim
ValueCountFrequency (%)
kim 31
 
4.3%
lee 22
 
3.1%
park 17
 
2.4%
김지한 8
 
1.1%
nam 8
 
1.1%
ji 8
 
1.1%
김희경 7
 
1.0%
jeong 7
 
1.0%
choi 7
 
1.0%
곽한섭 6
 
0.8%
Other values (396) 594
83.1%
2023-12-11T12:39:03.590312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
268
 
8.4%
n 234
 
7.4%
o 203
 
6.4%
e 165
 
5.2%
a 159
 
5.0%
i 133
 
4.2%
u 118
 
3.7%
h 105
 
3.3%
g 103
 
3.2%
H 70
 
2.2%
Other values (167) 1624
51.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1517
47.7%
Other Letter 757
23.8%
Uppercase Letter 577
 
18.1%
Space Separator 268
 
8.4%
Other Punctuation 60
 
1.9%
Decimal Number 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 61
 
8.1%
이 47
 
6.2%
정 37
 
4.9%
지 36
 
4.8%
희 27
 
3.6%
경 26
 
3.4%
영 23
 
3.0%
박 23
 
3.0%
한 21
 
2.8%
선 21
 
2.8%
Other values (111) 435
57.5%
Lowercase Letter
ValueCountFrequency (%)
n 234
15.4%
o 203
13.4%
e 165
10.9%
a 159
10.5%
i 133
8.8%
u 118
7.8%
h 105
6.9%
g 103
6.8%
m 58
 
3.8%
k 38
 
2.5%
Other values (15) 201
13.2%
Uppercase Letter
ValueCountFrequency (%)
H 70
12.1%
J 67
11.6%
S 65
11.3%
Y 54
9.4%
K 54
9.4%
C 40
 
6.9%
L 36
 
6.2%
M 26
 
4.5%
N 25
 
4.3%
P 22
 
3.8%
Other values (13) 118
20.5%
Other Punctuation
ValueCountFrequency (%)
. 22
36.7%
; 20
33.3%
, 17
28.3%
* 1
 
1.7%
Space Separator
ValueCountFrequency (%)
268
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2094
65.8%
Hangul 757
 
23.8%
Common 331
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 61
 
8.1%
이 47
 
6.2%
정 37
 
4.9%
지 36
 
4.8%
희 27
 
3.6%
경 26
 
3.4%
영 23
 
3.0%
박 23
 
3.0%
한 21
 
2.8%
선 21
 
2.8%
Other values (111) 435
57.5%
Latin
ValueCountFrequency (%)
n 234
 
11.2%
o 203
 
9.7%
e 165
 
7.9%
a 159
 
7.6%
i 133
 
6.4%
u 118
 
5.6%
h 105
 
5.0%
g 103
 
4.9%
H 70
 
3.3%
J 67
 
3.2%
Other values (38) 737
35.2%
Common
ValueCountFrequency (%)
268
81.0%
. 22
 
6.6%
; 20
 
6.0%
, 17
 
5.1%
* 1
 
0.3%
1 1
 
0.3%
( 1
 
0.3%
) 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2425
76.2%
Hangul 757
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
268
 
11.1%
n 234
 
9.6%
o 203
 
8.4%
e 165
 
6.8%
a 159
 
6.6%
i 133
 
5.5%
u 118
 
4.9%
h 105
 
4.3%
g 103
 
4.2%
H 70
 
2.9%
Other values (46) 867
35.8%
Hangul
ValueCountFrequency (%)
김 61
 
8.1%
이 47
 
6.2%
정 37
 
4.9%
지 36
 
4.8%
희 27
 
3.6%
경 26
 
3.4%
영 23
 
3.0%
박 23
 
3.0%
한 21
 
2.8%
선 21
 
2.8%
Other values (111) 435
57.5%

학술지명
Text

Distinct219
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-11T12:39:03.896675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length53
Mean length25.318681
Min length4

Characters and Unicode

Total characters11520
Distinct characters131
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)29.0%

Sample

1st rowKorean Journal of Food Science and Technology
2nd rowKorean Journal of Food Science and Technology
3rd row한국식품과학회지
4th rowApplied Biological Chemistry
5th rowJournal of the Korean Society for Applied Biological Chemistry
ValueCountFrequency (%)
of 163
 
10.2%
food 161
 
10.1%
journal 142
 
8.9%
and 120
 
7.5%
science 104
 
6.5%
biotechnology 45
 
2.8%
korean 44
 
2.8%
28
 
1.8%
technology 27
 
1.7%
microbiology 24
 
1.5%
Other values (246) 737
46.2%
2023-12-11T12:39:04.378258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1184
 
10.3%
1144
 
9.9%
n 742
 
6.4%
e 732
 
6.4%
i 642
 
5.6%
a 540
 
4.7%
r 508
 
4.4%
c 503
 
4.4%
l 431
 
3.7%
t 376
 
3.3%
Other values (121) 4718
41.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7576
65.8%
Uppercase Letter 1491
 
12.9%
Other Letter 1216
 
10.6%
Space Separator 1144
 
9.9%
Other Punctuation 58
 
0.5%
Math Symbol 14
 
0.1%
Dash Punctuation 13
 
0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 130
 
10.7%
회 118
 
9.7%
국 107
 
8.8%
한 107
 
8.8%
지 98
 
8.1%
식 78
 
6.4%
품 72
 
5.9%
과 54
 
4.4%
유 43
 
3.5%
공 42
 
3.5%
Other values (59) 367
30.2%
Lowercase Letter
ValueCountFrequency (%)
o 1184
15.6%
n 742
9.8%
e 732
9.7%
i 642
8.5%
a 540
 
7.1%
r 508
 
6.7%
c 503
 
6.6%
l 431
 
5.7%
t 376
 
5.0%
d 320
 
4.2%
Other values (16) 1598
21.1%
Uppercase Letter
ValueCountFrequency (%)
F 167
11.2%
S 164
 
11.0%
J 147
 
9.9%
A 102
 
6.8%
E 99
 
6.6%
N 94
 
6.3%
O 86
 
5.8%
C 81
 
5.4%
B 72
 
4.8%
R 69
 
4.6%
Other values (14) 410
27.5%
Other Punctuation
ValueCountFrequency (%)
. 40
69.0%
& 12
 
20.7%
: 4
 
6.9%
, 2
 
3.4%
Math Symbol
ValueCountFrequency (%)
= 11
78.6%
+ 3
 
21.4%
Close Punctuation
ValueCountFrequency (%)
) 3
75.0%
] 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 3
75.0%
[ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9067
78.7%
Common 1237
 
10.7%
Hangul 1216
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 130
 
10.7%
회 118
 
9.7%
국 107
 
8.8%
한 107
 
8.8%
지 98
 
8.1%
식 78
 
6.4%
품 72
 
5.9%
과 54
 
4.4%
유 43
 
3.5%
공 42
 
3.5%
Other values (59) 367
30.2%
Latin
ValueCountFrequency (%)
o 1184
 
13.1%
n 742
 
8.2%
e 732
 
8.1%
i 642
 
7.1%
a 540
 
6.0%
r 508
 
5.6%
c 503
 
5.5%
l 431
 
4.8%
t 376
 
4.1%
d 320
 
3.5%
Other values (40) 3089
34.1%
Common
ValueCountFrequency (%)
1144
92.5%
. 40
 
3.2%
- 13
 
1.1%
& 12
 
1.0%
= 11
 
0.9%
: 4
 
0.3%
) 3
 
0.2%
+ 3
 
0.2%
( 3
 
0.2%
, 2
 
0.2%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10304
89.4%
Hangul 1216
 
10.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1184
 
11.5%
1144
 
11.1%
n 742
 
7.2%
e 732
 
7.1%
i 642
 
6.2%
a 540
 
5.2%
r 508
 
4.9%
c 503
 
4.9%
l 431
 
4.2%
t 376
 
3.6%
Other values (52) 3502
34.0%
Hangul
ValueCountFrequency (%)
학 130
 
10.7%
회 118
 
9.7%
국 107
 
8.8%
한 107
 
8.8%
지 98
 
8.1%
식 78
 
6.4%
품 72
 
5.9%
과 54
 
4.4%
유 43
 
3.5%
공 42
 
3.5%
Other values (59) 367
30.2%

Interactions

2023-12-11T12:38:58.632193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:38:58.449594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:38:58.725084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:38:58.533850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:39:04.523150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호과제번호과제명연구책임자학술지 출판년도
번호1.0000.9980.9950.9950.431
과제번호0.9981.0001.0001.0000.130
과제명0.9951.0001.0001.0000.585
연구책임자0.9951.0001.0001.0000.585
학술지 출판년도0.4310.1300.5850.5851.000
2023-12-11T12:39:04.660061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호과제번호학술지 출판년도
번호1.0000.9990.192
과제번호0.9991.0000.171
학술지 출판년도0.1920.1711.000

Missing values

2023-12-11T12:38:58.880068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:38:59.035854image/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

번호분류과제번호과제명연구책임자논문명학술지 출판년도저자학술지명
01식품1130163분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발김동호Droplet Digital PCR을 이용한 Bacillus cereus, Staphylococcus aureus, Salmonella Typhimurium과 Escherichia coli O157:H7의 검출 및 정량2016김진희Korean Journal of Food Science and Technology
12식품1130163분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발김동호식품으로부터 식중독 세균 검출을 위한 Real-time PCR에 적합한 DNA 추출 방법 비교2016구은정Korean Journal of Food Science and Technology
23식품1130163분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발김동호Whole genome amplification을 이용한 식중독 세균 신속 검출 기술 개발2016성지영한국식품과학회지
34식품1130163분자 농축 기술 개발을 통한 식중독균 검출시간 단축 및 현장형 검출시스템 개발김동호Real-time PCR-based quantification of Shigella sonnei in beef and a modified Gompertz equation-based predictive modeling of its growth2016채창훈Applied Biological Chemistry
45식품1130183마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화지근억Characterization of soybean fermented by aflatoxin non-producing Aspergillus oryzae and γ-aminobutyric acid producing Lactobacillus brevis2014Nam Yeun KimJournal of the Korean Society for Applied Biological Chemistry
56식품1130183마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화지근억γ-Aminobutyric Acid (GABA) Production and Angiotensin-I Converting Enzyme (ACE) Inhibitory Activity of Fermented Soybean Containing Sea Tangle by the Co-Culture of Lactobacillus brevis with Aspergillus oryzae.2015Eun Kyeong JangJournal of microbiology and biotechnology
67식품1130183마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화지근억An Evaluation of Aflatoxin and Cyclopiazonic Acid Production in Aspergillus oryzae2014Nam Yeun KimJournal of food protection
78식품1130183마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화지근억Fermentation of Platycodi radix and bioconversion of platycosides using co-cultures of Saccharomyces cerevisiae KCTC 7928 and Aspergillus awamori FMB S9002015Yul ly HwangFood science and biotechnology
89식품1130183마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화지근억Characterization of the Production of Biogenic Amines and Gamma-Aminobutyric Acid in the Soybean Pastes Fermented by Aspergillus oryzae and Lactobacillus brevis2015Nam Yeun KimJournal of microbiology and biotechnology
910식품1130183마이코톡신 프리 가바 함유 고기능성 저염 된장의 제품화지근억Production of γ-aminobutyric acid during fermentation of Gastrodia elata Bl. by co-culture of Lactobacillus brevis GABA 100 with Bifidobacterium bifidum BGN42014Kim, J. A.;Food science and biotechnology
번호분류과제번호과제명연구책임자논문명학술지 출판년도저자학술지명
445446식품3140472수출용 대용량 HMR 식자재 상품 개발윤원병Characterizing Texture, Color and Sensory Attributes of Cookies Made with Jerusalem2016Youn Ju Leeinterntional journal of food engineering
446447식품3140532고령층 영양섭취 및 면역증진을 위한 시리얼 및 곡물 유동식 제품 개발이점균고령층을 위한 포장디자인 연구2016손수경한국일러스아트학회
447448식품3140532고령층 영양섭취 및 면역증진을 위한 시리얼 및 곡물 유동식 제품 개발이점균Enzymatic Susceptibility of Wheat Gluten after Subcritical Water Treatment2016황윤희Food Science and Biotechnology
448449식품3140532고령층 영양섭취 및 면역증진을 위한 시리얼 및 곡물 유동식 제품 개발이점균간편 가정식 포장디자인에 관한 연구 -포장연구를 중심으로 -2016손수경A Treatise On The Plastic Media
449450식품3140552한식소비층 확대를 위한 아동용 메뉴 현지정보 수집 및 메뉴 개발홍상필지역별 전통된장과 개량된장의 품질특성2016박선영한국식품조리과학회지
450451식품3140552한식소비층 확대를 위한 아동용 메뉴 현지정보 수집 및 메뉴 개발홍상필영유아 이유식 브랜드 이미지가 브랜드 관계의 질과 재이용의도에 미치는 영향2017이호진Journal of Nutrition and Health
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