Overview

Dataset statistics

Number of variables9
Number of observations394
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.6 KiB
Average record size in memory74.3 B

Variable types

Text5
Categorical3
Numeric1

Dataset

Description해양수산 분야의 국가연구개발사업 과제 정보(공고번호, 예산년도, 접수번호, 사업명, 과제명, 연구책임자, 주관연구개발기관, 과제담당자, 확정여부) .
URLhttps://www.data.go.kr/data/15104447/fileData.do

Alerts

확정여부 has constant value ""Constant
과제접수번호 is highly overall correlated with 예산년도 and 1 other fieldsHigh correlation
예산년도 is highly overall correlated with 과제접수번호 and 1 other fieldsHigh correlation
과제담당자 is highly overall correlated with 과제접수번호 and 1 other fieldsHigh correlation
과제접수번호 has unique valuesUnique
과제명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:32:45.233844
Analysis finished2023-12-12 07:32:46.642472
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공고번호
Text

Distinct127
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:32:46.997818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.9238579
Min length6

Characters and Unicode

Total characters2728
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

Unique68 ?
Unique (%)17.3%

Sample

1st row2023-19
2nd row2023-19
3rd row2023-19
4th row2022-310
5th row2022-310
ValueCountFrequency (%)
2020-6 25
 
6.3%
2021-25 24
 
6.1%
2022-39 19
 
4.8%
2020-5 18
 
4.6%
2022-50 15
 
3.8%
2020-4 12
 
3.0%
2021-18 12
 
3.0%
2021-19 12
 
3.0%
2022-32 11
 
2.8%
2022-49 9
 
2.3%
Other values (117) 237
60.2%
2023-12-12T16:32:47.522417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1042
38.2%
0 547
20.1%
- 394
 
14.4%
1 243
 
8.9%
5 92
 
3.4%
9 86
 
3.2%
4 79
 
2.9%
3 77
 
2.8%
8 68
 
2.5%
6 67
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2334
85.6%
Dash Punctuation 394
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1042
44.6%
0 547
23.4%
1 243
 
10.4%
5 92
 
3.9%
9 86
 
3.7%
4 79
 
3.4%
3 77
 
3.3%
8 68
 
2.9%
6 67
 
2.9%
7 33
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2728
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1042
38.2%
0 547
20.1%
- 394
 
14.4%
1 243
 
8.9%
5 92
 
3.4%
9 86
 
3.2%
4 79
 
2.9%
3 77
 
2.8%
8 68
 
2.5%
6 67
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1042
38.2%
0 547
20.1%
- 394
 
14.4%
1 243
 
8.9%
5 92
 
3.4%
9 86
 
3.2%
4 79
 
2.9%
3 77
 
2.8%
8 68
 
2.5%
6 67
 
2.5%

예산년도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2022
143 
2021
139 
2020
102 
2023
 
10

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2022 143
36.3%
2021 139
35.3%
2020 102
25.9%
2023 10
 
2.5%

Length

2023-12-12T16:32:47.685021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:32:47.808485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 143
36.3%
2021 139
35.3%
2020 102
25.9%
2023 10
 
2.5%

과제접수번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct394
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20211918
Minimum20200004
Maximum20230022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-12T16:32:47.956193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200004
5-th percentile20200128
Q120200612
median20210598
Q320220314
95-th percentile20220582
Maximum20230022
Range30018
Interquartile range (IQR)19701.75

Descriptive statistics

Standard deviation8364.735
Coefficient of variation (CV)0.00041385163
Kurtosis-1.1013256
Mean20211918
Median Absolute Deviation (MAD)9727
Skewness-0.057883551
Sum7.9634956 × 109
Variance69968792
MonotonicityStrictly decreasing
2023-12-12T16:32:48.123382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230022 1
 
0.3%
20210159 1
 
0.3%
20210176 1
 
0.3%
20210178 1
 
0.3%
20210179 1
 
0.3%
20210180 1
 
0.3%
20210184 1
 
0.3%
20210194 1
 
0.3%
20210199 1
 
0.3%
20210220 1
 
0.3%
Other values (384) 384
97.5%
ValueCountFrequency (%)
20200004 1
0.3%
20200006 1
0.3%
20200025 1
0.3%
20200028 1
0.3%
20200034 1
0.3%
20200038 1
0.3%
20200067 1
0.3%
20200068 1
0.3%
20200073 1
0.3%
20200075 1
0.3%
ValueCountFrequency (%)
20230022 1
0.3%
20230021 1
0.3%
20230018 1
0.3%
20230015 1
0.3%
20230010 1
0.3%
20230009 1
0.3%
20230008 1
0.3%
20230007 1
0.3%
20230005 1
0.3%
20230003 1
0.3%

사업명
Text

Distinct87
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:32:48.525923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length19.068528
Min length8

Characters and Unicode

Total characters7513
Distinct characters259
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

Unique39 ?
Unique (%)9.9%

Sample

1st row해양수산 도전적 R&D 시범사업
2nd row해양수산 도전적 R&D 시범사업
3rd row해양수산 도전적 R&D 시범사업
4th row해양수산산업 핵심 기자재 국산화 및 표준화 기술개발
5th row해양수산산업 핵심 기자재 국산화 및 표준화 기술개발
ValueCountFrequency (%)
및 139
 
7.6%
개발 133
 
7.3%
기술개발 122
 
6.7%
지원 105
 
5.8%
해양 79
 
4.3%
상용화 70
 
3.8%
바이오 69
 
3.8%
전략소재 68
 
3.7%
해양산업 54
 
3.0%
해양수산 54
 
3.0%
Other values (248) 926
50.9%
2023-12-12T16:32:49.062283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1427
 
19.0%
기 326
 
4.3%
해 292
 
3.9%
발 282
 
3.8%
개 281
 
3.7%
양 262
 
3.5%
산 245
 
3.3%
술 238
 
3.2%
업 219
 
2.9%
수 183
 
2.4%
Other values (249) 3758
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5752
76.6%
Space Separator 1427
 
19.0%
Lowercase Letter 169
 
2.2%
Uppercase Letter 98
 
1.3%
Dash Punctuation 36
 
0.5%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%
Other Punctuation 10
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 326
 
5.7%
해 292
 
5.1%
발 282
 
4.9%
개 281
 
4.9%
양 262
 
4.6%
산 245
 
4.3%
술 238
 
4.1%
업 219
 
3.8%
수 183
 
3.2%
화 163
 
2.8%
Other values (220) 3261
56.7%
Uppercase Letter
ValueCountFrequency (%)
S 28
28.6%
I 15
15.3%
O 9
 
9.2%
M 9
 
9.2%
N 7
 
7.1%
T 6
 
6.1%
L 5
 
5.1%
G 5
 
5.1%
C 3
 
3.1%
D 3
 
3.1%
Other values (4) 8
 
8.2%
Lowercase Letter
ValueCountFrequency (%)
p 28
16.6%
u 28
16.6%
e 28
16.6%
l 28
16.6%
a 28
16.6%
c 28
16.6%
o 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
· 5
50.0%
& 3
30.0%
, 2
 
20.0%
Space Separator
ValueCountFrequency (%)
1427
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5752
76.6%
Common 1494
 
19.9%
Latin 267
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 326
 
5.7%
해 292
 
5.1%
발 282
 
4.9%
개 281
 
4.9%
양 262
 
4.6%
산 245
 
4.3%
술 238
 
4.1%
업 219
 
3.8%
수 183
 
3.2%
화 163
 
2.8%
Other values (220) 3261
56.7%
Latin
ValueCountFrequency (%)
S 28
10.5%
p 28
10.5%
u 28
10.5%
e 28
10.5%
l 28
10.5%
a 28
10.5%
c 28
10.5%
I 15
 
5.6%
O 9
 
3.4%
M 9
 
3.4%
Other values (11) 38
14.2%
Common
ValueCountFrequency (%)
1427
95.5%
- 36
 
2.4%
( 10
 
0.7%
) 10
 
0.7%
· 5
 
0.3%
& 3
 
0.2%
, 2
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5752
76.6%
ASCII 1756
 
23.4%
None 5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1427
81.3%
- 36
 
2.1%
S 28
 
1.6%
p 28
 
1.6%
u 28
 
1.6%
e 28
 
1.6%
l 28
 
1.6%
a 28
 
1.6%
c 28
 
1.6%
I 15
 
0.9%
Other values (18) 82
 
4.7%
Hangul
ValueCountFrequency (%)
기 326
 
5.7%
해 292
 
5.1%
발 282
 
4.9%
개 281
 
4.9%
양 262
 
4.6%
산 245
 
4.3%
술 238
 
4.1%
업 219
 
3.8%
수 183
 
3.2%
화 163
 
2.8%
Other values (220) 3261
56.7%
None
ValueCountFrequency (%)
· 5
100.0%

과제명
Text

UNIQUE 

Distinct394
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:32:49.484010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length106
Median length61
Mean length33.558376
Min length6

Characters and Unicode

Total characters13222
Distinct characters557
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique394 ?
Unique (%)100.0%

Sample

1st row데이터 기반 맞춤형 블루푸드 설계 플랫폼 구축 및 실증
2nd row수산 부산물로부터 유용 곤충을 이용한 중금속이 저감된 고기능성 소재의 자원화 기술 개발
3rd row해양동물에 식물세포를 이식한 혼합영양성 공생체 개발
4th row동해 남서부 해저퇴적물에 기록된 기후 및 퇴적 역사 연구
5th row북서태평양 마젤란해산군 퇴적물의 광물학적, 생지화학적 분석을 통한 심층해류가 퇴적물에 미친 영향 복원
ValueCountFrequency (%)
개발 237
 
7.4%
및 164
 
5.1%
위한 57
 
1.8%
기술 49
 
1.5%
기술개발 48
 
1.5%
시스템 43
 
1.3%
이용한 38
 
1.2%
기반 34
 
1.1%
해양 29
 
0.9%
소재 26
 
0.8%
Other values (1677) 2478
77.4%
2023-12-12T16:32:50.150505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2834
 
21.4%
개 343
 
2.6%
기 337
 
2.5%
발 326
 
2.5%
해 214
 
1.6%
용 182
 
1.4%
한 173
 
1.3%
화 171
 
1.3%
및 164
 
1.2%
이 156
 
1.2%
Other values (547) 8322
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9563
72.3%
Space Separator 2834
 
21.4%
Lowercase Letter 307
 
2.3%
Uppercase Letter 290
 
2.2%
Decimal Number 109
 
0.8%
Other Punctuation 56
 
0.4%
Dash Punctuation 26
 
0.2%
Close Punctuation 18
 
0.1%
Open Punctuation 18
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 343
 
3.6%
기 337
 
3.5%
발 326
 
3.4%
해 214
 
2.2%
용 182
 
1.9%
한 173
 
1.8%
화 171
 
1.8%
및 164
 
1.7%
이 156
 
1.6%
스 141
 
1.5%
Other values (472) 7356
76.9%
Uppercase Letter
ValueCountFrequency (%)
I 29
 
10.0%
S 23
 
7.9%
D 21
 
7.2%
G 21
 
7.2%
N 18
 
6.2%
L 18
 
6.2%
A 18
 
6.2%
P 16
 
5.5%
E 15
 
5.2%
M 15
 
5.2%
Other values (15) 96
33.1%
Lowercase Letter
ValueCountFrequency (%)
e 38
12.4%
t 29
 
9.4%
o 28
 
9.1%
a 23
 
7.5%
r 23
 
7.5%
i 21
 
6.8%
n 18
 
5.9%
s 18
 
5.9%
m 17
 
5.5%
l 14
 
4.6%
Other values (13) 78
25.4%
Decimal Number
ValueCountFrequency (%)
0 31
28.4%
3 19
17.4%
2 15
13.8%
1 14
12.8%
5 10
 
9.2%
8 7
 
6.4%
9 5
 
4.6%
4 5
 
4.6%
7 2
 
1.8%
6 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 28
50.0%
· 15
26.8%
. 7
 
12.5%
/ 3
 
5.4%
？ 2
 
3.6%
& 1
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 15
83.3%
] 1
 
5.6%
」 1
 
5.6%
） 1
 
5.6%
Open Punctuation
ValueCountFrequency (%)
( 15
83.3%
[ 1
 
5.6%
「 1
 
5.6%
（ 1
 
5.6%
Space Separator
ValueCountFrequency (%)
2834
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9561
72.3%
Common 3062
 
23.2%
Latin 597
 
4.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 343
 
3.6%
기 337
 
3.5%
발 326
 
3.4%
해 214
 
2.2%
용 182
 
1.9%
한 173
 
1.8%
화 171
 
1.8%
및 164
 
1.7%
이 156
 
1.6%
스 141
 
1.5%
Other values (471) 7354
76.9%
Latin
ValueCountFrequency (%)
e 38
 
6.4%
I 29
 
4.9%
t 29
 
4.9%
o 28
 
4.7%
a 23
 
3.9%
r 23
 
3.9%
S 23
 
3.9%
D 21
 
3.5%
G 21
 
3.5%
i 21
 
3.5%
Other values (38) 341
57.1%
Common
ValueCountFrequency (%)
2834
92.6%
0 31
 
1.0%
, 28
 
0.9%
- 26
 
0.8%
3 19
 
0.6%
) 15
 
0.5%
( 15
 
0.5%
2 15
 
0.5%
· 15
 
0.5%
1 14
 
0.5%
Other values (17) 50
 
1.6%
Han
ValueCountFrequency (%)
新 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9560
72.3%
ASCII 3637
 
27.5%
None 21
 
0.2%
CJK 2
 
< 0.1%
CJK Compat 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2834
77.9%
e 38
 
1.0%
0 31
 
0.9%
I 29
 
0.8%
t 29
 
0.8%
, 28
 
0.8%
o 28
 
0.8%
- 26
 
0.7%
a 23
 
0.6%
r 23
 
0.6%
Other values (58) 548
 
15.1%
Hangul
ValueCountFrequency (%)
개 343
 
3.6%
기 337
 
3.5%
발 326
 
3.4%
해 214
 
2.2%
용 182
 
1.9%
한 173
 
1.8%
화 171
 
1.8%
및 164
 
1.7%
이 156
 
1.6%
스 141
 
1.5%
Other values (470) 7353
76.9%
None
ValueCountFrequency (%)
· 15
71.4%
？ 2
 
9.5%
」 1
 
4.8%
「 1
 
4.8%
） 1
 
4.8%
（ 1
 
4.8%
CJK
ValueCountFrequency (%)
新 2
100.0%
CJK Compat
ValueCountFrequency (%)
㎥ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

연구책임자
Text

Distinct287
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:32:50.677626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.0431472
Min length2

Characters and Unicode

Total characters1199
Distinct characters149
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique220 ?
Unique (%)55.8%

Sample

1st row이*원
2nd row이*정
3rd row정*진
4th row이*은
5th row양*호
ValueCountFrequency (%)
이*희 5
 
1.3%
김*환 5
 
1.3%
김*식 5
 
1.3%
김*철 4
 
1.0%
박*현 4
 
1.0%
이*수 4
 
1.0%
김*호 4
 
1.0%
강*진 4
 
1.0%
김*수 4
 
1.0%
이*호 4
 
1.0%
Other values (277) 351
89.1%
2023-12-12T16:32:51.295425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 396
33.0%
김 76
 
6.3%
이 66
 
5.5%
박 38
 
3.2%
정 19
 
1.6%
진 19
 
1.6%
현 18
 
1.5%
강 16
 
1.3%
최 16
 
1.3%
희 15
 
1.3%
Other values (139) 520
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 778
64.9%
Other Punctuation 396
33.0%
Uppercase Letter 25
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 76
 
9.8%
이 66
 
8.5%
박 38
 
4.9%
정 19
 
2.4%
진 19
 
2.4%
현 18
 
2.3%
강 16
 
2.1%
최 16
 
2.1%
희 15
 
1.9%
호 15
 
1.9%
Other values (122) 480
61.7%
Uppercase Letter
ValueCountFrequency (%)
E 3
12.0%
L 3
12.0%
M 2
 
8.0%
T 2
 
8.0%
R 2
 
8.0%
O 2
 
8.0%
N 2
 
8.0%
J 1
 
4.0%
A 1
 
4.0%
S 1
 
4.0%
Other values (6) 6
24.0%
Other Punctuation
ValueCountFrequency (%)
* 396
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 778
64.9%
Common 396
33.0%
Latin 25
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 76
 
9.8%
이 66
 
8.5%
박 38
 
4.9%
정 19
 
2.4%
진 19
 
2.4%
현 18
 
2.3%
강 16
 
2.1%
최 16
 
2.1%
희 15
 
1.9%
호 15
 
1.9%
Other values (122) 480
61.7%
Latin
ValueCountFrequency (%)
E 3
12.0%
L 3
12.0%
M 2
 
8.0%
T 2
 
8.0%
R 2
 
8.0%
O 2
 
8.0%
N 2
 
8.0%
J 1
 
4.0%
A 1
 
4.0%
S 1
 
4.0%
Other values (6) 6
24.0%
Common
ValueCountFrequency (%)
* 396
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 778
64.9%
ASCII 421
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 396
94.1%
E 3
 
0.7%
L 3
 
0.7%
M 2
 
0.5%
T 2
 
0.5%
R 2
 
0.5%
O 2
 
0.5%
N 2
 
0.5%
J 1
 
0.2%
A 1
 
0.2%
Other values (7) 7
 
1.7%
Hangul
ValueCountFrequency (%)
김 76
 
9.8%
이 66
 
8.5%
박 38
 
4.9%
정 19
 
2.4%
진 19
 
2.4%
현 18
 
2.3%
강 16
 
2.1%
최 16
 
2.1%
희 15
 
1.9%
호 15
 
1.9%
Other values (122) 480
61.7%

주관연구기관
Text

Distinct229
Distinct (%)58.4%
Missing2
Missing (%)0.5%
Memory size3.2 KiB
2023-12-12T16:32:51.538343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length18
Mean length10.469388
Min length2

Characters and Unicode

Total characters4104
Distinct characters276
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

Unique177 ?
Unique (%)45.2%

Sample

1st row서울대학교 산학협력단
2nd row가천대학교 산학협력단
3rd row서울대학교 산학협력단
4th row한국해양대학교 산학협력단
5th row부산대학교 산학협력단
ValueCountFrequency (%)
한국해양과학기술원 53
 
9.4%
산학협력단 51
 
9.0%
주식회사 46
 
8.1%
부설 25
 
4.4%
선박해양플랜트연구소 18
 
3.2%
부경대학교산학협력단 13
 
2.3%
서울대학교 9
 
1.6%
국립해양생물자원관 7
 
1.2%
극지연구소 7
 
1.2%
중소조선연구원 7
 
1.2%
Other values (232) 330
58.3%
2023-12-12T16:32:51.898115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 258
 
6.3%
174
 
4.2%
주 173
 
4.2%
산 133
 
3.2%
) 122
 
3.0%
( 122
 
3.0%
원 120
 
2.9%
국 115
 
2.8%
해 111
 
2.7%
한 109
 
2.7%
Other values (266) 2667
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3636
88.6%
Space Separator 174
 
4.2%
Close Punctuation 122
 
3.0%
Open Punctuation 122
 
3.0%
Uppercase Letter 37
 
0.9%
Decimal Number 4
 
0.1%
Other Punctuation 4
 
0.1%
Dash Punctuation 3
 
0.1%
Lowercase Letter 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 258
 
7.1%
주 173
 
4.8%
산 133
 
3.7%
원 120
 
3.3%
국 115
 
3.2%
해 111
 
3.1%
한 109
 
3.0%
양 109
 
3.0%
단 106
 
2.9%
대 100
 
2.8%
Other values (244) 2302
63.3%
Uppercase Letter
ValueCountFrequency (%)
T 7
18.9%
C 6
16.2%
D 5
13.5%
E 4
10.8%
M 3
8.1%
K 3
8.1%
H 2
 
5.4%
L 2
 
5.4%
O 2
 
5.4%
S 1
 
2.7%
Other values (2) 2
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3637
88.6%
Common 429
 
10.5%
Latin 38
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 258
 
7.1%
주 173
 
4.8%
산 133
 
3.7%
원 120
 
3.3%
국 115
 
3.2%
해 111
 
3.1%
한 109
 
3.0%
양 109
 
3.0%
단 106
 
2.9%
대 100
 
2.7%
Other values (245) 2303
63.3%
Latin
ValueCountFrequency (%)
T 7
18.4%
C 6
15.8%
D 5
13.2%
E 4
10.5%
M 3
7.9%
K 3
7.9%
H 2
 
5.3%
L 2
 
5.3%
O 2
 
5.3%
S 1
 
2.6%
Other values (3) 3
7.9%
Common
ValueCountFrequency (%)
174
40.6%
) 122
28.4%
( 122
28.4%
- 3
 
0.7%
1 2
 
0.5%
, 2
 
0.5%
2 2
 
0.5%
. 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3636
88.6%
ASCII 467
 
11.4%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 258
 
7.1%
주 173
 
4.8%
산 133
 
3.7%
원 120
 
3.3%
국 115
 
3.2%
해 111
 
3.1%
한 109
 
3.0%
양 109
 
3.0%
단 106
 
2.9%
대 100
 
2.8%
Other values (244) 2302
63.3%
ASCII
ValueCountFrequency (%)
174
37.3%
) 122
26.1%
( 122
26.1%
T 7
 
1.5%
C 6
 
1.3%
D 5
 
1.1%
E 4
 
0.9%
- 3
 
0.6%
M 3
 
0.6%
K 3
 
0.6%
Other values (11) 18
 
3.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

과제담당자
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
손*희
71 
김*림
36 
장*원
28 
박*영
 
19
김*기
 
18
Other values (26)
222 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row정*형
2nd row정*형
3rd row정*형
4th row한*영
5th row한*영

Common Values

ValueCountFrequency (%)
손*희 71
18.0%
김*림 36
 
9.1%
장*원 28
 
7.1%
박*영 19
 
4.8%
김*기 18
 
4.6%
이*진 18
 
4.6%
최*진 18
 
4.6%
박*배 17
 
4.3%
이*현 16
 
4.1%
김*빈 14
 
3.6%
Other values (21) 139
35.3%

Length

2023-12-12T16:32:52.008897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
손*희 71
18.0%
김*림 36
 
9.1%
장*원 28
 
7.1%
박*영 19
 
4.8%
김*기 18
 
4.6%
이*진 18
 
4.6%
최*진 18
 
4.6%
박*배 17
 
4.3%
이*현 16
 
4.1%
김*빈 14
 
3.6%
Other values (21) 139
35.3%

확정여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
확정
394 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
확정 394
100.0%

Length

2023-12-12T16:32:52.117354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:32:52.225299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
확정 394
100.0%

Interactions

2023-12-12T16:32:45.925962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:32:52.288672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산년도과제접수번호사업명과제담당자
예산년도1.0001.0000.9240.864
과제접수번호1.0001.0000.9230.863
사업명0.9240.9231.0000.999
과제담당자0.8640.8630.9991.000
2023-12-12T16:32:52.438438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산년도과제담당자
예산년도1.0000.626
과제담당자0.6261.000
2023-12-12T16:32:52.541806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과제접수번호예산년도과제담당자
과제접수번호1.0001.0000.626
예산년도1.0001.0000.626
과제담당자0.6260.6261.000

Missing values

2023-12-12T16:32:46.405205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:32:46.570226image/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

공고번호예산년도과제접수번호사업명과제명연구책임자주관연구기관과제담당자확정여부
02023-19202320230022해양수산 도전적 R&D 시범사업데이터 기반 맞춤형 블루푸드 설계 플랫폼 구축 및 실증이*원서울대학교 산학협력단정*형확정
12023-19202320230021해양수산 도전적 R&D 시범사업수산 부산물로부터 유용 곤충을 이용한 중금속이 저감된 고기능성 소재의 자원화 기술 개발이*정가천대학교 산학협력단정*형확정
22023-19202320230018해양수산 도전적 R&D 시범사업해양동물에 식물세포를 이식한 혼합영양성 공생체 개발정*진서울대학교 산학협력단정*형확정
32022-310202320230015해양수산산업 핵심 기자재 국산화 및 표준화 기술개발동해 남서부 해저퇴적물에 기록된 기후 및 퇴적 역사 연구이*은한국해양대학교 산학협력단한*영확정
42022-310202320230010해양수산산업 핵심 기자재 국산화 및 표준화 기술개발북서태평양 마젤란해산군 퇴적물의 광물학적, 생지화학적 분석을 통한 심층해류가 퇴적물에 미친 영향 복원양*호부산대학교 산학협력단한*영확정
52022-310202320230009해양수산산업 핵심 기자재 국산화 및 표준화 기술개발북서태평양 심해저 고희토류 점토층의 기원서*아전북대학교 산학협력단한*영확정
62022-310202320230008해양수산산업 핵심 기자재 국산화 및 표준화 기술개발동해환경·생태의 과거와 현재 변화 규명 및 미래 예측최*식충남대학교산학협력단한*영확정
72022-310202320230007해양수산산업 핵심 기자재 국산화 및 표준화 기술개발열대 서인도양 용승 해역의 대기 중 수증기량 일변화 연구나*나서울대학교 산학협력단한*영확정
82022-310202320230005해양수산산업 핵심 기자재 국산화 및 표준화 기술개발인도양 세이셀레스-차고스 수온약층 융기 해역의 중심부에 서식하는 해양수산생물의 시계열 생태 및 분포 역학 특징 추출강*희경상국립대학교 산학협력단한*영확정
92022-310202320230003해양수산산업 핵심 기자재 국산화 및 표준화 기술개발울릉해저간극 심층 해류의 비대칭 변동 특성 연구박*형부경대학교산학협력단한*영확정
공고번호예산년도과제접수번호사업명과제명연구책임자주관연구기관과제담당자확정여부
3842020-5202020200075해양산업 수요기반 기술개발항만 컨테이너 검색기의 사업화 연계기술 개발김*만(주)쎄크최*진확정
3852020-5202020200073해양산업 수요기반 기술개발유산균이 살아있는 고농도 발효 GABA소금의 개발 및 상용화 계획박*현(주)마린바이오프로세스최*진확정
3862020-5202020200068해양산업 수요기반 기술개발해양 생태계 회복력 증대를 위한 생태플랫폼 개발 및 효과 검증손*호(주)해양생태기술연구소최*진확정
3872020-8202020200067IMO 선박 국제규제 선도기술개발8900kW급 엔진용 Helix flow type의 LNG 추진선박용 열교환기 개발이*석(주)마이텍이*력확정
3882020-4202020200038해양산업 수요기반 기술개발선박 발전기 엔진 GE용 저주파수대역72Hz, 108Hz의 10dB 저감 및 방사소음 35dB 저감이 가능한 친환경 하이브리드형 소음기 개발김*석대원엔지니어링김*림확정
3892020-6202020200034해양 바이오 전략소재 개발 및 상용화 지원제주산 해조류 기반의 대사증후군 개선 헬스케어 신소재 DY-NAO의 북미, 유럽 인증 획득 및 해외 진출 사업화이*현다인바이오(주)손*희확정
3902020-5202020200028해양산업 수요기반 기술개발조선소 도장부스 급기용 마이크로웨이브 제습설비박*준(주)에코프로최*진확정
3912020-5202020200025해양산업 수요기반 기술개발EEZ내 불법어업 단속을 위한 저고도 항공 영상 인공지능 분석 및 AIS 연동 관제시스템 개발김*욱(주)스카이시스최*진확정
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