Overview

Dataset statistics

Number of variables13
Number of observations364
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.8 KiB
Average record size in memory106.4 B

Variable types

Numeric2
Categorical6
Text5

Dataset

Description우리 기관이 보유하고 있는 농림식품R&D 중분류 중 기계시스템 R&D 과제정보 공개 분류,사업명,총괄과제번호,세부과제번호,과제명,연구수행기관,주관기관,총연구기간 시작일,총연구기간 종료일,당해년도연구 시작일,당해년도연구 종료일,총연구비,연구내용요약 으로 구성
Author농림식품기술기획평가원
URLhttps://www.data.go.kr/data/15089455/fileData.do

Alerts

분류 has constant value ""Constant
번호 is highly overall correlated with 사업명High correlation
사업명 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
총연구기관 시작일 is highly overall correlated with 사업명 and 3 other fieldsHigh correlation
총연구기간 종료일 is highly overall correlated with 사업명 and 3 other fieldsHigh correlation
당해년연구기간 시작일 is highly overall correlated with 사업명 and 3 other fieldsHigh correlation
당해년연구기간 종료일 is highly overall correlated with 사업명 and 3 other fieldsHigh correlation
당해년연구기간 종료일 is highly imbalanced (88.1%)Imbalance
번호 has unique valuesUnique
세부과제번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:35:43.369926
Analysis finished2023-12-12 23:35:45.078160
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct364
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean182.5
Minimum1
Maximum364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T08:35:45.159466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.15
Q191.75
median182.5
Q3273.25
95-th percentile345.85
Maximum364
Range363
Interquartile range (IQR)181.5

Descriptive statistics

Standard deviation105.22199
Coefficient of variation (CV)0.57655884
Kurtosis-1.2
Mean182.5
Median Absolute Deviation (MAD)91
Skewness0
Sum66430
Variance11071.667
MonotonicityStrictly increasing
2023-12-13T08:35:45.300164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
252 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
244 1
 
0.3%
243 1
 
0.3%
Other values (354) 354
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%
358 1
0.3%
357 1
0.3%
356 1
0.3%
355 1
0.3%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
농림식품 기계ㆍ시스템
364 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
농림식품 기계ㆍ시스템 364
100.0%

Length

2023-12-13T08:35:45.444546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:45.548462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농림식품 364
50.0%
기계ㆍ시스템 364
50.0%

사업명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
내역사업명없음
99 
농기계산업혁신기술
51 
첨단농기계생산
28 
ICT융복합시스템
26 
5G기반 식품안전생산기술개발
24 
Other values (20)
136 

Length

Max length21
Median length15
Mean length9.1730769
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row5G기반 식품안전생산기술개발
2nd row5G기반 식품안전생산기술개발
3rd row5G기반 식품안전생산기술개발
4th row5G기반 식품안전생산기술개발
5th row5G기반 식품안전생산기술개발

Common Values

ValueCountFrequency (%)
내역사업명없음 99
27.2%
농기계산업혁신기술 51
14.0%
첨단농기계생산 28
 
7.7%
ICT융복합시스템 26
 
7.1%
5G기반 식품안전생산기술개발 24
 
6.6%
축산시설환경개선 18
 
4.9%
농기계 성능고도화 15
 
4.1%
차세대 식품가공 기술개발 12
 
3.3%
민간중심 R&D 사업화 지원 12
 
3.3%
에너지자립형생산기술개발 11
 
3.0%
Other values (15) 68
18.7%

Length

2023-12-13T08:35:45.677586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내역사업명없음 99
18.1%
농기계산업혁신기술 51
 
9.3%
첨단농기계생산 28
 
5.1%
ict융복합시스템 26
 
4.8%
5g기반 24
 
4.4%
식품안전생산기술개발 24
 
4.4%
기술개발 23
 
4.2%
사업화 19
 
3.5%
축산시설환경개선 18
 
3.3%
농기계 15
 
2.7%
Other values (35) 220
40.2%

총괄과제번호
Text

Distinct106
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T08:35:45.982750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters2912
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

Unique14 ?
Unique (%)3.8%

Sample

1st row321049-5
2nd row321049-5
3rd row321049-5
4th row321049-5
5th row321049-5
ValueCountFrequency (%)
321049-5 9
 
2.5%
421044-4 8
 
2.2%
421032-4 8
 
2.2%
421008-4 8
 
2.2%
421033-4 7
 
1.9%
121027-3 7
 
1.9%
421035-4 7
 
1.9%
321044-3 7
 
1.9%
421039-3 6
 
1.6%
421031-4 6
 
1.6%
Other values (96) 291
79.9%
2023-12-13T08:35:46.405214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 520
17.9%
2 456
15.7%
3 455
15.6%
1 429
14.7%
- 364
12.5%
4 293
10.1%
5 112
 
3.8%
9 96
 
3.3%
8 79
 
2.7%
6 58
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2548
87.5%
Dash Punctuation 364
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 520
20.4%
2 456
17.9%
3 455
17.9%
1 429
16.8%
4 293
11.5%
5 112
 
4.4%
9 96
 
3.8%
8 79
 
3.1%
6 58
 
2.3%
7 50
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 520
17.9%
2 456
15.7%
3 455
15.6%
1 429
14.7%
- 364
12.5%
4 293
10.1%
5 112
 
3.8%
9 96
 
3.3%
8 79
 
2.7%
6 58
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 520
17.9%
2 456
15.7%
3 455
15.6%
1 429
14.7%
- 364
12.5%
4 293
10.1%
5 112
 
3.8%
9 96
 
3.3%
8 79
 
2.7%
6 58
 
2.0%

세부과제번호
Text

UNIQUE 

Distinct364
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T08:35:46.595684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters5096
Distinct characters16
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

Unique364 ?
Unique (%)100.0%

Sample

1st row321049051HD040
2nd row321049051HD070
3rd row321049051SB010
4th row321049051HD030
5th row321049051HD0b0
ValueCountFrequency (%)
321049051hd040 1
 
0.3%
821049031sb010 1
 
0.3%
821048031sb010 1
 
0.3%
121025031hd030 1
 
0.3%
121025031hd020 1
 
0.3%
121025031sb010 1
 
0.3%
120101032hd020 1
 
0.3%
120101032sb010 1
 
0.3%
120100032hd030 1
 
0.3%
120100032hd040 1
 
0.3%
Other values (354) 354
97.3%
2023-12-13T08:35:46.943191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1607
31.5%
1 776
15.2%
2 618
 
12.1%
3 550
 
10.8%
4 344
 
6.8%
H 260
 
5.1%
D 260
 
5.1%
5 150
 
2.9%
S 104
 
2.0%
B 104
 
2.0%
Other values (6) 323
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4366
85.7%
Uppercase Letter 728
 
14.3%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1607
36.8%
1 776
17.8%
2 618
 
14.2%
3 550
 
12.6%
4 344
 
7.9%
5 150
 
3.4%
9 98
 
2.2%
8 85
 
1.9%
6 79
 
1.8%
7 59
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
H 260
35.7%
D 260
35.7%
S 104
 
14.3%
B 104
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
a 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4366
85.7%
Latin 730
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1607
36.8%
1 776
17.8%
2 618
 
14.2%
3 550
 
12.6%
4 344
 
7.9%
5 150
 
3.4%
9 98
 
2.2%
8 85
 
1.9%
6 79
 
1.8%
7 59
 
1.4%
Latin
ValueCountFrequency (%)
H 260
35.6%
D 260
35.6%
S 104
 
14.2%
B 104
 
14.2%
b 1
 
0.1%
a 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5096
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1607
31.5%
1 776
15.2%
2 618
 
12.1%
3 550
 
10.8%
4 344
 
6.8%
H 260
 
5.1%
D 260
 
5.1%
5 150
 
2.9%
S 104
 
2.0%
B 104
 
2.0%
Other values (6) 323
 
6.3%

과제명
Text

Distinct316
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T08:35:47.263618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length45
Mean length29.785714
Min length10

Characters and Unicode

Total characters10842
Distinct characters449
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

Unique291 ?
Unique (%)79.9%

Sample

1st row수삼 및 홍삼의 분광 영상 획득 및 AI 학습용 데이터 구축
2nd row고춧가루 품위 적용을 위한 브랜딩 기준 도출 및 맛김치 이물 제어 시스템의 현장 실증
3rd row식품 품질인식 등급 판정이 가능한 품질 결정 기술 및 맛김치 이물 검출 자동화/로봇 시스템 개발
4th row딥러닝을 이용한 영상 및 초분광 이미징 검사시스템 개발
5th row수삼 품질 판정용 자동화 라인 및 로봇 시스템 개발
ValueCountFrequency (%)
개발 246
 
8.4%
및 199
 
6.8%
시스템 66
 
2.3%
기술 58
 
2.0%
기반 51
 
1.7%
위한 45
 
1.5%
실증 37
 
1.3%
스마트 24
 
0.8%
구축 24
 
0.8%
로봇 22
 
0.8%
Other values (1008) 2152
73.6%
2023-12-13T08:35:47.852065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2568
 
23.7%
발 297
 
2.7%
개 285
 
2.6%
기 277
 
2.6%
및 199
 
1.8%
스 161
 
1.5%
용 151
 
1.4%
시 135
 
1.2%
화 128
 
1.2%
이 125
 
1.2%
Other values (439) 6516
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7857
72.5%
Space Separator 2568
 
23.7%
Uppercase Letter 170
 
1.6%
Lowercase Letter 94
 
0.9%
Decimal Number 73
 
0.7%
Other Punctuation 23
 
0.2%
Open Punctuation 20
 
0.2%
Close Punctuation 19
 
0.2%
Dash Punctuation 18
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 297
 
3.8%
개 285
 
3.6%
기 277
 
3.5%
및 199
 
2.5%
스 161
 
2.0%
용 151
 
1.9%
시 135
 
1.7%
화 128
 
1.6%
이 125
 
1.6%
한 107
 
1.4%
Other values (384) 5992
76.3%
Lowercase Letter
ValueCountFrequency (%)
k 15
16.0%
e 11
11.7%
i 9
9.6%
o 7
 
7.4%
s 7
 
7.4%
v 6
 
6.4%
c 6
 
6.4%
a 6
 
6.4%
t 5
 
5.3%
p 4
 
4.3%
Other values (9) 18
19.1%
Uppercase Letter
ValueCountFrequency (%)
I 25
14.7%
T 21
12.4%
W 20
11.8%
C 18
10.6%
A 15
8.8%
G 10
 
5.9%
O 10
 
5.9%
H 9
 
5.3%
E 8
 
4.7%
B 7
 
4.1%
Other values (8) 27
15.9%
Decimal Number
ValueCountFrequency (%)
5 25
34.2%
1 13
17.8%
7 10
 
13.7%
2 8
 
11.0%
3 7
 
9.6%
4 5
 
6.8%
0 4
 
5.5%
9 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 15
65.2%
. 4
 
17.4%
& 3
 
13.0%
% 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 18
94.7%
] 1
 
5.3%
Space Separator
ValueCountFrequency (%)
2568
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7857
72.5%
Common 2721
 
25.1%
Latin 264
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
발 297
 
3.8%
개 285
 
3.6%
기 277
 
3.5%
및 199
 
2.5%
스 161
 
2.0%
용 151
 
1.9%
시 135
 
1.7%
화 128
 
1.6%
이 125
 
1.6%
한 107
 
1.4%
Other values (384) 5992
76.3%
Latin
ValueCountFrequency (%)
I 25
 
9.5%
T 21
 
8.0%
W 20
 
7.6%
C 18
 
6.8%
k 15
 
5.7%
A 15
 
5.7%
e 11
 
4.2%
G 10
 
3.8%
O 10
 
3.8%
i 9
 
3.4%
Other values (27) 110
41.7%
Common
ValueCountFrequency (%)
2568
94.4%
5 25
 
0.9%
( 19
 
0.7%
) 18
 
0.7%
- 18
 
0.7%
/ 15
 
0.6%
1 13
 
0.5%
7 10
 
0.4%
2 8
 
0.3%
3 7
 
0.3%
Other values (8) 20
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7857
72.5%
ASCII 2985
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2568
86.0%
5 25
 
0.8%
I 25
 
0.8%
T 21
 
0.7%
W 20
 
0.7%
( 19
 
0.6%
) 18
 
0.6%
C 18
 
0.6%
- 18
 
0.6%
/ 15
 
0.5%
Other values (45) 238
 
8.0%
Hangul
ValueCountFrequency (%)
발 297
 
3.8%
개 285
 
3.6%
기 277
 
3.5%
및 199
 
2.5%
스 161
 
2.0%
용 151
 
1.9%
시 135
 
1.7%
화 128
 
1.6%
이 125
 
1.6%
한 107
 
1.4%
Other values (384) 5992
76.3%

연구수행기관
Text

Distinct214
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T08:35:48.107967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.206044
Min length2

Characters and Unicode

Total characters3351
Distinct characters268
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

Unique161 ?
Unique (%)44.2%

Sample

1st row경북대학교 산학협력단
2nd row대상(주)
3rd row한국식품연구원
4th row오즈레이주식회사
5th row주식회사 대도
ValueCountFrequency (%)
산학협력단 81
 
16.3%
주식회사 26
 
5.2%
충남대학교 17
 
3.4%
국립농업과학원 13
 
2.6%
전남대학교 9
 
1.8%
한국식품연구원 8
 
1.6%
농업기술실용화재단 8
 
1.6%
서울대학교 8
 
1.6%
강원대학교 7
 
1.4%
전북대학교산학협력단 7
 
1.4%
Other values (218) 313
63.0%
2023-12-13T08:35:48.658048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 225
 
6.7%
주 138
 
4.1%
133
 
4.0%
산 122
 
3.6%
대 116
 
3.5%
단 108
 
3.2%
( 104
 
3.1%
) 104
 
3.1%
협 103
 
3.1%
력 101
 
3.0%
Other values (258) 2097
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2996
89.4%
Space Separator 133
 
4.0%
Open Punctuation 104
 
3.1%
Close Punctuation 104
 
3.1%
Uppercase Letter 10
 
0.3%
Decimal Number 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 225
 
7.5%
주 138
 
4.6%
산 122
 
4.1%
대 116
 
3.9%
단 108
 
3.6%
협 103
 
3.4%
력 101
 
3.4%
교 98
 
3.3%
원 98
 
3.3%
국 81
 
2.7%
Other values (244) 1806
60.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
20.0%
B 2
20.0%
G 1
10.0%
F 1
10.0%
D 1
10.0%
R 1
10.0%
P 1
10.0%
K 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2996
89.4%
Common 345
 
10.3%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 225
 
7.5%
주 138
 
4.6%
산 122
 
4.1%
대 116
 
3.9%
단 108
 
3.6%
협 103
 
3.4%
력 101
 
3.4%
교 98
 
3.3%
원 98
 
3.3%
국 81
 
2.7%
Other values (244) 1806
60.3%
Latin
ValueCountFrequency (%)
A 2
20.0%
B 2
20.0%
G 1
10.0%
F 1
10.0%
D 1
10.0%
R 1
10.0%
P 1
10.0%
K 1
10.0%
Common
ValueCountFrequency (%)
133
38.6%
( 104
30.1%
) 104
30.1%
1 2
 
0.6%
9 1
 
0.3%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2996
89.4%
ASCII 355
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 225
 
7.5%
주 138
 
4.6%
산 122
 
4.1%
대 116
 
3.9%
단 108
 
3.6%
협 103
 
3.4%
력 101
 
3.4%
교 98
 
3.3%
원 98
 
3.3%
국 81
 
2.7%
Other values (244) 1806
60.3%
ASCII
ValueCountFrequency (%)
133
37.5%
( 104
29.3%
) 104
29.3%
A 2
 
0.6%
B 2
 
0.6%
1 2
 
0.6%
G 1
 
0.3%
9 1
 
0.3%
F 1
 
0.3%
D 1
 
0.3%
Other values (4) 4
 
1.1%

주관기관
Text

Distinct214
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T08:35:49.236182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.206044
Min length2

Characters and Unicode

Total characters3351
Distinct characters268
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

Unique161 ?
Unique (%)44.2%

Sample

1st row경북대학교 산학협력단
2nd row대상(주)
3rd row한국식품연구원
4th row오즈레이주식회사
5th row주식회사 대도
ValueCountFrequency (%)
산학협력단 81
 
16.3%
주식회사 26
 
5.2%
충남대학교 17
 
3.4%
국립농업과학원 13
 
2.6%
전남대학교 9
 
1.8%
한국식품연구원 8
 
1.6%
농업기술실용화재단 8
 
1.6%
서울대학교 8
 
1.6%
강원대학교 7
 
1.4%
전북대학교산학협력단 7
 
1.4%
Other values (218) 313
63.0%
2023-12-13T08:35:49.726195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 225
 
6.7%
주 138
 
4.1%
133
 
4.0%
산 122
 
3.6%
대 116
 
3.5%
단 108
 
3.2%
( 104
 
3.1%
) 104
 
3.1%
협 103
 
3.1%
력 101
 
3.0%
Other values (258) 2097
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2996
89.4%
Space Separator 133
 
4.0%
Open Punctuation 104
 
3.1%
Close Punctuation 104
 
3.1%
Uppercase Letter 10
 
0.3%
Decimal Number 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 225
 
7.5%
주 138
 
4.6%
산 122
 
4.1%
대 116
 
3.9%
단 108
 
3.6%
협 103
 
3.4%
력 101
 
3.4%
교 98
 
3.3%
원 98
 
3.3%
국 81
 
2.7%
Other values (244) 1806
60.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
20.0%
B 2
20.0%
G 1
10.0%
F 1
10.0%
D 1
10.0%
R 1
10.0%
P 1
10.0%
K 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2996
89.4%
Common 345
 
10.3%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 225
 
7.5%
주 138
 
4.6%
산 122
 
4.1%
대 116
 
3.9%
단 108
 
3.6%
협 103
 
3.4%
력 101
 
3.4%
교 98
 
3.3%
원 98
 
3.3%
국 81
 
2.7%
Other values (244) 1806
60.3%
Latin
ValueCountFrequency (%)
A 2
20.0%
B 2
20.0%
G 1
10.0%
F 1
10.0%
D 1
10.0%
R 1
10.0%
P 1
10.0%
K 1
10.0%
Common
ValueCountFrequency (%)
133
38.6%
( 104
30.1%
) 104
30.1%
1 2
 
0.6%
9 1
 
0.3%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2996
89.4%
ASCII 355
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 225
 
7.5%
주 138
 
4.6%
산 122
 
4.1%
대 116
 
3.9%
단 108
 
3.6%
협 103
 
3.4%
력 101
 
3.4%
교 98
 
3.3%
원 98
 
3.3%
국 81
 
2.7%
Other values (244) 1806
60.3%
ASCII
ValueCountFrequency (%)
133
37.5%
( 104
29.3%
) 104
29.3%
A 2
 
0.6%
B 2
 
0.6%
1 2
 
0.6%
G 1
 
0.3%
9 1
 
0.3%
F 1
 
0.3%
D 1
 
0.3%
Other values (4) 4
 
1.1%

총연구기관 시작일
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2021-04-01
152 
2021-04-07
90 
2020-04-29
60 
2019-04-16
23 
2018-04-26
 
11
Other values (9)
28 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique4 ?
Unique (%)1.1%

Sample

1st row2021-04-01
2nd row2021-04-01
3rd row2021-04-01
4th row2021-04-01
5th row2021-04-01

Common Values

ValueCountFrequency (%)
2021-04-01 152
41.8%
2021-04-07 90
24.7%
2020-04-29 60
 
16.5%
2019-04-16 23
 
6.3%
2018-04-26 11
 
3.0%
2020-01-29 6
 
1.6%
2020-07-23 6
 
1.6%
2019-08-30 5
 
1.4%
2020-05-29 4
 
1.1%
2017-10-18 3
 
0.8%
Other values (4) 4
 
1.1%

Length

2023-12-13T08:35:49.912689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-04-01 152
41.8%
2021-04-07 90
24.7%
2020-04-29 60
 
16.5%
2019-04-16 23
 
6.3%
2018-04-26 11
 
3.0%
2020-01-29 6
 
1.6%
2020-07-23 6
 
1.6%
2019-08-30 5
 
1.4%
2020-05-29 4
 
1.1%
2017-10-18 3
 
0.8%
Other values (4) 4
 
1.1%

총연구기간 종료일
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2022-12-31
111 
2023-12-31
79 
2024-12-31
76 
2021-12-31
56 
2025-12-31
34 
Other values (3)
 
8

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row2025-12-31
2nd row2025-12-31
3rd row2025-12-31
4th row2025-12-31
5th row2025-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 111
30.5%
2023-12-31 79
21.7%
2024-12-31 76
20.9%
2021-12-31 56
15.4%
2025-12-31 34
 
9.3%
2024-01-28 6
 
1.6%
2022-01-27 1
 
0.3%
2023-02-28 1
 
0.3%

Length

2023-12-13T08:35:50.060351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:50.219012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 111
30.5%
2023-12-31 79
21.7%
2024-12-31 76
20.9%
2021-12-31 56
15.4%
2025-12-31 34
 
9.3%
2024-01-28 6
 
1.6%
2022-01-27 1
 
0.3%
2023-02-28 1
 
0.3%

당해년연구기간 시작일
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2021-04-01
158 
2021-01-01
108 
2021-04-07
90 
2021-01-29
 
6
2021-01-28
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row2021-04-01
2nd row2021-04-01
3rd row2021-04-01
4th row2021-04-01
5th row2021-04-01

Common Values

ValueCountFrequency (%)
2021-04-01 158
43.4%
2021-01-01 108
29.7%
2021-04-07 90
24.7%
2021-01-29 6
 
1.6%
2021-01-28 1
 
0.3%
2021-04-16 1
 
0.3%

Length

2023-12-13T08:35:50.389318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:50.520672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-01 158
43.4%
2021-01-01 108
29.7%
2021-04-07 90
24.7%
2021-01-29 6
 
1.6%
2021-01-28 1
 
0.3%
2021-04-16 1
 
0.3%

당해년연구기간 종료일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2021-12-31
350 
2022-01-28
 
6
2022-03-31
 
5
2024-12-31
 
1
2022-04-30
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row2021-12-31
2nd row2021-12-31
3rd row2021-12-31
4th row2021-12-31
5th row2021-12-31

Common Values

ValueCountFrequency (%)
2021-12-31 350
96.2%
2022-01-28 6
 
1.6%
2022-03-31 5
 
1.4%
2024-12-31 1
 
0.3%
2022-04-30 1
 
0.3%
2022-01-27 1
 
0.3%

Length

2023-12-13T08:35:50.679625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:50.822212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-31 350
96.2%
2022-01-28 6
 
1.6%
2022-03-31 5
 
1.4%
2024-12-31 1
 
0.3%
2022-04-30 1
 
0.3%
2022-01-27 1
 
0.3%

총연구비
Real number (ℝ)

Distinct177
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9402202 × 108
Minimum0
Maximum1.614 × 109
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T08:35:50.974627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35040000
Q180000000
median1.4 × 108
Q32.540095 × 108
95-th percentile4.74615 × 108
Maximum1.614 × 109
Range1.614 × 109
Interquartile range (IQR)1.740095 × 108

Descriptive statistics

Standard deviation1.8280625 × 108
Coefficient of variation (CV)0.94219328
Kurtosis18.207473
Mean1.9402202 × 108
Median Absolute Deviation (MAD)71750000
Skewness3.379956
Sum7.0624017 × 1010
Variance3.3418124 × 1016
MonotonicityNot monotonic
2023-12-13T08:35:51.160462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000000 32
 
8.8%
200000000 18
 
4.9%
90000000 12
 
3.3%
80000000 11
 
3.0%
50000000 11
 
3.0%
70000000 10
 
2.7%
300000000 10
 
2.7%
130000000 8
 
2.2%
60000000 7
 
1.9%
30000000 6
 
1.6%
Other values (167) 239
65.7%
ValueCountFrequency (%)
0 1
 
0.3%
15000000 2
 
0.5%
20000000 2
 
0.5%
25000000 3
0.8%
26700000 2
 
0.5%
26800000 1
 
0.3%
28572000 1
 
0.3%
30000000 6
1.6%
35040000 2
 
0.5%
37500000 1
 
0.3%
ValueCountFrequency (%)
1614000000 1
0.3%
1420400000 1
0.3%
1150000000 1
0.3%
995000000 1
0.3%
957475000 1
0.3%
865000000 1
0.3%
670000000 1
0.3%
603134000 1
0.3%
600000000 2
0.5%
567070000 1
0.3%

Interactions

2023-12-13T08:35:44.558153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:35:44.352115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:35:44.666348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:35:44.455995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:35:51.270454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호사업명총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
번호1.0000.9590.7640.7460.6510.2880.149
사업명0.9591.0000.9580.9830.9600.8610.703
총연구기관 시작일0.7640.9581.0000.9460.9660.8440.796
총연구기간 종료일0.7460.9830.9461.0000.9120.8120.675
당해년연구기간 시작일0.6510.9600.9660.9121.0000.9350.312
당해년연구기간 종료일0.2880.8610.8440.8120.9351.0000.217
총연구비0.1490.7030.7960.6750.3120.2171.000
2023-12-13T08:35:51.413884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업명당해년연구기간 종료일총연구기관 시작일당해년연구기간 시작일총연구기간 종료일
사업명1.0000.5910.7240.8090.879
당해년연구기간 종료일0.5911.0000.6160.6300.626
총연구기관 시작일0.7240.6161.0000.8840.802
당해년연구기간 시작일0.8090.6300.8841.0000.798
총연구기간 종료일0.8790.6260.8020.7981.000
2023-12-13T08:35:51.548075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호총연구비사업명총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일
번호1.000-0.0920.7470.4370.4790.4130.155
총연구비-0.0921.0000.3260.4770.4040.1690.115
사업명0.7470.3261.0000.7240.8790.8090.591
총연구기관 시작일0.4370.4770.7241.0000.8020.8840.616
총연구기간 종료일0.4790.4040.8790.8021.0000.7980.626
당해년연구기간 시작일0.4130.1690.8090.8840.7981.0000.630
당해년연구기간 종료일0.1550.1150.5910.6160.6260.6301.000

Missing values

2023-12-13T08:35:44.827370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:35:45.003760image/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

번호분류사업명총괄과제번호세부과제번호과제명연구수행기관주관기관총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
01농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD040수삼 및 홍삼의 분광 영상 획득 및 AI 학습용 데이터 구축경북대학교 산학협력단경북대학교 산학협력단2021-04-012025-12-312021-04-012021-12-31100000000
12농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD070고춧가루 품위 적용을 위한 브랜딩 기준 도출 및 맛김치 이물 제어 시스템의 현장 실증대상(주)대상(주)2021-04-012025-12-312021-04-012021-12-3172000000
23농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051SB010식품 품질인식 등급 판정이 가능한 품질 결정 기술 및 맛김치 이물 검출 자동화/로봇 시스템 개발한국식품연구원한국식품연구원2021-04-012025-12-312021-04-012021-12-311150000000
34농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD030딥러닝을 이용한 영상 및 초분광 이미징 검사시스템 개발오즈레이주식회사오즈레이주식회사2021-04-012025-12-312021-04-012021-12-31400000000
45농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD0b0수삼 품질 판정용 자동화 라인 및 로봇 시스템 개발주식회사 대도주식회사 대도2021-04-012025-12-312021-04-012021-12-31133334000
56농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD090식품 법적 표시 가이드 및 평가 플랫폼 개발주식회사 제닛시컨설팅주식회사 제닛시컨설팅2021-04-012025-12-312021-04-012021-12-31200000000
67농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD060맛김치 이물선별 시스템 실증 및 성과확산한국식품연구원 부설 세계김치연구소한국식품연구원 부설 세계김치연구소2021-04-012025-12-312021-04-012021-12-3150000000
78농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD020고채널다중영상 인식용 딥러닝 AI 모델 및 병렬로봇제어기술 개발한국생산기술연구원한국생산기술연구원2021-04-012025-12-312021-04-012021-12-31300000000
89농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321049-5321049051HD050고춧가루의 chemometrics 기반 품질 인식을 위한 매운맛 데이터 구축중앙대학교 산학협력단중앙대학교 산학협력단2021-04-012025-12-312021-04-012021-12-31100000000
910농림식품 기계ㆍ시스템5G기반 식품안전생산기술개발321051-5321051051SB0105G 기반 김치 원료 배합공정 제어관리 기술 개발한국식품연구원 부설 세계김치연구소한국식품연구원 부설 세계김치연구소2021-04-012025-12-312021-04-012021-12-31249000000
번호분류사업명총괄과제번호세부과제번호과제명연구수행기관주관기관총연구기관 시작일총연구기간 종료일당해년연구기간 시작일당해년연구기간 종료일총연구비
354355농림식품 기계ㆍ시스템축산시설환경개선321087-5321087051HD040축산농가 기반 악취처리 통합시스템의 현장적용을 위한 공정설계 연구주식회사 아코펀키코리아주식회사 아코펀키코리아2021-04-012025-12-312021-04-012021-12-3137500000
355356농림식품 기계ㆍ시스템축산시설환경개선321087-5321087051HD030내방사성 미생물 기반 축산악취 저감용 바이오필터 개발한국원자력연구원한국원자력연구원2021-04-012025-12-312021-04-012021-12-31140000000
356357농림식품 기계ㆍ시스템축산시설환경개선321087-5321087051HD020축산악취 저감을 위한 현장 맞춤형 전자선 발생장치 개발한국원자력연구원한국원자력연구원2021-04-012025-12-312021-04-012021-12-31335000000
357358농림식품 기계ㆍ시스템축산시설환경개선321087-5321087051SB010전자선 분해 기술 기반 축산악취 처리 통합 시스템 개발 및 실증연구한국원자력연구원한국원자력연구원2021-04-012025-12-312021-04-012021-12-31230000000
358359농림식품 기계ㆍ시스템축산시설환경개선321090-2321090021SB010농가 휴대용 부숙도 측정 장치 상용 제품 개발(주)케이엔알(주)케이엔알2021-04-012022-12-312021-04-012021-12-31200000000
359360농림식품 기계ㆍ시스템축산시설환경개선321090-2321090021HD020센서 기반 기체 농도 계측 시스템 소형 경량화 연구국립농업과학원국립농업과학원2021-04-012022-12-312021-04-012021-12-31100000000
360361농림식품 기계ㆍ시스템축산시설환경개선321090-2321090021HD030가축분뇨 유래 부숙지표 탐색 및 측정장비 현장 적용성 평가국립축산과학원국립축산과학원2021-04-012022-12-312021-04-012021-12-3150000000
361362농림식품 기계ㆍ시스템축산시설환경개선321093-2321093021HD030가축분뇨 고체연료화 시설 표준화 설계 개발 및 제도 개선 방안 연구한경대학교 산학협력단한경대학교 산학협력단2021-04-012022-12-312021-04-012021-12-3170000000
362363농림식품 기계ㆍ시스템축산시설환경개선321093-2321093021SB010가축분뇨 고체연료화를 위한 습공기 제어형 스마트 바이오드라잉 시스템 실증한국산업기술시험원한국산업기술시험원2021-04-012022-12-312021-04-012021-12-31200000000
363364농림식품 기계ㆍ시스템축산시설환경개선321093-2321093021HD020가축분뇨 Bio-drying 공정 최적화 및 실증BK환경종합건설(주)BK환경종합건설(주)2021-04-012022-12-312021-04-012021-12-31240000000