Overview

Dataset statistics

Number of variables9
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory79.6 B

Variable types

Categorical3
Numeric5
Text1

Dataset

Description경기도농수산진흥원 귀농귀촌대학현황
Author경기도농수산진흥원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=0TMC0D594A8J5UTEF03S32132706&infSeq=1

Alerts

사업년도 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
교육인원 is highly overall correlated with 수료인원High correlation
수료인원 is highly overall correlated with 교육인원High correlation
자부담비율 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 사업년도 and 2 other fieldsHigh correlation
교육기간 is highly overall correlated with 사업년도 and 2 other fieldsHigh correlation

Reproduction

Analysis started2024-03-12 23:24:45.408985
Analysis finished2024-03-12 23:24:47.611643
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size540.0 B
12기
4 
11기
4 
8기
4 
7기
4 
6기
4 
Other values (10)
31 

Length

Max length3
Median length2
Mean length2.372549
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15기
2nd row15기
3rd row14기
4th row14기
5th row14기

Common Values

ValueCountFrequency (%)
12기 4
 
7.8%
11기 4
 
7.8%
8기 4
 
7.8%
7기 4
 
7.8%
6기 4
 
7.8%
5기 4
 
7.8%
4기 4
 
7.8%
14기 3
 
5.9%
13기 3
 
5.9%
10기 3
 
5.9%
Other values (5) 14
27.5%

Length

2024-03-13T08:24:47.665377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12기 4
 
7.8%
11기 4
 
7.8%
8기 4
 
7.8%
7기 4
 
7.8%
6기 4
 
7.8%
5기 4
 
7.8%
4기 4
 
7.8%
14기 3
 
5.9%
13기 3
 
5.9%
10기 3
 
5.9%
Other values (5) 14
27.5%

사업년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.8039
Minimum2009
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-13T08:24:47.745209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2009.5
Q12012.5
median2016
Q32019
95-th percentile2022
Maximum2023
Range14
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation4.1086232
Coefficient of variation (CV)0.0020382058
Kurtosis-1.1102474
Mean2015.8039
Median Absolute Deviation (MAD)3
Skewness0.043482847
Sum102806
Variance16.880784
MonotonicityDecreasing
2024-03-13T08:24:47.826566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2020 4
 
7.8%
2019 4
 
7.8%
2016 4
 
7.8%
2015 4
 
7.8%
2014 4
 
7.8%
2013 4
 
7.8%
2012 4
 
7.8%
2022 3
 
5.9%
2021 3
 
5.9%
2018 3
 
5.9%
Other values (5) 14
27.5%
ValueCountFrequency (%)
2009 3
5.9%
2010 3
5.9%
2011 3
5.9%
2012 4
7.8%
2013 4
7.8%
2014 4
7.8%
2015 4
7.8%
2016 4
7.8%
2017 3
5.9%
2018 3
5.9%
ValueCountFrequency (%)
2023 2
3.9%
2022 3
5.9%
2021 3
5.9%
2020 4
7.8%
2019 4
7.8%
2018 3
5.9%
2017 3
5.9%
2016 4
7.8%
2015 4
7.8%
2014 4
7.8%

대학교명
Categorical

Distinct11
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size540.0 B
여주농업경영전문학교
13 
농협대학교
12 
신한대학교
10 
한국농수산대학
5 
농협대학
3 
Other values (6)
8 

Length

Max length16
Median length5
Mean length6.6862745
Min length4

Unique

Unique4 ?
Unique (%)7.8%

Sample

1st row농협대학교
2nd row신한대학교
3rd row농협대학교
4th row신한대학교
5th row여주농전(여주농업경영전문학교)

Common Values

ValueCountFrequency (%)
여주농업경영전문학교 13
25.5%
농협대학교 12
23.5%
신한대학교 10
19.6%
한국농수산대학 5
 
9.8%
농협대학 3
 
5.9%
동원대학교 2
 
3.9%
한경대학교 2
 
3.9%
여주농전(여주농업경영전문학교) 1
 
2.0%
수원과학대 1
 
2.0%
수원과학대학교 1
 
2.0%

Length

2024-03-13T08:24:47.924931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여주농업경영전문학교 13
25.5%
농협대학교 12
23.5%
신한대학교 10
19.6%
한국농수산대학 5
 
9.8%
농협대학 3
 
5.9%
동원대학교 2
 
3.9%
한경대학교 2
 
3.9%
여주농전(여주농업경영전문학교 1
 
2.0%
수원과학대 1
 
2.0%
수원과학대학교 1
 
2.0%

교육과정명
Text

Distinct28
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-13T08:24:48.056513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length7.4117647
Min length2

Characters and Unicode

Total characters378
Distinct characters38
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)35.3%

Sample

1st row시설채소, 밭작물, 특용작물
2nd row약용약초 창업
3rd row밭작물, 시설채소, 특용작물
4th row약용식물
5th row원예
ValueCountFrequency (%)
원예 17
16.7%
밭작물 12
11.8%
채소 10
 
9.8%
약용작물 10
 
9.8%
밭 8
 
7.8%
특용 5
 
4.9%
화훼 5
 
4.9%
시설채소 4
 
3.9%
약용약초 3
 
2.9%
창업 3
 
2.9%
Other values (15) 25
24.5%
2024-03-13T08:24:48.337044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
13.5%
, 50
13.2%
물 30
 
7.9%
작 29
 
7.7%
용 27
 
7.1%
원 20
 
5.3%
예 20
 
5.3%
약 20
 
5.3%
밭 20
 
5.3%
소 17
 
4.5%
Other values (28) 94
24.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
72.8%
Space Separator 51
 
13.5%
Other Punctuation 50
 
13.2%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 30
10.9%
작 29
10.5%
용 27
9.8%
원 20
 
7.3%
예 20
 
7.3%
약 20
 
7.3%
밭 20
 
7.3%
소 17
 
6.2%
채 16
 
5.8%
특 10
 
3.6%
Other values (24) 66
24.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
72.8%
Common 101
 
26.7%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 30
10.9%
작 29
10.5%
용 27
9.8%
원 20
 
7.3%
예 20
 
7.3%
약 20
 
7.3%
밭 20
 
7.3%
소 17
 
6.2%
채 16
 
5.8%
특 10
 
3.6%
Other values (24) 66
24.0%
Common
ValueCountFrequency (%)
51
50.5%
, 50
49.5%
Latin
ValueCountFrequency (%)
I 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
72.8%
ASCII 103
 
27.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
49.5%
, 50
48.5%
I 1
 
1.0%
T 1
 
1.0%
Hangul
ValueCountFrequency (%)
물 30
10.9%
작 29
10.5%
용 27
9.8%
원 20
 
7.3%
예 20
 
7.3%
약 20
 
7.3%
밭 20
 
7.3%
소 17
 
6.2%
채 16
 
5.8%
특 10
 
3.6%
Other values (24) 66
24.0%

교육기간
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size540.0 B
4월∼10월
14 
4월∼11월
11 
5월∼12월
10 
4월~11월
5 
5월∼11월
5 
Other values (2)
6 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4월~11월
2nd row4월~11월
3rd row4월~11월
4th row4월~11월
5th row4월~11월

Common Values

ValueCountFrequency (%)
4월∼10월 14
27.5%
4월∼11월 11
21.6%
5월∼12월 10
19.6%
4월~11월 5
 
9.8%
5월∼11월 5
 
9.8%
4월~10월 3
 
5.9%
3월~10월 3
 
5.9%

Length

2024-03-13T08:24:48.433668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:24:48.516131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4월∼10월 14
27.5%
4월∼11월 11
21.6%
5월∼12월 10
19.6%
4월~11월 5
 
9.8%
5월∼11월 5
 
9.8%
4월~10월 3
 
5.9%
3월~10월 3
 
5.9%

교육시간
Real number (ℝ)

Distinct22
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.70588
Minimum112
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-13T08:24:48.602205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum112
5-th percentile112
Q1124
median140
Q3150
95-th percentile165.5
Maximum184
Range72
Interquartile range (IQR)26

Descriptive statistics

Standard deviation17.021509
Coefficient of variation (CV)0.12183817
Kurtosis-0.32010986
Mean139.70588
Median Absolute Deviation (MAD)14
Skewness0.16624024
Sum7125
Variance289.73176
MonotonicityNot monotonic
2024-03-13T08:24:48.690048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
150 6
11.8%
112 6
11.8%
124 6
11.8%
136 6
11.8%
155 3
 
5.9%
140 3
 
5.9%
122 2
 
3.9%
143 2
 
3.9%
130 2
 
3.9%
144 2
 
3.9%
Other values (12) 13
25.5%
ValueCountFrequency (%)
112 6
11.8%
122 2
 
3.9%
124 6
11.8%
130 2
 
3.9%
135 1
 
2.0%
136 6
11.8%
137 1
 
2.0%
138 1
 
2.0%
140 3
5.9%
141 1
 
2.0%
ValueCountFrequency (%)
184 1
 
2.0%
170 1
 
2.0%
167 1
 
2.0%
164 1
 
2.0%
161 2
 
3.9%
160 1
 
2.0%
158 1
 
2.0%
155 3
5.9%
154 1
 
2.0%
150 6
11.8%

교육인원
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.784314
Minimum22
Maximum140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-13T08:24:48.786098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile25
Q130
median50
Q387.5
95-th percentile120
Maximum140
Range118
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation35.050429
Coefficient of variation (CV)0.54951487
Kurtosis-0.94089048
Mean63.784314
Median Absolute Deviation (MAD)20
Skewness0.6350904
Sum3253
Variance1228.5325
MonotonicityNot monotonic
2024-03-13T08:24:48.905611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
30 10
19.6%
50 7
13.7%
120 6
11.8%
105 4
 
7.8%
25 3
 
5.9%
85 2
 
3.9%
75 2
 
3.9%
60 2
 
3.9%
81 1
 
2.0%
90 1
 
2.0%
Other values (13) 13
25.5%
ValueCountFrequency (%)
22 1
 
2.0%
25 3
 
5.9%
28 1
 
2.0%
30 10
19.6%
32 1
 
2.0%
35 1
 
2.0%
38 1
 
2.0%
40 1
 
2.0%
50 7
13.7%
55 1
 
2.0%
ValueCountFrequency (%)
140 1
 
2.0%
128 1
 
2.0%
120 6
11.8%
105 4
7.8%
90 1
 
2.0%
85 2
 
3.9%
81 1
 
2.0%
75 2
 
3.9%
71 1
 
2.0%
70 1
 
2.0%

수료인원
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.45098
Minimum22
Maximum136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-13T08:24:49.003576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile24.5
Q130
median50
Q387.5
95-th percentile120
Maximum136
Range114
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation34.611162
Coefficient of variation (CV)0.55421327
Kurtosis-0.99210054
Mean62.45098
Median Absolute Deviation (MAD)22
Skewness0.60987613
Sum3185
Variance1197.9325
MonotonicityNot monotonic
2024-03-13T08:24:49.096203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
30 5
 
9.8%
50 3
 
5.9%
28 3
 
5.9%
29 3
 
5.9%
49 3
 
5.9%
103 2
 
3.9%
25 2
 
3.9%
118 2
 
3.9%
120 2
 
3.9%
23 1
 
2.0%
Other values (25) 25
49.0%
ValueCountFrequency (%)
22 1
 
2.0%
23 1
 
2.0%
24 1
 
2.0%
25 2
 
3.9%
28 3
5.9%
29 3
5.9%
30 5
9.8%
32 1
 
2.0%
37 1
 
2.0%
38 1
 
2.0%
ValueCountFrequency (%)
136 1
2.0%
121 1
2.0%
120 2
3.9%
119 1
2.0%
118 2
3.9%
116 1
2.0%
105 1
2.0%
104 1
2.0%
103 2
3.9%
90 1
2.0%

자부담비율
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.490196
Minimum25
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-13T08:24:49.368535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile25
Q134
median43
Q350
95-th percentile64
Maximum64
Range39
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.772977
Coefficient of variation (CV)0.30957331
Kurtosis-1.2979338
Mean44.490196
Median Absolute Deviation (MAD)9
Skewness0.14138152
Sum2269
Variance189.6949
MonotonicityNot monotonic
2024-03-13T08:24:49.453530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
50 13
25.5%
64 12
23.5%
36 6
11.8%
25 6
11.8%
34 4
 
7.8%
43 4
 
7.8%
31 3
 
5.9%
28 3
 
5.9%
ValueCountFrequency (%)
25 6
11.8%
28 3
 
5.9%
31 3
 
5.9%
34 4
 
7.8%
36 6
11.8%
43 4
 
7.8%
50 13
25.5%
64 12
23.5%
ValueCountFrequency (%)
64 12
23.5%
50 13
25.5%
43 4
 
7.8%
36 6
11.8%
34 4
 
7.8%
31 3
 
5.9%
28 3
 
5.9%
25 6
11.8%

Interactions

2024-03-13T08:24:47.112651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:45.704565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.071913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.404449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.758303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:47.179914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:45.769782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.137747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.467698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.826948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:47.249001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:45.835636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.202583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.534782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.893583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:47.314272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:45.908680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.268578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.598817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.959941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:47.380936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:45.993178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.333614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:46.674011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:24:47.036804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:24:49.523480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분사업년도대학교명교육과정명교육기간교육시간교육인원수료인원자부담비율
구분1.0001.0000.0000.0000.9460.5440.5450.6100.962
사업년도1.0001.0000.0000.0000.9170.7610.4760.5830.852
대학교명0.0000.0001.0000.9540.4810.4240.6830.5950.463
교육과정명0.0000.0000.9541.0000.6530.8870.9240.9020.629
교육기간0.9460.9170.4810.6531.0000.6820.5380.5590.745
교육시간0.5440.7610.4240.8870.6821.0000.7340.6920.666
교육인원0.5450.4760.6830.9240.5380.7341.0000.9960.600
수료인원0.6100.5830.5950.9020.5590.6920.9961.0000.573
자부담비율0.9620.8520.4630.6290.7450.6660.6000.5731.000
2024-03-13T08:24:49.608273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육기간대학교명구분
교육기간1.0000.2410.732
대학교명0.2411.0000.000
구분0.7320.0001.000
2024-03-13T08:24:49.676237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업년도교육시간교육인원수료인원자부담비율구분대학교명교육기간
사업년도1.0000.0190.0480.0250.3620.9370.0000.676
교육시간0.0191.0000.4720.4670.4100.2060.1810.414
교육인원0.0480.4721.0000.9920.0270.2400.3570.329
수료인원0.0250.4670.9921.0000.0410.2680.3050.325
자부담비율0.3620.4100.0270.0411.0000.7550.2350.556
구분0.9370.2060.2400.2680.7551.0000.0000.732
대학교명0.0000.1810.3570.3050.2350.0001.0000.241
교육기간0.6760.4140.3290.3250.5560.7320.2411.000

Missing values

2024-03-13T08:24:47.476564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:24:47.573496image/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

구분사업년도대학교명교육과정명교육기간교육시간교육인원수료인원자부담비율
015기2023농협대학교시설채소, 밭작물, 특용작물4월~11월150817850
115기2023신한대학교약용약초 창업4월~11월140616150
214기2022농협대학교밭작물, 시설채소, 특용작물4월~11월16010510450
314기2022신한대학교약용식물4월~11월140717150
414기2022여주농전(여주농업경영전문학교)원예4월~11월122282850
513기2021농협대학교채소,식량작물,특용작물4월∼11월15010510350
613기2021신한대학교약용약초 창업5월∼11월143757236
713기2021여주농업경영전문학교원 예4월∼11월122302950
812기2020농협대학교채소,식량작물,특용작물5월∼12월15010510350
912기2020수원과학대밭작물, 약용작물5월∼11월124605934
구분사업년도대학교명교육과정명교육기간교육시간교육인원수료인원자부담비율
414기2012여주농업경영전문학교원예4월∼10월136303031
423기2011농협대학채소, 화훼, 밭작물4월∼10월155858228
433기2011한국농수산대학약용작물, 밭작물, 원예4월∼10월161858528
443기2011여주농업경영전문학교원예4월∼10월155575728
452기2010한국농수산대학약용작물, 밭작물, 원예4월~10월112505025
462기2010농협대학채소, 화훼, 밭작물4월~10월112504825
472기2010여주농업경영전문학교원예4월~10월112504925
481기2009한국농수산대학밭, 약용3월~10월112505025
491기2009농협대학시설채소, 화훼3월~10월112505025
501기2009여주농업경영전문학교원예, 과수3월~10월112504925