Overview

Dataset statistics

Number of variables7
Number of observations578
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.9 KiB
Average record size in memory58.2 B

Variable types

Categorical2
Text1
DateTime2
Numeric2

Dataset

Description한국농수산식품유통공사 농식품유통교육원(https://edu.at.or.kr/cmm/main/mainPage.do)에서 실시하는 농식품 관련 교육의 정보(교육과정명, 교육일정, 교육인원 등)
URLhttps://www.data.go.kr/data/15002730/fileData.do

Alerts

기당인원 is highly overall correlated with 진행현황High correlation
진행현황 is highly overall correlated with 기당인원High correlation
진행현황 is highly imbalanced (80.0%)Imbalance
기당인원 has 18 (3.1%) zerosZeros

Reproduction

Analysis started2023-12-12 02:42:44.853882
Analysis finished2023-12-12 02:42:45.764870
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육과정대분류코드
Categorical

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
식품교육
290 
유통교육
266 
수산교육
 
17
수출교육
 
4
푸드플랜
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row식품교육
2nd row유통교육
3rd row유통교육
4th row유통교육
5th row유통교육

Common Values

ValueCountFrequency (%)
식품교육 290
50.2%
유통교육 266
46.0%
수산교육 17
 
2.9%
수출교육 4
 
0.7%
푸드플랜 1
 
0.2%

Length

2023-12-12T11:42:45.836469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:42:45.941395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품교육 290
50.2%
유통교육 266
46.0%
수산교육 17
 
2.9%
수출교육 4
 
0.7%
푸드플랜 1
 
0.2%

교육과정명
Text

Distinct192
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T11:42:46.299032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length15.108997
Min length6

Characters and Unicode

Total characters8733
Distinct characters279
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)11.1%

Sample

1st row식품이물관리 실무
2nd row농식품 대량수요처 경영인전문가과정
3rd row농식품 미래유통 혁신리더 과정
4th row농산물 마케팅 경영인·전문가 과정
5th row농산물 CEO MBA 과정
ValueCountFrequency (%)
농산물 85
 
4.5%
농식품 83
 
4.4%
및 59
 
3.1%
실무 57
 
3.0%
식품기업 44
 
2.3%
경매사 43
 
2.3%
식품이물관리 31
 
1.7%
온라인 25
 
1.3%
표시기준 24
 
1.3%
산지조직 22
 
1.2%
Other values (307) 1403
74.8%
2023-12-12T11:42:46.847014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1318
 
15.1%
품 393
 
4.5%
식 358
 
4.1%
농 208
 
2.4%
기 201
 
2.3%
) 194
 
2.2%
( 194
 
2.2%
산 184
 
2.1%
업 155
 
1.8%
물 146
 
1.7%
Other values (269) 5382
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6708
76.8%
Space Separator 1318
 
15.1%
Close Punctuation 194
 
2.2%
Open Punctuation 194
 
2.2%
Uppercase Letter 167
 
1.9%
Lowercase Letter 80
 
0.9%
Other Punctuation 48
 
0.5%
Decimal Number 21
 
0.2%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 393
 
5.9%
식 358
 
5.3%
농 208
 
3.1%
기 201
 
3.0%
산 184
 
2.7%
업 155
 
2.3%
물 146
 
2.2%
이 143
 
2.1%
무 140
 
2.1%
실 132
 
2.0%
Other values (232) 4648
69.3%
Uppercase Letter
ValueCountFrequency (%)
C 43
25.7%
A 32
19.2%
P 21
12.6%
H 18
10.8%
S 17
 
10.2%
F 7
 
4.2%
E 5
 
3.0%
O 5
 
3.0%
M 5
 
3.0%
B 5
 
3.0%
Other values (3) 9
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
d 15
18.8%
o 14
17.5%
i 10
12.5%
u 8
10.0%
t 8
10.0%
h 5
 
6.2%
c 5
 
6.2%
e 5
 
6.2%
s 2
 
2.5%
k 2
 
2.5%
Other values (3) 6
 
7.5%
Other Punctuation
ValueCountFrequency (%)
· 40
83.3%
, 4
 
8.3%
. 2
 
4.2%
/ 2
 
4.2%
Decimal Number
ValueCountFrequency (%)
5 12
57.1%
4 6
28.6%
6 3
 
14.3%
Space Separator
ValueCountFrequency (%)
1318
100.0%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6708
76.8%
Common 1778
 
20.4%
Latin 247
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 393
 
5.9%
식 358
 
5.3%
농 208
 
3.1%
기 201
 
3.0%
산 184
 
2.7%
업 155
 
2.3%
물 146
 
2.2%
이 143
 
2.1%
무 140
 
2.1%
실 132
 
2.0%
Other values (232) 4648
69.3%
Latin
ValueCountFrequency (%)
C 43
17.4%
A 32
13.0%
P 21
 
8.5%
H 18
 
7.3%
S 17
 
6.9%
d 15
 
6.1%
o 14
 
5.7%
i 10
 
4.0%
u 8
 
3.2%
t 8
 
3.2%
Other values (16) 61
24.7%
Common
ValueCountFrequency (%)
1318
74.1%
) 194
 
10.9%
( 194
 
10.9%
· 40
 
2.2%
5 12
 
0.7%
4 6
 
0.3%
, 4
 
0.2%
- 3
 
0.2%
6 3
 
0.2%
. 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6700
76.7%
ASCII 1985
 
22.7%
None 40
 
0.5%
Compat Jamo 8
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1318
66.4%
) 194
 
9.8%
( 194
 
9.8%
C 43
 
2.2%
A 32
 
1.6%
P 21
 
1.1%
H 18
 
0.9%
S 17
 
0.9%
d 15
 
0.8%
o 14
 
0.7%
Other values (26) 119
 
6.0%
Hangul
ValueCountFrequency (%)
품 393
 
5.9%
식 358
 
5.3%
농 208
 
3.1%
기 201
 
3.0%
산 184
 
2.7%
업 155
 
2.3%
물 146
 
2.2%
이 143
 
2.1%
무 140
 
2.1%
실 132
 
2.0%
Other values (231) 4640
69.3%
None
ValueCountFrequency (%)
· 40
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
100.0%

교육시작일자
Date

Distinct430
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2017-02-16 00:00:00
Maximum2021-12-30 00:00:00
2023-12-12T11:42:47.258411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:42:47.395346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

교육종료일자
Date

Distinct403
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2017-02-16 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T11:42:47.541176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:42:47.719727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

기수
Real number (ℝ)

Distinct21
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9031142
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-12T11:42:47.857468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile9
Maximum35
Range34
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.1494136
Coefficient of variation (CV)1.4292974
Kurtosis32.186285
Mean2.9031142
Median Absolute Deviation (MAD)1
Skewness5.1787241
Sum1678
Variance17.217633
MonotonicityNot monotonic
2023-12-12T11:42:47.968966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 247
42.7%
2 167
28.9%
3 51
 
8.8%
4 27
 
4.7%
5 19
 
3.3%
8 13
 
2.2%
6 13
 
2.2%
7 11
 
1.9%
9 11
 
1.9%
10 7
 
1.2%
Other values (11) 12
 
2.1%
ValueCountFrequency (%)
1 247
42.7%
2 167
28.9%
3 51
 
8.8%
4 27
 
4.7%
5 19
 
3.3%
6 13
 
2.2%
7 11
 
1.9%
8 13
 
2.2%
9 11
 
1.9%
10 7
 
1.2%
ValueCountFrequency (%)
35 1
0.2%
34 1
0.2%
33 1
0.2%
32 1
0.2%
31 1
0.2%
30 1
0.2%
29 1
0.2%
28 1
0.2%
27 1
0.2%
12 1
0.2%

진행현황
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
교육완료
560 
교육중
 
18

Length

Max length4
Median length4
Mean length3.9688581
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육완료 560
96.9%
교육중 18
 
3.1%

Length

2023-12-12T11:42:48.121316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:42:48.228976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육완료 560
96.9%
교육중 18
 
3.1%

기당인원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.356401
Minimum0
Maximum300
Zeros18
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-12T11:42:48.316852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q125
median30
Q335
95-th percentile66
Maximum300
Range300
Interquartile range (IQR)10

Descriptive statistics

Standard deviation40.173078
Coefficient of variation (CV)1.1362321
Kurtosis27.60196
Mean35.356401
Median Absolute Deviation (MAD)5
Skewness5.0037834
Sum20436
Variance1613.8762
MonotonicityNot monotonic
2023-12-12T11:42:48.419294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
25 174
30.1%
30 144
24.9%
35 85
14.7%
40 40
 
6.9%
20 33
 
5.7%
3 21
 
3.6%
0 18
 
3.1%
50 12
 
2.1%
100 11
 
1.9%
4 10
 
1.7%
Other values (6) 30
 
5.2%
ValueCountFrequency (%)
0 18
 
3.1%
3 21
 
3.6%
4 10
 
1.7%
15 2
 
0.3%
20 33
 
5.7%
25 174
30.1%
30 144
24.9%
35 85
14.7%
40 40
 
6.9%
42 9
 
1.6%
ValueCountFrequency (%)
300 8
 
1.4%
200 8
 
1.4%
130 2
 
0.3%
100 11
 
1.9%
60 1
 
0.2%
50 12
 
2.1%
42 9
 
1.6%
40 40
 
6.9%
35 85
14.7%
30 144
24.9%

Interactions

2023-12-12T11:42:45.382383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:42:45.124030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:42:45.482832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:42:45.252908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:42:48.512269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육과정대분류코드기수진행현황기당인원
교육과정대분류코드1.0000.0000.2880.501
기수0.0001.0000.2600.309
진행현황0.2880.2601.0000.532
기당인원0.5010.3090.5321.000
2023-12-12T11:42:48.610004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육과정대분류코드진행현황
교육과정대분류코드1.0000.351
진행현황0.3511.000
2023-12-12T11:42:48.702181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기수기당인원교육과정대분류코드진행현황
기수1.0000.1760.0000.277
기당인원0.1761.0000.3620.570
교육과정대분류코드0.0000.3621.0000.351
진행현황0.2770.5700.3511.000

Missing values

2023-12-12T11:42:45.603526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:42:45.718594image/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

교육과정대분류코드교육과정명교육시작일자교육종료일자기수진행현황기당인원
0식품교육식품이물관리 실무2017-02-162017-02-161교육완료35
1유통교육농식품 대량수요처 경영인전문가과정2017-02-212017-07-062교육완료35
2유통교육농식품 미래유통 혁신리더 과정2017-02-212017-07-063교육완료35
3유통교육농산물 마케팅 경영인·전문가 과정2017-02-212017-07-0627교육완료35
4유통교육농산물 CEO MBA 과정2017-02-212017-12-078교육완료35
5식품교육식품법규와 표시기준 핵심2017-02-212017-02-211교육완료40
6식품교육식품클레임 대응기법2017-02-232017-02-231교육완료40
7유통교육농산물 경매사 기본 역량 강화2017-02-272017-02-281교육완료40
8식품교육식품품질관리(사이버)2017-03-012017-03-311교육완료0
9식품교육식품이물관리 실무(사이버)2017-03-012017-03-311교육완료0
교육과정대분류코드교육과정명교육시작일자교육종료일자기수진행현황기당인원
568식품교육식품생산현장 이물관리 실무2021-11-032021-11-033교육완료30
569수산교육수산물 도매시장 신규임원, 개설자 역량강화(법정)2021-11-082021-11-092교육완료25
570식품교육식품클레임 대응기법2021-11-102021-11-104교육완료40
571식품교육식품산업의 스마트 생산시스템 구축 준비2021-11-112021-11-122교육완료25
572유통교육도매시장 신규임원 역량강화(법정)2021-11-112021-11-122교육완료25
573유통교육친환경 농산물 유통의 이해2021-11-162021-11-172교육완료25
574식품교육식품기업 생산원가 절감2021-11-162021-11-162교육완료25
575식품교육식품산업의 Risk 관리2021-11-182021-11-192교육완료25
576유통교육농식품 온라인 플랫폼 마케팅 실습(심화)2021-11-222021-11-241교육완료25
577식품교육신혁명 푸드테크(Food Tech)2021-12-302021-12-312교육완료25