Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells4
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory62.3 B

Variable types

Categorical2
Text4
Numeric1

Dataset

Description국립농산물품질관리원에서 실시하는 GAP 인증담당자 및 시설담당자 교육일정(교육일자, 교육지역, 교육기관,교육 장소, 교육인원)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220614000000002104

Alerts

인원(명) is highly overall correlated with 교육대상High correlation
본·지원 is highly overall correlated with 교육대상High correlation
교육대상 is highly overall correlated with 인원(명) and 1 other fieldsHigh correlation
교육대상 is highly imbalanced (75.0%)Imbalance
일 시 has 2 (8.3%) missing valuesMissing
인원(명) has 2 (8.3%) missing valuesMissing

Reproduction

Analysis started2024-04-13 11:13:34.005750
Analysis finished2024-04-13 11:13:37.945593
Duration3.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

본·지원
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
경남
10 
충남
4 
전남
4 
경북
3 
본원
2 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row본원
2nd row본원
3rd row충남
4th row충남
5th row충남

Common Values

ValueCountFrequency (%)
경남 10
41.7%
충남 4
 
16.7%
전남 4
 
16.7%
경북 3
 
12.5%
본원 2
 
8.3%
전북 1
 
4.2%

Length

2024-04-13T20:13:38.165532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:13:38.504057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경남 10
41.7%
충남 4
 
16.7%
전남 4
 
16.7%
경북 3
 
12.5%
본원 2
 
8.3%
전북 1
 
4.2%

과·사무소별
Text

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-04-13T20:13:39.193042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.375
Min length2

Characters and Unicode

Total characters57
Distinct characters28
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)29.2%

Sample

1st row인증관리팀
2nd row인증관리팀
3rd row천안
4th row천안
5th row천안
ValueCountFrequency (%)
보성 4
16.7%
품질 4
16.7%
천안 3
12.5%
인증관리팀 2
8.3%
고령 2
8.3%
하동 2
8.3%
부여 1
 
4.2%
임실 1
 
4.2%
상주 1
 
4.2%
고성 1
 
4.2%
Other values (3) 3
12.5%
2024-04-13T20:13:40.202883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
성 5
 
8.8%
보 4
 
7.0%
품 4
 
7.0%
질 4
 
7.0%
고 3
 
5.3%
천 3
 
5.3%
안 3
 
5.3%
령 3
 
5.3%
해 2
 
3.5%
하 2
 
3.5%
Other values (18) 24
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56
98.2%
Other Punctuation 1
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 5
 
8.9%
보 4
 
7.1%
품 4
 
7.1%
질 4
 
7.1%
고 3
 
5.4%
천 3
 
5.4%
안 3
 
5.4%
령 3
 
5.4%
해 2
 
3.6%
하 2
 
3.6%
Other values (17) 23
41.1%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56
98.2%
Common 1
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 5
 
8.9%
보 4
 
7.1%
품 4
 
7.1%
질 4
 
7.1%
고 3
 
5.4%
천 3
 
5.4%
안 3
 
5.4%
령 3
 
5.4%
해 2
 
3.6%
하 2
 
3.6%
Other values (17) 23
41.1%
Common
ValueCountFrequency (%)
· 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56
98.2%
None 1
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
성 5
 
8.9%
보 4
 
7.1%
품 4
 
7.1%
질 4
 
7.1%
고 3
 
5.4%
천 3
 
5.4%
안 3
 
5.4%
령 3
 
5.4%
해 2
 
3.6%
하 2
 
3.6%
Other values (17) 23
41.1%
None
ValueCountFrequency (%)
· 1
100.0%

연락처
Text

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-04-13T20:13:40.830989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique7 ?
Unique (%)29.2%

Sample

1st row054-429-4173
2nd row054-429-4173
3rd row041-551-6060
4th row041-551-6060
5th row041-551-6060
ValueCountFrequency (%)
061-850-2632 4
16.7%
055-230-0853 4
16.7%
041-551-6060 3
12.5%
054-429-4173 2
8.3%
054-954-6060 2
8.3%
055-884-6060 2
8.3%
041-830-3407 1
 
4.2%
063-640-8212 1
 
4.2%
054-530-6223 1
 
4.2%
055-670-1912 1
 
4.2%
Other values (3) 3
12.5%
2024-04-13T20:13:41.933497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
21.2%
- 48
16.7%
5 44
15.3%
6 30
10.4%
2 20
 
6.9%
3 20
 
6.9%
4 20
 
6.9%
1 18
 
6.2%
8 15
 
5.2%
9 7
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
25.4%
5 44
18.3%
6 30
12.5%
2 20
 
8.3%
3 20
 
8.3%
4 20
 
8.3%
1 18
 
7.5%
8 15
 
6.2%
9 7
 
2.9%
7 5
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
21.2%
- 48
16.7%
5 44
15.3%
6 30
10.4%
2 20
 
6.9%
3 20
 
6.9%
4 20
 
6.9%
1 18
 
6.2%
8 15
 
5.2%
9 7
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
21.2%
- 48
16.7%
5 44
15.3%
6 30
10.4%
2 20
 
6.9%
3 20
 
6.9%
4 20
 
6.9%
1 18
 
6.2%
8 15
 
5.2%
9 7
 
2.4%

교육대상
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size320.0 B
농업인
23 
시설담당자
 
1

Length

Max length5
Median length3
Mean length3.0833333
Min length3

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row농업인
2nd row시설담당자
3rd row농업인
4th row농업인
5th row농업인

Common Values

ValueCountFrequency (%)
농업인 23
95.8%
시설담당자 1
 
4.2%

Length

2024-04-13T20:13:42.337365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:13:42.656301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농업인 23
95.8%
시설담당자 1
 
4.2%

일 시
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing2
Missing (%)8.3%
Memory size320.0 B
2024-04-13T20:13:43.144653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length24.954545
Min length24

Characters and Unicode

Total characters549
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row2020.07.21. 10:00 ~ 12:00
2nd row2020.07.27. 10:00 ~ 12:00
3rd row2020.08.13. 10:00 ~ 12:00
4th row2020.10.07. 14:00 ~ 16:00
5th row2020.07.08. 10:00 ~12:00
ValueCountFrequency (%)
21
24.1%
10:00 8
 
9.2%
16:00 7
 
8.0%
14:00 7
 
8.0%
12:00 6
 
6.9%
15:00 5
 
5.7%
2020.08.06 4
 
4.6%
18:00 4
 
4.6%
13:00 4
 
4.6%
2020.08.13 3
 
3.4%
Other values (17) 18
20.7%
2024-04-13T20:13:43.897802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172
31.3%
. 66
 
12.0%
65
 
11.8%
1 58
 
10.6%
2 57
 
10.4%
: 44
 
8.0%
~ 22
 
4.0%
8 20
 
3.6%
6 11
 
2.0%
7 10
 
1.8%
Other values (4) 24
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 352
64.1%
Other Punctuation 110
 
20.0%
Space Separator 65
 
11.8%
Math Symbol 22
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 172
48.9%
1 58
 
16.5%
2 57
 
16.2%
8 20
 
5.7%
6 11
 
3.1%
7 10
 
2.8%
3 8
 
2.3%
4 8
 
2.3%
5 5
 
1.4%
9 3
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 66
60.0%
: 44
40.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 549
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 172
31.3%
. 66
 
12.0%
65
 
11.8%
1 58
 
10.6%
2 57
 
10.4%
: 44
 
8.0%
~ 22
 
4.0%
8 20
 
3.6%
6 11
 
2.0%
7 10
 
1.8%
Other values (4) 24
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172
31.3%
. 66
 
12.0%
65
 
11.8%
1 58
 
10.6%
2 57
 
10.4%
: 44
 
8.0%
~ 22
 
4.0%
8 20
 
3.6%
6 11
 
2.0%
7 10
 
1.8%
Other values (4) 24
 
4.4%

장 소
Text

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-04-13T20:13:44.538877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length10.375
Min length2

Characters and Unicode

Total characters249
Distinct characters89
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)62.5%

Sample

1st row미정
2nd row미정
3rd row직산농협 회의실
4th row직산농협 회의실
5th row천안배원예농협 회의실
ValueCountFrequency (%)
회의실 6
 
12.0%
대강당 5
 
10.0%
보성군 3
 
6.0%
농업기술센터 3
 
6.0%
직산농협 2
 
4.0%
경남사회복지센터 2
 
4.0%
미정 2
 
4.0%
미나리 1
 
2.0%
동읍농협 1
 
2.0%
경제사업장 1
 
2.0%
Other values (24) 24
48.0%
2024-04-13T20:13:45.757776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
10.4%
농 16
 
6.4%
협 10
 
4.0%
실 9
 
3.6%
회 8
 
3.2%
센 7
 
2.8%
터 7
 
2.8%
의 7
 
2.8%
대 6
 
2.4%
강 6
 
2.4%
Other values (79) 147
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 221
88.8%
Space Separator 26
 
10.4%
Decimal Number 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 16
 
7.2%
협 10
 
4.5%
실 9
 
4.1%
회 8
 
3.6%
센 7
 
3.2%
터 7
 
3.2%
의 7
 
3.2%
대 6
 
2.7%
강 6
 
2.7%
업 6
 
2.7%
Other values (76) 139
62.9%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 221
88.8%
Common 28
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 16
 
7.2%
협 10
 
4.5%
실 9
 
4.1%
회 8
 
3.6%
센 7
 
3.2%
터 7
 
3.2%
의 7
 
3.2%
대 6
 
2.7%
강 6
 
2.7%
업 6
 
2.7%
Other values (76) 139
62.9%
Common
ValueCountFrequency (%)
26
92.9%
5 1
 
3.6%
2 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 221
88.8%
ASCII 28
 
11.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
92.9%
5 1
 
3.6%
2 1
 
3.6%
Hangul
ValueCountFrequency (%)
농 16
 
7.2%
협 10
 
4.5%
실 9
 
4.1%
회 8
 
3.6%
센 7
 
3.2%
터 7
 
3.2%
의 7
 
3.2%
대 6
 
2.7%
강 6
 
2.7%
업 6
 
2.7%
Other values (76) 139
62.9%

인원(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)77.3%
Missing2
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean48.590909
Minimum3
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-04-13T20:13:46.129100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile14
Q124.25
median35
Q378.25
95-th percentile117.1
Maximum120
Range117
Interquartile range (IQR)54

Descriptive statistics

Standard deviation35.395263
Coefficient of variation (CV)0.72843386
Kurtosis-0.58614576
Mean48.590909
Median Absolute Deviation (MAD)19.5
Skewness0.81228547
Sum1069
Variance1252.8247
MonotonicityNot monotonic
2024-04-13T20:13:46.518651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
25 3
12.5%
80 2
 
8.3%
35 2
 
8.3%
14 2
 
8.3%
21 1
 
4.2%
17 1
 
4.2%
24 1
 
4.2%
32 1
 
4.2%
100 1
 
4.2%
40 1
 
4.2%
Other values (7) 7
29.2%
(Missing) 2
 
8.3%
ValueCountFrequency (%)
3 1
 
4.2%
14 2
8.3%
17 1
 
4.2%
21 1
 
4.2%
24 1
 
4.2%
25 3
12.5%
32 1
 
4.2%
35 2
8.3%
38 1
 
4.2%
40 1
 
4.2%
ValueCountFrequency (%)
120 1
4.2%
118 1
4.2%
100 1
4.2%
90 1
4.2%
80 2
8.3%
73 1
4.2%
60 1
4.2%
40 1
4.2%
38 1
4.2%
35 2
8.3%

Interactions

2024-04-13T20:13:36.756670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T20:13:46.767636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본·지원과·사무소별연락처교육대상일 시장 소인원(명)
본·지원1.0001.0001.0000.7781.0001.0000.000
과·사무소별1.0001.0001.0000.0000.8531.0000.499
연락처1.0001.0001.0000.0000.8531.0000.499
교육대상0.7780.0000.0001.000NaN0.000NaN
일 시1.0000.8530.853NaN1.0000.9270.977
장 소1.0001.0001.0000.0000.9271.0000.725
인원(명)0.0000.4990.499NaN0.9770.7251.000
2024-04-13T20:13:46.961995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본·지원교육대상
본·지원1.0000.522
교육대상0.5221.000
2024-04-13T20:13:47.101680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인원(명)본·지원교육대상
인원(명)1.0000.0001.000
본·지원0.0001.0000.522
교육대상1.0000.5221.000

Missing values

2024-04-13T20:13:37.108992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T20:13:37.505220image/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.
2024-04-13T20:13:37.810730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

본·지원과·사무소별연락처교육대상일 시장 소인원(명)
0본원인증관리팀054-429-4173농업인<NA>미정<NA>
1본원인증관리팀054-429-4173시설담당자<NA>미정<NA>
2충남천안041-551-6060농업인2020.07.21. 10:00 ~ 12:00직산농협 회의실80
3충남천안041-551-6060농업인2020.07.27. 10:00 ~ 12:00직산농협 회의실40
4충남천안041-551-6060농업인2020.08.13. 10:00 ~ 12:00천안배원예농협 회의실118
5충남부여041-830-3407농업인2020.10.07. 14:00 ~ 16:00부여군농업기술센터21
6전북임실063-640-8212농업인2020.07.08. 10:00 ~12:00임실군청 5층 농민교육장25
7전남보성061-850-2632농업인2020.08.06. 09:00 ~ 11:00보성군 농업기술센터 대강당17
8전남보성061-850-2632농업인2020.08.06. 13:00 ~ 15:00보성군 농업기술센터 대강당25
9전남보성061-850-2632농업인2020.08.06. 16:00 ~ 18:00보성군 농업기술센터 대강당24
본·지원과·사무소별연락처교육대상일 시장 소인원(명)
14경남품질055-230-0853농업인2020.07.14. 13:00 ~ 15:00경남사회복지센터 대강당60
15경남품질055-230-0853농업인2020.07.28. 13:00 ~ 15:00경남사회복지센터 대강당73
16경남품질055-230-0853농업인2020.08.06. 14:00 ~ 16:00경남지원 함안사무소3
17경남품질055-230-0853농업인2020.08.18. 16:00 ~ 18:00동읍농협 경제사업장 회의실35
18경남고성055-670-1912농업인2020.08.13. 14:00 ~ 16:00고성거제통영농협 쌀조합공동사업법인 강의실25
19경남김해·양산055-310-4919농업인2020.07.29. 13:00 ~ 15:00경남단감원예농협80
20경남의령055-570-6205농업인2020.10.12. 10:00 ~ 12:00가례면 미나리 작목반 선별장14
21경남하동055-884-6060농업인2020.08.13. 14:00 ~ 16:00악양대봉감명품관38
22경남하동055-884-6060농업인2020.08.18. 14:00 ~ 18:00성평권역화합센터35
23경남남해055-860-6060농업인2020.10.28. 15:00 ~ 17:00새남해농협120