Overview

Dataset statistics

Number of variables4
Number of observations58
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory35.3 B

Variable types

Text1
Numeric1
Categorical2

Dataset

Description부산광역시 강서구 농협별 작목별 작목반 현황입니다. (농협별 - 대저농협, 강동농협, 가락농협, 녹산농협, 부경원협, 웅동농협) (작목별 - 벼, 토마토, 엽채류, 화훼류 등)
Author부산광역시 강서구
URLhttps://www.data.go.kr/data/15040345/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:20:44.639264
Analysis finished2023-12-12 23:20:45.122891
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단체명
Text

UNIQUE 

Distinct58
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size596.0 B
2023-12-13T08:20:45.304418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.051724
Min length8

Characters and Unicode

Total characters641
Distinct characters116
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

Unique58 ?
Unique (%)100.0%

Sample

1st row가락농협 참살이 쌀 작목회
2nd row가락농협 가락화훼작목회
3rd row가락농협 해바라기작목회
4th row강동농협 화훼작목회
5th row강동농협 시설채소연구회
ValueCountFrequency (%)
대저농협 34
28.8%
강동농협 9
 
7.6%
부경원협 6
 
5.1%
녹산농협 4
 
3.4%
가락농협 3
 
2.5%
대파작목반 2
 
1.7%
무지개토마토 1
 
0.8%
맥도토마토 1
 
0.8%
미래토마토 1
 
0.8%
순서토마토 1
 
0.8%
Other values (56) 56
47.5%
2023-12-13T08:20:45.726428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
 
9.4%
협 59
 
9.2%
농 53
 
8.3%
토 50
 
7.8%
대 39
 
6.1%
저 35
 
5.5%
작 33
 
5.1%
목 32
 
5.0%
마 25
 
3.9%
반 25
 
3.9%
Other values (106) 230
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
90.5%
Space Separator 60
 
9.4%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
협 59
 
10.2%
농 53
 
9.1%
토 50
 
8.6%
대 39
 
6.7%
저 35
 
6.0%
작 33
 
5.7%
목 32
 
5.5%
마 25
 
4.3%
반 25
 
4.3%
회 14
 
2.4%
Other values (104) 215
37.1%
Space Separator
ValueCountFrequency (%)
60
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
90.5%
Common 61
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
협 59
 
10.2%
농 53
 
9.1%
토 50
 
8.6%
대 39
 
6.7%
저 35
 
6.0%
작 33
 
5.7%
목 32
 
5.5%
마 25
 
4.3%
반 25
 
4.3%
회 14
 
2.4%
Other values (104) 215
37.1%
Common
ValueCountFrequency (%)
60
98.4%
1 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
90.5%
ASCII 61
 
9.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60
98.4%
1 1
 
1.6%
Hangul
ValueCountFrequency (%)
협 59
 
10.2%
농 53
 
9.1%
토 50
 
8.6%
대 39
 
6.7%
저 35
 
6.0%
작 33
 
5.7%
목 32
 
5.5%
마 25
 
4.3%
반 25
 
4.3%
회 14
 
2.4%
Other values (104) 215
37.1%

회원수
Real number (ℝ)

Distinct25
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.775862
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size654.0 B
2023-12-13T08:20:45.848335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.85
Q113
median17
Q322
95-th percentile47.9
Maximum120
Range115
Interquartile range (IQR)9

Descriptive statistics

Standard deviation18.175599
Coefficient of variation (CV)0.83466724
Kurtosis15.734469
Mean21.775862
Median Absolute Deviation (MAD)5
Skewness3.5192066
Sum1263
Variance330.35239
MonotonicityNot monotonic
2023-12-13T08:20:46.020305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
17 7
 
12.1%
15 6
 
10.3%
13 4
 
6.9%
18 4
 
6.9%
16 4
 
6.9%
22 3
 
5.2%
10 3
 
5.2%
8 3
 
5.2%
12 2
 
3.4%
20 2
 
3.4%
Other values (15) 20
34.5%
ValueCountFrequency (%)
5 1
 
1.7%
7 2
 
3.4%
8 3
5.2%
10 3
5.2%
11 2
 
3.4%
12 2
 
3.4%
13 4
6.9%
15 6
10.3%
16 4
6.9%
17 7
12.1%
ValueCountFrequency (%)
120 1
1.7%
79 1
1.7%
53 1
1.7%
47 1
1.7%
38 2
3.4%
35 1
1.7%
33 2
3.4%
31 2
3.4%
30 1
1.7%
27 1
1.7%

재배작목
Categorical

Distinct16
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size596.0 B
토마토
26 
엽채류
10 
화훼
4 
깻잎
3 
벼
 
2
Other values (11)
13 

Length

Max length5
Median length3
Mean length2.6896552
Min length1

Unique

Unique9 ?
Unique (%)15.5%

Sample

1st row벼
2nd row화훼
3rd row토마토
4th row국화
5th row엽채

Common Values

ValueCountFrequency (%)
토마토 26
44.8%
엽채류 10
 
17.2%
화훼 4
 
6.9%
깻잎 3
 
5.2%
벼 2
 
3.4%
국화 2
 
3.4%
대파 2
 
3.4%
엽채 1
 
1.7%
호박 1
 
1.7%
배추 1
 
1.7%
Other values (6) 6
 
10.3%

Length

2023-12-13T08:20:46.140127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
토마토 26
44.8%
엽채류 10
 
17.2%
화훼 4
 
6.9%
깻잎 3
 
5.2%
벼 2
 
3.4%
국화 2
 
3.4%
대파 2
 
3.4%
엽채 1
 
1.7%
호박 1
 
1.7%
배추 1
 
1.7%
Other values (6) 6
 
10.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size596.0 B
2022-10-20
58 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-20
2nd row2022-10-20
3rd row2022-10-20
4th row2022-10-20
5th row2022-10-20

Common Values

ValueCountFrequency (%)
2022-10-20 58
100.0%

Length

2023-12-13T08:20:46.254935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:46.384444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-20 58
100.0%

Interactions

2023-12-13T08:20:44.813999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:20:46.453343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단체명회원수재배작목
단체명1.0001.0001.000
회원수1.0001.0000.543
재배작목1.0000.5431.000
2023-12-13T08:20:46.527689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회원수재배작목
회원수1.0000.249
재배작목0.2491.000

Missing values

2023-12-13T08:20:44.963428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:20:45.080217image/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

단체명회원수재배작목데이터기준일자
0가락농협 참살이 쌀 작목회38벼2022-10-20
1가락농협 가락화훼작목회53화훼2022-10-20
2가락농협 해바라기작목회47토마토2022-10-20
3강동농협 화훼작목회120국화2022-10-20
4강동농협 시설채소연구회31엽채2022-10-20
5강동농협 토마토연구회18토마토2022-10-20
6강동농협 덕도토마토작목회31토마토2022-10-20
7강동농협 방울토마토작목회8토마토2022-10-20
8강동농협 호박작목회21호박2022-10-20
9강동농협 배추연구회33배추2022-10-20
단체명회원수재배작목데이터기준일자
48대저농협 맛깔작목반17엽채류2022-10-20
49대저농협 대저대파작목반8엽채류2022-10-20
50대저농협 햇살작목반12엽채류2022-10-20
51대저농협 대평화훼작목반13화훼2022-10-20
52대저농협 중리1구작목반16화훼2022-10-20
53대저농협 청화화훼작목반10화훼2022-10-20
54대저농협 선농회18벼2022-10-20
55대저농협 청년작목반18토마토2022-10-20
56대저농협 토마토공선회30토마토2022-10-20
57부산축협 한우작목반27한우2022-10-20