Overview

Dataset statistics

Number of variables4
Number of observations50
Missing cells128
Missing cells (%)64.0%
Duplicate rows1
Duplicate rows (%)2.0%
Total size in memory1.7 KiB
Average record size in memory34.6 B

Variable types

Text1
Unsupported3

Dataset

Description농림축산검역본부는 전국 꿀벌질병 병성감정을 수행하고 있으며, 분기별 진단 실적을 개방함으로써 농가에서 국내 질병 발생 현황을 파악하고 이동양봉 및 사양관리에 활용하여 선제적 질병방제 기반을 마련하고자함
Author농림축산식품부
URLhttps://www.data.go.kr/data/15075939/fileData.do

Alerts

Dataset has 1 (2.0%) duplicate rowsDuplicates
축종 has 37 (74.0%) missing valuesMissing
전염병1(14종※) has 30 (60.0%) missing valuesMissing
전염병(14종)+농약검사2(43종) has 24 (48.0%) missing valuesMissing
농약검사2(43종) has 37 (74.0%) missing valuesMissing
전염병1(14종※) is an unsupported type, check if it needs cleaning or further analysisUnsupported
전염병(14종)+농약검사2(43종) is an unsupported type, check if it needs cleaning or further analysisUnsupported
농약검사2(43종) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 14:50:15.513872
Analysis finished2023-12-12 14:50:15.886624
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

축종
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing37
Missing (%)74.0%
Memory size532.0 B
2023-12-12T23:50:16.000737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length4.5384615
Min length2

Characters and Unicode

Total characters59
Distinct characters34
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

Unique13 ?
Unique (%)100.0%

Sample

1st row꿀벌
2nd row0종
3rd row1종
4th row2종
5th row3종
ValueCountFrequency (%)
꿀벌 2
 
10.5%
0종 1
 
5.3%
43종 1
 
5.3%
분류 1
 
5.3%
그래프 1
 
5.3%
실적 1
 
5.3%
질병진단 1
 
5.3%
4분기 1
 
5.3%
바이러스성 1
 
5.3%
기생충성 1
 
5.3%
Other values (8) 8
42.1%
2023-12-12T23:50:16.378054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
종 6
 
10.2%
6
 
10.2%
성 4
 
6.8%
4 3
 
5.1%
꿀 2
 
3.4%
벌 2
 
3.4%
기 2
 
3.4%
진 2
 
3.4%
균 2
 
3.4%
분 2
 
3.4%
Other values (24) 28
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44
74.6%
Decimal Number 9
 
15.3%
Space Separator 6
 
10.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 6
 
13.6%
성 4
 
9.1%
꿀 2
 
4.5%
벌 2
 
4.5%
기 2
 
4.5%
진 2
 
4.5%
균 2
 
4.5%
분 2
 
4.5%
병 2
 
4.5%
질 2
 
4.5%
Other values (18) 18
40.9%
Decimal Number
ValueCountFrequency (%)
4 3
33.3%
3 2
22.2%
1 2
22.2%
2 1
 
11.1%
0 1
 
11.1%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44
74.6%
Common 15
 
25.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 6
 
13.6%
성 4
 
9.1%
꿀 2
 
4.5%
벌 2
 
4.5%
기 2
 
4.5%
진 2
 
4.5%
균 2
 
4.5%
분 2
 
4.5%
병 2
 
4.5%
질 2
 
4.5%
Other values (18) 18
40.9%
Common
ValueCountFrequency (%)
6
40.0%
4 3
20.0%
3 2
 
13.3%
1 2
 
13.3%
2 1
 
6.7%
0 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44
74.6%
ASCII 15
 
25.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
종 6
 
13.6%
성 4
 
9.1%
꿀 2
 
4.5%
벌 2
 
4.5%
기 2
 
4.5%
진 2
 
4.5%
균 2
 
4.5%
분 2
 
4.5%
병 2
 
4.5%
질 2
 
4.5%
Other values (18) 18
40.9%
ASCII
ValueCountFrequency (%)
6
40.0%
4 3
20.0%
3 2
 
13.3%
1 2
 
13.3%
2 1
 
6.7%
0 1
 
6.7%

전염병1(14종※)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)60.0%
Memory size532.0 B

전염병(14종)+농약검사2(43종)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)48.0%
Memory size532.0 B

농약검사2(43종)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)74.0%
Memory size532.0 B

Missing values

2023-12-12T23:50:15.594107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:50:15.696476image/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.
2023-12-12T23:50:15.810538image/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

축종전염병1(14종※)전염병(14종)+농약검사2(43종)농약검사2(43종)
0꿀벌146
1<NA>건수질병지역
20종1NaN경북 칠곡
31종0NaNNaN
42종3ACAR + IAPV충북 괴산
5<NA>NaNDWV + IAPV경북 구미
6<NA>NaNNOSEMA+ASCO충북 제천
73종1SBV+DWV+CBPV경북 김천
8꿀벌 질병 14종NaNNaNNaN
9세균성AFB미국부저병NaN
축종전염병1(14종※)전염병(14종)+농약검사2(43종)농약검사2(43종)
40<NA>NaNNaNNaN
41<NA>NaNNaNNaN
42<NA>NaNNaNNaN
43<NA>NaNNaNNaN
44분류NaN검출물질명건수
4543종 농약검사NaN사이퍼메트린2
46<NA>NaN페니트로티온2
47<NA>NaN티아메톡삼1
48<NA>NaN클로티아니딘1
49<NA>NaN카바릴1

Duplicate rows

Most frequently occurring

축종# duplicates
0<NA>37