Clase 2 CE 2022 - 2

library(readxl)

Nemato2 <- read_excel("C:/Users/usuagro/Downloads/mmacostasaranorato.xlsx", 
    sheet = "data")

Nemato2

## # A tibble: 26 x 15
##    g         L   MBW   ABW     E   LRW   DGO  DCPE    Le    Lc    Ph     a     b
##    <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
##  1 L      527.  17.3 11.2   12.9  4.1   3.98  85.1  90.2  52.1  15.3  30.5  5.84
##  2 L      483.  16.2 11.0   14.0  4.29  4.19  88.9 100.   50.0  13.0  29.8  4.83
##  3 L      442.  18.5 11.8   13.5  3.8   4.89  92.3  98.2  51.4  13.2  24.0  4.50
##  4 L      451.  14.2  9.22  12.7  3.97  3.87  89.1  85.2  51.5  16.9  31.8  5.29
##  5 L      455.  15.4 12.3   12.1  4.72  3.96  88.1  88.9  51.0  13.3  29.7  5.12
##  6 L      460.  13.0 11.2   12.5  3.71  4.08  87.6  90.2  51.9  12.7  35.4  5.10
##  7 L      431.  13.0 10.4   12.5  4.62  4.37  90.1  92.3  49.0  12.6  33.1  4.67
##  8 L      467.  10.7 10.4   13.4  4.43  4.85  92.3  89.9  49.4  13.5  43.6  5.20
##  9 L      409.  15.4 14.2   13.2  3.79  4.21  86.8  95.2  52.7  12.4  26.6  4.30
## 10 L      446.  18.4 10.4   13.7  4.64  3.99  87.0  93.5  51.8  12.7  24.2  4.77
## # ... with 16 more rows, and 2 more variables: c1 <dbl>, c2 <dbl>

library(corrplot)

## corrplot 0.92 loaded

Nemato2= Nemato2[,-1]
M=cor(Nemato2)
corrplot(M, method = "circle")

corrplot(M, method = "number")

library(PerformanceAnalytics)

## Loading required package: xts

## Loading required package: zoo

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

## 
## Attaching package: 'PerformanceAnalytics'

## The following object is masked from 'package:graphics':
## 
##     legend

chart.Correlation(M, histogram = T, method = "pearson")

Nemato2.1 <- read_excel("C:/Users/usuagro/Downloads/mmacostasaranorato.xlsx", 
    sheet = "data")
library(lattice)
library(ggplot2)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:xts':
## 
##     first, last

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

P1<-ggplot(Nemato2.1, aes(x=g, y=L, fill=g))+geom_boxplot()

P2<-ggplot(Nemato2.1, aes(x=g, y=MBW, fill=g))+geom_boxplot()

P3<-ggplot(Nemato2.1, aes(x=g, y=ABW, fill=g))+geom_boxplot()

P4<-ggplot(Nemato2.1, aes(x=g, y=E, fill=g))+geom_boxplot()

library(gridExtra)

## 
## Attaching package: 'gridExtra'

## The following object is masked from 'package:dplyr':
## 
##     combine

grid.arrange(P1,P2,P3,P4)

P5<-ggplot(Nemato2.1, aes(x=g, y=c1, fill=g))+geom_boxplot()
P6<-ggplot(Nemato2.1, aes(x=g, y=c2, fill=g))+geom_boxplot()

grid.arrange(P5, P6)

for(i in 2:ncol(Nemato2.1)){
  p<-ggplot(Nemato2.1,aes(x=g,y=unlist(Nemato2.1[,i]),fill=g))+
  geom_boxplot()+
    labs(y=colnames(Nemato2.1)[i])
  print(p)
}