Repaso 1

rto=rnorm(100, mean = 5, sd = 0.25)
rto=round(rto, digits = 2); rto

##   [1] 5.12 4.90 4.43 4.59 5.24 5.54 4.88 4.83 5.03 4.36 4.57 4.67 5.09 5.21 5.17
##  [16] 5.27 4.86 4.84 4.76 5.13 4.88 5.05 5.01 4.51 4.65 5.07 4.77 5.06 4.62 5.00
##  [31] 4.98 5.37 5.11 5.17 4.83 5.04 5.14 5.15 4.69 5.06 4.85 5.36 4.57 4.80 5.20
##  [46] 4.67 5.34 4.88 4.95 5.10 5.19 4.66 5.31 5.16 4.86 5.28 5.11 4.94 5.14 5.16
##  [61] 4.97 4.86 4.96 4.73 4.85 4.44 5.59 5.01 5.22 4.89 5.15 4.90 4.92 4.74 4.96
##  [76] 5.35 5.15 5.09 5.03 5.12 4.91 5.08 4.74 5.16 4.88 5.10 4.82 5.12 4.57 4.93
##  [91] 4.96 4.97 5.13 5.01 5.11 4.92 4.60 5.21 5.06 4.89

pH = c(7.6,6,NA, 5, 5, 3.7, 6.3,8,4.2,7)

length(rto)

## [1] 100

rto[length(rto)]

## [1] 4.89

rto[100]

## [1] 4.89

# Cambiar valores
rto[100]=3
rto[100]

## [1] 3

which.max(rto) # Posición (Dónde está)

## [1] 67

rto[which.max(rto)] # (indexar) El número máximo

## [1] 5.59

boxplot(rto)

boxplot(rto, horizontal = T)

sismo=rexp(100, rate=0.6)
hist(sismo,ylim=c(0,50))

#library(readxl)
#datosNE <- read_excel("C:/Users/jmigu/Desktop/datosNE.xlsx")
#View(datosNE)

#hist(repaso$datosNE)

M1 = matrix(data = 1:9, nrow = 3, byrow = T)
M1

##      [,1] [,2] [,3]
## [1,]    1    2    3
## [2,]    4    5    6
## [3,]    7    8    9

# [fila, columna]
M1[1,3]

## [1] 3

M2=M1[,-3]
M2

##      [,1] [,2]
## [1,]    1    2
## [2,]    4    5
## [3,]    7    8

#Matriz identidad
v1=rep(1,5)
v1

## [1] 1 1 1 1 1

v2=diag(v1)
v2

##      [,1] [,2] [,3] [,4] [,5]
## [1,]    1    0    0    0    0
## [2,]    0    1    0    0    0
## [3,]    0    0    1    0    0
## [4,]    0    0    0    1    0
## [5,]    0    0    0    0    1

#dataframes
MO=c(2,5,9,6,8,5,8,5,6,9)
rto2=rnorm(10,5,3)
df=data.frame(MO,rto2)
df

##    MO      rto2
## 1   2 1.5714684
## 2   5 3.7191634
## 3   9 6.6716627
## 4   6 4.9695217
## 5   8 8.0291522
## 6   5 4.4906766
## 7   8 0.2561059
## 8   5 1.1549912
## 9   6 9.1537404
## 10  9 5.9283567

df[5,2]=NA

df$Alt=rnorm(10,2,0.25)
df

##    MO      rto2      Alt
## 1   2 1.5714684 1.982802
## 2   5 3.7191634 1.606244
## 3   9 6.6716627 1.876649
## 4   6 4.9695217 2.147875
## 5   8        NA 2.105907
## 6   5 4.4906766 1.944162
## 7   8 0.2561059 1.889040
## 8   5 1.1549912 2.644970
## 9   6 9.1537404 1.855899
## 10  9 5.9283567 2.102743

colnames(df)=c("N1","N2","N3")
df

##    N1        N2       N3
## 1   2 1.5714684 1.982802
## 2   5 3.7191634 1.606244
## 3   9 6.6716627 1.876649
## 4   6 4.9695217 2.147875
## 5   8        NA 2.105907
## 6   5 4.4906766 1.944162
## 7   8 0.2561059 1.889040
## 8   5 1.1549912 2.644970
## 9   6 9.1537404 1.855899
## 10  9 5.9283567 2.102743

Edward Rolf Tufte, sometimes known as "ET", is an American statistician and professor emeritus of political science, statistics, and computer science at Yale University. He is noted for his writings on information design and as a pioneer in the field of data visualization.