I'm applying a fertility model and to execute I need to save matrices for each childbearing intensity, which I called `mati`, according to its order. In this case, i=(1, 2, 3,...n)
The data frame bellow is an example of how my data is displayed. My real dataframe have 525 rows and 10 columns (`"AGE" "year" "mat1" "mat2" "mat3" "mat4" "mat5" "mat6" "mat7" "mat8"`). 

```
year <- c(rep(1998:2001, 4))
Age <- c(rep(15:18, 4))
mat1 <- c(rep(0.01, 16))
mat2 <- c(rep(0.012, 16))
mat3 <- c(rep(0.015, 16))
mat <- data.frame(year, Age, mat1, mat2, mat3)

mat

   year Age mat1  mat2  mat3
1  1998  15 0.01 0.012 0.015
2  1999  16 0.01 0.012 0.015
3  2000  17 0.01 0.012 0.015
4  2001  18 0.01 0.012 0.015
5  1998  15 0.01 0.012 0.015
6  1999  16 0.01 0.012 0.015
7  2000  17 0.01 0.012 0.015
8  2001  18 0.01 0.012 0.015
9  1998  15 0.01 0.012 0.015
10 1999  16 0.01 0.012 0.015
11 2000  17 0.01 0.012 0.015
12 2001  18 0.01 0.012 0.015
13 1998  15 0.01 0.012 0.015
14 1999  16 0.01 0.012 0.015
15 2000  17 0.01 0.012 0.015
16 2001  18 0.01 0.012 0.015

```

To execute get my final numeric matrices I already executed the code below, but it takes a long time.

```
##mat1###

library(dlyr)
library(tidyr)

mat1 <- #selecting just intensities of order 1 and creating matrices
  select(mat, Age, year, mat1) %>% 
  spread(year, mat1) 

names(mat1)[c(2:6)] <- paste0("year ", names(mat1[2:6])) #alter colnames
mat1[ ,1] <- paste0("age ", mat1[,1]) #alter the row from column "age"

mat_oe1 <- data.matrix(mat1[2:6])
dimnames(mat_oe1) <- list(c(mat1[,1]),
                          c(names(mat1[2:6])))
#Saving as txt to read i the model
write.table(mat_oe2, file = "mat_oe1.txt", sep = "\t",
            row.names = T, col.names = T)

##mat2
mat2 <- #selecting just intensities of order 1 and creating matrices
  select(mat, Age, year, mat2) %>% 
  spread(year, mat2) 

names(mat2)[c(2:6)] <- paste0("year ", names(mat2[2:6])) #alter colnames
mat2[ ,1] <- paste0("age ", mat2[,1]) #alter the row from column "age"

mat_oe2 <- data.matrix(mat2[2:6])
dimnames(mat_oe2) <- list(c(mat1[,1]),
                          c(names(mat1[2:6])))
#Saving as txt to read i the model
write.table(mat_oe2, file = "mat_oe2.txt", sep = "\t",
            row.names = T, col.names = T)

##mat3
mat3 <- #selecting just intensities of order 1 and creating matrices
  select(mat, Age, year, mat3) %>% 
  spread(year, mat3) 

names(mat3)[c(2:6)] <- paste0("year ", names(mat3[2:6])) #alter colnames
mat3[ ,1] <- paste0("age ", mat3[,1]) #alter the row from column "age"

mat_oe3 <- data.matrix(mat3[2:6])
dimnames(mat_oe3) <- list(c(mat3[,1]),
                          c(names(mat3[2:6])))
#Saving as txt to read i the model
write.table(mat_oe3, file = "mat_oe3.txt", sep = "\t",
            row.names = T, col.names = T)  

```

I'm using `spread` because I need data with the format below:

```
mat1 

     1998        1999       2000       2001
15   0.01        0.01       0.01       0.01
16   0.01        0.01       0.01       0.01
17   0.01        0.01       0.01       0.01
18   0.01        0.01       0.01       0.01

```

I also started to write a loop, but I'm stuck in the first line already.

```
mat_list <- list()
for(i in names(mat[,3:7])) {
  mat_list[[i]] <- data.frame(
                      spread(
                        select(mat, AGE, year, mat[[paste0("mat",i)]]), year, mat[[paste0("mat", i)]])) 

```

After applying the code above I've achieved the results below:

```
view(mat1)
        year 1998  year 1999  year 2000  year 2001
age 15   0.01        0.01       0.01       0.01
age 16   0.01        0.01       0.01       0.01
age 17   0.01        0.01       0.01       0.01
age 18   0.01        0.01       0.01       0.01

view(mat2)
        year 1998  year 1999    year 2000    year 2001
age 15   0.012        0.012       0.012       0.012
age 16   0.012        0.012       0.012       0.012
age 17   0.012        0.012       0.012       0.012
age 18   0.012        0.012       0.012       0.012

view(mat3)
        year 1998  year 1999    year 2000    year 2001
age 15   0.015        0.015       0.015       0.015
age 16   0.015        0.015       0.015       0.015
age 17   0.015        0.015       0.015       0.015
age 18   0.015        0.015       0.015       0.015

```