How to use the `dplyr::rowwise` function with more than one variable?

Question

Consider the data set below:

df_1 <- data.frame(
  x = replicate(4, runif(30, 20, 100)), 
  y = sample(1:3, 30, replace = TRUE)
)

I did the following analysis:

library(tidyverse)

df_1 %>% 
  select(-y) %>% 
  rowwise() %>% 
  mutate(var = sum(c(x.1, x.3)))

And it works. But I want to analyze all the variables in one go. I tried this in two ways:

1) Conventional method using the . as a substitute for variables:

df_1 %>% 
  select(-y) %>% 
  rowwise() %>% 
  mutate(var = sum(.))

2) Method select_if, to select only numerical variables:

df_1 %>% 
  select(-y) %>% 
  rowwise() %>% 
  mutate(var = sum(select_if(., is.numeric)))

The two methods above return this:

Source: local data frame [30 x 5]
Groups: <by row>

# A tibble: 30 x 5
     x.1   x.2   x.3   x.4   var
   <dbl> <dbl> <dbl> <dbl> <dbl>
 1  32.7  42.7  50.1  20.8 7091.
 2  75.9  71.3  83.6  77.6 7091.
 3  49.6  28.7  97.0  59.7 7091.
 4  47.4  96.1  31.9  79.7 7091.
 5  54.2  47.1  81.7  41.6 7091.
 6  27.9  58.1  97.4  25.9 7091.
 7  61.8  78.3  52.6  67.7 7091.
 8  85.4  51.3  38.8  82.0 7091.
 9  27.9  72.6  68.9  25.2 7091.
10  87.2  42.1  27.6  73.9 7091.
# ... with 20 more rows

Where 7091. is an incorrect sum.

How do I adjust both functions? I also tried one mutate_at in the first method, but without success.

Answer 1

In method 1 I understood that it is returning the total sum value of all objects. In method 2 there is something analogous.

set.seed(1)
df_1 <- data.frame(
  x = replicate(4, runif(30, 20, 100)), 
  y = sample(1:3, 30, replace = TRUE))

library(dplyr)
df_x <- df_1 %>% 
  dplyr::select(-y) %>% 
  dplyr::mutate(Var = rowSums(.))

---

> df_x
        x.1      x.2      x.3      x.4      Var
1  41.24069 58.56641 93.03007 39.17035 232.0075
2  49.76991 67.96527 43.48827 24.71475 185.9382
3  65.82827 59.48330 56.72526 71.38306 253.4199
4  92.65662 34.89741 46.59157 90.10154 264.2471
5  36.13455 86.18987 72.06964 82.31317 276.7072
. . .

---

• Using the for:

library(tidyverse)
df_1 <- df_1 %>% 
  dplyr::select(-y)
df <- matrix(nrow = nrow(df_1), ncol = 1)
for (i in 1:nrow(df_1)) {
  valor <- df_1 %>% 
    dplyr::slice(i) %>% 
    dplyr::rowwise() %>% 
    dplyr::mutate(var = sum(.))
  df[i,1] <- valor$var

}
df <- as.data.frame(df)
df_1 <- df_1 %>% 
  dplyr::mutate(var = df[,1])
df_1 

> df_1
        x.1      x.2      x.3      x.4      var
1  41.24069 58.56641 93.03007 39.17035 232.0075
2  49.76991 67.96527 43.48827 24.71475 185.9382
3  65.82827 59.48330 56.72526 71.38306 253.4199
4  92.65662 34.89741 46.59157 90.10154 264.2471

. . .