You can use the following methods to convert multiple columns to factor using functions from the package:

Method 1: Convert Specific Columns to Factor

library(dplyr) 

df %>% mutate_at(c('col1', 'col2'), as.factor)

Method 2: Convert All Character Columns to Factor

library(dplyr)

df %>% mutate_if(is.character, as.factor)

The following examples show how to use each method in practice. 

Example 1: Convert Specific Columns to Factor

Suppose we have the following data frame in R:

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'B', 'B', 'C', 'C', 'D'),
                 position=c('G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'),
                 starter=c('Y', 'Y', 'Y', 'N', 'N', 'Y', 'N', 'N'),
                 points=c(12, 24, 25, 35, 30, 14, 19, 11))

#view structure of data frame
str(df)

'data.frame':	8 obs. of  4 variables:
 $ team    : chr  "A" "A" "A" "B" ...
 $ position: chr  "G" "G" "F" "F" ...
 $ starter : chr  "Y" "Y" "Y" "N" ...
 $ points  : num  12 24 25 35 30 14 19 11

We can see that the team, position, and starter columns are characters while the points column is numeric.

To convert just the team and position columns to factors, we can use the following syntax:

library(dplyr) 

#convert team and position columns to factor
df <- df %>% mutate_at(c('team', 'position'), as.factor)

#view structure of updated data frame
str(df)

'data.frame':	8 obs. of  4 variables:
 $ team    : Factor w/ 4 levels "A","B","C","D": 1 1 1 2 2 3 3 4
 $ position: Factor w/ 2 levels "F","G": 2 2 1 1 2 2 1 1
 $ starter : chr  "Y" "Y" "Y" "N" ...
 $ points  : num  12 24 25 35 30 14 19 11

We can see that the team and position columns are now both factors.

Example 2: Convert All Character Columns to Factor

Suppose we have the following data frame in R:

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'B', 'B', 'C', 'C', 'D'),
                 position=c('G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'),
                 starter=c('Y', 'Y', 'Y', 'N', 'N', 'Y', 'N', 'N'),
                 points=c(12, 24, 25, 35, 30, 14, 19, 11))

#view structure of data frame
str(df)

'data.frame':	8 obs. of  4 variables:
 $ team    : chr  "A" "A" "A" "B" ...
 $ position: chr  "G" "G" "F" "F" ...
 $ starter : chr  "Y" "Y" "Y" "N" ...
 $ points  : num  12 24 25 35 30 14 19 11

We can see that three of the columns in the data frame are character columns.

library(dplyr) 

#convert all character columns to factor
df <- df %>% mutate_if(is.character, as.factor)

#view structure of updated data frame
str(df)

'data.frame':	8 obs. of  4 variables:
 $ team    : Factor w/ 4 levels "A","B","C","D": 1 1 1 2 2 3 3 4
 $ position: Factor w/ 2 levels "F","G": 2 2 1 1 2 2 1 1
 $ starter : Factor w/ 2 levels "N","Y": 2 2 2 1 1 2 1 1
 $ points  : num  12 24 25 35 30 14 19 11

We can see that all of the character columns are now factors.

Note: Refer to the for a complete explanation of the mutate_at and mutate_if functions.