Rewriting code using dplyr

In the previous chapter, R was used to find the estimate of the total road length in 2011. Here are the steps that were completed in the previous chapter, written using dplyr verbs:

• Filter out the rows with a mean greater than 2000
• Filter out the rows in which all values are NA
• Mutate the 2011 column to create a copy in which the NA values are replaced with the row mean
• Select the new 2011 column and find the sum of its values

At the beginning of dplyr_intro.R, the first step should be to read artificial_roads_by_region.csv to an R dataframe as follows:

roads.lengths <- read.csv("data/artificial_roads_by_region.csv")

Next, In the following continuation of dplyr_intro.R, a copy of the original roads length data called roads.length2 is created. The row averages and the row sums of the roads.length2 dataframe are calculated and added as columns to the dataframe. These columns will help with the filtering steps.

roads.lengths2<-roads.lengths
roads.lengths2$mean_val ...