Summarizing data with dplyr

The following makes use of the dplyr package. You may need to install it from CRAN using the code install.packages("dplyr") if you want to run this on your computer. (The package is already installed on the notebook container, however.)

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Here we use data from the British Election Study 2010. The data set bes2010feelings.RData is prepared from the original available at https://www.britishelectionstudy.com/data-object/2010-bes-cross-section/ by removing identifying information and scrambling the data.

load("bes2010feelings.RData")

# A convenience function
Mean <- function(x,...) mean(x,na.rm=TRUE,...) 

bes2010feelings %>% group_by(wave,region) %>%
                    summarize(Brown=Mean(flng.brown),
                              Cameron=Mean(flng.cameron),
                              Clegg=Mean(flng.clegg),
                              N=n())

`summarise()` has grouped output by 'wave'. You can override using the
`.groups` argument.

# A tibble: 7 x 6
# Groups:   wave [2]
  wave  region   Brown Cameron Clegg     N
  <fct> <fct>    <dbl>   <dbl> <dbl> <int>
1 Pre   England   4.09    5.28  4.62  1159
2 Pre   Scotland  5.40    4.50  4.41   207
3 Pre   Wales     4.33    4.77  4.59   132
4 Pre   NA        4.51    4.93  4.43   437
5 Post  England   4.14    5.44  5.16  2175
6 Post  Scotland  5.51    4.54  4.51   665
7 Post  Wales     4.31    4.86  4.81   235