Combining Data Manipulations in dplyr · Data Science in Omics Introduction

Combine a series of data manipulation actions
Do each action in sequential order

Intermediate variables

Determine the mean weight of DS in each year

surveys_DS <- filter(surveys, species_id == "DS", !is.na(weight))
surveys_DS_by_yr <- group_by(surveys_DS, year)
avg_weight_DS_by_yr <- summarize(surveys_DS_by_yr,
                                 avg_weight = mean(weight))

Do Portal Data Manipulation Exercise 1-2

Pipes

Intermediate variables can get cumbersome if their are lots of steps.
%>% (“pipe”) takes the output of one command and passes it as input to the next command
x %>% f(y) translates to f(x, y)

surveys %>%
  filter(species_id == "DS", !is.na(weight))

avg_weight_DS_by_yr <- surveys %>%
  filter(species_id == "DS", !is.na(weight)) %>%
  group_by(year) %>%
  summarize(avg_weight = mean(weight))

Modify your answer to Task 2 in Portal Data Manipulation to use pipes.