Problem understanding the dot operator in dplyr

Carlo Rivera 0
Viewed 55

I'm trying the edX Harvard R Basics and Data Visualization courses, but I'm having quite a hard time trying to understand the functionality of the dot (.) operator.

I tried the code below:

gapminder %>%
  filter(year %in% c(1970, 2010) & !is.na(gdp)) %>%
  mutate(group = ifelse(region %in% west, "West", "Developing")) %>%
  ggplot(aes(dollars_per_day)) +
  geom_histogram(binwidth = 1, color = "black") +
  scale_x_continuous(trans = "log2") +
  facet_grid(year ~ group)

Here's where I get stuck, because I'm trying to intersect both lists, but if I put the "%>% .$country" in both lists, intersect them, then go to the histogram, everything runs well.

country_list_1 <- gapminder %>%
  filter(year == 1970 & !is.na(dollars_per_day)) %>% .$country
country_list_2 <- gapminder %>%
  filter(year == 2010 & !is.na(dollars_per_day)) %>% .$country
country_list <- intersect(country_list_1, country_list_2)

gapminder %>%
  filter(year %in% c(1970, 2010) & country %in% country_list) %>% 
  mutate(group = ifelse(region %in% west, "West", "Developing")) %>%
  ggplot(aes(dollars_per_day)) +
  geom_histogram(binwidth = 1, color = "black") +
  scale_x_continuous(trans = "log2") +
  facet_grid(year ~ group)

But if I do this (skip the %>% .$country) it returns the error "Faceting variables must have at least one value":

country_list_1 <- gapminder %>%
  filter(year == 1970 & !is.na(dollars_per_day))
country_list_2 <- gapminder %>%
  filter(year == 2010 & !is.na(dollars_per_day))
country_list <- intersect(country_list_1, country_list_2)

gapminder %>%
  filter(year %in% c(1970, 2010) & country %in% country_list) %>% 
  mutate(group = ifelse(region %in% west, "West", "Developing")) %>%
  ggplot(aes(dollars_per_day)) +
  geom_histogram(binwidth = 1, color = "black") +
  scale_x_continuous(trans = "log2") +
  facet_grid(year ~ group)

I don't quite get the logic of that, nor the function of the dot per se.

Section 3, 3.2 Using the Gapminder Dataset, 5th video "comparing distributions" of the Data Science: Visualization in R course HarvardX

dplyr r
1 Answers

In addition to the comments above, you may need to learn about subsetting with $. When you run

my_new_df <- gapminder %>%
  filter(year == 1970 & !is.na(dollars_per_day))

you get back a data set (a tibble) with fewer rows then before. But you still have all of the columns. Now the $ lets you pick out a single column. So the list of countries is in the vector.

my_new_df$country

As mentioned in the comments to your question, the . operator just says to put everything coming in from the left side of the pipe %>% into that spot.

Michael Dewar0
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