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Introduction
Filtering by row
Extracting data by column
Practice using filter() and select()
The pipe operator
22. More pipes!
Sorting rows
Summary

## Instruction

Did you see an advantage to using the pipe operator? Compared to the following line, it's more readable:

filter(select(data, conditions), conditions)

Soon, we will write even longer code, and we'll see more advantages to using pipes. For now, let's see how we can add more conditions to a statement.

Let's try selecting country_name and population information for countries with a population over 10,000,000. The code looks like this:

countries %>%
select(country_name, population) %>%
filter(population > 10 000 000)


## Exercise

Select the country_name, population, and continent information for Asian countries with populations under 1,000,000.

### Stuck? Here's a hint!

Type:

countries %>%
select(country_name, population, continent) %>%
filter(population < 1000000, continent == "Asia")