Filtering Rows

What is Filtering?

Datasets often contain a large amount of data, and it can be challenging to work with all of it at once. Filtering is a way to reduce the size of the dataset by selecting only the rows that meet specific criteria.

Why do we need to filter data?

There are several reasons why we might want to filter data. Some reasons include:

What we’ll learn in this section

Basic Syntax for Filtering

To use the filter function in dplyr, we use the following syntax:

 data |> 
  filter(condition) 

We specify the dataset we want to filter, followed by the |> operator, and then the filter function. Inside the filter function, we specify the condition that we want to filter on.

The condition can be any logical expression that evaluates to TRUE or FALSE . Rows where the condition is TRUE are kept, and rows where the condition is FALSE are removed.

For example, here is an example condition:

 column_name > 10 

This code will keep only the rows where the value in the column column_name is greater than 10.

If we need to filter rows that are equal to a specific value, we use the == operator. It has two equal signs, not one. For a value less than, we use < , for greater than, we use > , for less than or equal to, we use <= , and for greater than or equal to, we use >= .

We can also use != to filter rows that are not equal to a specific value.

Remember that you have to use two equal signs == for comparison, not one equal sign = .

Filtering with a Single Condition

 flowers |> 
  filter(growth == "fast") 

Filtering with Multiple Conditions

You can also filter rows based on multiple conditions. To do this, you can use the & operator to combine conditions.

Syntax for when both conditions must be met

You can use a comma , or the & operator to filter rows that meet both conditions.

 data |> 
  filter(condition1, condition2) 

or

 data |> 
  filter(condition1 & condition2) 

 flowers |> 
  filter(season == "Summer", growth == "fast") 

Syntax for when at least one condition must be met

You can use the | operator to filter rows that meet either of two conditions.

 data |> 
  filter(condition1 | condition2) 

This code will return rows that satisfy either condition1 or condition2 .

 flowers |> 
  filter(height < 91 | sunlight > 8.5) 

Filtering rows that do not meet a condition

You can use the ! operator to filter rows that do not meet a condition.

 data |> 
  filter(!condition) 

 flowers |> 
  filter(!(growth == "slow"))
 
# or 
 
flowers |> 
  filter(growth != "slow") 

Review