How to filter data in R programming language?

In R programming language, you can filter data using the following methods:

1. Filter data using logical operators. Create logical expressions using logical operators (such as <, >, <=, >=, ==, !=) and use them as index conditions to filter the data. For example, if there is a data set df and you want to filter out observations with an age greater than or equal to 18, you can use the following code:

df_subset <- df[df$age >= 18, ]

1. Filter the data using conditional statements. Use the ifelse() function to create a conditional statement, then use this statement as an indexing condition to filter the data. For example, suppose there is a dataset df, and you want to filter out observations with an age greater than or equal to 18 years old, you can use the following code:

df_subset <- df[ifelse(df$age >= 18, TRUE, FALSE), ]

1. Filter the data using the subset() function. The subset() function can filter the data based on specified conditions, and selectively retain specified variables. For example, if there is a dataset df, and we want to filter out observations with ages greater than or equal to 18, while retaining only the variables of name and age, the following code can be used:

df_subset <- subset(df, age >= 18, select = c(name, age))

The above are common methods for filtering datasets, and you can choose the appropriate method for data filtering based on specific needs.