How can I filter out NA values in R?
I am assigned a particular task which is about analyzing databases which includes handling datasets with values that are missing or NAs. I need to pre-process the data and I want to perform operations on a particular column while excluding the missing values. Explain the steps for me to filter out NA values from my database in R.
For the process of filtering out NA in R for your particular data analytics project, you can use functions such as “na.omit()”, “complete.cases()”, or even utilize the direct subsetting. Here is the explanation given along with the coding analogy:-
By using na.omit()
# Assume ‘data’ is your dataset and ‘column_name’ is the specific column
Cleaned_data <- na.omit(data[, column_name])This particular function would remove the rows with any NA values in the column in which you want to create a cleaned subset of the dataset.
By using complete.cases()
# Assume ‘data’ is your dataset and ‘column_name’ is the specific column
Cleaned_data <- data[complete.cases(data[, column_name]), ]
This above function identifies the rows with the complete classes in the specified column.
Direct Subsetting
# Assume ‘data’ is your dataset and ‘column_name’ is the specific column
Cleaned_data <- data[!is.na(data[, column_name]), ]This above method would directly subset your particular dataset.