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I have a data.frame containing some columns with all NA values. How can I delete them from the data.frame?
Can I use the function,
na.omit(...) specifying some additional arguments?
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To remove observations with missing values in at least one column, you can use the na. omit() function. The na. omit() function in the R language inspects all columns from a data frame and drops rows that have NA's in one or more columns.
To remove all rows having NA, we can use na. omit function. For Example, if we have a data frame called df that contains some NA values then we can remove all rows that contains at least one NA by using the command na. omit(df).
The most easiest way to drop columns is by using subset() function. In the code below, we are telling R to drop variables x and z. The '-' sign indicates dropping variables. Make sure the variable names would NOT be specified in quotes when using subset() function.
One way of doing it:
df[, colSums(is.na(df)) != nrow(df)] If the count of NAs in a column is equal to the number of rows, it must be entirely NA.
Or similarly
df[colSums(!is.na(df)) > 0] If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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