Warning message: In `...` : invalid factor level, NA generated

The warning message is because your "Type" variable was made a factor and "lunch" was not a defined level. Use the stringsAsFactors = FALSE flag when making your data frame to force "Type" to be a character.

> fixed <- data.frame("Type" = character(3), "Amount" = numeric(3))> str(fixed)'data.frame':   3 obs. of  2 variables: $ Type  : Factor w/ 1 level "": NA 1 1 $ Amount: chr  "100" "0" "0"> > fixed <- data.frame("Type" = character(3), "Amount" = numeric(3),stringsAsFactors=FALSE)> fixed[1, ] <- c("lunch", 100)> str(fixed)'data.frame':   3 obs. of  2 variables: $ Type  : chr  "lunch" "" "" $ Amount: chr  "100" "0" "0"

If you are reading directly from CSV file then do like this.

myDataFrame <- read.csv("path/to/file.csv", header = TRUE, stringsAsFactors = FALSE)

Here is a flexible approach, it can be used in all cases, in particular:

1. to affect only one column, or
2. the dataframe has been obtained from applying previous operations (e.g. not immediately opening a file, or creating a new data frame).

First, un-factorize a string using the as.character function, and, then, re-factorize with the as.factor (or simply factor) function:

fixed <- data.frame("Type" = character(3), "Amount" = numeric(3))# Un-factorize (as.numeric can be use for numeric values)#              (as.vector  can be use for objects - not tested)fixed$Type <- as.character(fixed$Type)fixed[1, ] <- c("lunch", 100)# Re-factorize with the as.factor function or simple factor(fixed$Type)fixed$Type <- as.factor(fixed$Type)