Numeric data is not numeric.

[EconomiCurtis]

You can use the str function to find out what type a variable is.

For example

df <- data.frame(c1 = 1:3, c2 = c(1.2, 1.3, 1.4), c4 = LETTERS[1:3])
str(df)
#> 'data.frame':    3 obs. of  3 variables:
#>  $ c1: int  1 2 3
#>  $ c2: num  1.2 1.3 1.4
#>  $ c4: Factor w/ 3 levels "A","B","C": 1 2 3

^{Created on 2019-05-08 by the reprex package (v0.2.1)}

Note this tells you that c1 and c2 are both numerics (an integer and a floating point are both considered numerics by R), where c4 is a factor.

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As a note, it is extremely hard to help debug code and/or error messages when screenshots are posted. Posting screenshots, instead of actual code/error messages, is likely to decrease your chances of getting the help you are looking for in general.

I'd encourage you to ask this kind of question with a minimal REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

FAQ: What's a reproducible example (`reprex`) and how do I create one?

Why reprex? Getting unstuck is hard. Your first step here is usually to create a reprex, or reproducible example. The goal of a reprex is to package your code, and information about your problem so that others can run it and feel your pain. Then, hopefully, folks can more easily provide a solution. What's in a Reproducible Example? Parts of a reproducible example: background information - Describe what you are trying to do. What have you already done? complete set up - include any library() calls and data to reproduce your issue. data for a reprex: Here's a discussion on setting up data for a reprex make it run - include the minimal code required to reproduce your error on the data…