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I imported a table as a database to handle in R. However, I need to do some calculations with just a few columns of this table.
How do I select only these columns for calculations?
2 answers
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There are several ways to select columns from a data.frame in R, let’s use as an example the data.frame mtcars. To find out which columns exist, you can ask to see the names or colnames of data.frame:
names(mtcars)
[1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear" "carb"
To select any of these columns, for example, the column mpg, you can use the $mpg, the brackets [,"mpg"] as if it were a matrix, or double brackets as if it were a list [["mpg"]]:
mtcars$mpg
mtcars[, "mpg"]
mtcars[["mpg"]]
These three mentioned forms return a vector as a result. You can also select a date.frame containing the column mpg (note the difference, you get a data.frame and not an array). For that you will use the simple bracket as if it were a list:
mtcars["mpg"]
Or also use the matrix were, with the argument drop = FALSE.
mtcars[ ,"mpg", drop = FALSE]
If you want to select more than one column, you can use both the simple bracket and the simple bracket as an array.
mtcars[ ,c("mpg", "cyl")] # seleciona duas colunas
mtcars[c("mpg", "cyl")] # seleciona duas colunas
Note that now the matrix form returns a data.frame, since you are selecting more than one column. There are convenience functions to do this too, such as function subset that Rafael mentioned. She will return you a data.frame with the column mpg and not a vector:
subset(mtcars, select = c("mpg","cyl"))
And each data manipulation package also has its own way of selecting columns. For example, the dplyr has the select function, which is very similar to the subset mentioned:
mtcars %>% select(mpg, cyl)
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It would be easier if you included your database (or some part of it) so that we could work on it. Take a look at the function dput to that end. It would also be nice if you included the code you developed / tried to develop.
As to your doubt, the functions subset, of the very basis of R, or the function select, package dplyr, should assist you.
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