I have a dataframe (simplified) that looks like this:
Age, Kodiak, Banana, Banff, Montreal, Fairfax
Age_1, 5, 6 , 7, 9, 2
Age_2, 7, 6, 4, 3, 2
Age_3, 5, 3, 8, 5, 9
I would like my dataframe to look more like this:
Location, Age_1, Age_2, Age_3
Kodiak, 5, 7, 5
Banana, 6, 6, 3
Banff, 7, 4, 8
Montreal, 9, 3, 5
Fairfax, 2, 2, 9
I've looked at the transpose function but I'm a bit confused on how to switch both the columns and rows. I'm very new to R.
There are two ways you can do this. The first one is using t
to just transpose the dataframe as if it would be a matrix (indeed the result of t
is a matrix, not a dataframe).
The other option is to take the tidy data approach and use tidyr::spread
along with tidyr::gather
. Both have similar results although the second one is more versatile as it can be applied partially. Also notice that when using t
the first column (which has type chr
) will become the first row in the new matrix and therefore the entire matrix will be converted into a chr
matrix, while gather
+ spread
keeps the columns numeric.
library(tidyr)
df <- read.table(text = "Age Kodiak Banana Banff Montreal Fairfax
Age_1 5 6 7 9 2
Age_2 7 6 4 3 2
Age_3 5 3 8 5 9", header = T)
t(df)
#> [,1] [,2] [,3]
#> Age "Age_1" "Age_2" "Age_3"
#> Kodiak "5" "7" "5"
#> Banana "6" "6" "3"
#> Banff "7" "4" "8"
#> Montreal "9" "3" "5"
#> Fairfax "2" "2" "9"
df %>%
gather("location", "value", 2:ncol(df)) %>%
spread(Age, value)
#> location Age_1 Age_2 Age_3
#> 1 Banana 6 6 3
#> 2 Banff 7 4 8
#> 3 Fairfax 2 2 9
#> 4 Kodiak 5 7 5
#> 5 Montreal 9 3 5
Use the t() function to transpose dataframes.
For example:
cars <- mtcars[1:5,1:4]
cars
mpg cyl disp hp
Mazda RX4 21.0 6 160 110
Mazda RX4 Wag 21.0 6 160 110
Datsun 710 22.8 4 108 93
Hornet 4 Drive 21.4 6 258 110
Hornet Sportabout 18.7 8 360 175
t(cars)
Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive Hornet Sportabout
mpg 21 21 22.8 21.4 18.7
cyl 6 6 4.0 6.0 8.0
disp 160 160 108.0 258.0 360.0
hp 110 110 93.0 110.0 175.0
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