I have the following generic DataFrame with 100 rows:
using DataFrames
df = DataFrame(X=linspace(0.0, 2π, 100))
head(df)
X
1 0.0
2 1.0471975511965976
3 2.0943951023931953
4 3.141592653589793
How to, for example, compute the sine of the values of the column X and insert in a new column SinX ?
To include the new column, simply assign the value (s) to this new column.
Example:
df[:SinX] = sin(df[:X])
head(df)
X SinX
1 0.0 0.0
2 0.06346651825433926 0.0634239196565645
3 0.12693303650867852 0.12659245357374926
4 0.19039955476301776 0.1892512443604102
5 0.25386607301735703 0.2511479871810792
6 0.3173325912716963 0.31203344569848707
I think using the map function is more efficient because of composition, so you do not have to go through DataFrame twice, one initializing and the other assigning a functional value.
df[:error] = map((x,y) -> x-y , df[:A], df[:B])
Although specifically in your case it leads only to more code, I believe it leads to a better understanding.
df[:SinX] = map((x) -> sin(x), df[:X])
This means that for each entry of df[:X] , map to a new entry by applying the function sin(x)