dplyr Use Cases: Non-Interactive Mode
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The current release of dplyr (v 0.4.1) offers lot more flexibility regarding usage of important verbs in non-interactive mode. In this post, I’m exploring different possible use-cases.
- group_by_, select_, rename_:
- filter_:
- mutate_, transmute_, summarise_:
- joins:
For 2 table verbs, there’s no *_join_ function and we don’t need one for general purposes. We can just pass a named vector to by argument. setNames function comes in handy while doing this.
The R Code for the above mentioned use cases is shown below and can also be found on this GitHub Gist.
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# using dplyr finctions in non-interactive mode | |
# examples | |
library(plyr) | |
library(dplyr) | |
d1 = data_frame(x = seq(1,20),y = rep(1:10,2),z = rep(1:5,4)) | |
head(d1) | |
#### single table verbs #### | |
# group_by | |
group_by_fn <- function(d_in,gp_vec){ | |
d_out = d_in %>% | |
group_by_(.dots = gp_vec) | |
} | |
gp_vec = c("y","z") | |
d1_gp_by_out = group_by_fn(d1,gp_vec) | |
head(d1_gp_by_out) | |
# select/rename (haven't included drop variables case) | |
select_fn <- function(d_in,sel_vec){ | |
d_out = d_in %>% | |
select_(.dots = sel_vec) | |
} | |
sel_vec = c("x","y") | |
d1_select_out = select_fn(d1,sel_vec) | |
head(d1_select_out) | |
# filter | |
filter_fn <- function(d_in,filter_crit){ | |
d_out = d_in %>% | |
filter_(filter_crit) | |
} | |
y_vec = 6:8 | |
filter_crit = interp(~ filter_var %in% y_vec,filter_var = as.name("y")) | |
d1_filter_out = filter_fn(d1,filter_crit) | |
head(d1_filter_out) | |
z_vec = 1:2 | |
filter_crit2 = interp(~ filter_var1 %in% y_vec & filter_var2 %in% z_vec,.values = list(filter_var1 = as.name("y"), | |
filter_var2 = as.name("z"))) | |
d1_filter2_out = filter_fn(d1,filter_crit2) | |
head(d1_filter2_out) | |
# mutate, transmute, summarise | |
mutate_fn <- function(d_in,op_ls,var_vec){ | |
d_out = d_in %>% | |
mutate_(.dots = setNames(op_ls,var_vec)) | |
} | |
var1_rng = 3:5 | |
op_ls = list(interp(~f(var1,var2), .values = list(f = as.name("*"), | |
var1 = as.name("x"), | |
var2 = as.name("y"))), | |
interp(~f(var1 %in% var1_rng,var2,var3),.values= list(f = as.name("ifelse"), | |
var1 = as.name("x"), | |
var2 = as.name("y"), | |
var3 = as.name("z")))) | |
var_vec = c("yy","zz") | |
d1_mutate_out = mutate_fn(d1, op_ls, var_vec) | |
head(d1_mutate_out) | |
var_ls = list("yy","zz") | |
d1_mutate_out1 = mutate_fn(d1, op_ls, var_ls) | |
head(d1_mutate_out1) | |
#### two table verbs #### | |
# joins | |
d2 = data_frame(xx = seq(1,20),yy = rep(1:10,2),zz = rep(1:2,10)) | |
join_fn <-function(d_in1,d_in2,var_vec1,var_vec2){ | |
d_out = d_in1 %>% | |
left_join(d_in2,setNames(var_vec2,var_vec1)) | |
} | |
var_vec1 = c("x","y") | |
var_vec2 = c("xx","yy") | |
d_join_out = join_fn(d1,d2,var_vec1,var_vec2) | |
head(d_join_out) | |
# everything combined (essentially, power of %>%) | |
d_combined_out = d1 %>% | |
filter_fn(filter_crit) %>% | |
group_by_fn(gp_vec) %>% | |
mutate_fn(op_ls,var_vec) %>% | |
select_fn(c("x","y","z")) %>% | |
join_fn(.,d2,var_vec1,var_vec2) | |
head(d_combined_out) | |
# sources: | |
# http://cran.r-project.org/web/packages/dplyr/vignettes/nse.html | |
# http://stackoverflow.com/questions/28125816/r-standard-evalation-for-join-dplyr |
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