r - dplyr standard evaluation: summarise_ with variable name for summed variable -

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i went through lot of questions similar mine addressed 1 part of problem. using dplyr standard evaluation accommodate variable names. works fine filter_ , group_by_ in pipe. however, summarize cannot have variable name metric i'm summing. example make clear.

library(dplyr) library(lazyeval)  # create data <- data.frame(   x = c(2010, 2010, 2011, 2011, 2011),   y_zm = c(rep(10, 5)),   y_r2 = c(rep(20, 5)))  # define variable names tag <- "2011" metric <- "y" run1 <- "zm" run2 <- "r2"  # working example pipe fixed variable name %>%   filter_(~x == tag) %>%   group_by_(tag) %>%   summarise_(variable_name = interp(~sum(var, na.rm = t),                                      var = as.name(paste0(metric,"_",run1))))  # non-working example of want %>%   filter_(~x == tag) %>%   group_by_(tag) %>%   summarise_(as.name(paste0(metric,"_",run1)) =                 interp(~sum(var, na.rm = t),                        var = as.name(paste0(metric,"_",run1))))

i tried lot of different things involving as.name() or interp() nothing seems work.

after poring on nse vignette awhile , poking @ things, found can use setnames within summarise_ if use .dots argument , put interp work in list.

a %>%     filter_(~x == tag) %>%     group_by_(tag) %>%     summarise_(.dots = setnames(list(interp(~sum(var, na.rm = true),                                             var = as.name(paste0(metric,"_",run1)))),                                                              paste0(metric,"_",run1)))  source: local data frame [1 x 2]    2011 y_zm 1 2011   30

you add rename_ step same thing. see being less ideal, relies on knowing name used in summarise_. if use same name, variable_name, seem viable alternative situations.

a %>%     filter_(~x == tag) %>%     group_by_(tag) %>%     summarise_(variable_name = interp(~sum(var, na.rm = t),                                           var = as.name(paste0(metric,"_",run1)))) %>%     rename_(.dots = setnames("variable_name", paste0(metric,"_",run1)))  source: local data frame [1 x 2]    2011 y_zm 1 2011   30

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