purrr

I wonder how to get the list name or group name as a flag when using pipe operation with purrr. for example: I want to use a dynameic parameter of each list name pass to the ggsave function. require(purrr) require(ggplot2) lst=list(a1=data.frame(x=1:10,y=2:11),a2=data.frame(x=1:10,y=-1*2:11)) df=rbind(transform(lst[[1]],id="a1"),transform(lst[[2]],id="a2")) lst %>% map(~ggsave(plot=qplot(data=.,x="x",y="y",geom="line"),file=paste(listname(.),".png"))) df %>% slice_rows("id") %>% by_slice(~ggsave(plot=qplot(data=.,x="x",y="y",geom="line"),file=paste("slicename(.)",".png"))) the slicename(.)

I have a situation where my data frame contains the results of image analysis where the columns are the proportion of a particular class present in the image, such that an example dataframe class_df would look like: id A B C D E F 1 0.20 0.30 0.10 0.15 0.25 0.00 2 0.05 0.10 0.05 0.30 0.10 0.40 3 0.10 0.10 0.10 0.20 0.20 0.30 Each of these classes belongs to a functional group and I want to create new columns where the proportions of each functional group are calculated from the classes. An example mapping class_fg class fg A Z B Z C Z D Y E Y F X and the desired result would be (line added to

I want to recode a bunch of variables with as few function calls as possible. I have one data.frame where I want to recode a number of variables. I create a named list of all variable names and the recoding arguments I want to execute. Here I have no problem using map and dpylr . However, when it comes to recoding I find it much easier using recode from the car package, instead of dpylr 's own recoding function. A side question is whether there is a nice way of doing the same thing with dplyr::recode . As a next step I break the data.frame down into a nested tibble. Here I want to do specific

I want to update a lm -model using the update -function inside a map -call, but this throws the following error: mtcars %>% group_by(cyl) %>% nest() %>% mutate(lm1 = map(data, ~lm(mpg ~ wt, data = .x)), lm2 = map(lm1, ~update(object = .x, formula = .~ . + hp))) Error in mutate_impl(.data, dots) : Evaluation error: cannot coerce class ""lm"" to a data.frame. Can anyone help me with this problem? I am confused about this error, because e.g. this works totally fine: mtcars %>% group_by(cyl) %>% nest() %>% mutate(lm1 = map(data, ~lm(mpg ~ wt, data = .x)), lm2 = map_dbl(lm1, ~coefficients(.x)[1]))

I'm using the mtcars dataset as an example to illustrate my question. I ran linear regression on each cylinder type and put all model result together using map_df. (Code and output below). What I want to do is adding another column named 'cylinder' (4,4,6,6,8,8). How can I do that in map_df? When I add argument .id='cylinder', I only got a column as 1,1,2,2,3,3. Thanks a lot in advance. library(purrr) cyls <- c(4,6,8) map_df(cyls, ~tidy(lm(hp~wt,data=mtcars %>% filter(cyl == .x)))) Using set_names should do it cyls %>% set_names() %>% map_df(., ~tidy(lm(hp~wt,data=mtcars %>% filter(cyl == .x))