dataframe - Testing for 1-level factors in R -

i have large dataset i'm breaking down smaller data frames based on 1 of factors: state. unfortunately, states, have little data (alaska, example). when run basic model on smaller data frames problems 1 of factors (a gender variable that's 'm' or 'f').

i'm using loop set each state's data frame. planning on building if statement run model if didn't have 1-level factor. don't know how build if.

states_list<-c("ak", ... "wy") # shortened brevity resultslist<-list() j<-1 (i in states_list){     temp_data<-raw[raw$state==i,]     fac <- min(factor(temp_data) # <- part don't have right     if(fac > 1){         model<-lm(y_var~gender,data=temp_data)         resultslist[[j]]<-summary(model)     } else {         print(i)         print("doesn't have enough data points")     }     j=j+1 } 

thanks -w

you don't need use loops , i'd recommend using broom package save models output dataframe, can access value need.

library(dplyr) library(broom)  # example dataframe dt = data.frame(state = c(rep("aa",20), rep("bb",15)),                 gender = c(rep("m",10), rep("f",10), rep("m",15)),                 value = rnorm(35, 100, 5), stringsasfactors = f)  dt %>%   group_by(state) %>%                                # each state   mutate(numuniquegenders = n_distinct(gender)) %>%  # count how many unique values of gender have (and add each row)   filter(numuniquegenders == 2) %>%                  # keep rows belong state both m , f   do(tidy(lm(value ~ gender, data=.))) %>%       # run model , save output dataframe   ungroup                                            # forget grouping   # # tibble: 2 x 6 #     state        term   estimate std.error  statistic      p.value #     <chr>       <chr>      <dbl>     <dbl>      <dbl>        <dbl> #   1    aa (intercept) 99.9643476  1.092526 91.4983355 1.787784e-25 #   2    aa     genderm  0.6236803  1.545066  0.4036594 6.912182e-01 

so, in end you'll dataframe has 2 rows each state. 1 intercept , 1 gender.