Count specific characters from column associated with dual categories of other column. Do it iteratively based on frequency bins

Question

I have a huge dataframe df1, whose oversimplified version consists of 3 columns, \"Words\", \"Frequency\" and \"Letters\":

Words           Frequency   Letter         


        

Answer 1

You can use cut to bin Frequency, substr to clean Letters, and tidyr::separate_rows to unnest Word. Aggregate with dplyr::count, and you're set:

library(tidyverse)

df %>% separate_rows(Words) %>% 
    count(Words, 
          Letters = substr(Letters, 1, 1),    # use regex if more than one letter
          Frequency = cut(Frequency, breaks = seq(0, 1, .25)))

## Source: local data frame [11 x 4]
## Groups: Frequency, Words [?]
## 
##     Frequency  Words Letters     n
##              
## 1    (0,0.25] flower       a     1
## 2    (0,0.25] flower       b     1
## 3    (0,0.25] planet       a     1
## 4    (0,0.25]   tree       a     1
## 5  (0.25,0.5] planet       c     1
## 6  (0.25,0.5]   tree       c     1
## 7  (0.5,0.75] flower       b     1
## 8  (0.5,0.75] planet       b     1
## 9  (0.5,0.75]   tree       a     1
## 10   (0.75,1] planet       b     1
## 11   (0.75,1]   tree       a     1