February 2018
Beginner to intermediate
258 pages
5h 47m
English
Content preview from R Deep Learning Projects
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Working with tidy text
For this, we will use the tidytext package. This package is built on the philosophy of tidy data, introduced by Hadley Wickham in his 2014 paper (https://www.jstatsoft.org/article/view/v059i10). A dataset is tidy if the following three conditions are satisfied:
- Each variable is a column
- Each observation is a row
- Each type of observational unit is a table
The tidytext package helps us turn our text into tidy form, by putting one token per row. Let's start by loading dplyr and tidytext. If you don't have tidytext, install it first using install.packages("tidytext").
Load the packages and let's transform our text into a data frame:
library(tidytext)library(dplyr)text_df <- data_frame(line = 1:4, text = text)
The unnest_tokens ...
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