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DoSS Toolkit
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Table of contents
1
Preface
Hello World!
2
Introduction
3
Getting and setting up RStudio
4
Getting to know what is what
5
Hello World!
6
Hello World, again!
7
Hello World, yet again!
8
The R community
Operating in an error prone world
9
Introduction
10
Getting help is normal!
11
Using Google and Stack Overflow
12
Even more on Stack Overflow
13
When your code doesn’t work
14
Making reproducible examples
15
How to make the most of R’s cryptic error messages
Holding the chaos at bay
16
Introduction
17
R Projects and working directory
18
Folder set-up
19
Writing comments
20
Installing packages
21
Install from GitHub
22
Calling packages
23
How to update packages
24
Read CSVs
25
Reading tables dta and other data types
Hand me my plyrs
26
Introduction
27
What is the tidyverse?
28
The pipe
29
select
30
filter
31
group and ungroup
32
summarise
33
arrange
34
mutate
35
Pivoting data from long to wide and vice versa
36
rename
37
Counting
38
slice
39
Representations of data
40
length, rows, columns and dimensions
Totally addicted to base
41
Introduction
42
mean, median, sd, lm, and summary
43
Generalized linear models with glm
44
Mixed-effect linear models with lme4
45
function
46
for and while
47
if, if else and case when
48
c, seq, seq along, and rep
49
hist, plot and boxplot
50
apply, sapply, and lapply
51
File creation and manipulation
52
sum round etc
53
Investigating and playing with data
54
row and column names
55
floor(), ceiling(), round(), and abs()
He was a d8er boi
56
Introduction
57
head, tail, glimpse and summary
58
paste, paste0, glue and stringr
59
names, rbind and cbind
60
Joins
61
Looking for missing data
62
setseed, runif, rnorm, and sample
63
Simulating datasets for regression
64
Conditional mutating and summarising
65
Tidying up datasets
66
pull, pluck and unnest
67
forcats and factors
68
More on strings
69
Working with dates
70
Regular expressions
71
janitor
72
tidyr package
To ggplot or not to ggplot
73
Introduction
74
Overview of ggplot2
75
Bar charts
76
Histograms
77
Scatter plots
78
Various useful options
79
Saving graphs
80
gganimate
81
Some other geom
82
some geom
R Marky Markdown and the Funky Docs
83
Introduction
84
Introduction to R Markdown
85
Top Matter: Title, Date, Author, Abstract
86
Tables: kable, kableextra, and gt
87
Multiple plots with patchwork
88
References and Bibtex
89
PDF outputs
90
here and filepaths
Git outta here
91
Introduction
92
What is version control and GitHub?
93
Git: pull, status, add, commit, push
94
Branches in GitHub
95
Dealing with conflicts
96
Putting (G)it All together in RStudio
97
Projects issues
Indistinguishable from magic
98
Introduction
99
Iteration
100
Coding style
101
Static maps using ggmap
102
Writing R Packages
103
Writing R Packages II
104
Getting started with Blogdown
105
postcards
106
Getting started with Shiny
107
Writing a CV
108
tidymodels
109
leaflet
110
diagrammer
Specialised topics
111
Overview
112
Stan
113
devtools
114
usethis
115
testthat
116
Tidytext and NLP
117
OOP
118
Functional programming
119
SQL
120
Python
121
C++
View book source
116
Tidytext and NLP
Written by ADD NAME and last updated on ADD DATE.
116.1
Introduction
116.2
Exercises
116.2.1
Question 1
116.2.2
Question 2
116.2.3
Question 3
116.2.4
Question 4
116.2.5
Question 5
116.2.6
Question 6
116.2.7
Question 7
116.2.8
Question 8
116.2.9
Question 9
116.2.10
Question 10
115
testthat
117
OOP
On this page
116
Tidytext and NLP
116.1
Introduction
116.2
Exercises
116.2.1
Question 1
116.2.2
Question 2
116.2.3
Question 3
116.2.4
Question 4
116.2.5
Question 5
116.2.6
Question 6
116.2.7
Question 7
116.2.8
Question 8
116.2.9
Question 9
116.2.10
Question 10
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