DSBA 5122: Visual Analytics

# DSBA 5122: Visual Analytics
## Why R/RStudio and tidyverse?
### Ryan Wesslen
### August 26, 2019

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# What is R?

![](../../images/slides/dsba-rintro/r.gif)

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# What is RStudio?

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# 1. Why R / RStudio?

It's free, as in ... free beer?

<p align="center">
<div style="width:80%;height:0;padding-bottom:77%;position:relative;"><iframe src="https://giphy.com/embed/3o6MbkGRfcasxz9rnW" width="80%" height="80%" style="position:absolute" align="middle" frameBorder="0" class="giphy-embed" allowFullScreen></iframe></div><p><a href="https://giphy.com/gifs/season-11-the-simpsons-11x5-3o6MbkGRfcasxz9rnW">via GIPHY</a></p>
</p>

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# 2. Why R / RStudio?

<blockquote class="twitter-tweet tw-align-center" width="50%" data-lang="en"><p lang="en" dir="ltr">well this R=Batman, Python=Superman apparently showed up in a vendor pitch to one of my colleagues. That must make it official. <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/python?src=hash&amp;ref_src=twsrc%5Etfw">#python</a> <a href="https://t.co/pkKGB8EOHj">pic.twitter.com/pkKGB8EOHj</a></p>&mdash; JD Long (@CMastication) <a href="https://twitter.com/CMastication/status/1037486624500854784?ref_src=twsrc%5Etfw">September 5, 2018</a></blockquote>
<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

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# 3. Why R / RStudio?

The [`#rstats`](https://twitter.com/search?q=%23rstats) community (h/t [`@hrbrmstr`](https://rud.is/books/21-recipes/visualizing-a-graph-of-retweet-relationships.html))

```r
library(rtweet)
library(igraph)
library(ggraph)
library(tidyverse)

rt_g <- search_tweets("#rstats", n=3200) %>%    # twitter api
  filter(retweet_count > 0) %>%                 # keep tweets with RT's
  select(screen_name, mentions_screen_name) %>% # select column from/to
  unnest(mentions_screen_name) %>%              # unnest json
  filter(!is.na(mentions_screen_name)) %>%      # include mentions
  graph_from_data_frame()                       # convert to ggraph format
```

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# 3. Why R / RStudio?

The [`#rstats`](https://twitter.com/search?q=%23rstats) community (h/t [`@hrbrmstr`](https://rud.is/books/21-recipes/visualizing-a-graph-of-retweet-relationships.html))

```r
# ggplot inspired networks: ggraph
ggraph(rt_g, layout = 'linear', circular = TRUE) + 
  geom_edge_arc(edge_width=0.125, aes(alpha=..index..)) +
  geom_node_label(aes(label=node_label, size=node_size),
                  label.size=0, fill="#ffffff66", segment.colour="springgreen",
                  color="slateblue", repel=TRUE, fontface="bold") +
  coord_fixed() +
  scale_size_area(trans="sqrt") +
  labs(title="Retweet Relationships", 
       subtitle= subt) +
  theme_graph() +
  theme(legend.position="none")
```

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![](../../images/slides/dsba-rintro/r9.png)

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# And it's just fun!

<blockquote class="twitter-tweet tw-align-center" width="45%" data-conversation="none" data-lang="en"><p lang="en" dir="ltr">I can and it&#39;s HORRIFYING😬😬😬😬 <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a> <a href="https://t.co/aMQiwva7fr">pic.twitter.com/aMQiwva7fr</a></p>&mdash; Tyler Morgan-Wall (@tylermorganwall) <a href="https://twitter.com/tylermorganwall/status/1088978382195437568?ref_src=twsrc%5Etfw">January 26, 2019</a></blockquote>
<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

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<blockquote class="twitter-tweet tw-align-center" data-conversation="none" data-lang="en"><p lang="und" dir="ltr"> <a href="https://t.co/BhS5yaeMbk">pic.twitter.com/BhS5yaeMbk</a></p>&mdash; David Schoppik (@schoppik) <a href="https://twitter.com/schoppik/status/1088983406220886016?ref_src=twsrc%5Etfw">January 26, 2019</a></blockquote>
<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

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# tidyverse

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# What are R packages?

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# What are R packages?

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# What are R packages?

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# What are R packages?

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# How to install and run packages:

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# How to install and run packages:

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# How to install and run packages:

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# How to install and run packages:

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# Data science workflow

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# tidy data

> “Tidy datasets are all alike but every messy dataset is messy in its own way.” – Hadley Wickham

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# tidy data: "pivoting"

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# Core packages: dplyr, ggplot2, piping

<img src="../../images/slides/dsba-rintro/r21.png" width="90%" style="display: block; margin: auto;" />
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# Core packages: dplyr, ggplot2, piping

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# Core packages: dplyr, ggplot2, piping

What are the top 3 most popular years for males born "Taylor"?

```r
# Load the data
library(babynames)
data(babynames)
```

```r
df <- filter(babynames, sex=="M")
df <- filter(df, name=="Taylor") 
df <- arrange(df, desc(n))
df <- select(df, year, n, prop)

head(df, n=3)
```

```
## # A tibble: 3 x 3
##    year     n    prop
##   <dbl> <int>   <dbl>
## 1  1992  8240 0.00393
## 2  1991  7967 0.00376
## 3  1993  7688 0.00372
```
]
.pull-right[

```r
babynames %>%
  filter(sex=="M") %>%
  filter(name=="Taylor") %>%
  arrange(desc(n)) %>%
  select(year, n, prop) %>%
  head(n=3)
```

```
## # A tibble: 3 x 3
##    year     n    prop
##   <dbl> <int>   <dbl>
## 1  1992  8240 0.00393
## 2  1991  7967 0.00376
## 3  1993  7688 0.00372
```
]

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# Happy R programming!