R Markdown tips and GPS data visualization

# R Markdown tips and GPS data visualization
## R workshop
### Issac Lee
### 2021-02-26

---

# The University of Iowa

![](https://upload.wikimedia.org/wikipedia/en/thumb/4/49/University_of_Iowa_seal.svg/225px-University_of_Iowa_seal.svg.png)

## Statistics and Actuarial Science

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# Why RMarkdown?

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<iframe width="1300" height="600" src="https://www.youtube.com/embed/s3JldKoA0zw?version=3&rel=0" frameborder="0" allow="accelerometer; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
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# We use them in our daily life..

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# **R**Markdown packages

* [**Bookdown**](https://bookdown.org/yihui/bookdown/) - pdf, epub, or html book

* Writing a gitbook like [Prof. Tierney](http://homepage.stat.uiowa.edu/~luke/classes/STAT7400-2021/_book/index.html)

* [**Blogdown**](https://bookdown.org/yihui/blogdown/) - Static website builder Hugo wrapper

* Personal website like [me](theissaclee.com)

* Theme: Academy, Apero (is developing by Rstudio)

* [**Pagedown**](https://pagedown.rbind.io/): single html document generation. a.k.a. goodbye LaTeX?

]
.pull-right[

* [**Distill**](https://rstudio.github.io/distill/): if you really like minimalizm.

* Concept is developed by Google, package developed by Rstudio.
  * Suitible for academic writing

* [**Xaringan**](https://slides.yihui.org/xaringan/#1): Presentation

*  Like the one you're looking at.

* `xaringan themer` - Easy theme for `xaringan` 
  
* [**Thesisdown**](https://github.com/ismayc/thesisdown): Thesis with Rmd.

]
---

# Use them wisely!

# Useful 3 tips!

---
# Use **R**md as **Py**md!

* R package `reticulate` allows us to use Rmarkdown for handling `python` code.

* https://rstudio.github.io/reticulate/index.html

* Use `python` code chunk in your `.Rmd` file!

````markdown
```{r}
library(reticulate)
```

```{python}
import numpy
import pandas

```
````

]
.pull-right[
![](https://rstudio.github.io/reticulate/images/reticulated_python.png)
]

---
# Shortcuts!

`Alt` + `Shift` + `K` shows all shortcuts! However, some are USEFUL, some are **NOT**!

### Useful **Shortcuts!**

add `%>%` operator: `Ctrl` + `Shift` + `m`

add `<-` operator: `Alt` + -

add cursors! : `Ctrl` + `Alt` + down or up

search functions: `Ctrl` + .

search commands: `Ctrl` + `Shift` + `p`

]
.pull-right[

Run current chunk: `Ctrl` + `Alt` + `c`

R code re-formatting: `Ctrl` + `Shift` + `a`

Copy current below: `Shift` + `Alt` + down

Insert `R` code chunk: `Ctrl` + `Alt` + i

]

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# However, so many syntax tho..

---

# Including images

Should I type all of these to insert just a picture?

````markdown
```{r chunkname, 
            fig.cap="picture caption",
            fig.align="center",
            out.width="50%"}
knitr::include_graphics("question.png")
```
````
]

<div class="figure" style="text-align: center">
<img src="./question.svg" alt="picture caption" width="50%" />
<p class="caption">picture caption</p>
</div>

]
---
# Tables

Should I memorize all these options for generating table?

````markdown
```{r}
knitr::kable(head(as_tibble(mtcars[,1:3]), 5), 
             position = "!h",
             col.names = c("col1", "col2", "col3"),
             caption = "caption", 
             align = "lrc", booktab = TRUE)
```
````
]

Table: caption

|col1 | col2| col3 |
|:----|----:|:----:|
|21.0 |    6| 160  |
|21.0 |    6| 160  |
|22.8 |    4| 108  |
|21.4 |    6| 258  |
|18.7 |    8| 360  |

]

---
# Snippet will **save** you

**Snippet** save your time, almost 1 year during your whole life, no joke.

.pull-left[
### What the hack is snippet
* **Text macros** that are used for quickly inserting common snippets of code

* `Tools` > `Global option` > `Code` > `Snippet`

* Some people know there are *code snippet* in Rstudio

]
.pull-right[

<div class="figure" style="text-align: center">
<img src="./snippet.jpg" alt="Available snippets languages" width="80%" />
<p class="caption">Available snippets languages</p>
</div>

]

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# Live demo

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# GPS data visualization

---
# I Know How You Drive

* `R` package, `ikhyd`, is for driving behavior analysis, but it has a **GPS visualization** function `track_vis()`.

```r
# devtools::install_github("issactoast/ikhyd")
library(ikhyd)
```

```
## To cite this package use citation('ikhyd') 
## 
##  Text citation: 
## 
##  Issac Lee (2020). ikhyd : I Know How You Drive - Collection of R functions to make telematics analysis easier.
##  R package version 0.1.0. URL https://github.com/issactoast/ikhyd
```

* Need to register Google API

```r
google_api <- keyring::key_get("GOOGLEMAP_API")
```

---
## How to access to data set

`ikhyd` package contains seven telematics files; One of them is sample trip.

1. Sample route telematics: `sample_trip.csv`

1. Test route with OBD information: with and w/o OBD

1. 4 Driving telematics files

]
.pull-right[

* File path in your local computer

```r
system.file("extdata", "sample_trip.csv", package = "ikhyd")
```

```
## [1] "C:/R/R-4.0.3/library/ikhyd/extdata/sample_trip.csv"
```

]

---
# Load trip data

When you have a path of telematics data, you can load the data using `get_trip()` with `data_option` arguments as follows:

```r
# telematics file path
sample_trip_path <- system.file("extdata", "sample_trip.csv", package = "ikhyd")

# load data
sample_trip <- load_telematic_data(sample_trip_path, all_in_one = TRUE)
summary(sample_trip)
```

```
##            Length Class      Mode
## gps_data   6      data.frame list
## acc_data   4      data.frame list
## lacc_data  4      data.frame list
## gyro_data  4      data.frame list
## angle_data 4      data.frame list
## speed_data 3      data.frame list
```

---
# Visualization GPS

The snippet of `gps_data` for the sample trip looks as follows:

```r
gps_data <- sample_trip$gps_data
head(gps_data)
```

```
##    time         x        y        z accuracy_horiz accuracy_vert
## 1 0.000 -91.53799 41.66253 197.2922              5             4
## 2 0.038 -91.53799 41.66253 197.2922              5             4
## 3 0.079 -91.53799 41.66253 197.2821              5             4
## 4 0.120 -91.53799 41.66253 197.2821              5             4
## 5 0.153 -91.53799 41.66253 197.2821              5             4
## 6 0.194 -91.53799 41.66253 197.2821              5             4
```

---
# Google map loading

```r
library(ggmap)
register_google(key = google_api)
center_vec <- colMeans(gps_data[,2:3])
map_obj <- get_googlemap(center = as.numeric(center_vec), maptype = "hybrid",
                       zoom = 17)
ggmap(map_obj)
```

---
# Track was around IMU and Pappajohn Business Building

```r
p <- ggmap(map_obj) + 
  geom_path(data = gps_data, aes(x = x, y = y),
            size = 0.7, color = "yellow") +
  geom_point(data = gps_data, aes(x, y), col = "red", size = 3)
p
```

---
# Let's take a look at the speed!

```r
plot_speed(sample_trip$speed_data, tripname = "the sample trip")
```

<div class="figure" style="text-align: center">
<img src="presentation_files/figure-html/gpsspeed-1.png" alt="The result of `plot_speed()` code."  />
<p class="caption">The result of `plot_speed()` code.</p>
</div>

---
# Can we add this to the map?

```r
library(gganimate)
p <- p + transition_reveal(time) +
    ease_aes('linear')
p
```

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# Thanks!