intro2R.knit

class: center, bottom
background-image: url("start.jpg")
<span style="font-size: 50pt; ">See What You R</span> <br><br>
<span style="font-size: 20pt; ">Budhaditya Basu</span>

---
class: center, middle

# What is the purpose of this Hands-on session?

To generate following plots

To get a hang of R codes

To build a R community within RGCB

---

class: center, middle
background-image: url("stack.jpg")
background-size: contain

---

---

class: center, middle
background-image: url("PlotsCombined.jpg")
background-size: contain

---

class: center, middle
background-image: url("R_course.jpg")
background-size: contain

---

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:steelblue;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

# R is a language and environment <br>generally used for

Data Analysis

Data Visualization

Statistics

Making professional CV/Resume

Visual Blogs

Professional Website

Academic Paper/Book writing

And many more..

---

# What is R for a Biologist?

- RNA-Seq, ChIP-Seq etc.
- Single-cell RNA-Seq
- Proteomics study

- Better representation of data
- Better insights of complex data
- Interesting data visualization

- An open source platform for R packages related to biological data analysis

---

<span style="font-size: 90pt; color: steelblue ">1.  Install R </span>
--

Install **R** from R project homepage:
https://cran.r-project.org/

You are recommended to use the [RStudio IDE](https://www.rstudio.com/products/rstudio/)

---

# Rstudio has four main panels

![](r_panels.png)

---

# Rstudio has four main panels

- .dark-pink[Scripts] are the records of codes (like a recipe)

- .dark-pink[Console] is the place where a code is executed (cooking)

- .dark-pink[Environment] is like a kitchen where ingredients (data) and finished dishes (output) can be found.

- .dark-pink[Files] are the ingredients and .dark-pink[packages] are like tools (saucepan) in a kitchen.

---

# How to execute a code?

- To execute a line of code where cursor currently resides, press <br> **Ctrl + Enter** or use **Run** toolbar button

- Multiple lines of code can be selected and executed by similar way.

---

Before running any code, we need to set the working directory.

Go to .dark-blue[Session > Set Working Directory > Choose Directory]

---

Alternatively, we can set the working directory by using <br> `setwd("path to directory")`

---
class: center, middle
# Get Started

Open R Studio

---

#Variable Assignment

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
num <- 2
```

- `num` holds the value 2

]

- Here, `num` is a <span style="color: deeppink;"> "variable"</span>

- <- is <span style="color: deeppink;">"assignment operator"</span>

]

Now, if we execute the variable `num`, it will return the value 2

]

```r
num
```

```
## [1] 2
```

]

--
.pull-left[

```r
150 -> fruits

fruits
```

```
## [1] 150
```
]

--
.pull-right[

- Both operators are same.

- Simply "left-form" and "right-form"

]

---

#Variable types in R

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- <span style="color: blue;">int</span> for integers.

- <span style="color: blue;">dbl</span> for doubles or real numbers.

- <span style="color: blue;">chr</span> for character

- <span style="color: blue;">dttm</span> for date-time

- <span style="color: blue;">lgl</span> for logical vectors like TRUE or FALSE

- <span style="color: blue;">fct</span> for categorical variables

---

#Convention for naming variables

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
my_name <- "Budhaditya"

my_weight <- 66.678

print(my_name)
```

```
## [1] "Budhaditya"
```

]

--
.pull-right[

- It cannot include <span style="color: deeppink;">space</span>. <br><br>
  e.g. <span style="color: blue;">"my name"</span> is not valid. But <br><br><span style="color: blue;">"my_name"</span> or <span style="color: blue;">"my.name"</span> is perfect
 ]

--
.pull-left[

```r
"cat" == "cat"
```

```
## [1] TRUE
```

```r
"cat" == "CAT"
```

```
## [1] FALSE
```
]

--
.pull-right[
<br><br><br><br>
- Variable is <span style="color: deeppink;">case sensitive</span>.

]

---

#Vector

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:20px;width:20px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[

```r
my_value <- c(1, 3, 9, 27)

my_value
```

```
## [1]  1  3  9 27
```
]

--
.pull-right[
- Variable that stores multiple values are <span style="color: deeppink;">"Vector"</span>

- c ( ) is called <span style="color: deeppink;">"Combine function"</span>
]
--

```r
my_value[3]
```

```
## [1] 9
```

]

--
.pull-right[

- Square brackets [] identify the position within a vector **(index)**

- This index can be used to extract relevant values

]

```r
my_value[3] <- "gene"

my_value
```

```
## [1] "1"    "3"    "gene" "27"
```

]
--

- **Index** can be used to modify the vector
]

---

class: center, middle
<span style="font-size: 90pt; color: steelblue; ">2.  Packages </span>

---
#Installing and Loading of Packages

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- Packages extend the capabilities of <span style="font-size: 15pt; color: deeppink; "> R </span>

- <span style="font-size: 15pt; color: deeppink; "> "Installing" </span> is downloading the package into your computer.

- <span style="font-size: 15pt; color: deeppink; "> "Loading" </span> is telling R to use it.

<br>
--

- ...you need to <span style="font-size: 15pt; color: deeppink; "> "install" </span> a package only once.

- ...but you have to <span style="font-size: 15pt; color: deeppink; "> "load" </span> it every time.

<br>
--

- <span style="font-size: 15pt; color: deeppink; "> "Install" </span> using `install.packages()`

- <span style="font-size: 15pt; color: deeppink; "> "Load" </span> using `library()`

---

class: center, middle
background-image: url("thoughts.jpg")
background-size: cover

#...Time for break

---

#R Packages

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- "Packages" are collection of functions and data sets

- <span style="font-size: 15pt; color: deeppink; "> "dplyr" </span> is used for data manipulation.

- <span style="font-size: 15pt; color: deeppink; "> "ggplot2" </span> for data visualization.

- <span style="font-size: 15pt; color: deeppink; "> "tidyverse" </span> is a bundle of 8 packages together. <br>

<img src="tidyverse_packages.png" width="60%" height="50%" style="display: block; margin: auto;" />
---

#R function

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- <span style="font-size: 15pt; color: deeppink; "> "Functions" </span> are meant for doing calculation.

--
.pull-left[

```r
sqrt(25)
```

```
## [1] 5
```

```r
log2(8)
```

```
## [1] 3
```

```r
round(x = 3.141592, digits = 2)
```

```
## [1] 3.14
```

]
--
<br><br>
.pull-right[
- `sqrt()`, `log2()` or `round()` are the examples of <span style="font-size: 15pt; color: deeppink; "> functions </span><br><br>

- (<span style="font-size: 15pt; color: seagreen; "> "Arguments" </span>) are kept within the parentheses.<br><br> 
- If multiple arguments present, that must be separated by comma.
]

---

class: inverse, center, middle
background-image: url('data.jpg')
<span style="font-size: 90pt; color: white; ">3.  Data Frames </span>

---
#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

`install.packages("palmerpenguins")`

```r
library(palmerpenguins)

*df <- penguins
```

<br><br>
- `penguins` data set is assigned to the variable named `df`

]
---
#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- `head()` function shows first few rows of the data frame `df`

```r
head(df)
```

---

#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]
--

```r
df[1, 3]
```

```
## # A tibble: 1 x 1
##   bill_length_mm
##            <dbl>
## 1           39.1
```

]

- Give me the value stored in <span style="font-size: 15pt; color: deeppink; "> first row, third column</span> of `df`
]

---

#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- Give me the values of <span style="font-size: 15pt; color: deeppink; "> first row</span> of `df` (all columns)

```r
df[1,]
```

---

#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
df[,3]
```

```
## # A tibble: 344 x 1
##    bill_length_mm
##             <dbl>
##  1           39.1
##  2           39.5
##  3           40.3
##  4           NA  
##  5           36.7
##  6           39.3
##  7           38.9
##  8           39.2
##  9           34.1
## 10           42  
## # i 334 more rows
```
]
--

.pull-right[
- Give me the values of <span style="font-size: 15pt; color: deeppink; "> third column </span> of `df` (all rows)
]

---

#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[

```r
df[1:2, 2:4]
```

```
## # A tibble: 2 x 3
##   island    bill_length_mm bill_depth_mm
##   <fct>              <dbl>         <dbl>
## 1 Torgersen           39.1          18.7
## 2 Torgersen           39.5          17.4
```

]

- Give me the values of <span style="font-size: 15pt; color: deeppink; "> rows 1-2 and columns 2-4 </span> of `df` (all rows)
]

---

#Data Frames

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]
--
.pull-left[

```r
df[, "island"]
```

```
## # A tibble: 344 x 1
##    island   
##    <fct>    
##  1 Torgersen
##  2 Torgersen
##  3 Torgersen
##  4 Torgersen
##  5 Torgersen
##  6 Torgersen
##  7 Torgersen
##  8 Torgersen
##  9 Torgersen
## 10 Torgersen
## # i 334 more rows
```

]

- Prints the data stored in "island" column

]
---
# Matrix

--
-  In a data frame the columns contain different types of data, but in a matrix all the elements are the same type of data.

- A matrix in R is like a mathematical matrix, containing all the same type of thing (usually numbers).

- For example when we work with RNA-Seq data we use a matrix of read counts. So it will be worth our time to learn to use matrices as well.
--

```r
is.data.frame(mtcars)
```

```
## [1] TRUE
```

```r
is.matrix(mtcars)
```

```
## [1] FALSE
```

---
# Matrix

### Convert Data frame to matrix

```r
mat <- as.matrix(mtcars)
```

### Check the matrix

```r
is.matrix(mat)
```

```
## [1] TRUE
```

---

# Generic X-Y Plotting

```r
barplot(c(2,5,7,10))
```

![](intro2R_files/figure-html/unnamed-chunk-43-1.png)

---

# Generic X-Y Plotting

```r
library(RColorBrewer)
```

```
## Warning: package 'RColorBrewer' was built under R version 4.1.3
```

```r
barplot(c(2,5,7,10), 
        col = brewer.pal(n = 4, name = "RdBu"))
```

![](intro2R_files/figure-html/unnamed-chunk-44-1.png)

--
- To know more about `RColorBrewer` use `help("RColorBrewer")`

---
# Generic X-Y Plotting

```r
head(ToothGrowth)
```

```
##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
## 5  6.4   VC  0.5
## 6 10.0   VC  0.5
```

--
-  The length of the odontoblasts (teeth) in each of 10 guinea pigs at three Vitamin C dosage levels (0.5, 1, and 2 mg) with two delivery methods (orange juice or ascorbic acid (Vitamin C)).

---

# Generic X-Y Plotting

```r
boxplot(len ~ dose, 
        data = ToothGrowth, 
        frame = FALSE,
        col = brewer.pal(n = 3, 
                         name = "Blues"))
```

![](intro2R_files/figure-html/unnamed-chunk-46-1.png)

---

# Generic X-Y Plotting

```r
boxplot(len ~ dose, 
        data = ToothGrowth, 
        frame = FALSE,
        col = c("#999999", 
                "#E69F00", "#56B4E9"))
```

![](intro2R_files/figure-html/unnamed-chunk-47-1.png)

---
# Generic X-Y Plotting

```r
dat <- data.frame(group = c("Male", "Female", "Child"),
  value = c(25, 25, 50))
```

```r
pie(dat$value, labels = dat$group, radius = 1,
    #$ sign used to select a column
    col = brewer.pal(n = 3, name = "PiYG")) 
```

![](intro2R_files/figure-html/unnamed-chunk-49-1.png)

---
# Generic X-Y Plotting

```r
hist(mtcars$mpg, col = "steelblue", xlab = "", 
     main = "Histogram")
```

![](intro2R_files/figure-html/unnamed-chunk-50-1.png)

---
# Generic X-Y Plotting

```r
# Compute the density data
dens <- density(mtcars$mpg)
# plot density
plot(dens, frame = FALSE, col = "steelblue", 
     main = "Density plot of mpg")
```

![](intro2R_files/figure-html/unnamed-chunk-51-1.png)

---
# Generic X-Y Plotting

```r
# Create some variables
x <- 1:10
y1 <- x*x
y2  <- 2*y1
```
---
# Generic X-Y Plotting

```r
# Create a first line
#p= points, l= lines, b = both, 
plot(x, y1, type = "b", frame = FALSE, pch = 19, 
     col = "red", xlab = "x", ylab = "y")
# Add a second line
lines(x, y2, pch = 18, col = "blue", 
      type = "b", lty = 2)#lty=1; solid line, lty=2;dashed line
# Add a legend to the plot
legend("topleft", legend=c("Line 1", "Line 2"),
       col=c("red", "blue"), lty = 1:2, cex=0.8)
```

![](intro2R_files/figure-html/unnamed-chunk-53-1.png)
---
# Generic X-Y Plotting

```r
wt <- mtcars$wt # weight in pounds
mpg <- mtcars$mpg #miles per gallon
```

```r
plot(wt, mpg, main = "Scatter plot",
     xlab = "X axis title", ylab = "Y axis title",
     pch = 19, frame = F)
```

![](intro2R_files/figure-html/unnamed-chunk-55-1.png)
---
# Generic X-Y Plotting

- We have so far created the following plots

![](intro2R_files/figure-html/unnamed-chunk-56-1.png)

---
# How to save a plot?

- To save the plot as .tiff file, use

```r
tiff(filename = "Boxplot.tiff",
     height = 4, width = 6, units = "in", res = 300)
boxplot(len ~ dose, data = ToothGrowth, 
        frame = FALSE,
        col = c("#999999", "#E69F00", "#56B4E9"))
dev.off()
```

- To save the plot as .jpg file, use

```r
jpeg(filename = "Boxplot.jpg",
     height = 4, width = 6, units = "in", res = 300)
boxplot(len ~ dose, data = ToothGrowth, 
        frame = FALSE,
        col = c("#999999", "#E69F00", "#56B4E9"))
dev.off()
```

---

#Pipe &nbsp;&nbsp;&nbsp;%>%

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- We <span style="font-size: 15pt; color: deeppink; "> "pipe" </span> our data through several functions.

- The data set flows through the cascade of operations

<img src="pipe.jpg" width="70%" style="display: block; margin: auto;" />
]

```r
library(tidyverse)

df %>%
  group_by(species) %>%
  drop_na()%>%
  summarize(mean(bill_length_mm))
```

```
## # A tibble: 3 x 2
##   species   `mean(bill_length_mm)`
##   <fct>                      <dbl>
## 1 Adelie                      38.8
## 2 Chinstrap                   48.8
## 3 Gentoo                      47.6
```
]

---

class: inverse, center, middle
background-image: url('tidy.jpg')
<span style="font-size: 90pt; color: white; ">4.  Tidying Data </span>

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()` <span style="color: deeppink; "> << </span>

- `select()` function selects only user defined columns from a data frame

<br><br>
<img src="dplyr_logo.png" width="35%" style="display: block; margin: auto;" />
]

```r
iris %>%
* select(Sepal.Length,
*        Petal.Width)%>%
  head()
```

```
##   Sepal.Length Petal.Width
## 1          5.1         0.2
## 2          4.9         0.2
## 3          4.7         0.2
## 4          4.6         0.2
## 5          5.0         0.2
## 6          5.4         0.4
```

]

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()` <span style="color: deeppink; "> << </span>

- `filter()` function helps to subset a data frame that satisfy a user defined condition.
<br><br>
<img src="filter.jpg" width="100%" height="100%" style="display: block; margin: auto;" />
]

```r
iris %>%
  select(Sepal.Length, 
         Petal.Width)%>%
* filter(Petal.Width > 2.3)
```

```
##   Sepal.Length Petal.Width
## 1          6.3         2.5
## 2          7.2         2.5
## 3          5.8         2.4
## 4          6.3         2.4
## 5          6.7         2.4
## 6          6.7         2.5
```

]

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange()` <span style="color: deeppink; "> << </span>
<br><br><br>
- It arranges low to high
]

```r
iris %>%
  select(Sepal.Length, 
         Petal.Width)%>%
  filter(Petal.Width > 2.3)%>%
* arrange(Petal.Width)
```

```
##   Sepal.Length Petal.Width
## 1          5.8         2.4
## 2          6.3         2.4
## 3          6.7         2.4
## 4          6.3         2.5
## 5          7.2         2.5
## 6          6.7         2.5
```

]

---
#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange(desc())` <span style="color: deeppink; "> << </span>
<br><br><br>
- It arranges high to low
]

```r
iris %>%
  select(Sepal.Length, 
         Petal.Width)%>%
  filter(Petal.Width > 2.3)%>%
* arrange(desc(Petal.Width))
```

```
##   Sepal.Length Petal.Width
## 1          6.3         2.5
## 2          7.2         2.5
## 3          6.7         2.5
## 4          5.8         2.4
## 5          6.3         2.4
## 6          6.7         2.4
```

]
---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange(desc())` 
- `rename()` <span style="color: deeppink; "> << </span>
<br><br><br>
- It renames the column name
]

```r
iris %>%
  select(Sepal.Length, Petal.Width)%>%
  filter(Petal.Width > 2.3)%>%
  arrange(desc(Petal.Width))%>%
* rename(petal_width = Petal.Width,
*        sepal_length = Sepal.Length)
```

```
##   sepal_length petal_width
## 1          6.3         2.5
## 2          7.2         2.5
## 3          6.7         2.5
## 4          5.8         2.4
## 5          6.3         2.4
## 6          6.7         2.4
```

]

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange(desc())` 
- `rename()` 
- `mutate()` <span style="color: deeppink; "> << </span>
<br><br><br>
- It creates one or more column
]

```r
iris %>%
  select(Petal.Length, Petal.Width)%>%
  filter(Petal.Width > 2.3)%>%
  arrange(desc(Petal.Width))%>%
  rename(petal_width = Petal.Width,  
         petal_length = Petal.Length)%>%
* mutate(petal = petal_width + petal_length)
```

```
##   petal_length petal_width petal
## 1          6.0         2.5   8.5
## 2          6.1         2.5   8.6
## 3          5.7         2.5   8.2
## 4          5.1         2.4   7.5
## 5          5.6         2.4   8.0
## 6          5.6         2.4   8.0
```

]

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange(desc())`
- `rename()` 
- `mutate()`
- `summarise()`<span style="color: deeppink; "> << </span>
]

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
penguins %>%
  group_by(species) %>%
  drop_na()%>%
  select(bill_length_mm, body_mass_g, flipper_length_mm)%>%
* summarize(across(everything(), mean))
```

```
## # A tibble: 3 x 4
##   species   bill_length_mm body_mass_g flipper_length_mm
##   <fct>              <dbl>       <dbl>             <dbl>
## 1 Adelie              38.8       3706.              190.
## 2 Chinstrap           48.8       3733.              196.
## 3 Gentoo              47.6       5092.              217.
```

- across() function used as nested function here to apply summarize() function to multiple column<br><br>
- everything() used here for selecting all variables/columns

---

#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange(desc())`
]

.pull-right[
- `rename()` 
- `mutate()`
- `summarise()`
- `join()`<span style="color: deeppink; "> << </span>

]

--
.pull-left[

```r
df1 <- data.frame(
  Gene = c("gene1",
           "gene2",
           "gene3"),
  Sample1 = c(5, 6, 13))
df1
```

```
##    Gene Sample1
## 1 gene1       5
## 2 gene2       6
## 3 gene3      13
```
]

--
.pull-right[

```r
df2 <- data.frame(
  Gene = c("gene1",
           "gene2",
           "gene3"),
  Sample2 = c(15, 38, 3))
df2
```

```
##    Gene Sample2
## 1 gene1      15
## 2 gene2      38
## 3 gene3       3
```
]

---
#dplyr verbs

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[
- `select()`
- `filter()`
- `arrange(desc())`
]

.pull-right[
- `rename()` 
- `mutate()`
- `summarise()`
- `join()`<span style="color: deeppink; "> << </span>

]

```r
full_join(df1, df2, by = "Gene")
```

```
##    Gene Sample1 Sample2
## 1 gene1       5      15
## 2 gene2       6      38
## 3 gene3      13       3
```

---

#Changing rownames to column with dplyr

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
data <- datasets::USArrests
head(data, 2)
```

```
##         Murder Assault UrbanPop Rape
## Alabama   13.2     236       58 21.2
## Alaska    10.0     263       48 44.5
```

```r
data <- USArrests %>%
* rownames_to_column(var = "State")
head(data, 2)
```

```
##     State Murder Assault UrbanPop Rape
## 1 Alabama   13.2     236       58 21.2
## 2  Alaska   10.0     263       48 44.5
```

---
#Reshaping data with tidyr

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[

- `gather()` <span style="color: deeppink; "> << </span>
- `gather()` makes "wide" data longer
<br><br>
<img src="tidyr.png" width="35%" style="display: block; margin: auto;" />
]

--
.pull-right[

```r
*tidy_data <- gather(
  data = data,
  key = "Crime",
  value = "Estimate",
  - State)
head(tidy_data)
```

```
##        State  Crime Estimate
## 1    Alabama Murder     13.2
## 2     Alaska Murder     10.0
## 3    Arizona Murder      8.1
## 4   Arkansas Murder      8.8
## 5 California Murder      9.0
## 6   Colorado Murder      7.9
```
]

---

#Reshaping data with tidyr

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

--
.pull-left[

- `gather()`
- `spread()` <span style="color: deeppink; "> << </span>
- `spread()` makes "long" data wider
<br><br>
<img src="tidyr.png" width="35%" style="display: block; margin: auto;" />
]

--
.pull-right[

```r
*orig_data <- spread(
  data = tidy_data,
  key = "Crime",
  value = "Estimate")

head(orig_data[,1:3])
```

```
##        State Assault Murder
## 1    Alabama     236   13.2
## 2     Alaska     263   10.0
## 3    Arizona     294    8.1
## 4   Arkansas     190    8.8
## 5 California     276    9.0
## 6   Colorado     204    7.9
```
]
---

#Data Import and Export using readr

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- `read_csv()` is used for data importing into R environment.

- `write_csv()` is meant for saving any data frame as csv file into the current working directory. 
]

```r
library(readr)

*file <- read_csv(
  "filename.csv")

*write_csv(x = data,
          file = "filename.csv")
```

]

---

#Data Import and Export using readxl

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

- `read_xlsx()` is used for data importing into R environment.
]

```r
library(readxl)

*file <- read_xlsx(
  "filename.xlsx")
```

]

---

---

class: inverse, center, middle
background-image: url('viz1.jpg')
<span style="font-size: 90pt; color: white; ">5.  Data Visualization </span>

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

.pull-right[
<img src="layers.png" width="100%" height="100%" style="display: block; margin: auto;" />

- Graphics has distinct layers
]

--
<br><br>
- Resources:: [Introduction to ggplot2](https://englelab.gatech.edu/useRguide/introduction-to-ggplot2.html)
---
#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

.pull-left[
<img src="ge_data.png" width="100%" height="100%" style="display: block; margin: auto;" />

- Data layer

- It has only got input data. But the ggplot2 does not know what to plot.

- It returns an empty plot
]

```r
library(ggplot2)

ggplot(data = penguins)
```

![](intro2R_files/figure-html/unnamed-chunk-104-1.png)

]

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

.pull-left[
<img src="ge_aes.png" width="100%" height="100%" style="display: block; margin: auto;" />

- Aesthetic Layer

- X and Y coordinates are defined
]

```r
library(ggplot2)

g <- ggplot(data = penguins,
       aes(
         x = flipper_length_mm,
         y = body_mass_g))
g
```

![](intro2R_files/figure-html/unnamed-chunk-107-1.png)

]
---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

.pull-left[
<img src="ge_geom.png" width="100%" height="100%" style="display: block; margin: auto;" />

- Geometries Layer
- Here, we define what kind of plot we want (boxplot, histogram etc.)
]

```r
*g + geom_point()
```

![](intro2R_files/figure-html/unnamed-chunk-110-1.png)

]

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

.pull-left[
<img src="ge_facet.png" width="100%" height="100%" style="display: block; margin: auto;" />

- Facet wrapping creates subplots
]

```r
g + geom_point()+
* facet_wrap(~ species)
```

![](intro2R_files/figure-html/unnamed-chunk-113-1.png)

]

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
*g + geom_point(aes(color = sex))+
  facet_wrap(~ species)
```

![](intro2R_files/figure-html/unnamed-chunk-115-1.png)

---

#Themes

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

![](intro2R_files/figure-html/unnamed-chunk-117-1.png)

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
g + geom_point(aes(color = sex))+
* facet_wrap(~ species)+ theme_minimal()
```

![](intro2R_files/figure-html/unnamed-chunk-119-1.png)

---
#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
*ggplot(data = penguins %>% drop_na(),
       aes(x = flipper_length_mm,
           y = body_mass_g)) + geom_point(aes(color = sex))+
  facet_wrap(~ species)+ theme_minimal()
```

![](intro2R_files/figure-html/unnamed-chunk-121-1.png)

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
ggplot(data = penguins %>% drop_na(), 
       aes(x = flipper_length_mm,
           y = body_mass_g)) + geom_point(aes(color = sex))+
  facet_wrap(~ species)+ theme_minimal()+
* labs(title = "Penguin flipper and body mass",
       x = "Flipper length (mm)",#renaming x axis
       y = "Body mass (g)",#renaming y axis
       color = "Penguin sex") #renaming legend title
```

![](intro2R_files/figure-html/unnamed-chunk-123-1.png)

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
ggplot(data = penguins %>% drop_na(), 
       aes(x = flipper_length_mm,
           y = body_mass_g)) + 
  geom_point(aes(color = sex), alpha = 0.50)+
  facet_wrap(~ species)+ theme_minimal()+
  labs(title = "Penguin flipper and body mass",
       x = "Flipper length (mm)",
       y = "Body mass (g)",
       color = "Penguin sex")+
  scale_color_manual(values = c("darkorange","cyan4"))+
  theme(axis.title.x = element_text(size = 20),
        axis.title.y = element_text(size = 20),
        legend.title = element_text(size = 15),
        plot.title = element_text(size = 25))
```

]

![](intro2R_files/figure-html/unnamed-chunk-125-1.png)

]
]]

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

![](intro2R_files/figure-html/unnamed-chunk-129-1.png)

---
#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
ggplot(data = penguins, aes(x = species, y = flipper_length_mm))+ 
  geom_boxplot(width = 0.2)+ geom_jitter(width = 0.1)+
* ggdist::stat_halfeye(width = 0.3,justification = - .4)
```

![](intro2R_files/figure-html/unnamed-chunk-131-1.png)

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
ggplot(data = penguins, aes(x = species, 
                            y = flipper_length_mm, 
                            fill = species))+
geom_boxplot(width = 0.2, alpha = 0.25,
             aes(color = species) )+ 
  geom_jitter(width = 0.1, size = 2, 
              alpha = 0.25, aes(color = species))+ 
ggdist::stat_halfeye(width = 0.3,justification = - .4, alpha = 0.25)+
scale_fill_manual(values = c("darkorange","purple","cyan4"))+
scale_color_manual(values = c("darkorange","purple","cyan4"))+ 
  theme_minimal()+ 
  theme(legend.position = "none")+
  labs(x = "", y = "Flipper length (mm)")
```

]

![](intro2R_files/figure-html/unnamed-chunk-133-1.png)

]
]]

---

#Data Visualization with {ggplot2}

.footnote[
<svg preserveAspectRatio="none" aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:30px;width:35px;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#E33D85;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
]

```r
ggplot(data = penguins, aes(x = species, 
                            y = flipper_length_mm, 
                            fill = species))+
geom_boxplot(width = 0.2, alpha = 0.25,
             aes(color = species))+ 
geom_point(shape = 95 ,width = 0.1, 
           size = 10, alpha = 0.25, 
           aes(color = species))+ 
ggdist::stat_halfeye(width = 0.3,
                     justification = - .4, 
                     alpha = 0.25)+
scale_fill_manual(values = c("darkorange","purple","cyan4"))+
scale_color_manual(values = c("darkorange","purple","cyan4"))+ 
  theme_minimal()+ 
  theme(legend.position = "none")+
  labs(x = "", y = "Flipper length (mm)")
```

]

![](intro2R_files/figure-html/unnamed-chunk-136-1.png)

]
]]
---

#Acknowledgement

- I owe every bit of coding knowledge because of the `rstats` community.

- This slide was designed using [xaringan](https://github.com/yihui/xaringan)

- This presentation is mostly inspired from 
[Allison Horst](https://www.allisonhorst.com/), [Allison Hill](https://www.apreshill.com/), [Cédric Scherer](https://www.cedricscherer.com/), [Danielle Navarro](https://djnavarro.net/)

- The data sets used in this package were <br><br>
&nbsp;&nbsp;&nbsp;1. penguins from `palmerpenguins` package <br><br>
&nbsp;&nbsp;&nbsp;2. iris, USarrests from `datasets` package in built in R.

---

#My Inspiration

<img src="danielle.jpg" width="30%" align= "left"/><br><br><br>
<pre class="tab"><span style="font-size: 30pt; ">Danielle Navarro</span></pre>
<br><br><br>

<img src="cedric.png" width="30%" align="right"/><br><br><br> 
<pre class="tab"><span style="font-size: 30pt; ">       Cédric Scherer </span></pre>

---

class: center, middle
background-image: url("rocket.jpg")
background-size: cover
---