R for Data Analysis

# R for Data Analysis
## Data Visualization
### Ayush Patel
### 28-Jul-2021

---

---

## Find me

[__@ayushbipinpatel__](https://twitter.com/ayushbipinpatel) <img src="data:image/svg+xml;base64,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" width=5%> 
 
[__@AyushBipinPatel__](https://github.com/AyushBipinPatel) <img src="data:image/svg+xml;base64,PHN2ZyBlbmFibGUtYmFja2dyb3VuZD0ibmV3IDAgMCAyNCAyNCIgaGVpZ2h0PSI1MTIiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjUxMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj48cGF0aCBkPSJtMTIgLjVjLTYuNjMgMC0xMiA1LjI4LTEyIDExLjc5MiAwIDUuMjExIDMuNDM4IDkuNjMgOC4yMDUgMTEuMTg4LjYuMTExLjgyLS4yNTQuODItLjU2NyAwLS4yOC0uMDEtMS4wMjItLjAxNS0yLjAwNS0zLjMzOC43MTEtNC4wNDItMS41ODItNC4wNDItMS41ODItLjU0Ni0xLjM2MS0xLjMzNS0xLjcyNS0xLjMzNS0xLjcyNS0xLjA4Ny0uNzMxLjA4NC0uNzE2LjA4NC0uNzE2IDEuMjA1LjA4MiAxLjgzOCAxLjIxNSAxLjgzOCAxLjIxNSAxLjA3IDEuODAzIDIuODA5IDEuMjgyIDMuNDk1Ljk4MS4xMDgtLjc2My40MTctMS4yODIuNzYtMS41NzctMi42NjUtLjI5NS01LjQ2Ni0xLjMwOS01LjQ2Ni01LjgyNyAwLTEuMjg3LjQ2NS0yLjMzOSAxLjIzNS0zLjE2NC0uMTM1LS4yOTgtLjU0LTEuNDk3LjEwNS0zLjEyMSAwIDAgMS4wMDUtLjMxNiAzLjMgMS4yMDkuOTYtLjI2MiAxLjk4LS4zOTIgMy0uMzk4IDEuMDIuMDA2IDIuMDQuMTM2IDMgLjM5OCAyLjI4LTEuNTI1IDMuMjg1LTEuMjA5IDMuMjg1LTEuMjA5LjY0NSAxLjYyNC4yNCAyLjgyMy4xMiAzLjEyMS43NjUuODI1IDEuMjMgMS44NzcgMS4yMyAzLjE2NCAwIDQuNTMtMi44MDUgNS41MjctNS40NzUgNS44MTcuNDIuMzU0LjgxIDEuMDc3LjgxIDIuMTgyIDAgMS41NzgtLjAxNSAyLjg0Ni0uMDE1IDMuMjI5IDAgLjMwOS4yMS42NzguODI1LjU2IDQuODAxLTEuNTQ4IDguMjM2LTUuOTcgOC4yMzYtMTEuMTczIDAtNi41MTItNS4zNzMtMTEuNzkyLTEyLTExLjc5MnoiIGZpbGw9IiMyMTIxMjEiLz48L3N2Zz4=" width=5%>
 
 
[__ayushpatel.netlify.app__](https://ayushpatel.netlify.app/) <img src="data:image/svg+xml;base64,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" width=5%> 
 
 
[__ayush.ap58@gmail.com__](ayush.ap58@gmail.com)<img src="data:image/svg+xml;base64,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" width=5%>

]

.small[
Image: [John Biglin in a Single Scull by Thomas Eakins](https://images.metmuseum.org/CRDImages/ad/original/57258.jpg)
]

]
---

#  Pre-requisite

understand __different types of objects, how to create objects and assign values to objects__.

__how to access specific values within an object.__

know __what a function is and how to use a function.__

know __basics of data wrangling__

]

.small[
[Image:  Lake George by John Frederick Kensett ](https://images.metmuseum.org/CRDImages/ad/original/DT84.jpg)
]
]
---

# Before we get to it..

Load the following libraries and data

```r
library(tidyverse)
library(palmerpenguins)
library(nycflights13)

read_csv("https://raw.githubusercontent.com/AyushBipinPatel/R-for-Data-Analysis/main/clean_ccs.csv") -> data_ccs
```

---

# ggplot2 Package

[ggplot2 logo from RStudio hexstickers repo](https://raw.githubusercontent.com/rstudio/hex-stickers/master/thumbs/ggplot2.png)

]

[Art by @allisonhorst](https://github.com/allisonhorst)
]

---

# The Thought Process

---

# What will you learn?

Types of geometries and when to use them 
 How to map variables in data to aesthetics of a plot 
 About the theme of a plot 
 Labeling the plot

]

geom_*() (density, histogram, bar, point, jitter, col, boxplot) 
 The aes() (mapping variables to axes, shape, size, colour, fill and alpha of the geom) 
 Intro to available themes theme_*() 
 The labs() to add title, subtitle, axes labels and caption to the plot.

]

---

```r
* ggplot(data = penguins) # the plot area and data
```
]
 
.panel2-comp_plot-auto[
<img src="data-viz_files/figure-html/comp_plot_auto_01_output-1.png" width="100%" />
]

---
count: false
 
Components of a plot
.panel1-comp_plot-auto[

```r
 ggplot(data = penguins)+ # the plot area and data
* geom_boxplot(
* aes(species, body_mass_g,
* fill = species),
* alpha = 0.5
* ) # geom and aesthetic
```
]
 
.panel2-comp_plot-auto[
<img src="data-viz_files/figure-html/comp_plot_auto_02_output-1.png" width="100%" />
]

---
count: false
 
Components of a plot
.panel1-comp_plot-auto[

```r
 ggplot(data = penguins)+ # the plot area and data
 geom_boxplot(
 aes(species, body_mass_g,
 fill = species),
 alpha = 0.5
 )+ # geom and aesthetic
* geom_jitter(
* aes(species,body_mass_g,
* colour = species),
* alpha = 0.5
* ) # another layer with aesthetics
```
]
 
.panel2-comp_plot-auto[
<img src="data-viz_files/figure-html/comp_plot_auto_03_output-1.png" width="100%" />
]

---
count: false
 
Components of a plot
.panel1-comp_plot-auto[

```r
 ggplot(data = penguins)+ # the plot area and data
 geom_boxplot(
 aes(species, body_mass_g,
 fill = species),
 alpha = 0.5
 )+ # geom and aesthetic
 geom_jitter(
 aes(species,body_mass_g,
 colour = species),
 alpha = 0.5
 )+ # another layer with aesthetics
* theme_bw() # theme
```
]
 
.panel2-comp_plot-auto[
<img src="data-viz_files/figure-html/comp_plot_auto_04_output-1.png" width="100%" />
]

---
count: false
 
Components of a plot
.panel1-comp_plot-auto[

```r
 ggplot(data = penguins)+ # the plot area and data
 geom_boxplot(
 aes(species, body_mass_g,
 fill = species),
 alpha = 0.5
 )+ # geom and aesthetic
 geom_jitter(
 aes(species,body_mass_g,
 colour = species),
 alpha = 0.5
 )+ # another layer with aesthetics
 theme_bw()+ # theme
* labs(
* x = "Species",
* y = "Body mass in grams",
* title = "Distribution of Mass of penguins"
* ) # labels
```
]
 
.panel2-comp_plot-auto[
<img src="data-viz_files/figure-html/comp_plot_auto_05_output-1.png" width="100%" />
]

???

explain each layer and aes mapping
---
class: left,top

# Plotting one continuous variable

<code class ='r hljs remark-code'>ggplot(data = penguins)+ &nbsp;&nbsp;geom_density(aes(x = body_mass_g))</code>

<img src="data-viz_files/figure-html/unnamed-chunk-1-1.png" width="100%" />
]

<code class ='r hljs remark-code'>ggplot(data = penguins)+ &nbsp;&nbsp;geom_histogram(aes(x = body_mass_g))</code>

]

---

# Activity 1

From the `penguins` data:
  
    + Choose a continious variable of your interest
    + Write code to create a histogram for that variable
    + Write code to create a density plot for that variable

---

# Plotting one discrete variable

<code class ='r hljs remark-code'>ggplot(data = penguins)+ &nbsp;&nbsp;geom_bar(aes(x = island))</code>

---

# Activity 2

Use the `data_ccs` (this is the [RBI's consumer confidence survey](https://dbie.rbi.org.in/DBIE/dbie.rbi?site=unitLevelData) (22nd round) 2012-2014. This is a subset of the survey data.)

Write code to create a bar chart for any two discrete variables of your liking. You could choose from:

+ city
 + age
 + gender
 + occupation_of_respondent
 + annual_income
 + education_qualification
 .....
 
<div class="countdown" id="timer_6102a11a" style="top:0;right:0;" data-warnwhen="0">
<code class="countdown-time">05:00</code>
</div>
 
---

# Plotting two continuous variables

<code class ='r hljs remark-code'>ggplot(data = penguins)+ &nbsp;&nbsp;geom_point(aes(x = bill_length_mm,y = bill_depth_mm))</code>

---

# Activity 3

View the `penguins` data

Write code to plot two continuous variables of you choice and interest.

---

## Plotting one continuous and one discrete variable

<code class ='r hljs remark-code'>penguins %>% &nbsp;&nbsp;group_by(species) %>% &nbsp;&nbsp;summarise( &nbsp;&nbsp;&nbsp;&nbsp;avg_body_mass = mean(body_mass_g,na.rm = T) &nbsp;&nbsp;) %>% &nbsp;&nbsp;ggplot() + &nbsp;&nbsp;geom_col(aes(species,avg_body_mass))</code>

]

<code class ='r hljs remark-code'>penguins %>% &nbsp;&nbsp;ggplot() + &nbsp;&nbsp;geom_boxplot(aes(species,body_mass_g))</code>

]

---

# Activity 4

Use the `flights` data

Write code to generate following plots:

+ A column chart that show the average departure delays from various origin airports
 + A box plot that shows distributions of departure delays at various origin airports.
 
<div class="countdown" id="timer_6102a11a" style="top:0;right:0;" data-warnwhen="0">
<code class="countdown-time">05:00</code>
</div>

---

# Aesthetics of geoms

```r
penguins %>% 
  ggplot()+
  geom_boxplot(aes(species, body_mass_g,
                   fill = sex))
```

]

```r
penguins %>% 
  ggplot()+
  geom_point(aes(bill_length_mm, bill_depth_mm,
                 colour = species))
```

]

```r
penguins %>% 
  ggplot()+
  geom_point(aes(bill_length_mm, bill_depth_mm,
                 shape = species))
```

]

```r
penguins %>% 
  ggplot()+
  geom_point(aes(bill_length_mm, bill_depth_mm,
                 colour = species),
             alpha = 0.5)
```

]

```r
penguins %>% 
  ggplot()+
  geom_point(aes(bill_length_mm, bill_depth_mm,
                 size = species),
             alpha = 0.5)
```

]

]
---

# Activity 5

Replicate these two charts. Chart on the left using `mtcars` and chart on the right using `penguins`.

---
class: left, middle

# Plot Labels

```
.....
.....  ## Your awesome plot code
..... +
labs(
title = "Chart title",
subtitle = "Chart Subtitle",
x = "x-axis title",
y = "y-axis title",
caption = "Chart caption"
)
```
]

]

---

# Activity 6

You have made some good charts during this session.

Pick two charts you like the most, and label these appropriately.

---