Data Visualization — Summary and Further Topics

# Data Visualization — Summary and Further Topics

## Data Analysis with R and Python

### Deepayan Sarkar

---

# Traditional graphics

---

* Implemented in the  __graphics__ package

* Add-on packages provide further functionality

* Mainly two types

- High-level functions

- Low-level functions

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---

# Common High-Level functions in __graphics__

| Function         | Default Display                                   |
|:-----------------|:--------------------------------------------------|
| `stripchart()`   | Strip Chart (Comparative 1-D Scatter Plots)       |
| `boxplot()`      | Comparative Box-and-Whisker Plots                 |
| `hist()`         | Histogram                                         |
| `plot(density())`| Kernel Density Plot                               |
| `plot()`         | Scatter Plot, Time-series Plot (with `type="l"`)  |
| `barplot()`      | Bar Plot                                          |
| `dotchart()`     | Cleveland Dot Plot                                |
| `qqnorm()`       | Normal Quantile-Quantile Plot                     |
| `qqplot()`       | Two-sample Quantile-Quantile Plot                 |
| `pairs()`        | Scatter-Plot Matrix                               |

---

# Common High-Level functions in __lattice__

| Function         | Default Display                                   |
|:-----------------|:--------------------------------------------------|
| `stripplot()`    | Strip Chart (Comparative 1-D Scatter Plots)       |
| `bwplot()`       | Comparative Box-and-Whisker Plots                 |
| `histogram()`    | Histogram                                         |
| `densityplot()`  | Kernel Density Plot                               |
| `xyplot()`       | Scatter Plot, Time-series Plot (with `type="l"`)  |
| `barchart()`     | Bar Plot                                          |
| `dotplot()`      | Cleveland Dot Plot                                |
| `qqmath()`       | Normal Quantile-Quantile Plot                     |
| `qq()`           | Two-sample Quantile-Quantile Plot                 |
| `splom()`        | Scatter-Plot Matrix                               |

---

# Some useful low-level functions in __graphics__

| Function      | Purpose                               |
|:--------------|:--------------------------------------|
| `text()`      | Add Text to a Plot                    |
| `lines()`     | Add Connected Line Segments to a Plot |
| `points()`    | Add Points to a Plot                  |
| `polygon()`   | Add Polygons to a Plot                |
| `rect()`      | Add Rectangles to a Plot              |
| `segments()`  | Add Line Segments to a Plot           |

---

# Some other low-level utility functions in __graphics__

| Function     | Purpose                            |
|:-------------|:-----------------------------------|
| `abline()`   | Add Straight Lines to a Plot       |
| `arrows()`   | Add Arrows to a Plot               |
| `axis()`     | Add an Axis to a Plot              |
| `box()`      | Draw a Box around a Plot           |
| `grid()`     | Add Grid to a Plot                 |
| `legend()`   | Add Legends to Plots               |
| `title()`    | Add Annotation (Titles and Labels) |

---

# Common low-level functions in __lattice__

| Function           | Purpose                                |
|:-------------------|:---------------------------------------|
| `panel.text()`     | Add Text to a Panel                    |
| `panel.lines()`    | Add Connected Line Segments to a Panel |
| `panel.points()`   | Add Points to a Panel                  |
| `panel.polygon()`  | Add Polygons to a Panel                |
| `panel.rect()`     | Add Rectangles to a Panel              |
| `panel.segments()` | Add Line Segments to a Panel           |
| `panel.abline()`   | Add Straight Lines to a Panel          |
| `panel.arrows()`   | Add Arrows to a Panel                  |
| `panel.grid()`     | Add Grid to a Panel                    |

---

# The ggplot2 approach

* Specify a plot using a __grammar__ consisting of

* Geometric constructs

* Aesthetic Mappings

* Statistical Summaries

---

# ggplot2: List of geoms

``` r
library(ggplot2)
apropos("^geom_")
```

```
 [1] "geom_abline"            "geom_area"              "geom_bar"              
 [4] "geom_bin_2d"            "geom_bin2d"             "geom_blank"            
 [7] "geom_boxplot"           "geom_col"               "geom_contour"          
[10] "geom_contour_filled"    "geom_count"             "geom_crossbar"         
[13] "geom_curve"             "geom_density"           "geom_density_2d"       
[16] "geom_density_2d_filled" "geom_density2d"         "geom_density2d_filled" 
[19] "geom_dotplot"           "geom_errorbar"          "geom_errorbarh"        
[22] "geom_freqpoly"          "geom_function"          "geom_hex"              
[25] "geom_histogram"         "geom_hline"             "geom_jitter"           
[28] "geom_label"             "geom_line"              "geom_linerange"        
[31] "geom_map"               "geom_path"              "geom_point"            
[34] "geom_pointrange"        "geom_polygon"           "geom_qq"               
[37] "geom_qq_line"           "geom_quantile"          "geom_raster"           
[40] "geom_rect"              "geom_ribbon"            "geom_rug"              
[43] "geom_segment"           "geom_sf"                "geom_sf_label"         
[46] "geom_sf_text"           "geom_smooth"            "geom_spoke"            
[49] "geom_step"              "geom_text"              "geom_tile"             
[52] "geom_violin"            "geom_vline"            
```

???

---

# ggplot2: List of stats

``` r
apropos("^stat_")
```

```
 [1] "stat_align"             "stat_bin"               "stat_bin_2d"           
 [4] "stat_bin_hex"           "stat_bin2d"             "stat_binhex"           
 [7] "stat_boxplot"           "stat_contour"           "stat_contour_filled"   
[10] "stat_count"             "stat_density"           "stat_density_2d"       
[13] "stat_density_2d_filled" "stat_density2d"         "stat_density2d_filled" 
[16] "stat_ecdf"              "stat_ellipse"           "stat_function"         
[19] "stat_identity"          "stat_qq"                "stat_qq_line"          
[22] "stat_quantile"          "stat_sf"                "stat_sf_coordinates"   
[25] "stat_smooth"            "stat_spoke"             "stat_sum"              
[28] "stat_summary"           "stat_summary_2d"        "stat_summary_bin"      
[31] "stat_summary_hex"       "stat_summary2d"         "stat_unique"           
[34] "stat_ydensity"         
```

---

# Interactive Graphics

* R works on many platforms: Windows, Mac, Linux, UNIX

* Static graphics achieves portability through _graphics devices_

* Cross-platform interactive graphics is even more difficult

---

# Interactive Graphics: Cross-platform technology

- OpenGL (R package __rgl__)

- Browser-based visualization technology (R packages __plotly__, __rbokeh__)

---

# Plotly: Example

---

``` r
library(package = "ggplot2")
library(package = "plotly")
library(package = "gapminder")
p1 <- 
    ggplot(data = gapminder,
           mapping = aes(x = log(gdpPercap), y = lifeExp,
                         size = pop, color = continent)) +
    facet_wrap(~ year) + geom_point()
```

---

``` r
p1
```

![plot of chunk unnamed-chunk-4](figures/8-vizsummary-unnamed-chunk-4-1.svg)

---

```r
ggplotly(p1)
```

---

* Want to add country name

* Easiest way is to add a fake aesthetic

``` r
p2 <- 
    ggplot(data = gapminder,
           mapping = aes(x = log(gdpPercap), y = lifeExp,
                         size = pop, color = continent,
                         tooltip = country)) +
    facet_wrap(~ year) + geom_point()
```

---

```r
ggplotly(p2)
```