ggplot Detailed Features

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# ggplot Detailed Features
## for OECD Charte Graphique
### 2017/06/29

---

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# OECDPlotR

![](under_construction.gif)

---

## OECDPlotR: Column Chart

```r
ggplot(data=dat1, aes(x=time, y=scrap, fill=dat1$region)) +
  geom_barOECD(scaled=TRUE, # Used to pass on default to OECDggplotscale()
               stat="identity", position=position_dodge()) +
  OECDggplotscale(name="Country",scaleType = "fill") + # pecify color of scaling
  xlab("Year") + ylab("Scrap") + ggtitle("China Plastic Scrap") + OECDtheme()
```

![](10-ggplot-detailed-features/fig-html/oecdplotr-bar-1-1.svg)

---

```r
ggplot(data=dat1, aes(x=time, y=scrap, fill=dat1$region)) +
  geom_barOECD(scaled=TRUE, stat="identity", position=position_dodge()) +
  coord_flip() + OECDggplotscale(name="Country",scaleType = "fill") +
  xlab("Year") + ylab("Scrap") + ggtitle("China Plastic Scrap") + OECDtheme()
```

![](10-ggplot-detailed-features/fig-html/oecdplotr-bar-2-1.svg)

---

## OECDPlotR: Stacked Column

```r
ggplot(data=dat1, aes(x=time, y=scrap, fill=dat1$region)) +
  geom_barOECD(scaled=TRUE, stat="identity") +
  OECDggplotscale(name="Country",scaleType = "fill") +
  xlab("Year") + ylab("Scrap")+ OECDtheme()
```

![](10-ggplot-detailed-features/fig-html/oecdplotr-bar-3-1.svg)

---

## OECDPlotR: STI-OLIS Theme

![](10-ggplot-detailed-features/fig-html/oecdplotr-bar-4-1.svg)

---

## OECDPlotR: Other Features

```r
ggplot(mpg, aes(class)) +
  geom_barOECD(aes(fill = drv), position = position_stack(reverse = TRUE),scaled = TRUE) +
  OECDggplotscale(scaleType="fill")+ OECDtheme()
```

![](10-ggplot-detailed-features/fig-html/oecdplotr-bar-10-1.svg)

---

## OECDPlotR: Other Features

```r
ggplot(mpg, aes(class)) +
  geom_barOECD(aes(fill = drv), position = position_stack(reverse = TRUE),scaled = TRUE) +
  OECDggplotscale(scaleType="fill") + OECDtheme(inbox = TRUE)
```

![](10-ggplot-detailed-features/fig-html/oecdplotr-bar-11-1.svg)

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# theming

http://ggplot2.tidyverse.org/reference/theme.html

---

## Grobs: Legend Width

```r
gp <- ggplot2::ggplotGrob(p)
leg <- gtable::gtable_filter(gp, "guide-box")
panel <- gtable::gtable_filter(gp, "panel")
leg[[1]][[1]]$widths[[elem]] =
  panel$grobs[[1]]$children[[1]]$children[[1]]$width -
  sum(leg[[1]][[1]]$widths) + leg[[1]][[1]]$widths[[elem]]
gp.new = gtable::gtable_add_grob(gp, leg, t = 4, l = 4)
```

![](10-ggplot-detailed-features/fig-html/legend-width-eval-1.svg)

---

## Legend Guides

It is possible to specify the `legend.key` height and width separately for each guide (colour, linetype etc.), see [guide_legend.html](http://ggplot2.tidyverse.org/reference/guide_legend.html)

```r
p2 <- p1 + guides(fill = guide_legend(keywidth = unit(10, "mm"),
                                keyheight = unit(10, "mm"), title = "",
                                override.aes = list(color = "black")),
            linetype = guide_legend(keywidth = unit(20, "mm"), title = ""))
gp2 <- absLegend(p2); grid.newpage(); grid.draw(gp2)
```

![](10-ggplot-detailed-features/fig-html/key-size-1.svg)

---

## Y-Axis Position

The y-axis title position can be modified in the theme using the parameters of `element_text`, see [theme elements](http://ggplot2.tidyverse.org/reference/element.html)

```r
p2 <- p1 + scale_y_continuous(name = "%") +
  theme(axis.title.y = element_text(vjust = 1.08, angle = 0,
                                    margin = margin(r = -10, unit = "pt")))
gp2 <- absLegend(p2); grid.newpage(); grid.draw(gp2)
```

![](10-ggplot-detailed-features/fig-html/axis-title-position-1.svg)

---

## Secondary Y-Axis

The `sec.axis` parameter of `scale_y_continuous` can define a transformed
version of the primary y-axis,
see [sec_axis()](http://ggplot2.tidyverse.org/reference/sec_axis.html). Prior to
plotting, series with different units need to be scaled to the same unit manually.

```r
ggplot(mtcars, aes(cyl, mpg)) + geom_point()
```

![](10-ggplot-detailed-features/fig-html/sec-axis-1.svg)

---

We may want to display the levels of `mpg` and `hp` on the same plot

<div id="htmlwidget-05451616150977026663" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-05451616150977026663">{"x":{"filter":"none","fillContainer":false,"data":[["Mazda RX4","Mazda RX4 Wag","Datsun 710","Hornet 4 Drive","Hornet Sportabout","Valiant","Duster 360","Merc 240D","Merc 230","Merc 280"],[21,21,22.8,21.4,18.7,18.1,14.3,24.4,22.8,19.2],[6,6,4,6,8,6,8,4,4,6],[160,160,108,258,360,225,360,146.7,140.8,167.6],[110,110,93,110,175,105,245,62,95,123],[3.9,3.9,3.85,3.08,3.15,2.76,3.21,3.69,3.92,3.92],[2.62,2.875,2.32,3.215,3.44,3.46,3.57,3.19,3.15,3.44],[16.46,17.02,18.61,19.44,17.02,20.22,15.84,20,22.9,18.3],[0,0,1,1,0,1,0,1,1,1],[1,1,1,0,0,0,0,0,0,0],[4,4,4,3,3,3,3,4,4,4],[4,4,1,1,2,1,4,2,2,4]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>mpg<\/th>\n      <th>cyl<\/th>\n      <th>disp<\/th>\n      <th>hp<\/th>\n      <th>drat<\/th>\n      <th>wt<\/th>\n      <th>qsec<\/th>\n      <th>vs<\/th>\n      <th>am<\/th>\n      <th>gear<\/th>\n      <th>carb<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"pageLength":5,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[5,10,25,50,100]},"selection":{"mode":"multiple","selected":null,"target":"row"}},"evals":[],"jsHooks":[]}</script>

```r
mtcars %>% select(mpg, hp) %>% mutate(hp_scaled = hp / 10) %>% summary()
```

```
##       mpg              hp          hp_scaled    
##  Min.   :10.40   Min.   : 52.0   Min.   : 5.20  
##  1st Qu.:15.43   1st Qu.: 96.5   1st Qu.: 9.65  
##  Median :19.20   Median :123.0   Median :12.30  
##  Mean   :20.09   Mean   :146.7   Mean   :14.67  
##  3rd Qu.:22.80   3rd Qu.:180.0   3rd Qu.:18.00  
##  Max.   :33.90   Max.   :335.0   Max.   :33.50
```

---

Plot on separate axes, manual axis title and legend labels

```r
scalefactor <- 10^1; p1 <- mtcars %>% mutate(hp_scaled = hp / scalefactor) %>%
  select(cyl, mpg, hp_scaled) %>% gather(key = variable, value = value, -cyl) %>%
  ggplot(aes(x=cyl, y = value, color = variable)) + geom_point() +
  scale_y_continuous(name = "mpg", sec.axis = sec_axis(name="hp", ~.*scalefactor)) +
  scale_color_discrete(labels = c("hp", "mpg")) +
  guides(color = guide_legend(title = NULL)) +
theme(legend.position = "top", legend.background = element_rect(fill = FALSE, color = FALSE),
      legend.margin = margin(0.5, 0, 0.5, 0, unit = "mm"), # trbl
      legend.key = element_rect(color = FALSE, fill = FALSE))
grid.newpage(); p1 %>% absLegend() %>% grid.draw()
```

![](10-ggplot-detailed-features/fig-html/rescale-mtcars-1.svg)

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# aesthetics

---

## data labels

The `geom_text` layer accepts parameters for `element_text`, for details see
[geom_text](http://ggplot2.tidyverse.org/reference/geom_text.html).
The fonts must be installed on your computer.

```r
## labelpos = 100 - (cumsum(pct) - pct / 2)
p + geom_text(aes(y = labelpos,
                  label = paste0(as.character(pct), "%")),
              family = "serif", size = 6, color = "red") +
  coord_polar(theta = "y")
```

![](10-ggplot-detailed-features/fig-html/pie-label-1.svg)

---

## High Low Plot

Analogue to colors, linetypes and shapes can be mapped to variables,
see [Shapes and line types](http://www.cookbook-r.com/Graphs/Shapes_and_line_types/)

```r
p_hl <- ggplot(data = df_hl, aes(x = date, y = value,
                                 color = label, fill = label)) +
  geom_point(aes(shape = label), size = 2) +
  scale_shape_manual(values = c(17, 23, 15))
themeHighLow(p = p_hl, col = c("black", "#4f81bd", "black"))
```

![](10-ggplot-detailed-features/fig-html/high-low-plot-base-1.svg)

---

## High Low Plot with Lines

`geom_segment` allows drawing arbitrary lines, see [Line segments and curves](http://ggplot2.tidyverse.org/reference/geom_segment.html)

```r
df_hl2 <- df_hl %>% group_by(date) %>% mutate(min=min(value), max=(max(value))) %>% ungroup()
p_hl2 <- ggplot(data = df_hl2, aes( x = date, y = value, color = label, fill = label )) +
  geom_point( aes( shape = label ), size = 2) +
  geom_segment( aes( xend = date, y = min, yend = max ), size = 0.05) +
  scale_shape_manual(values = c(17, 23, 15)); themeHighLow(p = p_hl2)
```

![](10-ggplot-detailed-features/fig-html/high-low-plot-line-1.svg)

---
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# extensions

---

## Radar Plot

Data extracted from http://stats.oecd.org/Index.aspx?DataSetCode=BLI

```
mutate_at(vars(-LOCATION), funs(scales::rescale))
```

```
## 'data.frame':	2 obs. of  25 variables:
##  $ group                                            : Factor w/ 39 levels "AUS","AUT","BEL",..: 14 21
##  $ Air pollution                                    : num  0.348 0.522
##  $ Dwellings without basic facilities               : num  0.0244 0.039
##  $ Educational attainment                           : num  0.672 0.469
##  $ Employees working very long hours                : num  0.1573 0.0635
##  $ Employment rate                                  : num  0.62 0.34
##  $ Feeling safe walking alone at night              : num  0.636 0.437
##  $ Homicide rate                                    : num  0.08 0.08
##  $ Household net adjusted disposable income         : num  0.65 0.503
##  $ Household net financial wealth                   : num  0.314 0.333
##  $ Housing expenditure                              : num  0.667 0.867
##  $ Labour market insecurity                         : num  0.222 0.371
##  $ Life expectancy                                  : num  0.964 0.95
##  $ Life satisfaction                                : num  0.517 0.345
##  $ Long-term unemployment rate                      : num  0.176 0.386
##  $ Personal earnings                                : num  0.622 0.533
##  $ Quality of support network                       : num  0.5 0.5
##  $ Rooms per person                                 : num  0.611 0.389
##  $ Self-reported health                             : num  0.552 0.517
##  $ Stakeholder engagement for developing regulations: num  0.481 0.259
##  $ Student skills                                   : num  0.734 0.64
##  $ Time devoted to leisure and personal care        : num  1 0.592
##  $ Voter turnout                                    : num  0.729 0.562
##  $ Water quality                                    : num  0.755 0.367
##  $ Years in education                               : num  0.356 0.441
```

---

## Radar Plot

The existing ggplot2 extension [ggradar](http://www.ggplot2-exts.org/ggradar.html) can be modified. Alternatively, the [plotrix package](https://cran.r-project.org/web/packages/plotrix/index.html) can be tested. More examples can be found [here](http://boot.rdata.work/contrib/radar-example/)

```r
p_radar <-
  ggradar(bli_radar,
          font.radar = "sans",
          grid.label.size = 4,
          axis.label.size = 4,
          group.point.size = 1,
          group.line.width = 1,
          plot.extent.x.sf = 1.8) +
  scale_color_manual(values = c("#8cc841", "#da2128")) +
theme(
  legend.position = c(0.05, 0.95),
  legend.justification = "left",
  legend.direction = "horizontal",
  legend.text = element_text(size = 8),
  legend.background = element_rect(fill = NULL)
)
```

---

## Radar Plot

![](10-ggplot-detailed-features/fig-html/radar-chart-2-1.svg)

---
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# hrbrthemes

https://github.com/hrbrmstr/hrbrthemes

---

```r
ggplot(uspopage, aes(x=Year, y=Thousands, fill=AgeGroup)) + geom_area() +
  scale_fill_ipsum() + scale_x_continuous(expand=c(0,0)) + scale_y_comma() +
  labs(title="Age distribution of population in the U.S., 1900-2002",
       subtitle="Example data from the R Graphics Cookbook",
       caption="Source: R Graphics Cookbook") +
  theme_ipsum_rc(grid="XY") + theme(legend.position="right") +
  theme(axis.text.x=element_text(hjust=c(0, 0.5, 0.5, 0.5, 1)))
```

![](10-ggplot-detailed-features/fig-html/hrbrthemes-example-area-1.svg)

---

```
## R version 3.4.1 (2017-06-30)
## Platform: x86_64-redhat-linux-gnu (64-bit)
## Running under: Fedora 26 (Workstation Edition)
## 
## Matrix products: default
## BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  base     
## 
## other attached packages:
##  [1] bindrcpp_0.2     DT_0.2           knitr_1.17       OECDplot_1.5.6  
##  [5] gcookbook_1.0    hrbrthemes_0.1.0 scales_0.5.0     ggradar_0.1     
##  [9] gtable_0.2.0     tidyr_0.7.0      dplyr_0.7.2      ggplot2_2.2.1   
## [13] rmarkdown_1.6   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.12     compiler_3.4.1   plyr_1.8.4       bindr_0.1       
##  [5] methods_3.4.1    tools_3.4.1      extrafont_0.17   digest_0.6.12   
##  [9] evaluate_0.10.1  tibble_1.3.4     pkgconfig_2.0.1  rlang_0.1.2     
## [13] yaml_2.1.14      hunspell_2.5     Rttf2pt1_1.3.4   stringr_1.2.0   
## [17] htmlwidgets_0.9  rprojroot_1.2    glue_1.1.1       R6_2.2.2        
## [21] XML_3.98-1.9     xaringan_0.3     purrr_0.2.3      extrafontdb_1.0 
## [25] magrittr_1.5     backports_1.1.0  htmltools_0.3.6  assertthat_0.2.0
## [29] colorspace_1.3-2 labeling_0.3     stringi_1.1.5    lazyeval_0.2.0  
## [33] munsell_0.4.3
```