stacked area OK

136-stacked-area-chart.Rmd

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+---
+title: "Basic Stacked area chart with R"
+descriptionMeta: "This post provides the basics concerning stacked area chart with R and ggplot2. It takes into account several input format types and show how to customize the output."
+descriptionTop: "This post provides the basics concerning [stacked area chart](stacked-area-graph.html) with R and `ggplot2`. It takes into account several input format types and show how to customize the output."
+sectionText: "Stacked area section"
+sectionLink: "stacked-area-graph.html"
+DataToVizText: "Data to Viz"
+DataToVizLink: "data-to-viz.com/graph/stackedarea.html"
+url: "136-stacked-area-chart"
+output:
+  html_document:
+      self_contained: false    
+      mathjax: default
+      lib_dir: libs
+      template: template_rgg.html
+      css: style.css
+      toc: TRUE
+      toc_float: TRUE
+      toc_depth: 2
+      df_print: "paged"
+---
+
+
+```{r global options, include = FALSE}
+knitr::opts_chunk$set( warning=FALSE, message=FALSE)
+```
+
+<div class="container">
+
+
+
+
+# Most basic stacked area with ggplot2
+***
+
+<div class = "row">
+
+<div class = "col-md-6  col-sm-12 align-self-center">
+
+The data frame used as input to build a stacked area chart requires 3 columns:
+
+- `x`: numeric variable used for the X axis, often it is a time.
+- `y`: numeric variable used for the Y axis. What are we looking at?
+- `group`: one shape will be done per group.
+
+The chart is built using the `geom_area()` function. 
+
+</div>
+
+
+<div class = "col-md-6  col-sm-12">
+
+```{r thecode, echo=FALSE, out.width = "100%", fig.height=6}
+# Packages
+library(ggplot2)
+library(dplyr)
+ 
+# create data
+time <- as.numeric(rep(seq(1,7),each=7))  # x Axis
+value <- runif(49, 10, 100)               # y Axis
+group <- rep(LETTERS[1:7],times=7)        # group, one shape per group
+data <- data.frame(time, value, group)
+
+# stacked area chart
+ggplot(data, aes(x=time, y=value, fill=group)) + 
+    geom_area()
+```
+</div>
+</div>
+
+
+
+```{r thecode, eval=FALSE}
+```
+
+
+
+
+
+
+
+
+
+
+
+
+# Control stacking order with `ggplot2`
+***
+
+<div class = "row">
+
+<div class = "col-md-6  col-sm-12 align-self-center">
+
+The gallery offers a post dedicated to [reordering with ggplot2](267-reorder-a-variable-in-ggplot2.html). This step can be tricky but the code below shows how to:
+
+- give a specific order with the `factor()` function.
+- order alphabetically using `sort()`
+- order following values at a specific data
+
+</div>
+
+
+<div class = "col-md-6  col-sm-12">
+
+```{r thecode2, echo=FALSE, out.width = "100%", fig.height=6}
+# Give a specific order:
+data$group <- factor(data$group , levels=c("B", "A", "D", "E", "G", "F", "C") )
+
+# Plot again
+ggplot(data, aes(x=time, y=value, fill=group)) + 
+    geom_area()
+
+# Note: you can also sort levels alphabetically:
+myLevels <- levels(data$group)
+data$group <- factor(data$group , levels=sort(myLevels) )
+
+# Note: sort followinig values at time = 5
+myLevels <- data %>%
+  filter(time==6) %>%
+  arrange(value)
+data$group <- factor(data$group , levels=myLevels$group )
+```
+</div>
+</div>
+
+
+
+```{r thecode2, eval=FALSE}
+```
+
+
+
+
+
+
+
+
+
+
+
+# Proportional stacked area chart
+***
+
+<div class = "row">
+
+<div class = "col-md-6  col-sm-12 align-self-center">
+
+In a proportional stacked area graph, the sum of each year is always equal to hundred and value of each group is represented through percentages. 
+
+To make it, you have to calculate these percentages first. This can be done using `dplyr` of with `base R`.
+
+</div>
+
+
+<div class = "col-md-6  col-sm-12">
+
+```{r thecode3, echo=FALSE, out.width = "100%", fig.height=6}
+# Compute percentages with dplyr
+library(dplyr)
+data <- data  %>%
+  group_by(time, group) %>%
+  summarise(n = sum(value)) %>%
+  mutate(percentage = n / sum(n))
+
+# Plot
+ggplot(data, aes(x=time, y=percentage, fill=group)) + 
+    geom_area(alpha=0.6 , size=1, colour="black")
+
+# Note: compute percentages without dplyr:
+my_fun <- function(vec){ 
+  as.numeric(vec[2]) / sum(data$value[data$time==vec[1]]) *100 
+}
+data$percentage <- apply(data , 1 , my_fun)
+
+```
+</div>
+</div>
+
+
+
+```{r thecode3, eval=FALSE}
+```
+
+
+
+
+
+
+
+
+
+
+
+
+# Color & Style
+***
+
+<div class = "row">
+
+<div class = "col-md-4  col-sm-12 align-self-center">
+
+Let's improve the chart general appearance:
+
+- usage of the `viridis` color scale
+- `theme_ipsum` of the `hrbrthemes` package
+- add title with `ggtitle` 
+
+
+</div>
+
+
+<div class = "col-md-6  col-sm-12">
+
+```{r thecode4, echo=FALSE, out.width = "100%", fig.height=5}
+# Library
+library(viridis)
+library(hrbrthemes)
+
+# Plot
+ggplot(data, aes(x=time, y=value, fill=group)) + 
+    geom_area(alpha=0.6 , size=.5, colour="white") +
+    scale_fill_viridis(discrete = T) +
+    theme_ipsum() + 
+    ggtitle("The race between ...")
+
+
+```
+</div>
+</div>
+
+
+
+```{r thecode4, eval=FALSE}
+```
+
+
+
+
+<!-- Close container -->
+</div>
+
+
+
+
+```{r, echo=FALSE}
+htmltools::includeHTML("htmlChunkRelatedMap.html")
+```