plotting-time-series-data-with-ggplot2.Rmd

---
title: Plotting time series data with ggplot2
output: 
  html_document :
    toc: true
    theme: united
    toc_float: true
---
The original version of this article has been published at [sthda.com](http://www.sthda.com/english/articles/32-r-graphics-essentials/128-plot-time-series-data-using-ggplot).

In this chapter, we start by describing how to plot simple and multiple time series data using the R function geom_line() [in ggplot2].

Next, we show how to set date axis limits and add trend smoothed line to a time series graphs. Finally, we introduce some extensions to the ggplot2 package for easily handling and analyzing time series objects.

Additionally, you’ll learn how to detect peaks (maxima) and valleys (minima) in time series data.

```{r}
library(ggplot2)
theme_set(theme_minimal())

# Demo dataset
str(economics)
```

# Basic line plot
```{r}
ggplot(data = economics, aes(x = date, y = pop))+
  geom_line(color = "#00AFBB", size = 2)
```

# Plot a subset of the data
```{r}
ss <- subset(economics, date > as.Date("2006-1-1"))
ggplot(data = ss, aes(x = date, y = pop)) + 
  geom_line(color = "#FC4E07", size = 2)
```

To control line size by the value of a continuous variable:
```{r}
ggplot(data = economics, aes(x = date, y = pop)) +
  geom_line(aes(size = unemploy/pop), color = "#FC4E07")
```

# Plot multiple time series data
Here, we’ll plot the variables psavert and uempmed by dates. You should first reshape the data using the tidyr package: - Collapse psavert and uempmed values in the same column (new column). R function: gather()[tidyr] - Create a grouping variable that with levels = psavert and uempmed
```{r}
library(tidyr)
library(dplyr)
df <- economics %>%
  select(date, psavert, uempmed) %>%
  gather(key = "variable", value = "value", -date)
str(df)
```
```{r}
# Multiple line plot
ggplot(df, aes(x = date, y = value)) + 
  geom_line(aes(color = variable), size = 1) +
  scale_color_manual(values = c("#00AFBB", "#E7B800")) +
  theme_minimal()
```