---
title: "Overview"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{overview}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 6,
  fig.align = "center"
)
```

Use ezplot to quickly create presentation-ready charts that are also useful for
exploratory data analysis. By default, ezplot functions aggregate multiple 
values of y for repeated categories of x, group, facet_y and facet_x.

```{r setup}
library(ezplot)
suppressPackageStartupMessages(library(tsibble))
library(tsibbledata)
suppressPackageStartupMessages(library(lubridate))
library(ggplot2)
library(grid)
```

### line_plot
Weekly aggregation:
```{r}
line_plot(ansett, x = "Week", y = "Passengers")
```

Add grouping:
```{r}
line_plot(ansett, x = "Week", y = "Passengers", group = "Class")
```

Add faceting:
```{r, fig.width = 7, fig.height = 6}
line_plot(ansett, x = "Week", y = "Passengers",
          group = "Class", facet_x = "Airports",
          facet_scales = "free_y", size = 10) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.38, hjust = 1))
```

Plot YOY comparisons:
```{r, fig.height = 5}
line_plot(gafa_stock, "Date", c("Closing Stock Price" = "Close"),
          facet_y = "Symbol",
          facet_scales = "free_y",
          yoy = TRUE,
          labels = function(x) ez_labels(x, prepend = "$"))
```

Plot multiple numeric columns:
```{r, fig.width = 7, fig.height = 5}
line_plot(hh_budget,
          "Year",
          c("DI", "Expenditure", "Savings"),
          facet_x = "Country") +
  theme(panel.spacing.x = unit(1, "lines")) +
  ylab(NULL)
  
```

### area_plot
Weekly aggregation:
```{r}
area_plot(ansett, x = "as.Date(Week)", y = "Passengers")
```

Add grouping:
```{r}
area_plot(ansett, x = "as.Date(Week)",
          y = c("Weekly Passengers" = "Passengers"),
          "Class")
```

Add faceting:
```{r, fig.width = 7, fig.height = 4}
area_plot(ansett,
          "year(Week) + (month(Week) - 1) / 12",
          y = c("Monthly Passengers" = "Passengers"),
          group = "substr(Airports, 5, 7)",
          facet_x = "substr(Airports, 1, 3)", facet_y = "Class",
          facet_scales = "free_y") +
          theme(axis.text.x = element_text(angle = 90, vjust = 0.38, hjust = 1))
```

### bar_plot
Yearly aggregation
```{r}
bar_plot(subset(aus_retail, year(Month) >= 2010), 
         x = "year(Month)",
         y = "Turnover")
```

With grouping:
```{r, fig.width = 7, fig.height = 4}
bar_plot(subset(aus_retail, year(Month) >= 2010), 
         x = "year(Month)",
         y = "Turnover",
         group = "State",
         size = 10)
```