---
title: "Static timeline plots with gg_vistime()"
date: "`r format(Sys.Date(), '%B %Y')`"
output: 
   prettydoc::html_pretty:
     theme: architect
     highlight: github
     toc: true
vignette: >
  %\VignetteIndexEntry{Static timeline plots with gg_vistime()}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(vistime)
```

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**Feedback welcome:** <a href = "mailto:sa.ra.online@posteo.de">sa.ra.online@posteo.de</a>


## 1. Basic example

`gg_vistime()` produces **ggplot2** charts. For interactive **Plotly** output, see `vistime()`, for interactive **Highcharts** output, see `hc_vistime()`.

```{r gg_vistime_basic_ex, warning=FALSE, fig.width=5, fig.height=1.5}
timeline_data <- data.frame(event = c("Event 1", "Event 2"), 
                            start = c("2020-06-06", "2020-10-01"), 
                            end = c("2020-10-01", "2020-12-31"), 
                            group = "My Events")

gg_vistime(timeline_data)
```

## 2. Installation

To install the package from CRAN, type the following in your R console:

```{r eval=FALSE}
install.packages("vistime")
```

## 3. Usage and default arguments

The simplest way to create a timeline is by providing a data frame with `event` and `start` columns. If your columns are named otherwise, you need to tell the function using the `col.` arguments. You can also tweak the y positions, linewidth, title, label visibility and number of lines in the background.

```{r eval = FALSE}
gg_vistime(data, 
           col.event = "event", 
           col.start = "start", 
           col.end = "end", 
           col.group = "group", 
           col.color = "color", 
           col.fontcolor = "fontcolor",
           optimize_y = TRUE, 
           linewidth = NULL, 
           title = NULL, 
           show_labels = TRUE,
           background_lines = NULL)

```



## 4. Arguments

parameter | optional? | data type | explanation 
--------- |----------- | -------- | ----------- 
data | mandatory | data.frame | data.frame that contains the data to be visualized
col.event | optional | character | the column name in data that contains event names. Default: *event*
col.start | optional | character | the column name in data that contains start dates. Default: *start*
col.end | optional | character | the column name in data that contains end dates. Default: *end*
col.group | optional | character | the column name in data to be used for grouping. Default: *group*
col.color | optional | character | the column name in data that contains colors for events. Default: *color*, if not present, colors are chosen via RColorBrewer.
col.fontcolor | optional | character | the column name in data that contains the font color for event labels. Default: *fontcolor*, if not present, color will be black.
optimize_y | optional | logical | distribute events on y-axis by smart heuristic (default) or use order of input data.
linewidth | optional | numeric | override the calculated linewidth for events. Default: heuristic value.
title | optional | character | the title to be shown on top of the timeline. Default: empty.
show_labels | optional | logical | choose whether or not event labels shall be visible. Default: `TRUE`.
background_lines | optional | integer | the number of vertical lines to draw in the background to demonstrate structure. Default: 10.


## 5. Value

* `gg_vistime` returns an object of class `gg` and `ggplot`


## 6. Examples  

### Ex. 1: Presidents
```{r presidents example, fig.height = 2.5, fig.width=5}
pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'),
                   fontcolor = c("black", "white", "black"))
                  
gg_vistime(pres, col.event = "Position", col.group = "Name", title = "Presidents of the USA")
```


### Ex. 2: Project Planning
```{r project planning example, fig.height = 4.5, fig.width=10}
data <- read.csv(text="event,group,start,end,color
                       Phase 1,Project,2016-12-22,2016-12-23,#c8e6c9
                       Phase 2,Project,2016-12-23,2016-12-29,#a5d6a7
                       Phase 3,Project,2016-12-29,2017-01-06,#fb8c00
                       Phase 4,Project,2017-01-06,2017-02-02,#DD4B39
                       Room 334,Team 1,2016-12-22,2016-12-28,#DEEBF7
                       Room 335,Team 1,2016-12-28,2017-01-05,#C6DBEF
                       Room 335,Team 1,2017-01-05,2017-01-23,#9ECAE1
                       Group 1,Team 2,2016-12-22,2016-12-28,#E5F5E0
                       Group 2,Team 2,2016-12-28,2017-01-23,#C7E9C0
                       3-200,category 1,2016-12-25,2016-12-25,#1565c0
                       3-330,category 1,2016-12-25,2016-12-25,#1565c0
                       3-223,category 1,2016-12-28,2016-12-28,#1565c0
                       3-225,category 1,2016-12-28,2016-12-28,#1565c0
                       3-226,category 1,2016-12-28,2016-12-28,#1565c0
                       3-226,category 1,2017-01-19,2017-01-19,#1565c0
                       3-330,category 1,2017-01-19,2017-01-19,#1565c0
                       1-217.0,category 2,2016-12-27,2016-12-27,#90caf9
                       4-399.7,moon rising,2017-01-13,2017-01-13,#f44336
                       8-831.0,sundowner drink,2017-01-17,2017-01-17,#8d6e63
                       9-984.1,birthday party,2016-12-22,2016-12-22,#90a4ae
                       F01.9,Meetings,2016-12-26,2016-12-26,#e8a735
                       Z71,Meetings,2017-01-12,2017-01-12,#e8a735
                       B95.7,Meetings,2017-01-15,2017-01-15,#e8a735
                       T82.7,Meetings,2017-01-15,2017-01-15,#e8a735")
                           
gg_vistime(data)
```


### Ex. 3: Gantt Charts

The argument `optimize_y` can be used to change the look of the timeline. `TRUE` (the default) will find a nice heuristic to save `y`-space, distributing the events:

```{r gantt_true, fig.height = 2.3, fig.width=6}
data <- read.csv(text="event,start,end
                       Phase 1,2020-12-15,2020-12-24
                       Phase 2,2020-12-23,2020-12-29
                       Phase 3,2020-12-28,2021-01-06
                       Phase 4,2021-01-06,2021-02-02")
        
gg_vistime(data, optimize_y = TRUE, linewidth = 25)
```


`FALSE` will plot events as-is, not saving any space:

```{r gantt_false, fig.height = 3.7, fig.width=6}
gg_vistime(data, optimize_y = FALSE, linewidth = 25)
```


## 7. Export of vistime as PNG

Once created, you can use `ggplot2::ggsave()` for saving your vistime chart as PNG:

```{r eval=FALSE}
chart <- vistime(pres, col.event = "Position")
ggplot2::ggsave("presidents.png", timeline)
```

## 8. Usage in Shiny apps

- `gg_vistime()` objects can be integrated into Shiny via `plotOutput()` and `renderPlot()`


```{r eval=FALSE}
library(vistime)

pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'),
                   fontcolor = c("black", "white", "black"))

shinyApp(
  ui = plotOutput("myVistime"),
  server = function(input, output) {
    output$myVistime <- renderPlot({
      vistime(pres, col.event = "Position", col.group = "Name")
    })
  }
)
```

## 9. Customization

Since every `gg_vistime()` output is a `ggplot` object, you can customize and override literally everything:

```{r gg_customization, fig.height=2.5, fig.width=5, message=FALSE}
library(vistime)
data <- read.csv(text="event,start,end
                       Phase 1,2020-12-15,2020-12-24
                       Phase 2,2020-12-23,2020-12-29
                       Phase 3,2020-12-28,2021-01-06
                       Phase 4,2021-01-06,2021-02-02")
        
p <- gg_vistime(data, optimize_y = T, col.group = "event", title = "ggplot customization example")

library(ggplot2)
p + ggplot2::theme(
      plot.title = element_text(hjust = 0, size=10),
      axis.text.x = element_text(size = 10, color = "violet"),
      axis.text.y = element_text(size = 10, color = "red", angle = 30),
      panel.border = element_rect(linetype = "dashed", fill=NA),
      panel.background = element_rect(fill = 'green')) +
    coord_cartesian(ylim = c(0.7, 3.5))

```



