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https://shosaco.github.io/vistime/
Pretty timelines in R.
https://shosaco.github.io/vistime/
charts timelines
Last synced: 2 days ago
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Pretty timelines in R.
- Host: GitHub
- URL: https://shosaco.github.io/vistime/
- Owner: shosaco
- License: gpl-3.0
- Created: 2017-01-29T00:44:24.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2024-05-13T20:14:23.000Z (6 months ago)
- Last Synced: 2024-09-16T14:08:25.802Z (2 months ago)
- Topics: charts, timelines
- Language: R
- Homepage: https://shosaco.github.io/vistime
- Size: 8.53 MB
- Stars: 170
- Watchers: 12
- Forks: 11
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
# vistime - Pretty Timelines in R 
[](https://www.buymeacoffee.com/shosaco)
[](https://cran.r-project.org/package=vistime)
[](https://github.com/shosaco/vistime/actions)
[](https://www.r-pkg.org/pkg/vistime)
[](https://app.codecov.io/github/shosaco/vistime)
[](https://github.com/shosaco/vistime)
A library for creating time-based charts, like Gantt or timelines. Possible outputs include `ggplot`s, `plotly` graphs, `Highcharts` or data.frames. Results can be used in the RStudio viewer pane, in R Markdown documents or in Shiny apps. In the interactive outputs created by `vistime()` and `hc_vistime()` you can interact with the plot using mouse hover or zoom. Timelines and their components can afterwards be manipulated using `ggplot::theme()`, `plotly_build()` or `hc_*`functions (for `gg_vistime()`, `vistime()` or `hc_vistime()`, respectively). When choosing the `data.frame` output, you can use your own plotting package for visualizing the graph.
I'm glad if this can help people save time and effort, like this feedback suggests:
If you find vistime useful, please consider supporting its development: 
**Feedback welcome:** [[email protected]](mailto:[email protected])
## Table of Contents
1. [Installation](#1-installation)
2. [Main functionality](#2-main-functionality)
3. [Real-life example](#3-real-life-example)
3. [Usage and documentation](#4-usage-and-documentation)
## 1. Installation
To install the package from CRAN, type the following in your R console:
```r
install.packages("vistime")
```
## 2. Main functionality
This package `vistime` provides four main functions, the first three allow you to draw a timeline with Plotly, Highcharts or ggplot2, the last one
outputs the pure optimized data frame ready for plotting.
### vistime() - interactive `Plotly` charts
```r
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")
vistime(timeline_data)
```
### hc_vistime() - interactive `Highcharts` timelines
```r
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")
hc_vistime(timeline_data)
```
This is facilitated by the `highcharter` package, so, this package needs to be installed before attempting to produce any `hc_vistime()` output.
### gg_vistime() - static `ggplot2` output
```r
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)
```
### vistime_data() - pure `data.frame` output if you want to draw yourself
```r
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")
vistime_data(timeline_data)
#> event start end group tooltip col subplot y
#> 1 Event 1 2020-06-06 2020-10-01 My Events from 2020-06-06 to 2020-10-01 #8DD3C7 1 1
#> 2 Event 2 2020-10-01 2020-12-31 My Events from 2020-10-01 to 2020-12-31 #FFFFB3 1 1
```
You want to use this for the intelligent y-axis assignment depending on overlapping of events (this can be disabled with `optimize_y = FALSE`).
## 3. Real-life example
During COVID-19 2020, [@wlhamilton](https://github.com/wlhamilton) used `gg_vistime()` for visualizing patient ward movements as timelines in order to investigate possible hospital acquired infections. See [his github](https://github.com/wlhamilton/Patient-ward-movement-timelines) for the code.
## 4. Usage and documentation
There is a vignette for each of the three functions of the package where they are explained in detail:
- `vistime()` for interactive **Plotly** output: [Link to manual](https://CRAN.R-project.org/package=vistime/vignettes/vistime-vignette.html)
- `gg_vistime()` for static **ggplot2** output: [Link to manual](https://CRAN.R-project.org/package=vistime/vignettes/gg_vistime-vignette.html)
- `hc_vistime()` for interactive **Highcharts** output: [Link to manual](https://CRAN.R-project.org/package=vistime/vignettes/hc_vistime-vignette.html)