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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.\n\nI'm glad if this can help people save time and effort, like this feedback suggests:\n\n![grafik](https://github.com/shosaco/vistime/assets/20717764/2af48992-6285-493a-8f4d-d5bb6e991b67)\n\nIf you find vistime useful, please consider supporting its development: \u003ca href=\"https://www.buymeacoffee.com/shosaco\" target=\"_blank\"\u003e\u003cimg src=\"https://i.imgur.com/kN1GxnC.png\" alt=\"Buy Me A Coffee\"\u003e\u003c/a\u003e\n\n\n**Feedback welcome:** [sa.ra.online@posteo.de](mailto:sa.ra.online@posteo.de)\n\n## Table of Contents\n\n1. [Installation](#1-installation)\n2. [Main functionality](#2-main-functionality)\n3. [Real-life example](#3-real-life-example)\n3. [Usage and documentation](#4-usage-and-documentation)\n\n\n## 1. Installation\n\nTo install the package from CRAN, type the following in your R console:\n\n```r\ninstall.packages(\"vistime\")\n```\n\n\u003c!--\nTo install the development version containing most recent fixes and improvements, but not released on CRAN yet, see NEWS.md), run the following code in an R console:\n\n```{r}\nif (!require(\"remotes\")) install.packages(\"remotes\")\nremotes::install_github(\"shosaco/vistime\")\n```\n\n--\u003e\n\n## 2. Main functionality\n\nThis package `vistime` provides four main functions, the first three allow you to draw a timeline with Plotly, Highcharts or ggplot2, the last one \noutputs the pure optimized data frame ready for plotting.\n\n### vistime() - interactive `Plotly` charts\n\n```r\ntimeline_data \u003c- data.frame(event = c(\"Event 1\", \"Event 2\"),\n                            start = c(\"2020-06-06\", \"2020-10-01\"), \n                            end   = c(\"2020-10-01\", \"2020-12-31\"),\n                            group = \"My Events\")\n                            \nvistime(timeline_data)\n```\n\n\u003cimg src=\"man/figures/basic_plotly.png\" /\u003e\n\n\n### hc_vistime() - interactive `Highcharts` timelines\n\n```r\ntimeline_data \u003c- data.frame(event = c(\"Event 1\", \"Event 2\"),\n                            start = c(\"2020-06-06\", \"2020-10-01\"), \n                            end   = c(\"2020-10-01\", \"2020-12-31\"),\n                            group = \"My Events\")\n                            \nhc_vistime(timeline_data)\n```\n\n\u003cimg src=\"man/figures/basic_highchart.png\" /\u003e\n\nThis is facilitated by the `highcharter` package, so, this package needs to be installed before attempting to produce any `hc_vistime()` output.\n\n### gg_vistime() - static `ggplot2` output\n\n```r\ntimeline_data \u003c- data.frame(event = c(\"Event 1\", \"Event 2\"),\n                            start = c(\"2020-06-06\", \"2020-10-01\"), \n                            end   = c(\"2020-10-01\", \"2020-12-31\"),\n                            group = \"My Events\")\n                            \ngg_vistime(timeline_data)\n```\n\u003cimg src=\"man/figures/basic_ggplot.png\" /\u003e\n\n### vistime_data() - pure `data.frame` output if you want to draw yourself\n\n```r\ntimeline_data \u003c- data.frame(event = c(\"Event 1\", \"Event 2\"),\n                            start = c(\"2020-06-06\", \"2020-10-01\"), \n                            end   = c(\"2020-10-01\", \"2020-12-31\"),\n                            group = \"My Events\")\n                            \nvistime_data(timeline_data)\n\n#\u003e     event      start        end     group                                      tooltip      col subplot   y\n#\u003e 1 Event 1 2020-06-06 2020-10-01 My Events  from \u003cb\u003e2020-06-06\u003c/b\u003e to \u003cb\u003e2020-10-01\u003c/b\u003e  #8DD3C7       1   1\n#\u003e 2 Event 2 2020-10-01 2020-12-31 My Events  from \u003cb\u003e2020-10-01\u003c/b\u003e to \u003cb\u003e2020-12-31\u003c/b\u003e  #FFFFB3       1   1\n```\n\nYou want to use this for the intelligent y-axis assignment depending on overlapping of events (this can be disabled with `optimize_y = FALSE`).\n\n\n## 3. Real-life example\n\nDuring 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.\n\n\u003cimg src=\"man/figures/ward_movements.png\" width=\"500\" height=\"283\"/\u003e\n\n## 4. Usage and documentation\n\nThere is a vignette for each of the three functions of the package where they are explained in detail:\n\n- `vistime()` for interactive **Plotly** output: [Link to manual](https://CRAN.R-project.org/package=vistime/vignettes/vistime-vignette.html)\n- `gg_vistime()` for static **ggplot2** output: [Link to manual](https://CRAN.R-project.org/package=vistime/vignettes/gg_vistime-vignette.html)\n- `hc_vistime()` for interactive **Highcharts** output: [Link to manual](https://CRAN.R-project.org/package=vistime/vignettes/hc_vistime-vignette.html)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshosaco%2Fvistime","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshosaco%2Fvistime","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshosaco%2Fvistime/lists"}