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‎r/2015-07-30-2D-Histogram.Rmd

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---
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name: 2D Histograms
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permalink: r/2D-Histogram/
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description: How to make a 2D histogram in R. A 2D histogram is a visualization of a bivariate distribution.
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layout: base
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thumbnail: thumbnail/histogram2d.jpg
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language: r
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page_type: example_index
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display_as: statistical
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order: 1
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output:
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html_document:
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keep_md: true
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---
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```{r, echo = FALSE, message=FALSE}
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knitr::opts_chunk$set(message = FALSE, warning=FALSE)
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```
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### New to Plotly?
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Plotly's R library is free and open source!<br>
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[Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
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You can set up Plotly to work in [online](https://plot.ly/r/getting-started/#hosting-graphs-in-your-online-plotly-account) or [offline](https://plot.ly/r/offline/) mode.<br>
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We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
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### Version Check
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Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
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Check out [this post](http://moderndata.plot.ly/upgrading-to-plotly-4-0-and-above/) for more information on breaking changes and new features available in this version.
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```{r}
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library(plotly)
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packageVersion('plotly')
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```
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#### Basic 2D Histogram
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2D histograms require `x`/`y`, but in contrast to heatmaps, `z` is optional. If `z` is not provided, binning occurs in the browser (see [here](https://plot.ly/r/reference/#histogram2d-histnorm) for a list of binning options).
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```{r}
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# install.packages('mvtnorm')
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library(plotly)
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s <- matrix(c(1, -.75, -.75, 1), ncol = 2)
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obs <- mvtnorm::rmvnorm(500, sigma = s)
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p <- plot_ly(x = obs[,1], y = obs[,2])
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pp <- subplot(
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p %>% add_markers(alpha = 0.2),
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p %>% add_histogram2d()
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)
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pp
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```
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#### Colorscale
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If `z` is not provided, the only way to control coloring is through the [colorscale attribute](https://plot.ly/r/reference/#histogram2d-colorscale)
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```{r}
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p <- p %>% add_histogram2d(colorscale = "Blues")
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p
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```
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#### Z Matrix
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If you want more control for the binning algorithm, you can supply a 2D table or matrix to `z`. In this case, the R package will impose it's colorscale default (and the `colors` argument can be used to control the colorscale from R):
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```{r}
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cnt <- with(diamonds, table(cut, clarity))
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p <- plot_ly(diamonds, x = ~cut, y = ~clarity, z = ~cnt) %>%
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add_histogram2d()
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p
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```

‎r/2015-07-30-LaTeX.Rmd

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---
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name: LaTeX Typesetting in R Graphs
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permalink: r/LaTeX/
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description: How to add LaTeX to R graphs.
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layout: base
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thumbnail: thumbnail/latex.jpg
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language: r
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page_type: example_index
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display_as: style_opt
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order: 4
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output:
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html_document:
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keep_md: true
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---
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```{r, echo = FALSE, message=FALSE}
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knitr::opts_chunk$set(message = FALSE, warning=FALSE)
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```
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### New to Plotly?
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Plotly's R library is free and open source!<br>
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[Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
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You can set up Plotly to work in [online](https://plot.ly/r/getting-started/#hosting-graphs-in-your-online-plotly-account) or [offline](https://plot.ly/r/offline/) mode.<br>
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We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
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### Version Check
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Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
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Check out [this post](http://moderndata.plot.ly/upgrading-to-plotly-4-0-and-above/) for more information on breaking changes and new features available in this version.
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```{r}
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library(plotly)
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packageVersion('plotly')
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```
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#### LaTeX Typesetting
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```{r}
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library(plotly)
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p <- plot_ly(
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x = c(1, 2, 3, 4),
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y = c(1, 4, 9, 16),
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name = TeX("\\alpha_{1c} = 352 \\pm 11 \\text{ km s}^{-1}")) %>%
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add_trace(
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x = c(1, 2, 3, 4),
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y = c(0.5, 2, 4.5, 8),
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name = TeX("\\beta_{1c} = 25 \\pm 11 \\text{ km s}^{-1}")) %>%
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layout(
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xaxis = list(
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title = TeX("\\sqrt{(n_\\text{c}(t|{T_\\text{early}}))}")),
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yaxis = list(
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title = TeX("d, r \\text{ (solar radius)}"))) %>%
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config(mathjax = 'cdn')
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p
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```
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#### Reference
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For more information about LaTeX, [click here](https://github.com/ropensci/plotly/blob/master/inst/examples/rmd/MathJax/index.Rmd).

‎r/2015-07-30-box-plots.Rmd

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---
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name: Box Plots
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permalink: r/box-plots/
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description: How to make an interactive box plot in R. Examples of box plots in R that are grouped, colored, and display the underlying data distribution.
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layout: base
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thumbnail: thumbnail/box.jpg
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language: r
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page_type: example_index
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display_as: statistical
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order: 2
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output:
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html_document:
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keep_md: true
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---
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```{r, echo = FALSE, message=FALSE}
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knitr::opts_chunk$set(message = FALSE, warning=FALSE)
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```
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### New to Plotly?
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Plotly's R library is free and open source!<br>
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[Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
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You can set up Plotly to work in [online](https://plot.ly/r/getting-started/#hosting-graphs-in-your-online-plotly-account) or [offline](https://plot.ly/r/offline/) mode.<br>
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We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
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### Version Check
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Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
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Check out [this post](http://moderndata.plot.ly/upgrading-to-plotly-4-0-and-above/) for more information on breaking changes and new features available in this version.
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```{r}
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library(plotly)
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packageVersion('plotly')
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```
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### Basic Boxplot
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```{r}
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library(plotly)
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p <- plot_ly(y = ~rnorm(50), type = "box") %>%
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add_trace(y = ~rnorm(50, 1))
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p
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```
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### Horizontal Boxplot
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```{r}
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library(plotly)
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p <- plot_ly(x = ~rnorm(50), type = "box") %>%
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add_trace(x = ~rnorm(50, 1))
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p
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```
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### Adding Jittered Points
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```{r}
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p <- plot_ly(y = ~rnorm(50), type = "box", boxpoints = "all", jitter = 0.3,
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pointpos = -1.8)
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p
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```
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### Several Box Plots
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```{r}
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p <- plot_ly(ggplot2::diamonds, y = ~price, color = ~cut, type = "box")
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p
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```
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### Grouped Box Plots
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```{r}
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p <- plot_ly(ggplot2::diamonds, x = ~cut, y = ~price, color = ~clarity, type = "box") %>%
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layout(boxmode = "group")
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p
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```
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### Styling Outliers
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```{r}
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library(plotly)
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y1 <- c(0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
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8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25)
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y2 <- c(0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
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8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25)
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y3 <- c(0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
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8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25)
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y4 <- c(0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
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8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25)
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p <- plot_ly(type = 'box') %>%
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add_boxplot(y = y1, jitter = 0.3, pointpos = -1.8, boxpoints = 'all',
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marker = list(color = 'rgb(7,40,89)'),
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line = list(color = 'rgb(7,40,89)'),
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name = "All Points") %>%
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add_boxplot(y = y2, name = "Only Whiskers", boxpoints = FALSE,
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marker = list(color = 'rgb(9,56,125)'),
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line = list(color = 'rgb(9,56,125)')) %>%
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add_boxplot(y = y3, name = "Suspected Outlier", boxpoints = 'suspectedoutliers',
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marker = list(color = 'rgb(8,81,156)',
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outliercolor = 'rgba(219, 64, 82, 0.6)',
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line = list(outliercolor = 'rgba(219, 64, 82, 1.0)',
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outlierwidth = 2)),
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line = list(color = 'rgb(8,81,156)')) %>%
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add_boxplot(y = y4, name = "Whiskers and Outliers", boxpoints = 'outliers',
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marker = list(color = 'rgb(107,174,214)'),
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line = list(color = 'rgb(107,174,214)')) %>%
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layout(title = "Box Plot Styling Outliers")
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p
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```
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### Reference
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See [https://plot.ly/r/reference/#box](https://plot.ly/r/reference/#box) for more information and chart attribute options!

‎r/2015-07-30-histograms.Rmd

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---
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name: Histograms
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permalink: r/histograms/
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description: How to make a histogram in R.
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layout: base
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thumbnail: thumbnail/histogram.jpg
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language: r
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page_type: example_index
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display_as: statistical
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order: 3
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output:
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html_document:
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keep_md: true
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---
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```{r, echo = FALSE, message=FALSE}
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knitr::opts_chunk$set(message = FALSE, warning=FALSE)
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```
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### New to Plotly?
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Plotly's R library is free and open source!<br>
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[Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
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You can set up Plotly to work in [online](https://plot.ly/r/getting-started/#hosting-graphs-in-your-online-plotly-account) or [offline](https://plot.ly/r/offline/) mode.<br>
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We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
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### Version Check
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Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
29+
Check out [this post](http://moderndata.plot.ly/upgrading-to-plotly-4-0-and-above/) for more information on breaking changes and new features available in this version.
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```{r}
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library(plotly)
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packageVersion('plotly')
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```
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#### Basic Histogram
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```{r}
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library(plotly)
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p <- plot_ly(x = ~rnorm(50), type = "histogram")
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p
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```
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#### Normalized Histogram
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```{r}
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library(plotly)
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p <- plot_ly(x = ~rnorm(50),
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type = "histogram",
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histnorm = "probability")
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p
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```
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#### Specify Binning Function
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```{r}
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library(plotly)
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x = c("Apples","Apples","Apples","Organges", "Bananas")
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y = c("5","10","3","10","5")
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p <- plot_ly(y=y, x=x, histfunc='sum', type = "histogram") %>%
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layout(yaxis=list(type='linear'))
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p
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```
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#### Horizontal Histogram
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```{r}
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library(plotly)
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p <- plot_ly(y = ~rnorm(50), type = "histogram")
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p
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```
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#### Overlaid Histograms
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```{r}
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p <- plot_ly(alpha = 0.6) %>%
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add_histogram(x = ~rnorm(500)) %>%
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add_histogram(x = ~rnorm(500) + 1) %>%
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layout(barmode = "overlay")
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p
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```
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#### Stacked Histograms
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```{r}
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p <- plot_ly(alpha = 0.6) %>%
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add_histogram(x = ~rnorm(500)) %>%
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add_histogram(x = ~rnorm(500) + 1) %>%
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layout(barmode = "overlay")
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p
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```
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#### Cumulative Histogram
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```{r}
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library(plotly)
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p <- plot_ly(x = ~rnorm(50),
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type = "histogram",
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cumulative = list(enabled=TRUE))
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p
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```
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### Reference
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See [https://plot.ly/r/reference/#histogram](https://plot.ly/r/reference/#histogram) for more information and chart attribute options!

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