8000 Merge pull request #51 from plotly/plotlyjs1-54-docs-update · plotly/plotly.r-docs@411c402 · GitHub
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Merge pull request #51 from plotly/plotlyjs1-54-docs-update
Plotlyjs1 54 docs update
2 parents e70b753 + ec5a8ce commit 411c402

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‎.circleci/config.yml

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name: install application-level dependencies
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command: |
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sudo apt-get install -y pandoc libudunits2-dev libgdal-dev libxt-dev libglu1-mesa-dev libfftw3-dev
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sudo R -e 'install.packages(c("plotly", "curl", "devtools", "mvtnorm")); devtools::install_github("hypertidy/anglr"); devtools::install_github("johannesbjork/LaCroixColoR"); install.packages("BiocManager"); BiocManager::install("EBImage"); devtools::install_deps(dependencies = TRUE) '
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sudo R -e 'install.packages(c("curl", "devtools", "mvtnorm")); devtools::install_github("hypertidy/anglr"); devtools::install_github("ropensci/plotly"); devtools::install_github("johannesbjork/LaCroixColoR"); install.packages("BiocManager"); BiocManager::install("EBImage"); devtools::install_deps(dependencies = TRUE) '
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- save_cache:
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key: cache4
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paths:

‎r/2015-07-30-time-series.Rmd

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fig
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```
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### Hiding Weekends and Holidays
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The `rangebreaks` attribute available on x- and y-axes of type date can be used to hide certain time-periods. In the example below, we show two plots: one in default mode to show gaps in the data, and one where we hide weekends and holidays to show an uninterrupted trading history. Note the smaller gaps between the grid lines for December 21 and January 4, where holidays were removed. Check out the reference for more options: https://plotly.com/r/reference/#layout-xaxis-rangebreaks
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```{r}
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library(plotly)
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df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
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fig <- plot_ly(
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type = "scatter",
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x = as.Date(df$Date, format= "%Y-%m-%d"),
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y = df$AAPL.High,
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name = 'AAPL High',
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mode = "markers",
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)
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fig <- fig %>%
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layout(
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title = "Time Series with Custom Date-Time Format",
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xaxis = list(
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type = "date",
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range=c('2015-12-01', '2016-01-15')
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)
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)
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fig
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```
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```{r}
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library(plotly)
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df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
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fig <- plot_ly(
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type = "scatter",
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x = as.Date(df$Date, format= "%Y-%m-%d"),
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y = df$AAPL.High,
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name = 'AAPL High',
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mode = "markers",
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)
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fig <- fig %>%
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layout(
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title = "Time Series with Custom Date-Time Format",
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xaxis = list(
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type = "date",
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range=c('2015-12-01', '2016-01-15'),
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rangebreaks = list(
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list(bounds=c("sat", "mon")),
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list(values=c("2015-12-25", "2016-01-01"))
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)
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)
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)
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fig
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```
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### POSIXlt date time class with timezone
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```{r}

‎r/2015-11-19-shapes.Rmd

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fig
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```
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### Drawing Shapes on Cartesian Plots
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You can create layout shapes programatically, but you can also draw shapes manually by setting the `dragmode` to one of the shape-drawing modes: `drawline`,`drawopenpath`, `drawclosedpath`, `drawcircle`, or `drawrect`. If you need to switch between different shape-drawing or other dragmodes (panning, selecting, etc.), modebar buttons can be added in the `config` of your figure to select the dragmode.
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If you switch to a different dragmode such as pan or zoom, you will need to select the drawing tool in the modebar to go back to shape drawing.
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This shape-drawing feature is particularly interesting for annotating graphs, in particular [image traces](https://plotly.com/r/displaying-images/#drawing-shapes-on-images).
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Once you have drawn shapes, you can select and modify an existing shape by clicking on its boundary (note the arrow pointer). Its fillcolor turns to pink to highlight the activated shape and then you can
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- drag and resize it for lines, rectangles and circles/ellipses
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- drag and move individual vertices for closed paths
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- move individual vertices for open paths.
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An activated shape is deleted by cliking on the `eraseshape` button.
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Drawing or modifying a shape triggers a `relayout` event, which [can be captured by a callback inside a Dash For R application](https://dash.plotly.com/interactive-graphing).
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```{r}
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library(plotly)
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df <- diamonds[sample(nrow(diamonds), 1000), ]
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fig <- plot_ly(df, x = ~carat, y = ~price, text = ~paste("Clarity: ", clarity),
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mode = "markers", color = ~carat, size = ~carat)
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fig <- layout(fig, dragmode="drawrect", xaxis = list(title = 'Click and drag inside the figure to draw a rectangle or select another shape in the modebar'))
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fig <- fig %>%
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config(modeBarButtonsToAdd = list("drawine", "drawopenpath", "drawclosedpath", "drawcircle", "drawrect", "eraseshape" ) )
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fig
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```
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### Style of user-drawn shapes
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The layout `newshape` attribute controls the visual appearance of new shapes drawn by the user. `newshape` attributes have the same names as layout shapes.
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Note on shape opacity: having a new shape's opacity > 0.5 makes it possible to activate a shape by clicking inside the shape (for opacity <= 0.5 you have to click on the border of the shape), but you cannot start a new shape within an existing shape (which is possible for an opacity <= 0.5).
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```{r}
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library(plotly)
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df <- diamonds[sample(nrow(diamonds), 1000), ]
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fig <- plot_ly(df, x = ~carat, y = ~price, text = ~paste("Clarity: ", clarity),
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mode = "markers", color = ~carat, size = ~carat)
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fig <- layout(fig, dragmode="drawrect", newshape=list(fillcolor="yellow", opacity=0.5), xaxis = list(title = 'Click and drag inside the figure to draw a rectangle or select another shape in the modebar'))
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fig <- fig %>%
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config(modeBarButtonsToAdd = list("drawine", "drawopenpath", "drawclosedpath", "drawcircle", "drawrect", "eraseshape" ) )
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fig
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```
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### Reference
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Check out our <b>[reference page](https://plotly.com/r/reference/#layout-shapes)</b> for more information on using shapes!

‎r/2018-01-29-hover-text-and-formatting.Rmd

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fig
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```
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#### Unified hovermode
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If you set the `hovermode` attribute of your figure's layout to `x unified` or `y unified`), a single hover label will appear, describing one point per trace, for points at the same x (or y) value as the cursor.
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If multiple points in a given trace exist at the same coordinate, only one will get an entry in the hover label. In the line plot below we have forced markers to appear, to make it clearer what can be hovered over:
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```{r}
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library(plotly)
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trace_0 <- rnorm(100, mean = 5)
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trace_1 <- rnorm(100, mean = 0)
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trace_2 <- rnorm(100, mean = -5)
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x <- c(1:100)
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data <- data.frame(x, trace_0, trace_1, trace_2)
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fig <- plot_ly(data, x = ~x, y = ~trace_0, name = 'trace 0', type = 'scatter', mode = 'lines')
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fig <- fig %>% add_trace(y = ~trace_1, name = 'trace 1', mode = 'lines+markers')
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fig <- fig %>% add_trace(y = ~trace_2, name = 'trace 2', mode = 'markers')
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fig <- fig %>%
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layout(hovermode = "x unified")
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fig
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```
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#### Format Hover Text
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```{r}

‎r/2020-02-25-images.Rmd

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fig
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```
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### Drawing Shapes on Images
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You can create layout shapes programatically, but you can also draw shapes manually by setting the `dragmode` to one of the shape-drawing modes: `drawline`,`drawopenpath`, `drawclosedpath`, `drawcircle`, or `drawrect`. If you need to switch between different shape-drawing or other dragmodes (panning, selecting, etc.), modebar buttons can be added in the `config` of your figure to select the dragmode.
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If you switch to a different dragmode such as pan or zoom, you will need to select the drawing tool in the modebar to go back to shape drawing.
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This shape-drawing feature is particularly interesting for annotating graphs, in particular [image traces](https://plotly.com/r/displaying-images/).
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Once you have drawn shapes, you can select and modify an existing shape by clicking on its boundary (note the arrow pointer). Its fillcolor turns to pink to highlight the activated shape and then you can
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- drag and resize it for lines, rectangles and circles/ellipses
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- drag and move individual vertices for closed paths
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- move individual vertices for open paths.
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An activated shape is deleted by cliking on the `eraseshape` button.
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Drawing or modifying a shape triggers a `relayout` event, which [can be captured by a callback inside a Dash For R application](https://dash.plotly.com/interactive-graphing).
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```{r}
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library(plotly)
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library(plotly)
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library(EBImage)
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img = readImage('https://upload.wikimedia.org/wikipedia/commons/thumb/0/00/Crab_Nebula.jpg/240px-Crab_Nebula.jpg')
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fig <- plot_ly(type="image", z=img*255)
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fig <- layout(fig, dragmode="drawrect", xaxis = list(title = 'Click and drag inside the figure to draw a rectangle or select another shape in the modebar'))
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fig <- fig %>%
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config(modeBarButtonsToAdd = list("drawine", "drawopenpath", "drawclosedpath", "drawcircle", "drawrect", "eraseshape" ) )
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fig
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```
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### Reference
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See [https://plotly.com/r/reference/#image](https://plotly.com/r/reference/#area) for more information and chart attribute options!

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