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Wrap all code blocks to at most 57 columns in plotly.Rmd #10

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Wrap all code blocks to at most 57 columns in plotly.Rmd #10

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72 changes: 47 additions & 25 deletions plotly/plotly.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -50,27 +50,31 @@ You can add color to your scatterplot points according to a categorical variable
in the data frame you use with `plot_ly()`.

```{r, eval=FALSE}
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter", color = ~factor(cyl))
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter",
color = ~factor(cyl))
```

## Scatterplot Color

```{r, echo=FALSE, message=FALSE}
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter", color = ~factor(cyl))
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter",
color = ~factor(cyl))
```

## Continuous Color

You can also show continuous variables with color in scatterplots.

```{r, eval=FALSE}
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter", color = ~disp)
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter",
color = ~disp)
```

## Continuous Color

```{r, echo=FALSE, message=FALSE}
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter", color = ~disp)
plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter",
color = ~disp)
```

## Scatterplot Sizing
Expand Down Expand Up @@ -123,14 +127,16 @@ showing change over time:

```{r, eval=FALSE}
data("airmiles")
plot_ly(x = ~time(airmiles), y = ~airmiles, type = "scatter", mode = "lines")
plot_ly(x = ~time(airmiles), y = ~airmiles,
type = "scatter", mode = "lines")
```

## Line Graph

```{r, echo=FALSE, message=FALSE}
data("airmiles")
plot_ly(x = ~time(airmiles), y = ~airmiles, type = "scatter", mode = "lines")
plot_ly(x = ~time(airmiles), y = ~airmiles,
type = "scatter", mode = "lines")
```

## Multi Line Graph
Expand All @@ -148,7 +154,8 @@ stocks <- as.data.frame(EuStockMarkets) %>%
gather(index, price) %>%
mutate(time = rep(time(EuStockMarkets), 4))

plot_ly(stocks, x = ~time, y = ~price, color = ~index, type = "scatter", mode = "lines")
plot_ly(stocks, x = ~time, y = ~price, color = ~index,
type = "scatter", mode = "lines")
```

## Multi Line Graph
Expand All @@ -163,7 +170,8 @@ stocks <- as.data.frame(EuStockMarkets) %>%
gather(index, price) %>%
mutate(time = rep(time(EuStockMarkets), 4))

plot_ly(stocks, x = ~time, y = ~price, color = ~index, type = "scatter", mode = "lines")
plot_ly(stocks, x = ~time, y = ~price, color = ~index,
type = "scatter", mode = "lines")
```

## Histogram
Expand All @@ -187,13 +195,15 @@ Boxplots are wonderful for comparing how different datasets are distributed.
Specify `type = "box"` to create a boxplot.

```{r, eval=FALSE}
plot_ly(iris, y = ~Petal.Length, color = ~Species, type = "box")
plot_ly(iris, y = ~Petal.Length, color = ~Species,
type = "box")
```

## Boxplot

```{r, echo=FALSE, message=FALSE}
plot_ly(iris, y = ~Petal.Length, color = ~Species, type = "box")
plot_ly(iris, y = ~Petal.Length, color = ~Species,
type = "box")
```

## Heatmap
Expand All @@ -220,14 +230,16 @@ Why limit yourself to two dimensions when you can render three dimensions on a
computer!? Create moveable 3D surfaces with `type = "surface"`.

```{r, eval=FALSE}
terrain2 <- matrix(sort(rnorm(100*100)), nrow = 100, ncol = 100)
terrain2 <- matrix(sort(rnorm(100*100)), nrow = 100,
ncol = 100)
plot_ly(z = ~terrain2, type = "surface")
```

## 3D Surface

```{r, echo=FALSE, message=FALSE}
terrain2 <- matrix(sort(rnorm(100*100)), nrow = 100, ncol = 100)
terrain2 <- matrix(sort(rnorm(100*100)), nrow = 100,
ncol = 100)
plot_ly(z = ~terrain2, type = "surface")
```

Expand All @@ -239,9 +251,11 @@ require more setup compared to other Plotly graphics.

```{r, eval=FALSE}
# Create data frame
state_pop <- data.frame(State = state.abb, Pop = as.vector(state.x77[,1]))
state_pop <- data.frame(State = state.abb,
Pop = as.vector(state.x77[,1]))
# Create hover text
state_pop$hover <- with(state_pop, paste(State, '<br>', "Population:", Pop))
state_pop$hover <- with(state_pop, paste(State, '<br>',
"Population:", Pop))
# Make state borders white
borders <- list(color = toRGB("red"))
# Set up some mapping options
Expand All @@ -256,19 +270,24 @@ map_options <- list(
## Choropleth Maps: Mapping

```{r, eval=FALSE}
plot_ly(z = ~state_pop$Pop, text = ~state_pop$hover, locations = ~state_pop$State,
type = 'choropleth', locationmode = 'USA-states',
color = state_pop$Pop, colors = 'Blues', marker = list(line = borders)) %>%
layout(title = 'US Population in 1975', geo = map_options)
plot_ly(z = ~state_pop$Pop, text = ~state_pop$hover,
locations = ~state_pop$State,
type = 'choropleth', locationmode = 'USA-states',
color = state_pop$Pop, colors = 'Blues',
marker = list(line = borders)) %>%
layout(title = 'US Population in 1975',
geo = map_options)
```

## Choropleth Maps

```{r, echo=FALSE, message=FALSE}
# Create data frame
state_pop <- data.frame(State = state.abb, Pop = as.vector(state.x77[,1]))
state_pop <- data.frame(State = state.abb,
Pop = as.vector(state.x77[,1]))
# Create hover text
state_pop$hover <- with(state_pop, paste(State, '<br>', "Population:", Pop))
state_pop$hover <- with(state_pop,
paste(State, '<br>', "Population:", Pop))
# Make state borders white
borders <- list(color = toRGB("red"))
# Set up some mapping options
Expand All @@ -279,10 +298,13 @@ map_options <- list(
lakecolor = toRGB('white')
)

plot_ly(z = ~state_pop$Pop, text = ~state_pop$hover, locations = ~state_pop$State,
type = 'choropleth', locationmode = 'USA-states',
color = state_pop$Pop, colors = 'Blues', marker = list(line = borders)) %>%
layout(title = 'US Population in 1975', geo = map_options)
plot_ly(z = ~state_pop$Pop, text = ~state_pop$hover,
locations = ~state_pop$State,
type = 'choropleth', locationmode = 'USA-states',
color = state_pop$Pop, colors = 'Blues',
marker = list(line = borders)) %>%
layout(title = 'US Population in 1975',
geo = map_options)
```

## More Resources
Expand All @@ -291,4 +313,4 @@ plot_ly(z = ~state_pop$Pop, text = ~state_pop$hover, locations = ~state_pop$Stat
- [The Plotly R API](https://plot.ly/r/)
- [The Plotly R Package on GitHub](https://github.com/ropensci/plotly)
- [The Plotly R Cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf)
- ["Plotly for R" book by Carson Sievert](https://cpsievert.github.io/plotly_book/)
- ["Plotly for R" book by Carson Sievert](https://cpsievert.github.io/plotly_book/)