plotly

23 / 6 / 2018

library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

plot_ly(mtcars, x = mtcars$wt, y = mtcars$mpg, mode = "markers" )

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

color

plot_ly(mtcars, x = mtcars$wt, y = mtcars$mpg,
        mode = "markers",
        color = mtcars$cyl)

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

here we need the color to be factor

plot_ly(mtcars, x = mtcars$wt, y = mtcars$mpg,
        mode = "markers",
        color = as.factor(mtcars$cyl))

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

continuous colors

plot_ly(mtcars, x = mtcars$wt, y = mtcars$mpg,
        mode = "markers",
        color = mtcars$disp,
        size = mtcars$hp)

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

3d scatter plot

# webgl > opengl 
set.seed(2018-07-21)
temp <- rnorm(100, mean = 30, sd = 5)
pressure <- rnorm(100)
dtime <- 1:100
plot_ly(x = temp, y = pressure, z = dtime,
        type = "scatter3d", mode = "markers",
        color = temp)

line graphs

data("airmiles")
plot_ly(x = time(airmiles), y= airmiles, mode = "line")

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

## A line object has been specified, but lines is not in the mode
## Adding lines to the mode...

multi line graph

library(tidyr);
library(dplyr);

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

data("EuStockMarkets");
stocks <- as.data.frame(EuStockMarkets) %>%
  gather(index, price) %>%  # from short format to long format data needed for plotly
  mutate(time = rep(time(EuStockMarkets), 4));

plot_ly(stocks, x= stocks$time, y = stocks$price,
        color = stocks$index)

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter

## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode

some examples

plot_ly(x = precip, type ="histogram")

plot_ly(iris, y = iris$Petal.Length,
        color = iris$Species,
        type = "box")

terrain <- matrix(rnorm(100*100), nrow = 100, ncol = 100)
plot_ly(z = terrain, type = "heatmap") # must be z

terrain2 <- matrix(sort(rnorm(100*100)),
                   nrow = 100, ncol = 100)
map <- plot_ly(z = terrain2, type = "surface")

state_pop <- data.frame(State = state.abb,
                        Pop = as.vector(state.x77[,1]))
state_pop$hover <- with(state_pop,
                        paste(state_pop$State, '<br>',
                              "Population",
                              state_pop$Pop))

borders <- list (color = toRGB("red"))
map_options <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showlakes = TRUE,
  lakecolor = toRGB('white')
)
plot_ly(state_pop,
        z = state_pop$Pop,
        text = state_pop$hover,
        type = 'choropleth',
        locationmode = 'USA-states',
        color = state_pop$Pop,
        colors = 'Blues',
        marker = list(line = borders)) %>%
  layout(title = 'US Populationn in 1975',
         geo = map_options)

plotly and ggplot

library(ggplot2)
set.seed(100)
data("diamonds")
d <- diamonds[sample(nrow(diamonds), 1000),]
p <- ggplot(data = d,
            aes (x = d$carat ,
                 y = d$price)) +
  geom_point(aes(text = paste("Clarity:", d$clarity)),
             size = 4) +
  geom_smooth(aes( colour = d$cut, fill = d$cut )) +
  facet_wrap(~ d$cut)

## Warning: Ignoring unknown aesthetics: text

(gg <- ggplotly(p))

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : span too small. fewer data values than degrees of freedom.

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 1.3563

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.369e-05

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 1.3563

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.0037

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 1

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : at 2.1037

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : radius 1.369e-05

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : all data on boundary of neighborhood. make span bigger

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 1.369e-05

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : zero-width neighborhood. make span bigger

## Warning: Computation failed in `stat_smooth()`:
## NA/NaN/Inf in foreign function call (arg 5)

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : span too small. fewer data values than degrees of freedom.

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 0.8969

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.6031

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.00053361

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : span too small.
## fewer data values than degrees of freedom.

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 0.8969

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 0.6031

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 0.00053361

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : span too small. fewer data values than degrees of freedom.

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 0.3945

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 0.5055

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 0

## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 0.36663

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : span too small.
## fewer data values than degrees of freedom.

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 0.3945

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 0.5055

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 0

## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 0.36663