数据可视化-plotly_scatter

R语言数据可视化包：

• 1、ggplot2
• 2、rCharts
• 3、recharts
• 4、plotly
• 5、networkD3,igraph
• 6、REmap

knitr::opts_chunk$set(echo = TRUE, eval = TRUE, tidy = TRUE, highlight = TRUE, warning = FALSE, error = FALSE, message = FALSE, include = TRUE,fig.width = 9.4,fig.height = 4)

安装包

require(devtools)
# install_github('rCharts', 'ramnathv') install_github('yihui/recharts')
# install.packages('plotly') install_github('Lchiffon/REmap')
# install.packages('igraph') install.packages('networkD3')
library(plotly)

用法：

• plot_ly(df, type=“scatter”[, …])
• add_trace(p, type=“scatter”[, …])

设置散点图标记的样式

str(iris)

## 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

p0 <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, showlegend = FALSE)

p1 <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, showlegend = FALSE, 
    marker = list(size = 10, color = "lightblue", line = list(color = "black", 
        width = 2))) %>% layout(title = "Styled Scatter", yaxis = list(zeroline = FALSE), 
    xaxis = list(zeroline = FALSE))
subplot(p0, p1, nrows = 1, margin = 0.05)

绘制标记和线

library(plotly)

trace_0 <- rnorm(100, mean = 5)
trace_1 <- rnorm(100, mean = 0)
trace_2 <- rnorm(100, mean = -5)
x <- c(1:100)

data <- data.frame(x, trace_0, trace_1, trace_2)

p <- plot_ly(data, x = ~x) %>% add_trace(y = ~trace_0, type = "scatter", name = "node = 'lines'", 
    mode = "lines") %>% add_trace(y = ~trace_1, type = "scatter", name = "node = 'lines+markers'", 
    mode = "lines+markers") %>% add_trace(y = ~trace_2, type = "scatter", name = "node = 'markers'", 
    mode = "markers", marker = list(size = 10, color = "white", line = list(color = "black", 
        width = 2)))
p

将不同的分类数据映射到颜色

plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species)

使用调色板的颜色

plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, 
    colors = "Set1")

使用自定义颜色

pal <- c("red", "blue", "green")
plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, 
    colors = pal)

为了确保特定的数据值被映射到特定颜色，提供颜色代码的字符向量，并相应地匹配名称属性。

pal <- c("red", "blue", "green")
pal <- setNames(pal, c("virginica", "setosa", "versicolor"))

p <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, 
    colors = pal)

将不同的分类数据映射到形状符号

plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, type = "scatter", 
    mode = "markers", symbol = ~Species, symbols = c("circle", "x", "o"), color = I("black"), 
    marker = list(size = 10))

添加颜色和大小的映射

library(ggplot2)
d <- diamonds[base::sample(nrow(diamonds), 1000), ]

plot_ly(d, x = ~carat, y = ~price, color = ~carat, colors = "Set1", size = ~carat)