R语言数据可视化包：
knitr::opts_chunk$set(echo = TRUE, eval = TRUE, tidy = TRUE, highlight = TRUE, warning = FALSE, error = FALSE, message = FALSE, include = TRUE,fig.width = 9.4,fig.height = 4)require(devtools)
# install_github('rCharts', 'ramnathv') install_github('yihui/recharts')
# install.packages('plotly') install_github('Lchiffon/REmap')
# install.packages('igraph') install.packages('networkD3')
library(plotly)用法：
x <- c(1:100)
random_y <- rnorm(100, mean = 0)
data <- data.frame(x, random_y)
p <- plot_ly(data, x = ~x, y = ~random_y, type = "scatter", mode = "lines")
p# 数据集：
month <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct",
"Nov", "Dec")
high_2000 <- c(32.5, 37.6, 49.9, 53, 69.1, 75.4, 76.5, 76.6, 70.7, 60.6, 45.1,
29.3)
low_2000 <- c(13.8, 22.3, 32.5, 37.2, 49.9, 56.1, 57.7, 58.3, 51.2, 42.8, 31.6,
15.9)
high_2007 <- c(36.5, 26.6, 43.6, 52.3, 71.5, 81.4, 80.5, 82.2, 76, 67.3, 46.1,
35)
low_2007 <- c(23.6, 14, 27, 36.8, 47.6, 57.7, 58.9, 61.2, 53.3, 48.5, 31, 23.6)
high_2014 <- c(28.8, 28.5, 37, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3,
39.9)
low_2014 <- c(12.7, 14.3, 18.6, 35.5, 49.9, 58, 60, 58.6, 51.7, 45.2, 32.2,
29.1)
data <- data.frame(month, high_2000, low_2000, high_2007, low_2007, high_2014,
low_2014)
data$month <- factor(data$month, levels = data[["month"]])
head(data)## month high_2000 low_2000 high_2007 low_2007 high_2014 low_2014
## 1 Jan 32.5 13.8 36.5 23.6 28.8 12.7
## 2 Feb 37.6 22.3 26.6 14.0 28.5 14.3
## 3 Mar 49.9 32.5 43.6 27.0 37.0 18.6
## 4 Apr 53.0 37.2 52.3 36.8 56.8 35.5
## 5 May 69.1 49.9 71.5 47.6 69.7 49.9
## 6 Jun 75.4 56.1 81.4 57.7 79.7 58.0p <- plot_ly(data, x = ~month, y = ~high_2014, name = "High 2014", type = "scatter",
mode = "lines", line = list(color = "rgb(205, 12, 24)", width = 4)) %>%
add_trace(y = ~low_2014, name = "Low 2014", line = list(color = "rgb(22, 96, 167)",
width = 4)) %>%
add_trace(y = ~high_2007, name = "High 2007", line = list(color = "rgb(205, 12, 24)",
width = 4, dash = "dash")) %>%
add_trace(y = ~low_2007, name = "Low 2007", line = list(color = "rgb(22, 96, 167)",
width = 4, dash = "dash")) %>%
add_trace(y = ~high_2000, name = "High 2000", line = list(color = "rgb(205, 12, 24)",
width = 4, dash = "dot")) %>%
add_trace(y = ~low_2000, name = "Low 2000", line = list(color = "rgb(22, 96, 167)",
width = 4, dash = "dot")) %>%
layout(title = "Average High and Low Temperatures in New York", xaxis = list(title = "Months"),
yaxis = list(title = "Temperature (degrees F)"))
plibrary(plyr)
tg <- ddply(ToothGrowth, c("supp", "dose"), summarise, length = mean(len))
tg## supp dose length
## 1 OJ 0.5 13.23
## 2 OJ 1.0 22.70
## 3 OJ 2.0 26.06
## 4 VC 0.5 7.98
## 5 VC 1.0 16.77
## 6 VC 2.0 26.14p <- plot_ly(tg, x = ~dose, y = ~length, type = "scatter", mode = "lines", linetype = ~supp,
color = I("black")) %>%
layout(title = "The Effect of Vitamin C on Tooth Growth in Guinea Pigs by Supplement Type",
xaxis = list(title = "Dose in milligrams/day"), yaxis = list(title = "Tooth length"))
px <- c(1:15)
y <- c(10, 20, NA, 15, 10, 5, 15, NA, 20, 10, 10, 15, 25, 20, 10)
data <- data.frame(x, y)
p <- plot_ly(data, x = ~x, y = ~y, name = "Gaps", type = "scatter", mode = "lines") %>%
add_trace(y = ~y - 5, name = "<b>No</b> Gaps", connectgaps = TRUE)
px <- c(1:5)
y <- c(1, 3, 2, 3, 1)
p <- plot_ly(x = ~x) %>%
add_lines(y = ~y, name = "linear", line = list(shape = "linear")) %>%
add_lines(y = y + 5, name = "spline", line = list(shape = "spline")) %>%
add_lines(y = y + 10, name = "vhv", line = list(shape = "vhv")) %>%
add_lines(y = y + 15, name = "hvh", line = list(shape = "hvh")) %>%
add_lines(y = y + 20, name = "vh", line = list(shape = "vh")) %>%
add_lines(y = y + 25, name = "hv", line = list(shape = "hv"))
px <- c(2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013)
y_television <- c(74, 82, 80, 74, 73, 72, 74, 70, 70, 66, 66, 69)
y_internet <- c(13, 14, 20, 24, 20, 24, 24, 40, 35, 41, 43, 50)
data <- data.frame(x, y_television, y_internet)
data## x y_television y_internet
## 1 2001 74 13
## 2 2002 82 14
## 3 2003 80 20
## 4 2004 74 24
## 5 2005 73 20
## 6 2006 72 24
## 7 2007 74 24
## 8 2008 70 40
## 9 2009 70 35
## 10 2010 66 41
## 11 2011 66 43
## 12 2013 69 50# x轴相关设置：
xaxis <- list(title = "", showline = TRUE, showgrid = FALSE, showticklabels = TRUE,
linecolor = "rgb(204, 204, 204)", linewidth = 2, autotick = FALSE, ticks = "outside",
tickcolor = "rgb(204, 204, 204)", tickwidth = 2, ticklen = 5, tickfont = list(family = "Arial",
size = 12, color = "rgb(82, 82, 82)"))
# y轴相关设置：
yaxis <- list(title = "", showgrid = FALSE, zeroline = FALSE, showline = FALSE,
showticklabels = FALSE)
margin <- list(autoexpand = FALSE, l = 100, r = 100, t = 110, b = 100)
# Build the annotations
television_1 <- list(xref = "paper", yref = "y", x = 0.05, y = y_television[1],
xanchor = "right", yanchor = "middle", text = ~paste("Television ", y_television[1],
"%"), font = list(family = "Arial", size = 16, color = "rgba(67,67,67,1)"),
showarrow = FALSE)
internet_1 <- list(xref = "paper", yref = "y", x = 0.05, y = y_internet[1],
xanchor = "right", yanchor = "middle", text = ~paste("Internet ", y_internet[1],
"%"), font = list(family = "Arial", size = 16, color = "rgba(49,130,189, 1)"),
showarrow = FALSE)
television_2 <- list(xref = "paper", x = 0.95, y = y_television[12], xanchor = "left",
yanchor = "middle", text = paste("Television ", y_television[12], "%"),
font = list(family = "Arial", size = 16, color = "rgba(67,67,67,1)"), showarrow = FALSE)
internet_2 <- list(xref = "paper", x = 0.95, y = y_internet[12], xanchor = "left",
yanchor = "middle", text = paste("Internet ", y_internet[12], "%"), font = list(family = "Arial",
size = 16, color = "rgba(67,67,67,1)"), showarrow = FALSE)
p <- plot_ly(data, x = ~x) %>%
add_trace(y = ~y_television, type = "scatter", mode = "lines", line = list(color = "rgba(67,67,67,1)",
width = 2)) %>%
add_trace(y = ~y_internet, type = "scatter", mode = "lines", line = list(color = "rgba(49,130,189, 1)",
width = 4)) %>%
add_trace(x = ~c(x[1], x[12]), y = ~c(y_television[1], y_television[12]), type = "scatter",
mode = "markers", marker = list(color = "rgba(67,67,67,1)", size = 8)) %>%
add_trace(x = ~c(x[1], x[12]), y = ~c(y_internet[1], y_internet[12]), type = "scatter",
mode = "markers", marker = list(color = "rgba(49,130,189, 1)", size = 12)) %>%
layout(title = "Main Source for News", xaxis = xaxis, yaxis = yaxis, margin = margin,
autosize = FALSE, showlegend = FALSE, annotations = television_1) %>%
layout(annotations = internet_1) %>%
layout(annotations = television_2) %>%
layout(annotations = internet_2)
pmonth <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct",
"Nov", "Dec")
high_2014 <- c(28.8, 28.5, 37, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3,
39.9)
low_2014 <- c(12.7, 14.3, 18.6, 35.5, 49.9, 58, 60, 58.6, 51.7, 45.2, 32.2,
29.1)
data <- data.frame(month, high_2014, low_2014)
data$average_2014 <- rowMeans(data[, c("high_2014", "low_2014")])
# The default order will be alphabetized unless specified as below:
data$month <- factor(data$month, levels = data[["month"]])
data## month high_2014 low_2014 average_2014
## 1 Jan 28.8 12.7 20.75
## 2 Feb 28.5 14.3 21.40
## 3 Mar 37.0 18.6 27.80
## 4 Apr 56.8 35.5 46.15
## 5 May 69.7 49.9 59.80
## 6 Jun 79.7 58.0 68.85
## 7 Jul 78.5 60.0 69.25
## 8 Aug 77.8 58.6 68.20
## 9 Sep 74.1 51.7 62.90
## 10 Oct 62.6 45.2 53.90
## 11 Nov 45.3 32.2 38.75
## 12 Dec 39.9 29.1 34.50p <- plot_ly(data, x = ~month, y = ~high_2014, type = "scatter", mode = "lines",
line = list(color = "transparent"), showlegend = FALSE, name = "High 2014") %>%
add_trace(y = ~low_2014, type = "scatter", mode = "lines", fill = "tonexty",
fillcolor = "rgba(0,100,80,0.2)", line = list(color = "transparent"), showlegend = FALSE,
name = "Low 2014") %>%
add_trace(x = ~month, y = ~average_2014, type = "scatter", mode = "lines", line = list(color = "rgb(0,100,80)"),
name = "Average") %>%
layout(title = "Average, High and Low Temperatures in New York", paper_bgcolor = "rgb(255,255,255)",
plot_bgcolor = "rgb(229,229,229)", xaxis = list(title = "Months", gridcolor = "rgb(255,255,255)",
showgrid = TRUE, showline = FALSE, showticklabels = TRUE, tickcolor = "rgb(127,127,127)",
ticks = "outside", zeroline = FALSE), yaxis = list(title = "Temperature (degrees F)",
gridcolor = "rgb(255,255,255)", showgrid = TRUE, showline = FALSE, showticklabels = TRUE,
tickcolor = "rgb(127,127,127)", ticks = "outside", zeroline = FALSE))
p绘图前需要提前对数据进行处理
dens <- with(diamonds, tapply(price, INDEX = cut, density))
df <- data.frame(x = unlist(lapply(dens, "[[", "x")), y = unlist(lapply(dens,
"[[", "y")), cut = rep(names(dens), each = length(dens[[1]]$x)))
head(df)## x y cut
## Fair1 -1114.8694 6.744087e-08 Fair
## Fair2 -1073.4981 9.022150e-08 Fair
## Fair3 -1032.1268 1.196403e-07 Fair
## Fair4 -990.7555 1.572893e-07 Fair
## Fair5 -949.3842 2.064376e-07 Fair
## Fair6 -908.0129 2.708506e-07 Fairp <- plot_ly(df, x = ~x, y = ~y, color = ~cut) %>% add_lines()
p