构建R绘图跟踪回路时如何调整编组 在R中使用trace loop#for plotly后,如何使用另一个属性重新分组数据 #初始化空绘图 P # Initialize empty plot p <- plot_ly() # Each task is
构建R绘图跟踪回路时如何调整编组 在R中使用trace loop#for plotly后,如何使用另一个属性重新分组数据构建R绘图跟踪回路时如何调整编组 在R中使用trace loop#for plotly后,如何使用另一个属性重新分组数据 #初始化空绘图 P # Initialize empty plot p <- plot_ly() # Each task is,r,loops,group-by,plotly,trace,R,Loops,Group By,Plotly,Trace,构建R绘图跟踪回路时如何调整编组 在R中使用trace loop#for plotly后,如何使用另一个属性重新分组数据 #初始化空绘图 P # Initialize empty plot p <- plot_ly() # Each task is a separate trace # Each trace is essentially a thick line plot # x-axis ticks are dates and handled automatically for(i
#初始化空绘图
P
# Initialize empty plot
p <- plot_ly()
# Each task is a separate trace
# Each trace is essentially a thick line plot
# x-axis ticks are dates and handled automatically
for(i in 1:(nrow(df) - 1)){
p <- add_trace(p,
x = c(df$Start[i], df$Start[i] + df$Duration[i]), # x0, x1
y = c(i, i), # y0, y1
mode = "lines",
line = list(color = df$color[i], width = 20),
showlegend = F,
hoverinfo = "text",
# Create custom hover text
text = paste("Task: ", df$Task[i], "<br>",
"Duration: ", df$Duration[i], "days<br>",
"Resource: ", df$Resource[i]),
evaluate = T # needed to avoid lazy loading
)
}