R : 绘制时间线流程图
R : Draw timeline flowchart
我有一个数据框,其中包含有关从不同团队执行的任务的信息。
我想使用 R.Blue box = team 绘制一个类似的图,如下所示。任务完成 = 绿框。做任务=灰框。我正在考虑为此使用 ggplot2 geom_tile 但我想知道是否还有其他现有解决方案?
示例:
task team status
1 A completed
2 A completed
3 B completed
4 A to do
5 C to do
6 B to do
7 C to do
8 A to do
dput
重现性:
structure(list(task = 1:8, team = c("A", "A", "B", "A", "C",
"B", "C", "A"), status = c("completed", "completed", "completed",
"to do", "to do", "to do", "to do", "to do")), .Names = c("task",
"team", "status"), class = "data.frame", row.names = c(NA, -8L
))
我没有为此找到现有的解决方案,所以我编写了一个函数来满足您的需要。当然,对于大数据集,它会给出不合适的结果。
require(dplyr)
timeline_plot <- function(dat, spacing = 0.01, team_size = 0.25, notch = 0.1,
cols = list(team = "lightblue",
completed = "green3",
"to do" = "lightgray"),
cex_label = 2){
# Arguments:
# dat = data frame
# spacing = space between polygons (part of plot width)
# team_size = size of team polygon (part of plot width)
# notch = size of arrow side protruding (part of plot width)
# cols = color for each status
# cex_lab = cex of labels
# Count number of columns
dat_n <- dat %>%
group_by(team) %>%
summarise(n = length(team))
# Get number of rows
nr <- length(dat_n$team)
# Prepare polygon
poly <- matrix(c(0, 0, 0, 1, 1, 1, 0, 0.5, 1, 1, 0.5, 0), ncol = 2)
# Function for polygon scaling, shifting and notch adding
morph_poly <- function(poly, scale_x = 1, shift_x = 0, notch){
poly[, 1] <- poly[, 1] * scale_x + shift_x
poly[c(2, 5), 1] <- poly[c(2, 5), 1] + notch
return(poly)
}
# Fucntion for label positioning
label_pos_x <- function(poly){
x <- poly[2, 1] + (poly[5, 1] - poly[2, 1]) / 3
return(x)
}
# Save old par
opar <- par()
# Set number of rows for plotting
par(mfrow = c(nr, 1))
par(mar = c(0,0,0,0))
# Actual plotting
for (i in c(1:nr)){
# Each row will be presentd as
# team_polygon + spacing + n * (spacing + task_polygon) + notch
team <- dat_n$team[i]
tasks <- dat[dat$team == team, ]
tasks <- tasks[order(tasks$task), ]
# Create empty plot
plot(NA, xlim = c(0, 1), ylim = c(0, 1), xlab = "", ylab = "", bty = "n", xaxt = "n", yaxt = "n")
# Plot team polygon
team_poly <- morph_poly(poly, team_size, 0, notch)
polygon(team_poly, col = cols$team)
# Add team label
text(label_pos_x(team_poly), 0.5, labels = dat_n$team[i], cex = cex_label)
# Calculate the size of task polygon
tasks_n <- dat_n$n[i]
size_x <- (1 - team_size - (tasks_n * spacing) - notch) / tasks_n
shift <- team_size + spacing
# plot each task polygon
for (j in 1:nrow(tasks)){
# Get task color
task_col = cols[[tasks$status[j]]]
# Prepare polygon
task_poly <- morph_poly(poly, scale_x = size_x, shift_x = shift + spacing, notch = notch)
polygon(task_poly, col = task_col)
# Add task label
text(label_pos_x(task_poly), 0.5, labels = tasks$task[j], cex = cex_label)
# Update shift
shift <- shift + size_x + spacing
}
}
# Set initial par
par(opar)
}
将您的数据设置为 dat
它给出:
timeline_plot(dat)
我有一个数据框,其中包含有关从不同团队执行的任务的信息。
我想使用 R.Blue box = team 绘制一个类似的图,如下所示。任务完成 = 绿框。做任务=灰框。我正在考虑为此使用 ggplot2 geom_tile 但我想知道是否还有其他现有解决方案?
示例:
task team status
1 A completed
2 A completed
3 B completed
4 A to do
5 C to do
6 B to do
7 C to do
8 A to do
dput
重现性:
structure(list(task = 1:8, team = c("A", "A", "B", "A", "C",
"B", "C", "A"), status = c("completed", "completed", "completed",
"to do", "to do", "to do", "to do", "to do")), .Names = c("task",
"team", "status"), class = "data.frame", row.names = c(NA, -8L
))
我没有为此找到现有的解决方案,所以我编写了一个函数来满足您的需要。当然,对于大数据集,它会给出不合适的结果。
require(dplyr)
timeline_plot <- function(dat, spacing = 0.01, team_size = 0.25, notch = 0.1,
cols = list(team = "lightblue",
completed = "green3",
"to do" = "lightgray"),
cex_label = 2){
# Arguments:
# dat = data frame
# spacing = space between polygons (part of plot width)
# team_size = size of team polygon (part of plot width)
# notch = size of arrow side protruding (part of plot width)
# cols = color for each status
# cex_lab = cex of labels
# Count number of columns
dat_n <- dat %>%
group_by(team) %>%
summarise(n = length(team))
# Get number of rows
nr <- length(dat_n$team)
# Prepare polygon
poly <- matrix(c(0, 0, 0, 1, 1, 1, 0, 0.5, 1, 1, 0.5, 0), ncol = 2)
# Function for polygon scaling, shifting and notch adding
morph_poly <- function(poly, scale_x = 1, shift_x = 0, notch){
poly[, 1] <- poly[, 1] * scale_x + shift_x
poly[c(2, 5), 1] <- poly[c(2, 5), 1] + notch
return(poly)
}
# Fucntion for label positioning
label_pos_x <- function(poly){
x <- poly[2, 1] + (poly[5, 1] - poly[2, 1]) / 3
return(x)
}
# Save old par
opar <- par()
# Set number of rows for plotting
par(mfrow = c(nr, 1))
par(mar = c(0,0,0,0))
# Actual plotting
for (i in c(1:nr)){
# Each row will be presentd as
# team_polygon + spacing + n * (spacing + task_polygon) + notch
team <- dat_n$team[i]
tasks <- dat[dat$team == team, ]
tasks <- tasks[order(tasks$task), ]
# Create empty plot
plot(NA, xlim = c(0, 1), ylim = c(0, 1), xlab = "", ylab = "", bty = "n", xaxt = "n", yaxt = "n")
# Plot team polygon
team_poly <- morph_poly(poly, team_size, 0, notch)
polygon(team_poly, col = cols$team)
# Add team label
text(label_pos_x(team_poly), 0.5, labels = dat_n$team[i], cex = cex_label)
# Calculate the size of task polygon
tasks_n <- dat_n$n[i]
size_x <- (1 - team_size - (tasks_n * spacing) - notch) / tasks_n
shift <- team_size + spacing
# plot each task polygon
for (j in 1:nrow(tasks)){
# Get task color
task_col = cols[[tasks$status[j]]]
# Prepare polygon
task_poly <- morph_poly(poly, scale_x = size_x, shift_x = shift + spacing, notch = notch)
polygon(task_poly, col = task_col)
# Add task label
text(label_pos_x(task_poly), 0.5, labels = tasks$task[j], cex = cex_label)
# Update shift
shift <- shift + size_x + spacing
}
}
# Set initial par
par(opar)
}
将您的数据设置为 dat
它给出:
timeline_plot(dat)