मुझे संदेह है कि geom_tileपैकेज से ggplot2आप वह काम कर सकते हैं जिसकी आपको तलाश है। इस StackOverflow सवाल पर शेन का जवाब आपको मिलना चाहिए।
संपादित करें: यहां एक उदाहरण है, तुलना के लिए कुछ अन्य भूखंडों के साथ।
library(ggplot2)
# Here's some data I had lying around
tb <- structure(list(region = c("Africa", "Asia", "Latin America",
"Other", "US-born"), ncases = c(36L, 34L, 56L, 2L, 44L)), .Names = c("region",
"ncases"), row.names = c(NA, -5L), class = "data.frame")
# A bar chart of counts
ggplot(tb, aes(x = region, weight = ncases, fill = region)) +
geom_bar()
# Pie chart. Forgive me, Hadley, for I must sin.
ggplot(tb, aes(x = factor(1), weight = ncases, fill = region)) +
geom_bar(width = 1) +
coord_polar(theta = "y") +
labs(x = "", y = "")
# Percentage pie.
ggplot(tb, aes(x = factor(1), weight = ncases/sum(ncases), fill = region)) +
geom_bar() +
scale_y_continuous(formatter = 'percent') +
coord_polar(theta = "y") +
labs(x = "", y = "")
# Waffles
# How many rows do you want the y axis to have?
ndeep <- 5
# I need to convert my data into a data.frame with uniquely-specified x
# and y coordinates for each case
# Note - it's actually important to specify y first for a
# horizontally-accumulating waffle
# One y for each row; then divide the total number of cases by the number of
# rows and round up to get the appropriate number of x increments
tb4waffles <- expand.grid(y = 1:ndeep,
x = seq_len(ceiling(sum(tb$ncases) / ndeep)))
# Expand the counts into a full vector of region labels - i.e., de-aggregate
regionvec <- rep(tb$region, tb$ncases)
# Depending on the value of ndeep, there might be more spots on the x-y grid
# than there are cases - so fill those with NA
tb4waffles$region <- c(regionvec, rep(NA, nrow(tb4waffles) - length(regionvec)))
# Plot it
ggplot(tb4waffles, aes(x = x, y = y, fill = region)) +
geom_tile(color = "white") + # The color of the lines between tiles
scale_fill_manual("Region of Birth",
values = RColorBrewer::brewer.pal(5, "Dark2")) +
opts(title = "TB Cases by Region of Birth")
जाहिर है, सौंदर्यशास्त्र सही होने पर अतिरिक्त काम करना है (उदाहरण के लिए, उन कुल्हाड़ियों का मतलब क्या है?), लेकिन यह इसके बारे में यांत्रिकी है। मैं पाठक के लिए एक अभ्यास के रूप में "सुंदर" छोड़ता हूं।
