mycolors <- c('#6A99D0', '#F5C242', '#A5A5A5', '#DE8344')
sales <- c(1728.02, 3456.04, 1851.45, 5307.49)
pie(sales, init.angle = 40, col = mycolors, labels = '', main = 'Sales Chart', radius = 0.9)
legend(1, 0.5, c("Toys","Furniture","Home Decor", 'Electronics'),
cex = 0.7,
fill = mycolors)
text(0.2, 0.4, '14%')
text(-0.3, 0.2, '28%')
text(-0.35, -0.25, '15%')
text(0.3, -0.3, '43%') # 0.3 and -0.3 in here are the x and y-coordinates of the textmycolors <- c('#6A99D0', '#F5C242', '#A5A5A5', '#DE8344')
sales <- c(1728.02, 3456.04, 1851.45, 5307.49)
pie(sales, init.angle = 40, col = mycolors, labels = '', main = 'Sales Chart', radius = 0.9)
legend(1, 0.5, c("Toys","Furniture","Home Decor", 'Electronics'),
cex = 0.7,
fill = mycolors)
text(0.25, 0.6, '14%')
text(-0.5, 0.4, '28%')
text(-0.45, -0.4, '15%')
text(0.5, -0.4, '43%') # 0.3 and -0.3 in here are the x and y-coordinates of the text
symbols(0, 0, circles = 0.5, inches = FALSE,
bg = 'white', add = TRUE, ) # Draw a white disc in the centerpar(mar = c(4, 7, 2, 1), oma = c(3, 2, 0, 0))
impact <-c(17.7, 9.9, 9.1, 5.4, 3.8, 3.0, 2.9, 2.1, 1, 0.4, 0.1)
food <-c("Beef", "Lamb", "Farmed crustaceans", "Cheese", "Pork", "Farmed fish", "Poultry", "Eggs", "Tofu", "Beans", "Nuts")
barplot(impact[order(impact,decreasing=FALSE)],
names.arg=food[order(impact,decreasing=FALSE)],
horiz = TRUE, las = 1,
col = "orange",
xlim = c(0, 20), xlab = "Avg. Greenhouse Gas Impact", ylab = "",
main = "Effect of Food We Eat on Environment"
)nonfatal <- c(55, 56, 69)
fatal <- c(3, 3, 1)
x <- as.matrix(rbind(nonfatal, fatal))
colnames(x) <- c("2005", "2006", "2007")
barplot(x, ylim = c(0, 100), col = c("lightblue", "royalblue"),
main = "Shark Attacks", xlab = "Year", ylab = "Number of Attacks",
las = 1)
legend("topleft", legend = c("Non Fatal", "Fatal"),
fill = c("lightblue", "royalblue")
)savings <-matrix(c(20, 13, 36, 19, 12,
28, 10, 36, 14, 12,
38, 16, 32, 6, 8,
41, 18, 27, 7,7), nrow =5)
colnames(savings) <-c( "70-79", "60-69", "50-59", "40-49")
par(mar =c(4,6,6,2), mgp =c(4, 1, 0), xpd =TRUE)
pic <-barplot(savings, horiz =TRUE, xaxt ="n", space =0.5,
col =c("royalblue", "dodgerblue", "green", "darkseagreen", "gray30"),
main ="How much do you currently have saved for retirement?",
ylab ="Age", las =2)
legend("top", inset =-0.15, ncol =5, box.col ="blue", cex = 0.7,
legend =c("Less than $50K", "$50-99K", "$100-500K", "$500-999K", "$1M+"),
fill =c("royalblue", "dodgerblue", "green", "darkseagreen", "gray30"))
text(pic, x =c(10, 16, 20, 25), c("20%", "28%","38%", "41%"))
text(pic, x =c(25, 34, 45, 50), c("13%", "10%", "16%", "18%"))
text(pic, x =c(50, 57, 70, 75), c("36%", "36%", "32%", "27%"))
text(pic, x =c(80, 83, 89, 90), c("19%", "14%", "6%", "7%"))
text(pic, x =c(95, 95, 96, 97), c("12%", "12%", "8%", "7%"))globalhuman <- c(1700, 600, 300)
globalnature <- c(1200, 400, 250)
x <- as.matrix(rbind(globalhuman, globalnature))
barplot(x, beside = TRUE, ylim = c(0, 2000)) # Initiate bargraph
abline(h = c(500, 1000, 1500, 2000),col = "lightgray") # Plot the grid lines
par(new = TRUE) # Continue to plot on the same panel
# Plot the bargraph again so that the grid lines are in the background
barplot(x, beside = TRUE,
ylim = c(0, 2000),
col = c("coral", "lightblue"),
names.arg = c("2000-2005", "2005-2010", "2010-2015"),
main = "Global Mangrove Loss by Driver (km)")
legend("topright", legend = c("Human-driven", "Natural"), fill = c("coral", "lightblue"))years <- c(2009, 2010, 2011, 2012, 2013, 2014)
concussions <- c(92, 129, 142, 161, 145, 123)
par(bg = "#87A86F") # Background color
pic <- barplot(concussions, names.arg = years, ylim = c(0, 200), las = 1,
col = "#D2E1BC",
main = "Concussions declining, finally!")
text(pic, y = concussions - 10, labels = concussions) # Add textsballots <- c(14783, 13989, 9012, 21393, 16112)
groups <- c("Democrats", "Republicans", "Unaffiliated", "Female", "Male")
pic <- barplot(ballots,
xaxt = 'n', # Remove x lables
cex.names = 0.7,
main = "Absentee Ballots in 2014 in North Carolina",
col = c("blue", "red", "purple", "yellow", "maroon"),
width = 0.5,
space = c(1, 1, 1, 4, 1),
ylim = c(0, 25000))
text(pic, ballots + 1000, labels = ballots)
text(cex=1, x=c(1, 2, 3, 5.5, 6.5) - 0.5, y=-2500, groups, xpd=TRUE, srt=35) # Add x labels and rotate thempar(mar = c(4,4,4,4) + 0.1)
x <- c(2.7, 2.5, 2.45, 2.7, 2.5, 2.3, 2.6, 3.05, 3.3, 3.01, 3.58)
year <- 2009:2019
plot(year, x, type = "b", col = "red", ylim = c(0, 3.6), xaxt = "n", yaxt = 'n',
lwd = 3, las = 1,
xlab = "Year",
ylab = NA,
main = "The percentage of plate appearances that result in\n a home run has shot up in recent years")
abline(h = seq(0, 3.6, by = 0.2), col = "lightgray")
axis(1, at = 2009:2019, labels = 2009:2019)
axis(4, las = 1) # Add axis to the right
mtext('Home Run Percentage Per Plate Appearance', side = 4, line = 3) # Add axis label to the right