Assignment 07
Muhammad Bilal
2023-11-29
library(dslabs)
data("longley")
head(longley)## GNP.deflator GNP Unemployed Armed.Forces Population Year Employed
## 1947 83.0 234.289 235.6 159.0 107.608 1947 60.323
## 1948 88.5 259.426 232.5 145.6 108.632 1948 61.122
## 1949 88.2 258.054 368.2 161.6 109.773 1949 60.171
## 1950 89.5 284.599 335.1 165.0 110.929 1950 61.187
## 1951 96.2 328.975 209.9 309.9 112.075 1951 63.221
## 1952 98.1 346.999 193.2 359.4 113.270 1952 63.639Formula method
barplot(GNP ~ Year, data = longley)
barplot(cbind(Employed, Unemployed) ~ Year, data = longley)
This code creates a barplot where the variable GNP is plotted against
the variable Year using the data from the longley dataset. The ~ symbol
is used to specify the relationship between the variables. And in 2nd
line This code creates a grouped barplot where the variables Employed
and Unemployed are plotted against the variable Year using the data from
the longley dataset. The cbind function is used to combine the two
variables into a matrix.
3rd form of formula - 2 categories :
op <- par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1))
summary(d.Titanic <- as.data.frame(Titanic))## Class Sex Age Survived Freq
## 1st :8 Male :16 Child:16 No :16 Min. : 0.00
## 2nd :8 Female:16 Adult:16 Yes:16 1st Qu.: 0.75
## 3rd :8 Median : 13.50
## Crew:8 Mean : 68.78
## 3rd Qu.: 77.00
## Max. :670.00barplot(Freq ~ Class + Survived, data = d.Titanic,
subset = Age == "Adult" & Sex == "Male",
main = "barplot(Freq ~ Class + Survived, *)", ylab = "# {passengers}", legend.text = TRUE)
This code involves creating a barplot using the barplot function with a
formula method. The formula Freq ~ Class + Survived indicates that the
frequency (Freq) is plotted against the interaction of the variables
Class and Survived. The plot is further subsetted to include only cases
where Age is “Adult” and Sex is “Male”. # Corresponding table :
(xt <- xtabs(Freq ~ Survived + Class + Sex, d.Titanic, subset = Age=="Adult"))## , , Sex = Male
##
## Class
## Survived 1st 2nd 3rd Crew
## No 118 154 387 670
## Yes 57 14 75 192
##
## , , Sex = Female
##
## Class
## Survived 1st 2nd 3rd Crew
## No 4 13 89 3
## Yes 140 80 76 20This code uses the xtabs function to create a contingency table (xt) based on the formula Freq ~ Survived + Class + Sex from the d.Titanic dataset. It further subsets the data to include only cases where Age is “Adult”. # Alternatively, a mosaic plot :
mosaicplot(xt[,,"Male"], main = "mosaicplot(Freq ~ Class + Survived, *)", color=TRUE)
par(op)This line of code uses the mosaicplot function to create a mosaic plot. The data for the plot is taken from the contingency table xt for the subset of males ([,,“Male”]). The main title of the plot is set to “mosaicplot(Freq ~ Class + Survived, *)” and the color parameter is set to TRUE to use color in the plot.Following the creation of the mosaic plot, this line of code uses the par function to reset the graphics parameters to their original values. The op object was previously defined to store the original graphics parameters before making changes. This step ensures that any subsequent plots are not affected by the changes made for the mosaic plot, reverting the graphics settings to their initial state. # Default method
# Default method
require(grDevices) # for colours
tN <- table(Ni <- stats::rpois(100, lambda = 5))
r <- barplot(tN, col = rainbow(20))
#- type = "h" plotting *is* 'bar'plot
lines(r, tN, type = "h", col = "red", lwd = 2)
barplot(tN, space = 1.5, axisnames = FALSE,
sub = "barplot(..., space= 1.5, axisnames = FALSE)")
barplot(VADeaths, plot = FALSE)## [1] 0.7 1.9 3.1 4.3barplot(VADeaths, plot = FALSE, beside = TRUE)## [,1] [,2] [,3] [,4]
## [1,] 1.5 7.5 13.5 19.5
## [2,] 2.5 8.5 14.5 20.5
## [3,] 3.5 9.5 15.5 21.5
## [4,] 4.5 10.5 16.5 22.5
## [5,] 5.5 11.5 17.5 23.5mp <- barplot(VADeaths) # default
tot <- colMeans(VADeaths)
text(mp, tot + 3, format(tot), xpd = TRUE, col = "blue")
barplot(VADeaths, beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender", "cornsilk"),
legend.text = rownames(VADeaths), ylim = c(0, 100))
title(main = "Death Rates in Virginia", font.main = 4)
hh <- t(VADeaths)[, 5:1]
mybarcol <- "gray20"
mp <- barplot(hh, beside = TRUE,
col = c("lightblue", "mistyrose",
"lightcyan", "lavender"),
legend.text = colnames(VADeaths), ylim = c(0,100),
main = "Death Rates in Virginia", font.main = 4,
sub = "Faked upper 2*sigma error bars", col.sub = mybarcol,
cex.names = 1.5)
segments(mp, hh, mp, hh + 2*sqrt(1000*hh/100), col = mybarcol, lwd = 1.5)
stopifnot(dim(mp) == dim(hh)) # corresponding matrices
mtext(side = 1, at = colMeans(mp), line = -2,
text = paste("Mean", formatC(colMeans(hh))), col = "red")
# Bar shading example
barplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black",
legend.text = rownames(VADeaths))
title(main = list("Death Rates in Virginia", font = 4))
Generate Poisson-distributed Data:
Generates a random dataset Ni with 100 values following a Poisson distribution with a mean of 5. Creates a table tN to count the occurrences of each unique value in Ni. Create a Basic Bar Plot:
Creates a basic bar plot (r) using the counts from the previous step and colors the bars with a rainbow palette. Add Lines to the Bar Plot:
Adds horizontal lines to the existing bar plot (r) in red, enhancing the visual representation. Customize Bar Plot:
Creates a bar plot with customized spacing and without axis names. Includes a subtitle providing information about the customization. Multiple Grouped Bar Plots:
Creates two variations of bar plots for the “VADeaths” dataset, one as a single plot and the other as a grouped plot without plotting it. Annotate Bar Plot:
Creates a default bar plot (mp) for the “VADeaths” dataset. Computes the column means of the dataset and adds text labels above each bar. Colored Grouped Bar Plot with Legend:
Creates a grouped bar plot with custom colors for each group. Adds a legend, sets y-axis limits, and adds a main title. Error Bars and Statistical Annotations:
Creates a grouped bar plot with custom colors. Adds error bars based on statistical calculations and includes a subtitle with additional information. Bar Shading Example:
Creates a bar plot with angled lines, increased density, and black color. Adds a legend and a main title with a specific font.
Bar shading example
barplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black",
legend.text = rownames(VADeaths))
title(main = list("Death Rates in Virginia", font = 4))
This barplot is creating a bar chart (barplot) of the data in VADeaths.
The bars have shading with an angle that varies for each bar (angle =
15+10*1:5), a density of 20, and a black color. The legend is set to
display the row names of VADeaths, and a main title is added to the
chart. # Border color
barplot(VADeaths, border = "dark blue") 
This barplot is similar to the previous one, but with the addition of a
dark blue border around each bar.
Log scales (not much sense here)
barplot(tN, col = heat.colors(12), log = "y")
barplot(tN, col = gray.colors(20), log = "xy")
The first barplot uses a logarithmic scale on the y-axis (log = “y”)
with a color palette from heat.colors(12). The second barplot uses a
logarithmic scale on both the x and y axes (log = “xy”) with a gray
color palette from gray.colors(20). # Legend location
barplot(height = cbind(x = c(465, 91) / 465 * 100,
y = c(840, 200) / 840 * 100,
z = c(37, 17) / 37 * 100),
beside = FALSE,
width = c(465, 840, 37),
col = c(1, 2),
legend.text = c("A", "B"),
args.legend = list(x = "topleft"))
This barplot creates a chart with bars specified by the height matrix.
The beside = FALSE argument arranges the bars in a stacked manner.
Widths of the bars are set, and colors are assigned. A legend is added
with custom text (“A” and “B”) at the top-left corner of the plot.