even if I am getting used to R I am still new with it and I hope that someone can help me deal with this task ...I have tried to look for some previous topics but I couldn't find what I was looking for, so here I am hoping for some help.
I am trying to draw my bar plot but I am not having much luck on some of the settings so I hope someone could help. I am using R 3.1.1 on my mac OS 10.9.4.
my table look like this:
family area1 area2 area3 area4 area5 area6
A 15 20 500 200 17 26
B 170 520 26 13 100 70
C 35 250 358 128 88 26
D 95 375 289 156 169 356
E 425 177 136 144 285 70
since I have the file save it as a csv I am doing this steps:
fam <- read.csv ("family_per_area_count.csv", sep =";", header = T)
I am converting the file as a matrix
fam.mat <- as.matrix(fam_1, ncol = 6, byrow = T)
then I assign row names and col names
rownames(fam.mat) <- c("A", "B", "C", "D", "E")
colnames(fam.mat) <- c("area1", "area2", "area3", "area4", "area5", "area6")
then I am simply running the bar plot command as
barplot(fam.mat, beside = T, col = rainbow(ncol(fam.mat)))
but I am missing most of the labels for the x axis and the plot seems to be pressed together.
I also tried to run the cumulative bar plot using this command
par(mar = c(5.1, 4.1, 4.1, 7.1), xpd = TRUE)
prop <- prop.table(data_mat, margin = 2)
barplot(data_mat, col = rainbow(length(rownames(data_mat))), width = 3)
legend("topright", inset = c(-0.25, 0), fill = rainbow(length(rownames(data_mat))),
legend = rownames(data_mat))
but the legend colours don't match the data and again my x-axis seems out of center. I have tried to transpose the matrix but still no luck.
Can anyone make any suggestion?
Thank you so much in advance
F.
Here is a start:
DF <- read.table(text="family area1 area2 area3 area4 area5 area6
A 15 20 500 200 17 26
B 170 520 26 13 100 70
C 35 250 358 128 88 26
D 95 375 289 156 169 356
E 425 177 136 144 285 70", header=TRUE)
library(reshape2)
DF <- melt(DF, id.var="family")
library(ggplot2)
ggplot(DF, aes(x=family, y=value, fill=variable)) +
geom_bar(stat="identity", position="dodge")
Study ggplot2 documentation and tutorials to learn how to customise the plot.
Related
I am struggling to plot a specific row from a dataframe. Below is the Graph i am trying to plot. I have tried using ggplot and normal plot but i cannot figure it out.
Wt2 Wt3 Wt4 Wt5 Lngth2 Lngth3 Lngth4 Lngth5
1 48 59 95 82 141 157 168 183
2 59 68 102 102 140 168 174 170
3 61 77 93 107 145 162 172 177
4 54 43 104 104 146 159 176 171
5 100 145 185 247 150 158 168 175
6 68 82 95 118 142 140 178 189
7 68 95 109 111 139 171 176 175
Above is the Data frame I am trying to plot with. The rows are for each bears measurement. So row 1 is for bear 1. How would I plot only the Wt columns for bear 1 against an X-axis that goes from years 2 to 5
You can pivot your data frame into a longer format:
First add a column with the row number (bear number):
df = cbind("Bear"=as.factor(1:nrow(df)), df)
It needs to be factor so we can pass it as a group variable to ggplot. Now pivot:
df2 = tidyr::pivot_longer(df[,1:5], cols=2:5,
names_to="Year", values_to="Weight", names_prefix="Wt")
df2$Year = as.numeric(df2$Year)
We ignore the Length columns with df[,1:5]; say that we only want to pivot the weight columns with df[,2:5]; then say the name of the columns we want to create with names_to and values_to; and lastly the names_prefix="Wt" removes the "Wt" before the column names, leaving only the year number, but we get a character, so we need to make it numeric with as.numeric().
Then plot:
ggplot(df2, aes(x=Year, y=Weight, linetype=Bear)) + geom_line()
Output (Ps: i created my own data, so the actual numbers are off):
Just an addition, if you don't want to specify the columns of your dataset explicity, you can do:
df2 = df2[,grep("Wt|Bear", colnames(df)]
df2 = tidyr::pivot_longer(df2, cols=grep("Wt", colnames(df2)),
names_to="Year", values_to="Weight", names_prefix="Wt")
Edit: one plot for each group
You can use facet_wrap:
ggplot(df2, aes(x=Year, y=Weight, linetype=Bear)) +
facet_wrap(~Bear, nrow=2, ncol=4) +
geom_line()
Output:
You can change the nrow and ncol as you wish, and can remove the linetype from aes() as you already have a differenciation, but it's not mandatory.
You can also change the levels of the categorical data to make the labels on each graph better, do levels(df2$Bear) = paste("Bear", 1:7) for example (or do that the when creating it).
Try
ggplot(mapping = aes(x = seq.int(2, 5), y = c(48, 59, 95, 82))) +
geom_point(color = "blue") +
geom_line(color = "blue") +
xlab("Year") +
ylab("Weight")
I have the following table(data frame):
week24 week25 week26
under 0.5m 1824 1878 1955
0.5 to 1m 170 205 211
1to3 117 109 124
3to6 19 19 25
6to10 9 8 8
10to15 4 3 5
15to30 9 13 9
above 30m 19 32 28
i am looking for the best way to visualize it on a graph then i can i have row names under 0.5m:above 30m in X axis .
i have already tried barplot() but the results are not that good
how can i make it more informative?
It's not clear to me what exactly are you trying to obtain. Maybe just by adding the legend your graph will be way more descriptive. I've a simple data frame to show what I mean:
df <- data.frame(Z=c(1,2,3),Y=c(2,3,1))
row.names(df) <- c("Cat1","Cat2","Cat3")
barplot(as.matrix(df),
legend.text = row.names(df),
args.legend = list(x = "right"),
col = c("blue","green","red"))
If you want check better colours, check this website: http://www.stat.columbia.edu/~tzheng/files/Rcolor.pdf
Im trying to make a barplot with the following data
Dept
Admit A B C D E F
Admitted 601 370 322 269 147 46
Rejected 332 215 596 523 437 668
and I have tried the following code:
admission_department <- barplot(biasUCB_d, main="Admit by deparment",
xlab="biasUCB_d[['Dept']]",
col=c("darkblue","red"),
legend = rownames(biasUCB_d[['Dept']]),
beside=TRUE)
The name of the coding used to create the dataset is:
biasUCB_d <- margin.table(UCBAdmissions, c(1,3))
What am I doing wrong?
Assuming that Dept is an element of a list this should work:
Data:
biasUCB_d <- list(Dept = read.table(header=T, text='
Admit A B C D E F
Admitted 601 370 322 269 147 46
Rejected 332 215 596 523 437 668'))
Solution:
dmission_department <- barplot(as.matrix(biasUCB_d$Dept[2:7]), main="Admit by deparment",
xlab="biasUCB_d[['Dept']]",
col=c("darkblue","red"),
legend = biasUCB_d$Dept$Admit,
beside=TRUE)
Output:
Try:
admission_department <- barplot(biasUCB_d, main="Admit by deparment",
xlab="Department",
col=c("darkblue","red"),
legend.text = rownames(biasUCB_d),
beside=TRUE)
I'm trying to bin a symmetric matrix with irregular intervals in R but am not sure how to proceed. My ideas are:
Reshape the matrix to long format, aggregate and cast it back?
Bin as-is in both dimensions (somehow... tapply, aggregate?)
Keep the regular binning but for each of my (larger) irregular bins, replace all inner values with their sum?
Here's an example of what I'm trying to do:
set.seed(42)
# symmetric matrix
a <- matrix(rpois(1e4, 2), 100)
a[upper.tri(a)] <- t(a)[upper.tri(a)]
image(x=1:100, y=1:100, a, asp=1, frame=F, axes=F)
# vector of irregular breaks for binning
breaks <- c(12, 14, 25, 60, 71, 89)
# white line show the desired bins
abline(h=breaks-.5, lwd=2, col="white")
abline(v=breaks-.5, lwd=2, col="white")
(The aim being that each rectangle drawn above be filled according to the sum of values within it.) I'd appreciate any pointers of how best to approach this.
This answer provides a great starting point using tapply:
b <- melt(a)
bb <- with(b, tapply(value,
list(
y=cut(Var1, breaks=c(0, breaks, Inf), include.lowest=T),
x=cut(Var2, breaks=c(0, breaks, Inf), include.lowest=T)
),
sum)
)
bb
# x
# y [0,12] (12,14] (14,25] (25,60] (60,71] (71,89] (89,Inf]
# [0,12] 297 48 260 825 242 416 246
# (12,14] 48 3 43 141 46 59 33
# (14,25] 260 43 261 794 250 369 240
# (25,60] 825 141 794 2545 730 1303 778
# (60,71] 242 46 250 730 193 394 225
# (71,89] 416 59 369 1303 394 597 369
# (89,Inf] 246 33 240 778 225 369 230
These can then be plotted as rectangular bins using a base plot and rect — i.e.:
library("reshape2")
library("magrittr")
bsq <- melt(bb)
# convert range notation to numerics
getNum <- . %>%
# rm brackets
gsub("\\[|\\(|\\]|\\)", "", .) %>%
# split digits and convert
strsplit(",") %>%
unlist %>% as.numeric
y <- t(sapply(bsq[,1], getNum))
x <- t(sapply(bsq[,2], getNum))
# normalise bin intensity by area
bsq$size <- (y[,2] - y[,1]) * (x[,2] - x[,1])
bsq$norm <- bsq$value / bsq$size
# draw rectangles on top of empty plot
plot(1:100, 1:100, type="n", frame=F, axes=F)
rect(ybottom=y[,1], ytop=y[,2],
xleft=x[,1], xright=x[,2],
col=rgb(colorRamp(c("white", "steelblue4"))(bsq$norm / max(bsq$norm)),
alpha=255*(bsq$norm / max(bsq$norm)), max=255),
border="white")
May be it is simple. But I am not getting how to plot the following data using R.
Basically the x-axis has type (i.e., A, B, C, D four labels). On the plot I want to represent the numbers (v1, v2, v3, v4) as points. For example, for A, on the y-axis I want to point 99, 110, 150, and 170. Moreover, I need to use different pch value for point. I tried to use stripchart but I am not sure how to assign different pch values under each of the types A, B, C, D. Please see for points (99, 110, 150, 170) of A in the below figure.
Data:
type A B C D
v1 99 227 295 503
v2 110 440 620 970
v3 150 600 934 1330
v4 170 650 1012 1390
Are you looking for something like this?
df = read.table(header=TRUE, text="type A B C D
v1 99 227 295 503
v2 110 440 620 970
v3 150 600 934 1330
v4 170 650 1012 1390")
stripchart(df[-1], pch=c(1, 2, 3, 4), vertical=TRUE)
Resulting in:
Update
Sorry, I misread the first question. Try this:
df2 = data.frame(t(df[-1]))
names(df2) = df$type
df2$group = rownames(df2)
library(lattice)
stripplot(v1 + v2 + v3 + v4 ~ group, data=df2, pch=c(1, 2, 3, 4))