Is there a way to plot 2 data frames on R despite that they have different values?. For example:
data1
[hour] [value]
1 5
2 4
3 3
4 4
data2
[hour] [value]
1 4
2 8
4 9
5 2
I would like to paint in the x axis 1,2,3,4,5 and in the y axis the value it correspond.
Thanks :)
You just need to add three lines of codes as below.
plot(data2$hour,data2$value,xlab='hour',ylab='value')
par(new=TRUE)
points(data1$hour,data1$value)
Hope it helps!
Try:
plot(data1, type="l", xlim = c(0,6), ylim = c(0,10))
lines(data2)
Here is one way.
library(ggplot2)
data1 <- data.frame(hour=c(1,2,3,4),value=c(5,4,3,4))
data2 <- data.frame(hour=c(1,2,4,5),value=c(4,8,9,2))
data3 <- rbind(data1,data2)
data3$data <- c(rep("data1",4),rep("data2",4))
#try this
ggplot(data3,aes(x=hour,y=value))+
geom_point()+
facet_wrap(~data)+
theme_bw()
Here is another way (with colours and lines):
#or this
ggplot(data3,aes(x=hour,y=value,col=data))+
geom_point()+
geom_line()+
theme_bw()
We can use:
par(mfrow=c(1,2))
By using this, we can have two different dataframe individually on same row.
Related
I am currently stuck on formatting a grouped bar chart.
I have a dataframe, which I would like to visualize:
iteration position value
1 1 eEP_SRO 20346
2 1 eEP_drift 22410
3 1 eEP_hole 29626
4 2 eEP_SRO 35884
5 2 eEP_drift 39424
6 2 eEP_hole 51491
7 3 eEP_SRO 51516
8 3 eEP_drift 55523
9 3 eEP_hole 74403
The position should be shown as color and the value should be represented in the height of the bar.
My code is:
fig <- ggplot(df_eEP_Location_plot, aes(fill=position, y=value, x=iteration, order=position)) +
geom_bar(stat="identity")
which gives me this result:
I would like to have a correct y-axis labelling and would also like to sort my bars from largest to smallest (ignoring the iteration number). How can I achieve this?
Thank you very much for your help!
I would recommend using fct_reorder from the forcats package to reorder your iterations along the specified values prior to plotting in ggplot. See the following with the sample data you've provided:
library(ggplot2)
library(forcats)
iteration <- factor(c(1,1,1,2,2,2,3,3,3))
position <- factor(rep(c("eEP_SRO","eEP_drift","eEP_hole")))
value <- c(20346,22410,29626,35884,39424,51491,51516,55523,74403)
df_eEP_Location_plot <- data.frame(iteration, position, value)
df_eEP_Location_plot$iteration <- fct_reorder(df_eEP_Location_plot$iteration,
-df_eEP_Location_plot$value)
fig <- ggplot(df_eEP_Location_plot, aes(y=value, x=iteration, fill=position)) +
geom_bar(stat="identity")
fig
I have two groups with one measurement variable.
I would like to plot them on one graph to see if they show a correlation or they overlap.
The measurement for both group is in the same scale.
I thought of doing a scatter plot, but in this case, I thought it would just give me a straight line as I only have one measurement.
Could I get some ideas and suggestions please?
You can unstack the data.
set.seed(1234)
df <- data.frame(var = rnorm(200, 50, 10), gp = gl(2,100))
head(df)
var gp
1 37.92934 1
2 52.77429 1
3 60.84441 1
4 26.54302 1
5 54.29125 1
6 55.06056 1
unstack(df)
X1 X2
1 37.92934 54.14524
2 52.77429 45.25282
3 60.84441 50.65993
4 26.54302 44.97522
5 54.29125 41.74001
6 55.06056 51.66989
And then plot this.
library(ggplot2)
library(dplyr)
unstack(df) %>% ggplot(aes(x=X1, y=X2)) +
geom_point() +
geom_smooth(method="lm")
I want to make a simple histogram which involves two vectors ,
values <- c(1,2,3,4,5,6,7,8)
freq <- c(4,6,4,4,3,2,1,1)
df <- data.frame(values,freq)
Now the data.farame df consists the following values :
values freq
1 4
2 6
3 4
4 4
5 3
6 2
7 1
8 1
Now I want to draw a simple histogram, in which values are on the x axis and freq is on y axis. I am trying to use the hist function, but I am not able to give two variables. How can I make a simple histogram from this data?
using ggplot2:
library(ggplot2)
ggplot(df, aes(x = values, y = freq)) +
geom_bar(stat="identity")
Since you have the frequencies already, what you really want is a bar plot:
barplot(df$freq,names.arg=df$values)
If you've got your heart set on using hist, you should do:
hist(rep(df$values,df$freq))
Please read ?barplot and ?hist for further plotting options.
Also, because I'm somewhat of a zealot, I think the code looks cleaner if you use data.table:
library(data.table)
setDT(df) #convert df to a data.table by reference
df[,barplot(freq,names.arg=values)]
and
df[,hist(rep(values,freq))]
My question maybe very simple but I couldn't find the answer!
I have a matrix with 12 entries and I made a stack barplot with barplot function in R.
With this code:
mydata <- matrix(nrow=2,ncol=6, rbind(sample(1:12, replace=T)))
barplot(mydata, xlim=c(0,25),horiz=T,
legend.text = c("A","B","C","D","E","F"),
col=c("blue","green"),axisnames = T, main="Stack barplot")
Here is the image from the code:
What I want to do is to give each of the group (A:F , only the blue part) a different color but I couldn't add more than two color.
and I also would like to know how can I start the plot from x=2 instead of 0.
I know it's possible to choose the range of x by using xlim=c(2,25) but when I choose that part of my bars are out of range and I get picture like this:
What I want is to ignore the part of bars that are smaller than 2 and start the x-axis from two and show the rest of bars instead of put them out of range.
Thank you in advance,
As already mentioned in the other post is entirely clear your desired output. Here another option using ggplot2. I think the difficulty here is to reshape2 the data, then the plot step is straightforwardly.
library(reshape2)
library(ggplot2)
## Set a seed to make your data reproducible
set.seed(1)
mydata <- matrix(nrow=2,ncol=6, rbind(sample(1:12, replace=T)))
## tranfsorm you matrix to names data.frame
myData <- setNames(as.data.frame(mydata),LETTERS[1:6])
## put the data in the long format
dd <- melt(t(myData))
## transform the fill variable to the desired behavior.
## I used cumsum to bes sure to have a unique value for all VAR2==2.
## maybe you should chyange this step if you want an alternate behvior
## ( see other solution)
dd <- transform(dd,Var2 =ifelse(Var2==1,cumsum(Var2)+2,Var2))
## a simple bar plot
ggplot(dd) +
## use stat identity since you want to set the y aes
geom_bar(aes(x=Var1,fill=factor(Var2),y=value),stat='identity') +
## horizontal rotation and zooming
coord_flip(ylim = c(2, max(dd$value)*2)) +
theme_bw()
Another option using lattice package
I like the formula notation in lattice and its flexibility for flipping coordinates for example:
library(lattice)
barchart(Var1~value,groups=Var2,data=dd,stack=TRUE,
auto.key = list(space = "right"),
prepanel = function(x,y, ...) {
list(xlim = c(2, 2*max(x, na.rm = TRUE)))
})
You do this by using the "add" and "offset" arguments to barplot(), along with setting axes and axisnames FALSE to avoid double-plotting: (I'm throwing in my color-blind color palette, as I'm red-green color-blind)
# Conservative 8-color palette adapted for color blindness, with first color = "black".
# Wong, Bang. "Points of view: Color blindness." nature methods 8.6 (2011): 441-441.
colorBlind.8 <- c(black="#000000", orange="#E69F00", skyblue="#56B4E9", bluegreen="#009E73",
yellow="#F0E442", blue="#0072B2", reddish="#D55E00", purplish="#CC79A7")
mydata <- matrix(nrow=2,ncol=6, rbind(sample(1:12, replace=T)))
cols <- colorBlind.8[1:ncol(mydata)]
bar2col <- colorBlind.8[8]
barplot(mydata[1,], xlim=c(0,25), horiz=T, col=cols, axisnames=T,
legend.text=c("A","B","C","D","E","F"), main="Stack barplot")
barplot(mydata[2,], offset=mydata[1,], add=T, axes=F, axisnames=F, horiz=T, col=bar2col)
For the second part of your question, the "offset" argument is used for the first set of bars also, and you change xlim and use xaxp to adjust the x-axis numbering, and of course you must also adjust the height of the first row of bars to remove the excess offset:
offset <- 2
h <- mydata[1,] - offset
h[h < 0] <- 0
barplot(h, offset=offset, xlim=c(offset,25), xaxp=c(offset,24,11), horiz=T,
legend.text=c("A","B","C","D","E","F"),
col=cols, axisnames=T, main="Stack barplot")
barplot(mydata[2,], offset=offset+h, add=T, axes=F, axisnames=F, horiz=T, col=bar2col)
I'm not entirely sure if this is what you're looking for: 'A' has two values (x1 and x2), but your legend seems to hint otherwise.
Here is a way to approach what you want with ggplot. First we set up the data.frame (required for ggplot):
set.seed(1)
df <- data.frame(
name = letters[1:6],
x1=sample(1:6, replace=T),
x2=sample(1:6, replace=T))
name x1 x2
1 a 5 3
2 b 3 5
3 c 5 6
4 d 3 2
5 e 5 4
6 f 6 1
Next, ggplot requires it to be in a long format:
# Make it into ggplot format
require(dplyr); require(reshape2)
df <- df %>%
melt(id.vars="name")
name variable value
1 a x1 5
2 b x1 3
3 c x1 5
4 d x1 3
5 e x1 5
6 f x1 6
...
Now, as you want some bars to be a different colour, we need to give them an alternate name so that we can assign their colour manually.
df <- df %>%
mutate(variable=ifelse(
name %in% c("b", "d", "f") & variable == "x1",
"highlight_x1",
as.character(variable)))
name variable value
1 a x1 2
2 b highlight_x1 3
3 c x1 4
4 d highlight_x1 6
5 e x1 2
6 f highlight_x1 6
7 a x2 6
8 b x2 4
...
Next, we build the plot. This uses the standard colours:
require(ggplot2)
p <- ggplot(data=df, aes(y=value, x=name, fill=factor(variable))) +
geom_bar(stat="identity", colour="black") +
theme_bw() +
coord_flip(ylim=c(1,10)) # Zooms in on y = c(2,12)
Note that I use coord_flip (which in turn calls coord_cartesian) with the ylim=c(1,10) parameter to 'zoom in' on the data. It doesn't remove the data, it just ignores it (unlike setting the limits in the scale). Now, if you manually specify the colours:
p + scale_fill_manual(values = c(
"x1"="coral3",
"x2"="chartreuse3",
"highlight_x1"="cornflowerblue"))
I would like to simplify the proposed solution by #tedtoal, which was the finest one for me.
I wanted to create a barplot with different colors for each bar, without the need to use ggplot or lettuce.
color_range<- c(black="#000000", orange="#E69F00", skyblue="#56B4E9", bluegreen="#009E73",yellow="#F0E442", blue="#0072B2", reddish="#D55E00", purplish="#CC79A7")
barplot(c(1,6,2,6,1), col= color_range[1:length(c(1,6,2,6,1))])
assume the following frequency table in R, which comes out of a survey:
1 2 3 4 5 8
m 5 16 3 16 5 0
f 12 25 3 10 3 1
NA 1 0 0 0 0 0
The rows stand for the gender of the survey respondent (male/female/no answer). The colums represent the answers to a question on a 5 point scale (let's say: 1= agree fully, 2 = agree somewhat, 3 = neither agree nor disagree, 4= disagree somewhat, 5 = disagree fully, 8 = no answer).
The data is stored in a dataframe called "slm", the gender variable is called "sex", the other variable is called "tv_serien".
My problem is, that I don't find a (in my opinion) proper way to create a line chart, where the x-axis represents the 5-point scale (plus the don't know answers) and the y-axis represents the frequencies for every point on the scale. Furthemore I want to create two lines (one for males, one for females).
My solution so far is the following:
I create a plot without plotting the "content" and the x-axis:
plot(slm$tv_serien, xlim = c(1,6), ylim = c(0,100), type = "n", xaxt = "n")
The problem here is that it feels like cheating to specify the xlim=c(1,6), because the raw scores of slm$tv_serienare 100 values. I tried also to to plot the variable via plot(factor(slm$tv_serien)...), but then it would still create a metric scale from 1 to 8 (because the dont know answer is 8).
So my first question is how to tell R that it should take the six distinct values (1 to 5 and 8) and take that as the x-axis?
I create the new x axis with proper labels:
axis(1, 1:6, labels = c("1", "2", "3", "4", "5", "DK"))
At least that works pretty well. ;-)
Next I create the line for the males:
lines(1:5, table(slm$tv_serien[slm$sex == 1]), col = "blue")
The problem here is that there is no DK (=8) answer, so I manually have to specify x = 1:5 instead of 1:6 in the "normal" case. My question here is, how to tell R to also draw the line for nonexisting values? For example, what would have happened, if no male had answered with 3, but I want a continuous line?
At last I create the line for females, which works well:
lines(1:6, table(slm$tv_serien[slm$sex == 2], col = "red")
To summarize:
How can I tell R to take the 6 distinct values of slm$tv_serien as the x axis?
How can i draw continuous lines even if the line contains "0"?
Thanks for your help!
PS: Attached you find the current plot for the abovementiond functions.
PPS: I tried to make a list from "1." to "4." but it seems that every new list element started again with "1.". Sorry.
Edit: Response to OP's comment.
This directly creates a line chart of OP's data. Below this is the original answer using ggplot, which produces a far superior output.
Given the frequency table you provided,
df <- data.frame(t(freqTable)) # transpose (more suitable for plotting)
df <- cbind(Response=rownames(df),df) # add row names as first column
plot(as.numeric(df$Response),df$f,type="b",col="red",
xaxt="n", ylab="Count",xlab="Response")
lines(as.numeric(df$Response),df$m,type="b",col="blue")
axis(1,at=c(1,2,3,4,5,6),labels=c("Str.Agr.","Sl.Agr","Neither","Sl.Disagr","Str.Disagr","NA"))
Produces this, which seems like what you were looking for.
Original Answer:
Not quite what you asked for, but converting your frequency table to a data frame, df
df <- data.frame(freqTable)
df <- cbind(Gender=rownames(df),df) # append rownames (Gender)
df <- df[-3,] # drop unknown gender
df
# Gender X1 X2 X3 X4 X5 X8
# m m 5 16 3 16 5 0
# f f 12 25 3 10 3 1
df <- df[-3,] # remove unknown gender column
library(ggplot2)
library(reshape2)
gg=melt(df)
labels <- c("Agree\nFully","Somewhat\nAgree","Neither Agree\nnor Disagree","Somewhat\nDisagree","Disagree\nFully", "No Answer")
ggp <- ggplot(gg,aes(x=variable,y=value))
ggp <- ggp + geom_bar(aes(fill=Gender), position="dodge", stat="identity")
ggp <- ggp + scale_x_discrete(labels=labels)
ggp <- ggp + theme(axis.text.x = element_text(angle=90, vjust=0.5))
ggp <- ggp + labs(x="", y="Frequency")
ggp
Produces this:
Or, this, which is much better:
ggp + facet_grid(Gender~.)