I am trying to create a Stacked Bar Graph using ggplot2. Here is how my data looks like
Date Full.Page.Ads Total.Pages
11/10/2015 3 24
12/10/2015 10 24
13/10/2015 15 24
This is the code which I am trying to use to visualize the data
library("ggplot2")
library("reshape2")
ns <- read.csv("NS.csv")
ggplot(data=ns, aes(x = Date, y = Total.Pages, fill=Full.Page.Ads)) + geom_bar(stat = "identity")
But for some reason rather than making a proper stacked bar chart, it keeps making something like this http://imgur.com/rqxEzjF.jpg. Rather than this I would like to show the main bars as Total.Pages and inside those bars, Full.Page.Ads bar in different colours.
I am not sure what I am doing wrong out here.
This is a sample of what I am aspiring to make http://blog.visual.ly/wp-content/uploads/2012/08/StackedPercent.png
You have to melt your data before plotting. You also need to compute the difference between Total.Pages and Full.Page.Ads if you want your graph to represent the proportion of Full.Page.Ads with respect to the total number of pages. Something like:
ns <- data.frame(Date = c("11/10/2015", "12/10/2015", "13/10/2015"),
Full.Page.Ads = c(3, 10, 15),
Total.Pages = c(24, 24, 24))
# Date Full.Page.Ads Total.Pages
# 1 11/10/2015 3 24
# 2 12/10/2015 10 24
# 3 13/10/2015 15 24
ns$not.Full.Page.Ads <- ns$Total.Pages - ns$Full.Page.Ads
ns$Total.Pages <- NULL
ns2 <-melt(ns)
# Date variable value
#1 11/10/2015 Full.Page.Ads 3
#2 12/10/2015 Full.Page.Ads 10
#3 13/10/2015 Full.Page.Ads 15
#4 11/10/2015 not.Full.Page.Ads 21
#5 12/10/2015 not.Full.Page.Ads 14
#6 13/10/2015 not.Full.Page.Ads 9
ggplot(data = ns2, aes(x = Date, y = value, fill = variable)) + geom_bar(stat = "identity")
Related
I need some help. Here is my data which i want to plot. I want to keep $path.ID on y axis and numerics of all other columns added stepwise. this is a subset of very large dataset so i want to pathID labels attached to each line. and also the values of the other columns with each point if possible.
head(table)
Path.ID sc st rc rt
<chr> <dbl> <dbl> <dbl> <dbl>
1 map00230 1 12 5 52
2 map00940 1 20 10 43
3 map01130 NA 15 8 34
4 map00983 NA 14 5 28
5 map00730 NA 5 3 26
6 map00982 NA 16 2 24
somewhat like this
Thank you
Here is the pseudo code.
library(tidyr)
library(dplyr)
library(ggplot2)
# convert your table into a long format - sorry I am more used to this type of data
table_long <- table %>% gather(x_axis, value, sc:rt)
# Plot with ggplot2
ggplot() +
# draw line
geom_line(data=table_long, aes(x=x_axis, y=value, group=Path.ID, color=Path.ID)) +
# draw label at the last x_axis in this case is **rt**
geom_label(data=table_long %>% filter(x_axis=="rt"),
aes(x=x_axis, y=value, label=Path.ID, fill=Path.ID),
color="#FFFFFF")
Note that with this code if a Path.ID doesn't have the rt value then it will not have any label
p<-ggplot() +
# draw line
geom_line(data=table_long, aes(x=x_axis, y=value, group=Path.ID, color=Path.ID)) +
geom_text(data=table_long %>% filter(x_axis=="rt"),
aes(x=x_axis, y=value, label=Path.ID),
color= "#050505", size = 3, check_overlap = TRUE)
p +labs(title= "title",x = "x-lable", y="y-label")
I had to use geom_text as i had large dataset and it gave me somewhat more clear graph
thank you #sinh it it helped a lot.
I'm trying to plot the following dataframe as bar plot, where the values for the filteredprovince column are listed on a separate column (n)
Usually, the ggplot and all the other plots works on horizontal dataframe, and after several searches I am not able to find a way to plot this "transposed" version of dataframe.
The cluster should group each bar graph, and within each cluster I would plot each filteredprovince based on the value of the n column
Thanks you for the support
d <- read.table(text=
" cluster PROVINCIA n filteredprovince
1 1 08 765 08
2 1 28 665 28
3 1 41 440 41
4 1 11 437 11
5 1 46 276 46
6 1 18 229 18
7 1 35 181 other
8 1 29 170 other
9 1 33 165 other
10 1 38 153 other ", header=TRUE,stringsAsFactors = FALSE)
UPDATE
Thanks to the suggestion in comments I almost achived the format desired :
ggplot(tab_s, aes(x = cluster, y = n, fill = factor(filteredprovince))) + geom_col()
There is any way to put on Y labels not frequencies but the % ?
If I understand correctly, you're trying to use the geom_bar() geom which gives you problems because it wants to make sort of an histogram but you already have done this kind of summary.
(If you had provided code which you have tried so far I would not have to guess)
In that case you can use geom_col() instead.
ggplot(d, aes(x = filteredprovince, y = n, fill = factor(PROVINCIA))) + geom_col()
Alternatively, you can change the default stat of geom_bar() from "count" to "identity"
ggplot(d, aes(x = filteredprovince, y = n, fill = factor(PROVINCIA))) +
geom_bar(stat = "identity")
See this SO question for what a stat is
EDIT: Update in response to OP's update:
To display percentages, you will have to modify the data itself.
Just divide n by the sum of all n and multiply by 100.
d$percentage <- d$n / sum(d$n) * 100
ggplot(d, aes(x = cluster, y = percentage, fill = factor(filteredprovince))) + geom_col()
I'm not sure I perfectly understand, but if the problem is the orientation of your dataframe, you can transpose it with t(data) where data is your dataframe.
I am working with longitudinal data and assess the utilization of a policy over 13 months. In oder to get some barplots with the different months on my x-axis, I converted my data from wide Format to Long Format.
So now, my dataset looks like this
id month hours
1 1 13
1 2 16
1 3 20
2 1 0
2 2 0
2 3 10
I thought, after reshaping I could easily use my newly created "month" variable as a factor and plot some graphs. However, it does not work out and tells me it's a list or an atomic vector. Transforming it into a factor did not work out - I would desperately Need it as a factor.
Does anybody know how to turn it into a factor?
Thank you very much for your help!
EDIT.
The OP's graph code was posted in a comment. Here it is.
library(ggplot2)
ggplot(data, aes(x = hours, y = month)) + geom_density() + labs(title = 'Distribution of hours')
# Loading ggplot2
library(ggplot2)
# Placing example in dataframe
data <- read.table(text = "
id month hours
1 1 13
1 2 16
1 3 20
2 1 0
2 2 0
2 3 10
", header = TRUE)
# Converting month to factor
data$month <- factor(data$month, levels = 1:12, labels = 1:12)
# Plotting grouping by id
ggplot(data, aes(x = month, y = hours, group = id, color = factor(id))) + geom_line()
# Plotting hour density by month
ggplot(data, aes(hours, color = month)) + geom_density()
The problem seems to be in the aes. geom_density only needs a x value, if you think about it a little, y doesn't make sense. You want the density of the x values, so on the vertical axis the values will be the values of that density, not some other values present in the dataset.
First, read in the data.
Indirekte_long <- read.table(text = "
id month hours
1 1 13
1 2 16
1 3 20
2 1 0
2 2 0
2 3 10
", header = TRUE)
Now graph it.
library(ggplot2)
g <- ggplot(Indirekte_long, aes(hours))
g + geom_density() + labs(title = 'Distribution of hours')
I'm trying to plot the number of observations for each instance of a word, both of which are stored in a data frame.
I can generate the plot with ggplot2, but the y-axis displays "1+e05", "2+e05",...,etc...instead of numerical values.
How can I modify this code so that the y-axis displays numbers instead?
Here is my code:
> w
p.word p.freq
1 the 294571
2 and 158624
3 you 84152
4 for 77117
5 that 71672
6 with 47987
7 this 42768
8 was 41088
9 have 39835
10 are 36458
11 but 33899
12 not 30370
13 all 27079
14 your 26923
15 just 25507
16 from 24497
17 out 22578
18 like 22501
19 what 22150
20 will 21530
21 they 21435
22 about 21184
23 one 20877
24 its 20109
ggplot(w, aes(x = p.word, y = p.freq))+ geom_bar(stat = "identity")
Here is the plot that is generated:
"1e+05" etc are numerical values (scientific notation).
If you want the long notation (e.g. "100,000") use library(scales) and the comma formatter:
library(scales)
ggplot(w, aes(x = p.word, y = p.freq))+ geom_bar(stat = "identity") +
scale_y_continuous(labels=comma)
I would like to create a multivariate boxplot time series with ggplot2 and I need to have an x axis that positions the boxplots based on their associated dates.
I found two posts about this question: one is Time series plot with groups using ggplot2 but the x axis is not a scale_x_axis so graph is biased in my case. The other one is ggplot2 : multiple factors boxplot with scale_x_date axis in R but the person uses an interaction function which i don't use in my case.
Here is an example file and my code:
dtm <- read.table(text="date ruche mortes trmt
03.10.2013 1 8 P+
04.10.2013 1 7 P+
07.10.2013 1 34 P+
03.10.2013 7 16 P+
04.10.2013 7 68 P+
07.10.2013 7 170 P+
03.10.2013 2 7 P-
04.10.2013 2 7 P-
07.10.2013 2 21 P-
03.10.2013 5 8 P-
04.10.2013 5 27 P-
07.10.2013 5 24 P-
03.10.2013 3 15 T
04.10.2013 3 6 T
07.10.2013 3 13 T
03.10.2013 4 6 T
04.10.2013 4 18 T
07.10.2013 4 19 T ", h=T)
require(ggplot2)
require(visreg)
require(MASS)
require(reshape2)
library(scales)
dtm$asDate = as.Date(dtm[,1], "%d.%m.%Y")
## Plot 1: Nearly what I want but is biased by the x-axis format where date should not be a factor##
p2<-ggplot(data = dtm, aes(x = factor(asDate), y = mortes))
p2 + geom_boxplot(aes(fill = factor(dtm$trmt)))
## Plot 2: Doesn't show me what I need, ggplot apparently needs a factor as x##
p<-ggplot(data = dtm, aes(x = asDate, y = mortes))
p + geom_boxplot(aes( group = asDate, fill=trmt) ) `
Can anyone help me with this issue, please?
Is this what you want?
Code:
p <- ggplot(data = dtm, aes(x = asDate, y = mortes, group=interaction(date, trmt)))
p + geom_boxplot(aes(fill = factor(dtm$trmt)))
The key is to group by interaction(date, trmt) so that you get all of the boxes, and not cast asDate to a factor, so that ggplot treats it as a date. If you want to add anything more to the x axis, be sure to do it with + scale_x_date().