I have a dataset of about 1000 records, following is the sample of it-
Var1 Freq
3 Abhay Jadhav 22
4 Abhijit Rana 8
5 Abhinav Sahu 24
6 Abhishek Chaudhary 22
7 Abhishek Dutt 7
8 Abhishek Gautam 7
9 Abhishek Mishra 13
10 Abhishek Mukherjee 23
11 Abhishek Nair 22
12 Abhishek Panigrahi 15
13 Abhishek Tiwari 21
14 Abzal Ayub 5
15 Adhiraj Banerjee 7
I want to plot the same within the range of Freq like (1..5 , 6..10,11...) , the number of var1 .
Like
1..5 => 3 Var1 Items
6...10 => 10 Var1 Items
Wold like to use ggplot for doing the same,
I tried to use normal plot with break but was not impressed and my intention to use ggplot only.
I am fine to use histogram or barplot or any better option
I think this is what you're looking for:
df$group <- cut(df$Freq, breaks = seq(0, max(df$Freq) + 4, by = 5), include.lowest = T)
ggplot(df, aes(x = group)) + geom_bar()
Related
How to create the ordered bar plot in ggplot2 with both positive and negative values. Here is the data:
down -11
down -10
down -9
down -6
up 6
up 6
up 6
up 6
up 7
up 7
up 8
up 8
up 8
up 8
up 8
up 8
up 8
up 10
up 10
up 11
up 11
up 12
up 14
up 14
up 21
up 21
up 24
I have tried this code:
ggplot(GO, aes(x = d1, y = order(d2), fill = factor(d1))) +
geom_bar(stat = "identity", position = "identity", width = 0.6)
This is not working.
I would like to order the plot. Can anybody please suggest some code.
Please check out my answer for a similar question. You should set your vector up in the order you want and then use +scale_y_discrete(limits = yourOrderedData) and it should plot in your order.
I got a data in table form which look like this in R:
V1 V2
1 19 -1539
2 7 -1507
3 3 -1446
4 7 -1427
5 8 -1401
6 2 -422
7 22 4178
8 5 4277
9 10 4303
10 18 4431
....200 million more lines to go
I would like to plot a density plot for the value in the second column with respect to the label in the first column (i.e. each label has on density curve on a same graph). But I don't know how. Any suggestion?
If I understood the question correctly, this would end up somewhat like a density heatmap in the end. (Considering there are 200 million observations total and V1 has fairly considerable range of variation)
For that I would try ggplot and stat_binhex:
df <- read.table(text="V1 V2
1 19 -1539
2 7 -1507
3 3 -1446
4 7 -1427
5 8 -1401
6 2 -422
7 22 4178
8 5 4277
9 10 4303
10 18 4431")
library(ggplot2)
ggplot(data=df,aes(V1,V2)) +
stat_binhex() +
scale_fill_gradient(low="red", high="steelblue") +
scale_y_continuous() +
theme_bw()
stat_binhex should work well with large data and has several parameters that will help with presentation (like bins, binwidth. See ?stat_binhex)
OK I figure it out by myself
ggplot(data, aes(x=V2, color=V1)) + geom_density(aes(group=V1))
Should be able to do that.
However there is two thing I need to make sure first in order to let it run:
V1 is a factor
V2 is a numerical value
The data I got wasn't set directly by read.tables in the way I want, so I have to do the following before using ggplot:
data$V1 = as.factor(data$V1)
data$V2 = as.numeric(as.character(data$V2))
Column data$form contains 170 unique different values, (numbers from 1 to ~800).
I would like to merge some values (e.g with a 10 radius/step).
I need to do this in order to use:
colors = rainbow(length(unique(data$form)))
In a plot and provide a better visual result.
Thank you in advance for your help.
you can use %/% to group them and mean to combine them and normalize to scale them.
# if you want specifically 20 groups:
groups <- sort(form) %/% (800/20)
x <- c(by(sort(form), groups, mean))
x <- normalize(x, TRUE) * 19 + 1
0 1 2 3 4
1.000000 1.971781 2.957476 4.103704 4.948560
5 6 7 8 9
5.950617 7.175309 7.996914 8.953086 9.952263
10 11 12 13 14
10.800705 11.901235 12.888889 13.772291 14.888889
15 16 17 18 19
15.927984 16.864198 17.918519 18.860082 20.000000
You could also use cut. If you use the argument labels=FALSE, you get an integer value:
form <- runif(170, min=1,max=800)
> cut(form, breaks=20)
[1] (518,558] (280,320] (240,280] (121,160] (757,797]
[6] (160,200] (320,359] (598,638] (80.8,121] (359,399]
[7] (121,160] (200,240] ...
20 Levels: (1.18,41] (41,80.8] (80.8,121] (121,160] (160,200] (200,240] (240,280] (280,320] (320,359] (359,399] (399,439] ... (757,797]
> cut(form, breaks=20, labels=FALSE)
[1] 14 8 7 4 20 5 9 16 3 10 4 6 5 18 18 6 2 12
[19] 2 19 13 11 13 11 14 12 17 5 ...
On a side-note, I want you to re-consider plotting with rainbow colours, as it distorts reading the data, cf. Rainbow Color Map (Still) Considered Harmful.
I need help with a R plot, with a data format I have not worked with before. Please help if you know.
NUMBER FREQUENCY
10 1
11 1
12 3
10 45
11 2
12 3
i need a bar plot with numbers on X axis (continuous, not bins in histogram) and frequency on Y, but combined.
like
10 46
11 3
12 6
it seems simple enough, but i have 10,000 rows and large numbers in real data so I am looking for a good solution in R without doing it manually.
What about:
##tapply splits dd$FREQ by dd$NUM and "sums" them
barplot(tapply(dd$FREQUENCY, dd$NUMBER, sum))
to get:
Read in your data:
dd = read.table(textConnection("NUMBER FREQUENCY
10 1
11 1
12 3
10 45
11 2
12 3"), header=TRUE)
I'm trying to create a stacked bar graph using ggplot 2. My data in its wide form, looks like this. The numbers in each cell are the frequency of responses.
activity yes no dontknow
Social events 27 3 3
Academic skills workshops 23 5 8
Summer research 22 7 7
Research fellowship 20 6 9
Travel grants 18 8 7
Resume preparation 17 4 12
RAs 14 11 8
Faculty preparation 13 8 11
Job interview skills 11 9 12
Preparation of manuscripts 10 8 14
Courses in other campuses 5 11 15
Teaching fellowships 4 14 16
TAs 3 15 15
Access to labs in other campuses 3 11 18
Interdisciplinary research 2 11 18
Interdepartamental projects 1 12 19
I melted this table using reshape2 and
melted.data(wide.data,id.vars=c("activity"),measure.vars=c("yes","no","dontknow"),variable.name="haveused",value.name="responses")
That's as far as I can get. I want to create a stacked bar chart with activities on the x axis, frequency of responses in the y axis, and each bar showing the distribution of the yes, nos and dontknows
I've tried
ggplot(melted.data,aes(x=activity,y=responses))+geom_bar(aes(fill=haveused))
but I'm afraid that's not the right solution
Any help is much appreciated.
You haven't said what it is that's not right about your solution. But some issues that could be construed as problems, and one possible solution for each, are:
The x axis tick mark labels run into each other. SOLUTION - rotate the tick mark labels;
The order in which the labels (and their corresponding bars) appear are not the same as the order in the original dataframe. SOLUTION - reorder the levels of the factor 'activity';
To position text inside the bars set the vjust parameter in position_stack to 0.5
The following might be a start.
# Load required packages
library(ggplot2)
library(reshape2)
# Read in data
df = read.table(text = "
activity yes no dontknow
Social.events 27 3 3
Academic.skills.workshops 23 5 8
Summer.research 22 7 7
Research.fellowship 20 6 9
Travel.grants 18 8 7
Resume.preparation 17 4 12
RAs 14 11 8
Faculty.preparation 13 8 11
Job.interview.skills 11 9 12
Preparation.of.manuscripts 10 8 14
Courses.in.other.campuses 5 11 15
Teaching.fellowships 4 14 16
TAs 3 15 15
Access.to.labs.in.other.campuses 3 11 18
Interdisciplinay.research 2 11 18
Interdepartamental.projects 1 12 19", header = TRUE, sep = "")
# Melt the data frame
dfm = melt(df, id.vars=c("activity"), measure.vars=c("yes","no","dontknow"),
variable.name="haveused", value.name="responses")
# Reorder the levels of activity
dfm$activity = factor(dfm$activity, levels = df$activity)
# Draw the plot
ggplot(dfm, aes(x = activity, y = responses, group = haveused)) +
geom_col(aes(fill=haveused)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.25)) +
geom_text(aes(label = responses), position = position_stack(vjust = .5), size = 3) # labels inside the bar segments