I was wondering how I could view certain lines of data based on specific data i.e. good for viewing anomalies in results.
E.g. I have the following results from the command table(df$A)
2 3 4 5 6 19
143914 52194 30856 10662 2901 1
I'm surprised by the 1 observation where df$A=19. How can I see this observation easily in the console without having to make a subset (x<-subset(df, df$A==19)) ?
Thanks in advance
If your goal is to just view the output in an interactive session, and you have no interest in storing that value, you can use [ to "interactively" subset and view the result:
df[df$A == 19, ]
Related
Okay, let me be as clear as I can in my problem. I'm new to R, so your patience is appreciated.
I want to create a histogram using two different vectors. The first vector contains a list of models (products). These models are listed as either integers, strings, or NA. I'm not exactly sure how R is storing them (I assume they're kept as strings), or if that is a relevant issue. I also have a vector containing a list of incidents pertaining to that model. So for example, one row in the dataframe might be:
Model Incidents
XXX1991 7
How can I create a histogram where the number of incidents for each model is shown? So the histogram will look like
| =
| =
Frequency of | =
Incidents | = =
| = = =
| = = = = =
- - - - - -
Each different Model
Just to give a general idea.
I also need to be able to map everything out with standard deviation lines, so that it's easy to see which models are the least reliable. But that's not the main question here. I just don't want to do anything that will make me unable to use standard deviation in the future.
So far, all I really understand is how to make a histogram with the frequency marked, but for some reason, the x-axis is marked with numbers, not the models' names.
I don't really care if I have to download new packages to make this work, but I suspect that this already exists in basic R or ggplot2 and I'm just too dumb to figure it out.
Feel free to ask clarfying questions. Thanks.
EDIT: I forgot to mention, there are multiple rows of incidents listed under each model. So to add to my example earlier:
Model Incidents
XXX1991 7
XXX1991 1
XXX1991 19
3
5
XXX1002 9
XXX1002 4
etc . . .
I want to add up all the incidents for a model under one label.
I am assuming that you did not mean to leave the model blank in your example, so I filled in some values.
You can add up the number of incidents by model using aggregate then make the relevant plot using barplot.
## Example Data
data = read.table(text="Model Incidents
XXX1991 7
XXX1991 1
XXX1991 19
XXX1992 3
XXX1992 5
XXX1002 9
XXX1002 4",
header=TRUE)
TAB = aggregate(data$Incidents, list(data$Model), sum)
TAB
Group.1 x
1 XXX1002 13
2 XXX1991 27
3 XXX1992 8
barplot(TAB$x, names.arg=TAB$Group.1 )
I am working on a project for school in R that is looking at swimming data compiled up of 8 different teams looking at each of the 13 events, over 6 years. I have over 8700 rows of data that I have appended and am trying to find out how to draw the specific means that I am looking for. For example, I would like to look at the progression of mean times for team 1 for event 3 for men. Thanks!
You can subset your data-frame to only include those variables, e.g.
ss = subset(df, team == 1 & event == 3)
mean(ss$times)
In SparkR I have a DataFrame data. It contains time, game and id.
head(data)
then gives ID = 1 4 1 1 215 985 ..., game = 1 5 1 10 and time 2012-2-1, 2013-9-9, ...
Now game contains a gametype which is numbers from 1 to 10.
For a given gametype I want to find the minimum time, meaning the first time this game has been played. For gametype 1 I do this
data1 <- filter(data, data$game == 1)
This new data contains all data for gametype 1. To find the minimum time I do this
g <- groupBy(data1, game$time)
first(arrange(g, desc(g$time)))
but this can't run in sparkR. It says "object of type S4 is not subsettable".
Game 1 has been played 2012-01-02, 2013-05-04, 2011-01-04,... I would like to find the minimum-time.
If all you want is a minimum time sorting a whole data set doesn't make sense. You can simply use min:
agg(df, min(df$time))
or for each type of game:
groupBy(df, df$game) %>% agg(min(df$time))
By typing
arrange(game, game$time)
I get all of the time sorted. By taking first function I get the first entry. If I want the last entry I simply type this
first(arrange(game, desc(game$time)))
Just to clarify because this is something I keep running into: the error you were getting is probably because you also imported dplyr into your environment. If you would have used SparkR::first(SparkR::arrange(g, SparkR::desc(g$time))) things would probably have been fine (although obviously the query could've been more efficient).
I have a large data set in which I have to search for specific codes depending on what i want. For example, chemotherapy is coded by ~40 codes, that can appear in any of 40 columns called (diag1, diag2, etc).
I am in the process of writing a function that produces plots depending on what I want to show. I thought it would be good to specify what I want to plot in a input data frame. Thus, for example, in case I only want to plot chemotherapy events for patients, I would have a data frame like this:
Dataframe name: Style
Name SearchIn codes PlotAs PlotColour
Chemo data[substr(names(data),1,4)=="diag"] 1,2,3,4,5,6 | red
I already have a function that searches for codes in specific parts of the data frame and flags the events of interest. What i cannot do, and need your help with, is referring to a data frame (Style$SearchIn[1]) using codes in a data frame as above.
> Style$SearchIn[1]
[1] data[substr(names(data),1,4)=="diag"]
Levels: data[substr(names(data),1,4)=="diag"]
I thought perhaps get() would work, but I cant get it to work:
> get(Style$SearchIn[1])
Error in get(vars$SearchIn[1]) : invalid first argument
enter code here
or
> get(as.character(Style$SearchIn[1]))
Error in get(as.character(Style$SearchIn[1])) :
object 'data[substr(names(data),1,5)=="TDIAG"]' not found
Obviously, running data[substr(names(data),1,5)=="TDIAG"] works.
Example:
library(survival)
ex <- data.frame(SearchIn="lung[substr(names(lung),1,2) == 'ph']")
lung[substr(names(lung),1,2) == 'ph'] #works
get(ex$SearchIn[1]) # does not work
It is not a good idea to store R code in strings and then try to eval them when needed; there are nearly always better solutions for dynamic logic, such as lambdas.
I would recommend using a list to store the plot specification, rather than a data.frame. This would allow you to include a function as one of the list's components which could take the input data and return a subset of it for plotting.
For example:
library(survival);
plotFromSpec <- function(data,spec) {
filteredData <- spec$filter(data);
## ... draw a plot from filteredData and other stuff in spec ...
};
spec <- list(
Name='Chemo',
filter=function(data) data[,substr(names(data),1,2)=='ph'],
Codes=c(1,2,3,4,5,6),
PlotAs='|',
PlotColour='red'
);
plotFromSpec(lung,spec);
If you want to store multiple specifications, you could create a list of lists.
Have you tried using quote()
I'm not entirely sure what you want but maybe you could store the things you're trying to get() like
quote(data[substr(names(data),1,4)=="diag"])
and then use eval()
eval(quote(data[substr(names(data),1,4)=="diag"]), list(data=data))
For example,
dat <- data.frame("diag1"=1:10, "diag2"=1:10, "other"=1:10)
Style <- list(SearchIn=c(quote(data[substr(names(data),1,4)=="diag"]), quote("Other stuff")))
> head(eval(Style$SearchIn[[1]], list(data=dat)))
diag1 diag2
1 1 1
2 2 2
3 3 3
4 4 4
5 5 5
6 6 6
thank you for the help. I am attempting to write an equation that uses values selected from an .csv file. It looks something like this, let's call it df.
df<-read.csv("SiteTS.csv", header=TRUE,sep=",")
df
Site TS
1 H4A1 -42.75209
2 H4A2 -43.75101
3 H4A3 -41.75318
4 H4C3 -46.76770
5 N1C1 -42.68940
6 N1C2 -36.95200
7 N1C3 -43.16750
8 N2A2 -38.58040
9 S4C1 -35.32000
10 S4C2 -34.52420
My equation requires the value in the TS column for each site. I am attempting to create a new column called SigmaBS with the results of the equation using TS.
df["SigmaBS"]<-10^(subset(df, Site=="H4A1"/10)
Which is where I am running into issues, as the subset function returns all columns that correlate with the Site column = H4A1
subset(df, Site =="H4A1")
Site TS
1 2411 -42.75209
But again, I only need the value -42.75209.
I apologize if this is a simple question, but I would very much appreciate any help you may be able to offer.
If you insist on using the subset function, it has a select argument:
subset(df, Site=="H4A1", select="TS")
A better option is to use [] notation:
df[df$Site=="H4A1", "TS"]
Or the $ operator:
subset(df, Site=="H4A1")$TS
You can use this simple command:
df$SigmaBS <- 10 ^ (df$TS / 10)
It sounds like you're trying to create a new column called SigmaBS where the values in each row are 10^(value of TS) / 10
If so, this code should work:
SigmaBS <- sapply(df$TS, function(x) 10^(x/10))
df$SigmaBS <- SigmaBS