Sorry if this sounds a bit messy, I'm new to using R. I have a data frame named "AB13" ( a postcode) and I am using a list of all postcodes which I imported as a .csv file. Is there any way I can print one of the columns and run it through the console automatically. Say print the 10th element of the list, which is AB13. Then it will display AB13 ( the data frame)?
I have tried using print, cat and multiple other print functions but I haven't been able to get anywhere.
You can do
get(your_list[[10]])
Related
I am reading some files into R with a "for loop" and naming them based on the looping index. I have used the assign fucntion to dynamically name one data frame for each file being read as follows:
for (i in 1:10){
assign(paste0("df",i),read_csv(paste0("file",i,".csv")))
}
This works fine. However, while inside the for loop, I also want to do some other operations to the data frame, but I dont know how to refer to it given that the name is changing as the loop progresses.
I want to add to the loop something along the lines of:
names(paste0("df",i)) <- make.names(names(paste0("df",i)))
I want to execute the above command but I don't know how to properly pass the changing data frame name to the names() function.
Thanks in advance,
MR
I am a novice in R and I have been having some trouble trying to get R and Excel to cooperate.
I have written a code that makes it able to compare two vectors with each other and determine the differences between them:
data.x<-read.csv(file.choose(), header=T)
data.y<-read.csv(file.choose(), header=T)
newdata.x<-grep("DAG36|G379",data.x,value=TRUE,invert=TRUE)
newdata.x
newdata.y<-grep("DAG36|G379",data.y,value=TRUE,invert=TRUE)
newdata.y
setdiff(newdata.x,newdata.y)
setdiff(newdata.y,newdata.x)
The data I want to transfer from Excel to R is a long row of numbers placed as so:
“312334-2056”, “457689-0932”, “857384-9857”,….,
There are about 350 of these numbers placed in their own separate cell along a single row.
I used the command: = """" & A1 & """" To put double quotes around every number in order for R to read it properly.
At first I tried to simply copy/paste the data directly into a vector in R, but it's as if R won’t read it as a single row of data and therefore splits it up.
I also tried to save the excel file as a CSV file but that didn’t work either.
Lastly I tried to open it directly in to R using the command:
data.x<- read.csv(file.choose(), header=T)
But as I type in: data.x and press enter it simply says:
<0 rows> (or 0-lenghts row.names)
I simply can’t figure out what I’m doing wrong. Any help would be greatly appreciated.
It's hard to access without a reproducible example, but you should be able to transpose the Excel file into a single column. Then import using read_csv from the readr package. Take a look at the tidyverse package, which will contain some great tools to import and work with this type of data.
I use https://github.com/tidyverse/readxl/. It makes it easy to maintain formatting from excel into type safe tibbles.
If you can share some sample data a working solution can be generated.
It should be very simple, but for now cannot figure it out. Say I create a generic dataframe with some data in a loop, let's call it df.
Now I want to assign a specific name to it and want to save it to specific destination. I generate two character variables - filename and file_destination and try to use the following in the script code:
assign(filename, df)
save(filename, file = file_destination)
Of course it save just a string with a name in the file and not the actual data.
How do i save the dataframe created via assign(filename,df)?
Try save(list=filename,file=file_destination). Also, use better names for your variables. filename for an object which is not a file name is very odd.
Put this as answer, to ensure other people find it easily.
I've been given SAS data which I'd like to export to CSV, so that I can analyze it using R. I've never used SAS but I found Efficiently convert a SAS dataset into a CSV, which explains how to convert to CSV using code like this:
proc export data=sashelp.class
outfile='c:\temp\sashelp class.csv'
dbms=csv
replace;
run;
This works, but I've noticed that I end up with what I'll call short column names in the CSV, whereas I see long, verbose column descriptions when I look at the data in SAS (i.e. using the SAS software).
I'd like to programmatically save those column descriptions to a txt file, so that I can read them into an R vector. In other words, I'm happy having the short column names in my CSV header (i.e. the first line of my CSV), but I'd like to also have a second file, with only one line, containing the longer column descriptions. How do I do that? I googled and didn't notice anything helpful.
To give an example, the long column descriptions I see in SAS might be something like "Number of elephants in Tanzania", with a corresponding short column name of "ElephTanz".
You can use the SAS "dictionary" library to access this kind of info. The following code creates a table work.column_labels that has two columns: the "short name" you're seeing and the longer label that appears when you view the data in SAS. (Note that the sashelp.class data doesn't happen to have labeled columns to this particular example will have the second column empty.)
proc sql;
create table work.column_lables as
select Name,label
from dictionary.columns
where libname = 'SASHELP'
and memname = 'CLASS';
quit;
Then you can export this table to a csv using code similar to what you already have.
I am looking for an easy way to get objects into MS Excel.
(I am using the preinstalled "Puromycin"-dataset for the examples)
I would like to place the contents of these objects to a single excel file:
Puromycin
summary(Puromycin$rate)
summary(Purymycin$conc)
table(Puromycin$state)
lm( conc ~ rate , data=Puromycin)
By "contents" i mean what is shown in the console when i press enter. I dont know what to call it.
I tried to do this:
sink("datafilewhichexcelhopefullyunderstands.csv")
Puromycin
summary(Puromycin$rate)
summary(Purymycin$conc)
table(Puromycin$state)
lm( conc ~ rate , data=Puromycin)
sink()
This gives med a file with the CSV-extension, however when i open the file in notepad,
there is comma-separation. That means that i cant get Excel to open it properly. By properly
i mean that each number is in its own cell.
Others have suggested this for a similar problem
https://stackoverflow.com/a/13007555/1831980
But as a novice i feel that the solution is too complex, and I am hoping for a simpler method.
What I am doing now is this:
write.table(Puromycin, file="clipboard" , sep=";" , row.names=FALSE )
write.table(summary(Purymycin$conc), file="clipboard" , sep=";" , row.names=FALSE )
... etc...
But this requires i lot of copy-ing and pasting, which I hope to eliminate.
Any help would appreciated.
write.table and its friends are intended to write out columns of data separated by whatever separator is specified. Your clipboard contains several data types because you are using summary which always gives a unique output.
For writing the data values out, you can use write.csv on a data frame and then open with Excel. For example, Puromycin is already a data frame (which you can see with str(Puromycin)) so you can just write it out directly:
write.csv(file = "some file.csv", x = Puromycin)
Which will go into the current working directory (which can be determined with getwd()).
To write out/save the results of the regression model is a bit more of a challenge. You could definitely use sink as you did, but specify an extension of .txt on your file so a text editor can open it. There are fancier methods (sweave, knitr) which you might want to look into in the long run, as they can write really nice reports automatically.
In the meantime, get to know str(any R object) as it will be your friend. You can see all the objects in your workspace with ls().
This will only be helpful if you are prepared to use Excel's Data/Text to Columns functions:
capture.output( sapply( c(Puromycin,
summary(Puromycin$rate),
summary(Puromycin$conc),
table(Puromycin$state),
lm( conc ~ rate , data=Puromycin) ), FUN=print), file="datafilewhichexcelhopefullyunderstands.csv", append=TRUE)
The problem being that Excel will not read the whitespace as a cell separator unless you specifically tell it to. You can (and I have often done so) use the fixed filed input features offered by the Text-to-Columns dialog interface.
Your simplest option may be to use the RExcel tool, it transfers information between R and Excel. However it is not free software.
The XLConnect package is another option, it can be used to write information directly to an Excel file.
The tricky part is the lm call. lm does not return a simple vector, matrix, or data frame (all of which are easy to convert to csv or send directly) and there is not a clear way to convert the various parts of a list to cells in a spreadsheet. What would be better is to use extractor functions to pull the important parts from the return of lm or the summary of the lm object and send those to Excel using the other tools.
If you can tell us more about why you want the numbers in Excel and what you plan to do with them after, then we may be able to offer better help (you may be able to completely skip excel).
If the main goal is to share output with others then you should really look at the knitr package (or other related packages). This will not create Excel files, but can be used (along with the pandoc program and possibly other tools) to create a report file in a format easy to share with others not familiar with R. You could put everything into a .pdf file or a .docx file (the latter read by MS Word and would have tables wich can be edited using Word). There is not a simple way to get edits back into R, but with the track changes you can easily see what changes have been made and hand edit your R script/template accordingly.