I have a csv file with a list of bird species (heading=Sci.Name) which I would like to bulk enquire their CITES appendix listing using the "spp_taxonconcept" function in the package rcites.
After setting the token, loading the csv file and all the packages needed I use the following code to generate the result in the column named "results":
bird.cites<-mutate(bird.cites,results=map(Sci.Name,spp_taxonconcept(taxonomy="CITES")))
which returns the following error msg:
x argument "query_taxon" is missing, with no default
Elements of the object "Sci.Name" was not passed to spp_taxaonconcept as the first argument, which should be query_taxon = "sci names of individual species" using the map function.
Any help with this would be greatly appreciated!
I think there are some syntax issues Try. -
bird.cites <- mutate(bird.cites,results=map(Sci.Name,spp_taxonconcept, taxonomy="CITES"))
which can also be written as -
bird.cites <- mutate(bird.cites, results = map(Sci.Name,~spp_taxonconcept(.x, taxonomy="CITES")))
Related
I am using the package RGEE (R wrapper for the Google Earth Engine Python API). The function ee_print() seems to work perfectly for an ImageCollection of just one variable, but seems to fail for ImageCollection with different variables where one needs to select the variable of interest. Any ideas on how to approach this issues with the latter kind of data.
Here's an example code:
GRIDMET = ee$ImageCollection("IDAHO_EPSCOR/GRIDMET")
ee_print(GRIDMET)
Where I get the following error message in return:
Error in strsplit(code, ":") : non-character argument
Have you considered the following approach?
GRIDMET = ee$ImageCollection("IDAHO_EPSCOR/GRIDMET")
print(GRIDMET, type = getOption("rgee.print.option"))
And play with the list of all metadata properties
GRIDMET$propertyNames()$getInfo()# Get a list of all metadata properties
(GRIDMET$get("product_tags")$getInfo()) # you can choose to show a characteristic like "product_tags"
I am a beginner at using Rstudio and have been working through the exercises outlined as part of our course notes.
We are to work with the 'iris' dataset however I haven't been able to successfully save it as a valid data.frame. The best I have done is created an empty dataframe in the global environment with 0 obs. of 0 variables.
Here is some of the codes I have worked through and the outputs. I am very new to R and am struggling a little with using inbuilt data sets in terms of loading and using - I am ok with importing and creating however.
data()
> View(iris)
> iris<-write.csv(iris)
""
> iris
NULL
> str(iris)
NULL
> iris<-data.frame(iris)
> iris<-read.csv(iris.csv)
Error in read.table(file = file, header = header, sep = sep, quote = quote, :
object 'iris.csv' not found
> library(datasets)
> data.frame(iris)
data frame with 0 columns and 0 rows
I have tried > write.csv(iris, 'iris.csv') # no luck
First check if iris is already a data.frame by running the following command:-
is.data.frame(iris)
If the answer is TRUE, then run in the following command to write it to a .csv file:-
write.csv(iris, "/location/at/which/you/want/to/save/the/file)
If one wants to save objects as R objects, one has to use save() and the file extension has to be .RData. Like in you case you can run the following command:-
save(iris, file = '/location/iris.RData'
And you can load an .RData file with the load() function in R. In your case it could be :-
load('/location/iris.RData')
Some mistakes that you've made:-
In your second code line where you run
> iris<-write.csv(iris)
you've just provided write.csv with it's first argument called x, but never specified the second argument it requires which is file. And also, one never assign write.csv() function with it's arguments to an object with the help of <- because write.csv() is a function which does not returns a value or an object. Another example of a function like write.csv() could be library().
So the way you code flows is you worte a wrong syntax for by running the following line
> iris<-write.csv(iris)
and hence, you got a NULL object. And the str of a NULL object is itself NULL.
Then you created a data.frame objects by passing iris as a data object, but since earlier iris became a NULL object, data.frame of a NULL object is NULL. Since there never was an iris.csv file written, R won't be able to read it too.
Also in your read.csv() function, you passed the file argument as a data object and not as a path. This is why you got the error object 'iris.csv' not found and not as cannot open file 'iris.csv': No such file or directory. To pass it as a path you should always put the location of your file in quotes, either single or double.
If you ever you don't understand how you have to pass objects in a function, please run the command ?function_name, for example ?write.csv(), ?library, ?read.csv. This will provide you with documentation on the function. It will also provide you with usage examples.
I hope this helps.
We have always been an SPSS shop but we're trying to learn R. Been doing some basics. I am trying to do a simple t-test, just to learn that code.
Here's my code, and what's happening:
Code screenshot
I don't get why it says "score" isn't found. It's in the table, and the read.csv code defaults to assuming the first row contains headers. I can't see why it's not "finding" the column for score. I'm sure it's something simple, but would appreciate any help.
You didn't store your imported csv file in a variable. It printed to the console because it had nowhere else to go - it just gets printed and then thrown away. You need to assign it for it to be saved in memory:
my_data_frame <- read.csv("ttest.csv")
Now your data exists in the variable my_data_frame and you can use it by supplying it as the data argument:
t.test(score ~ class, mu=0, alt="two.sided", conf=0.95, var.eg=F, paired=F, data=my_data_frame)
Also, in general, I would recommend using read_csv from the package readr over the default read.csv - it's faster.
Finally, when you ask questions, please provide your code as text, not a picture. You should also provide your data or a toy dataset - you can use the function dput to print code that will create your data, or just provide the csv file or some code that creates toy data.
I am trying to create a script that I run about once a week. The goal is that it will go out and check an MS Excel file that a co-worker manages. It then tests to see if the date the file was modified is newer then the last time it was imported. If it is newer, it will import the file (I am using readxl package - WONDERFUL!) into a new object that is a named with the date the original Excel file was last modified included in the object name. I have everything working except for the assignment of the imported data.frame to a new object that includes the date.
An example of the code I am using is:
First I create an object with a path pointing to the file of interest.
pfdFilePath <- file.path("H:", "3700", "3780", "002-00", "3.
Project Information", "Program", "RAH program.xls")
after testing to verify the file has been modified, I have tried simple assignment ("test" is just an example for simplification):
paste("df-", as.Date(file.info(pfdFilePath)$mtime), sep = "") <- "test"
But that code produces an error:
Error in paste("df-", as.Date(file.info(pfdFilePath)$mtime), sep = "") <- "test" :
target of assignment expands to non-language object
I then try the assign function:
assign(paste("df-", as.Date(file.info(pfdFilePath)$mtime), sep = ""), "test")
Running this code creates an object that looks to be okay, but when I evaluate it, or try using str() or class() I get the following error:
Error in df - df-2016-08-09 :
non-numeric argument to binary operator
I am pretty sure this is an error that has to do with the environment I am using assign, but being relatively new to R, I cannot figure it out. I understand that the assign function seems to be frowned upon, but those warnings seem to centered on for-loops vs. lapply functions. I am not really iterating within a function though. Just a dynamically named object whenever I run a script. I can't come up with a better way to do it. If there is another way to do this that doesn't require the assign function, or a better way to use assign function , I would love to know it.
Thank you in advance, and sorry if this is a duplicate. I have spent the entire evening digging and can't derive what I need.
Abdou provided the key.
assign(paste0("df.", "pfd.", strftime(file.info(pfdFilePath)$mtime, "%Y%m%d")), "test01")
I also converted to the cleaner paste0 function and got rid of the dashes to avoid confusion. Lesson learned.
Works perfectly.
I am doing following in Cooccur library in R.
> fb<-read.table("Fb6_peaks.bed")
> f1<-read.table("F16_peaks.bed")
everything is ok with the first two commands and I can also display the data:
> fb
> f1
But when I give the next command as given below
> explore_pairs(c("fb", "f1"))
I get an error message:
Error in sum(sapply(tf1_s, score_sample, tf2_hits = tf2_s, hit_list = hit_l)) :
invalid 'type' (list) of argument
Could anyone suggest something?
Despite promising to release a version to the Bioconductor depository in the article the authors published over a year ago, they have still not delivered. The gz file that is attached to the article is not of a form that my installation recognizes. Your really should be corresponding with the authors for this question.
The nature of the error message suggests that the function is expecting a different data class. You should be looking at the specification for the arguments in the help(explore_pairs) file. If it is expecting 2 matrices, then wrapping data.matrix around the arguments may solve the problem, but if it is expecting a class created by one of that packages functions then you need to take the necessary step to construct the right objects.
The help file for explore_pairs does exist (at least in the MAN directory) and says the first argument should be a character vector with further provisos:
\arguments{
\item{factornames}{an vector of character strings, each naming a GFF-like
data frame containing the binding profile of a DNA-binding factor.
There is also a load utility, load_GFF, which I assume is designed for creation of such files.
Try rename your data frame:
names(fb)=c("seq","start","end")
Check the example datasets. The column names are as above. I set the names and it worked.