I've been given a data set for a project that I need to reformat in order to work with it.
The problem is that all of the column names and corresponding values are mashed into one column in the file. As shown in the picture.
I'm new to R so I hardly know how to work with complex commands.
My Questions:
Is there a simple way to separate this from 1 column into 12 columns?
Desire Output:
I'll also need to remove the periods between the column names and the semicolons between the values.
I just need to be able to do basic statistical analysis on the table.
Thanks
table
Although your data is in one column, it is semi colon separated. The read.csv function has the ability to accept a column separator:
df <- read.csv(file="path/to/your/file.txt", skip=1, header=FALSE, sep=";")
The above call will generate columns based on a ; separator. I skip the first line and ignore the header, because it is a single string. You may manually assign the columns names via:
names(df) <- c("name1", "name2", ..., "name12")
Related
Complete noob here, specially with R.
For a school project I have to work with a specific dataset which doesn't come with column names in the dataset it self but there is a .txt that has extra information regarding the dataset, including the column names. The problem I'm having is that when I load the dataset rstudio assumes that the first line of data is actually the column names. Initially I just substituted the name with colnames() but by doing so I ended up ignoring/deleting the first line of data, and I'm sure that's not the right away of dealing with it.
How can I go about adding the correct column names without deleting the first line of data? (Preferably inside R due to school work requirements)
Thanks in advance!
When we read the data with read.table, use header = FALSE so that it automatically assigns a column name
df1 <- read.table('file.txt', header = FALSE)
Then, we can assign the preferred column names from the other .txt column
colnames(df1) <- scan('names.txt', what = '', quiet = TRUE)
I have a data frame in R containing over 29,000 rows. I need to remove multiple rows using only a list of names (187 names).
My dataset is about airlines, and I need to remove specific airlines from my data set that contains over 200 types of airlines. My first column contains all airline names, and I need to remove the entire row for those specific airlines.
I singled out all airline names that I want removed by this code: transmute(a_name_remove, airline_name). This gave me a table of all names of airlines that I want removed, now I have to remove that list of names from my original dataset named airlines.
I know there is a way to do this manually, which is: mydata[-c("a", "b"), ], for example. But writing out each name would be hectic.
Can you please help me by giving me a way to use the list that I have to forwardly remove those rows from my dataset?
I cannot write out each name on its own.
I also tried this: airlines[!(row.names(airlines) %in% c(remove)), ], in which I made my list "removed" into a data frame and as a vector, then used that code to remove it from my original dataset "airlines", still did not work.
Thank you!
You can create a function that negates %in%, e.g.
'%not_in%' <- Negate('%in%')
so per your code, it should look like this
airlines[row.names(airlines) %not_in% remove, ]
additionally, I do not recommend using remove as a variable name, since it is a base function in R, if possible rename the variable, e.g. discard_airlines ,
airlines[row.names(airlines) %not_in% discard_airlines, ]
I'm trying to pull data from a file, but only pull certain columns based on the column name.
I have this bit of code:
filepath <- ([my filepath])
files <- list.files(filepath, full.names=T)
newData <- fread(file,select=c(selectCols))
selectCols contains a list of column names (as strings). But in the data I'm pulling, there may be underscores placed differently in each file for the same data.
Here's an example:
PERIOD_ID
PERIOD_ID_
_PERIOD_ID_
And so on. I know I can use gsub to change the column names once the data is already pulled:
colnames(newData) <- gsub("_","",newData)
Then I can select by column name, but given that it's a lot of data I'm not sure this is the most efficient idea.
Is there a way to do ignore underscores or other characters within the fread function?
I would like to assign names to rows in R but so far I have only found ways to assign names to columns. My data is in two columns where the first column (geo) is assigned with the name of the specific location I'm investigating and the second column (skada) is the observed value at that specific location. To clarify, I want to be able to assign names for every location instead of just having them all in one .txt file so that the data is easier to work with. Anyone with more experience than me that knows how to handle this in R?
First you need to import the data to your global environment. Try the function read.table()
To name rows, try
(assuming your data.frame is named df):
rownames(df) <- df[, "geo"]
df <- df[, -1]
Well, your question is not that clear...
I assume you are trying to create a data.frame with named rows. If you look at the data.frame help you can see the parameter row.names description
NULL or a single integer or character string specifying a column to be used as row names, or a character or integer vector giving the row names for the data frame.
which means you can manually specify the row names when you create the data.frame or the column containing the names. The former can be achived as follows
d = data.frame(x=rnorm(10), # 10 random data normally distributed
y=rnorm(10), # 10 random data normally distributed
row.names=letters[1:10] # take the first 10 letters and use them as row header
)
while the latter is
d = data.frame(x=rnorm(10), # 10 random data normally distributed
y=rnorm(10), # 10 random data normally distributed
r=letters[1:10], # take the first 10 letters
row.names=3 # the column with the row headers is the 3rd
)
If you are reading the data from a file I will assume you are using the command read.table. Many of its parameters are the same of data.frame, in particular you will find that the row.headers parameter works the same way:
a vector of row names. This can be a vector giving the actual row names, or a single number giving the column of the table which contains the row names, or character string giving the name of the table column containing the row names.
Finally, if you have already read the data.frame and you want to change the row names, Pierre's answer is your solution
I am trying to remove endings from sample names in my data frame. There are about 200 samples so I was hoping there was a way to end the name before the first - (common to each sample).
Examples of names are:
Glyc.1.20C.1wk-ATGGTTCACCCG-CATCAGTACGCC-R1.fastq
Glyc.1.20C.2m-CACTACGCTAGA-GTTCCTCCATTA-R1.fastq
Glyc.1.20C.2wk-GCTCGAAGATTC-CGAGGGAAAGTC-R1.fastq
Glyc.1.20C.3m-GTAGGTGCTTAC-GCATAAACGACT-R1.fastq
Using the change colnames(x) <- c("Glyc.1.20C.1wk, etc) would take me forever.
Any ideas?
If df is your dataframe, take the names, remove everything after the first -, and reset the names to the new short values...
names(df) <- gsub("\\-.+","",names(df))