NAS

I am using an if else statement to convert the values in column X into bins in a new column Y. Code:

First time asking a question on here, so I apologise if I have missed something. I have been looking through existing answers and couldn't find any that address this issue specifically.

I'm trying to split inconsistent strings into two variables using the extract function of the tidyr package.

Reprex of my data with library calls:

I am trying to learn data-cleaning with simple code.

My central question is: what is the use of two single square brackets side by side?

Here is df as an example.

I have written a function that draws random variates from a normal distribution with outliers. However I now want to take the mean of this data and append it to an empty vector 1000 times (so essentially a vector with 1000 different means using my function) Here is my attempt so so far.

Problem

I have a large JSON file (~700.000 lines, 1.2GB filesize) containing twitter data that I need to preprocess for data and network analysis. During the data collection an error happend: Instead of using " as a seperator ' was used. As this does not conform with the JSON standard, the file can not be processed by R or Python.

Information about the dataset: Every about 500 lines start with meta info + meta information for the users, etc. then there are the tweets in json (order of fields not stable) starting with a space, one tweet per line.

This is what I tried so far:

1. A simple data.replace('\'', '\"') is not possible, as the "text" fields contain tweets which may contain ' or " themselves.
2. Using regex, I was able to catch some of the instances, but it does not catch everything: re.compile(r'"[^"]*"(*SKIP)(*FAIL)|\'')
3. Using literal.eval(data) from the ast package also throws an error.

As the order of the fields and the legth for each field is not stable I am stuck on how to reformat that file in order to conform to JSON.

Normal sample line of the data (for this options one and two would work, but note that the tweets are also in non-english languages, which use " or ' in their tweets):

I would like to run this equation based on different variable scores in multiple columns simultaneously:

#1scores/(#1scores+#2scores+#0scores)

If my DF looks like this

I have some NifTi files of brain images where there are lots of zeros that I want to replace with NAs but I'm not sure how to do it. I read in the description of the is.na() function that: "the generic function is.na<- sets elements to NA" so I thought I could use that, but it didn't work. Here is specifically what I tried:

My problem is the following:
I usually backup files (e.g. pictures) on external harddisc drives and the store them away in safe places. In the meantime also on NAS. But I don't want to have them connected and online all the time, for power and security reasons.
If I'm now looking for an old file (e.g. a special jpg from the holiday in April 2004) I would have to connect a few discs and search them for the needed file. To overcome this problem I usually create a recursive dir-dump into a textfile for the whole disc after backup.
This way I can search the filename in the text-file. But there still is a problem if I don't exactly know the file name that I am looking for. I know the Year and month and maybe the camera I was using then, but there must be hundreds of files in this month.

Therefore I would like to create a "dummy"-backup-filesystem with all the filesnames on the harddisc but without the actual data behind it. This way I could click through the folders and see the foldernames and filenames and easily find the respective file.

The question is: How do I create such a filesystem copy with the complete folderstructures but only the filenames and not the data?
I'm working on Linux, Opensuse, but I guess this is not a linux specific question.

probably a really basic question but I cannot figure it out. Assume the following test code: