I'm trying to split a huge .txt file into multiples .txt files containing just one paragraph each.
Let me provide an example. I would need a text like this:
This is the first paragraph. It makes no sense because is just an example.
This a second paragraph, as meaningless as the previous one.
Saved as two independent .txt files containing the first paragraph (the first file) and the second paragraph (the second file).
The first file would have only: "This is the first paragraph. It makes no sense because is just an example."
And the second one: "This a second paragraph, as meaningless as the previous one."
And the same for the whole text. In the huge .txt file paragraphs are divided by one or several empty lines. Ideas?
Thank you very much!
I created a 3 paragraph example and am using your comment here to recreate what I think you're describing.
text <- "This is the first paragraph. It makes no sense because is just an example. Nothing makes sense and I'm trying to understand what I'm doing with life. This paragraph does not seem to end.
What are we doing here.
This a second paragraph, as meaningless as the previous one.
There's too much to do - this is meaningless though.
Wow, that's funny."
paras <- unlist(strsplit(text, "\n\n"))
for (i in 1:length(paras)) {
write.table(paras[i], file = paste0("paragraph", i, ".txt"), row.names = F)
}
This code first assigns the value to the variable text and is followed bu the use of the strsplit function with the argument "\n\n" to split the text at each double newline character.
Then, a for loop is used to go through each element and save it into a separate .txt file.
Related
I'm stumped. My issue is that I want to grab specific names from a given column. However, when I try and filter them I get most of the names except for a few, even though I can clearly see their names in the original excel file. I think it has to do what some sort of special characters or spacing in the name column. I am confused on how I can fix this.
I have tried using excels clean() function to apply that to the given column. I have tried working an Alteryx flow to clean the data. All of these steps haven't helped any. I am starting to wonder if this is an r issue.
surveyData %>% filter(`Completed By` == "Spencer,(redbox with whitedot in middle)Amy")
surveyData %>% filter(`Completed By` == "Spencer, Amy")
in r the first line had this redbox with white dot in between the comma and the first name. I got this red box with white dot by copy the name from the data frame and copying it into notepad and then pasting it in r. This actually works and returns what I want. Now the second case is a standard space which doesn't return what I want. So how can I fix this issue by not having to copy a name from the data frame and copy to notepad then copying the results from notepad to r, which has the redbox with a white dot in between the comma(,) and first name.
Expected results is that I get the rows that are attached to what ever name I filter by.
I was able to find the answer, it turns out the space is actually a break space with unicode of (U+00A0) compared to the normal space unicode (U+0020). The break space is not apart of the American Standard Code for Information Interchange(ACSII). Thus r filter() couldn't grab some names because they had break spaces. I fixed this by subbing the Unicode of the break space with the Unicode for a normal space and applying that to my given column. Example below:
space_fix = gsub("\u00A0", " ", surveyData$`Completed By`, fixed = TRUE) #subbing break space unicode with space unicode for the given column I am interested in
surveyData$`Completed By Clean` = space_fix
Once, I applied this I could easily filter any name!
Thanks everyone!
Please any advice will be appreciated.. This is time sensitive. I have PDF reports that are mostly blocks of text. They are long reports (~50-100 pages). I'm trying to write an R script that is capable of extracting specific sections of these PDF reports using start/stop positional strings. NOTE: Reports vary in length. Short example:
DOCUMENT TITLE
01. SECTION 1
This is a test section that I DONT want to extract.
This text would normally be much longer... Over 100 words.
Sample Text Text Text Text Text Text Text Text
02. SECTION 2
This is a test section that I do want to extract.
This text would normally be much longer... Over 100 words.
Sample Text Text Text Text Text Text Text Text
...
11. SECTION 11
This is a test section that I do want to extract.
This text would normally be much longer... Over 100 words.
Sample Text Text Text Text Text Text Text Text
...
12. SECTION 12
This is a test section that I DONT want to extract.
This text would normally be much longer... Over 100 words.
Sample Text Text Text Text Text Text Text Text
...
So the goal in this example, is to extract the paragraph below Section 2 and store it as a field/data point. I also want to store Section 11 as a field/data point. Note the document is in PDF format
I have tried used pdftools, tm, stringr, I've literally spent 20+ hours searching for solutions and tutorials on how to do this. I know it is possible as I have done it using SAS before...
Please see code below, I added comments with questions. I believe RegEx will be part of the solution but i'm so lost.
# Init Step
libs <- c("tm","class","stringr","testthat",
"pdftools")
lapply(libs, require, character.only= TRUE)
# File name & location
filename = "~/pdf_test/test.pdf"
# converting PDF to text
textFile <- pdf_text(filename)
cat(textFile[1]) # Text of pg. 1 of PDF
cat(textFile[2]) # Text of pg. 2 of PDF
# I'm at a loss of how to parse the values I want. I have seen things
like:
sectionxyz <- str_extract_all(textFile, #??? )
rm_between()
# 1) How do I loop through each page of PDF file?
# 2) How do I identify start/stop positions for section to be extracted?
# 3) How do I add logic to extract text between start/stop positions
# and then add the result to a data field?
# 4) Sections in PDF will be long sections of text (i.e. 100+ words into a field)
NEW------
So I have been able to:
-Prep doc correctly
-Identify the correct start/stop patterns:
length(grep("^11\\. LIMITS OF LIABILITY( +){1}$",source_main2))
length(grep("Applicable\\s+[Ll]imits\\s+[Oo]f",source_main2))
pat_st_lol <- "^11\\. LIMITS OF LIABILITY( +){1}$"
pat_ed_lol <- "Applicable\\s+[Ll]imits\\s+[Oo]f"
The length(grep()) statements verify only 1 instance is being found. From here I am kind of lost based on how to use gsub or similar to extract the portion of data I want. I tried:
pat <- paste0(".*",pat_st_lol,"(.*)",pat_ed_lol,".*")
test <- gsub(".*^11\\. LIMITS OF LIABILITY( +){1}$(.*)\n",
"Applicable\\s+[Ll]imits\\s+[Oo]f", source_main2)
test2 <-gsub(".*pat_st_lol(.*)\npat_ed_lol.*")
So far, little progress, but progress anyways.
Provided you can come with a systematic to identify the sections you need, you could, as you indicated, use Regex to extract the text you want.
In your above example, something like gsub(".*SECTION 11(.*)\n12\\..*","\\1",string) ought to work.
Now you could define patterns dynamically using paste and iterate through all files. Each result can then be saved in your data.frame, list,....
Here is a brief more detailed explanation of the pattern:
Firstly, .* is way of matching "anything". If you want to match digits you can use \\d or equivalently [0-9]. Here is a short intro to Regex in R (which I found to be quite useful) where you can find several character classes.
.* at the edges of the pattern means that there can be text before/after
(.*) denotes the content we want (so here matching any content as .* is used). Basically it means extract "anything" between SECTION 11 and 12.
\\. means the dot and \n is the "newline" metacharacter (as before "12.", a new line is started)
In Regex you can create groupings within your pattern using the brackets, i.e. gsub(".*(\\d{2}\\:\\d{2})", "\\1","18.05.2018, 21:37") will return 21:37, or gsub("([A-z]) \\d+","\\1","hello 123") will give hello.
Now the second argument in gsub can and is often used to provide a substitute, i.e. something to replace to matched pattern with. Here however, we do not want any substitue, we want to extract something. \\1 means extract the first grouping, i.e. what it inside the first brackets (you could have multiple groupings).
Finally, string is the string from which we want to extract, i.e. the PDF file
Now if you want to perform something similar in a loop you could do the following:
# we are in the loop
# first is your starting point in the extraction, i.e. "SECTION 11"
# last is your end point, i.e. "12."
first <- "SECTION 11" # first and last can be dynamically assigned
last <- "12\\." # "\\" is added before the dot as "." is a Regex metachar
# If last doesn't systematically contain a dot
# you could use gsub to add "\\" before the dot when needed:
# gsub("\\.","\\\\.",".") returns "\\."
# so gsub("\\.","\\\\.","12.") returns "12\\."
pat <- paste0(".*",first,"(.*)","\n",last,".*") #"\n" is added to stop before the newline, but it could be omitted (then "\n" might appear in the extraction)
gsub(pat,"\\1",string) # returns the same as above
I am currently working on a data sat which has two header rows (The first one acting as overall category description and the second one containing subcategories. And it happens to be that both contain various <text> intervals. For example:
In the first row (column names of the data frame), i have a cell that contains:
- text... <span style=\"text-decoration: underline;\">in the office</span> on the activities below. Total must add up to 100%. <br /><br />
The second row contains multiple cells with:
- text <strong>
- text </strong>
Now, I was able to work out of how to remove all <text> intervals in the second row through:
data[1,] = gsub("<.*>", "", data[1,])
However, for the column names row, if I use:
colnames(data) = gsub("<.*>", "",colnames(data))
I end up just with "text", which I don't want. Due to the fact, that I still want to have:
text... in the office on the activities below. Total must add up to 100%
If some one would have an idea of how to solve it. I would really appreciate it.
Thanks!
You can get what you need by changing the regular expression you are using with the following:
colnames(data) <- gsub("<[^>]+>", "",colnames(data))
This will remove anything between opening and closing tags (including the tag). That should give you what you want.
Your current regex is greedy and is consuming everything in between the first opening bracket and last closing bracket. One quick fix would be to make your regex non greedy by using ?:
data[1,] = gsub("<.*?>", "", data[1,])
Note that using regex to parse HTML generally is not a good idea. If you plan on doing anything with nested content then you should consider using an R package which can parse HTML content.
Demo
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This is my first ever question here and I'm new to R, trying to figure out my first step in how to do data processing, please keep it easy : )
I'm wondering what would be the best function and a useful data structure in R to load unstructured text data for further processing. For example, let's say I have a book stored as a text file, with no new line characters in it.
Is it a good idea to use read.delim() and store the data in a list? Or is a character vector better, and how would I define it?
Thank you in advance.
PN
P.S. If I use "." as my delimeter, it would treat things like "Mr." as a separate sentence. While this is just an example and I'm not concerned about this flaw, just for educational purposes, I'd still be curious how you'd go around this problem.
read.delim reads in data in table format (with rows and columns, as in Excel). It is not very useful for reading a string of text.
To read text from a text file into R you can use readLines(). readLines() creates a character vector with as many elements as lines of text. A line, for this kind of software, is any string of text that ends with a newline. (Read about newline on Wikipedia.) When you write text, you enter your system specific newline character(s) by pressing Return. In effect, a line of text is not defined by the width of your software window, but can run over many visual rows. In effect, a line of text is what in a book would be a a paragraph. So readLines() splits your text at the paragraphs:
> readLines("/path/to/tom_sawyer.txt")
[1] "\"TOM!\""
[2] "No answer."
[3] "\"TOM!\""
[4] "No answer."
[5] "\"What's gone with that boy, I wonder? You TOM!\""
[6] "No answer."
[7] "The old lady pulled her spectacles down and looked over them about the room; then she put them up and looked out under them. She seldom or never looked through them for so small a thing as a boy; they were her state pair, the pride of her heart, and were built for \"style,\" not service—she could have seen through a pair of stove-lids just as well. She looked perplexed for a moment, and then said, not fiercely, but still loud enough for the furniture to hear:"
[8] "\"Well, I lay if I get hold of you I'll—\"
Note that you can scroll long text to the left here in Stackoverflow. That seventh line is longer than this column is wide.
As you can see, readLines() read that long seventh paragraph as one line. And, as you can also see, readLines() added a backslash in front of each quotation mark. Since R holds the individual lines in quotation marks, it needs to distinguish these from those that are part of the original text. Therefore, it "escapes" the original quotation marks. Read about escaping on Wikipedia.
readLines() may output a warning that an "incomplete final line" was found in your file. This only means that there was no newline after the last line. You can suppress this warning with readLines(..., warn = FALSE), but you don't have to, it is not an error, and supressing the warning will do nothing but supress the warning message.
If you don't want to just output your text to the R console but process it further, create an object that holds the output of readLines():
mytext <- readLines("textfile.txt")
Besides readLines(), you can also use scan(), readBin() and other functions to read text from files. Look at the manual by entering ?scan etc. Look at ?connections to learn about many different methods to read files into R.
I would strongly advise you to write your text in a .txt-file in a text editor like Vim, Notepad, TextWrangler etc., and not compose it in a word processor like MS Word. Word files contain more than the text you see on screen or printed, and those will be read by R. You can try and see what you get, but for good results you should either save your file as a .txt-file from Word or compose it in a text editor.
You can also copy-paste your text from a text file open in any other software to R or compose your text in the R console:
myothertext <- c("What did you do?
+ I wrote some text.
+ Ah, interesting.")
> myothertext
[1] "What did you do?\nI wrote some text.\nAh, interesting."
Note how entering Return does not cause R to execute the command before I closed the string with "). R just replies with +, telling me that I can continue to edit. I did not type in those plusses. Try it. Note also that now the newlines are part of your string of text. (I'm on a Mac, so my newline is \n.)
If you input your text manually, I would load the whole text as one string into a vector:
x <- c("The text of your book.")
You could load different chapters into different elements of this vector:
y <- c("Chapter 1", "Chapter 2")
For better reference, you can name the elements:
z <- c(ch1 = "This is the text of the first chapter. It is not long! Why was the author so lazy?", ch2 = "This is the text of the second chapter. It is even shorter.")
Now you can split the elements of any of these vectors:
sentences <- strsplit(z, "[.!?] *")
Enter ?strsplit to read the manual for this function and learn about the attributes it takes. The second attribute takes a regular expression. In this case I told strsplit to split the elements of the vector at any of the three punctuation marks followed by an optional space (if you don't define a space here, the resulting "sentences" will be preceded by a space).
sentences now contains:
> sentences
$ch1
[1] "This is the text of the first chapter" "It is not long"
[3] "Why was the author so lazy"
$ch2
[1] "This is the text of the second chapter" "It is even shorter"
You can access the individual sentences by indexing:
> sentences$ch1[2]
[3] "It is not long"
R will be unable to know that it should not split after "Mr.". You must define exceptions in your regular expression. Explaining this is beyond the scope of this question.
How you would tell R how to recognize subjects or objects, I have no idea.
I want to read a long text file in two-column format on my terminal. This means that the columns must be page-aware, so that text at the bottom of the first column continues at the top of the second column, but text at the bottom of the second column continues at the beginning of the first column after a page-down.
I tried column and less to get this result, but with no luck. If I pipe the text into column, it produces two columns but truncates the text before it reaches the end of the file. And if I pipe the output of column into less, it also reverts back to single-column.
a2ps does what I want in the way of reformatting, but I would rather have the output in pure plain text, readable from the terminal, rather than a PostScript file that I would need to read in a PDF reader.
You can use pr for this, eg.
ls /usr/src/linux/drivers/char/ | pr -2 |less