Remove all numbers in the text column but error - r

I have a material A, and I use "select()" to pick out text column,and then using "str_replace_all()" to delete all numbers.
This is the code I wrote. I expect text column will not appear any of numbers, showing only text column without other columns.
B<-select(A,text)%>%
text = str_replace_all(text,
pattern ="\d",
replacement="")
B
I'm not sure what's wrong in it...
Besides, if i want to reserve other columns,how can I cancel "select()" function and reserve text column which has revised?

Related

Scrapy - Remove comma and whitespace from getall() results

would there be an effective way to directly remove commas from the yielded results via getall()?
As an example, the data I'm trying to retrieve is in this format:
<div>
Text 1
<br>
Text 2
<br>
Text 3
</div>
My current selector for this is:
response.xpath("//div//text()").getall()
Which does get the correct data but they come out as:
Text 1,
Text 2,
Text 3
instead of
Text 1
Text 2
Text 3
I understand that they get recognized as a list which is the reason for the commas but would there be a direct function to remove them without affecting the commas from the text itself?
I'm just going to leave the solution I used in case someone needs it:
tc = response.xpath("//div//text()").getall() #xpath selector
tcl = "".join(tc) #used to convert the list into a string

Replacing strings in vector: Every instance replaced by previous found instance

I'm working with a lot of text files I have loaded into R and I'm trying to replace every instance (or tag) of </SPEAKER> with a certain string found earlier in the text file.
Example:
"<BOB> Lots of text here </SPEAKER> <HARRY> More text here by a different speaker </SPEAKER>"
I'd like to replace every instance of "</SPEAKER>" with the name of, say "<BOB>" and "<HARRY>" based on the NAME that has been found earlier, so I'd get this at the end:
"<BOB> Lots of text here </BOB> <HARRY> More text here by a different speaker </HARRY>"
I was thinking of looping through the vector text but as I only have limited experience with R, I wouldn't know how to tackle this.
If anyone has any suggestions for how to do this, possibly even outside of R using Notepad++ or another text/tag editor, I'd most appreciate any help.
Thanks!
Match
<,
word characters (capturing them in capture group 1),
>,
the shortest string (capturing it in capture group 2) until
</SPEAKER>
and then replace that with the
<,
capture group 1,
>,
capture group 2 and
</ followed by
capture group 1 and
>
This gives
x <- "<BOB> Lots of text here </SPEAKER> <HARRY> More text here by a different speaker </SPEAKER>"
gsub("<(\\w+)>(.*?)</SPEAKER>", "<\\1>\\2</\\1>", x)
## [1] "<BOB> Lots of text here </BOB> <HARRY> More text here by a different speaker </HARRY>"

Cleaning a column with break spaces that obtain last, first name so I can filter it from my data frame

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!

How to extract sections of specific text from PDF files into R data frames? Complex

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

turning text into paginated two-column format and pipe this into less

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

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