My x axis labels look like [100000,250000] which makes it hard to understand the numer at first sight, I want it to look like [100.000,250.000], I know that the cut2 function has a formatfun parameter but I think I don´t know how to use it properly.
Try using the "formatC" function on your cut data. e.g.
formatC(my_cuts, big.mark = ".", decimal.mark = ",")
Let's create an example to work on:
x <- cut(seq(0,1,length.out=8) + 1e6, 3)
This is a factor. Although at bottom it's a numeric array, you don't want to format its values; you want to format its levels, which are the strings associated with its values. This is what the levels look like in the example (calling head to prevent lots of printing in case x has many distinct levels):
(head(levels(x)))
[1] "(1000000,1000000.3]" "(1000000.3,1000000.7]" "(1000000.7,1000001]"
To format the levels, we need to pick them apart into their numeric components (which are separated by a comma ","), format each component, and reassemble the results.
Here's the picking-apart-and-formatting step in one go, using only base R functionality. It calls gsub and strsplit on the first line (for cleaning out the "(" and "]" characters and splitting each pair of numeric strings into two strings) and employs prettyNum on the second line (for the formatting), which conveniently will format any character string that looks like a number:
s <- lapply(strsplit(gsub("]|[(]", "", levels(x)), ","),
prettyNum, big.mark=".", decimal.mark=",", input.d.mark=".", preserve.width="individual")
(You might not need the input.d.mark argument, but I did because my locale uses "." for a decimal point, as you could see above. The docs say "individual" is the default for setting the output width, but that just isn't the case on my system: I had to specify it explicitly.)
The paste* functions will perform the reassembly, whose results we simply re-assign to the levels of x:
levels(x) <- paste0("(", sapply(s, function(a) paste0(a, collapse="; ")), "]")
(Since each number potentially already includes "," and "." delimiters, I have specified a third punctuation mark, ";", to separate the numbers themselves -- but you may use what you wish, of course.)
Let's display the new levels to verify the results:
(head(levels(x)))
[1] "(1.000.000; 1.000.000,3]" "(1.000.000,3; 1.000.000,7]" "(1.000.000,7; 1.000.001]"
Related
I just learnt R and was trying to clean data for analysis using R using string manipulation using the code given below for Amount_USD column of a table. I could not find why changes were not made. Please help.
Code:
csv_file2$Amount_USD <- ifelse(str_sub(csv_file$Amount_USD,1,10) == "\\\xc2\\\xa0",
str_sub(csv_file$Amount_USD,12,-1),csv_file2$Amount_USD)
Result:
\\xc2\\xa010,000,000
\\xc2\\xa016,200,000
\\xc2\\xa019,350,000
Expected Result:
10,000,000
16,200,000
19,350,000
You could use the following code, but maybe there is a more compact way:
vec <- c("\\xc2\\xa010,000,000", "\\xc2\\xa016,200,000", "\\xc2\\xa019,350,000")
gsub("(\\\\x[[:alpha:]]\\d\\\\x[[:alpha:]]0)([d,]*)", "\\2", vec)
[1] "10,000,000" "16,200,000" "19,350,000"
A compact way to extract the numbers is by using str_extract and negative lookahead:
library(stringr)
str_extract(vec, "(?!0)[\\d,]+$")
[1] "10,000,000" "16,200,000" "19,350,000"
How this works:
(?!0): this is negative lookahead to make sure that the next character is not 0
[\\d,]+$: a character class allowing only digits and commas to occur one or more times right up to the string end $
Alternatively:
str_sub(vec, start = 9)
There were a few minor issues with your code.
The main one being two unneeded backslashes in your matching statement. This also leads to a counting error in your first str_sub(), where you should be getting the first 8 characters not 10. Finally, you should be getting the substring from the next character after the text you want to match (i.e. position 9, not 12). The following should work:
csv_file2$Amount_USD <- ifelse(str_sub(csv_file$Amount_USD,1,8) == "\\xc2\\xa0", str_sub(csv_file$Amount_USD,9,-1),csv_file2$Amount_USD)
However, I would have done this with a more compact gsub than provided above. As long as the text at the start to remove is always going to be "\\xc2\\xa0", you can simply replace it with nothing. Note that for gsub you will need to escape all the backslashes, and hence you end up with:
csv_file2$Amount_USD <- gsub("\\\\xc2\\\\xa0", replacement = "", csv_file2$Amount_USD)
Personally, especially if you plan to do any sort of mathematics with this column, I would go the additional step and remove the commas, and then coerce the column to be numeric:
csv_file2$Amount_USD <- as.numeric(gsub("(\\\\xc2\\\\xa0)|,", replacement = "", csv_file2$Amount_USD))
I would like to convert this:
AIR-GEN-SUM-UD-ELA-NH-COMBINED-3-SEG1
to this:
ELA-3
I tried this function:
str_extract(.,pattern = ":?(ELA).*(\\d\\-)"))
it printed this:
"ELA-NH-COMBINED-3-"
I need to get rid of the text or anything between the two extracts. The number will be a number between 3 and 9. How should I modify my expression in pattern =?
Thanks!
1) Match everything up to -ELA followed by anything (.*) up to - followed by captured digits (\\d+)followed by - followed by anything. Then replace that with ELA- followed by the captured digits. No packages are used.
x <- "AIR-GEN-SUM-UD-ELA-NH-COMBINED-3-SEG1"
sub(".*-ELA.*-(\\d+)-.*", "ELA-\\1", x)
## [1] "ELA-3"
2) Another approach if there is only one numeric field is that we can read in the fields, grep out the numeric one and preface it with ELA- . No packages are used.
s <- scan(text = x, what = "", quiet = TRUE, sep = "-")
paste("ELA", grep("^\\d+$", s, value = TRUE), sep = "-")
## [1] "ELA-3"
TL;DR;
You can't do that with a single call to str_extract because you cannot match discontinuous portions of texts within a single match operation.
Again, it is impossible to match texts that are separated with other text into one group.
Work-arounds/Solutions
There are two solutions:
Capture parts of text you need and then join them (2 operations: match + join)
Capture parts of text you need and then replace with backreferences to the groups needed (1 replace operation)
Capturing groups only keep parts of text you match in separate memory buffers, but you also need a method or function that is capable of accessing these chunks.
Here, in R, str_extract drops them, but str_match keeps them in the result.
s <- "AIR-GEN-SUM-UD-ELA-NH-COMBINED-3-SEG1"
m <- str_match(s, ":?(ELA).*-(\\d+)")
paste0(m[,2], "-", m[,3])
This prints ELA-3. See R demo online.
Another way is to replace while capturing the parts you need to keep and then using backreferences to those parts in the replacement pattern:
x <- "AIR-GEN-SUM-UD-ELA-NH-COMBINED-3-SEG1"
sub("^.*-ELA.*?-([^-]+)-[^-]+$", "ELA-\\1", x)
See this R demo
I imported a vector of p-values from an Excel table. The numbers are given as superscripted Unicode strings. After hours of trying I still struggle to convert them into numbers.
See example below. Simple conversion with as.numeric() doesn't work. I also tried to use Regex to capture the superscripted numbers, but it turned out that each superscripted number has a distinct Unicode code, for which there is no translation.
test <- c("0.0126", "0.000289", "4.26x10⁻¹⁴", "6.36x10⁻⁴⁸",
"4.35x10⁻⁹", "0.115", "0.0982", "0.000187", "0.0484", "0.000223")
as.numeric(test)
Does somebody know of an R-package which could do the translation painlessly, or do I have to translate the codes one by one into digits?
This kind of formatting is definitely not very portable... Here's one possible solution though, for the exercise...
test <- c("0.0126", "0.000289", "4.26x10⁻¹⁴", "6.36x10⁻⁴⁸",
"4.35x10⁻⁹", "0.115", "0.0982", "0.000187", "0.0484",
"0.000223")
library(utf8)
library(stringr)
# normalize, ie everything to "normal text"
testnorm <- utf8_normalize(test, map_case = TRUE, map_compat = TRUE)
# replace exponent part
# \\N{Minus Sign} is the unicode name of the minus sign symbol
# (see [ICU regex](http://userguide.icu-project.org/strings/regexp))
# it is necessary because the "-" is not a plain text minus sign...
testnorm <- str_replace_all(testnorm, "x10\\N{Minus Sign}", "e-")
# evaluate these character strings
p_vals <- sapply(X = testnorm,
FUN = function(x) eval(parse(text = x)),
USE.NAMES = FALSE
)
# everything got adjusted to the "e-48" element...
format(p_vals, digits = 2, scientific = F)
I am interested to assign names to list elements. To do so I execute the following code:
file_names <- gsub("\\..*", "", doc_csv_names)
print(file_names)
"201409" "201412" "201504" "201507" "201510" "201511" "201604" "201707"
names(docs_data) <- file_names
In this case the name of the list element appears with ``.
docs_data$`201409`
However, in this case the name of the list element appears in the following way:
names(docs_data) <- paste("name", 1:8, sep = "")
docs_data$name1
How can I convert the gsub() result to receive the latter naming pattern without quotes?
gsub() and paste () seem to produce the same class () object. What is the difference?
Both gsub and paste return character objects. They are different because they are completely different functions, which you seem to know based on their usage (gsub replaces instances of your pattern with a desired output in a string of characters, while paste just... pastes).
As for why you get the quotations, that has nothing to do with gsub and everything to do with the fact that you are naming variables/columns with numbers. Indeed, try
names(docs_data) <- paste(1:8)
and you'll realize you have the same problem when invoking the naming pattern. It basically has to do with the fact that R doesn't want to be confused about whether a number is really a number or a variable because that would be chaos (how can 1 refer to a variable and also the number 1?), so what it does in such cases is change a number 1 into the character "1", which can be given names. For example, note that
> 1 <- 3
Error in 1 <- 3 : invalid (do_set) left-hand side to assignment
> "1" <- 3 #no problem!
So R is basically correcting that for you! This is not a problem when you name something using characters. Finally, an easy fix: just add a character in front of the numbers of your naming pattern, and you'll be able to invoke them without the quotations. For example:
file_names <- paste("file_",gsub("\\..*", "", doc_csv_names),sep="")
Should do the trick (or just change the "file_" into whatever you want as long as it's not empty, cause then you just have numbers left and the same problem)!
I have a file with internationally formatted numbers (i.e strings) including units of measurement. In this case the decimal place is indicated by "," and the 1e3 seperator is indicated as "." (i.e. German number formats).
a <- c('2.200.222 €',
' 180.109,3 €')
or
b <- c('28,42 m²',
'47,70 m²')
I'd like to convert these strings efficiently to numeric. I've tried to filter out numbers by codes like
require(stringr)
str_extract(a, pattern='[0-9]+.[0-9]+.[0-9]+')
str_extract(b, pattern='[0-9]+,[0-9]+')
however, this does seem to be too prone to errors and I guess there must be a more standardized way. So here's my question: Is there a custom function, package or something else that is capable of such a problem?
Thank you very much!
Here is a function that uses gsub to deal with the sample data you posted:
x <- c('2.200.222 €', ' 180.109,3 €', '28,42 m²', '47,70 m²')
strip <- function(x){
z <- gsub("[^0-9,.]", "", x)
z <- gsub("\\.", "", z)
gsub(",", ".", z)
}
as.numeric(strip(x))
[1] 2200222.00 180109.30 28.42 47.70
It works like this:
First strip out all trailing non-digits (and anything after these non-digits)
Then strip out all periods.
Finally, convert commas to periods.