I am working with the following data set: https://www.kaggle.com/crowdflower/twitter-user-gender-classification
My goal is developing a R script to detect gender through emojis but they are in a weird code that I can´t convert in UNICODE that allows linking in one of the emoji dictionaries. I tried iconv but it converted to hilo format and I don´t know how to convert it to unicode.
I write an example with one of the data set tweets.
new <- iconv("Its a double capsule day _Ù÷ã_Ù÷ã 27 varieties of fruit and veg...in a capsule, simples _Ù÷ã_Ù÷ã #fruitandveg #juiceplus #health", from="utf-8", to="UNICODE", "byte")
[1] "Its a double capsule day _<d9><f7><e3>_<d9><f7><e3> 27 varieties of fruit and veg...in a capsule, simples _<d9><f7><e3>_<d9><f7><e3> #fruitandveg #juiceplus #health"
Any help?
Thanks in advance
Related
I have a data frame which has one column of text with info that I need to extract, here is one observation from that column: each question has three attributes associated to it objectives,KeyResults and responsible
[{"text":"Newideas.","translationKey":"new.question-4","id":4,"objectives":"Great","KeyResults":"Awesome","responsible":"myself"},{"text":"customer focus.","translationKey":"new.question-5","id":5,"objectives":"Goalset","KeyResults":"Amazing","responsible":"myself"}
-------------------------DESIRED OUTPUT -----------------------
Question# Objectives KeyResults responsible Question# Objectives KeyResults responsible
4 Great Awesome myself 5 Goalset Amazin myself
Data is a valid json (but you need square bracket closing ] on it). You can read json into R object using json parser package (eg. jsonlite)
Let say your text is in column text of data frame df, then this will transform that text into R dataframe.
library(jsonlite)
dat <- fromJSON(df$text)
dat
# text translationKey id objectives KeyResults responsible
# 1 Newideas. new.question-4 4 Great Awesome myself
# 2 customer focus. new.question-5 5 Goalset Amazing myself
You need to install jsonlite to make it works
install.packages("jsonlite")
I have tried using the ocr tesseract package in R to extract text from a png image (below)
The text is mostly in Spanish. Here is my code:
library(tesseract)
#tesseract_download("spa") #download the Spanish train data if you haven't already
spanish <- tesseract("spa")
path_string <- "factura.png"
text <- ocr(path_string, engine = spanish)
cat(text)
But the result is disappointing.
ném…c……
…r …
nw£ccwm … m…… u
mmm …"
pz… u—=,:4| nm;
mmmnzvgm 3134
NUM“ vmnscwm
cuaw ……er
nmcmvcn4 c…r vum
£m|unmusnm . u7m
¡…una
suma… ……
ncm u|s
m:s .
mm u7m
cmmo 1240
nmrAm au…va m m
m.
515 mu .…
…
=mmnzmo
a… rn¿a> rc.¿… ……
u7m
Rm mmm… swmks
…… mmm
m…—
Guuumwsucmm
Is this poor result due to low dpi? Would it be possible to improve this by tinkering with the pre-processing?
For each of these receipts, what I really need is just to pull out the line item with the word "equilibrio" and the value to the right of that (41,760 in this case). Can tesseract be told to focus only on certain words and to also pull out numbers?
My dataframe column looks like this:
head(tweets_date$Tweet)
[1] b"It is #DineshKarthik's birthday and here's a rare image of the captain of #KKRiders. Have you seen him do this before? Happy birthday, DK\\xf0\\x9f\\x98\\xac
[2] b'The awesome #IPL officials do a wide range of duties to ensure smooth execution of work! Here\\xe2\\x80\\x99s #prabhakaran285 engaging with the #ChennaiIPL kid-squad that wanted to meet their daddies while the presentation was on :) #cutenessoverload #lineofduty \\xf0\\x9f\\x98\\x81
[3] b'\\xf0\\x9f\\x8e\\x89\\xf0\\x9f\\x8e\\x89\\n\\nCHAMPIONS!!
[4] b'CHAMPIONS - 2018 #IPLFinal
[5] b'Chennai are Super Kings. A fairytale comeback as #ChennaiIPL beat #SRH by 8 wickets to seal their third #VIVOIPL Trophy \\xf0\\x9f\\x8f\\x86\\xf0\\x9f\\x8f\\x86\\xf0\\x9f\\x8f\\x86. This is their moment to cherish, a moment to savour.
[6] b"Final. It's all over! Chennai Super Kings won by 8 wickets
These are tweets which have mentions starting with '#', I need to extract all of them and save each mention in that particular tweet as "#mention1 #mention2". Currently my code just extracts them as lists.
My code:
tweets_date$Mentions<-str_extract_all(tweets_date$Tweet, "#\\w+")
How do I collapse those lists in each row to a form a string separated by spaces as mentioned earlier.
Thanks in advance.
I trust it would be best if you used an asis column in this case:
extract words:
library(stringr)
Mentions <- str_extract_all(lis, "#\\w+")
some data frame:
df <- data.frame(col = 1:6, lett = LETTERS[1:6])
create a list column:
df$Mentions <- I(Mentions)
df
#output
col lett Mentions
1 1 A #DineshK....
2 2 B #IPL, #p....
3 3 C
4 4 D
5 5 E #ChennaiIPL
6 6 F
I think this is better since it allows for quite easy sub setting:
df$Mentions[[1]]
#output
[1] "#DineshKarthik" "#KKRiders"
df$Mentions[[1]][1]
#output
[1] "#DineshKarthik"
and it succinctly shows whats inside the column when printing the df.
data:
lis <- c("b'It is #DineshKarthik's birthday and here's a rare image of the captain of #KKRiders. Have you seen him do this before? Happy birthday, DK\\xf0\\x9f\\x98\\xac",
"b'The awesome #IPL officials do a wide range of duties to ensure smooth execution of work! Here\\xe2\\x80\\x99s #prabhakaran285 engaging with the #ChennaiIPL kid-squad that wanted to meet their daddies while the presentation was on :) #cutenessoverload #lineofduty \\xf0\\x9f\\x98\\x81",
"b'\\xf0\\x9f\\x8e\\x89\\xf0\\x9f\\x8e\\x89\\n\\nCHAMPIONS!!",
"b'CHAMPIONS - 2018 #IPLFinal",
"b'Chennai are Super Kings. A fairytale comeback as #ChennaiIPL beat #SRH by 8 wickets to seal their third #VIVOIPL Trophy \\xf0\\x9f\\x8f\\x86\\xf0\\x9f\\x8f\\x86\\xf0\\x9f\\x8f\\x86. This is their moment to cherish, a moment to savour.",
"b'Final. It's all over! Chennai Super Kings won by 8 wickets")
The str_extract_all function from the stringr package returns a list of character vectors. So, if you instead want a list of single CSV terms, then you may try using sapply for a base R option:
tweets <- str_extract_all(tweets_date$Tweet, "#\\w+")
tweets_date$Mentions <- sapply(tweets, function(x) paste(x, collapse=", "))
Demo
Via Twitter's help site: "Your username cannot be longer than 15 characters. Your real name can be longer (20 characters), but usernames are kept shorter for the sake of ease. A username can only contain alphanumeric characters (letters A-Z, numbers 0-9) with the exception of underscores, as noted above. Check to make sure your desired username doesn't contain any symbols, dashes, or spaces."
Note that email addresses can be in tweets as can URLs with #'s in them (and not just the silly URLs with username/password in the host component). Thus, something like:
(^|[^[[:alnum:]_]#/\\!?=&])#([[:alnum:]_]{1,15})\\b
is likely a better, safer choice
I apologize in advance for the somewhat lack of reproducibility here. I am doing an analysis on a very large (for me) dataset. It is from the CMS Open Payments database.
There are four files I downloaded from that website, read into R using readr, then manipulated a bit to make them smaller (column removal), and then stuck them all together using rbind. I would like to write my pared down file out to an external hard drive so I don't have to read in all the data each time I want to work on it and doing the paring then. (Obviously, its all scripted but, it takes about 45 minutes to do this so I'd like to avoid it if possible.)
So I wrote out the data and read it in, but now I am getting different results. Below is about as close as I can get to a good example. The data is named sa_all. There is a column in the table for the source. It can only take on two values: gen or res. It is a column that is actually added as part of the analysis, not one that comes in the data.
table(sa_all$src)
gen res
14837291 822559
So I save the sa_all dataframe into a CSV file.
write.csv(sa_all, 'D:\\Open_Payments\\data\\written_files\\sa_all.csv',
row.names = FALSE)
Then I open it:
sa_all2 <- read_csv('D:\\Open_Payments\\data\\written_files\\sa_all.csv')
table(sa_all2$src)
g gen res
1 14837289 822559
I did receive the following parsing warnings.
Warning: 4 parsing failures.
row col expected actual
5454739 pmt_nature embedded null
7849361 src delimiter or quote 2
7849361 src embedded null
7849361 NA 28 columns 54 columns
Since I manually add the src column and it can only take on two values, I don't see how this could cause any parsing errors.
Has anyone had any similar problems using readr? Thank you.
Just to follow up on the comment:
write_csv(sa_all, 'D:\\Open_Payments\\data\\written_files\\sa_all.csv')
sa_all2a <- read_csv('D:\\Open_Payments\\data\\written_files\\sa_all.csv')
Warning: 83 parsing failures.
row col expected actual
1535657 drug2 embedded null
1535657 NA 28 columns 25 columns
1535748 drug1 embedded null
1535748 year an integer No
1535748 NA 28 columns 27 columns
Even more parsing errors and it looks like some columns are getting shuffled entirely:
table(sa_all2a$src)
100000000278 Allergan Inc. gen GlaxoSmithKline, LLC.
1 1 14837267 1
No res
1 822559
There are columns for manufacturer names and it looks like those are leaking into the src column when I use the write_csv function.
I am new to R and my question should be trivial. I need to create a word cloud from a txt file containing the words and their occurrence number. For that purposes I am using the snippets package.
As it can be seen at the bottom of the link, first I have to create a vector (is that right that words is a vector?) like bellow.
> words <- c(apple=10, pie=14, orange=5, fruit=4)
My problem is to do the same thing but create the vector from a file which would contain words and their occurrence number. I would be very happy if you could give me some hints.
Moreover, to understand the format of the file to be inserted I write the vector words to a file.
> write(words, file="words.txt")
However, the file words.txt contains only the values but not the names(apple, pie etc.).
$ cat words.txt
10 14 5 4
Thanks.
words is a named vector, the distinction is important in the context of the cloud() function if I read the help correctly.
Write the data out correctly to a file:
write.table(words, file = "words.txt")
Create your word occurrence file like the txt file created. When you read it back in to R, you need to do a little manipulation:
> newWords <- read.table("words.txt", header = TRUE)
> newWords
x
apple 10
pie 14
orange 5
fruit 4
> words <- newWords[,1]
> names(words) <- rownames(newWords)
> words
apple pie orange fruit
10 14 5 4
What we are doing here is reading the file into newWords, the subsetting it to take the one and only column (variable), which we store in words. The last step is to take the row names from the file read in and apply them as the "names" on the words vector. We do the last step using the names() function.
Yes, 'vector' is the proper term.
EDIT:
A better method than write.table would be to use save() and load():
save(words. file="svwrd.rda")
load(file="svwrd.rda")
The save/load combo preserved all the structure rather than doing coercion. The write.table followed by names()<- is kind of a hassle as you can see in both Gavin's answer here and my answer on rhelp.
Initial answer:
Suggest you use as.data.frame to coerce to a dataframe an then write.table() to write to a file.
write.table(as.data.frame(words), file="savew.txt")
saved <- read.table(file="savew.txt")
saved
words
apple 10
pie 14
orange 5
fruit 4