Matching multiple search criteria (Unlisting a nested dataset, take 2)
I do not have your command of base r, Bert. That is a herculean effort! Here?s what I spent my night putting together:
## Create search terms
## dput(st)
st <- structure(list(word1 = c("technique", "me", "me", "feel", "feel"
), word2 = c("olympic", "abused", "hurt", "hopeless", "alone"
), word3 = c("lifts", "depressed", "depressed", "depressed",
"depressed")), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-5L))
## Create tweets
## dput(th)
th <- structure(list(status_id = c("x1047841705729306624", "x1046966595610927105",
"x1047094786610552832", "x1046988542818308097", "x1046934493553221632",
"x1047227442899775488", "x1048126008941981696", "x1047798782673543173",
"x1048269727582355457", "x1048092408544677890"), created_at = c("2018-10-04T13:31:45Z",
"2018-10-02T03:34:22Z", "2018-10-02T12:03:45Z", "2018-10-02T05:01:35Z",
"2018-10-02T01:26:49Z", "2018-10-02T20:50:53Z", "2018-10-05T08:21:28Z",
"2018-10-04T10:41:11Z", "2018-10-05T17:52:33Z", "2018-10-05T06:07:57Z"
), text = c("technique is everything with olympic lifts ! @ body by john ",
"@subtronics just went back and rewatched ur fblice with ur cdjs and let me tell you man. you are the fucking messiah",
"@ic4rus1 opportunistic means short-game. as in getting drunk now vs. not being hung over tomorrow vs. not fucking up your life ten years later.",
"i tend to think about my dreams before i sleep.", "@michaelavenatti @senatorcollins so if your client was in her 20s attending parties with teenagers doesnt that make her at the least immature as hell or at the worst a pedophile and a person contributing to the delinquency of minors?",
"i wish i could take credit for this", "i woulda never imagined. #lakeshow ",
"@philipbloom @blackmagic_news its ok phil! i feel your pain! ",
"sunday ill have a booth in katy at the real craft wives of katy fest @nolabelbrewco cmon yall!everything is better when you top it with tias!order today we ship to all 50 ",
"dolly is so baddd"), lat = c(43.6835853, 40.284123, 37.7706565,
40.431389, 31.1688935, 33.9376735, 34.0207895, 44.900818, 29.7926,
32.364145), lng = c(-70.3284118, -83.078589, -122.4359785, -79.9806895,
-100.0768885, -118.130426, -118.4119065, -89.5694915, -95.8224,
-86.2447285), county_name = c("Cumberland County", "Delaware County",
"San Francisco County", "Allegheny County", "Concho County",
"Los Angeles County", "Los Angeles County", "Marathon County",
"Harris County", "Montgomery County"), fips = c(23005L, 39041L,
6075L, 42003L, 48095L, 6037L, 6037L, 55073L, 48201L, 1101L),
state_name = c("Maine", "Ohio", "California", "Pennsylvania",
"Texas", "California", "California", "Wisconsin", "Texas",
"Alabama"), state_abb = c("ME", "OH", "CA", "PA", "TX", "CA",
"CA", "WI", "TX", "AL"), urban_level = c("Medium Metro",
"Large Fringe Metro", "Large Central Metro", "Large Central Metro",
"NonCore (Nonmetro)", "Large Central Metro", "Large Central Metro",
"Small Metro", "Large Central Metro", "Medium Metro"), urban_code = c(3L,
2L, 1L, 1L, 6L, 1L, 1L, 4L, 1L, 3L), population = c(277308L,
184029L, 830781L, 1160433L, 4160L, 9509611L, 9509611L, 127612L,
4233913L, 211037L), linenumber = 1:10), row.names = c(NA,
10L), class = "data.frame")
## Clean tweets - basically just remove everything we don?t need from the text including punctuation and urls
th %>%
mutate(linenumber = row_number(),
text = str_remove_all(text, "[^\x01-\x7F]"),
text = str_remove_all(text, "\n"),
text = str_remove_all(text, ","),
text = str_remove_all(text, "'"),
text = str_remove_all(text, "&"),
text = str_remove_all(text, "<"),
text = str_remove_all(text, ">"),
text = str_remove_all(text, "http[s]?://[[:alnum:].\\/]+"),
text = tolower(text)) -> th
## Create search function that looks for each search term in the provided string, evaluates if all three search terms have been found, and returns a logical
srchr <- function(df) {
str_detect(df, "olympic") -> a
str_detect(df, "technique") -> b
str_detect(df, "lifts") -> c
ifelse(a == TRUE & b == TRUE & c == TRUE, TRUE, FALSE)
}
## Evaluate tweets for presence of search term
th %>%
mutate(flag = map_chr(text, srchr)) -> th_flagged
As far as I can tell, this works. I have to manually enter each set of search terms into the function, which is not ideal. Also, this only generates a True/False for each tweet based on one search term - I end up with an evaluatory column for each search term that I would then have to collapse together somehow. I?m sure there?s a more elegant solution.
--
Nate Parsons
Pronouns: He, Him, His
Graduate Teaching Assistant
Department of Sociology
Portland State University
Portland, Oregon
503-725-9025
503-725-3957 FAX
On Oct 16, 2018, 7:20 PM -0700, Bert Gunter <bgunter.4567 at gmail.com>, wrote:
OK, as no one else has offered a solution, I'll take a whack at it. Caveats: This is a brute force attempt using R's basic regular expression engine. It is inelegant and barely tested, so likely to be at best incomplete and buggy, and at worst, incorrect. But maybe Nathan or someone else on the list can fix it up. So if (when) it breaks, complain on the list to give someone (almost certainly not me) the opportunity. The basic idea is that the tweets are just character strings and the search phrases are just character vectors all of whose elements must match "appropriately" -- i.e. they must match whole words -- in the character strings. So my desired output from the code is a list indexed by the search phrases, each of whose components if a logical vector of length the number of tweets each of whose elements = TRUE iff all the words in the search phrase match somewhere in the tweet. Here's the code(using the data Nathan provided):
words <- sapply(st[[1]],strsplit,split = " +" )
## convert the phrases to a list of character vectors of the words ## Result:
words
$`me abused depressed` [1] "me"??????? "abused"??? "depressed" $`me hurt depressed` [1] "me"??????? "hurt"????? "depressed" $`feel hopeless depressed` [1] "feel"????? "hopeless"? "depressed" $`feel alone depressed` [1] "feel"????? "alone"???? "depressed" $`i feel helpless` [1] "i"??????? "feel"???? "helpless" $`i feel worthless` [1] "i"???????? "feel"????? "worthless"
expand.words <-? function(z)lapply(z,function(x)paste0(c("^ *"," "," "),x, c(" "," "," *$")))
## function to create regexes for words when they are at the beginning, middle, or end of tweets
wordregex <- lapply(words,expand.words)
##Result ## too lengthy to include ##
tweets <- th$text
##extract the tweets
findin <- function(x,y)
?? ## x is a vector of regex patterns
?? ## y is a character vector
?? ## value = vector,vec, with length(vec) == length(y) and vec[i] == TRUE iff any of x matches y[i]
{ apply(sapply(x,function(z)grepl(z,y)), 1,any)
}
## add a matching "tweet" to the tweet vector:
tweets <- c(tweets," i xxxx worthless yxxc ght feel")
ans <- lapply(wordregex,function(z)apply(sapply(z,function(x)findin(x,tweets)), 1, all))
## Result:
ans
$`me abused depressed` [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE $`me hurt depressed` [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE $`feel hopeless depressed` [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE $`feel alone depressed` [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE $`i feel helpless` [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE $`i feel worthless` [1] FALSE FALSE FALSE FALSE FALSE FALSE? TRUE ## None of the tweets match any of the phrases except for the last tweet that I added. ## Note: you need to add capabilities to handle upper and lower case. See, e.g. ?casefold Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Tue, Oct 16, 2018 at 3:03 PM Bert Gunter <bgunter.4567 at gmail.com> wrote:
The problem wasn't the data tibbles. You posted in html -- which you were explictly warned against -- and that corrupted your text (e.g. some quotes became "smart quotes", which cannot be properly cut and pasted into R). Bert
On Tue, Oct 16, 2018 at 2:47 PM Nathan Parsons <nathan.f.parsons at gmail.com> wrote:
Argh! Here are those two example datasets as data frames (not tibbles).
Sorry again. This apparently is just not my day.
th <- structure(list(status_id = c("x1047841705729306624",
"x1046966595610927105",
"x1047094786610552832", "x1046988542818308097", "x1046934493553221632",
"x1047227442899775488"), created_at = c("2018-10-04T13:31:45Z",
"2018-10-02T03:34:22Z", "2018-10-02T12:03:45Z", "2018-10-02T05:01:35Z",
"2018-10-02T01:26:49Z", "2018-10-02T20:50:53Z"), text = c("Technique is
everything with olympic lifts ! @ Body By John https://t.co/UsfR6DafZt",
"@Subtronics just went back and rewatched ur FBlice with ur CDJs and let me
tell you man. You are the fucking messiah",
"@ic4rus1 Opportunistic means short-game. As in getting drunk now vs. not
being hung over tomorrow vs. not fucking up your life ten years later.",
"I tend to think about my dreams before I sleep.", "@MichaelAvenatti
@SenatorCollins So,? if your client was in her 20s, attending parties with
teenagers, doesn't that make her at the least immature as hell, or at the
worst, a pedophile and a person contributing to the delinquency of minors?",
"i wish i could take credit for this"), lat = c(43.6835853, 40.284123,
37.7706565, 40.431389, 31.1688935, 33.9376735), lng = c(-70.3284118,
-83.078589, -122.4359785, -79.9806895, -100.0768885, -118.130426
), county_name = c("Cumberland County", "Delaware County", "San Francisco
County",
"Allegheny County", "Concho County", "Los Angeles County"), fips = c(23005L,
39041L, 6075L, 42003L, 48095L, 6037L), state_name = c("Maine",
"Ohio", "California", "Pennsylvania", "Texas", "California"),
? ? state_abb = c("ME", "OH", "CA", "PA", "TX", "CA"), urban_level =
c("Medium Metro",
? ? "Large Fringe Metro", "Large Central Metro", "Large Central Metro",
? ? "NonCore (Nonmetro)", "Large Central Metro"), urban_code = c(3L,
? ? 2L, 1L, 1L, 6L, 1L), population = c(277308L, 184029L, 830781L,
? ? 1160433L, 4160L, 9509611L)), class = "data.frame", row.names = c(NA,
-6L))
st <- structure(list(terms = c("me abused depressed", "me hurt depressed",
"feel hopeless depressed", "feel alone depressed", "i feel helpless",
"i feel worthless")), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame"))
On Tue, Oct 16, 2018 at 2:39 PM Nathan Parsons <nathan.f.parsons at gmail.com>
wrote:
Thanks all for your patience. Here?s a second go that is perhaps more
explicative of what it is I am trying to accomplish (and hopefully in plain
text form)...
I?m using the following packages: tidyverse, purrr, tidytext
I have a number of tweets in the following form:
th <- structure(list(status_id = c("x1047841705729306624",
"x1046966595610927105",
"x1047094786610552832", "x1046988542818308097", "x1046934493553221632",
"x1047227442899775488"), created_at = c("2018-10-04T13:31:45Z",
"2018-10-02T03:34:22Z", "2018-10-02T12:03:45Z", "2018-10-02T05:01:35Z",
"2018-10-02T01:26:49Z", "2018-10-02T20:50:53Z"), text = c("Technique is
everything with olympic lifts ! @ Body By John https://t.co/UsfR6DafZt",
"@Subtronics just went back and rewatched ur FBlice with ur CDJs and let
me tell you man. You are the fucking messiah",
"@ic4rus1 Opportunistic means short-game. As in getting drunk now vs. not
being hung over tomorrow vs. not fucking up your life ten years later.",
"I tend to think about my dreams before I sleep.", "@MichaelAvenatti
@SenatorCollins So, if your client was in her 20s, attending parties with
teenagers, doesn't that make her at the least immature as hell, or at the
worst, a pedophile and a person contributing to the delinquency of minors?",
"i wish i could take credit for this"), lat = c(43.6835853, 40.284123,
37.7706565, 40.431389, 31.1688935, 33.9376735), lng = c(-70.3284118,
-83.078589, -122.4359785, -79.9806895, -100.0768885, -118.130426
), county_name = c("Cumberland County", "Delaware County", "San Francisco
County",
"Allegheny County", "Concho County", "Los Angeles County"), fips =
c(23005L,
39041L, 6075L, 42003L, 48095L, 6037L), state_name = c("Maine",
"Ohio", "California", "Pennsylvania", "Texas", "California"),
state_abb = c("ME", "OH", "CA", "PA", "TX", "CA"), urban_level = c("Medium
Metro",
"Large Fringe Metro", "Large Central Metro", "Large Central Metro",
"NonCore (Nonmetro)", "Large Central Metro"), urban_code = c(3L,
2L, 1L, 1L, 6L, 1L), population = c(277308L, 184029L, 830781L,
1160433L, 4160L, 9509611L)), class = c("data.table", "data.frame"
), row.names = c(NA, -6L), .internal.selfref = )
I also have a number of search terms in the following form:
st <- structure(list(terms = c("me abused depressed", "me hurt depressed",
"feel hopeless depressed", "feel alone depressed", "i feel helpless",
"i feel worthless")), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame?))
I am trying to isolate the tweets that contain all of the words in each of
the search terms, i.e ?me? ?abused? and ?depressed? from the first example
search term, but they do not have to be in order or even next to one
another.
I am familiar with the dplyr suite of tools and have been attempting to
generate some sort of ?filter()? to do this. I am not very familiar with
purrr, but there may be a solution using the map function? I have also
explored the tidytext ?unnest_tokens? function which transforms the ?th?
data in the following way:
tidytext::unnest_tokens(th, word, text, token = "tweets") -> tt
head(tt)
status_id created_at lat lng 1: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841 2: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841 3: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841 4: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841 5: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841 6: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841 county_name fips state_name state_abb urban_level urban_code 1: Cumberland County 23005 Maine ME Medium Metro 3 2: Cumberland County 23005 Maine ME Medium Metro 3 3: Cumberland County 23005 Maine ME Medium Metro 3 4: Cumberland County 23005 Maine ME Medium Metro 3 5: Cumberland County 23005 Maine ME Medium Metro 3 6: Cumberland County 23005 Maine ME Medium Metro 3 population word 1: 277308 technique 2: 277308 is 3: 277308 everything 4: 277308 with 5: 277308 olympic 6: 277308 lifts but once I have unnested the tokens, I am unable to recombine them back into tweets. Ideally the end result would append a new column to the ?th? data that would flag a tweet that contained all of the search words for any of the search terms; so the work flow would look like 1) look for all search words for one search term in a tweet 2) if all of the search words in the search term are found, create a flag (mutate(flag = 1) or some such) 3) do this for all of the tweets 4) move on the next search term and repeat Again, my thanks for your patience. -- Nate Parsons Pronouns: He, Him, His Graduate Teaching Assistant Department of Sociology Portland State University Portland, Oregon 503-725-9025 503-725-3957 FAX
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