Here are one dataframe/tibble and one character element(this element is one column of a tibble)
df1 <- structure(list(Twitter_name = c("CHESHIREKlD", "JellyComons",
"kirmiziburunlu", "erkekdeyimleri", "herosFrance", "IkishanShah"
), Declared_followers = c(60500L, 43100L, 31617L, 27852L, 26312L,
16021L), Real_followers = c(60241, 43054, 31073, 27853, 25736,
15856), Twitter_Id = c("783866366", "1424086592", "2367932244",
"3352977681", "2580703352", "521094407")), .Names = c("Twitter_name",
"Declared_followers", "Real_followers", "Twitter_Id"), row.names = c(NA,
-6L), class = c("tbl_df", "tbl", "data.frame"))
myId <- c("867211097882804224", "868806957133688832", "549124465","822580282452754432",
"109344546", "482666188", "61716107", "3642392237", "595318933",
"833365943044628480", "1045015087", "859830740669800448", "860562940059045888",
"2854457294", "871784135983067136", "866922354554814464", "4839343547",
"849451474572759040", "872084673526214656", "794841530053853184")
N:B: df1 has been shortened and has indeed 128 observations.
I am looking to test all row elements of df1$Twitter_Id and see if they are in myId. I can run this:
> match(myId[1], df1$Twitter_Id)
but:
it stops at the first occurrence
I need to apply the match() function to all elements of myId.
I can't find a clean and simple way to do this, using lapply() or other functions from dplyr, tydiverse packages.
Thank you for help.
EDIT I need to be more explicit with the whole real case.
myTw <- structure(list(id_str = c("893445199661330433", "893116842558050304",
"892739336466305024", "892401780105019393", "892401594272296963",
"892365572486430720", "891964139756818432")), .Names = "id_str", row.names = c(NA,
-7L), class = c("tbl_df", "tbl", "data.frame"))
these are tweets ID.What I am looking for is to obtain which twitter users have retweeted these ones. To do this, I use the retweeters() function from package twitteR.
library(twitteR)
MyRtw <- retweeters(myTw[1])
MyRtw <- c("889135428028084224", "867211097882804224", "868806957133688832",
"549124465", "822580282452754432", "109344546", "482666188",
"61716107", "3642392237", "595318933", "833365943044628480",
"1045015087", "859830740669800448", "860562940059045888", "2854457294",
"871784135983067136", "866922354554814464", "4839343547", "849451474572759040",
"872084673526214656")
This is a list of Twitter user Id.
Now finally I want to see which users from df1$Twitte_Id have retweeted MyTw[1].
You can use the '%in%' operator.
Edit: Probably this is what you want. Here I used the data posted in your original post (before editing).
matchVector = NULL
for (id in df1$Twitter_Id) {
matchCounter <- sum(myId %in% id)
matchVector <- c(matchVector, matchCounter)
}
df1$numberOfMatches <- matchVector
Related
I wanted to get the standard deviation of the 3 previous row of the data, the present row and the 3 rows after.
This is my attempt:
mutate(ming_STDDEV_SAMP = zoo::rollapply(ming_f, list(c(-3:3)), sd, fill = 0)) %>%
Result
ming_f
ming_STDDEV_SAMP
4.235279667
0.222740262
4.265353
0.463348209
4.350810667
0.442607461
3.864739333
0.375839159
3.935632333
0.213821765
3.802632333
0.243294783
3.718387667
0.051625808
4.288542333
0.242010836
4.134689
0.198929941
3.799883667
0.112733475
This is what I expected:
ming_f
ming_STDDEV_SAMP
4.235279667
0.225532646
4.265353
0.212776157
4.350810667
0.23658801
3.864739333
0.253399417
3.935632333
0.26144862
3.802632333
0.246259684
3.718387667
0.20514358
4.288542333
0.208578409
4.134689
0.208615874
3.799883667
0.233948429
It doesn't match your output exactly, but perhaps this is what you need:
zoo::rollapply(quux$ming_f, 7, FUN=sd, partial=TRUE)
(It also works replacing 7 with list(-3:3).)
This expression isn't really different from your sample code, but the output is correct. Perhaps your original frame has a group_by still applied?
Data
quux <- structure(list(ming_f = c(4.235279667, 4.265353, 4.350810667, 3.864739333, 3.935632333, 3.802632333, 3.718387667, 4.288542333, 4.134689, 3.799883667), ming_STDDEV_SAMP = c(0.225532646, 0.212776157, 0.23658801, 0.253399417, 0.26144862, 0.246259684, 0.20514358, 0.208578409, 0.208615874, 0.233948429)), class = "data.frame", row.names = c(NA, -10L))
I'm trying to apply the discretize_rgr function (here) of the package funModeling to multiple columns of a dataframe.
For a single column, it is working for me in this way:
discretize_rgr(input = df.div$to_be_discretized, target = df.div$TARGET, max_n_bins=10)
So, I'm trying to use the purrr package to manage multiple columns in this way:
df.div %>%
modify_if( is.numeric, ~ discretize_rgr(., target = df.div$TARGET, max_n_bins=10))
but I'm get the following error:
Error in order(fpoints_top) : argument 1 is not a vector
What's wrong?
UPDATE (example data)
structure(list(to_be_discretized = c(0.0152096300012854, 0.0132660373578711,
0.014699121782711, 0.0157102877064037, 0.0197417484744586, 0.019651999420645
), TARGET = c(27136, 30048, 34840, 138812, 191088, 240370)), class = c("spec_tbl_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L))
I am trying to adapt the code found here to import employee data from an Excel file into a data frame and then use the as.node function from the data.tree package.
This is the code I have written so far
library(data.tree)
library(readxl)
baseframe <- read_excel("Test Emplist.xlsx")
baseframe$pathstring <- paste("CompanyName",
baseframe$LastName,
baseframe$FirstName,
sep = "/")
stafflist <- as.Node(baseframe)
The data frame is being created successfully. Below is the dput representation
> dput(head(baseframe))
structure(list(LastName = c("Vasa", "Vasa", "Pras", "Tang", "Sing",
"Vats"), FirstName = c("Evan", "Koma", "Shil", "Hand", "Smri",
"Saur"), pathstring = c("CompanyName/Vasa/Evan", "CompanyName/Vasa/Koma",
"CompanyName/Pras/Shil", "CompanyName/Tang/Hand", "CompanyName/Sing/Smri",
"CompanyName/Vats/Saur")), .Names = c("LastName", "FirstName",
"pathstring"), row.names = c(NA, 6L), class = c("tbl_df", "tbl",
"data.frame"))
but when I get to the line stafflist <- as.Node(baseframe) I am getting an error message saying
Error in strsplit(mypath, pathDelimiter, fixed = TRUE :
non-character argument
I'm guessing the as.node function calls another function called strsplit somewhere. I have tried running the function myself as so
strsplit(baseframe$pathstring, "/", fixed = TRUE)
which is running no problem. I'm not sure why the as.node function is throwing the error?
If I have the following data:
df <- structure(list(x = c(1.63145539094563, 1.67548187017034, 1.71950834939504,
1.76353482861975, 1.80756130784445, 1.85158778706915, 1.89561426629386,
1.93964074551856, 1.98366722474327, 2.02769370396797, 2.07172018319267,
2.11574666241738, 2.15977314164208, 2.20379962086679, 2.24782610009149,
2.2918525793162, 2.3358790585409, 2.3799055377656, 2.42393201699031,
2.46795849621501, 2.51198497543972, 2.55601145466442, 2.60003793388912,
2.64406441311383, 2.68809089233853, 2.73211737156324, 2.77614385078794,
2.82017033001265, 2.86419680923735, 2.90822328846205, 2.95224976768676,
2.99627624691146, 3.04030272613617, 3.08432920536087, 3.12835568458557,
3.17238216381028, 3.21640864303498, 3.26043512225969, 3.30446160148439,
3.3484880807091, 3.3925145599338, 3.4365410391585, 3.48056751838321,
3.52459399760791, 3.56862047683262, 3.61264695605732, 3.65667343528202,
3.70069991450673, 3.74472639373143, 3.78875287295614), y = c(24.144973858154,
18.6408277478876, 21.9174270206615, 22.8017876727379, 20.9766270378248,
18.604384256745, 18.4805250429826, 15.8436744335752, 13.6357170277296,
11.6228806771368, 9.4065868126964, 6.81644596802601, 4.41187500831424,
4.31911614349431, 0.678259284890563, -1.18632719250877, -2.32986407762089,
-3.84480566043122, -5.24738510499144, -5.20160089844013, -5.42094587600499,
-5.39886757202858, -5.26753920575326, -4.68727963638973, -2.73267203102102,
0.296905237887623, 2.45725152489283, 5.12102449689086, 7.13986218237411,
10.2044876281093, 14.4358946463429, 19.0643081865458, 22.8920445618834,
26.7229418763085, 31.3776791707576, 36.19058349817, 41.2843224331918,
46.3396522631345, 51.4321502764393, 56.4080998038294, 61.5215778808583,
66.6845421308734, 71.3912749310486, 76.0856977880158, 80.7039319129457,
84.4095953723555, 88.0163019647757, 89.918078622734, 91.6341473685881,
94.0404562451352)), class = c("tbl_df", "tbl", "data.frame"), .Names = c("x",
"y"), row.names = c(NA, -50L))
Plot:
How do I find the exact x value when y == 0? I tried doing interpolation, but it does not necessarily give me a y value equals to zero. Does anyone know of a function to find zero crossings?
Firstly, one can define a corresponding (linearly) interpolated function with
approxfun(df$x, df$y)
where the result looks like
curve(approxfun(df$x, df$y)(x), min(df$x), max(df$x))
Those zero crossing then can be seen as the roots of this function. In base R there is a function uniroot, but it looks for a single root, while in your case we have two. Hence, one option would be the rootSolve package as in
library(rootSolve)
uniroot.all(approxfun(df$x, df$y), interval = range(df$x))
# [1] 2.263841 2.727803
I am trying to use the structure() function to create a data frame in R.
I saw something like this
structure(mydataframe, class="data.frame")
Where did class come from? I saw someone using it, but it is not listed in the R document.
Is this something programmers learned in another language and carries it over? And it works. I am very confused.
Edit: I realized dput(), is what actually created a data frame looking like this. I got it figured out, cheers!
You probably saw someone using dput. dput is used to post (usually short) data. But normally you would not create a data frame like that. You would normally create it with the data.frame function. See below
> example_df <- data.frame(x=rnorm(3),y=rnorm(3))
> example_df
x y
1 0.2411880 0.6660809
2 -0.5222567 -0.2512656
3 0.3824853 -1.8420050
> dput(example_df)
structure(list(x = c(0.241188014013708, -0.522256746461544, 0.382485333260912
), y = c(0.666080872170054, -0.251265630627216, -1.84200501106852
)), .Names = c("x", "y"), row.names = c(NA, -3L), class = "data.frame")
Then, if someone wants to "copy" your data.frame, he just has to run the following:
> copied_df <- structure(list(x = c(0.241188014013708, -0.522256746461544, 0.382485333260912
+ ), y = c(0.666080872170054, -0.251265630627216, -1.84200501106852
+ )), .Names = c("x", "y"), row.names = c(NA, -3L), class = "data.frame")
I put "copy" in quotes because note the following:
> identical(example_df,copied_df)
[1] FALSE
> all.equal(example_df,copied_df)
[1] TRUE
identical yields false because when you post your dput output, often the numbers get rounded to a certain decimal point.
'class' is not a specific argument to the structure function - that's why you didn't find it in the help file.
structure takes an object and then any number of name/value pairs and sets them as attributes on the object. In this case, class was such an attribute. You can try this to add fictional 'foo' and 'bar' attributes to a vector:
x <- structure(1:3, foo=42, bar='hello')
attributes(x)
#$foo
#[1] 42
#
#$bar
#[1] "hello"
And as Joshua Ulrich and Xu Wang mentioned, you should not create a data.frame like that.
I'm scratching my head, wondering what "R Document" would not have said something about "class". It's a very basic component of the the language and how functions get applied. You should type this and read:
?class
?methods