similar to: return NA

Question : Is it possible to create a function, using a for ifelse function, inside sapply, to compare the values in one data frame to a set of upper and lower limits in another data frame, same number of columns., Take the values which meet the requirements "TRUE" and create a new data frame or table containing the filtered data? Can you give me a shove in the correct direction?

I'm new to R and not an experienced writer of programs, which may help explain my question. I wish to create a table or data frame which contains the quantiles of the columns in the data frame DF. I wish to produce a table T where T[1] shows me the quantiles of column DF[1] right up through the entirety of DF. Tried several approaches with limited success. This looked like the best

I have a general question. Is there a setting that can be used for a multiple line type? The situation is that I want a solid line between x and y points but if the y point is missing, I want a dashed line type to the next point. In other words, if point 1 to 2 exists, make that line solid, otherwise, make it dashed up to the next existing x/y point. Additionally, what plot type would you

Is there anyway to preset date formats? I have a date from a cover.dbf that is shown as this: > cover$FINALREPOR [1] "2003-06-24" The numeric value in cover$FINALREPOR is 12227. I'd rather not create another vector to hold the properly formatted date. When I put this in a WordPerfect merge, I want the date to be June 24, 2003. I could take care of the problem in a

I am using rbind to add one list with one row to another master list. The problem is that not all columns exist in both lists. What methods would you recommend to reorder one list based on the column names of another? If both sets have the same order and columns, I can then use rbind. I can live with columns being added to the master list set it makes the task easier using something like

In this simple function, how can I pass strings for index and column names to the function? I've posted this type of question before and received no response. Maybe this example will be easier to understand and troubleshoot. ds <- function(myds, vec) {myds[[vec]]*2} ds1 <- c(X=list(1:10), Y=list(11:20)) ds(get("ds1"),get("Y")) khobson at odot.org Kenneth Ray

How can I stop the following warning from occuring? invalid factor level, NAs generated in: "[<-.factor"(`*tmp*`, iseq, value = structure(1, .Label = "12", class = "factor")) The Label messages are for "5", "8", "12" and "46". I want the NAs to be generated as needed. Is this causing R to slow down by generating the warning

For windows, how can I list only the folders in some folder? I was thinking that dir() and file.info() with isdir==TRUE being something that might work. These folders or directories are numerically named with no dot extension names or other characters. Typically, these are 3132, 3334, ... Here is what I tried. The last line is where I need more work. pData="C:/Myfiles/R/Data/" setwd

Dear expeRts, What is the best approach to create a third data frame from two given ones, when the new/third data frame has last column computed from the last columns of the two given data frames? ## Okay, sounds complicated, so here is an example. Assume we have the two data frames: df1 <- data.frame(Year=rep(2001:2010, each=2), Group=c("Group 1","Group 2"), Value=1:20)

Dear all, I have partial data set with four colums. First column is "site" with three factors (i.e., A, B, and C). From second to fourth columns (v1 ~ v3) are my observations. In the observations of the data set, "." indicates missing value. I replaced "." with NA. To replace "." with NA, I used two steps. First, I replaced "." with NA, and

#I want to "merge" or "join" 2 dataframes (df1 & df2) into a 3rd (mydf). I want the 3rd dataframe to contain 1 row for each row in df1 & df2, and all the columns in both df1 & df2. The solution should "work" even if the 2 dataframes are identical, and even if the 2 dataframes do not have the same column names. The rbind.fill function seems to work. For

Folks, I'm checking the structure of a dataframe for duplicate parameters at a site station (i.e depth should be measured once, not twice), using aggregate to count each parameter within a site station. The fake data below has only 26000 rows, and takes roughly 14 seconds. My real data has 750000 rows and I had to stop execution after about an hour. The by() function is faster, but I

Thanks, Jim. The code works, but I don't understand why you use q1090 <- quantile(DF1$B, probs=c()), rather than DF1$A? Also, how to add a legend for both points DF1 and DF2? On Wed, Jul 12, 2017 at 8:25 PM, Jim Lemon <drjimlemon at gmail.com> wrote: > Hi lily, > Here is the first plot: > > plot(DF1$A,DF1$B,pch=19,col="red") > meanA<-mean(DF1$A) >

Hi, I have two dataframes: The first, df1, contains some missing data: cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 The second, df2, contains the following: cola colb colc cold cole 1 1.4 0.8 0.02 1.6 0.6 I'm wanting all missing data in df1$cola to be replaced by the value of df2$cola.

Dear community, I'm working with the data.frame attached ( http://r.789695.n4.nabble.com/file/n4122926/df1.xls df1.xls ), let's call it df1. I typed: df1<- read.xls("C:/... dir .../df1.xls",colNames= TRUE, rowNames= TRUE) Then I splited randomly df1 using splitdf function (http://gettinggeneticsdone.blogspot.com/2011/03/splitting- dataset-revisited-keeping.html)

Hi, I have a data.frame that contains a variable act which records the duration (in seconds) of two states (wet-dry) for several individuals (identified by Ring) over a period of time. Since I want to work with daytime (i.e. from sunrise till sunset) and night time (i.e. from sunset till next sunrise), I have to split act from time[i] till sunset and from sunset until time[i+1], and from time[k]

Dear list, I am trying to make a contingency table with xtabs but I am getting a 0 where I expect a 'NA'. Here is a simple example: options(stringsAsFactors = FALSE) rn <- LETTERS[1:4] df1 <- data.frame(r07 = rep(rn, each=4), r08 = rep(rn, 4), value = 1:16) xtabs(value ~ r07 + r08, df1) # Delete the combination [A, C] df1 <- df1[-3,] # Set 'value'

Thank you Rui. I ran the following script df1 <- read.table("solar_hour", header = TRUE) df1$date <- as.Date(paste(df1$year, df1$hour), format = "%Y %j", origin = "2012-08-01-0") df2 <- df1[c("date", "IMF", "SWS", "SSN", "Dst", "f10")] head(df1) #To display all the rows print(df2). It gave me this

Hello, I would like to replace a for loop with lapply in order to speed up the treatment of my data (I've read lapply can help to do it). At the end of the message, you will find a simple example (function is more complex and data frames is more than 1 million of rows) of what I would like to do, that is applying the same calculation to all the rows of the data frame (knowing that I cannot

Dear Mailing-List, I think this is a newbie question. However, i would like to integrate a loop in the function below. So that the script calculates for each variable within the dataframe df1 the connecting data in df2. Actually it takes only the first row. I hope that's clear. My goal is to apply the function for each data in df1. Many thanks in advance. An example is as follows: df1