similar to: difference of two rows

Hi there. I collectad data of several animals (Id) that were caught and measured at several occasions. The dataframe looks like this: Grouped Data: mass ~ age | Id Id age mass 1 1 5.4 1 3 6.2 1 15 10.0 2 3 8.1 2 10 12.8 3 2 5.9 3 10 7.1 3 15 15.4 3 17

Dear Rlers, in the following dataset I would like to insert a new column that refers to the data of the previous row. My question is whether the probability of a female (Id) changes if she had given birth to a pup in the previous year. So my dataframe consists of the column Id, year (2003-2007 for each Id) and offspring (=of; 1-0): Id year of 1 2003 1 1 2004 0 1

Dear RUsers, I guess this is an easy question for someone a little familiar with programming...(which I am not)... I've got 2 colummns, one shows just dates(SST_date, Class 'Date' num), the other one shows the SeaSurfaceTemperature (SST, num) at that certain date. SST_date SST 2008-01-01 22.2 2008-01-02 21.8 2008-01-03 22.8 2008-01-04 22.9 2008-01-05 23.1 2008-01-06 23.2 ...

Dear R-helpers, I have two rows in my dataframe: ID VALUE 1A 10 1B 15 and I would like to combine these two rows into a single (new) row in my dataframe: ID VALUE 1 25 ...simply by specifying a new value for ID and summing the two VALUES. I have been trying to do this with with rbind, but it's not working. I'd appreciate any pointers. Thanks, Mark Na [[alternative

Hello- A basic question which has nonetheless floored me entirely. I have a dataset which looks like this: Type ID Date Value A 1 16/09/2020 8 A 1 23/09/2010 9 B 3 18/8/2010 7 B 1 13/5/2010 6 There are two Types, which correspond to different individuals in different conditions, and loads of ID labels (1:50)

Hi, I am relatively new to R; when creating functions, I run into problems with missing values. I would like my functions to ignore rows with missing values for arguments of my function) in the analysis (as for example is the case in STATA). Note that I don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my

I am working with a longitudinal data set in the long format. This data set has three observations per grade level per year. Here are the first 10 rows of the data frame: >tenn.dat[1:10,] year schid type grade gain se new cohort 6 2001 100005 5 4 33.1 3.5 4 3 7 2002 100005 5 4 33.9 3.9 4 2 8 2003 100005 5 4 32.3 4.2 4 1 10 2001 100005

Hi R help, I'm a fairly experienced R user but this manipulation has me stumped, please help: DATA id<-rep(LETTERS[1:5],20) distance<-rnorm(1:100, mean = 100) bearing<-sample(1:360,100,replace=T) month<-sample(1:12,100,replace=T) I have a dataset with records of individuals (id) , each with a distance (distance) & direction (bearing) recorded for each month (month). I want

Hi R-users, Following this post http://tolstoy.newcastle.edu.au/R/help/06/06/28965.html , how do I get last two rows (or six or ten) by id group out of the data frame? Here the example gives just the last row. Sincere thanks, Lauri [[alternative HTML version deleted]]

I have got a dataframe containing measurement of aircraft noise like this: > Id <- c(1,4,5,2,3,6,4,1,2,5,6,3) > Noise <- c(88,94,97,98,92,56,103,102,87,95,92,97) > Height <- c(190, 150, 120, 115, 188, 104, 101, 189, 146, 111, 124, 126) > > df <- data.frame(Id, Noise, Height) Now I would like to split this in two new dataframes. The first one containing the rows

Hi R-users, I'm trying to find an elegant way to count the number of rows in a dataframe with a unique combination of 2 values in the dataframe. My data is specifically one column with a year, one with a month, and one with a day. I'm trying to count the number of days in each year/month combination. But for simplicity's sake, the following dataset will do:

Dear R users, my dataframe looks like this head(dat) Id sex byear age 1 300 m 2003 50 2 300 m 2003 36 3 402 f 2003 29 4 402 f 2003 21 5 402 f 2003 64 6 150 m 2005 43 ... ...(where Id is just the Identification number of Individual, sex (male or female), byear (=birthyear)) now, I 'd like to add a column, where each Individual gets an automated number starting

I am having trouble doing the following. I have a data.frame like this, where x and y are a variable that I want to do calculations on: Name Year x y ab 2001 15 3 ab 2001 10 2 ab 2002 12 8 ab 2003 7 10 dv 2002 10 15 dv 2002 3 2 dv 2003 1 15 Before I do all the other things I need to do with this data, I need to summarize or collapse the data by name and year. I've

Previously, I posed the question pasted down below to the list and received some very helpful responses. While the code suggestions provided in response indeed work, they seem to only work with *very* small data sets and so I wanted to follow up and see if anyone had ideas for better efficiency. I was quite embarrased on this as our SAS programmers cranked out programs that did this in the blink

*Hi all, I know this is probably basic, but I have proven to be a slow learner in any programming language. Anyhow, how can I calculate the SD for each person in my table? I have two patients in this R data.frame, 7200 and 23955. I extracted this from a relational database, but am I better off attempting to compute SD in SQL, or is this easily accomplished in R? * SUBJECT_ID HR 1

Hi all, I'm new to the list but have benfited from it quite extensively. Straight to my rather strange question: I have a data frame that contains mapping rules in this way: ACCOUNT, RULE COLUMNS, Effective Date The dataframe comes from a database that stores all dates. What I would like to do is to create a data frame with only the most recent rule for each account. In traditional

Dear list, I have this dataframe: > names(events) [1] "EID" "X" "Y" "trip" "tow" "catch" "effort" "depth" [9] "season" Where some of my unique ID "EID" appears more than once in 162 cases. > length(events$EID)-length(unique(events$EID)) [1] 162 I would like to combined

Hi, folks, Please let me address the problem by the following codes: first=c('u','b','e','k','j','c','u','f','c','e') second=c('usa','Brazil','England','Korea','Japan','China','usa','France','China','England') third=1:10

I have a dataframe with 700,000 rows and 2 vectors (columns): ?group? and ?score?. I wish to calculate a third vector of length 700000: the average score by group. Even though the avarge value will repeat, I wish to return the average for that particular group for each row. (I know I can do this by calculating each group?s average and then using the merge command, but as my calculations get

Hello to all. My question is very simple... Let's say we have a data frame with three variables (columns): X, W and F. X is a numeric variable (e.g. like income) F is a factor (e.g. with 2 levels) and W is a case weight (data are from household sample but an individual was interviewed, weights are functions of number of persons in the house hold). I wanted to compute a means of X weighted