similar to: Dividing rows in groups

This will handle all the columns; it assumes the ones you want to start with are in column 2 through the end: > library(dplyr) > df1 <- read.table(text = "ID A B + 1 1 2 + 1 0 3 + 2 5 NA + 2 1 3 + 3 1 4 + 4 NA NA + 4 0 1 + 4

I have two tables like: Table A: id (autoincrement) name Table B id id_of_A desc I want to add a record to table A and based on the id of A, I want to add a record to table B. I don''t think there is any SQL command that support this (at least in MySQL 4.1, so I use LAST_INSERT_ID()). (Is there any other way? or MySQL 5 support any special SQL command?) But I need

I would like to read the following hierarchical data set. There is a family record followed by one or more personal records. If col. 7 is "1" it is a family record. If it is "2" it is a personal record. The family record is formatted as follows: col. 1-5 family id col. 7 "1" col. 9 dwelling type code The personal record is formatted as follows: col.

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)

#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

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.

Hi there, I have a list of dataframes (generated by reading multiple files) and all dataframes are comparable in dimension and column names. They also have a common column, which, I'd like to use for merging. To give a simple example of what I have: df1 <- data.frame(c(LETTERS[1:5]), c(2,6,3,1,9)) names(df1) <- c("pos", "data") df3 <- df2 <- df1 df2$data

The rbind on empty and nonempty data frames behaves inconsistently. I am not sure if by design. In the first example, first row is deleted, which may or may not be on purpose: df1 <- data.frame() df2 <- data.frame(foo=c(1, 2), bar=c("a", "b")) rbind(df1, df2) foo bar 2 2 b Now if we continue: df1 <- data.frame(matrix(0, 0, 2)) names(df1) <- names(df2)

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) >

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

Hola a todxs, No encuentro la manera de hacer algo que aparentemente parece muy sencillo: Tengo dos dataframe, en el primero tengo una serie de códigos con hora de inicio y hora de fin y en el segundo otros códigos asociados a una hora; Lo que necesito es crear una nueva variable en el segundo data frame que indique a qué intervalo del primer data frame (df1$id) pertenece cada nivel del segundo

Hi, Two ways to create what should normally be the same data frame: > df1 <- data.frame(a=character(0), b=character(0))> df1 [1] a b <0 rows> (or 0-length row.names) > df2 <- as.data.frame(matrix(character(0), ncol=2, dimnames=list(NULL, letters[1:2]))) > df2 [1] a b <0 rows> (or 0-length row.names) unique() works as expected except that I

I would suggest the method of Sokal and Rholf (1995) S. 498, using the F test. Below I repeat the analysis by Spencer Graves: Spencer: > df1 <- data.frame(x=1:3, y=1:3+rnorm(3)) > df2 <- data.frame(x=1:3, y=1:3+rnorm(3)) > fit1 <- lm(y~x, df1) > s1 <- summary(fit1)$coefficients > fit2 <- lm(y~x, df2) > s2 <- summary(fit2)$coefficients > db <-

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

Hello, I have two dataframes DF1 and DF2 that should be identical but are not (DF1 has some rows that aren't in DF2, and vice versa). I would like to produce a new dataframe DF3 containing rows in DF1 that aren't in DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1). I have a solution for this problem (see self contained example below) but it's awkward and

Hey Folks, Could somebody show me how to loop through a list of dataframes? I want to be able to generically access their elements and do something with them. For instance, instead of this: df1<- data.frame(x=(1:5),y=(1:5)); df2<- data.frame(x=(1:5),y=(1:5)); df3<- data.frame(x=(1:5),y=(1:5)); plot(df1$x,df1$y); plot(df2$x,df2$y); plot(df3$x,df3$y); I would like to do something like:

Hello all, I have a quandry I have been scratching my head about for a while. I've searched the manual and the web and have not been able to find an acceptable result, so I am hoping for some help. I have two data frames and I want to index into the first using the second, and replace the specific values I have indexed with more values from the second data.frame. I can do this

Hi, I'm trying to compare two linear regressions. I'm using the following approach: ################## xx<-1:100 df1 <- data.frame(x = xx, y = xx * 2 + 30 + rnorm(n=length(xx),sd=10), g = 1) df2 <- data.frame(x = xx, y = xx * 4 + 9 + rnorm(n=length(xx),sd=10), g = 2) dta <- rbind(df1, df2) dta$g <- factor(dta$g)

Hi I have two columns in data frame. First column is based on "ID" assigned to each group of my data (similar ID depicts one group). From second column, I want to identify highest value among each group and want to assign the same ID to that highest value. Right now the data looks like: ID Value 1 0.69 1 0.31 2 0.01 2 0.99 3 1.00 4 NA 4

Hello I have 2 data frames DF1 and DF2 where DF2 is a subset of DF1: DF1= data.frame(V1=1:6, V2= letters[1:6]) DF2= data.frame(V1=1:3, V2= letters[1:3]) How do I create a new data frame of the difference between DF1 and DF2 newDF=data.frame(V1=4:6, V2= letters[4:6]) In my real data, the rows are not in order as in the example I provided. Thanks much Joseph [[alternative HTML version