search for: sepal_length

...ll with one argument, the select statement. Here is an example which processes an SQL select statement whose functionality is similar to the R aggregate function. Note that although the iris dataset (which is built into R) uses the name Sepal.Length the R database interface, DBI, converts that to Sepal_Length. Just install the sqldf package from CRAN and type these two lines into R without the > prompts: > library(sqldf) > sqldf("select Species, avg(Sepal_Length) from iris group by Species") Species avg(Sepal_Length) 1 setosa 5.006 2 versicolor 5.93...

...ll with one argument, the select statement. Here is an example which processes an SQL select statement whose functionality is similar to the R aggregate function. Note that although the iris dataset (which is built into R) uses the name Sepal.Length the R database interface, DBI, converts that to Sepal_Length. Just install the sqldf package from CRAN and type these two lines into R without the > prompts: > library(sqldf) > sqldf("select Species, avg(Sepal_Length) from iris group by Species") Species avg(Sepal_Length) 1 setosa 5.006 2 versicolor 5.93...

I've completed an experiment and want to summarize the results. There are two things I like to create. 1) A simple count of things from the data.frame with predictions 1a) Number of predictions with probability greater than x 1b) Number of predictions with probability greater than x that are really true In SQL, this would be, "Select count(predictions) from

In polr.R the (several) functions gmin and fmin contain the code > theta <- beta[pc + 1L:q] > gamm <- c(-100, cumsum(c(theta[1L], exp(theta[-1L]))), 100) That's bad. There's no reason to suppose beta[pc+1L] is larger than -100 or that the cumulative sum is smaller than 100. For practical datasets those assumptions are frequently violated, causing the

Happy new year, dear listers, I have a question about Rsqlite. when I fetch the data out of sqlite database, there is something like '\r\n' at the end of last column. Here is the example: Sepal_Length Sepal_Width Petal_Length Petal_Width Species 1 5.1 3.5 1.4 0.2 setosa\r\n 2 4.9 3.0 1.4 0.2 setosa\r\n 3 4.7 3.2 1.3 0.2 setosa\r\n 4 4.6 3.1 1.5 0.2 setosa...

Hi folk, I tried this and it works just perfectly tapply(iris[,1],iris[5],mean) but, how to obtain a single table from multiple variables? In tapply x is an atomic object so this code doesn't work tapply(iris[,1:4],iris[5],mean) Thanx and great summer holidays Gianandrea -- View this message in context: http://www.nabble.com/multiple-tapply-tp18868063p18868063.html Sent from the R help

Hola a todos.Quiero saber si existe una forma mas apropiada para hacer esto:tengo un dataframe de 40 variables y una de ellas es de fechas.lo que quiero es una tabla agregada por suma y como criterio de agrupación esta variable de fecha.en sql sería algo así: select fecha, sum(v1), sum(v2)..., sum(v39)from tablagroup by fecha; mi problema es que las vn pueden ser de dimensión cambiante, es decir,