Muchas gracias a todos por su ayuda.
Hace un rato antes de abrir el correo, he encontrado dos soluciones a mi
problema de como calcular el porcentaje de variación.
La primera es usando el paquete dplyr:
Hola,
Te sale error porque has cargado el fichero con read.csv().
Si pruebas a cargarlo con "fread()" tus datos tendrán clase data.table.
El error que obtienes es porque el objeto df (igual que datos) no es un
data.table.
Saludos,
Carlos Ortega
www.qualityexcellence.es
El dom., 22 mar. 2020 a
Eric
¿Que dataset utilizo? Por curiosidad probé su código, pero me salen
errores. Copio y pego todo como me sale en la consola.
> #
https://raw.githubusercontent.com/datasets/covid-19/master/data/time-series-19-covid-combined.csv
> datos <-
Eric
Gracias por compartir.
Javier Marcuzzi
El dom., 22 mar. 2020 a las 16:52, neo ()
escribió:
> Hola Javier, yo lo hice de la siguiente forma:
>
> library(data.table)
> library(ggplot2)
> library(anytime)
>
> df <- fread("/home/neo/Desktop/rhelp/spain.csv")
> df[, fec:=anytime(fec)]
>
Hola Javier, yo lo hice de la siguiente forma:
library(data.table)
library(ggplot2)
library(anytime)
df <- fread("/home/neo/Desktop/rhelp/spain.csv")
df[, fec:=anytime(fec)]
setkey(df,com,fec)
# newc: son los nuevos casos
df[, newc:=ct - shift(ct), by=.(com)]
# tasa: es la tasa de
Thanks a lot - this does indeed do the trick!
-Oprindelig meddelelse-
Fra: peter dalgaard
Sendt: 21. marts 2020 18:08
Til: Troels Ring
Emne: Re: [R] cannot coerce class '"expression"' to a data.frame
Oops, disregard previous...
I'm no ggplot expert, but google "ggplot plotmath"
Wrong list. Way wrong. Pay attention to the Posting Guide.
The correct list would be the Rcpp-devel. If your question were less specific,
then r-package-devel. But absolutely not r-help.
There are known issues with Rcpp being fixed right now on the fly... go read
the recent archives for
Dear R-help-list,
In an e-mail received yesterday from a member of the CRAN maintainer
team, I was informed that the
package PCMBaseCpp (https://CRAN.R-project.org/package=PCMBaseCpp)
is going to be removed from CRAN on April 4th,
due to an R-process crash during unit-tests on the fedora-clang
Hi Rui,
Many thanks... it perfectly works
Best,
Sacha
Le dimanche 22 mars 2020 à 11:02:49 UTC+1, Rui Barradas
a écrit :
Correction:
In MSE
modmat <- model.matrix(as.formula(formula), data = d)
doesn't need as.formula, it should be
modmat <- model.matrix(formula, data = d)
Hi Jeff,
Hi David,
Thanks for your responses. As the predict function does not work with hbrfit, I
have tried something without the predict function. There is an error message
(Error in .subset2(x, i, exact = exact)) unclear to me. Many thanks for your
help.
# # # # # # # # # # # # # # # #
Or even split -> lapply -> unsplit, in cases where you want the results put
back in the original order.
(Doesn't matter here, but it would, had it been, say, ordered 1,2,3,1,2,2,3).
-pd
> On 22 Mar 2020, at 08:44 , Deepayan Sarkar wrote:
>
> Another possible approach is to use split ->
Correction:
In MSE
modmat <- model.matrix(as.formula(formula), data = d)
doesn't need as.formula, it should be
modmat <- model.matrix(formula, data = d)
Sorry,
rui Barradas
Às 09:59 de 22/03/20, Rui Barradas escreveu:
Hello,
1. There is no need to install package 'boot', it's a base
Hello,
1. There is no need to install package 'boot', it's a base package.
2. The question.
The problem is that FastTau returns an object of class "list" and there
is no 'predict' method for lists, you will have to define your own.
This is easy, it's just a matrix multiply.
And you are not
On 22/03/20 8:44 pm, Deepayan Sarkar wrote:
Another possible approach is to use split -> lapply -> rbind, which I
often find to be conceptually simpler:
d <- data.frame(Serial = c(1, 1, 2, 2, 2, 3, 3),
Measurement = c(17, 16, 12, 8, 10, 19, 13))
dlist <- split(d, d$Serial)
Another possible approach is to use split -> lapply -> rbind, which I
often find to be conceptually simpler:
d <- data.frame(Serial = c(1, 1, 2, 2, 2, 3, 3),
Measurement = c(17, 16, 12, 8, 10, 19, 13))
dlist <- split(d, d$Serial)
dlist <- lapply(dlist, within,
{
Serial_test
On 22/03/20 4:01 pm, Thomas Subia via R-help wrote:
Colleagues,
Here is my dataset.
Serial Measurement Meas_test Serial_test
1 17 failfail
1 16 passfail
2 12 passpass
2 8
Here's a very "step by step" example with dplyr as I'm trying to teach myself
the Tidyverse way of being
library(dplyr)
# SerialMeasurementMeas_testSerial_test
# 117failfail
# 116passfail
# 2
On Sat, 21 Mar 2020 20:01:30 -0700
Thomas Subia via R-help wrote:
> Serial_test is a pass, when all of the Meas_test are pass for a given
> serial. Else Serial_test is a fail.
Use by/tapply in base R or dplyr::group_by if you prefer tidyverse
packages.
--
Best regards,
Ivan
18 matches
Mail list logo
