tidyverse

问题 I am trying to fit some time series using the R packages tsibble and fable , the still-under-construction replacement for the redoubtable Rob Hyndman's forecast package. The series are all combined into one tsibble, which I then fit with ARIMA, a function which replaces, among other things, forecast::auto.arima . I use map_at , first to iterate over all the elements except the Date , and then again to extract the model information from the models that have been fit to each series using

问题 I am trying to fit some time series using the R packages tsibble and fable , the still-under-construction replacement for the redoubtable Rob Hyndman's forecast package. The series are all combined into one tsibble, which I then fit with ARIMA, a function which replaces, among other things, forecast::auto.arima . I use map_at , first to iterate over all the elements except the Date , and then again to extract the model information from the models that have been fit to each series using

问题 I see when I run library(multcomp) (see this example), it complains (among other things): Attaching package: ‘MASS’ The following object is masked from ‘package:dplyr’: select Masking select is going to be awkward. I suppose I can use multcomp without putting it into the namespace with library . EDIT : What is the easiest way to run Dunnett's test that works well with the tidyverse? (Old question: Is there another package that offers Dunnett's test that is more compatible with the tidyverse?)

问题 A heatwave is defined if the maximum temperature at a meteorological station is 3 °C or more than the normal temperature consecutively for 3 days or more (Adopted from India Meteorological Department, Pune). I have calculated the daily average (daily normal) from multiple-year daily maximum temperature data like df <- data.frame("date"= seq(from = as.Date("1970-1-1"), to = as.Date("2000-12-31"), by = "day"), "MaxT" = runif(length(seq.Date(as.Date("1970-1-1"), as.Date("2000-12-31"), "days")),

问题 I'm working through the Hyndman fpp3 package based on this markdown document. https://github.com/robjhyndman/ISI_Workshop_2019/blob/master/5_reconciliation/reconciliation.Rmd I just couldn't find out why the following code fail to run PBS %>% aggregate_key(ATC1/ATC2, Scripts = sum(Scripts)) %>% filter(Month == yearmonth("1991 Jul")) %>% print(n=18) I keep receiving the following error each time I run the above. New names: * `` -> ...1 * `` -> ...2 * `` -> ...3 * `` -> ...4 * `` -> ...5 * ...

问题 This question already has answers here : Add row to a data frame with total sum for each column (9 answers) Closed 18 days ago . Given an n by m tibble with numeric values. How do you calculate row and column totals for the tibble. Here is a reprex with a sample tibble: library(tidyverse) df <- tibble(names=c('a','b','c','d','e'),x = 1:5, y =5:1, z=2:6) df #> # A tibble: 5 x 4 #> names x y z #> <chr> <int> <int> <int> #> 1 a 1 5 2 #> 2 b 2 4 3 #> 3 c 3 3 4 #> 4 d 4 2 5 #> 5 e 5 1 6 Created on

问题 I have a very simple question about referencing data columns within a nested dataframe. For a reproducible example, I'll nest mtcars by the two values of variable am : library(tidyverse) mtcars_nested <- mtcars %>% group_by(am) %>% nest() mtcars_nested which gives data that looks like this. #> # A tibble: 2 x 2 #> # Groups: am [2] #> am data #> <dbl> <list> #> 1 1 <tibble [13 × 10]> #> 2 0 <tibble [19 × 10]> If I now wanted to use purrr::map to take the mean of mpg for each level of am I

问题 I have a very simple question about referencing data columns within a nested dataframe. For a reproducible example, I'll nest mtcars by the two values of variable am : library(tidyverse) mtcars_nested <- mtcars %>% group_by(am) %>% nest() mtcars_nested which gives data that looks like this. #> # A tibble: 2 x 2 #> # Groups: am [2] #> am data #> <dbl> <list> #> 1 1 <tibble [13 × 10]> #> 2 0 <tibble [19 × 10]> If I now wanted to use purrr::map to take the mean of mpg for each level of am I

问题 I am trying to create a simple summary statistics table (min, max, mean, n, etc) that handles both factor variables and continuous variables, even when there is more than one factor variable. I'm trying to produce good looking HTML output, eg stargazer or huxtable output. For a simple reproducible example, I'll use mtcars but change two of the variables to factors, and simplify to three variables. library(tidyverse) library(stargazer) mtcars_df <- mtcars mtcars_df <- mtcars_df %>% mutate(vs =

问题 I have a dataframe in R that looks like the following: a b c condition 1 4 2 acap 2 3 1 acap 2 4 3 acap 5 6 8 ncap 5 7 6 ncap 8 7 6 ncap I am trying to recode the values in columns a, b, and c for condition ncap (and also 2 other conditions not pictured here) while leaving the values for acap alone. The following code works when applied to the first 3 columns. I am trying to figure out how I can apply this only to rows that I specify by condition while keeping everything in the same dataframe