r

问题 I have a data set containing the following date, along with several others 03/12/2017 02:17:13 I want to put the whole data set into a data table, so I used read_csv and as.data.table to create DT which contained the date/time information in date. Next I used DT[, date := as.POSIXct(date, format = "%m/%d/%Y %H:%M:%S")] Everything looked fine except I had some NA values where the original data had dates. The following expression returns an NA as.POSIXct("03/12/2017 02:17:13", format = "%m/%d/

问题 I have the following tibble: library(tidyverse) df <- tibble::tribble( ~gene, ~colB, ~colC, "a", 1, 2, "b", 2, 3, "c", 3, 4, "d", 1, 1 ) df #> # A tibble: 4 x 3 #> gene colB colC #> <chr> <dbl> <dbl> #> 1 a 1 2 #> 2 b 2 3 #> 3 c 3 4 #> 4 d 1 1 What I want to do is to filter every columns after gene column for values greater or equal 2 (>=2). Resulting in this: gene, colB, colC a NA 2 b 2 3 c 3 4 How can I achieve that? The number of columns after genes actually is more than just 2. 回答1: One

问题 I have the following tibble: library(tidyverse) df <- tibble::tribble( ~gene, ~colB, ~colC, "a", 1, 2, "b", 2, 3, "c", 3, 4, "d", 1, 1 ) df #> # A tibble: 4 x 3 #> gene colB colC #> <chr> <dbl> <dbl> #> 1 a 1 2 #> 2 b 2 3 #> 3 c 3 4 #> 4 d 1 1 What I want to do is to filter every columns after gene column for values greater or equal 2 (>=2). Resulting in this: gene, colB, colC a NA 2 b 2 3 c 3 4 How can I achieve that? The number of columns after genes actually is more than just 2. 回答1: One

问题 Src=as.factor(c("nc","us","us","nc","nc","ci","nn","pr","nc","nc","ak","ak","ak","ak","ci","hv","ak","ci","nc","nc")) Version = as.factor(c(0,4,7,0,0,0,9,0,0,0,1,1,1,1,0,2,1,0,0,0)) table(Src,Version) Output: Version Src 0 1 2 4 7 9 ak 0 5 0 0 0 0 ci 3 0 0 0 0 0 hv 0 0 1 0 0 0 nc 7 0 0 0 0 0 nn 0 0 0 0 0 1 pr 1 0 0 0 0 0 us 0 0 0 1 1 0 Instead of showing the counted numbers, can I instead show relative frequencies? 回答1: Sure. You can use prop.table() to that effect: prop.table(table(Src,

问题 When I run (what I think is the same regression) in R and in Julia I get very different results. I think this is because the IV regression is using an indicator variable to instrument for another indicator variable but I can't figure out if I am doing something else wrong. I have tried several different methods, but the data starts like this: rc D tau May_ret Jun_ret Jul_ret Aug_ret Sep_ret 1 -43 0 0 0.04529617 0.02106667 0.009868421 0.032573290 0.010473186 2 -19 0 0 0.01973333 0.05752213 -0

问题 I have spent a couple of hours researching this but I am getting nowhere unfortunately. I am trying to get a subset of data by using sqldf to query a data frame, result. This is the structure of result: > str(result) 'data.frame': 316125 obs. of 6 variables: $ ID : int 1 2 3 4 5 6 7 8 9 10 ... $ dt : Date, format: "1999-12-31" "1999-12-31" "1999-12-31" "1999-12-31" ... $ Ticker: chr "0111145D US" "0113357D US" "0202445Q US" "0203524D US" ... $ px : num 32.5 20.6 34.2 21.4 11 ... $ High : num

问题 When making shiny apps I often struggle with how to arrange plots and text outputs on the page for the user. So, I like to try an make it possible for a user to select which output to display. For instance, the user may be able to display 3 graphs and 2 chunks of text but may only want to display the first graph and one chunk of text. I can usually accomplish this using if statements inside of render functions. But, I have found shiny will still add white space even if...the user does not

问题 I have developed an app which takes an .wav file as input and plays it. However it seems to be not working. On the other hand, if the audio file is placed in /www folder and path name is given, it is playing fine. What am I doing wrong ? app.R library( shinydashboard ) ui = source( file.path( "ui", "ui.R" ), local = T )$value #..... ui for ocr server = function( input, output, session ){ #..... Include server logic for each tab ..... source( file.path( "server", "server.R" ), local = T )

问题 This is a follow-up on this question. I am trying to write my own geoms with custom parameters. My question is how to use ellipsis (...) to pass extra arguments. The following example code works as expected: draw_panel_func <- function(data, panel_params, coord, showpoints=FALSE) { print(showpoints) if(showpoints) { coords <- coord$transform(data, panel_params) grid::pointsGrob(coords$x, coords$y) } else { zeroGrob() } } ## definition of the new geom. setup_data inserts the parameter ## into

问题 I am trying to understand the different between two forecasting package forecast and fable , as the two editions of the same book (second edition and third edition seems to imply that the two packages are equivalent. library(dplyr) raw <- c(44.4082519001086, 47.1074380165289, 43.5633367662204, 43.1003584229391, 42.5828970331588, 38.3217993079585, 38.5751520417029) # raw <- c(raw,rev(raw)) forecast.df <- ts(raw) forecast::autoplot(forecast.df) + forecast::autolayer(forecast::holt(forecast.df