data.table

问题 There are multiple ways to select columns of data.table by using a variable holding the desired column names ( with=FALSE , .. , mget , ...). Is there a consensus which to use (when)? Is one more data.table -y than the others? I could come up with the following arguments: with=FALSE and .. are almost equally fast, while mget is slower .. can't select concatenated column names "on the fly" ( EDIT : current CRAN version 1.12.8 definitely can, I was using an old version, which could not, so this

问题 There are multiple ways to select columns of data.table by using a variable holding the desired column names ( with=FALSE , .. , mget , ...). Is there a consensus which to use (when)? Is one more data.table -y than the others? I could come up with the following arguments: with=FALSE and .. are almost equally fast, while mget is slower .. can't select concatenated column names "on the fly" ( EDIT : current CRAN version 1.12.8 definitely can, I was using an old version, which could not, so this

问题 I have a data-frame like as shown below DF = structure(list(Age_visit = c(48, 48, 48, 49, 49, 77), Date_1 = c("8/6/2169 9:40", "8/6/2169 9:40", "8/6/2169 9:41", "8/6/2169 9:42", "24/7/2169 8:31", "12/9/2169 10:30", "19/6/2237 12:15"), Date_2 = c("NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA"), person_id = c("21", "21", "21", "21", "21", "21", "31" ), enc_id = c("A21BC","A21BC", "A22BC", "A23BC",

问题 I have a data-frame like as shown below DF = structure(list(Age_visit = c(48, 48, 48, 49, 49, 77), Date_1 = c("8/6/2169 9:40", "8/6/2169 9:40", "8/6/2169 9:41", "8/6/2169 9:42", "24/7/2169 8:31", "12/9/2169 10:30", "19/6/2237 12:15"), Date_2 = c("NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA", "NA-NA-NA NA:NA:NA"), person_id = c("21", "21", "21", "21", "21", "21", "31" ), enc_id = c("A21BC","A21BC", "A22BC", "A23BC",

问题 I have a data.table containing some state name abbreviations and county names. I want to get approx. coordinates from ggplot2::map_data('county') for each row. I can do this sequentially with multiple lines of code using := but I would like to make only one function call. Below is what I've tried: Data: library(data.table) library(ggplot2) > dput(dt[1:20, .(state, county, prime_mover)]) structure(list(state = c("AZ", "AZ", "CA", "CA", "CA", "CT", "FL", "IN", "MA", "MA", "MA", "MN", "NJ", "NJ"

问题 I have a data.table containing some state name abbreviations and county names. I want to get approx. coordinates from ggplot2::map_data('county') for each row. I can do this sequentially with multiple lines of code using := but I would like to make only one function call. Below is what I've tried: Data: library(data.table) library(ggplot2) > dput(dt[1:20, .(state, county, prime_mover)]) structure(list(state = c("AZ", "AZ", "CA", "CA", "CA", "CT", "FL", "IN", "MA", "MA", "MA", "MN", "NJ", "NJ"

问题 I have a data.table containing some state name abbreviations and county names. I want to get approx. coordinates from ggplot2::map_data('county') for each row. I can do this sequentially with multiple lines of code using := but I would like to make only one function call. Below is what I've tried: Data: library(data.table) library(ggplot2) > dput(dt[1:20, .(state, county, prime_mover)]) structure(list(state = c("AZ", "AZ", "CA", "CA", "CA", "CT", "FL", "IN", "MA", "MA", "MA", "MN", "NJ", "NJ"

问题 I have an example dataset, garden , as shown below. The real thing is thousands of rows. I also have an example list. productFruit . I want to know the calories of every fruit , considering the usage reported in garden . I basically want to loop through all the rows in my table, check if the usage is recorded in the productFruit list and the return either the calories or one of the following error messages: "usage out of scope" if no usage has been found in the productFruit list "fruit out of

问题 A) Instead of this (where cars <- data.table(cars) ) cars[ , .(`Totals:`=.N), by=speed] I need this strColumnName <- "Totals:" cars [ , strColumnName = .N, by=speed] How to do it? B) Similarly (more general case) - instead of this: cars[ dist > 50, .(`Totals:`=.N, x=dist*100), by=speed] I need this: strFactor <- "dist" cars[ strFactor > 50, .(`Totals:`=.N, x=strFactor*100), by=speed] This question is about GENERAL way of assigning/referencing column name variables in data.table, i.e. in 'j'

问题 Imagine that I have a dataframe or datatable with strings column where one row looks like this: a1; b: b1, b2, b3; c: c1, c2, c3; d: d1, d2, d3, d4 and a look-up table with codes for mapping each of these strings. For example: string code a1 10 b1 20 b2 30 b3 40 c1 50 c2 60 ... I would like to have a mapping function that maps this string to code: 10; b: 20, 30, 40; c: 50, 60, 70; d: 80, 90, 100 I have a column of these strings in data.table/data.frame (more tha 100k) so any quick solution