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| library(stringr) | |
| # I had something like this | |
| bobs <- c("bob.txt", "bob.scn", "bob") | |
| # I want to remove just the strings with "scn" | |
| # Using: https://stackoverflow.com/questions/5556213/regex-to-match-everything-except-the-given-words-which-may-include-hyphens-dash | |
| str_subset(bobs, "^(?:(?!scn).)*$") | |
| #> [1] "bob.txt" "bob" |
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| library(DBI) | |
| library(dbplyr) | |
| suppressPackageStartupMessages(library(dplyr)) | |
| #> Warning: package 'dplyr' was built under R version 3.4.1 | |
| options(tibble.width = Inf) | |
| cn <- dbConnect(odbc::odbc(), dsn = "access-odbc") | |
| #dbListTables(cn) |
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| library(DBI) | |
| library(dbplyr) | |
| library(dplyr, warn.conflicts = FALSE) | |
| # This is an Access connection | |
| cn <- dbConnect(odbc::odbc(), dsn = "dbplyr-testing") | |
| # Connect to the test table | |
| test_tbl <- tbl(cn, "test-1") |
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| db_write_table.ACCESS <- function(con, table, types, values, | |
| temporary = FALSE, ...) { | |
| db_create_table(con, table, types, temporary = temporary) | |
| # Convert factors to strings | |
| is_factor <- vapply(values, is.factor, logical(1)) | |
| values[is_factor] <- lapply(values[is_factor], as.character) | |
| # Encode special characters in strings |
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| library(rlang) | |
| library(tibble, warn.conflicts = FALSE) | |
| # A formula for the cars dataset | |
| f <- as.formula("speed ~ dist") | |
| f | |
| #> speed ~ dist | |
| #> <environment: 0x7f8399800d80> | |
| # X |
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| # Just an example "vector of means" | |
| vec_of_means <- c(6.4, 2, 3.3, 4.6, 5, 8) | |
| n <- length(vec_of_means) | |
| # Loops! | |
| for(i in 1:(n-1)) { | |
| print(paste0("Hello i: ", vec_of_means[i], " ===")) | |
| for(j in (i+1):n) { |
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| # devtools::install_github("business-science/tibbletime") | |
| library(tibbletime) | |
| #> | |
| #> Attaching package: 'tibbletime' | |
| #> The following object is masked from 'package:stats': | |
| #> | |
| #> filter | |
| library(tidyverse) | |
| #> Loading tidyverse: ggplot2 | |
| #> Loading tidyverse: tibble |
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| // [[Rcpp::depends(xtensor)]] | |
| #include <numeric> | |
| #include "xtensor/xmath.hpp" | |
| #include "xtensor-r/rarray.hpp" | |
| #include <Rcpp.h> | |
| using namespace Rcpp; | |
| // [[Rcpp::plugins(cpp14)]] |
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| suppressPackageStartupMessages(library(tibbletime)) | |
| suppressPackageStartupMessages(library(tidyverse)) | |
| data(FB) | |
| # Create the column names | |
| col_names <- map_chr(2:10, ~paste0("adjusted_", .x)) | |
| # Creating the rolling functions and assign them names | |
| rollers <- map(2:10, ~rollify(mean, window = .x)) %>% |
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| suppressPackageStartupMessages(library(tibbletime)) | |
| suppressPackageStartupMessages(library(dplyr)) | |
| suppressPackageStartupMessages(library(purrr)) | |
| # Create a tibble of event dates, ~100k | |
| # 2013-01-01 to the end of the year by 5 minutes | |
| event_dates <- create_series(~2013, 5~M, force_class = "POSIXct") | |
| event_dates | |
| #> # A time tibble: 105,120 x 1 |
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