DavisVaughan

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)

DavisVaughan

library(rlang)
library(tibble, warn.conflicts = FALSE)

# A formula for the cars dataset
f <- as.formula("speed ~ dist")
f
#> speed ~ dist
#> <environment: 0x7f8399800d80>

# X

DavisVaughan

# 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) {

DavisVaughan

# 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

DavisVaughan

// [[Rcpp::depends(xtensor)]]

#include <numeric>
#include "xtensor/xmath.hpp"
#include "xtensor-r/rarray.hpp"
#include <Rcpp.h>

using namespace Rcpp;

// [[Rcpp::plugins(cpp14)]]

DavisVaughan

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

DavisVaughan

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

DavisVaughan

``` r
library(odbc)
#> Warning: package 'odbc' was built under R version 3.4.2
library(DBI)

con <- DBI::dbConnect(odbc::odbc(),
                      Driver   = "PostgreSQL ODBC Driver(ANSI)",
                      Server   = "localhost",
                      Database = "postgres",
                      UID      = 'postgres',

DavisVaughan

``` r
library(tibbletime)
library(dplyr)

options(digits.secs = 6)

# 1000 values
ex <- create_series('2013' ~ '2013-01-01 00:00:00.999', period = "1 millisec")

# Random data

DavisVaughan

library(tibbletime)
library(dplyr)
library(zoo)

data(FB)

window <- 6
rolling_mean <- rollify(mean, window = window)

FB_roll <- FB %>%