| library(tidyverse) | |
| library(lubridate) | |
| library(leaflet) | |
| # https://www.fakenamegenerator.com/order.php | |
| # go there to generate fake addresses, don't forget to select to include longitude and latitude | |
| addresses <- read_csv("FakeNameGenerator.com_f201506b.csv") | |
| addresses <- addresses %>% mutate(Birthday = mdy(Birthday), |
| library(tidyverse) | |
| library(scales) | |
| scrapy_stocks <- function(stock){ | |
| if ("rvest" %in% installed.packages()) { | |
| library(rvest) | |
| }else{ | |
| install.packages("rvest") | |
| library(rvest) | |
| } |
| # to install the latest version 0.53 of Hugo on Ubuntu: | |
| # releases are here: https://github.com/gohugoio/hugo/releases | |
| export VER="0.55.5" | |
| wget https://github.com/gohugoio/hugo/releases/download/v0.55.5/hugo_${VER}_Linux-64bit.deb | |
| sudo dpkg -i hugo_${VER}_Linux-64bit.deb | |
| # check if right version is installed | |
| hugo version | |
| # make a new website (don't do that if you already have one) |
| library(tidyverse) | |
| library(lubridate) | |
| days <- tibble(date = seq(date("2018-01-01"), by = "days", length.out = 730)) %>% | |
| mutate(day = weekdays(date)) | |
| hours <- tibble(daytype = c("weekday", "weekday", "weekday", "weekday", "weekday", "weekend"), | |
| time_from = c("00:00", "08:00", "12:00", "13:00", "17:00", "00:00" ), | |
| time_to = c("08:00", "12:00", "13:00", "17:00", "23:59", "23:59" ), | |
| state = c("closed", "open", "closed", "open", "closed", "closed")) |
Compile all models first. There's a bash for this. After that, the models are in the home directory:
cd ~/inference_engine_samples_build/intel64/Release
Weights are in a subfolder of the installation directory:
| library(tidyverse) | |
| localurl <- function(document, path = ""){ | |
| path <- str_remove_all(path, "/$|^/") | |
| document <- str_remove_all(document, "/$|^/") | |
| path <- file.path(path, document) %>% | |
| str_remove_all("/$|^/") | |
| document <- last(str_split(path, pattern = "/", simplify = T)) |
| library(shiny) | |
| library(tidyverse) | |
| # data <- readRDS("persistent_data/data.RDS") | |
| data <- as_tibble(mtcars) %>% head() | |
| ui <- fluidPage( | |
| tableOutput("mytable"), | |
| actionButton("go", "filter it"), | |
| actionButton("save", "save it") |
| library(tidyverse) | |
| library(ggplot2) | |
| periods <- 10 | |
| trend <- 0 | |
| vola <- 0.1 | |
| leverage <- 2 |
| library(shiny) | |
| library(shinyWidgets) | |
| library(tidyverse) | |
| # read persistent data or create a new file if it does not exist yet | |
| if ("favs.csv" %in% list.files()) { | |
| favs <- read_file("favs.csv") %>% | |
| strsplit(", ") %>% | |
| .[[1]] %>% | |
| as.numeric() %>% |