| if (!require("pacman")) install.packages("pacman") | |
| pacman::p_load(dplyr, tidyr, wakefield) | |
| set.seed(10) | |
| dat <- r_data_frame(n = 10000, | |
| race, | |
| age, | |
| sex | |
| ) |
People
 :bowtie: |
😄 :smile: |
😆 :laughing: |
|---|---|---|
😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
| # Ruby is our language as asciidoctor is a ruby gem. | |
| lang: ruby | |
| before_install: | |
| - sudo apt-get install pandoc | |
| - gem install asciidoctor | |
| script: | |
| - make | |
| after_success: | |
| - .travis/push.sh | |
| env: |
| # ======================================= | |
| # = Enhancements to data tidying = | |
| # = Hadley Wickham = | |
| # = https://rstd.io/tidyhancements-2019 = | |
| # ======================================= | |
| # What is tidy data? ---------------------------------------------------------- | |
| # 1. Each column is a variable. | |
| # 2. Each row is an observation. | |
| # 3. Each cell is a value. |
| git clone https://github.com/coursera-dl/coursera-dl | |
| cd coursera-dl | |
| pip3 install -r requirements.txt | |
| ./coursera-dl -u <Email-id> -p <Password> --subtitle-language en raspberry-pi-interface |
| # ttable: a grammar of tables | |
| # https://gist.github.com/leeper/f9cfbe6bd185763762e126a4d8d7c286 | |
| # aggregate/summarize | |
| # arrange | |
| # annotation (metadata features) | |
| # theme |
| # List the jpg files in the folder | |
| old_files <- list.files("C:/ImageTest", pattern = "*.JPG", full.names = TRUE) | |
| old_files | |
| # Create vector of new files | |
| new_files <- paste0("C:/NewFiles/file_",1:length(old_files),".JPG") | |
| new_files |
| simple_roc <- function(labels, scores){ | |
| labels <- labels[order(scores, decreasing=TRUE)] | |
| data.frame(TPR=cumsum(labels)/sum(labels), FPR=cumsum(!labels)/sum(!labels), labels) | |
| } |
| library("shiny") | |
| library("foreign") |
| # Shamlessly stolen from: | |
| # https://www.r-bloggers.com/how-to-remove-all-user-installed-packages-in-r/ | |
| # create a list of all installed packages | |
| ip <- as.data.frame(installed.packages()) | |
| head(ip) | |
| # if you use MRO, make sure that no packages in this library will be removed | |
| ip <- subset(ip, !grepl("MRO", ip$LibPath)) | |
| # we don't want to remove base or recommended packages either\ | |
| ip <- ip[!(ip[,"Priority"] %in% c("base", "recommended")),] |