sbalci

# =======================================
# =     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.

sbalci

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

sbalci

# ttable: a grammar of tables
# https://gist.github.com/leeper/f9cfbe6bd185763762e126a4d8d7c286

# aggregate/summarize

# arrange

# annotation (metadata features)

# theme

sbalci

# 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

sbalci

# https://docs.ropensci.org/charlatan/articles/charlatan.html
# https://github.com/trinker/wakefield
# cat(wakefield::variables(), sep = ",\n")

fakedata <-
  
  wakefield::r_data_frame(
    n = 250,
    
    id,

sbalci

library(survival)

km_fit <- survfit(Surv(time, status) ~ sex, data = lung)

km_fit_summary <- summary(km_fit, times = c(0.5, 1, 2), scale = 365.25)

km_fit_df <- as.data.frame(km_fit_summary[c("strata", "time", "n.risk", "n.event", "surv", "std.err", "lower", "upper")])


km_fit_df %>% 

sbalci

When you use knit_expand it appears that the inclusion of the Rmd is done on the first pass, and then the complete document evaluated. This means that a Rmd block referenced in loop with knit_expand will only evaluate changing variables at their last value.

This can be worked around by passing the literal value of the variable at the time of the knit_expand with {{var}} syntax.

This is documented in the knitr_expand docs, but less clear (to an R noob like me) for embedded documents rather than strings.

sbalci

# Find Packages Used in a Project Using Regular Expressions RegEx

list_of_Rmd_R <- c(
    list.files(path = here::here(),
               pattern = "\\.Rmd|.R$", # find files ending with .Rmd and .R
               full.names = TRUE
    ),
    
    list.files(path = here::here("childRmd"),
               pattern = "\\.Rmd|.R$",

sbalci

How to use Gephi to visualize from Wikidata

I'm a long-time fan of the graph visualization tool Gephi and since Wikimania 2019 I got involved with Wikidata. I was aware of the Gephi plugin "Semantic Web Importer", but when I check it out, I only find old tutorials connecting to DBpedia, not Wikidata:

• "Visualising Related Entries in Wikipedia Using Gephi" by Tony Hirst, 2012-07-03
• "Let’s Play Gephi: Dbpedia, RDF, Sparql and your favorite Actors" by Matthieu Totet, 2015-10-06
• ["Gephi tutorials: Semantic Web Importer" by Matthieu

sbalci

simple_roc <- function(labels, scores){
  labels <- labels[order(scores, decreasing=TRUE)]
  data.frame(TPR=cumsum(labels)/sum(labels), FPR=cumsum(!labels)/sum(!labels), labels)
}