This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Prior to the tutorial make sure that the script below runs without error on your R installation. | |
# You first need to install the follwoing packages: | |
# install.packages(c("rstanarm", "prophet", "CausalImpact")) | |
library(rstanarm) | |
library(prophet) | |
library(CausalImpact) | |
# This will test that rstanarm works | |
# Don't be alarmed if you get a warning about "divergent transitions " |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# A barely tested R script that takes a backgammon match in any format | |
# gnubg can read, analyzes the match and returns a data frame with the analysis | |
# It requires that gnubg is readily available on the command line. | |
library(tidyverse) | |
library(jsonlite) | |
library(glue) | |
analyze_bg_match <- function(match_fname, match_format = "auto") { | |
gnubg_analysis_fname = tempfile() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
date | group | n_purchases | |
---|---|---|---|
2017-05-01 | 0 | 124 | |
2017-05-02 | 0 | 95 | |
2017-05-03 | 0 | 147 | |
2017-05-04 | 0 | 116 | |
2017-05-05 | 0 | 219 | |
2017-05-06 | 0 | 248 | |
2017-05-07 | 0 | 132 | |
2017-05-08 | 0 | 110 | |
2017-05-09 | 0 | 114 |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
date | births | deaths | |
---|---|---|---|
1841-01-01 | 254 | 37 | |
1841-02-01 | 239 | 18 | |
1841-03-01 | 277 | 12 | |
1841-04-01 | 255 | 4 | |
1841-05-01 | 255 | 2 | |
1841-06-01 | 200 | 10 | |
1841-07-01 | 190 | 16 | |
1841-08-01 | 222 | 3 | |
1841-09-01 | 213 | 4 |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
year | births | deaths | clinic | |
---|---|---|---|---|
1841 | 3036 | 237 | clinic 1 | |
1842 | 3287 | 518 | clinic 1 | |
1843 | 3060 | 274 | clinic 1 | |
1844 | 3157 | 260 | clinic 1 | |
1845 | 3492 | 241 | clinic 1 | |
1846 | 4010 | 459 | clinic 1 | |
1841 | 2442 | 86 | clinic 2 | |
1842 | 2659 | 202 | clinic 2 | |
1843 | 2739 | 164 | clinic 2 |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
library(tidyverse) | |
library(purrr) | |
library(rstan) | |
### Defining the data ### | |
######################### | |
bumblebees <- c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, | |
1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, | |
0, 0, 1, 0, 0, 0, 0, 0, 0) | |
toddler_steps <- c(26, 16, 37, 101, 12, 122, 90, 55, 56, 39, 55, 15, 45, 8) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# fuzzycolor() takes a vector of color names and matches it against the | |
# xkcdcolors list of color names using edit distance. fuzzycolor() always | |
# returns a vector of hex color strings, perhaps the ones you wanted... | |
fuzzycolor <- function(color_names) { | |
library(xkcdcolors) | |
names_distance <- adist(color_names, xcolors(), ignore.case = TRUE, partial = TRUE) | |
xkcd_colors <- xcolors()[ apply(names_distance, 1, which.min) ] | |
hex_colors <- name2color(xkcd_colors) | |
names(hex_colors) <- xkcd_colors | |
hex_colors |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Prior to the tutorial make sure that the script below runs without error on your python installation. | |
# What you need is a working installation of Stan: http://mc-stan.org/ . | |
# For installation instructions, see here: | |
# http://mc-stan.org/interfaces/pystan.html | |
# After installation you should be able to run this script which should output | |
# some summary statistics and some pretty plots, :) | |
# Fitting a simple binomial model using Stan |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Prior to the tutorial make sure that the script below runs without error on your R installation. | |
# What you need is a working installation of Stan: http://mc-stan.org/ . | |
# For installation instructions, see here: | |
# https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started | |
# After installation you should be able to run this script which should output | |
# some summary statistics and some pretty plots, :) | |
# Generating some fake data | |
set.seed(123) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
### An example of building a TensorFlow model from R using rPython ### | |
# For this script you need to | |
# 1. Have python 2.7 installed. | |
# 2. Install the rPython package in R. | |
# 3. Install Google's TensorFlow library as per these instructions: | |
# http://www.tensorflow.org/get_started/os_setup.md#binary_installation | |
### Here is how to setup and run a trivial TensorFlow model ### | |
# Load TensorFlow (I couldn't get this to work without setting sys.argv... ) |