seankross

function colors = pal_hue(n, s, v)
    % Generates a palette of n evenly spaced colors with default settings
    % similar to R's scales::pal_hue().
    % s is the saturation (default 0.75), v is the value (brightness, default 0.95).
    % The hue component varies from 0 to 1.
    
    if nargin < 2
        s = 0.75; % Default saturation
    end
    if nargin < 3

seankross

Make sure homebrew is all up to date.

Make sure you have venv working, I think it just comes with python3.

Start a brand new RStudio project and open it in RStudio.

In the terminal:

python -m venv .venv

seankross

From "Jazz" by Toni Morrison

It's nice when grown people whisper to each other under the covers. Their 
ecstasy is more leaf-sigh than bray and the body is the vehicle, not the point. 
They reach, grown people, for something beyond, way beyond and way, way down 
underneath tissue. They are remembering while they whisper the carnival dolls 
they won and the Baltimore boats they never sailed on. The pears they let hang 
on the limb because if they plucked them, they would be gone from there and who 
else would see that ripeness if they took it away for themselves? How could 
anybody passing by see them and imagine for themselves what the flavor would 

seankross

# You can find pch values for shapes here: 
# https://cdn-images-1.medium.com/max/1600/1*0QEVFHrgqmkVsCVCQceh6w.jpeg

data <- data.frame(
  Name = c("Ohio State", "Purdue", "Indiana", "Wisconsin", "Nebreaska"),
  Min =   c(0.37, 0.25, 0.13, 0.22, 0.28),
  Max =   c(0.88, 0.57, 0.68, 0.77, 0.63),
  Value = c(0.51, 0.32, 0.24, 0.65, 0.57),
  Pch = c(1, 2, 5, 6, 22),
  stringsAsFactors = FALSE

seankross

berkeley <- as.data.frame(UCBAdmissions)
model <- glm(Admit ~ Gender + Dept + Freq, data = berkeley, family = "binomial")

# Base R

model_summary <- summary(model)
model_summary$coefficients[,4]

# Or become one of the cool kids

seankross

library(shiny)
library(miniUI)

ui <- miniPage(
  gadgetTitleBar("My Gadget"),
  miniContentPanel(
    ## Your UI items go here.
  )
)

seankross

library(dplyr)

c(2, 5, 6) %>% sum()

cars_i_want <- mtcars %>%
  filter(mpg > 20) %>%
  filter(cyl == 4) %>%
  arrange(hp)

mtcars %>% 

seankross

steph <- structure(c(148L, 65L, 198L, 53L, 16L, 2004L), .Dim = c(3L, 2L
), .Dimnames = structure(list(c("EatNoTrans", "Request", "Stealing"
), c("0", "1")), .Names = c("", "")), class = "table")

chisq_steph <- chisq.test(steph)

chisq_steph$expected

seankross

#!/bin/bash

# Bash script to install latest version of ffmpeg and its dependencies on Ubuntu 12.04 or 14.04
# Inspired from https://gist.github.com/faleev/3435377

# Remove any existing packages:
sudo apt-get -y remove ffmpeg x264 libav-tools libvpx-dev libx264-dev

# Get the dependencies (Ubuntu Server or headless users):
sudo apt-get update

seankross

library(dplyr)
library(purrr)

set.seed(2017-06-27)

# Imagine this function gives us measurements from nature
data_generator <- function(n = 500){
  data_frame(var1 = rnorm(500)) %>%
    mutate(var2 = var1 + rnorm(500)) %>%
    mutate(var3 = var1 * var2 + rnorm(500)) %>%