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)) %>%

seankross

library(aws.polly)

jeff <- synthesize("Hello, I am Jeff Leek. Take a look at this chart on my left.", "Joey")
plot(jeff@left, type = "l")

seankross

library(dplyr)

x <- mtcars %>%
  group_by(cyl) %>%
  sample_frac(replace = TRUE)

mtcars %>%
  group_by(cyl) %>%
  summarise(sum = n())

seankross

library(gh)
library(jsonlite)
library(purrr)
library(tibble)
library(dplyr)
library(shiny)
library(plotly)

# You can create a GitHub PAT here: https://github.com/settings/tokens
Sys.setenv(GITHUB_PAT = "")

seankross

library(shiny)
library(dplyr)

delete_last_row <- function(df){
  df[1:(nrow(df) - 1),]
}

ui <- basicPage(
  plotOutput("plot1", click = "plot_click", dblclick = "plot_dblclick")
)

seankross

library(dplyr)

mtcars %>%
  group_by(cyl) %>%
  summarize(mean(disp))

# # A tibble: 3 × 2
# cyl `mean(disp)`
# <dbl>        <dbl>
#   1     4     105.1364

seankross

library(dplyr)

mtcars %>%
  group_by(cyl) %>%
  summarize(mean(disp))

# # A tibble: 3 × 2
# cyl `mean(disp)`
# <dbl>        <dbl>
#   1     4     105.1364

seankross

library(dplyr)

mtcars %>%
  group_by(cyl) %>%
  summarize(mean(disp))

# # A tibble: 3 × 2
# cyl `mean(disp)`
# <dbl>        <dbl>
#   1     4     105.1364