matt-dray

library(ggplot2)  # for plotting
library(gridExtra)  # for arranging plots

# Create example dataframe
df <- data.frame(x = letters[1:10]
                 , y1 = sample(1:100, 10)
                 , y2 = sample(1:100, 10)
                 , y3 = sample(1:100, 10)
                 , y4 = sample(1:100, 10)
                 , y5 = sample(1:100, 10)

matt-dray

# purpose: loop through plots of specified column pairs of a dataframe
# don't want to compare all possible permutations
# also avoids nested loop of x and y

library(tidyverse)  # for tibble and ggplot

# generate example dataframe

test_data <- tibble::tibble(x1 = rnorm(100)
                            , x2 = rnorm(100)

matt-dray

library(tidyverse)
library(stringr)

# list files in directory (in the format "x_y_z.csv")
list_files <- list.files("file/path")

for (i in seq_along(1:length(list_files))) {
  
  # read the data
  

matt-dray

# Basic googlesheets functions
# Jan 2018
# https://github.com/jennybc/googlesheets
# Browser sign-in required on first function execution

# 1. Load package ----

#install.packages(googlesheets)
library(googlesheets)

matt-dray

---
title: "Title"
subtitle: "Subtitle"
author: "Name"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
  html_document:
    theme: cerulean
    highlight: tango
    number_sections: yes

matt-dray

Keybase proof

I hereby claim:

• I am matt-dray on github.
• I am mattdray (https://keybase.io/mattdray) on keybase.
• I have a public key ASD-cOiAVRNCc2XIcTt3U-nwNwA32uzNhPZPmHDiBDH8pAo

To claim this, I am signing this object:

matt-dray

# Function to automate generation of RDS, simple CSV and plot using rtweet
# Matt Dray
# March 2018

# Purpose: create an RDS, simplified CSV and plot of tweets containing search term
# from rtweet::get_tweets function and save to to folder with unique descriptive
# name related to search term. Assumes you have an 'output' folder in your home
# directory to store these files. Assumes you've already sorted out a twitter
# token as per http://rtweet.info/articles/auth.html

matt-dray

# 1. Fake dataset

df <- data.frame(id = 1:1000, value = sample(10000:50000, 1000)) 

# 2. Histogram object for accessing binwidths

hist_df <- hist(
  df$value,  # column of data to be binned
  (50000-10000)/500  # bins of width 500 from 10k to 50k
)

matt-dray

# Approved colour palette for DfE
# Convert to hex the RGB values provided by the dept
# Matt Dray
# May 2018

# the main need is for plotting stats in publications
# inspiration from https://github.com/ukgovdatascience/govstyle 
# this may eventually be added to the dfeR package

# function for converting from RGB to hex

matt-dray

# The Rcrawler package for website crawling
# Matt Dray
# May 2018

# the need: extract hyperlinks containing certain string
# this code hasn't actually been tested

# install.packages("Rcrawler")
library(Rcrawler)