stephlocke

# Load R packages for use
library("dplyr")
library("recipes")
library("rsample")
library("broom")
library("jsonlite")
library("sessioninfo")

# Sample data
sm_iris = initial_split(iris)

stephlocke

let
 iterations = 10,          // Number of iterations
 url =
  "https://api.hubapi.com/deals/v1/deal/paged?" & "hapikey=demo" & "&includeAssociations=true" & "&limit=1" & "&properties=dealname" & "&propertiesWithHistory=true"
 ,
 FnGetOnePage =
  (url) as record =>
   let
    Source = Json.Document(Web.Contents(url)),
    data = try Source[deals] otherwise null,

stephlocke

library(rtweet) #rtweet API creds should already be set up
library(stringi)
library(dplyr)

friends = get_friends(user="stephlocke")
followers = get_followers("stephlocke")
tweeps_id = distinct(bind_rows(friends, followers))
tweeps_info = lookup_users(tweeps_id$user_id)

# A regex for a visit to Durham

stephlocke

Ethical data science

Intro

Who I am

Purpose / Agenda

Problems caused

Facial recognition

Justice system

Access to finance

Ethical obligation

stephlocke

title	author	date
Working with Git	Steph Locke	15 September 2018

Source control fundamentals

Source control concepts

stephlocke

[
  {
    "userId": 1,
    "id": 1,
    "title": "Analytics",
    "body": "quia et suscipit\nsuscipit recusandae consequuntur expedita et cum\nreprehenderit molestiae ut ut quas totam\nnostrum rerum est autem sunt rem eveniet architecto"
  },
  {
    "userId": 1,
    "id": 2,

stephlocke

## ----message=FALSE-------------------------------------------------------
library(tabulizer)
library(tidyverse)
library(zoo)
library(tidytext)

## ------------------------------------------------------------------------
"http://www.pass.org/Portals/0/Governance%202017/2018%20Budget.pdf?ver=2017-10-26-171625-747&timestamp=1509063392150" %>%
  tabulizer::extract_text() ->
  rawtxt

stephlocke

---
title: "sample"
output:
  md_document:
    variant: markdown_github
preserve_yaml: true
always_allow_html: yes
---

```{r setup, include = FALSE, message = FALSE, warning = FALSE, error = FALSE}

stephlocke

library(tidyverse)
library(rvest)

"https://en.wikipedia.org/wiki/List_of_superhero_debuts" %>%
  read_html() %>%
  html_nodes(xpath = "//*[@id='mw-content-text']/div/table") %>%
  map(html_table, fill = TRUE) %>%
  map_df( ~ mutate(., `Year Debuted` = as.character(`Year Debuted`))) %>%
  mutate(`Char_Team` = coalesce(`Character / Team / Series`, `Character / Team`)) %>%
  select(Char_Team, Year_Debut = `Year Debuted`) %>%

stephlocke

Precons

Practical R for everyone

This hands-on one-day training takes you through the following topics – fundamentals of R, R for ETL, producing reports, and doing data science. Starting with some simple data manipulation, we’ll quickly progress to tools that can make an immediate impact in your day job.

• For ETL, we’ll look at ways to import and export data, transform it, and apply data quality checks along the way.
• For producing reports we’ll see how we can build web reports, PDFs, and interactive dashboards.
• For data science, we’ll look at how R supports you along the process.

By the end of the day, you’ll know some R (including some advanced stuff!) that you can add to your toolbelt.