With the tidyquant Matt Dancho & David Curry Business Science Learning Lab Shiny Finance App (Excel in R) 

Learning Lab Structure ● Presentation (20 min) ● Demo’s (30 min) ● Pro-Tips (15 mins) 

Shiny API Series ● Lab 28 - Shiny Real Estate App ○ Zillow API ● Lab 29 - Shiny Oil & Gas App ○ Quandl API ● Lab 30 - Shiny Finance App ○ Tidyquant API ● Lab 31 - Shiny Marketing App ○ Google Analytics API ● Lab 32 - Shiny Twitter App ○ Twitter API 

Learning Labs PRO Every 2-Weeks 1-Hour Course Recordings + Code + Slack $19/month university.business-science.io Lab 30 - Shiny API Series, Pt 3 Shiny + Finance + Excel + R + Tidyquant Lab 29 - Shiny API Series, Pt 2 Shiny + Quandl + ARIMA for Energy Forecasting Lab 28 - Shiny API Series, Pt 1 Shiny + Zillow for Real Estate Lab 27 - Marketing Series, Pt 4 Google Trends Automation with Shiny Lab 26 - Marketing Series, Pt 3 Customer Journey with Machine Learning Lab 25 - Marketing Series, Pt 2 Attribution with ChannelAttribution Lab 24 - Marketing Series, Pt 1 A/B Testing with Infer Lab 23 - SQL Series SQL with BigQuery & Conversion Funnel 

Agenda ● Demo ○ Shiny App that analyzes stock returns ○ Drag N’ Drop Pivot Table Interface ● Why a Drag N’ Drop Finance App? ○ Helping to summarize data quickly ● Why Tidyquant 1.0.0? ○ Brief history ○ Why am I bringing Excel to R??? ● 30-Min Demo ○ Tidyquant API ○ VLOOKUP in R ○ Pivot Table in R ○ Summarizing by Time ○ NEW Excel Functions ○ Shiny Drag N’ Drop Finance App [LL PRO] ● Pro-Tips & Learning Guide 

Demo 

Why make a Drag N’ Drop App? Finance 

Excel is the Number 1 Analytics Tool Excel has powerful features Easy Pivot Tables Calculations 

Excel is the Number 1 Analytics Tool Excel has issues Not reproducible 2. Prone to Errors Leads to major disasters: ● ● ● much higher risk 

API + ARIMA + Shiny How an app can help Code can be independently validated Errors can be mitigated Money at desired risk Excel in R (NEW with tidyquant 1.0.0) 

Why bring Excel to R? Lowering the barrier to entry into R 

Brief History of tidyquant: https://business-science.github.io/tidyquant Start Finish 2017 Launched 0.1.0 Get Financial Data in Data Frames Apply Financial Analysis functions to tidyverse Quantmod, TTR, xts, zoo 2018-19 Releases 0.2.0 - 0.5.9 Portfolio Analysis via PerformanceAnalytics More Financial API’s ggplot2 themes, scales, geoms for business/finance 2020 NEW 1.0.0 R for Excel Users Pivot Tables VLOOKUPs Sum-Ifs 100+ Excel Functions Not just for Quants. Now Business Analysts 

Why Excel in R via Tidyquant? My 2 goals for 2020 Goal 1 Help Excel Users transition to R Goal 2 Help R Users learn Shiny Apps Data Science & Machine Learning, Fewer Errors, Bigger Data Businesses Need ML + Apps 

2 Goals to Lower the Barrier Goal 1 Help Excel Users transition to R Goal 2 Help R Users learn Shiny Apps 

Businesses can’t use these No 

Businesses need these 

Excel Functionality & Shiny Workflow 

Workflow Step-By-Step Start Finish 1 2 3 API Connect to Yahoo Finance, Tiingo, Quandl, & Alpha Vantage Excel in R Demo tidyquant’s New Features! Shiny App that drag & drop interface 

Drag N’ Drop App 

30-Min Demo Let’s do this! 

PRO-TIPS Yeahhhhhh! 

Pro-Tip #1: Give Businesses Apps Apps are what businesses need Businesses can’t scale excel Businesses can scale apps Apps are manageable 

Pro-Tip #1: Give Businesses Apps Apps are manageable Rev 1.0 Rev 6.0 Rev 4.0 Rev 6.0 Excel is not manageable 

Pro-Tip #2: Leverage Shiny by integrating your analysis Shiny is production for your analysis Shiny packages up: ● Machine Learning ● Visualizations ● Interactivity Use Shiny to help decision making 

Pro-Tip #3: Say no to Excel No 

Pro-Tip #3: ...and say YES to apps. Yes apps.business-science.io 

Advanced Visualization Advanced Data Wrangling Advanced Functional Programming & Modeling Advanced Machine Learning Visualization Data Cleaning & Manipulation Data Science Algorithms & Iteration Business Reporting Business Analysis with R (DS4B 101-R) Data Science For Business with R (DS4B 201-R) Web Apps & Shiny Developer (DS4B 102-R + DS4B 202A-R) Web Apps Data Science Foundations 7 Weeks Machine Learning & Business Consulting 10 Weeks Web Application Development 12 Weeks -TRACK Project-Based Courses with Business Application Business Science University R-Track 

Key Benefits - Fundamentals - Weeks 1-5 (25 hours of Video Lessons) - Data Manipulation (dplyr) - Time series (lubridate) - Text (stringr) - Categorical (forcats) - Visualization (ggplot2) - Programming & Iteration (purrr) - 3 Challenges - Machine Learning - Week 6 (8 hours of Video Lessons) - Clustering (3 hours) - Regression (5 hours) - 2 Challenges - Learn Business Reporting - Week 7 - RMarkdown & plotly - 2 Project Reports: 1. Product Pricing Algo 2. Customer Segmentation Visualization Data Cleaning & Manipulation Business Reporting Business Analysis with R (DS4B 101-R) Data Science Foundations 7 Weeks Data Science Algorithms & Iteration 

Key Benefits Understanding the Problem & Preparing Data - Weeks 1-4 - Project Setup & Framework - Business Understanding / Sizing Problem - Tidy Evaluation - rlang - EDA - Exploring Data -GGally, skimr - Data Preparation - recipes - Correlation Analysis - 3 Challenges Machine Learning - Weeks 5, 6, 7 - H2O AutoML - Modeling Churn - ML Performance - LIME Feature Explanation Return-On-Investment - Weeks 7, 8, 9 - Expected Value Framework - Threshold Optimization - Sensitivity Analysis - Recommendation Algorithm Data Science For Business (DS4B 201-R) Machine Learning & Business Consulting 10 Weeks Advanced Visualization Advanced Data Wrangling Advanced Functional Programming & Modeling Advanced Data Science End-to-End Churn Project 

Key Benefits Learn Shiny & Flexdashboard - Build Applications - Learn Reactive Programming - Integrate Machine Learning App #1: Predictive Pricing App - Model Product Portfolio - XGBoost Pricing Prediction - Generate new products instantly App #2: Sales Dashboard with Demand Forecasting - Model Demand History - Segment Forecasts by Product & Customer - XGBoost Time Series Forecast - Generate new forecasts instantly Shiny Apps for Business (DS4B 102-R) Web Application Development 4 Weeks Web Apps Machine Learning 

Key Benefits Frontend + Backend + Production Deployment Frontend for Shiny - Bootstrap Backend for Shiny - MongoDB Atlas Cloud - Dynamic UI - User Authentication & Security Production Deployment - AWS - EC2 Server - SSL & HTTPS Encryption Shiny Apps for Business (DS4B 202A-R) Web Application Development 6 Weeks 

-TRACK BUNDLE 15% OFF PROMO Code: learninglabs $127/mo Limited Time 

Career acceleration awaits university.business-science.io