Case Study I

This is a case study that allows you a glimpse into the life of a Data Analyst. The project isn’t glamorous, there are no machine learning algorithms but it reflects what a Data Analyst does most of the time. The tools we learned in the previous chapter along with some new one’s will help us prepare the analysis for an RMarkdown or Shiny App Presentation.

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Case Study I

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Task List


We will cover the following tasks in 44 minutes:


Stripping Out Data

In this chapter we’re going to remove data the old fashion way using Base R. Come in and see how to do this and also to keep up with the lesson.

Stripping Out Data

Introduction

In this section we’re going to look at the Big Picture. What are we going to do to the data and why.

Introduction

Lubridate

Finally. I told you in Chapter 2 we would do Lubridate. Better than late than ever. I’ll show you a couple useful functions within the package.

Lubridate

Tables and Branches

We’re going to do some analysis using our old dplyr tool set. We’re going to group by Branch and then do some analysis to see which branches are not living up to the others.

Tables and Branches

Final Thoughts

Final Thoughts

Colnames

Sometimes Data doesn’t come in with Colnames as is the case with this Data. We will add the colnames. Just follow me along.

Colnames

Adding a Column

In this chapter I will show you how to add a column to your data set. You can also use this for feature engineering when building models down the road.

Adding a Column

More Analytics

Let’s dive in a little further and see how the Credit Department might freak out at some of these orders.

More Analytics

Funny Data

Funny data isn’t funny if you don’t catch it. It can spell trouble down the road when others are looking at your work. Come in and we’ll learn some of the more basic ways to check for funny data.

Funny Data

More Clean Up

We’re going to discuss how to change the class of a Vector. This is important. I also will show you a quick way to look at the data to see what is needed to be changed.

More Clean Up

Watch Preview

Note: The actual session is completely hands-on where you interact with the software while watching the host's (Chris Shockley) instructions. You can preview the instructions here

Chris Shockley

About the Host


I am a R enthusiast, hiker, and amateur astronomer. My favorite hike is located in Mt. Rainier National Park, my favorite Deep Sky Object is Alberio, and my favorite R package is dplyr (since I use it everyday). I am single too. Maybe because I spend too much time playing? I have a dog named Coog (Lllasa Apso), who would rather be outside than inside, which means I have to take him on a lot of walks. I work as a Data Analyst/Financial Analyst for a Metals Co. located in Seattle, WA. I have been in my current position for 4 years. My hope is that I can help you, even if its with my enthusiasm. Yes you can learn R and the Rhyme Interface will help you. But. You also must take what you learn and practice, practice, practice. So... Let's get after it. See you soon.



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In Rhyme, all sessions are completely hands-on. You don't just passively watch someone else use the software. You use the software directly. While following the host's (Chris Shockley) instructions. Using the software is the only way to understand a software!
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