Intro to R for Finance

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Course Description

In this finance-oriented introduction to R, you will learn essential data structures such as lists and data frames and have the chance to apply that knowledge to real-world financial examples. By the end of the course, you will be comfortable with the basics of manipulating your data to perform financial analysis in R.

Get comfortable with the very basics of R and learn how to use it as a calculator. Also, create your first variables in R and explore some of the base data types such as numerics and characters.

Arguably the most important data structure in R, the data frame is what most of your data will take the form of. It combines the structure of a matrix with the flexibility of having different types of data in each column.

Wouldn't it be nice if there was a way to hold related vectors, matrices, or data frames together in R? In this final chapter, you will explore lists and many of their interesting features by building a small portfolio of stocks.

In this chapter, you will learn all about vectors and matrices using historical stock prices for companies like Apple and IBM. You will then be able to feel confident creating, naming, manipulating, and selecting from vectors and matrices.

Questions with answers that fall into a limited number of categories can be classified as factors. In this chapter, you will use bond credit ratings to learn all about creating, ordering, and subsetting factors.

1
The Basics
Free

Get comfortable with the very basics of R and learn how to use it as a calculator. Also, create your first variables in R and explore some of the base data types such as numerics and characters.
View Chapter Details Play Chapter Now
Vectors and Matrices

In this chapter, you will learn all about vectors and matrices using historical stock prices for companies like Apple and IBM. You will then be able to feel confident creating, naming, manipulating, and selecting from vectors and matrices.
View Chapter Details Play Chapter Now
Data Frames

Arguably the most important data structure in R, the data frame is what most of your data will take the form of. It combines the structure of a matrix with the flexibility of having different types of data in each column.
View Chapter Details Play Chapter Now
Factors

Questions with answers that fall into a limited number of categories can be classified as factors. In this chapter, you will use bond credit ratings to learn all about creating, ordering, and subsetting factors.
View Chapter Details Play Chapter Now
Lists

Wouldn't it be nice if there was a way to hold related vectors, matrices, or data frames together in R? In this final chapter, you will explore lists and many of their interesting features by building a small portfolio of stocks.
View Chapter Details Play Chapter Now

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Lloyd's Banking Group

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Lore Dirick

Director of Data Science Education at Flatiron School

Lore is a data scientist with expertise in applied finance. She obtained her PhD in Business Economics and Statistics at KU Leuven, Belgium. During her PhD, she collaborated with several banks working on advanced methods for the analysis of credit risk data. Lore formerly worked as a Data Science Curriculum Lead at DataCamp, and is and is now Director of Data Science Education at Flatiron School, a coding school with branches in 8 cities and online programs.

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Introduction to R for Finance

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Loved by learners at thousands of top companies:

Course Description

The Basics

Welcome to Introduction to R for Finance!

Your first R script

Arithmetic in R (1)

Arithmetic in R (2)

Assignment and variables (1)

Assignment and variables (2)

Financial returns

Financial returns (1)

Financial returns (2)

Basic data types

Data type exploration

What's that data type?

Data Frames

What is a data frame?

Create your first data.frame()

What goes in a data frame?

Making head()s and tail()s of your data with some str()ucture

Naming your columns / rows

Data frame manipulation

Accessing and subsetting data frames (1)

Accessing and subsetting data frames (2)

Accessing and subsetting data frames (3)

Adding new columns

Present value

Present value of projected cash flows (1)

Present value of projected cash flows (2)

Lists

What is a list?

Create a list

Named lists

Access elements in a list

Adding to a list

Removing from a list

A few list creating functions

Split it

Split-Apply-Combine

Attributes

Congratulations!

Vectors and Matrices

What is a vector?

c()ombine

Coerce it

Vector names()

Visualize your vector

Vector manipulation

Weighted average (1)

Weighted average (2)

Weighted average (3)

Vector subsetting

Matrix - a 2D vector

Create a matrix!

Matrix <- bind vectors

Visualize your matrix

cor()relation

Matrix subsetting

Factors

What is a factor?

Create a factor

Factor levels

Factor summary

Visualize your factor

Bucketing a numeric variable into a factor

Ordering and subsetting factors

Create an ordered factor

Subsetting a factor

stringsAsFactors

The Basics