You're reading from Hands-On Data Science with Anaconda

Product typeBook

Published inMay 2018

Reading LevelIntermediate

PublisherPackt

ISBN-139781788831192

Edition1st Edition

Languages

Python

Tools

Jupyter Anaconda

Concepts

Data Science

Authors (2):

Yuxing Yan

James Yan

View More author details

Finding all R packages

For R-related packages, go to http://r-project.org first. Click on CRAN and choose a mirror location, then click Packages on the left-hand side. We can see two lists, as shown here:

On February 22, 2018, there are 12,173 R packages available. The first list contains all available packages sorted by their publication dates (that is, the dates they updated, or published if they were never updated). The second list is sorted by their names. If we just want to find relevant packages, either list will be fine. For example, for the first list, here is a snapshot of a few lines:

The first column shows when the packages were last updated, or published if no updates were available. The second column shows the names of the packages, while the last column offers a short description of the usage for each package. We can use keywords to find the packages we want...

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Hands-On Data Science with Anaconda

Published in: May 2018Publisher: PacktISBN-13: 9781788831192

Authors (2)

Yuxing Yan

Yuxing Yan graduated from McGill University with a PhD in finance. Over the years, he has been teaching various finance courses at eight universities: McGill University and Wilfrid Laurier University (in Canada), Nanyang Technological University (in Singapore), Loyola University of Maryland, UMUC, Hofstra University, University at Buffalo, and Canisius College (in the US). His research and teaching areas include: market microstructure, open-source finance and financial data analytics. He has 22 publications including papers published in the Journal of Accounting and Finance, Journal of Banking and Finance, Journal of Empirical Finance, Real Estate Review, Pacific Basin Finance Journal, Applied Financial Economics, and Annals of Operations Research. He is good at several computer languages, such as SAS, R, Python, Matlab, and C. His four books are related to applying two pieces of open-source software to finance: Python for Finance (2014), Python for Finance (2nd ed., expected 2017), Python for Finance (Chinese version, expected 2017), and Financial Modeling Using R (2016). In addition, he is an expert on data, especially on financial databases. From 2003 to 2010, he worked at Wharton School as a consultant, helping researchers with their programs and data issues. In 2007, he published a book titled Financial Databases (with S.W. Zhu). This book is written in Chinese. Currently, he is writing a new book called Financial Modeling Using Excel — in an R-Assisted Learning Environment. The phrase "R-Assisted" distinguishes it from other similar books related to Excel and financial modeling. New features include using a huge amount of public data related to economics, finance, and accounting; an efficient way to retrieve data: 3 seconds for each time series; a free financial calculator, showing 50 financial formulas instantly, 300 websites, 100 YouTube videos, 80 references, paperless for homework, midterms, and final exams; easy to extend for instructors; and especially, no need to learn R.
Read more about Yuxing Yan

James Yan

James Yan is an undergraduate student at the University of Toronto (UofT), currently double-majoring in computer science and statistics. He has hands-on knowledge of Python, R, Java, MATLAB, and SQL. During his study at UofT, he has taken many related courses, such as Methods of Data Analysis I and II, Methods of Applied Statistics, Introduction to Databases, Introduction to Artificial Intelligence, and Numerical Methods, including a capstone course on AI in clinical medicine.
Read more about James Yan

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