You downloaded data files, or maybe you compiled them yourself. How will you get those data into R?
R offers built-in functions that let you access either delimited (where a certain character separates values) or fixed-width (where each column uses a certain number of characters) files. Like other popular statistical packages, R even supports its own data file format. Let’s explore some frequently-used functions.
Continue readingYou downloaded data files from the US government or some other organization that depends on proprietary spreadsheet software or statistical packages. How will you get those data into R?
Fortunately, other programmers have faced this issue and developed R packages that let you read data saved in various proprietary formats. Let’s explore several popular options.
Continue readingYou have data. You’ve cleaned it. You wonder: What statistical test should I run? Sage’s Which Stats Test tool can help you pick the right test for your statistical analysis.
How did the COVID-19 pandemic change how people at different income levels spent? What impact did economic stimulus measures have on purchases? Consumer Expenditure Surveys (CE) could help you answer these questions and more.
Have you tried working with what look like text data in R only to get back a number or an error about comparing or replacing elements? If this sounds familiar, you may have been working with factor data. Read on for more about how to create and handle factor data in R.
Healthy research requires reproducibility, but R works with so many community-sourced packages that tracking each one’s impact can seem daunting. How can you do it? R’s citation function makes citing R libraries simple.
Thomson ONE‘s full features are available only with the outdated Internet Explorer (IE) browser. This makes staying up-to-date on the latest browser workarounds critical to accessing this collection of company information, SEC filings, and analyst reports. Continue reading for details regarding this year’s Chromium-based update to Microsoft Edge.
Did you (or your company, or your government…) try something new? You’ll want to know whether that change made a difference. Fortunately, the R statistical programming language offers easy-to-run tests that can help you compare performance before and after the policy went into effect.
Have a mess of files to read into Python? Maybe you downloaded Kaiko trade data, with unpredictable sub-directories and file names, from Penn+Box. Or maybe you’ve dropped TXT, PDF, and PY files into a single working directory that you’d rather not reorganize. A simple script will find the files you need, listing their names and paths for easy processing.
Itching to analyze cryptocurrency data down to the tick? Kaiko’s rich historical data—accessible through the Lippincott Library—offer details from more than 50 exchanges and 7,500 currency pairs, letting you expand the boundaries of your research.
Datapoints: A blog from the Lippincott Library of the Wharton School of Business 