R Craft: Read CSV, RDA, and other Supported Data Files with R

You downloaded data files, or maybe you compiled them yourself. How will you get those data into R?

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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.

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R Craft: Read Excel, Stata, and other Unsupported Data Files with R

You 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? 

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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. 

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How do Americans spend money? The Consumer Expenditure Surveys know

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.

Line graph of mean US Consumer Expenditure for (in descending household spend) Housing, Transportation, Food, Entertainment, Alcoholic beverages, and Reading
Data from CE Tables, 2013-2019 Multiyear table
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R Craft: Did Your Policy Make a Difference?

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.

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Python Pointer: Find Files with os.walk()

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.

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Detailed Cryptocurrency Data from Kaiko – Available Now!

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.

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Clean Energy by the Numbers: Data Sources

WRIBusNeedsAccording to Christiana Figueres, Executive Secretary of the UN Climate Convention, “Never before have the risks of climate change been so obvious and the impacts so visible.” We could add that never before has there been such an interest in sources of information for climate change, energy use and “clean” (non-polluting)  technology.

 

 

In a previous blog post, Clean, Green, and Renewable Energy.  Are there any Alternatives? we described several  resources for  Penn students that cover clean technology. Here are some additional data sources on clean technology that may prove useful.

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