Descriptive analysis of Black Friday Death Count Database provides an example of how creative classification can make a quick and easy data science portfolio project!
Classification crosswalks are easy to make, and can help you reduce cardinality in categorical variables, making for insightful data science portfolio projects with only descriptive statistics. Read my blog post for guidance!
FAERS data are like any post-market surveillance pharmacy data – notoriously messy. But if you apply strong study design skills and a scientific approach, you can use the FAERS online dashboard to obtain a dataset and develop an enlightening portfolio project. I show you how in my blog post!
Dataset source documentation is good to keep when you are doing an analysis with data from multiple datasets. Read my blog to learn how easy it is to throw together some quick dataset source documentation in PowerPoint so that you don’t forget what you did.
Joins in base R must be executed properly or you will lose data. Read my tutorial on how to correctly execute left joins in base R.
NHANES data piqued your interest? It’s not all sunshine and roses. Read my blog post to see the pitfalls of NHANES data, and get practical advice about using them in a project.
Color in visualizations of data curation and other data science documentation can be used to enhance communication – I show you how!
Defaults in PowerPoint are set up for slides – not data visualizations. Read my blog post for tips on reconfiguring PowerPoint to make it easy for dataviz!
Text and arrows in dataviz, if used wisely, can help your audience understand something very abstract, like a data pipeline. Read my blog post for tips in choosing images for your data visualizations!
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