The United States is in a peculiar position. With 39% of its population fully vaccinated against Covid-19 as of May 23, and another 10% having received the first shot, it is among the most vaccinated countries in the world, according to the Washington Post.
Yet, due to vaccine hesitancy among the remaining Americans, the number of vaccines administered per day peaked in mid-April, and has been declining ever since, making it unlikely the nation will achieve herd immunity through vaccination.
Experts are now exploring ways to reach those hesitant to get the vaccine, and acknowledge that hesitancy may have different…
“Sorry, I can’t talk now. I’m iterating on a random forest that’s orthogonal to your value proposition.”
Techy people talk funny.
At least that’s what it feels like when you enter the tech world from a not-quite-technical background. In this story, I’ll explore the origins and meanings of some interestingly named Data Science terms.
When I started learning to code for Data Science, I was told that I would need Python. But in order to get Python, I would need Anaconda. Once I had both Anaconda and Python, I should then import pandas. …
In this story, I’ll discuss how to create subplots in matplotlib, and how to automate their creation using a for loop.
As a python beginner, I found myself unexpectedly flummoxed by trying to create subplots. What’s the difference between the plt.subplot() and plt.subplots() functions? What are the cryptic three-digit numbers such as plt.subplot(131)? And what does “fig, ax” mean? I will try to demystify subplot syntax below.
Using subplots simply means putting more than one plot in the same figure. For example, here is a figure containing six subplots. This data is from the King County House Sales dataset (https://www.kaggle.com/harlfoxem/housesalesprediction?select=kc_house_data.csv).
A few weeks ago, I began a journey to become a data scientist, by enrolling in the Data Science bootcamp offered by the Flatiron School. My instructors have challenged me to answer this question: Why data science?
The short answer is that I find data wrangling and analytics fascinating and enjoyable. While working in hospital finance, I often ran SQL reports and analyzed them in Excel. I became drawn to data, to the stories it could tell, and to its thorny, patchwork, unpredictable nature that requires careful attention to detail.
During a brief stint on the Analytics team of a…