Methods to extract meaningful words from a text and create word cloud art in python.

Illustration by Bryan Dickinson

I’m sure you’ve seen a word cloud. Generally, it’s a photo filled with words where the size depends on the frequency of times the word appears in the text you’d like to analyze. I wasn’t privy to this, but apparently, there has been/is (not sure) some pretty strong feelings against/for word clouds. I have read that they are bad, lame, equating them to a modern pie chart and even comparing them as the new mullet. Ouch. A mullet? Come on.

Natural Language Processing

Analyzing the 2020 democratic presidential debates using Natural Language Processing

Illustration by Bryan Dickinson based on photos from Gage Skidmore

In the past, I never spent much time watching party presidential nominee debates, I usually waited for the presidential debates. Though this year, I decided to tune in and observe. I grew increasingly frustrated after each debate because the candidates hardly answered the questions! I noticed a few things — the candidates focused on their background, their stance on a few topics, and attacked other candidates, and then sometimes they answered the question that was asked. I stopped watching the rest of the debates because the fighting grew and it didn’t seem like any questions were being answered. If they…


Data Scientist’s guide to hiding secret keys, IDs, and other sensitive information in a virtual environment using conda & Windows.

Photo by Jason D on Unsplash

I started a new data project focused on Covid-19 data. Grabbing the data and storing it involved quite a few API keys & IDs. As a thoughtful Data Scientist — when I started my project I created a new virtual environment, as we all do right…? Anyhow — I was going to be utilizing APIs from both AWS and Google and decided I needed to hide my secret keys since this project will be posted to a public repo. At that point I realized I hadn’t done this before — I would simply delete or exchange the key with ‘YOUR_SECRET_KEY_HERE’…


Analyzing the top five democratic presidential nominees data from Google Trends to find the most popular candidate during the debate season.

Image by Mary Pahlke from Pixabay

If you have been watching the debates Democratic Presidential Debates this past year — you may agree that it’s been somewhat of a wild ride. From finger nibbling to tense post-debate standoffs. We know that Joe Biden is the democratic presumptive nominee. But I’d like to take a look back at the data. We’ll walk through and explore the data in the form of search interest data from Google Trends using pandas and matplotlib libraries. We’ll recreate the Google Trends plot to visualize their popularity over time. And we’ll take a look — who was actually the most popular candidate?

Google Trends

Can the race of a stopped individual be predicted by officer & subject demographic information?

Photo by Sabine Ojeil on Unsplash


There has been a rise in tension between law enforcement and the public. I’ve seen & read many news articles with a lot of rhetoric. As a new Seattleite, I was interested in determining if there was a racial bias with law enforcement and race in the city of Seattle. I decided to to look into Terry Stops performed in the City of Seattle, and come to my own conclusion.

Through Seattle’s Open Data Program, I was able to download the Terry Stop Data from the past few years, perform statistical and exploratory analysis on the data, with the goal…

Bryan Dickinson

Data Science| Data Analytics| BI| Interested in solving real world problems. https://www.bryan-md.github.io/

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