For this month’s data visualization challenge, I identified some possible analyses to build on my Ohio voter file dataset I build last month. In this first update, I have conducted exploratory analysis to find further insights in the data. For example, let’s say you are the Ohio Democratic Party. You want to ensure you mobilize voters… Read More
Month 2 Master
M2M – March Introduction
For March, I originally set out to build an R visualization that runs on a production script. However, two months in, I have realized that my focus is not on productionalization, but the quality of the findings that come from the analysis. With this in mind, I will use the same data set as last… Read More
M2M – February Recap
This month, I set out to take political data and build an interactive visualization. First, I gathered data from different sources and manipulated them in R. I identified R Shiny as my visualization platform and was ready to complete my challenge. But then… I hit massive roadblocks. I got tied down in the nitty-gritty of… Read More
M2M – February – Update #2
This month’s goal is to make an interactive R visualization using political data. As I previously wrote, for the data side, I am using Ohio voter files combined with income and representation data. For the interactive visualization, I am using shinyapps.io to host my R shiny application. I will be publishing this to the web and… Read More
M2M – February – Update #1
My February goal is to make an interactive R visualization using political data. This covers technical skill growth as well a personal interest of mine. Here is how I am building my dataset: Obtain publicly-available Ohio voter file data to get party affiliation, voting record, congressional district, and zip code for each voter. Obtain publicly-available zip… Read More
M2M – February Introduction
On this year-long “Month to Master” challenge, for the month of February, I set out to build on January’s progress to build an R-based visualization using Shiny. Ultimately, I plan to build an interactive visualization that uses voter file political data. This achieves multiple objectives: Builds on my polling and Shiny courses from January. Allows… Read More
M2M – January Recap
In this first month of my year-long “Month to Master” challenge, I set out to refresh my R skills. But this was not an arbitrary decision – the courses I chose to take tied together into a bigger theme. First, I took G. Elliott Morris‘ Analyzing Election and Polling Data in R class on DataCamp. His… Read More
M2M – January – Update #3
As I’ve stated, this month’s goal is to refresh my R skills. I set out to complete G. Elliott Morris’ DataCamp political analytics course and Jeff Li’s Cracking the Data Science Interview course. Well, after finishing the polling course a couple weeks ago, I have just completed “Cracking the Data Science Interview” and found it to… Read More
M2M – January – Update #2
My theme month is refreshing my R skills. However, I took a little detour in the past week by taking Jeff Li’s Cracking the Data Science Interview course. This course covers: SQL (basic queries, joins, and window functions) Python (data structures, functions) Statistics and Machine Learning Product KPIs I have completed the SQL portion (although… Read More
M2M – January – Update # 1
For this month, my goal is to brush up on my R skills. I committed to completing a DataCamp course and my buddy Jeff Li’s data science hiring course. Since two of my passions are data analytics and politics, I thought it would be perfect to start with a DataCamp political analytics course taught by data journalist… Read More