Possible Blog Post Topics

I maintain a long list of potential posts, which usually don’t get written unless I have a lot of downtime. Often posts are researched or written when I’m sitting in an airport or a hotel room. “Regular” life doesn’t seem to provide enough time to focus on these things for long. This post is an opportunity for me to revisit some ideas I’ve been meaning to write about but haven’t found the time to do so. This is the first real assignment for the #cnc2018 blog more challenge. For this assignment, our instructions are as follows: Come up with 10 blog ideas, then narrow those down to 3. For this challenge, your blog should fall into 1 of 3 categories: tutorial, project, explainer.

Just as a reminder from my prior post on this topic, tutorials are “step-by-step guides with instructions to teach the reader how to do something specific,” while projects are “a breakdown that explains a technical concept to the reader,” and explainers are “posts that talks about a project you worked on and explains the journey and technical challenge you experienced.” I started out with four tutorial ideas, four project ideas and two explainer ideas:

Potential Tutorial Posts

  1. Tidy Data - explain Hadley Wickham’s ideas about what is meant by tidy data
  2. Basic Statistics in Pandas and SciPy - a brief refresher on available statistical tests in Python
  3. Pivot Tables - explanation of the use of pivot tables in Python and Excel
  4. Geographic Data - a post to get newbies up to speed using Python’s geographic libraries

Potential Project Posts

  1. Web Scraping - an introduction to web scraping in Python
  2. Sortino Ratio - a project to become familiar with Sortino Ratio
  3. D3 Intro - a quick intro to getting started with D3.js for data visualization
  4. Funnel Analysis - creating a funnel analysis in Python or SQL

Potential Explainer Posts

  1. Data Analysis Project Using data.world - an introduction to accessing data.world from Jupyter notebooks
  2. Populating Your Portfolio - how to create projects that will result in an impressive online portfolio

I should be able to narrow these down based on the amount of work they’ll take to write up, as well as my general interest on the topic. However, the topics that generally interest me the most are the most time-consuming and difficult to pick up. The final three will be actual posts at point in the near future.

Tutorial Post: Geographic Data

I’ve always been fascinated with GIS, but I’ve never taken the time to learn how to use it. Maps are also incredibly useful for data visualizations and will almost certainly come in handy at some point.

Project Post: D3 Intro

Although I would love to learn about web scraping and other random topics, D3.js seems to me by far the most useful data viz library. It’s ubiquitous and pairs pretty well with Jupyter Notebooks. There’s really no reason not to learn D3.js.

Explainer Post: Data Analysis Project Using data.world

This is my least favorite topic, mostly because it’s the most time-consuming and I have comparatively little experience to draw upon. But I love the data analysis possibilities that data.world provides, and it’s high time I learned how to use their API and their SQL query tools.

Written on January 29, 2018