Articles · Jun 2020
Develop a Rigid Workflow
Clean, reliable data is the foundation of sound analysis. Explore the eight critical steps in a data workflow, from gathering and verifying data integrity to building…
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Articles · points of view · data hacks
What we have learned, written down.
Points of view for leaders, practical data hacks for practitioners, and conversations from our webinars and podcast.
Articles · Jun 2020
Keep an internal inventory of data sources
It may seem like an obvious point, but it is hard to overemphasize the importance of keeping your own inventory of internal data sources. This will…
Read →Articles · May 2020
Think about Design First
Today's Data Hack Tuesday tip may seem obvious, but is too often overlooked. Before analyzing data for any project, it is important to consider the design…
Read →Articles · May 2020
Cleaning Data in Excel
We all know the old saying: data scientists spend 80% of their time cleaning and manipulating data and only 20% of their time actually analyzing it.…
Read →Articles · May 2020
Cross-validation
We have a simple tip for today to help evaluate models and avoid overfit. Start by separating your data into two sets. These will be the…
Read →Articles · May 2020
Interactive debugger
Looking for an easier way to find and eliminate errors in Jupyter? Don't forget about the interactive debugger. If you're running the code cell and get…
Read →Articles · Apr 2020
Using the .Plot() Function
Did you know that Pandas has a built-in .plot() function as part of the DataFrame class? The trouble is that the visualizations rendered this way are…
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