August 30, 2016• 5 minute read
Joel Carron
Data Scientist at Mode
You've probably heard of the Pareto principle, even if you didn't realize it at the time. Here are a few examples:
June 28, 2016• 7 minute read
Melissa Bierly
Content Marketing
When writers hit a block, they read. When musicians get stuck, they seek stimulation by listening to music. It's the same with any craft. The more you surround yourself with the work of others in your field, the more opportunities you have to learn, be inspired, and channel those influences back into your own work.
June 23, 2016• 8 minute read
Joel Carron
Data Scientist at Mode
As your business grows, maintaining excellent customer service requires delivering high-quality solutions efficiently and effectively. But balancing the goals that lead to great customer service is a challenge—overemphasize efficiency and your quality may suffer; provide a white-glove experience on every interaction and your customer service cost might bankrupt the entire company.
June 21, 2016• 2 minute read
Nick Binder
Product Marketing Manager
No matter how you're looking to present your data, there's a seemingly endless number of Python libraries and resources to use (check out ten of our favorites).
You may know Plotly as an easy-to-use online data visualization tool, but did you know they also offer a Python API so data scientists can use Plotly and Python together offline? We're excited to add Plotly to the growing list of supported libraries in Mode Python Notebooks.
With Plotly and Mode you can build beautiful, interactive data visualizations on top of a Python dataset and share it with teammates instantly.
June 15, 2016• 2 minute read
Nick Binder
Product Marketing Manager
Sometimes you just need to share a data set. A list of app users who meet certain criteria. A call list for a sales team. You get the idea. Often the next step with shared data sets like these is for someone to export the data as a CSV to do simple explorations in Excel.
June 8, 2016• 9 minute read
Melissa Bierly
Content Marketing
Scroll through the Python Package Index and you'll find libraries for practically every data visualization need—from GazeParser for eye movement research to pastalog for real-time visualizations of neural network training. And while many of these libraries are intensely focused on accomplishing a specific task, some can be used no matter what your field.