It’s been quite a while since the first issue. I promised that this would be a low volume list but maybe not this low volume! I’m still working through what I want to include in the list so feedback is welcome.
This issue will focus on sharing some useful resources that many of you may not have seen and are good to be aware of when working on you own projects in the future.
PB Python Articles
I have published two articles since the last mailing:
- Seaborn 0.9 was released and contained several updates that are very helpful. You can read the article here which highlights several of the most important updates.
- After doing some work with the pandas crosstab function, I wrote up a detailed article that walks through how to use this simple but powerful function.
Other Python Notes
Here are a few other updates in the python ecosystem.
- scikit-learn released version 0.20 and there are a lot of updates to make it work more effectively with pandas.
- Here’s an interesting video that talks about the path to pandas 1.0. The backup notebook is available here . I would not characterize any of the changes or updates as earth shattering but good foundations for a 1.0 release of this pillar of the python data science ecosystem.
In the Twin Cities, there are several great python and data science meetups that I try to attend as frequently as possible. A few months back, I was able to listen to Aayush Agrawal present some of his cookbook code samples for data science. I think these notebooks are great resources to bookmark and come back to when you’re doing your own analysis. The code is generally pretty easy to understand and shows an example of how a working data scientist approaches a problem. He also introduced the group to lime which seems like a great library to leverage when trying to interpret your models.
I also attended a talk by Jeff Macaluso on Ensemble Methods and thought this would be another resource to bookmark and refer back to. You can find the presentation and the notebook on his github repo . Jeff does a nice job of walking through several somewhat advanced concepts and showing how to interpret the results.
Projects to Explore
Someone reached out to me and asked me if I have ever heard of docassemble . I had not so I spent some time investigating the project. After working with it, I can tell you It is an extremely impressive framework.
The basic premise of this python open source project is that it is a customizable tool that allows you to build a yaml file with questions that are used to assemble final documents in PDF, Word or other formats. The project was designed for the legal profession but I thing there are a wide range of applications that people on this list might want to consider.
For instance, I played around with generating a custom quoting engine that would allow a sales person to answer some guided questions and get a final PDF document that they could deliver to their customer. There is a lot of flexibility and power in the solution that would likely be difficult to find in many paid offerings.
The documentation is extensive. It is likely going to be a challenge for someone brand new to python to get up and running. However, if you have a need for a tool like this, I encourage you to take a look at it and try it out yourself. Also, the main developer is incredibly responsive and very prolific with the code updates.
Getting Your Feedback
Well, I hope you found this useful. The list membership has grown a lot since the first mailing so I hope all of you new members enjoy the content. If you would like to give me some feedback on topics for the blog or this newsletter, I setup a short google form to capture your thoughts. I look forward to hearing what you have to say.