| Excel, Python, and the Future of Data Science |
What’s the most widely used tool in data science? Is it pandas or NumPy? Is it the Python language itself? Not really. It’s Excel. You might argue that data scientists aren’t using Excel as their primary tool, and you might be right. But Excel enables non-technical users, like small business owners, to gain insights into their data. In this article, Anaconda CEO Peter Wang discusses his goal of making Python and PyData the “conceptual successor” to Excel.
Practical SQL for Data Analysis
If you need to do some data analysis, what tool do you reach for first? Is it pandas? While pandas is great, it comes with some costs that you might not be aware of, including large memory overhead that can quickly get in the way of your projects. Using databases with SQL can alleviate memory issues. In this tutorial, you’ll learn how to do common data analysis tasks in SQL, which opens the door to mixing SQL and pandas to create lightweight programs that are also fast!
Visualize Performance and Quickly Troubleshoot your Python Application with Datadog APM
Datadog’s APM allows you to find the most resource-consuming parts in your production code all the time, at any scale, with minimal overhead. Trace requests across service boundaries and optimize bottlenecks by drilling into individual traces end-to-end and enhance user experience. Try it free →
Python Practice Problems: Parsing CSV Files
In this tutorial, you’ll prepare for future interviews by working through a set of Python practice problems that involve CSV files. You’ll work through the problems yourself and then compare your results with solutions developed by the Real Python team.
Jazzband Joins the PSF Fiscal Sponshorship Program
Microsoft Is Hiring to Help Speed Up Python
Mypy 0.900 Released
Why Can’t Comments Appear After a Line Continuation Character?
Chaining together many object methods can create long tines that break the PEP 8 79-character line length recommendation. You can use
\ to break the chain of methods onto individual lines, but if you want to leave comments at the end of some of the lines, you’re out of luck. There’s another pattern, though, that solves this.
What Are Some Common Ways to Distribute Python Packages Internally?
Brian Okken, co-host of the Python Bytes podcast, asks Twitter users about internal package distribution, and the Twitterverse responds.
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Articles & Tutorials
A Bayesian Analysis of Lego Prices in Python With PyMC3
Follow along with this in-depth analysis of LEGO prices to see Bayesian analysis in action. Along the way, you’ll how pooled and unpooled linear models can be used to determine if a LEGO set is fairly priced. The article is quite technical, so experience with Bayesian statistics is recommended.
How I Teach Python on the Raspberry Pi 400 at the Public Library
Community-based programming courses are a great way to introduce folks to computer programming that otherwise may not have the means to do so. One of the barriers to learning to code is cost. You need a computer to program on, after all. But with the advent of tiny computers like the Raspberry Pi, computers aimed at education are more affordable than ever.
Get Feedback Faster with YourBase Test Acceleration
YourBase Test Acceleration can reduce testing and compute cost time by up to 90%. You don’t have to replace your CI, your build system, or your version control. Getting started is as easy as a pip install, and security review is simple as you don’t have to share any data with us →
Using Pandas to Make a Gradebook in Python
With this Python project, you’ll build a script to calculate grades for a class using pandas. The script will quickly and accurately calculate grades from a variety of data sources. You’ll see examples of loading, merging, and saving data with pandas, as well as plotting some summary statistics.
REAL PYTHON course
Detecting Deforestation With Python & Using GraphQL With Django and Vue
Are you looking for an in-depth data science project to practice your skills on? Perhaps you would like to add new tools to your Python web development projects instead? This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects.
REAL PYTHON podcast
Design and Distribute your Python Notifications with Courier’s Omni-Channel API
Centralized Notification Strategies are much wow| Scale your Python app’s notification capabilities| Keep your codebase clean of HTML templates| Plugin Sendgrid, Mailgun, Firebase, Twilio, etc, and manage all of your notifications with one API and UI
Python Sentinel Objects, Type Hints, and PEP 661
PEP 661 proposes adding a utility for defining sentinel values in the standard library. In this article, you’ll get a summary of PEP 661, learn what sentinel objects are with real-world examples, and see how to use them with type hints.
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filter(): Extract Values From Iterables
In this step-by-step tutorial, you’ll learn how Python’s
filter() works and how to use it effectively in your programs. You’ll also learn how to use list comprehension and generator expressions to replace
filter() and make your code more Pythonic.
Projects & Code
novelWriter: Cross-Platform Editor Designed for Writing Novels Built With Python and Qt
speechbrain: A PyTorch-based Speech Toolkit
pyWhat: Identify Anything With Python
textual: A Text User Interface With Rich as the Renderer
pyrgg: Python Random Graph Generator