Posts tagged intro
Dealing With Dates in Python - Part 2
- 25 January 2023
Hello, everyone! Welcome back to Cameron’s Corner! This week, I want to continue our discussion of datetimes in Python. Last time, we established a dichotomy of date usages. We have things that represent a…
point-in-time
Dealing With Dates in Python - Part 1
- 18 January 2023
Welcome back to Cameron’s Corner! This week, I want to get our hands on some code and talk about some of the approaches for dealing with datetimes in Python. Additionally, I want to discuss some common considerations you’ll need when implementing dates and datetimes in your own code. Let’s dive in!
A datetime is a specific point-in-time, referring to an instance. As the name suggests, these typically contain both a date and a time component: the date is some combination of year, month, and day, and the time is some combination of hours, minutes, and seconds, down to some pre-defined level of specificity.
Working with Long Labels In Bokeh
- 10 August 2022
Hey all, I wanted to revisit a topic I discussed a few weeks ago and demonstrate how use deal with long labels in another one of my favorite plotting libraries in Python: bokeh.
In a previous post, I mentioned that I came across a fun blog post by Andrew Heiss covering how to work with long tick labels in R’s ggplot2. As I mentioned in my last post: “I couldn’t resist the urge to recreate the visualizations in and wanted to share with you how you can deal with long tick labels in Python!”
Working with Long Labels In Matplotlib
- 20 July 2022
Hey all, I came across a fun blog post covering how to work with long tick labels in R’s ggplot2. I couldn’t resist the urge to recreate the visualizations in matplotlib and wanted to share with you how you can deal with long tick labels in Python!
First we’ll need some data- using the same source as the above linked blog post, we can fetch and process our data like so:
Python: Decorator Fundamentals
- 14 May 2022
- English
Python has had the standard @decorator style decorator syntax since PEP 318 – Decorators for Functions and Methods was accepted, while some tweaks to the grammar have been made a long the way via PEP 3129 – Class Decorators and PEP 614 – Relaxing Grammar Restrictions On Decorators, their behavior has remained largely unchanged.
The most common misconception about decorators is that they are a function that takes a function and returns a function. While this does describe a common pattern for decorators, it ignores their generalized framework and misses strong usecases for decorators. Instead, I will say that a decorator is a callable that takes a class or function as an argument to encapsulate/manipulate some state and/or prepend/append some behavior to that class or function. While that definition is quite verbose, I think the following code snippets will help make my point.
Exceptions - Following a traceback
- 01 January 2022
This workshop will help you understand how to read and understand error messages in python.
Understand what Exceptions are and differentiate from the traceback