Why are you creating a virtual environment every time you install a module? Is it recommended? Does the virtual environment remove the module installations once you deactivate it?
Excellent question! It's best practice when encapsulating Python dependencies to use virtual environments. When you deactivate the virtual environment, the dependencies will also be deactivated.
I'm going to be rather critical here, but I intend it as feedback. For context: I've programmed for over 10 years, multiple paradigms, multiple languages, but have mostly written Python in the last 4 years. I see myself as intermediate to advanced. For who is this video? Beginners, right? I remember watching videos like these, back when I was a beginner, and they just confused me. I could now plot a graph with random data, but not my own data, nor could I change the graph in any meaningful way. Here's where I would like to see improvements: focus a bit more on the why. Why do I use plot(), and what kinds of data can I pass in there? Why use ylabel()? What is show() for - why does it not show automatically? Which other methods are there? How can I know? Can I somehow easily update the script to experiment and have the window update automatically? We're making a graph, but I don't know what kinds of data goes in there, nor how many. Is the type(s) of input for other kinds of graphs the same, or do I pass them differently? Also please link the code somehow to some documentation (doesn't have to be a literal link - you could make it visual as well) so newbies can learn to read the docs (and help themselves). Remember that this is the age of LLMs, and basic examples like these are better asked to ChatGPT. What YOU can do is provide more helpful information that would fit a newbie (who would barely know what to ask an LLM) so they can learn to ask the right questions. I like that you kept the video short, and your mic and camera (though a tad small - you can easily 2x your face for my phone screen) are good, so those fundamentals are covered.
I would have to disagree and I will explain why. I am on the older side and learning to code. These short videos are like video cheat sheets and I find it much more productive having someone showing me the actual code and a brief on what it does. If I want a full explanation of how it works I just paste the code into ChatGPT and tell it to explain this code to a 10 year old. Any age below that I find is doesn't do a good job. ChatGPT is not video and why it is good watching someone actually input the code, even if it is boring for someone with more experience. We all have different ways we learn and I have learnt a lot from these videos, it might be a bit different if I understand how to code a bit more but at the moment these videos are helping me quite a lot while I am learning and I appreciate the effort Taylor puts in.
Why are you creating a virtual environment every time you install a module? Is it recommended? Does the virtual environment remove the module installations once you deactivate it?
Excellent question! It's best practice when encapsulating Python dependencies to use virtual environments. When you deactivate the virtual environment, the dependencies will also be deactivated.
I'm going to be rather critical here, but I intend it as feedback. For context: I've programmed for over 10 years, multiple paradigms, multiple languages, but have mostly written Python in the last 4 years. I see myself as intermediate to advanced.
For who is this video? Beginners, right? I remember watching videos like these, back when I was a beginner, and they just confused me. I could now plot a graph with random data, but not my own data, nor could I change the graph in any meaningful way.
Here's where I would like to see improvements: focus a bit more on the why. Why do I use plot(), and what kinds of data can I pass in there? Why use ylabel()? What is show() for - why does it not show automatically? Which other methods are there? How can I know? Can I somehow easily update the script to experiment and have the window update automatically? We're making a graph, but I don't know what kinds of data goes in there, nor how many. Is the type(s) of input for other kinds of graphs the same, or do I pass them differently? Also please link the code somehow to some documentation (doesn't have to be a literal link - you could make it visual as well) so newbies can learn to read the docs (and help themselves).
Remember that this is the age of LLMs, and basic examples like these are better asked to ChatGPT. What YOU can do is provide more helpful information that would fit a newbie (who would barely know what to ask an LLM) so they can learn to ask the right questions.
I like that you kept the video short, and your mic and camera (though a tad small - you can easily 2x your face for my phone screen) are good, so those fundamentals are covered.
Thank you for your feedback!
I would have to disagree and I will explain why. I am on the older side and learning to code. These short videos are like video cheat sheets and I find it much more productive having someone showing me the actual code and a brief on what it does. If I want a full explanation of how it works I just paste the code into ChatGPT and tell it to explain this code to a 10 year old. Any age below that I find is doesn't do a good job. ChatGPT is not video and why it is good watching someone actually input the code, even if it is boring for someone with more experience.
We all have different ways we learn and I have learnt a lot from these videos, it might be a bit different if I understand how to code a bit more but at the moment these videos are helping me quite a lot while I am learning and I appreciate the effort Taylor puts in.