DataScience VS PlotDocs.jl

For all topics that explained briefly, I provided the links with more thorough documentation. In addition, I would highly recommend reading the Julia Data Science online book and learn the great set of machine learning examples in Julia Academy Data Science GitHub repository.

So, I just decided to try to learn Julia, and started by following the Julia for DataScience lectures on JuliaAcademy. In the first lecture, I get instructed to clone the DataScience repository on GitHub. According to instructions, I activated the environment with activate and check the status (status). I then ran instantiate to update any necessary packages, and get the following error message:

https://docs.juliaplots.org/stable/

3. See https://juliaacademy.com

Another alternative environment are Pluto notebooks. It's reactive like a spreadsheet, but easy to use in your browser.

https://featured.plutojl.org/

I have several users without much coding experience using Pluto notebooks just to generate plots from CSV files. They are finding the combination of a web based interface, reactive UI, and fast execution easier to use than a MATLAB Live script.

Using Plots.jl, you can create a lot of different graphs to analyze your data, similar to Matplotlib or Seaborn in Python. To use it, you have to install the Plots package to your notebook and import it:

Did you get that from this page? I'm fairly sure those are just Markdown tables including images created with cgrad or palette as described further up the page. You can check the source to confirm if you want.