#167: Often used Diagrams for Matplotlib
Different types of data need different forms for a graphical representation. In this post we explore the most often used types of diagrams in Matplotlib.
2023
#166: Export your Matplotlib Plots
Creating plots in Matplotlib is fun. But when we only can use the visualisations inside our Jupyter notebook we cannot fully benefit from our work. Let us change that and export our plots into various formats.
#165: Figures and Axes in Matplotlib
One of the main concepts you need to understand early on with Matplotlib is the idea of figures and axes. Today we explore these terms and find out how we can create them in code.
#164: Visualise Data With Matplotlib
The more complex the data, the more helpful a good visual representation is. Python offers us such a wide range of tools to visualise our data that it is difficult to make a choice. Therefore, we will look at a few different approaches to data visualisation in the coming months to use the right tool for our use cases.
#163: Share Your Jupyter Notebooks
After we created our analysis, it is time to share our Jupyter notebooks. Let us look at the options we have.
#162: Tips & Tricks to Work Effectively With JupyterLab
JupyterLab is a great tool for working with data. As with all tools, work goes much faster if you know their quirks and idiosyncrasies. Today we look at some small but important things that can help you in your daily work with JupyterLab.
#161: Organise Data and Code in Jupyter Notebooks
Jupyter Notebooks offer us a great flexibility on how we can work with code and documentation. Unfortunately, not every attempt will give us a maintainable notebook. Let us look at ways to organise our code and the data we need.
#160: Jupyter Notebooks for Your Data Analysis
While working through a Python data analytics course, I started to like Jupyter Notebooks a lot. Not only do we get much faster feedback when we plot our data, this format offers an effortless way to keep your documentation next to your code. Let us explore this fascinating runtime environment for our code.
#159: Find the Missing C++ Build Tools
On a freshly installed computer, I got this error message when I installed a package with pip:
error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
This error shows up because pip needs to compile a few files as part of the installation, but there are no C++ build tools installed. Let us figure out how we can fix this problem.
#158: Extract the Audio of an MP4 Video
I have some videos from which I would like to extract the audio and save it as MP3. I could do that manually with VLC media player, but there is a much better solution in Python.