Taking Your Matplotlib Figures from Boring to Interesting with a Few Lines of Code — When we create infographics or posters containing data, we want to catch the reader’s attention and make it aesthetically pleasing to look at whilst telling a convincing story. Within Python, we have numerous plotting libraries that allow us to create charts — one such library is the well-known matplotlib library…

Improve Your Polar Bar Chart Data Visualisations With a Few Simple Tweaks — Polar bar charts provide a great alternative to traditional bar charts. Rather than the bars being arranged horizontally or vertically on Cartesian coordinates, these charts represent them using a polar grid. Plotting data this way can help visualise cyclical data and provide a more eye-catching and aesthetically pleasing data visualisation.

Visualising geological data using Python’s most popular data visualisation library — Radar plots (also known as spider plots or radar charts) are a popular data visualisation tool that allows us to compare datasets by displaying multiple variables simultaneously on a 2-dimensional plot. Each variable is represented by a spoke extending from the plot's centre to the edge, and the magnitude of…

Combining python-docx and Streamlit for Data Science Report Automation — At the end of data-related projects, whether for petrophysics or data science, creating a report is a very common occurrence. The generated reports provide clients and end users with information on the key results and conclusions obtained during the study, as well as detailing the methodologies used. However, creating structured…

Improve Your Data Visualisations with These Easy-to-Use Matplotlib Style Libraries — Matplotlib is a widely used data visualisation Python library, and is often come across early in the data science and python learning journey. However, over the years, it has gained a reputation for creating plain-looking figures, and it can be awkward to use, especially for newcomers. In my last few…

Simplifying the process of creating stunning charts with Matplotx — Matplotib is one of the most popular data visualisation libraries available within the Python world. However, over the years, it has gained a reputation for creating boring figures and being awkward to use. As seen in my latest articles, converting the basic matplotlib charts to something visually appealing does require…

Easily Improve the Quality of Your Matplotlib Data Visualisations With a Few Simple Tweaks — Bar charts are a commonly used data visualisation tool where categorical features are represented by bars of varying lengths/heights. The height or length of the bar corresponds to the value being represented for that category. Bar charts can easily be created in matplotlib. However, the matplotlib library is often regarded…

Utilising Python’s Matplotlib to Create Advanced Data Visualisations — Often matplotlib has a bit of a reputation for creating boring figures and being awkward to use. However, with some patience, research and extra lines of python code, we can create some unique and very visually appealing figures. When learning python, matplotlib is often the first data visualisation library that…

Two Great Python Options for Visualising Geospatial Variation — Heatmaps, also known as Density Maps, are data visualizations that display the spatial distribution of a variable across a geographic area. They can be great tools for visualising and identifying trends, supporting decision-making, detecting outliers, and creating compelling visualisations for presentations. There are several mapping python libraries available, however, two…