Adding a Geological Facies Display to a Well Log Plot in Matplotlib and Plotly
Adding a column of colour to a well log plot using Python
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Filtering by tag: visualisation (21)
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6 Ways to Customise Your Raincloud Plot
Splitting, highlighting, connecting means, tuning the cloud, styling the rain, and knowing when to go vertical
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When a Line Chart Becomes Spaghetti
Past a handful of series, a line chart stops letting you follow any of them. Here is what breaks and what to plot instead
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Why a Histogram Can Show You the Wrong Shape
How the number and position of bins can change what you think the distribution is telling you
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9 Scientific Data Plots and When They Fail
Every chart has a blind spot. Learn where common scientific visualisations start to hide the patterns that matter.
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What Your Scatter Plot Stops Showing You Once It Gets Crowded
Overplotting is easy to miss and easy to fix, once you stop asking your chart to show every point.
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From Default to Publication-Ready: The Raincloud Plot
Six steps between the chart ptitprince gives you and one you would want to put in a report
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Raincloud Plots with PtitPrince: See What Your Data Is Really Doing
Three views of your data distribution in one function call
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From Boxplot to Raincloud: Building a Better Distribution Plot in Python
Constructing a raincloud plot one layer at a time
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How to Visualise Missing Data with an Interactive Plotly Heatmap
Explore well log data completeness with interactive heatmaps
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Boxplots Are Hiding Your Data. Here’s a Simple Fix
How overlaying raw data points reveals what your summary statistics quietly discard
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From Default to Publication-Ready: Transforming Matplotlib Histograms
Seven Steps From a Default Chart to Something Worth Publishing
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Ridgeline Plots in Matplotlib: An Underused Way to Compare Distributions
Build stacked KDE plots from scratch and with joypy to show shape, skew, and spread across multiple groups
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Why Whole-Well Completeness Numbers Can Hide Critical Data Gaps
Visualising Well Log Data Availability by Formation Across Multiple Wells
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3 Python Charts You’re Probably Not Using (But Should Be)
Three underused chart types and when to reach for them when working with well log data
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From Default to Publication-Ready: Transforming Matplotlib Heatmaps in 8 Steps
Take a Basic Well Log Data Availability Heatmap and Make It Something Worth Putting in a Report
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Tables, Pretty Prints, and Sanity: Python Output for Geoscience Data
Three simple libraries to make console output readable, useful and even stylish
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Adding Gradient Backgrounds to Plotly Charts
Using Plotly rectangle shapes to improve data visualisation
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Adding Inset Axes to Matplotlib Figures
A quick visual QC workflow using crossplots to surface tool issues and depth shifts.
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4 Essential Tools to Help You Select a Colour Palette for Your Data Visualisation
Tools for Making it Easy to Select Colour Palettes for Data Visualisations
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