calendar Sept. 25, 2024
by user James Kelly  

Creating powerful visuals doesn’t have to be complicated. Whether you're using Python (Matplotlib) or Excel, these five tips will help you build impactful plots that communicate your message effectively:

  1. Choose colours thoughtfully:
    • Excel: Use the "Format Chart" options to choose from a range of colour palettes, and ensure you stick to complementary or contrasting colours. You can also use the "Change Colours" feature to apply a consistent scheme across your plot.
    • Python (Matplotlib): Use the plt.scatter() or plt.plot() functions with the c or color parameter. You can also use predefined colour maps like plt.cm.coolwarm for consistency.
Adding colour in python: 
plt.scatter(x, y, c='darkblue')  # or use color maps like 'cmap=plt.cm.viridis'

2. Use consistent scales:

  • Excel: Ensure that the scales of your axes are consistent by right-clicking on the axis, selecting "Format Axis", and setting the same range for related plots.
  • Python (Matplotlib): You can fix axis scales using plt.xlim() and plt.ylim() to maintain uniformity across multiple graphs.
Set axis limits in python: 
plt.xlim(0, 100)  # Set consistent limits for x-axis
plt.ylim(0, 50)   # Set consistent limits for y-axis

3. Label clearly:

  • Excel: Use "Chart Elements" to add axis titles and chart titles. Ensure the text is descriptive and easy to read.
  • Python (Matplotlib): Use plt.xlabel(), plt.ylabel(), and plt.title() to add meaningful labels to your plots.
Creating axis labels in python 
plt.xlabel('X Axis Label')
plt.ylabel('Y Axis Label')
plt.title('Descriptive Chart Title')

4. Simplify the design:

  • Excel: Remove gridlines and unnecessary elements by right-clicking on them and selecting "Delete" or unticking "Gridlines" in the Chart Elements menu.
  • Python (Matplotlib): Use plt.grid(False) to turn off gridlines and avoid adding excessive plot markers or 3D effects.
Remove gridlines 
plt.grid(False)  # Disable gridlines for a cleaner look

5. Highlight key data:

  • Excel: Use "Conditional Formatting" to apply bold colours to specific data points or right-click on key data series and choose "Format Data Series" to customise its appearance.
  • Python (Matplotlib): You can pass a specific colour to certain data points or use the alpha parameter for transparency. Highlight specific points by using a different marker style or colour.
Highlight key data in python 
plt.scatter(x, y, c='lightgrey')  # Default
plt.scatter(x[important], y[important], c='red', s=100)  # Highlight key points

Make your visuals as clear as your message! 🎨📊
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