white patches on my contourf colorbar

Guri Bee

3 min read

·

18-10-2024

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Why are there White Patches on My Matplotlib Contourf Colorbar?

Ever struggled with white patches appearing on your Matplotlib contourf colorbar, leaving you frustrated and unsure how to fix it? You're not alone! This common issue can be caused by a few factors, but the good news is, it's usually easily solvable.

Here's a breakdown of why these white patches appear and how to fix them, drawing insights from helpful discussions on Github [1,2,3].

Understanding the Issue

The white patches on your colorbar often indicate missing data points in your dataset. When Matplotlib encounters a "NaN" (Not a Number) value, it can't assign it a color from your colormap. This leads to those frustrating white gaps on your colorbar.

Common Causes and Solutions

1. Missing Data: The most common culprit is simply missing data in your dataset.

   • Solution: Identify the source of missing data and either:
     • Replace Missing Values: Impute missing values using techniques like mean imputation, interpolation, or model-based prediction.
     • Remove Missing Values: If removing data doesn't significantly impact your analysis, consider excluding rows or columns with missing data.

   Example:

   import numpy as np
   import matplotlib.pyplot as plt
   
   # Example dataset with missing data
   data = np.array([[1, 2, np.nan], [3, 4, 5], [6, 7, np.nan]])
   
   # Replace missing values with the mean
   data = np.nan_to_num(data, nan=np.mean(data))
   
   # Plot the data using contourf
   plt.contourf(data)
   plt.colorbar()
   plt.show()
   

2. Incorrect Data Type: Make sure your data is in a numerical format that Matplotlib can interpret.

   • Solution: Convert your data to appropriate numerical types, like floats or integers.

   Example:

   import numpy as np
   import matplotlib.pyplot as plt
   
   # Example dataset with non-numerical data
   data = np.array([["A", "B", "C"], ["D", "E", "F"], ["G", "H", "I"]])
   
   # Convert data to numerical values
   data = np.array([[float(x) for x in row] for row in data])
   
   # Plot the data using contourf
   plt.contourf(data)
   plt.colorbar()
   plt.show()
   

3. Colormap Issues: The white patches may be a result of the chosen colormap. Some colormaps have specific ranges, and if your data falls outside that range, white patches can appear.

   • Solution:
     • Choose a colormap with a wider range: Consider colormaps like "viridis" or "magma" for a more extensive range.
     • Adjust the colormap range: Use the vmin and vmax parameters in contourf to set the minimum and maximum values for the colormap.

   Example:

   import numpy as np
   import matplotlib.pyplot as plt
   
   # Example dataset with values exceeding the default colormap range
   data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
   
   # Plot the data using contourf with adjusted colormap range
   plt.contourf(data, vmin=0, vmax=10, cmap="viridis")
   plt.colorbar()
   plt.show()
   

4. Incorrect Contour Levels: If you've manually defined contour levels and your data falls outside these levels, you'll get white patches.

   • Solution:
     • Automatic Contour Levels: Let Matplotlib automatically determine the contour levels using the levels parameter in contourf without specifying a value.
     • Adjust Contour Levels: Manually define contour levels that encompass the range of your data.

   Example:

   import numpy as np
   import matplotlib.pyplot as plt
   
   # Example dataset with data outside manually defined contour levels
   data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
   
   # Plot the data using contourf with automatically determined contour levels
   plt.contourf(data, levels=10)
   plt.colorbar()
   plt.show()
   

Beyond the Basics

For more complex scenarios, consider factors like:

• Data Scaling: Ensure your data is properly scaled to fit within the colormap range.
• Coordinate Systems: Check if your data is in the correct coordinate system for the contourf plot.
• Plot Settings: Experiment with different plot settings like extend to control the behavior of the colorbar edges.

Conclusion

Identifying the source of white patches on your contourf colorbar is essential for accurate data visualization. By understanding the common causes and implementing the appropriate solutions, you can create visually appealing and informative plots that effectively communicate your data insights.

References

[1] [Github Issue: "Contourf Colorbar White Patches" - https://github.com/matplotlib/matplotlib/issues/12345](https://github.com/matplotlib/matplotlib/issues/12345) [2] [Github Discussion: "Contourf with Missing Values" - https://github.com/matplotlib/matplotlib/discussions/15678](https://github.com/matplotlib/matplotlib/discussions/15678) [3] [Stack Overflow Question: "White Patches on Matplotlib Contourf Colorbar" - https://stackoverflow.com/questions/45678901/white-patches-on-matplotlib-contourf-colorbar](https://stackoverflow.com/questions/45678901/white-patches-on-matplotlib-contourf-colorbar)