👀 Views: 71 💬 Answers: 1 📅 Created: 2025-06-14

matplotlib scatter-plot nan-values data-visualization Python

I've been working on this all day and I've encountered a strange issue with I need help solving I'm trying to create a scatter plot using Matplotlib (version 3.4.3), where I want to represent data points with colors based on their values using a colormap... However, I've noticed that my plot has unexpected gaps in areas where I have NaN values in my dataset. I expected those points to either be skipped or to have some default color applied, but instead, they seem to create strange gaps in the visualization. Here's the code I've been using: ```python import numpy as np import matplotlib.pyplot as plt import matplotlib.cm as cm # Sample data with NaN values x = np.array([1, 2, 3, 4, 5, 6]) y = np.array([1, 4, np.nan, 16, 25, 36]) colors = np.array([10, 20, np.nan, 40, 50, 60]) # Normalizing the color values norm = plt.Normalize(colors.min(), colors.max()) plt.scatter(x, y, c=colors, cmap='viridis', norm=norm) plt.colorbar(label='Color scale') plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.title('Scatter plot with NaN values') plt.show() ``` I've tried using `np.nan_to_num(colors)` to replace NaNs with zeros, but it didn't solve the scenario as it just made the corresponding scatter points show up at a different location. I've also checked the documentation for `scatter`, but I couldn't find any specific mention of how NaN values are treated. Can anyone guide to understand why these gaps are appearing and how to properly handle NaNs to ensure that my plot looks clean? Is there a recommended best practice for dealing with missing or NaN values in scatter plots using colormaps? For context: I'm using Python on Windows 11. This is for a CLI tool running on macOS. Thanks in advance!