Matplotlib: How to implement custom tick frequency on a logarithmic scale for multiple subplots?
I've encountered a strange issue with I've been banging my head against this for hours. I'm reviewing some code and I keep running into After trying multiple solutions online, I still can't figure this out. I'm working on a project where I need to create multiple subplots with a logarithmic y-axis, but I'm struggling to set custom tick frequencies for each subplot. I'm using Matplotlib version 3.5.1. My goal is to have specific ticks that represent important data points, and I want these ticks to differ across subplots. Here's a simplified version of my code: ```python import matplotlib.pyplot as plt import numpy as np x = np.linspace(1, 100, 100) y1 = np.log10(x) y2 = np.log10(x * 10) y3 = np.log10(x ** 2) fig, axs = plt.subplots(3, 1, figsize=(8, 12)) axs[0].plot(x, y1) axs[1].plot(x, y2) axs[2].plot(x, y3) # Set the y-axis to logarithmic scale axs[0].set_yscale('log') axs[1].set_yscale('log') axs[2].set_yscale('log') plt.show() ``` When I run this code, the y-axis is set to logarithmic, but I don't know how to customize the ticks. I've tried using `axs[i].set_yticks()` with a list of values according to my needs, but it seems like the ticks aren’t appearing correctly, especially for the second subplot. Instead, it just shows default ticks that are far apart and don’t correlate with my data. Here’s what I tried to customize the ticks: ```python axs[0].set_yticks([1, 10, 100]) # for first subplot axs[1].set_yticks([10, 100, 1000]) # for second subplot axs[2].set_yticks([1, 10, 100]) # for third subplot ``` Even though I set the ticks, I still see the default logarithmic ticks alongside mine. I need to ensure that only my custom ticks are displayed. Additionally, is there a way to format the ticks to show them as integers (like `1`, `10`, `100` instead of `10^0`, `10^1`, etc.)? Any advice or examples would be greatly appreciated! I'm working on a API that needs to handle this. I'm coming from a different tech stack and learning Python. Could this be a known issue? I'm coming from a different tech stack and learning Python. This is my first time working with Python stable. Thanks in advance! How would you solve this?