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I have a scatter plot that displays the x (columns numbered 1 to 153) and y (mean of the column values), with a 95% confidence interval.

Since the plot is quite small, I wanted to show the ticks at every x position, but only have the labels every 10 elements.

Below is the code I started with:

df.sort_values(by=["Peak number"], inplace=True)
columns = list(df.iloc[:,2:].columns)
columns = np.asarray(columns, dtype='float')
means = df.iloc[:,2:].mean(axis = 0)

fig, ax = plt.subplots(figsize=(8, 6))
ax.plot(columns, means, "-", color="0.1", linewidth=1.5, alpha=0.5, label="Fit")  
ax.set_xlabel('Peak number')
ax.set_ylabel('Mean ratio')

Graph with many tick labels

Using the Matplotlib documentation error guide, I tried ensuring my x values were integer numbers, but to no avail. columns = np.asarray(columns, dtype='float')

Following that, I tried to manually set the x-axis tick labels using the xticks function. While that solved part of the issue (ie. only displayed the labels that I wanted), it didn't display the ticks without labels for all other x values. plt.xticks(np.arange(0, len(columns) + 1, 10)) Only wanted labels, but no ticks

Alternatively, I could remove all the tick labels, including the ones I wanted to keep. ax.set_xticks(np.arange(0, len(columns) + 1, 1), "") All ticks, but not wanted labels

Essentially, I am trying to combine removing all tick labels, with manually including only the labels that I want. Is there a way to do this simply?

Trenton McKinney
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user22037973
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1 Answers1

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You can follow the major and minor ticks documentation from Matplotlib.

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import numpy as np

plt.close("all")

x = np.arange(0, 100, 0.1)
y = np.sin(x)

fig, ax = plt.subplots()
ax.plot(x, y)

# major ticks every 10
ax.xaxis.set_major_locator(MultipleLocator(10))

# minor ticks at every point
ax.xaxis.set_minor_locator(MultipleLocator(1))

fig.show()

jared
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