In this tutorial, we will look at how to change the tick frequency in a matplotlib plot with the help of some examples.

You can change the number of ticks in matplotlib in the following two ways –

- Using the
`maplotlib.pyplot`

object’s`xticks()`

and the`yticks()`

functions to modify the ticks on the x-axis and the y-axis respectively. - You can also use the
`maplolib.pyplot`

object’s`locator_params()`

function to specify the number of ticks on a specific axis.

Let’s now look at both methods with some examples.

First, we will create a plot that we will use throughout this tutorial.

import matplotlib.pyplot as plt # x values - years x = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020] # y values - curde oil price per barrel in USD y = [94.88, 94.05, 97.98, 93.17, 48.66, 43.29, 50.80, 65.23, 56.99, 39.68] # plot x and y on a line plot plt.plot(x, y) # add axes labels plt.xlabel('Year') plt.ylabel('Crude oil price USD/barrel')

Output:

## Example 1 – Change the number of ticks on the x-axis

The `matplotlib.pyplot.xticks()`

function takes `ticks`

and `labels`

as parameters. You can pass the tick locations as an array to the `ticks`

parameter and the corresponding tick labels to the `labels`

parameter. In the above plot, we see that there are only 5 tick values, let’s now get a tick for each value in the `x`

list.

# plot x and y on a line plot plt.plot(x, y) # add axes labels plt.xlabel('Year') plt.ylabel('Crude oil price USD/barrel') # specify the ticks and its frequency plt.xticks(x) # draw the plot plt.draw()

Output:

There are now 10 ticks on the x-axis.

Alternatively, we can use the `maplotlib.pyplot.locator_params()`

function and only specify the **number of ticks** we want (instead of specifying the actual tick locations like above).

The `matplotlib.pylot.locator_params()`

function takes `axis`

and `nbins`

as parameters. Specify the axis to which you want to apply these settings with the `axis`

parameter and the number of ticks you want to the `nbins`

parameter.

# plot x and y on a line plot plt.plot(x, y) # add axes labels plt.xlabel('Year') plt.ylabel('Crude oil price USD/barrel') # specify the number of ticks on the x-axis plt.locator_params(axis='x', nbins=10) # draw the plot plt.draw()

Output:

We get the same result as above.

## Example 2 – Change the number of ticks on the y-axis

You can similarly change the number of ticks on the y-axis.

Use the `mapltolib.pyplot.yticks()`

function to give custom ticks and tick labels to the plot. Let’s change the number of ticks on the y-axis to 3 in the original scatter plot.

import numpy as np # plot x and y on a line plot plt.plot(x, y) # add axes labels plt.xlabel('Year') plt.ylabel('Crude oil price USD/barrel') # specify use 3 equally spaced values between min and max values as yticks plt.yticks(np.linspace(min(y), max(y), 3)) # draw the plot plt.draw()

Output:

The y-axis now has only 3 ticks.

Alternatively, use the `maplotlib.pyplot.locator_params()`

functions and specify the number of ticks for the y-axis.

# plot x and y on a line plot plt.plot(x, y) # add axes labels plt.xlabel('Year') plt.ylabel('Crude oil price USD/barrel') # specify the number of ticks on the y-axis plt.locator_params(axis='y', nbins=3) # draw the plot plt.draw()

Output:

## Example 3 – Changing the number of ticks on subplots

You can similarly change the number of ticks (on the x-axis and/or the y-axis) on subplots with the corresponding matplotlib axes object functions.

- Use the axes object’s
`set_xticks()`

function to change the ticks on the x-axis and the`set_yticks()`

function to change the ticks on the y-axis. - Alternatively, you can use the axes object’s
`locator_params()`

function.

Let’s look at an example –

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 5)) # plot the first subplot ax1.plot(x, y) # add axis labels ax1.set_xlabel('Year') ax1.set_ylabel('Crude oil price USD/barrel') # plot the second subplot ax2.plot(x, y) # add axis labels ax2.set_xlabel('Year') ax2.set_ylabel('Crude oil price USD/barrel')

Output:

Here, we created two subplots. Both the subplots have the same data but that is not important. Let’s see how to modify the number of ticks in the above subplots.

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 5)) # plot the first subplot ax1.plot(x, y) # add axis labels ax1.set_xlabel('Year') ax1.set_ylabel('Crude oil price USD/barrel') # change number of ticks to 10 on the x-axis ax1.set_xticks(x) # plot the second subplot ax2.plot(x, y) # add axis labels ax2.set_xlabel('Year') ax2.set_ylabel('Crude oil price USD/barrel') # change number of ticks to 10 on the x-axis ax2.locator_params(axis='x', nbins=10)

Output:

To change the number of ticks on the axis we used –

- For the first subplot, the axes object’s
`set_xticks()`

function. - For the second subplot, the axes object’s
`locator_params()`

function.

You might also be interested in –

- Remove Tick Labels from a Plot in Matplotlib
- Set Axis Range (axis limits) in Matplotlib Plots
- Show Gridlines on Matplotlib Plots
- How to Label Points on a Scatter Plot in Matplotlib?
- Reverse Axes of a Plot in Matplotlib
- Rotate Axis Labels in Matplotlib with Examples and Output

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