Matplotlib set_xticks – Detailed tutorial

In this Python Matplotlib tutorial, we will discuss Matplotlib set_xticks in matplotlib. Here we will cover different examples related to set_xticks using matplotlib. And we will also cover the following topics:

• Matplotlib set_xticks
• Matplotlib set_xticks invisible
• Matplotlib set_xticks rotation
• Matplotlib set_xticks fontsize
• Matplotlib set_xtciks labels
• Matplotlib set_xticks vertical
• Matplotlib set_xticks direction
• Matplotlib set_xticks length
• Matplotlib set_xticks color
• Matplotlib barplot set_xticks
• Matplotlib histogram set_xticks
• Matplotlib colorbar set_xticks
• Matplotlib set_xticks subplot
• Matplotlib set_xticks log scale
• Matplotlib set ticks right
• Matplotlib set ticks top
• Matplotlib set ticks every
• Matplotlib set_xticks range
• Matplotlib set minor ticks interval
• Matplotlib set xticks pad
• Matplotlib set xticks as text
• Matplotlib set theta ticks

Matplotlib set_xticks

In this section, we will learn about the set_xticks() function in the axes module of matplotlib in Python. The set_xticks() function is used to set the x ticks location.

The syntax is given below:

matplotlib.axes.Axes.set_xticks(ticks, labels=None, *, minor=False, **kwargs) 

The following are the parameters:

Parameters	Value	Description
ticks	list of floats	Set tick locations.
labels	list of string	Set a list of tick labels. If the list is not passed, it shows the data values.
minor	bool By default: False	Specify whether you want to set minor ticks or not.
kwargs		Text properties for the labels and ticks.

Let’s see an example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt

# Create figure and subplots

fig, ax = plt.subplots()
   
# Define Data Coordinates

x = np.linspace(0, 20 , 100)
y = np.sin(x)

# Plot

plt.plot(x, y)

# Set ticks

ax.set_xticks(np.arange(0, len(x)+1, 5))

# Add Title
 
fig.suptitle('set_xticks Example', fontweight ="bold")
               
# Display
               
plt.show()

Explanation:

• Import important libraries such as numpy, matplotlib.pyplot.
• After this, we create a subplot by using the subplots () method.
• To define data coordinates, we use linespace() and sin() methods of numpy.
• To set the x ticks, use set_xticks().
• To add a title to the figure, use suptitle() method.
• To visualize the plot on the user’s screen, use the show() method.

Read Matplotlib plot a line

Matplotlib set_xtciks invisible

Here we’ll learn to hide the ticks from the x-axis. For this, we have to pass the empty list to the set_xticks() method.

# Import Library

import numpy as np
import matplotlib.pyplot as plt

# Create figure and subplots

fig, ax = plt.subplots()
   
# Define Data Coordinates

x = np.linspace(0, 20 , 100)
y = np.tan(x)

# Plot

plt.plot(x, y)

# Set ticks invisible

ax.set_xticks([])
          
# Display
               
plt.show()

Here we use the set_xticks() method to set the x-axis ticks location. To make ticks invisible we pass an empty string to the method.

Output:

Read Python plot multiple lines using Matplotlib

Matplotlib set_xticks rotation

We’ll change the rotation of ticks at the x-axis. To change the rotation we pass the rotation parameter to the plt.xticks() method.

Let’s see an example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt
 
# Define Data Coordinates

x = np.linspace(0, 20 , 100)
y = np.cos(x)

# Plot

plt.plot(x, y)

# Set ticks Rotation

plt.xticks(rotation=45)
          
# Display
               
plt.show()

• Here we import matplotlib.pyplot and numpy library.
• Next, we define data coordinates using numpy.
• To plot the line chart, use the plot() method.
• To rotate the ticks at the x-axis, use the plt.xticks() method and pass the rotation argument to it.

Read What is matplotlib inline

Matplotlib set_xticks fontsize

Here we’ll see an example to change the fontsize of ticks at the x-axis. to change the fontsize we pass the fontsize argument to the plt.xticks() function.

Example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt
 
# Define Data Coordinates

x = np.linspace(0, 20 , 100)
y = np.exp(x)

# Plot

plt.plot(x, y)

# Set ticks Fontsize

plt.xticks(fontsize=13)
          
# Display
               
plt.show()

Output:

Read Matplotlib plot bar chart

Matplotlib set_xtciks labels

Here we’ll learn to set the location of ticks and also to add labels at the x-axis in matplotlib.

Let’s see an example:

# Import Library

import matplotlib.pyplot as plt
 
# Define Data Coordinates

x = [0, 1, 2, 3, 4, 5]
y = [1, 2.5, 4, 3.3, 10, 8]

# Plot

plt.plot(x, y)

# Set ticks Labels

plt.xticks([0, 1, 2, 3, 4, 5],['Term-1','Term-2','Term-3','Term-4', 'Term-5', 'Term-6'])
          
# Display
               
plt.show()

In the above example, we use the plt.xticks() method to add labels and ticks at x-axis manually.

Read Matplotlib subplot tutorial

Matplotlib set_xticks vertical

Here we’ll learn to rotate x-axis ticks vertically in Matplotlib.

Example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt
 
# Define Data Coordinates

x = np.linspace(0, 200 , 100)
y = np.sin(x)

# Plot

plt.plot(x, y)

# Set ticks Rotation Vertical

plt.xticks(rotation='vertical')
          
# Display
               
plt.show()

In the above example, we use the plt.xticks() function with rotation argument to rotate the x ticks vertically.

Read Matplotlib best fit line

Matplotlib set_xticks direction

Here we’ll see an example where we change the direction of x-axis ticks in Python matplotlib.

Example:

# Import Library

import matplotlib.pyplot as plt
import numpy as np

# Define Data Coordinates

x = np.random.randint(450,size=(80))

# Plot

plt.plot(x)

# Set ticks direction

plt.tick_params(axis='x',direction='in')
          
# Display
               
plt.show()

Explanation:

• Here we define data coordinates using random.randint() method of numpy.
• To plot the line graph, use plot() method.
• To adjust the tick behaviour, we use tick_params() function with the direction argument. We specify it to in to get placement of ticks inwards.

Read Matplotlib set_xticklabels

Matplotlib set_xticks length

Here we’ll learn to change the length of ticks at the x-axis in Matplotlib python. To change the length of ticks pass length argument to the tick_params() method.

Let’s see an example:

# Import Library

import matplotlib.pyplot as plt
import numpy as np

# Define Data Coordinates

x = np.random.randint(500,size=(20))

# Plot

plt.plot(x,color='darkblue')

# Tick length

plt.tick_params(axis='x', length=12)
          
# Display
               
plt.show()

Read Matplotlib fill_between

Matplotlib set ticks width

Here we’ll learn to change the width of ticks at the x-axis in Matplotlib. To change the width pass width argument to the tick_params() method.

Let’s see an example:

# Import Library

import matplotlib.pyplot as plt
import numpy as np

# Define Data Coordinates

x = [0, 1, 2, 3, 4, 5]
y = [1, 2, 3, 4, 5, 6]

# Plot

plt.plot(x,y,color='lightgreen')

# Tick Width

plt.tick_params(axis='x', width=20)
          
# Display
               
plt.show()

Read Matplotlib set_yticklabels

Matplotlib set_xticks color

We’ll learn to change the color of ticks located at the x-axis in Python matplotlib.

Example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt

# Define Data Coordinates

x = np.linspace(0, 50 , 100)
y = np.tan(x)

# Plot

plt.plot(x, y)

# Set ticks color

plt.tick_params(axis='x', color='red', length=12, width=10)
          
# Display
               
plt.show()

In the above example, we use the tick_params() function with axis, color, length, and width argument and set their value to x, red, 12, and 10 respectively.

Read Matplotlib tight_layout

Matplotlib barplot set_xticks

We” learn to set locations of x ticks in barplot. To set the location, we use the set_xticks method of the axes module in matplotlib.

Example:

# Import Library


import numpy as np
import matplotlib.pyplot as plt

# Create figure and subplots

fig, ax = plt.subplots()
   
# Define Data Coordinates

x = [1, 2, 3, 4, 6]
y = [10, 20, 25, 15, 30]

# Plot

plt.bar(x, y, color='darkorange')

# Set ticks 

ax.set_xticks([0, 2, 4, 6, 8])
          
# Display
               
plt.show()

• In the above example, we define the data coordinates x and y to draw a bar chart using the bar() method.
• To set locations of the x ticks, use the set_xticks() method.

The output after setting the ticks:

Read Python Matplotlib tick_params + 29 examples

Matplotlib histogram set_xticks

We’ll learn to set the x ticks according to our choice. To change the default x ticks, use set_xticks() function in Matplotlib.

The steps to set the x-ticks in the histogram plot are as fellow:

• Import important libraries, such as matplotlib.pyplot, and numpy.
• To define data coordinates x and y use numpy random.randn() function.
• To plot the histogram chart between x and y, use the plt.hist() function.
• To set the edge colors for each of the bars in the histogram, use the edgecolor argument in the hist() method.
• To set the x ticks, use the set_xtick() method and we use the range() method of numpy to set the location of ticks.
• To visualize the user’s plot, use the plt.show() method.

Read Matplotlib x-axis label

Matplotlib colorbar set_xticks

Here we’ll learn to set x ticks at the color bar by using the set_ticks() function in matplotlib.

Let’s see an example:

# Import Libraries

import matplotlib.pyplot as plt
import numpy as np

# Define Data

x = np.array([99,86,88,111,103,87,94])
y = np.array([20,50,200,500,1000,60,75])
colors = np.array([0, 10, 20, 30, 40, 45, 50])

# Define scatter() function

plt.scatter(x, y, c=colors, cmap= 'PiYG')

# Colorbar


cbar = plt.colorbar()

# Set ticks

cbar.set_ticks(range(5, 30, 10))

# Display the graph

plt.show()

• In the above example, we import the matplotlib.pyplot and numpy library.
• Then we define the x, y and color data points in the form of an array.
• plt.scatter() method is used to draw markers for each data point and we pass the parameter ‘cmap’ to set the color map.
• plt.colorbar() method is used to show the color strip in the plot.
• Then we use the set_ticks() function to set the ticks at x-axis.
• Then we finally use the method plt.show() to display the plotted graph.

Read Matplotlib multiple bar chart

Matplotlib set_xtciks subplot

In this section, we’ll see an example where we use the Matplotlib set_xticks() function in a subplot.

Example:

# Importing Libraries

import numpy as np
import matplotlib.pyplot as plt

# Create subplot

fig, ax = plt.subplots(2, 2)

# Define Data

x1= [0.2, 0.4, 0.6, 0.8, 1]
y1= [0.3, 0.6, 0.8, 0.9, 1.5]

x2= [2, 6, 7, 9, 10]
y2= [3, 4, 6, 9, 12]

x3= [5, 8, 12]
y3= [3, 6, 9]

x4= [7, 8, 15]
y4= [6, 12, 18]

# Plot graph

ax[0, 0].plot(x1, y1)
ax[0, 1].plot(x2, y2)
ax[1, 0].plot(x3, y3)
ax[1, 1].plot(x4, y4)

# Set x-ticks

ax[0, 0].set_xticks([])
ax[0, 1].set_xticks([0, 1, 2, 3])
ax[1, 0].set_xticks(range(-5, 11))

# Auto layout

fig.tight_layout()

# Display Graph

plt.show()

• In the above example, we use the set_xticks() function in subplot 1 to invisible the x ticks.
• In subplot 2, we use the set_xticks() function to set x ticks manually.
• And In subplot 3, we use the set_xticks() function to set x ticks by using the range() method of numpy.

Read Matplotlib scatter plot legend

Matplotlib set_xticks log scale

Here we’ll create a plot with a log scale at the x-axis and also set the x ticks by using the set_xticks() function.

The following steps are used:

• To create a subplot, use plt.subplots() function.
• Define x and y data coordinates.
• To plot the lines, use plt.plot() method.
• To set log scale at x-axis, use set_xscale() method.
• To set the ticks at x-axis, use set_xticks() method.
• To display the plot, use plt.show() method.

Example:

# Importing Libraries

import numpy as np
import matplotlib.pyplot as plt

# Create subplot

fig, ax = plt.subplots()

# Define Data Coordinates

x = [50, 500, 5000, 50000]
y = [0, 1, 2, 3]

# Plot

plt.plot(x, y)

# Set log scale

ax.set_xscale('log')

# Set x ticks

ax.set_xticks([10, 100, 1000, 10000, 100000, 1000000, 
               10000000])

# Display

plt.show()

Read Matplotlib 3D scatter

Matplotlib set ticks right

Here we’ll learn to set ticks on the right side of the plot in matplotlib. To set the ticks, use the tick_params() method with the right argument and set its value to True.

The following is the syntax:

matplotlib.plot.tick_params(right=True)

Example:

# Importing Libraries

import numpy as np
import matplotlib.pyplot as plt

# Define Data Coordinates

x = np.arange(0, 100, 10)
y = np.sin(x)

# Plot

plt.plot(x, y)

# Right

plt.tick_params(right=True)

# Display

plt.show()

Read Stacked Bar Chart Matplotlib

Matplotlib set ticks top

Here we’ll learn to set ticks at top of the plot in Matplotlib. To set the ticks, use the tick_params() method with the top argument and set its value to True.

The following is the syntax:

matplotlib.plot.tick_params(top=True)

Example:

# Importing Libraries

import numpy as np
import matplotlib.pyplot as plt

# Define Data Coordinates

x = np.random.rand(100)

# Plot

plt.plot(x)

# Tick at top

plt.tick_params(top=True)

# Display

plt.show()

Read Matplotlib two y axes

Matplotlib set ticks every

Here we’ll learn to set ticks at every side of the plot in matplotlib.

Example:

# Importing Libraries

import numpy as np
import matplotlib.pyplot as plt

# Define Data Coordinates

x = np.random.rand(500)

# Plot

plt.plot(x)

# Set ticks everywhere


plt.tick_params(top=True, right=True, labelleft=False, 
                labelbottom=False)

# Display

plt.show()

• In the above example, we use the tick_params() method set the ticks at every side of the plot.
• To turn on the ticks at right and top of the plot, use the tick_params() method with top and right argument and set its bool value to True.
• To hide the labels from bottom and left side of the plot, use the tick_params() method with labelbottom, and labeltop argument and set its bool value to False.

Read Horizontal line matplotlib

Matplotlib set_xticks range

Here we set the location of x ticks by using the range() method in matplotlib.

Example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt

# Create subplot

fig, ax = plt.subplots()

# Define Data Coordinates

y = [0, 1, 2, 3, 5]
x = [0, 5, 8, 9, 15]

# Ticks using arange method

x_ticks = np.arange(0, 25, 5)
ax.set_xticks(x_ticks)

# Plot

plt.plot(x, y)

# Display


plt.show()

Explanation:

• In the above example, to create a ticks at the x-axis, we use arange() method of numpy.
• In arange() method we define starting value of the ticks, non-inclusive ending value and a step which specify space between the ticks.
• To set the location of x ticks, use set_xticks() method of axes module.

Read Draw vertical line matplotlib

Matplotlib set minor ticks interval

Here we’ll see an example, where we use the matplotlib set_xticks() method to set minor ticks bypassing minor argument to the method and setting its bool value to True.

Example:

# Import Libraries

import numpy as np
import matplotlib.pyplot as plt

# Create subplot

fig, ax = plt.subplots()

# Set minor ticks

minor_ticks = np.arange(0, 50, 2)
ax.set_xticks(minor_ticks, minor=True)

# Display

plt.show()

Read Matplotlib invert y axis

Matplotlib set xticks pad

Here we’ll learn to add space between ticks and tickslabel at the x-axis in matplotlib. For this, we use the tick_parmas() method with pad argument.

Let’s see an example:

# Import Library

import numpy as np
import matplotlib.pyplot as plt

# Define Data Coordinates

x = np.linspace(0, 50 , 100)
y = np.cos(x)

# Plot

plt.plot(x, y)

# Set xticks pad

plt.tick_params(axis='x', pad=30)
          
# Display
               
plt.show()

Read Put legend outside plot matplotlib

Matplotlib set xticks as text

Here we’ll learn to set x-ticks as text. For this, use xticks() function with ticks locations and ticks labels in matplotlib.

Example:

# Import Library

import matplotlib.pyplot as plt
import numpy as np

# Define Data Coordinates


x = [0, 1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10, 12]

# Plot

plt.plot(x, y)

# Set ticks as text

plt.xticks([0, 1, 2, 3, 4, 5],['Value-1','Value-2','Value-3','Value-4', 'Value-5', 'Value-6'])
          
# Display
               
plt.show()

• Firstly, we import the matplotlib.pyplot, and numpy library.
• Next, we define data coordinates and plotline chart using the plot() method.
• To set x ticks as text, use plt.xticks() method.

Read Matplotlib save as pdf + 13 examples

Matplotlib set theta ticks

Here we’ll see an example where we set x ticks as theta values in Python matplotlib. We use the xticks() method and pass ticks location and tick labels as theta.

Example:

# Import Library

import matplotlib.pyplot as plt

# Define Data Coordinates

x = [0, 1, 2, 3, 4, 5]
y = [5.8, 3, 2.6, 6, 9, 5.6]

# Plot

plt.plot(x, y)

# Set theta ticks

plt.xticks([1, 2, 3, 4],[r'2$\theta$', r'4$\theta$', r'6$\theta$', r'8$\theta$'])
          
# Display
               
plt.show()

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• Matplotlib title font size
• Matplotlib default figure size
• Matplotlib savefig blank image
• Matplotlib save as png
• Matplotlib bar chart labels

So, in this Python tutorial, we have discussed the “Matplotlib set_xticks” and we have also covered some examples related to it. These are the following topics that we have discussed in this tutorial.

• Matplotlib set_xticks
• Matplotlib set_xticks invisible
• Matplotlib set_xticks rotation
• Matplotlib set_xticks fontsize
• Matplotlib set_xtciks labels
• Matplotlib set_xticks vertical
• Matplotlib set_xticks direction
• Matplotlib set_xticks length
• Matplotlib set_xticks color
• Matplotlib barplot set_xticks
• Matplotlib histogram set_xticks
• Matplotlib colorbar set_xticks
• Matplotlib set_xticks subplot
• Matplotlib set_xticks log scale
• Matplotlib set ticks right
• Matplotlib set ticks top
• Matplotlib set ticks every
• Matplotlib set_xticks range
• Matplotlib set minor ticks interval
• Matplotlib set xticks pad
• Matplotlib set xticks as text
• Matplotlib set theta ticks