search
HomeBackend DevelopmentPython TutorialHow to Annotate Scatter Plot Data Points with Custom Text in Matplotlib?

How to Annotate Scatter Plot Data Points with Custom Text in Matplotlib?

Annotate Scatter Plot Data Points with Custom Text

In data visualization, scatter plots are commonly used to depict the relationship between two variables. To enhance the insights gained from such plots, annotating individual data points with specific information can be valuable. However, annotating each point with different text can pose a challenge.

import matplotlib.pyplot as plt

# Define sample data
x = [0.15, 0.3, 0.45, 0.6, 0.75]
y = [2.56422, 3.77284, 3.52623, 3.51468, 3.02199]
n = [58, 651, 393, 203, 123]

# Create the scatter plot
fig, ax = plt.subplots()
ax.scatter(x, y)

Traditional plotting methods don't support annotating points with separate text from lists. Therefore, a workaround is required.

# Iterate over the annotation text and annotate each point
for i, txt in enumerate(n):
    ax.annotate(txt, (x[i], y[i]))

The annotate() function allows for customization of the annotation, including its position and text formatting. By iterating through the list of annotation text, you can assign specific values to each data point.

# Customize the annotation format
ax.annotate(txt, (x[i], y[i]), xytext=(0, 0), textcoords='offset points',
            bbox=dict(boxstyle='round', fc='w'), arrowprops=dict(arrowstyle='->'))

By utilizing annotate() and iterating over the annotation text, you can add customized text to individual data points in a scatter plot, providing valuable insights into the underlying data.

The above is the detailed content of How to Annotate Scatter Plot Data Points with Custom Text in Matplotlib?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Explain the performance differences in element-wise operations between lists and arrays.Explain the performance differences in element-wise operations between lists and arrays.May 06, 2025 am 12:15 AM

Arraysarebetterforelement-wiseoperationsduetofasteraccessandoptimizedimplementations.1)Arrayshavecontiguousmemoryfordirectaccess,enhancingperformance.2)Listsareflexiblebutslowerduetopotentialdynamicresizing.3)Forlargedatasets,arrays,especiallywithlib

How can you perform mathematical operations on entire NumPy arrays efficiently?How can you perform mathematical operations on entire NumPy arrays efficiently?May 06, 2025 am 12:15 AM

Mathematical operations of the entire array in NumPy can be efficiently implemented through vectorized operations. 1) Use simple operators such as addition (arr 2) to perform operations on arrays. 2) NumPy uses the underlying C language library, which improves the computing speed. 3) You can perform complex operations such as multiplication, division, and exponents. 4) Pay attention to broadcast operations to ensure that the array shape is compatible. 5) Using NumPy functions such as np.sum() can significantly improve performance.

How do you insert elements into a Python array?How do you insert elements into a Python array?May 06, 2025 am 12:14 AM

In Python, there are two main methods for inserting elements into a list: 1) Using the insert(index, value) method, you can insert elements at the specified index, but inserting at the beginning of a large list is inefficient; 2) Using the append(value) method, add elements at the end of the list, which is highly efficient. For large lists, it is recommended to use append() or consider using deque or NumPy arrays to optimize performance.

How can you make a Python script executable on both Unix and Windows?How can you make a Python script executable on both Unix and Windows?May 06, 2025 am 12:13 AM

TomakeaPythonscriptexecutableonbothUnixandWindows:1)Addashebangline(#!/usr/bin/envpython3)andusechmod xtomakeitexecutableonUnix.2)OnWindows,ensurePythonisinstalledandassociatedwith.pyfiles,oruseabatchfile(run.bat)torunthescript.

What should you check if you get a 'command not found' error when trying to run a script?What should you check if you get a 'command not found' error when trying to run a script?May 06, 2025 am 12:03 AM

When encountering a "commandnotfound" error, the following points should be checked: 1. Confirm that the script exists and the path is correct; 2. Check file permissions and use chmod to add execution permissions if necessary; 3. Make sure the script interpreter is installed and in PATH; 4. Verify that the shebang line at the beginning of the script is correct. Doing so can effectively solve the script operation problem and ensure the coding process is smooth.

Why are arrays generally more memory-efficient than lists for storing numerical data?Why are arrays generally more memory-efficient than lists for storing numerical data?May 05, 2025 am 12:15 AM

Arraysaregenerallymorememory-efficientthanlistsforstoringnumericaldataduetotheirfixed-sizenatureanddirectmemoryaccess.1)Arraysstoreelementsinacontiguousblock,reducingoverheadfrompointersormetadata.2)Lists,oftenimplementedasdynamicarraysorlinkedstruct

How can you convert a Python list to a Python array?How can you convert a Python list to a Python array?May 05, 2025 am 12:10 AM

ToconvertaPythonlisttoanarray,usethearraymodule:1)Importthearraymodule,2)Createalist,3)Usearray(typecode,list)toconvertit,specifyingthetypecodelike'i'forintegers.Thisconversionoptimizesmemoryusageforhomogeneousdata,enhancingperformanceinnumericalcomp

Can you store different data types in the same Python list? Give an example.Can you store different data types in the same Python list? Give an example.May 05, 2025 am 12:10 AM

Python lists can store different types of data. The example list contains integers, strings, floating point numbers, booleans, nested lists, and dictionaries. List flexibility is valuable in data processing and prototyping, but it needs to be used with caution to ensure the readability and maintainability of the code.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

VSCode Windows 64-bit Download

VSCode Windows 64-bit Download

A free and powerful IDE editor launched by Microsoft

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

SecLists

SecLists

SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment