search
HomeBackend DevelopmentPython TutorialHow to Correctly Set Y-Axis Limits in Matplotlib?

How to Correctly Set Y-Axis Limits in Matplotlib?

Setting Axis Limits in Matplotlib

Question:

Faced with an unsuccessful attempt to set the y-axis limits on a Matplotlib plot, a user seeks guidance on how to achieve the desired limits using the following code:

import matplotlib.pyplot as plt

plt.figure(1, figsize = (8.5,11))
plt.suptitle('plot title')
ax = []
aPlot = plt.subplot(321, axisbg = 'w', title = "Year 1")
ax.append(aPlot)
plt.plot(paramValues,plotDataPrice[0], color = '#340B8C', 
     marker = 'o', ms = 5, mfc = '#EB1717')
plt.xticks(paramValues)
plt.ylabel('Average Price')
plt.xlabel('Mark-up')
plt.grid(True)
plt.ylim((25,250))

Despite setting plt.ylim((25,250)), the y-axis limits default to 20 and 200. How can the limits be adjusted to the intended 20 and 250?

Answer:

To set the axis limits in Matplotlib, one needs to access the current axis using plt.gca(). Once the current axis is obtained, the limits can be set using the set_ylim() method. The following code snippet demonstrates this:

ax = plt.gca()
ax.set_ylim([20, 250])

By implementing this modification, the y-axis limits will be successfully adjusted to the desired 20 and 250.

The above is the detailed content of How to Correctly Set Y-Axis Limits 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
How do you create multi-dimensional arrays using NumPy?How do you create multi-dimensional arrays using NumPy?Apr 29, 2025 am 12:27 AM

Create multi-dimensional arrays with NumPy can be achieved through the following steps: 1) Use the numpy.array() function to create an array, such as np.array([[1,2,3],[4,5,6]]) to create a 2D array; 2) Use np.zeros(), np.ones(), np.random.random() and other functions to create an array filled with specific values; 3) Understand the shape and size properties of the array to ensure that the length of the sub-array is consistent and avoid errors; 4) Use the np.reshape() function to change the shape of the array; 5) Pay attention to memory usage to ensure that the code is clear and efficient.

Explain the concept of 'broadcasting' in NumPy arrays.Explain the concept of 'broadcasting' in NumPy arrays.Apr 29, 2025 am 12:23 AM

BroadcastinginNumPyisamethodtoperformoperationsonarraysofdifferentshapesbyautomaticallyaligningthem.Itsimplifiescode,enhancesreadability,andboostsperformance.Here'showitworks:1)Smallerarraysarepaddedwithonestomatchdimensions.2)Compatibledimensionsare

Explain how to choose between lists, array.array, and NumPy arrays for data storage.Explain how to choose between lists, array.array, and NumPy arrays for data storage.Apr 29, 2025 am 12:20 AM

ForPythondatastorage,chooselistsforflexibilitywithmixeddatatypes,array.arrayformemory-efficienthomogeneousnumericaldata,andNumPyarraysforadvancednumericalcomputing.Listsareversatilebutlessefficientforlargenumericaldatasets;array.arrayoffersamiddlegro

Give an example of a scenario where using a Python list would be more appropriate than using an array.Give an example of a scenario where using a Python list would be more appropriate than using an array.Apr 29, 2025 am 12:17 AM

Pythonlistsarebetterthanarraysformanagingdiversedatatypes.1)Listscanholdelementsofdifferenttypes,2)theyaredynamic,allowingeasyadditionsandremovals,3)theyofferintuitiveoperationslikeslicing,but4)theyarelessmemory-efficientandslowerforlargedatasets.

How do you access elements in a Python array?How do you access elements in a Python array?Apr 29, 2025 am 12:11 AM

ToaccesselementsinaPythonarray,useindexing:my_array[2]accessesthethirdelement,returning3.Pythonuseszero-basedindexing.1)Usepositiveandnegativeindexing:my_list[0]forthefirstelement,my_list[-1]forthelast.2)Useslicingforarange:my_list[1:5]extractselemen

Is Tuple Comprehension possible in Python? If yes, how and if not why?Is Tuple Comprehension possible in Python? If yes, how and if not why?Apr 28, 2025 pm 04:34 PM

Article discusses impossibility of tuple comprehension in Python due to syntax ambiguity. Alternatives like using tuple() with generator expressions are suggested for creating tuples efficiently.(159 characters)

What are Modules and Packages in Python?What are Modules and Packages in Python?Apr 28, 2025 pm 04:33 PM

The article explains modules and packages in Python, their differences, and usage. Modules are single files, while packages are directories with an __init__.py file, organizing related modules hierarchically.

What is docstring in Python?What is docstring in Python?Apr 28, 2025 pm 04:30 PM

Article discusses docstrings in Python, their usage, and benefits. Main issue: importance of docstrings for code documentation and accessibility.

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

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)