Skip to content
    geeksforgeeks
    • Interview Prep
      • DSA
      • Interview Corner
      • Aptitude & Reasoning
      • Practice Coding Problems
      • All Courses
    • Tutorials
      • Python
      • Java
      • ML & Data Science
      • Programming Languages
      • Web Development
      • CS Subjects
      • DevOps
      • Software and Tools
      • School Learning
    • Tracks
      • Languages
        • Python
        • C
        • C++
        • Java
        • Advanced Java
        • SQL
        • JavaScript
        • C#
      • Interview Preparation
        • GfG 160
        • GfG 360
        • System Design
        • Core Subjects
        • Interview Questions
        • Interview Puzzles
        • Aptitude and Reasoning
        • Product Management
        • Computer Organisation and Architecture
      • Data Science
        • Python
        • Data Analytics
        • Complete Data Science
        • Gen AI
        • Agentic AI
      • Dev Skills
        • Full-Stack Web Dev
        • DevOps
        • Software Testing
        • CyberSecurity
        • NextJS
        • Git
      • Tools
        • Computer Fundamentals
        • AI Tools
        • MS Excel & Google Sheets
        • MS Word & Google Docs
      • Maths
        • Maths For Computer Science
        • Engineering Mathematics
        • School Maths
    • Python Tutorial
    • Data Types
    • Interview Questions
    • Examples
    • Quizzes
    • DSA Python
    • Data Science
    • NumPy
    • Pandas
    • Practice
    • Django
    • Flask
    • Projects
    Open In App

    Matplotlib.pyplot.fill_between() in Python

    Last Updated : 12 Jul, 2025
    Comments
    Improve
    Suggest changes
    2 Likes
    Like
    Report
    See More

    Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

    matplotlib.pyplot.fill_between()

    The matplotlib.pyplot.fill_between() is used to fill area between two horizontal curves. Two points (x, y1) and (x, y2) define the curves. this creates one or more polygons describing the filled areas. The 'where' parameter can be used to selectively fill some areas. By default, edges connect the given points directly. The 'step' parameter is used if the filling needs to be a step function.

    Syntax: matplotlib.pyplot.fill_between(x, y1, y2=0, where=None, step=None, interpolate=False, *, data=None, **kwargs) Parameters:

    1. x: It is array of length N. These are the y coordinates of the nodes that define the curves.
    2. y1:It is an array of length N or a scalar. This represents the x coordinates of the nodes that define the first curve.
    3. y2: It is an array of length N and is optional in nature. Its default value is 0. This represents the x coordinates of the nodes that define the second curve.
    4. where: it is an array of boolean values of length N. It is defined if there is a need to exclude some vertical regions from being filled. It is important to note that this definition means that an isolated true value in between two false values is where it will not do the filling. Adjacent False values results in not filling both sides of the True value.
    5. interpolate: It is an optional parameter that accepts boolean values. It is only relevant if where is used and two curves are crossing each other. Semantically where if generally used for y1>y2 or similar cases. By default the filled regions will be placed at the x-array positions defining a filled polygonal area. The section of x that has the intersection are simply clipped. Setting this parameter to True results in calculation of the actual point of intersection and extends to the filled regions till the points.
    6. step: This is an optional parameter that accepts one of the three values namely, 'pre', 'post' and 'mid'. This is used to specify where the steps will occur.
      • pre: From every y position the x value is continued constantlyto the left, ie, the interval (x[i-1], x[i]) has the value y[i].
      • post:From every y position the x value is continued constantly to the right, ie, the interval (x[i], x[i+1]) has the value y[i].
      • mid: Half way between the x positions these steps occur.

    Returns: It returns a plotted polygon from the PolyCollection.

    other Parameters: **kwargs contains keywords from PolyCollection that controls the polygon properties;

    PropertyDescription
    agg_filtera filter function that takes a (m, n, 3) float array and a dpi value that returns a (m, n, 3) array
    alphafloat or None
    animatedbool
    arrayndarray
    capstyle{'butt', 'round', 'projecting'}
    clima length 2 sequence of floats; may be overridden in methods that have vmin and vmax kwargs.
    cmapcolormap or registered colormap
    antialiased or aa or antialiasedsbool or sequence of bools
    clip_boxBbox
    clip_onbool
    clip_path[(Path, Transform)|Patch|None]
    colorcolor or sequence of rgba tuples
    containscallable
    edgecolor or ec or edgecolorscolor or sequence of colors or 'face'
    facecolor or fc or facecolorscolor or sequence of colors
    figurefigure
    gidstr
    hatch{'/', '\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}
    in_layoutbool
    joinstyle{'miter', 'round', 'bevel'}
    linestyle or ls or linestyles or dashes{'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
    linewidth or linewidths or lwfloat or sequence of floats
    normNormalize
    offset_position{'screen', 'data'}
    offsetsfloat or sequence of floats
    path_effectsAbstractPathEffect
    pickerNone or bool or float or callable
    pickradiusunknown
    path_effectsAbstractPathEffect
    pickerfloat or callable[[Artist, Event], Tuple[bool, dict]]
    pickradiusfloat
    rasterizedbool or None
    sketch_params(scale: float, length: float, randomness: float)
    snapbool or None
    transformmatplotlib.transforms.Transform
    urlstr
    urlsList[str] or None
    visiblebool
    xdata1D array
    zorderfloat

    Example 1: 

    Python3
    import matplotlib.pyplot as plt
    import numpy as np
    
    x = np.arange(0,10,0.1)
    
    # plotting the lines
    a1 = 4 - 2*x
    a2 = 3 - 0.5*x
    a3 = 1 -x
    
    # The upper edge of
    # polygon
    a4 = np.minimum(a1, a2)
    
    # Setting the y-limit
    plt.ylim(0, 5)
    
    # Plot the lines
    plt.plot(x, a1,
            x, a2,
            x, a3)
    
    # Filling between line a3 
    # and line a4
    plt.fill_between(x, a3, a4, color='green',
                     alpha=0.5)
    plt.show()
    

    Output: python-matplotlib-find-between-1 Example 2: 

    Python3
    import matplotlib.pyplot as plt
    import numpy as np
    
    
    a = np.linspace(0,2*3.14,50)
    b = np.sin(a)
    
    plt.fill_between(a, b, 0,
                     where = (a > 2) & (a <= 3),
                     color = 'g')
    plt.plot(a,b)
    

    Output: python-matplotlib-fill-between2-

    Create Quiz

    R

    rajukumar19
    Improve

    R

    rajukumar19
    Improve
    Article Tags :
    • Python
    • Write From Home
    • Python-Library
    • Python-matplotlib

    Explore

      Python Fundamentals

      Python Introduction

      2 min read

      Input and Output in Python

      4 min read

      Python Variables

      4 min read

      Python Operators

      4 min read

      Python Keywords

      2 min read

      Python Data Types

      8 min read

      Conditional Statements in Python

      3 min read

      Loops in Python - For, While and Nested Loops

      5 min read

      Python Functions

      5 min read

      Recursion in Python

      4 min read

      Python Lambda Functions

      5 min read

      Python Data Structures

      Python String

      5 min read

      Python Lists

      4 min read

      Python Tuples

      4 min read

      Python Dictionary

      3 min read

      Python Sets

      6 min read

      Python Arrays

      7 min read

      List Comprehension in Python

      4 min read

      Advanced Python

      Python OOP Concepts

      11 min read

      Python Exception Handling

      5 min read

      File Handling in Python

      4 min read

      Python Database Tutorial

      4 min read

      Python MongoDB Tutorial

      3 min read

      Python MySQL

      9 min read

      Python Packages

      10 min read

      Python Modules

      3 min read

      Python DSA Libraries

      15 min read

      List of Python GUI Library and Packages

      3 min read

      Data Science with Python

      NumPy Tutorial - Python Library

      3 min read

      Pandas Tutorial

      4 min read

      Matplotlib Tutorial

      5 min read

      Python Seaborn Tutorial

      3 min read

      StatsModel Library - Tutorial

      3 min read

      Learning Model Building in Scikit-learn

      6 min read

      TensorFlow Tutorial

      2 min read

      PyTorch Tutorial

      6 min read

      Web Development with Python

      Flask Tutorial

      8 min read

      Django Tutorial | Learn Django Framework

      7 min read

      Django ORM - Inserting, Updating & Deleting Data

      4 min read

      Templating With Jinja2 in Flask

      6 min read

      Django Templates

      5 min read

      Build a REST API using Flask - Python

      3 min read

      Building a Simple API with Django REST Framework

      3 min read

      Python Practice

      Python Quiz

      1 min read

      Python Coding Practice

      1 min read

      Python Interview Questions and Answers

      15+ min read
    top_of_element && top_of_screen < bottom_of_element) || (bottom_of_screen > articleRecommendedTop && top_of_screen < articleRecommendedBottom) || (top_of_screen > articleRecommendedBottom)) { if (!isfollowingApiCall) { isfollowingApiCall = true; setTimeout(function(){ if (loginData && loginData.isLoggedIn) { if (loginData.userName !== $('#followAuthor').val()) { is_following(); } else { $('.profileCard-profile-picture').css('background-color', '#E7E7E7'); } } else { $('.follow-btn').removeClass('hideIt'); } }, 3000); } } }); } $(".accordion-header").click(function() { var arrowIcon = $(this).find('.bottom-arrow-icon'); arrowIcon.toggleClass('rotate180'); }); }); window.isReportArticle = false; function report_article(){ if (!loginData || !loginData.isLoggedIn) { const loginModalButton = $('.login-modal-btn') if (loginModalButton.length) { loginModalButton.click(); } return; } if(!window.isReportArticle){ //to add loader $('.report-loader').addClass('spinner'); jQuery('#report_modal_content').load(gfgSiteUrl+'wp-content/themes/iconic-one/report-modal.php', { PRACTICE_API_URL: practiceAPIURL, PRACTICE_URL:practiceURL },function(responseTxt, statusTxt, xhr){ if(statusTxt == "error"){ alert("Error: " + xhr.status + ": " + xhr.statusText); } }); }else{ window.scrollTo({ top: 0, behavior: 'smooth' }); $("#report_modal_content").show(); } } function closeShareModal() { const shareOption = document.querySelector('[data-gfg-action="share-article"]'); shareOption.classList.remove("hover_share_menu"); let shareModal = document.querySelector(".hover__share-modal-container"); shareModal && shareModal.remove(); } function openShareModal() { closeShareModal(); // Remove existing modal if any let shareModal = document.querySelector(".three_dot_dropdown_share"); shareModal.appendChild(Object.assign(document.createElement("div"), { className: "hover__share-modal-container" })); document.querySelector(".hover__share-modal-container").append( Object.assign(document.createElement('div'), { className: "share__modal" }), ); document.querySelector(".share__modal").append(Object.assign(document.createElement('h1'), { className: "share__modal-heading" }, { textContent: "Share to" })); const socialOptions = ["LinkedIn", "WhatsApp","Twitter", "Copy Link"]; socialOptions.forEach((socialOption) => { const socialContainer = Object.assign(document.createElement('div'), { className: "social__container" }); const icon = Object.assign(document.createElement("div"), { className: `share__icon share__${socialOption.split(" ").join("")}-icon` }); const socialText = Object.assign(document.createElement("span"), { className: "share__option-text" }, { textContent: `${socialOption}` }); const shareLink = (socialOption === "Copy Link") ? Object.assign(document.createElement('div'), { role: "button", className: "link-container CopyLink" }) : Object.assign(document.createElement('a'), { className: "link-container" }); if (socialOption === "LinkedIn") { shareLink.setAttribute('href', `https://www.linkedin.com/sharing/share-offsite/?url=${window.location.href}`); shareLink.setAttribute('target', '_blank'); } if (socialOption === "WhatsApp") { shareLink.setAttribute('href', `https://api.whatsapp.com/send?text=${window.location.href}`); shareLink.setAttribute('target', "_blank"); } if (socialOption === "Twitter") { shareLink.setAttribute('href', `https://twitter.com/intent/tweet?url=${window.location.href}`); shareLink.setAttribute('target', "_blank"); } shareLink.append(icon, socialText); socialContainer.append(shareLink); document.querySelector(".share__modal").appendChild(socialContainer); //adding copy url functionality if(socialOption === "Copy Link") { shareLink.addEventListener("click", function() { var tempInput = document.createElement("input"); tempInput.value = window.location.href; document.body.appendChild(tempInput); tempInput.select(); tempInput.setSelectionRange(0, 99999); // For mobile devices document.execCommand('copy'); document.body.removeChild(tempInput); this.querySelector(".share__option-text").textContent = "Copied" }) } }); // document.querySelector(".hover__share-modal-container").addEventListener("mouseover", () => document.querySelector('[data-gfg-action="share-article"]').classList.add("hover_share_menu")); } function toggleLikeElementVisibility(selector, show) { document.querySelector(`.${selector}`).style.display = show ? "block" : "none"; } function closeKebabMenu(){ document.getElementById("myDropdown").classList.toggle("show"); }
geeksforgeeks-footer-logo
Corporate & Communications Address:
A-143, 7th Floor, Sovereign Corporate Tower, Sector- 136, Noida, Uttar Pradesh (201305)
Registered Address:
K 061, Tower K, Gulshan Vivante Apartment, Sector 137, Noida, Gautam Buddh Nagar, Uttar Pradesh, 201305
GFG App on Play Store GFG App on App Store
  • Company
  • About Us
  • Legal
  • Privacy Policy
  • Contact Us
  • Advertise with us
  • GFG Corporate Solution
  • Campus Training Program
  • Explore
  • POTD
  • Job-A-Thon
  • Blogs
  • Nation Skill Up
  • Tutorials
  • Programming Languages
  • DSA
  • Web Technology
  • AI, ML & Data Science
  • DevOps
  • CS Core Subjects
  • Interview Preparation
  • Software and Tools
  • Courses
  • ML and Data Science
  • DSA and Placements
  • Web Development
  • Programming Languages
  • DevOps & Cloud
  • GATE
  • Trending Technologies
  • Videos
  • DSA
  • Python
  • Java
  • C++
  • Web Development
  • Data Science
  • CS Subjects
  • Preparation Corner
  • Interview Corner
  • Aptitude
  • Puzzles
  • GfG 160
  • System Design
@GeeksforGeeks, Sanchhaya Education Private Limited, All rights reserved
Lightbox
Improvement
Suggest Changes
Help us improve. Share your suggestions to enhance the article. Contribute your expertise and make a difference in the GeeksforGeeks portal.
geeksforgeeks-suggest-icon
Create Improvement
Enhance the article with your expertise. Contribute to the GeeksforGeeks community and help create better learning resources for all.
geeksforgeeks-improvement-icon
Suggest Changes
min 4 words, max Words Limit:1000

Thank You!

Your suggestions are valuable to us.

What kind of Experience do you want to share?

Interview Experiences
Admission Experiences
Career Journeys
Work Experiences
Campus Experiences
Competitive Exam Experiences