Matplotlib.pyplot.subplot2grid() in python Last Updated : 12 Jul, 2025 Comments Improve Suggest changes Like Article Like Report 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.subplot2grid() The Matplotlib.pyplot.subplot2grid() function give additional flexibility in creating axes object at a specified location inside a grid. It also helps in spanning the axes object across multiple rows or columns. In simpler words, this function is used to create multiple charts within the same figure. It is a sub-figure layout manager. Syntax : Plt.subplot2grid(shape, location, rowspan, colspan) Parameters : shape: As the name suggests it is used to define the shape of the grid to be plotted within the graph. It is a required argument and is generally passed in as a list or tuple of two numbers which are responsible for the layout of the grid with the first number being the number of rows and the second number as the number of columns. location (loc): This is the second mandatory argument that this function takes. Similar to the shape argument it is also a required argument and is generally passed in as a list or tuple of two numbers. It is used for specifying the row and column number to place the sub-plot. It is also important to note that the indexes start from 0. So (0, 0) would be the cell in the first row and the first column of the grid. rowspan: Once the grid layout is set and the starting index is decided using location(loc) one can expand the selection to take up more rows with this argument. This is an optional parameter and has a default value of 1. colspan: Similar to rowspan it is used to expand the selection to take up more columns. It is also an optional parameter with default value of 1. Example 1: Python3 1== import matplotlib.pyplot as plt fig = plt.figure() axes1 = plt.subplot2grid((4, 4), (0, 0), colspan = 4) axes2 = plt.subplot2grid((4, 4), (1, 0), colspan = 3) axes3 = plt.subplot2grid((4, 4), (1, 2), rowspan = 3) axes4 = plt.subplot2grid((4, 4), (2, 0)) axes5 = plt.subplot2grid((4, 4), (2, 1)) fig.tight_layout() Output : Example 2: Python3 1== import random import matplotlib.pyplot as plt from matplotlib import style style.use('fivethirtyeight') fig = plt.figure() # helper function to plot the lines def helper(): xs = [] ys = [] for i in range(10): x = i y = random.randrange(10) xs.append(x) ys.append(y) return xs, ys axes1 = plt.subplot2grid ((7, 1), (0, 0), rowspan = 2, colspan = 1) axes2 = plt.subplot2grid ((7, 1), (2, 0), rowspan = 2, colspan = 1) axes3 = plt.subplot2grid ((7, 1), (4, 0), rowspan = 2, colspan = 1) x, y = helper() axes1.plot(x, y) x, y = helper() axes2.plot(x, y) x, y = helper() axes3.plot(x, y) Output: Comment More infoAdvertise with us Next Article Interview Preparation For Software Developers R rajukumar19 Follow Improve Article Tags : Python Write From Home Python-Library Python-matplotlib Practice Tags : python Similar Reads Interview PreparationInterview Preparation For Software DevelopersMust Coding Questions - Company-wise Must Do Coding Questions - Topic-wiseCompany-wise Practice ProblemsCompany PreparationCompetitive ProgrammingSoftware Design-PatternsCompany-wise Interview ExperienceExperienced - Interview ExperiencesInternship - Interview ExperiencesPractice @GeeksforgeeksProblem of the DayTopic-wise PracticeDifficulty Level - SchoolDifficulty Level - BasicDifficulty Level - EasyDifficulty Level - MediumDifficulty Level - HardLeaderboard !!Explore More...Data StructuresArraysLinked ListStackQueueBinary TreeBinary Search TreeHeapHashingGraphAdvance Data StructuresMatrixStringAll Data StructuresAlgorithmsAnalysis of AlgorithmsSearching AlgorithmsSorting AlgorithmsPattern SearchingGeometric AlgorithmsMathematical AlgorithmsRandomized AlgorithmsGreedy AlgorithmsDynamic ProgrammingDivide & ConquerBacktrackingBranch & BoundAll AlgorithmsProgramming LanguagesCC++JavaPythonC#Go LangSQLPHPScalaPerlKotlinWeb TechnologiesHTMLCSSJavaScriptBootstrapTailwind CSSAngularJSReactJSjQueryNodeJSPHPWeb DesignWeb BrowserFile FormatsComputer Science SubjectsOperating SystemsDBMSComputer NetworkComputer Organization & ArchitectureTOCCompiler DesignDigital Elec. & Logic DesignSoftware EngineeringEngineering MathematicsData Science & MLComplete Data Science CourseData Science TutorialMachine Learning TutorialDeep Learning TutorialNLP TutorialMachine Learning ProjectsData Analysis TutorialTutorial LibraryPython TutorialDjango TutorialPandas TutorialKivy TutorialTkinter TutorialOpenCV TutorialSelenium TutorialGATE CSGATE CS NotesGate CornerPrevious Year GATE PapersLast Minute Notes (LMNs)Important Topic For GATE CSGATE CoursePrevious Year Paper: CS exams Like