{"id":50554,"date":"2025-05-30T16:28:10","date_gmt":"2025-05-30T10:58:10","guid":{"rendered":"https:\/\/www.iquanta.in\/blog\/?p=50554"},"modified":"2025-05-30T16:28:15","modified_gmt":"2025-05-30T10:58:15","slug":"data-visualization-using-matplotlib-in-python","status":"publish","type":"post","link":"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/","title":{"rendered":"Data Visualization using Matplotlib in Python"},"content":{"rendered":"\n<p>Have you ever looked at a big table full of numbers and felt totally confused. That\u2019s why we use something called data visualization. It basically means turning boring numbers into pictures like graphs and charts so they are easier to understand. If you are learning Python or just curious about how to show data in a better way there is a really cool tool called Matplotlib. Professionals like <a href=\"https:\/\/www.iquanta.in\/blog\/how-to-become-a-data-analyst-a-comprehensive-guide-in-2025\/\">data analysts<\/a> use this library in their day-to-day lives to perform several tasks.<\/p>\n\n\n\n<p>It is like a drawing tool in Python that helps you make all kinds of charts. You can make simple line graphs bar charts or even more fancy stuff once you get the hang of it. The best thing is you don not need to be a genius or have a lot of coding experience. If you know a little bit of Python then also you are good to go. In this blog i will show you how to use Matplotlib step by step in the easiest way possible so you can start making your own graphs without any stress.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/chat.whatsapp.com\/B6weknl7133BQXjPva0pgB\"><img fetchpriority=\"high\" decoding=\"async\" width=\"864\" height=\"129\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png\" alt=\"Matplotlib in Python\" class=\"wp-image-49032\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png 864w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-300x45.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-768x115.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-150x22.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-696x104.png 696w\" sizes=\"(max-width: 864px) 100vw, 864px\" \/><\/a><\/figure><\/div>\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_77 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Getting_Started_with_Matplotlib_in_Python\" >Getting Started with Matplotlib in Python<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#How_to_Install_Matplotlib_in_Python\" >How to Install Matplotlib in Python<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Types_of_Plot_You_Can_Make_Using_Matplotlib_in_Python\" >Types of Plot You Can Make Using Matplotlib in Python<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Line_Plot\" >Line Plot<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Bar_Chart\" >Bar Chart<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Pie_Chart\" >Pie Chart<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Histogram\" >Histogram<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Scatter_Plot\" >Scatter Plot<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Customizing_Plots_in_Matplotlib\" >Customizing Plots in Matplotlib<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Adding_Titles_and_Labels\" >Adding Titles and Labels<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Changing_Styles_and_Colors\" >Changing Styles and Colors<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Adding_a_Legend\" >Adding a Legend<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Comparison_of_Different_Matplotlib_Charts\" >Comparison of Different Matplotlib Charts<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#What_is_Matplotlib_used_for\" >What is Matplotlib used for?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Can_I_customize_the_look_of_my_graph\" >Can I customize the look of my graph?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Whats_the_difference_between_pltplot_and_pltbar\" >What\u2019s the difference between plt.plot() and plt.bar()?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#How_do_I_show_multiple_graphs_together\" >How do I show multiple graphs together?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Do_I_need_internet_to_use_Matplotlib\" >Do I need internet to use Matplotlib?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Is_Matplotlib_good_for_beginners\" >Is Matplotlib good for beginners?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#Conclusion\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\" id=\"h-getting-started-with-matplotlib-in-python\"><span class=\"ez-toc-section\" id=\"Getting_Started_with_Matplotlib_in_Python\"><\/span><strong>Getting Started with Matplotlib in Python<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Before we start making cool graphs, we need to make sure Matplotlib is ready to use in our Python setup. It is not built-in so we have to install it first. <\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-how-to-install-matplotlib-in-python\"><span class=\"ez-toc-section\" id=\"How_to_Install_Matplotlib_in_Python\"><\/span><strong>How to Install Matplotlib in Python<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>If you are using something like Jupyter Notebook, VS Code, or even just the command line installing Matplotlib is super easy. Just open your terminal or command prompt and type this.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>pip install matplotlib\r<\/code><\/pre>\n\n\n\n<p>Once it is installed then you need to import it in your Python file or notebook. Most people use this short way.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt<\/code><\/pre>\n\n\n\n<p>Post importing matplotlib try this code snippet a little to understand the terms.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\nx = &#091;1, 2, 3, 4]\r\ny = &#091;10, 20, 25, 30]\r\n\r\nplt.plot(x, y)\r\nplt.show()\r<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-types-of-plot-you-can-make-using-matplotlib-in-python\"><span class=\"ez-toc-section\" id=\"Types_of_Plot_You_Can_Make_Using_Matplotlib_in_Python\"><\/span><strong>Types of Plot You Can Make Using Matplotlib in Python<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Now that you have installed Matplotlib and made your first tiny graph. Let&#8217;s look at the different types of plots you can create. Each type helps tell a different kind of story with your data. You do not need to remember everything right away as you just have to read through and get an idea of what is possible. We will go through the most common ones step by step: <\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-line-plot\"><span class=\"ez-toc-section\" id=\"Line_Plot\"><\/span><strong>Line Plot<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>This is the simplest and most common type of plot. If you want to show how something changes over time or across steps then in that case line plots are perfect.<\/p>\n\n\n\n<p>A line plot is used to show trends or changes over time. It connects data points with straight line which is making it easy to see how values go up or down. It is perfect for showing progress, growth, or any continuous data.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\nx = &#091;1, 2, 3, 4, 5]\r\ny = &#091;5, 8, 6, 10, 12]\r\n\r\nplt.plot(x, y, color='green', marker='o', linestyle='-', linewidth=2)\r\nplt.title(\"Simple Line Plot\")\r\nplt.xlabel(\"Time\")\r\nplt.ylabel(\"Value\")\r\nplt.grid(True)\r\nplt.show()\r\n\r<\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"807\" height=\"290\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-191.png\" alt=\"matplotlib in python\" class=\"wp-image-50568\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-191.png 807w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-191-300x108.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-191-768x276.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-191-150x54.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-191-696x250.png 696w\" sizes=\"(max-width: 807px) 100vw, 807px\" \/><\/figure><\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img decoding=\"async\" width=\"563\" height=\"455\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-192.png\" alt=\"line plot graph\" class=\"wp-image-50569\" style=\"width:469px;height:auto\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-192.png 563w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-192-300x242.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-192-520x420.png 520w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-192-150x121.png 150w\" sizes=\"(max-width: 563px) 100vw, 563px\" \/><\/figure><\/div>\n\n\n<h3 class=\"wp-block-heading\" id=\"h-bar-chart\"><span class=\"ez-toc-section\" id=\"Bar_Chart\"><\/span><strong>Bar Chart<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A bar chart is used to compare values of different categories. Each bar is having height that represents a value. It is great for showing counts, totals, or frequencies across groups.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/chat.whatsapp.com\/B6weknl7133BQXjPva0pgB\"><img fetchpriority=\"high\" decoding=\"async\" width=\"864\" height=\"129\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png\" alt=\"Matplotlib in Python\" class=\"wp-image-49032\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png 864w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-300x45.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-768x115.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-150x22.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-696x104.png 696w\" sizes=\"(max-width: 864px) 100vw, 864px\" \/><\/a><\/figure><\/div>\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\ncategories = &#091;'Math', 'Science', 'English', 'History']\r\nscores = &#091;85, 90, 75, 60]\r\n\r\nplt.bar(categories, scores, color='skyblue', edgecolor='black')\r\nplt.title(\"Student Scores by Subject\")\r\nplt.xlabel(\"Subjects\")\r\nplt.ylabel(\"Scores\")\r\nplt.show()\r<\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"211\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-1024x211.png\" alt=\"matplotlib in python\" class=\"wp-image-50571\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-1024x211.png 1024w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-300x62.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-768x158.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-150x31.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-696x143.png 696w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193-1068x220.png 1068w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-193.png 1442w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure><\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"562\" height=\"455\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-194.png\" alt=\"bar chart graph\" class=\"wp-image-50572\" style=\"width:518px;height:auto\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-194.png 562w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-194-300x243.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-194-519x420.png 519w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-194-150x121.png 150w\" sizes=\"(max-width: 562px) 100vw, 562px\" \/><\/figure><\/div>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-pie-chart\"><span class=\"ez-toc-section\" id=\"Pie_Chart\"><\/span><strong>Pie Chart<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>A pie chart shows how a whole is divided into parts. Each slice represents a percentage of the total. It is best for showing proportions or percentages.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\nlabels = &#091;'Apples', 'Bananas', 'Cherries', 'Grapes']\r\nsizes = &#091;30, 25, 25, 20]\r\ncolors = &#091;'gold', 'lightgreen', 'lightcoral', 'lightskyblue']\r\n\r\nplt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', startangle=90)\r\nplt.title(\"Fruit Share in Basket\")\r\nplt.axis('equal')  # Makes the pie a circle\r\nplt.show()\r<\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"212\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-1024x212.png\" alt=\"matplotlib in python\" class=\"wp-image-50577\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-1024x212.png 1024w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-300x62.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-768x159.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-150x31.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-696x144.png 696w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195-1068x221.png 1068w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-195.png 1404w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure><\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"515\" height=\"411\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-196.png\" alt=\"\" class=\"wp-image-50578\" style=\"width:415px;height:auto\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-196.png 515w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-196-300x239.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-196-150x120.png 150w\" sizes=\"(max-width: 515px) 100vw, 515px\" \/><\/figure><\/div>\n\n\n<h3 class=\"wp-block-heading\" id=\"h-histogram\"><span class=\"ez-toc-section\" id=\"Histogram\"><\/span><strong>Histogram<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A histogram groups values into ranges called bins and shows how many values fall into each range. It is commonly used to see the spread or distribution of data.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\nages = &#091;22, 25, 27, 30, 35, 35, 36, 40, 41, 45, 50, 60, 65, 70]\r\nbins = &#091;20, 30, 40, 50, 60, 70, 80]\r\n\r\nplt.hist(ages, bins=bins, color='teal', edgecolor='black')\r\nplt.title(\"Age Distribution\")\r\nplt.xlabel(\"Age Groups\")\r\nplt.ylabel(\"Number of People\")\r\nplt.show()\r<\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"210\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-1024x210.png\" alt=\"matplotlib graph\" class=\"wp-image-50581\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-1024x210.png 1024w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-300x62.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-768x158.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-150x31.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-696x143.png 696w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197-1068x219.png 1068w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-197.png 1414w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure><\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"567\" height=\"455\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-198.png\" alt=\"\" class=\"wp-image-50582\" style=\"width:485px;height:auto\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-198.png 567w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-198-300x241.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-198-523x420.png 523w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-198-150x120.png 150w\" sizes=\"(max-width: 567px) 100vw, 567px\" \/><\/figure><\/div>\n\n\n<h3 class=\"wp-block-heading\" id=\"h-scatter-plot\"><span class=\"ez-toc-section\" id=\"Scatter_Plot\"><\/span><strong>Scatter Plot<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A scatter plot shows individual data points based on two variables. It helps you see patterns or relationships between the two variables like whether one increases as the other increases.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\nstudy_hours = &#091;1, 2, 3, 4, 5, 6, 7]\r\nmarks = &#091;40, 50, 55, 60, 65, 75, 85]\r\n\r\nplt.scatter(study_hours, marks, color='purple')\r\nplt.title(\"Study Time vs Marks\")\r\nplt.xlabel(\"Study Hours\")\r\nplt.ylabel(\"Marks\")\r\nplt.grid(True)\r\nplt.show()\r<\/code><\/pre>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"240\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-1024x240.png\" alt=\"matplotlib in python\" class=\"wp-image-50585\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-1024x240.png 1024w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-300x70.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-768x180.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-150x35.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-696x163.png 696w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199-1068x250.png 1068w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-199.png 1323w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure><\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"562\" height=\"455\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-200.png\" alt=\"scatter plot\" class=\"wp-image-50586\" style=\"width:426px;height:auto\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-200.png 562w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-200-300x243.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-200-519x420.png 519w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-200-150x121.png 150w\" sizes=\"(max-width: 562px) 100vw, 562px\" \/><\/figure><\/div>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-customizing-plots-in-matplotlib\"><span class=\"ez-toc-section\" id=\"Customizing_Plots_in_Matplotlib\"><\/span><strong>Customizing Plots in Matplotlib<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Making a graph is not just about putting lines and bars on the screen. It is about making it clear and attractive so people can understand it easily. Matplotlib gives you many ways to customize your charts that will help you can change colors, styles, add titles, labels, legends, and more according to the logic.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/chat.whatsapp.com\/B6weknl7133BQXjPva0pgB\"><img fetchpriority=\"high\" decoding=\"async\" width=\"864\" height=\"129\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png\" alt=\"Matplotlib in Python\" class=\"wp-image-49032\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png 864w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-300x45.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-768x115.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-150x22.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-696x104.png 696w\" sizes=\"(max-width: 864px) 100vw, 864px\" \/><\/a><\/figure><\/div>\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Adding_Titles_and_Labels\"><\/span><strong>Adding Titles and Labels<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A title tells what the graph is about. Labels help people understand what each axis shows.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\r\n\r\nx = &#091;1, 2, 3, 4]\r\ny = &#091;10, 20, 25, 30]\r\n\r\nplt.plot(x, y)\r\nplt.title(\"My First Line Plot\")\r\nplt.xlabel(\"X Axis - Time\")\r\nplt.ylabel(\"Y Axis - Sales\")\r\nplt.show()\r<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-changing-styles-and-colors\"><span class=\"ez-toc-section\" id=\"Changing_Styles_and_Colors\"><\/span>Changing Styles and Colors<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.plot(x, y, color='red', linestyle='--', marker='s')\r\nplt.title(\"Styled Line Chart\")\r\nplt.xlabel(\"X Axis\")\r\nplt.ylabel(\"Y Axis\")\r\nplt.grid(True)\r\nplt.show()\r<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-adding-a-legend\"><span class=\"ez-toc-section\" id=\"Adding_a_Legend\"><\/span><strong>Adding a Legend<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>x = &#091;1, 2, 3, 4]\r\ny1 = &#091;10, 20, 25, 30]\r\ny2 = &#091;5, 15, 20, 22]\r\n\r\nplt.plot(x, y1, label=\"Product A\", color='blue')\r\nplt.plot(x, y2, label=\"Product B\", color='green')\r\nplt.title(\"Sales Comparison\")\r\nplt.xlabel(\"Quarters\")\r\nplt.ylabel(\"Sales\")\r\nplt.legend()\r\nplt.show()\r<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-comparison-of-different-matplotlib-charts\"><span class=\"ez-toc-section\" id=\"Comparison_of_Different_Matplotlib_Charts\"><\/span><strong>Comparison of Different Matplotlib Charts<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>Plot Type<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Best Use Case<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Data Type<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Can Compare Categories<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Shows Trend Over Time<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Easy to Read<\/strong><\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Line Plot<\/td><td class=\"has-text-align-center\" data-align=\"center\">Showing trends or changes over time<\/td><td class=\"has-text-align-center\" data-align=\"center\">Continuous<\/td><td class=\"has-text-align-center\" data-align=\"center\">No<\/td><td class=\"has-text-align-center\" data-align=\"center\">Yes<\/td><td class=\"has-text-align-center\" data-align=\"center\">Yes<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Bar Chart<\/td><td class=\"has-text-align-center\" data-align=\"center\">Comparing values across categories<\/td><td class=\"has-text-align-center\" data-align=\"center\">Categorical<\/td><td class=\"has-text-align-center\" data-align=\"center\">Yes<\/td><td class=\"has-text-align-center\" data-align=\"center\">No<\/td><td class=\"has-text-align-center\" data-align=\"center\">Yes<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Pie Chart<\/td><td class=\"has-text-align-center\" data-align=\"center\">Showing parts of a whole as percentages<\/td><td class=\"has-text-align-center\" data-align=\"center\">Categorical<\/td><td class=\"has-text-align-center\" data-align=\"center\">Yes<\/td><td class=\"has-text-align-center\" data-align=\"center\">No<\/td><td class=\"has-text-align-center\" data-align=\"center\">Medium<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Histogram<\/td><td class=\"has-text-align-center\" data-align=\"center\">Checking the distribution of data<\/td><td class=\"has-text-align-center\" data-align=\"center\">Continuous <\/td><td class=\"has-text-align-center\" data-align=\"center\">No<\/td><td class=\"has-text-align-center\" data-align=\"center\">No<\/td><td class=\"has-text-align-center\" data-align=\"center\">Yes<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Scatter Plot<\/td><td class=\"has-text-align-center\" data-align=\"center\">Finding relationships between two numeric values<\/td><td class=\"has-text-align-center\" data-align=\"center\">Continuous<\/td><td class=\"has-text-align-center\" data-align=\"center\">No<\/td><td class=\"has-text-align-center\" data-align=\"center\">Sometimes<\/td><td class=\"has-text-align-center\" data-align=\"center\">Medium<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-frequently-asked-questions\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><strong>Frequently Asked Questions<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-what-is-matplotlib-used-for\"><span class=\"ez-toc-section\" id=\"What_is_Matplotlib_used_for\"><\/span><strong>What is Matplotlib used for?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Matplotlib is a Python library used to create all types of graphs and charts like line plots, bar graphs, pie charts and more. It helps you visualize your data easily.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-can-i-customize-the-look-of-my-graph\"><span class=\"ez-toc-section\" id=\"Can_I_customize_the_look_of_my_graph\"><\/span><strong>Can I customize the look of my graph?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Yes you can change the title, colors, labels, line styles, and even the size of your graph using simple functions in Matplotlib.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-what-s-the-difference-between-plt-plot-and-plt-bar\"><span class=\"ez-toc-section\" id=\"Whats_the_difference_between_pltplot_and_pltbar\"><\/span><strong>What\u2019s the difference between plt.plot() and plt.bar()?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/chat.whatsapp.com\/B6weknl7133BQXjPva0pgB\"><img fetchpriority=\"high\" decoding=\"async\" width=\"864\" height=\"129\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png\" alt=\"Matplotlib in Python\" class=\"wp-image-49032\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png 864w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-300x45.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-768x115.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-150x22.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-696x104.png 696w\" sizes=\"(max-width: 864px) 100vw, 864px\" \/><\/a><\/figure><\/div>\n\n\n<p>plt.plot() is used to draw line charts, while plt.bar() is used to draw bar charts. They are used for different kinds of data.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-how-do-i-show-multiple-graphs-together\"><span class=\"ez-toc-section\" id=\"How_do_I_show_multiple_graphs_together\"><\/span><strong>How do I show multiple graphs together?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>You can use plt.subplot() to divide your graph window and show more than one graph at a time.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-do-i-need-internet-to-use-matplotlib\"><span class=\"ez-toc-section\" id=\"Do_I_need_internet_to_use_Matplotlib\"><\/span><strong>Do I need internet to use Matplotlib?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>No actually once you install the library, you can use it offline in your local Python environment.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-is-matplotlib-good-for-beginners\"><span class=\"ez-toc-section\" id=\"Is_Matplotlib_good_for_beginners\"><\/span><strong>Is Matplotlib good for beginners?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Yes as it is one of the easiest libraries to learn if you are starting out with data visualization in Python.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/chat.whatsapp.com\/B6weknl7133BQXjPva0pgB\"><img fetchpriority=\"high\" decoding=\"async\" width=\"864\" height=\"129\" src=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png\" alt=\"Matplotlib in Python\" class=\"wp-image-49032\" srcset=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51.png 864w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-300x45.png 300w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-768x115.png 768w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-150x22.png 150w, https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/image-51-696x104.png 696w\" sizes=\"(max-width: 864px) 100vw, 864px\" \/><\/a><\/figure><\/div>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conclusion\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><strong>Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Matplotlib is like a drawing tool for your data. It helps you turn boring numbers into clear and colorful graphs that anyone can understand. Whether you are working on school projects or real-world business reports Matplotlib makes it easy to show what is going on in your data. With just a few lines of code you can make your data come alive. Once you get the hang of it you will realize how powerful and flexible it really is.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-\"><br><\/h3>\n","protected":false},"excerpt":{"rendered":"<p>Have you ever looked at a big table full of numbers and felt totally confused. That\u2019s why we use something called data visualization. It basically means turning boring numbers into pictures like graphs and charts so they are easier to understand. If you are learning Python or just curious about how to show data in [&hellip;]<\/p>\n","protected":false},"author":560,"featured_media":50595,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1074,1073],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.4 (Yoast SEO v21.9.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data Visualization using Matplotlib in Python - iQuanta<\/title>\n<meta name=\"description\" content=\"In this blog i will show you how to use Matplotlib in python step by step in the easiest way possible so you can start making your own graphs\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data Visualization using Matplotlib in Python\" \/>\n<meta property=\"og:description\" content=\"In this blog i will show you how to use Matplotlib in python step by step in the easiest way possible so you can start making your own graphs\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/\" \/>\n<meta property=\"og:site_name\" content=\"iQuanta\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/facebook.com\/iquanta.in\" \/>\n<meta property=\"article:published_time\" content=\"2025-05-30T10:58:10+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-05-30T10:58:15+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.iquanta.in\/blog\/wp-content\/uploads\/2025\/05\/Your-paragraph-text-26.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1600\" \/>\n\t<meta property=\"og:image:height\" content=\"900\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Nidhi Goswami\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Nidhi Goswami\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/\"},\"author\":{\"name\":\"Nidhi Goswami\",\"@id\":\"https:\/\/www.iquanta.in\/blog\/#\/schema\/person\/ec8c8c25d0526dd86557b6fed064f7f3\"},\"headline\":\"Data Visualization using Matplotlib in Python\",\"datePublished\":\"2025-05-30T10:58:10+00:00\",\"dateModified\":\"2025-05-30T10:58:15+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/\"},\"wordCount\":1001,\"publisher\":{\"@id\":\"https:\/\/www.iquanta.in\/blog\/#organization\"},\"articleSection\":[\"Data Analytics\",\"iSkills\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/\",\"url\":\"https:\/\/www.iquanta.in\/blog\/data-visualization-using-matplotlib-in-python\/\",\"name\":\"Data Visualization using Matplotlib in Python - 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