{"id":25553858,"date":"2023-02-15T18:12:54","date_gmt":"2023-02-15T12:42:54","guid":{"rendered":"https:\/\/entri.app\/blog\/?p=25553858"},"modified":"2023-05-17T12:13:54","modified_gmt":"2023-05-17T06:43:54","slug":"data-visualization-in-python","status":"publish","type":"post","link":"https:\/\/entri.app\/blog\/data-visualization-in-python\/","title":{"rendered":"Introduction to Data Visualization in Python"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69e375a4dc3f8\" class=\"ez-toc-cssicon-toggle-label\"><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><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69e375a4dc3f8\"  aria-label=\"Toggle\" \/><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:\/\/entri.app\/blog\/data-visualization-in-python\/#What_is_Data_Visualization\" >What is Data Visualization?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#Importance_of_Data_Visualization\" >Importance of Data Visualization<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#Advantages_of_Data_Visualization\" >Advantages of Data Visualization<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#Data_Visualization_in_Python\" >Data Visualization in Python<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#Data_Visualization_in_Python_FAQs\" >Data Visualization in Python FAQs<\/a><\/li><\/ul><\/nav><\/div>\n<p>Having tabular data can make it challenging to comprehend the data when working with it. Visualizing data or representing it in a pictorial form will enable us to understand better what the information means and how to clean and use it. Tables and CSV files can\u2019t reveal patterns, correlations, or trends.<\/p>\n<p style=\"text-align: center;\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/course\/python-programming-course\/\" target=\"_blank\" rel=\"noopener\">&#8220;Get hands-on with our python course &#8211; sign up for a free demo!&#8221;<\/a><\/strong><\/p>\n<p>The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.<\/p>\n<div class=\"lead-gen-block\"><a href=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2022\/03\/Python_PDF.pdf\" data-url=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2022\/03\/Python_PDF.pdf\" class=\"lead-pdf-download\" data-id=\"25556853\">\n<p style=\"text-align: center;\"><strong>Download Python Programming Course Syllabus! <\/a><\/div><\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_is_Data_Visualization\"><\/span><strong>What is Data Visualization?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Data visualization is a field in\u00a0data analysis\u00a0that deals with visual representation of data. It graphically plots data and is an effective way to communicate inferences from data.<\/p>\n<p>Using\u00a0data visualization, we can get a visual summary of our data. With pictures, maps and graphs, the human mind has an easier time processing and understanding any given data. Data visualization plays a significant role in the representation of both small and large data sets, but it is especially useful when we have large data sets, in which it is impossible to see all our data, let alone process and understand it manually.<\/p>\n<p>As part of the data delivery (DPA) discipline, data detection is also a feature of identifying, retrieving, managing, formatting, and efficiently delivering data.<\/p>\n<p>In large data sets, data viewing helps identify patterns, styles, and vendors by easier identifying patterns, styles, and vendors. Diagrams, charts, information drawings, and visuals are all examples of this term.<\/p>\n<p><strong><div class=\"lead-gen-block\"><a href=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/05\/1_merged-3_compressed.pdf\" data-url=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/05\/1_merged-3_compressed.pdf\" class=\"lead-pdf-download\" data-id=\"25556853\"><\/strong><\/p>\n<p style=\"text-align: center;\"><button class=\"btn btn-default\">Free SQL Tutorial for Beginners &#8211; Download PDF<\/button><\/p>\n<p><strong><\/a><\/div><\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Importance_of_Data_Visualization\"><\/span><strong>Importance of Data Visualization<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>By visualizing data, businesses can quickly identify trends that would prove challenging. Analysts can visualize new patterns and concepts through the pictorial representation of data sets. Data proliferation, including data visualization, is necessary to make sense of the quintillion bytes of data generated daily.<br \/>\nData can be visualized and understood using dashboards, graphs, infographics, maps, charts, videos, slides, etc.\u00a0Data Visualization\u00a0enables decision-makers to interrelate data to find better insights and reap the benefits of data visualization.<\/p>\n<p style=\"text-align: center;\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/course\/python-programming-course\/\" target=\"_blank\" rel=\"noopener\">&#8220;Ready to take your python skills to the next level? Sign up for a free demo today!&#8221;<\/a><\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Advantages_of_Data_Visualization\"><\/span><strong>Advantages of Data Visualization<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The advantages of data visualization are listed below<\/p>\n<p><strong>Simple to Understand<\/strong><\/p>\n<p>Using graphic representations provide us with clear and coherent expressions of vast amounts of data, allows us to understand the data, reach conclusions, and see perspectives.\u00a0A data visualization tool makes it easy for managers and decision-makers to create and consume critical metrics quickly and easily.<\/p>\n<p><strong>Represent Complex Relationships<\/strong><\/p>\n<p>Standard visuals, such as bar charts and line graphs, are often inadequate when presenting complex relationships.\u00a0It is virtually impossible to present a dataset with over a million distinct data points in a standard way.<\/p>\n<p><strong>Making Accessible Key Values<\/strong><\/p>\n<p>The first benefit of Data Visualization is that it allows massive data sets to be decoded and key values revealed. Especially when it comes to large amounts of data, it can be overwhelming to understand. Visualizing the data helps make key values of the data clear and easy to understand.<\/p>\n<p><strong>Identifying Spots<\/strong><\/p>\n<p>Our ability to visualize data enables us to recognize emerging trends and respond quickly based on what we see. Identifying strongly correlated parameters is easier when visuals and diagrams are used.<\/p>\n<p><strong>An Understanding of the Story<\/strong><\/p>\n<p>Dashboards are designed to tell stories. Visuals should be designed in such a way that they help the target audience quickly grasp the story. It would be best to convey the story in the simplest way possible without using excessively detailed visuals.<\/p>\n<p style=\"text-align: center;\"><strong><a href=\"https:\/\/entri.app\/course\/data-science-and-machine-learning-course\/\" target=\"_blank\" rel=\"noopener\">Ready to take your data science skills to the next level? Sign up for a free demo today!<\/a><\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Data_Visualization_in_Python\"><\/span><strong>Data Visualization in Python<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Python offers several plotting libraries, namely\u00a0Matplotlib,\u00a0Seaborn, Plotly\u00a0and many other such data visualization packages with different features for creating informative, customized, and appealing plots to present data in the most simple and effective way.<\/p>\n<p>Matplotlib and Seaborn are\u00a0libraries of Python\u00a0that are used for data visualization. They have inbuilt modules for plotting different graphs. While Matplotlib is used to embed graphs into applications, Seaborn is primarily used for statistical graphs.<\/p>\n<h3>Matplotlib<\/h3>\n<p>Matplotlib is the most popular Python plotting library. It is a low-level library with a Matlab-like interface that offers lots of freedom at the cost of having to write more code. Matplotlib is specifically suitable for creating basic graphs like line charts, bar charts, histograms, etc.<\/p>\n<h4>Line Charts<\/h4>\n<p>A Line chart is a graphical representation of information as a series of data points connected by a straight line. In line charts, each data point or marker is plotted and connected with a line or curve.\u00a0In Matplotlib, we can create a line chart by calling the\u00a0plot\u00a0method. We can also plot multiple columns in one graph by looping through the columns we want and plotting each column on the same axis.<\/p>\n<h4>Scatter Plot<\/h4>\n<p>To create a scatter plot in Matplotlib, we can use the\u00a0scatter\u00a0method. We will also create a figure and an axis using\u00a0plt.subplots\u00a0to give our plot a title and labels.<\/p>\n<p>We can give the graph more meaning by coloring each data point by its class. This can be done by creating a dictionary that maps from class to color and then scattering each point on its own using a for-loop and passing the respective color.<\/p>\n<h4>Histogram<\/h4>\n<p>In Matplotlib, we can create a Histogram using the\u00a0hist\u00a0method. If we pass categorical data like the points column from the wine-review dataset, it will automatically calculate how often each class occurs.<\/p>\n<h4>Bar Chart<\/h4>\n<p>A bar chart can be created using the\u00a0bar\u00a0method. The bar chart isn\u2019t automatically calculating the frequency of a category, so we will use pandas\u00a0value_counts\u00a0method to do this. The bar chart is useful for categorical data that doesn\u2019t have a lot of different categories (less than 30) because else it can get quite messy.<\/p>\n<h3>Seaborn<\/h3>\n<p>Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for creating attractive graphs. Seaborn has a lot to offer. For example, you can create graphs in one line that would take multiple tens of lines in Matplotlib.<\/p>\n<h4>Line Chart<\/h4>\n<p>To create a line chart, the sns.lineplot method can be used. The only required argument is the data, which in our case are the four numeric columns from the Iris dataset. We could also use the sns.kdeplot method, which soothes the edges of the curves and therefore is cleaner if you have a lot of outliers in your dataset. An easy way to make your charts look beautiful is to use some default styles from the Seaborn library. These can be applied globally using the sns.set_style function.<\/p>\n<h4>Scatter plot<\/h4>\n<p>We can use the\u00a0.scatterplot\u00a0method for creating a scatterplot, and just as in Pandas, we need to pass it the column names of the x and y data, but now we also need to pass the data as an additional argument because we aren\u2019t calling the function on the data directly.<\/p>\n<h4>Histogram<\/h4>\n<p>To create a histogram in Seaborn, we use the\u00a0sns.distplot\u00a0method. We need to pass it the column we want to plot, and it will calculate the occurrences itself. We can also pass it the number of bins and if we want to plot a gaussian kernel density estimate inside the graph.<\/p>\n<h4>Bar chart<\/h4>\n<p>In Seaborn, a bar chart can be created using the\u00a0sns.countplot\u00a0method and passing it the data.<\/p>\n<p>But when should we use either of the two data visualizations? We can understand this with the help of a comparative analysis.<\/p>\n<p>The table below provides the difference between Python\u2019s two well-known visualization packages Matplotlib and Seaborn<\/p>\n<p style=\"text-align: center;\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/course\/python-programming-course\/\" target=\"_blank\" rel=\"noopener\">&#8220;Ready to take your python skills to the next level? Sign up for a free demo today!&#8221;<\/a><\/strong><\/p>\n<table width=\"672\">\n<tbody>\n<tr>\n<td>\n<p style=\"text-align: center;\">Matplotlib<\/p>\n<\/td>\n<td width=\"255\">\n<p style=\"text-align: center;\">Seaborn<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>It is used for basic graph plotting like line charts, bar graphs, etc.<\/td>\n<td width=\"255\">It is mainly used for statistics visualization and can perform complex visualizations with fewer commands.<\/td>\n<\/tr>\n<tr>\n<td>It mainly works with datasets and arrays.<\/td>\n<td width=\"255\">It works with entire datasets.<\/td>\n<\/tr>\n<tr>\n<td>Seaborn is considerably more organized and functional than Matplotlib and treats the entire dataset as a solitary unit.<\/td>\n<td width=\"255\">Matplotlib acts productively with data arrays and frames. It regards the aces and figures as objects.<\/td>\n<\/tr>\n<tr>\n<td>Seaborn has more inbuilt themes and is mainly used for statistical analysis.<\/td>\n<td width=\"255\">Matplotlib is more customizable and pairs well with Pandas and NumPy for Exploratory Data Analysis.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3>Plotly<\/h3>\n<p>The plotly.py visualization library is an interactive, open-source, comprehensive, and declarative Python library. A wide variety of useful visualizations are available, such as scientific charts, 3D graphs, statistical charts, and financial charts.<\/p>\n<h4>Scatter Plot<\/h4>\n<p>Plotly\u2019s scatter() method can be used to create scatter plots. It is also necessary to include an additional data argument, like Seaborn.<\/p>\n<h4>Line Chart<\/h4>\n<p>In Plotly, line plots are much more accessible and illustrious additions that assemble easy-to-style statistics from various data types<strong>.<\/strong>\u00a0Each position of data is represented as a vertex with px. line<\/p>\n<h4>Bar Chart<\/h4>\n<p>With plotly.express, you can create bar charts using the bar() method.<\/p>\n<p>Python offers multiple other visualization packages which can be used to create different types of visualizations and not just graphs and plots. It is, therefore, also important to understand the challenges and advantages of the different libraries and how to use them to their full potential.<\/p>\n<p style=\"text-align: center;\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/course\/python-programming-course\/\" target=\"_blank\" rel=\"noopener\">&#8220;Experience the power of our web development course with a free demo &#8211; enroll now!&#8221;<\/a><\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Data_Visualization_in_Python_FAQs\"><\/span><strong>Data Visualization in Python FAQs<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h4><strong>1. Why do we need Data Visualization in Python?<\/strong><\/h4>\n<p>Ans. For\u00a0creating informative, customized, and appealing plots to present data in the most simple and effective way.<\/p>\n<h4><strong>2. What are the two main uses of Data Visualizations?<\/strong><\/h4>\n<p>Ans.\u00a0Exploration, which helps find a story the data is telling you, and an explanation, which tells a story to an audience.<\/p>\n<h4><strong>3. Does Data Visualization require coding?<\/strong><\/h4>\n<p>Ans. Data visualization does not require you to have coding skills.<\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"2\" width=\"623\">\n<p style=\"text-align: center;\"><strong>Related Articles<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"312\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/blog\/step-by-step-guide-for-getting-a-job-as-a-python-developer\/42\" target=\"_blank\" rel=\"noopener\">A Step-by-Step Guide for Getting a Job as a Python Developer<\/a><\/strong><\/td>\n<td width=\"312\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/blog\/why-python-is-used-for-data-science\/\" target=\"_blank\" rel=\"noopener\">Why Python Is Used For Data Science?<\/a><\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"312\"><strong><a href=\"https:\/\/entri.app\/blog\/exploratory-data-analysis-in-machine-learning\/\">EDA in Machine Learning\u00a0<\/a><\/strong><\/td>\n<td width=\"312\"><a href=\"https:\/\/entri.app\/blog\/top-applications-of-data-science-in-e-commerce\/\" target=\"_blank\" rel=\"noopener\"><strong>Top applications in Data Science<\/strong><\/a><\/td>\n<\/tr>\n<tr>\n<td width=\"312\"><strong><a href=\"https:\/\/entri.app\/blog\/best-data-visualization-tools-list\/\">Best Data visualization tools list<\/a><\/strong><\/td>\n<td width=\"312\"><strong><a href=\"https:\/\/entri.app\/blog\/how-to-make-a-bright-career-in-data-science\/\" target=\"_blank\" rel=\"noopener\">Bright career in Data Science<\/a><\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div class=\"modal\" id=\"modal25556853\"><div class=\"modal-content\"><span class=\"close-button\">&times;<\/span>\n\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f25556853-o1\" lang=\"en-US\" dir=\"ltr\" data-wpcf7-id=\"25556853\">\n<div class=\"screen-reader-response\"><p role=\"status\" aria-live=\"polite\" aria-atomic=\"true\"><\/p> <ul><\/ul><\/div>\n<form action=\"\/blog\/wp-json\/wp\/v2\/posts\/25553858#wpcf7-f25556853-o1\" method=\"post\" class=\"wpcf7-form init\" aria-label=\"Contact form\" novalidate=\"novalidate\" data-status=\"init\">\n<fieldset class=\"hidden-fields-container\"><input type=\"hidden\" name=\"_wpcf7\" value=\"25556853\" \/><input type=\"hidden\" name=\"_wpcf7_version\" value=\"6.1.4\" \/><input type=\"hidden\" name=\"_wpcf7_locale\" value=\"en_US\" \/><input type=\"hidden\" name=\"_wpcf7_unit_tag\" value=\"wpcf7-f25556853-o1\" \/><input type=\"hidden\" name=\"_wpcf7_container_post\" value=\"0\" \/><input type=\"hidden\" name=\"_wpcf7_posted_data_hash\" value=\"\" \/><input type=\"hidden\" name=\"_wpcf7cf_hidden_group_fields\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_hidden_groups\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_visible_groups\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_repeaters\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_steps\" value=\"{}\" \/><input type=\"hidden\" name=\"_wpcf7cf_options\" value=\"{&quot;form_id&quot;:25556853,&quot;conditions&quot;:[],&quot;settings&quot;:{&quot;animation&quot;:&quot;yes&quot;,&quot;animation_intime&quot;:200,&quot;animation_outtime&quot;:200,&quot;conditions_ui&quot;:&quot;normal&quot;,&quot;notice_dismissed&quot;:false,&quot;notice_dismissed_update-cf7-5.9.8&quot;:true,&quot;notice_dismissed_update-cf7-6.1.1&quot;:true}}\" \/>\n<\/fieldset>\n<p><span class=\"wpcf7-form-control-wrap\" data-name=\"full_name\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-text wpcf7-validates-as-required\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Name\" value=\"\" type=\"text\" name=\"full_name\" \/><\/span><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"phone\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-tel wpcf7-validates-as-required wpcf7-text wpcf7-validates-as-tel\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Phone\" value=\"\" type=\"tel\" name=\"phone\" \/><\/span><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"email_id\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-email wpcf7-text wpcf7-validates-as-email\" aria-invalid=\"false\" placeholder=\"Email\" value=\"\" type=\"email\" name=\"email_id\" \/><\/span><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"language\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required\" aria-required=\"true\" aria-invalid=\"false\" name=\"language\"><option value=\"\">Language<\/option><option value=\"Malayalam\">Malayalam<\/option><option value=\"Tamil\">Tamil<\/option><option value=\"Telugu\">Telugu<\/option><option value=\"Kannada\">Kannada<\/option><option value=\"Hindi\">Hindi<\/option><\/select><\/span><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"course\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required course-field-select\" aria-required=\"true\" aria-invalid=\"false\" name=\"course\"><option value=\"\">Upskill in<\/option><option value=\"Commerce\">Commerce<\/option><option value=\"Coding\">Coding<\/option><option value=\"Robotics &amp; AI Course\">Robotics &amp; AI Course<\/option><option value=\"Stock Market Course\">Stock Market Course<\/option><option value=\"Spoken English\">Spoken English<\/option><option value=\"German Language\">German Language<\/option><option value=\"Montessori Teacher Training\">Montessori Teacher Training<\/option><option value=\"IELTS\">IELTS<\/option><option value=\"OET\">OET<\/option><option value=\"MEP\">MEP<\/option><option value=\"Embedded System Software Engineering\">Embedded System Software Engineering<\/option><option value=\"Quantity Surveying\">Quantity Surveying<\/option><option value=\"Hospital and Healthcare Administration\">Hospital and Healthcare Administration<\/option><option value=\"Yoga TTC\">Yoga TTC<\/option><option value=\"Digital Marketing\">Digital Marketing<\/option><option value=\"AI for Teachers\">AI for Teachers<\/option><option value=\"Arabic\">Arabic<\/option><\/select><\/span>\n<\/p>\n<div data-id=\"group-coding\" data-orig_data_id=\"group-coding\" data-clear_on_hide class=\"\" data-class=\"wpcf7cf_group\">\n\t<p><span class=\"wpcf7-form-control-wrap\" data-name=\"course_name\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required course-name-select\" aria-required=\"true\" aria-invalid=\"false\" name=\"course_name\"><option value=\"\">Select Course<\/option><option value=\"Full Stack Development\">Full Stack Development<\/option><option value=\"Data Science and ML\">Data Science and ML<\/option><option value=\"Software Testing\">Software Testing<\/option><option value=\"Python Programming\">Python Programming<\/option><option value=\"AWS Training\">AWS Training<\/option><\/select><\/span>\n\t<\/p>\n<\/div>\n<div data-id=\"group-accounting\" data-orig_data_id=\"group-accounting\" data-clear_on_hide class=\"\" data-class=\"wpcf7cf_group\">\n\t<p><span class=\"wpcf7-form-control-wrap\" data-name=\"course_name\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required course-name-select\" aria-required=\"true\" aria-invalid=\"false\" name=\"course_name\"><option value=\"\">Select Course<\/option><option value=\"Business Accounting\">Business Accounting<\/option><option value=\"CMA USA\">CMA USA<\/option><option value=\"Enrolled Agent\">Enrolled Agent<\/option><option value=\"SAP FICO\">SAP FICO<\/option><option value=\"SAP MM\">SAP MM<\/option><option value=\"SAP SD\">SAP SD<\/option><option value=\"ACCA\">ACCA<\/option><option value=\"Tally\">Tally<\/option><option value=\"UAE Accounting\">UAE Accounting<\/option><option value=\"GST\">GST<\/option><\/select><\/span>\n\t<\/p>\n<\/div>\n<p><span class=\"wpcf7-form-control-wrap\" data-name=\"education\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-text wpcf7-validates-as-required\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Educational qualification\" value=\"\" type=\"text\" name=\"education\" \/><\/span>\n<\/p>\n<div style=\"display:none\">\n<input class=\"wpcf7-form-control wpcf7-hidden course-name-input\" value=\"\" type=\"hidden\" name=\"course_name\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden utm-source\" value=\"\" type=\"hidden\" name=\"utm_source\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden utm-medium\" value=\"\" type=\"hidden\" name=\"utm_medium\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden utm-campaign\" value=\"\" type=\"hidden\" name=\"utm_campaign\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden utm-content\" value=\"\" type=\"hidden\" name=\"utm_content\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden utm-term\" value=\"\" type=\"hidden\" name=\"utm_term\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden blog-url\" value=\"\" type=\"hidden\" name=\"blog_url\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden post-category-name\" value=\"\" type=\"hidden\" name=\"post_category_name\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden post-author-name\" value=\"\" type=\"hidden\" name=\"post_author_name\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden file-url\" value=\"\" type=\"hidden\" name=\"file_url\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden video-url\" value=\"\" type=\"hidden\" name=\"video_url\" \/>\n<input class=\"wpcf7-form-control wpcf7-hidden courseid\" value=\"\" type=\"hidden\" name=\"course_id\" \/>\n<\/div>\n<div class=\"cf7-cf-turnstile\" style=\"margin-top: 0px; margin-bottom: -15px;\"> <div id=\"cf-turnstile-cf7-3024865967\" class=\"cf-turnstile\" data-sitekey=\"0x4AAAAAABVigxtkiZeGTu5L\" data-theme=\"light\" data-language=\"auto\" data-size=\"normal\" data-retry=\"auto\" data-retry-interval=\"1000\" data-action=\"contact-form-7\" data-appearance=\"always\"><\/div> <script>document.addEventListener(\"DOMContentLoaded\", function() { setTimeout(function(){ var e=document.getElementById(\"cf-turnstile-cf7-3024865967\"); e&&!e.innerHTML.trim()&&(turnstile.remove(\"#cf-turnstile-cf7-3024865967\"), turnstile.render(\"#cf-turnstile-cf7-3024865967\", {sitekey:\"0x4AAAAAABVigxtkiZeGTu5L\"})); }, 0); });<\/script> <br class=\"cf-turnstile-br cf-turnstile-br-cf7-3024865967\"> <style>#cf-turnstile-cf7-3024865967 { margin-left: -15px; }<\/style> <script>document.addEventListener(\"DOMContentLoaded\",function(){document.querySelectorAll('.wpcf7-form').forEach(function(e){e.addEventListener('submit',function(){if(document.getElementById('cf-turnstile-cf7-3024865967')){setTimeout(function(){turnstile.reset('#cf-turnstile-cf7-3024865967');},1000)}})})});<\/script> <\/div><br\/><input class=\"wpcf7-form-control wpcf7-submit has-spinner\" type=\"submit\" value=\"Submit\" \/>\n<\/p><div class=\"wpcf7-response-output\" aria-hidden=\"true\"><\/div>\n<\/form>\n<\/div>\n\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Having tabular data can make it challenging to comprehend the data when working with it. Visualizing data or representing it in a pictorial form will enable us to understand better what the information means and how to clean and use it. Tables and CSV files can\u2019t reveal patterns, correlations, or trends. &#8220;Get hands-on with our [&hellip;]<\/p>\n","protected":false},"author":55,"featured_media":25554127,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[802,1864,1841,1888],"tags":[],"class_list":["post-25553858","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-data-science-ml","category-entri-skilling","category-python-programming"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Introduction to Data Visualization in Python - Entri Blog<\/title>\n<meta name=\"description\" content=\"The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Introduction to Data Visualization in Python - Entri Blog\" \/>\n<meta property=\"og:description\" content=\"The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\" \/>\n<meta property=\"og:site_name\" content=\"Entri Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/entri.me\/\" \/>\n<meta property=\"article:published_time\" content=\"2023-02-15T12:42:54+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-05-17T06:43:54+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png\" \/>\n\t<meta property=\"og:image:width\" content=\"820\" \/>\n\t<meta property=\"og:image:height\" content=\"615\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Ayesha Surayya\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@entri_app\" \/>\n<meta name=\"twitter:site\" content=\"@entri_app\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ayesha Surayya\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\"},\"author\":{\"name\":\"Ayesha Surayya\",\"@id\":\"https:\/\/entri.app\/blog\/#\/schema\/person\/568cc9d6e77fd5d01033b61c88343097\"},\"headline\":\"Introduction to Data Visualization in Python\",\"datePublished\":\"2023-02-15T12:42:54+00:00\",\"dateModified\":\"2023-05-17T06:43:54+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\"},\"wordCount\":1752,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/entri.app\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png\",\"articleSection\":[\"Articles\",\"Data Science and Machine Learning\",\"Entri Skilling\",\"Python Programming\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\",\"url\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\",\"name\":\"Introduction to Data Visualization in Python - Entri Blog\",\"isPartOf\":{\"@id\":\"https:\/\/entri.app\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png\",\"datePublished\":\"2023-02-15T12:42:54+00:00\",\"dateModified\":\"2023-05-17T06:43:54+00:00\",\"description\":\"The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.\",\"breadcrumb\":{\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/entri.app\/blog\/data-visualization-in-python\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage\",\"url\":\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png\",\"contentUrl\":\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png\",\"width\":820,\"height\":615,\"caption\":\"Introduction to Data Visualization in Python\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/entri.app\/blog\/data-visualization-in-python\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/entri.app\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Python Programming\",\"item\":\"https:\/\/entri.app\/blog\/category\/python-programming\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Introduction to Data Visualization in Python\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/entri.app\/blog\/#website\",\"url\":\"https:\/\/entri.app\/blog\/\",\"name\":\"Entri Blog\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/entri.app\/blog\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/entri.app\/blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/entri.app\/blog\/#organization\",\"name\":\"Entri App\",\"url\":\"https:\/\/entri.app\/blog\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/entri.app\/blog\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2019\/10\/Entri-Logo-1.png\",\"contentUrl\":\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2019\/10\/Entri-Logo-1.png\",\"width\":989,\"height\":446,\"caption\":\"Entri App\"},\"image\":{\"@id\":\"https:\/\/entri.app\/blog\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/entri.me\/\",\"https:\/\/x.com\/entri_app\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/entri.app\/blog\/#\/schema\/person\/568cc9d6e77fd5d01033b61c88343097\",\"name\":\"Ayesha Surayya\",\"url\":\"https:\/\/entri.app\/blog\/author\/ayesha-surayya\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Introduction to Data Visualization in Python - Entri Blog","description":"The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/entri.app\/blog\/data-visualization-in-python\/","og_locale":"en_US","og_type":"article","og_title":"Introduction to Data Visualization in Python - Entri Blog","og_description":"The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.","og_url":"https:\/\/entri.app\/blog\/data-visualization-in-python\/","og_site_name":"Entri Blog","article_publisher":"https:\/\/www.facebook.com\/entri.me\/","article_published_time":"2023-02-15T12:42:54+00:00","article_modified_time":"2023-05-17T06:43:54+00:00","og_image":[{"width":820,"height":615,"url":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png","type":"image\/png"}],"author":"Ayesha Surayya","twitter_card":"summary_large_image","twitter_creator":"@entri_app","twitter_site":"@entri_app","twitter_misc":{"Written by":"Ayesha Surayya","Est. reading time":"9 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#article","isPartOf":{"@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/"},"author":{"name":"Ayesha Surayya","@id":"https:\/\/entri.app\/blog\/#\/schema\/person\/568cc9d6e77fd5d01033b61c88343097"},"headline":"Introduction to Data Visualization in Python","datePublished":"2023-02-15T12:42:54+00:00","dateModified":"2023-05-17T06:43:54+00:00","mainEntityOfPage":{"@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/"},"wordCount":1752,"commentCount":0,"publisher":{"@id":"https:\/\/entri.app\/blog\/#organization"},"image":{"@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage"},"thumbnailUrl":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png","articleSection":["Articles","Data Science and Machine Learning","Entri Skilling","Python Programming"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/entri.app\/blog\/data-visualization-in-python\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/","url":"https:\/\/entri.app\/blog\/data-visualization-in-python\/","name":"Introduction to Data Visualization in Python - Entri Blog","isPartOf":{"@id":"https:\/\/entri.app\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage"},"image":{"@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage"},"thumbnailUrl":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png","datePublished":"2023-02-15T12:42:54+00:00","dateModified":"2023-05-17T06:43:54+00:00","description":"The process of finding trends and correlations in our data by representing it pictorially is called\u00a0Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.","breadcrumb":{"@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/entri.app\/blog\/data-visualization-in-python\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#primaryimage","url":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png","contentUrl":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2023\/02\/Introduction-to-Data-Visualization-in-Python-3.png","width":820,"height":615,"caption":"Introduction to Data Visualization in Python"},{"@type":"BreadcrumbList","@id":"https:\/\/entri.app\/blog\/data-visualization-in-python\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/entri.app\/blog\/"},{"@type":"ListItem","position":2,"name":"Python Programming","item":"https:\/\/entri.app\/blog\/category\/python-programming\/"},{"@type":"ListItem","position":3,"name":"Introduction to Data Visualization in Python"}]},{"@type":"WebSite","@id":"https:\/\/entri.app\/blog\/#website","url":"https:\/\/entri.app\/blog\/","name":"Entri Blog","description":"","publisher":{"@id":"https:\/\/entri.app\/blog\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/entri.app\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/entri.app\/blog\/#organization","name":"Entri App","url":"https:\/\/entri.app\/blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/entri.app\/blog\/#\/schema\/logo\/image\/","url":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2019\/10\/Entri-Logo-1.png","contentUrl":"https:\/\/entri.app\/blog\/wp-content\/uploads\/2019\/10\/Entri-Logo-1.png","width":989,"height":446,"caption":"Entri App"},"image":{"@id":"https:\/\/entri.app\/blog\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/entri.me\/","https:\/\/x.com\/entri_app"]},{"@type":"Person","@id":"https:\/\/entri.app\/blog\/#\/schema\/person\/568cc9d6e77fd5d01033b61c88343097","name":"Ayesha Surayya","url":"https:\/\/entri.app\/blog\/author\/ayesha-surayya\/"}]}},"_links":{"self":[{"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/posts\/25553858","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/users\/55"}],"replies":[{"embeddable":true,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/comments?post=25553858"}],"version-history":[{"count":13,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/posts\/25553858\/revisions"}],"predecessor-version":[{"id":25560295,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/posts\/25553858\/revisions\/25560295"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/media\/25554127"}],"wp:attachment":[{"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/media?parent=25553858"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/categories?post=25553858"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/entri.app\/blog\/wp-json\/wp\/v2\/tags?post=25553858"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}