{"id":5491,"date":"2023-12-11T06:09:38","date_gmt":"2023-12-11T06:09:38","guid":{"rendered":"https:\/\/www.pickl.ai\/blog\/?p=5491"},"modified":"2024-07-30T11:58:16","modified_gmt":"2024-07-30T11:58:16","slug":"powerful-python-libraries-to-automate-partial-eda","status":"publish","type":"post","link":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/","title":{"rendered":"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration"},"content":{"rendered":"<p><b>Summary: <\/b><span style=\"font-weight: 400;\">Explore essential Python libraries for Exploratory Data Analysis (EDA). Learn how Pandas, Matplotlib, Seaborn, Plotly, and Dask streamline data exploration and improve insights through automation and interactive visualisations.<\/span><\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 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.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Introduction\" >Introduction<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#What_is_Exploratory_Data_Analysis_EDA\" >What is Exploratory Data Analysis (EDA)?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#What_are_auto_EDA_libraires\" >What are auto EDA libraires?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Best_Python_EDA_libraries\" >Best Python EDA libraries<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Pandas\" >Pandas<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Matplotlib_and_Seaborn\" >Matplotlib and Seaborn<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Plotly\" >Plotly<\/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.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#NumPy\" >NumPy<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Scikit-Learn\" >Scikit-Learn<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Dask\" >Dask<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#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-12\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#What_is_Exploratory_Data_Analysis_EDA-2\" >What is Exploratory Data Analysis (EDA)?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#What_are_Auto_EDA_libraries\" >What are Auto EDA libraries?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#Which_Python_libraries_are_best_for_EDA\" >Which Python libraries are best for EDA?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#In_Closing\" >In Closing<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"introduction\"><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><b>Introduction<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Discover the power of <\/span><a href=\"https:\/\/pickl.ai\/blog\/list-of-python-libraries-for-data-science\/\"><span style=\"font-weight: 400;\">Python libraries<\/span><\/a><span style=\"font-weight: 400;\"> for (partial) automation of Exploratory Data Analysis (EDA). Pandas <\/span><a href=\"https:\/\/pickl.ai\/blog\/guide-to-data-profiling-its-examples-types\/\"><span style=\"font-weight: 400;\">Profiling<\/span><\/a><span style=\"font-weight: 400;\"> and SweetViz stand out, simplifying tasks like summary statistics, visualisations, and pattern identification. These tools empower seasoned <\/span><a href=\"https:\/\/pickl.ai\/blog\/skills-required-for-data-scientist-your-ultimate-success-roadmap\/\"><span style=\"font-weight: 400;\">Data Scientists<\/span><\/a><span style=\"font-weight: 400;\"> and beginners to explore datasets efficiently, extracting meaningful insights without the usual time constraints.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Elevate your data exploration game with these intuitive libraries, optimising your workflow and transforming your interaction with data.<\/span><\/p>\n<h2 id=\"what-is-exploratory-data-analysis-eda\"><span class=\"ez-toc-section\" id=\"What_is_Exploratory_Data_Analysis_EDA\"><\/span><b>What is Exploratory Data Analysis (EDA)?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Exploratory Data Analysis (EDA) is a crucial step in data analysis that involves summarising and <\/span><a href=\"https:\/\/pickl.ai\/blog\/why-is-data-visualization-important\/\"><span style=\"font-weight: 400;\">visualising data<\/span><\/a><span style=\"font-weight: 400;\"> to uncover patterns, anomalies, and insights. Analysts use EDA to explore data characteristics through statistical graphics, plots, and summary statistics. This process helps identify trends, detect outliers, and understand relationships between variables.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By performing EDA, data scientists gain a deeper understanding of their data&#8217;s structure and quality, guiding further analysis and modelling. EDA is essential for making informed decisions and ensuring that subsequent data processing and statistical methods are accurate and relevant.<\/span><\/p>\n<h2 id=\"what-are-auto-eda-libraires\"><span class=\"ez-toc-section\" id=\"What_are_auto_EDA_libraires\"><\/span><b>What are auto EDA libraires?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Auto EDA (Exploratory Data Analysis) libraries refer to a set of <\/span><a href=\"https:\/\/pickl.ai\/blog\/gigantic-python\/\"><span style=\"font-weight: 400;\">Python<\/span><\/a><span style=\"font-weight: 400;\"> tools designed to automate and streamline exploring and understanding datasets. These libraries are created to simplify the often time-consuming tasks involved in data analysis, allowing data professionals to gain insights quickly and efficiently.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Auto EDA libraries typically offer functionalities such as generating summary statistics, detecting missing values, identifying outliers, and creating visualisations to highlight patterns in the data.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Two famous examples of Auto EDA libraries are Pandas Profiling and SweetViz. Pandas Profiling, for instance, can generate detailed reports that cover various aspects of a dataset, providing a comprehensive overview with minimal coding effort.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">SweetViz specialises in creating visualisations that make it easier to interpret complex patterns within the data, offering a valuable tool for data exploration.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The essence of Auto EDA libraries lies in their ability to automate mundane aspects of data analysis, making it more accessible to a broader audience, from seasoned data scientists to beginners.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By leveraging these libraries, users can focus on deriving meaningful insights from their data, ultimately enhancing the efficiency and effectiveness of the entire data exploration process.<\/span><\/p>\n<h2 id=\"best-python-eda-libraries\"><span class=\"ez-toc-section\" id=\"Best_Python_EDA_libraries\"><\/span><b>Best Python EDA libraries<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone size-full wp-image-12755\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7.jpg\" alt=\"Best Python EDA libraries\" width=\"1000\" height=\"333\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7.jpg 1000w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-300x100.jpg 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-768x256.jpg 768w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-110x37.jpg 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-200x67.jpg 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-380x127.jpg 380w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-255x85.jpg 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-550x183.jpg 550w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-800x266.jpg 800w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image1-7-150x50.jpg 150w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Knowing the best Python EDA (Exploratory Data Analysis) libraries is essential for efficient data exploration and visualisation. These libraries provide powerful tools to analyse data patterns, uncover insights, and simplify decision-making. Mastering them enhances data-driven strategies and improves overall analytical capabilities.<\/span><\/p>\n<h3 id=\"pandas\"><span class=\"ez-toc-section\" id=\"Pandas\"><\/span><b>Pandas<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Pandas are often hailed as the Swiss Army knife of <\/span><a href=\"https:\/\/pickl.ai\/blog\/data-manipulation-types-examples\/\"><span style=\"font-weight: 400;\">data manipulation<\/span><\/a><span style=\"font-weight: 400;\"> and exploration, making it an essential library for any data scientist. Its core data structures, such as DataFrames and Series, facilitate seamless data manipulation. With Pandas, you can easily clean messy data, handle missing values, and perform aggregations. The library&#8217;s intuitive methods simplify tasks like merging datasets, filtering rows, and applying functions across your data.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">One of Pandas&#8217; key features is its ability to handle heterogeneous data types and complex operations efficiently. This makes it invaluable for tasks ranging from simple data exploration to complex transformations and aggregations.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Its integration with other libraries, like NumPy, enhances its versatility. Whether you\u2019re preparing data for machine learning models or generating summary statistics, Pandas provides a comprehensive suite of tools that make data manipulation straightforward and efficient.<\/span><\/p>\n<p><b>Check:<\/b> <a href=\"https:\/\/pickl.ai\/blog\/ultimate-pandas-cheat-sheets\/\"><span style=\"font-weight: 400;\">Ultimate Pandas Cheat Sheet: Mastering Pandas<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h3 id=\"matplotlib-and-seaborn\"><span class=\"ez-toc-section\" id=\"Matplotlib_and_Seaborn\"><\/span><b>Matplotlib and Seaborn<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Visualisation is a vital component of data storytelling, and Matplotlib and Seaborn excel in this domain. Matplotlib is the foundation for creating a wide array of plots and charts. It provides the basic building blocks for visualisations.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">It allows users to generate line plots, bar charts, histograms, and scatter plots. Its flexibility and customisation options make it a powerful tool for detailed visual representation.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Seaborn, built on top of Matplotlib, adds a layer of sophistication and aesthetic appeal. It simplifies the creation of complex visualisations like heatmaps, violin plots, and pair plots.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Seaborn\u2019s default themes and colour palettes enhance the visual appeal of plots, making them more engaging and more accessible to interpret. Matplotlib and Seaborn offer a robust toolkit for transforming data into compelling visual stories, allowing users to communicate complex trends and insights effectively.<\/span><\/p>\n<p><b>Get Your Hands On:<\/b> <a href=\"https:\/\/pickl.ai\/blog\/matplotlib-cheat-sheet\/\"><span style=\"font-weight: 400;\">Matplotlib Cheat Sheet: Visualise Data Like a Pro<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h3 id=\"plotly\"><span class=\"ez-toc-section\" id=\"Plotly\"><\/span><b>Plotly<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">For those seeking interactivity in their visualisations, <\/span><a href=\"https:\/\/plotly.com\/\"><span style=\"font-weight: 400;\">Plotly<\/span><\/a><span style=\"font-weight: 400;\"> is the go-to library. Unlike traditional static visualisations, Plotly enables users to create interactive plots that allow for deeper exploration of data points. With Plotly, you can build interactive dashboards, zoom into specific plot areas, and hover over data points to reveal additional information.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Plotly&#8217;s capabilities extend to various charts, including 3D plots and geographic maps. Its support for web-based visualisations allows users to share interactive plots seamlessly across different platforms.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This interactive dimension adds a layer of engagement that enhances user experience and makes data exploration more dynamic. Whether you&#8217;re developing a dashboard for stakeholders or exploring intricate data relationships, Plotly offers a compelling way to present data interactively.<\/span><\/p>\n<h3 id=\"numpy\"><span class=\"ez-toc-section\" id=\"NumPy\"><\/span><b>NumPy<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/pickl.ai\/blog\/numpy-in-python-types-function\/\"><span style=\"font-weight: 400;\">NumPy<\/span><\/a><span style=\"font-weight: 400;\"> is the powerhouse of numerical operations and mathematical computations in Python. It excels in handling large datasets through its array-oriented computing capabilities. NumPy\u2019s core feature is its N-dimensional array, which provides efficient storage and manipulation of numerical data.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">With a rich set of mathematical functions, NumPy supports operations like matrix multiplication, statistical computations, and Fourier transforms. These capabilities are crucial for numerical exploration in EDA. NumPy\u2019s seamless integration with other scientific libraries.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Examples include Pandas and Scikit-Learn, makes it an essential tool for any data scientist. Its performance optimisations and extensive functionality efficiently handle complex numerical tasks, laying a solid foundation for data analysis and computational tasks.<\/span><\/p>\n<h3 id=\"scikit-learn\"><span class=\"ez-toc-section\" id=\"Scikit-Learn\"><\/span><b>Scikit-Learn<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Scikit-Learn bridges the gap between exploratory data analysis (EDA) and <\/span><a href=\"https:\/\/pickl.ai\/blog\/what-is-machine-learning\/\"><span style=\"font-weight: 400;\">machine learning<\/span><\/a><span style=\"font-weight: 400;\">. It offers many tools for integrating machine learning into your EDA workflow. From data preprocessing to model evaluation, Scikit-Learn provides a cohesive environment that streamlines the transition from data exploration to predictive modelling.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Key features include its support for various machine learning algorithms, such as classification, regression, and clustering. Additionally, Scikit-Learn provides utilities for feature selection, dimensionality reduction, and model validation.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Its consistent API and comprehensive documentation make it accessible to users at all levels. Incorporating Scikit-Learn into your EDA process allows you to seamlessly transition from data analysis to building and evaluating machine learning models, enhancing your analytical capabilities.<\/span><\/p>\n<p><b>Uncover:<\/b> <a href=\"https:\/\/pickl.ai\/blog\/scikit-learn-cheat-sheet\/\"><span style=\"font-weight: 400;\">Scikit-Learn Cheat Sheet: A Comprehensive Guide<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h3 id=\"dask\"><span class=\"ez-toc-section\" id=\"Dask\"><\/span><b>Dask<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">As datasets become more complex, scalable computing becomes essential, and Dask effectively addresses this challenge. Dask enables parallel computing and distributed data processing, allowing data scientists to handle larger-than-memory datasets and perform advanced analytics.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dask\u2019s integration with <\/span><a href=\"https:\/\/www.interviewbit.com\/blog\/pandas-vs-numpy\/#:~:text=Pandas%20is%20mostly%20used%20for,easy%20to%20apply%20mathematical%20functions.&amp;text=Pandas%20library%20works%20well%20for,heterogeneous%20types%20of%20data%20simultaneously.\"><span style=\"font-weight: 400;\">Pandas and NumPy<\/span><\/a><span style=\"font-weight: 400;\"> means you can scale your existing workflows to handle big data without having to rewrite your code. It supports parallel computing and distributed processing, making it suitable for tasks that require substantial computational resources.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dask\u2019s ability to work with local and cluster-based computing environments ensures that your EDA efforts can scale as needed. Whether you\u2019re processing large volumes of data or running complex computations, Dask provides the tools to manage and analyse big data efficiently.<\/span><\/p>\n<h2 id=\"frequently-asked-questions\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><b>Frequently Asked Questions<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3 id=\"what-is-exploratory-data-analysis-eda-2\"><span class=\"ez-toc-section\" id=\"What_is_Exploratory_Data_Analysis_EDA-2\"><\/span><b>What is Exploratory Data Analysis (EDA)?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Exploratory Data Analysis (EDA) is a fundamental step in data analysis that involves summarising and visualising data to uncover patterns, anomalies, and insights. It uses statistical graphics and summary statistics to understand data characteristics, identify trends, and detect outliers, guiding subsequent data processing and modelling.<\/span><\/p>\n<h3 id=\"what-are-auto-eda-libraries\"><span class=\"ez-toc-section\" id=\"What_are_Auto_EDA_libraries\"><\/span><b>What are Auto EDA libraries?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Auto EDA libraries are Python tools that automate the exploratory data analysis process. They generate summary statistics, detect missing values, and create visualisations with minimal coding. Libraries like Pandas Profiling and SweetViz simplify data exploration, allowing users to gain insights and identify patterns quickly.<\/span><\/p>\n<h3 id=\"which-python-libraries-are-best-for-eda\"><span class=\"ez-toc-section\" id=\"Which_Python_libraries_are_best_for_EDA\"><\/span><b>Which Python libraries are best for EDA?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Top Python libraries for EDA include Pandas for data manipulation, Matplotlib and Seaborn for visualisations, Plotly for interactive plots, and Dask for scalable computing. These libraries enhance data analysis by offering powerful tools for summarising, visualising, and managing large datasets effectively.<\/span><\/p>\n<h2 id=\"in-closing\"><span class=\"ez-toc-section\" id=\"In_Closing\"><\/span><b>In Closing<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Leveraging the correct Python libraries can be a game-changer in the dynamic realm of data exploration. From Pandas&#8217;s foundational data manipulation capabilities to Plotly&#8217;s interactive prowess, each library plays a unique role in enhancing the efficiency and depth of your EDA.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As you embark on your data exploration journey, remember that mastering these Python libraries is not just about automation; it\u2019s about unlocking your data&#8217;s true potential. By incorporating these tools into your EDA arsenal, you will streamline your workflow and gain a competitive advantage in the data-driven landscape.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For beginners, learning Python could be intriguing, but at Pickl.AI\u2019s Python for Data Science course, you can learn the fundamentals of Python. The course encompasses modules focused on Pandas, Numpy, Python OOPs, and more.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By the end of this course, you will be familiar with the basics of Python.\u00a0 To learn more about this course, click on this link: <\/span><a href=\"https:\/\/www.pickl.ai\/course\/python-certification-training-program\"><span style=\"font-weight: 400;\">https:\/\/www.pickl.ai\/course\/python-certification-training-program<\/span><\/a><\/p>\n<p align=\"justify\">\n","protected":false},"excerpt":{"rendered":"Top Python libraries to enhance data exploration with automation and interactive visualisations.\n","protected":false},"author":29,"featured_media":12756,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1840],"tags":[1990,1992,1991,1993,1995,1996,1994],"ppma_author":[2219,2180],"class_list":{"0":"post-5491","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-python","8":"tag-auto-eda-libraries-python","9":"tag-best-python-eda-library","10":"tag-eda-libraries-in-python","11":"tag-what-are-the-python-libraries-for-automated-eda","12":"tag-what-is-the-alternative-to-pandas-profiling","13":"tag-what-libraries-in-python-are-used-for-data-analytics","14":"tag-which-python-library-is-commonly-used-for-performing-eda"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Explore data effortlessly with Python Libraries for (Partial) EDA<\/title>\n<meta name=\"description\" content=\"Discover the top Python libraries for Exploratory Data Analysis (EDA), including Pandas, Matplotlib, Seaborn, Plotly, and Dask.\" \/>\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.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration\" \/>\n<meta property=\"og:description\" content=\"Discover the top Python libraries for Exploratory Data Analysis (EDA), including Pandas, Matplotlib, Seaborn, Plotly, and Dask.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/\" \/>\n<meta property=\"og:site_name\" content=\"Pickl.AI\" \/>\n<meta property=\"article:published_time\" content=\"2023-12-11T06:09:38+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-30T11:58:16+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Aashi Verma, Tarun Chaturvedi\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Aashi Verma\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"7 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/\"},\"author\":{\"name\":\"Aashi Verma\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/#\\\/schema\\\/person\\\/8d771a2f91d8bfc0fa9518f8d4eee397\"},\"headline\":\"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration\",\"datePublished\":\"2023-12-11T06:09:38+00:00\",\"dateModified\":\"2024-07-30T11:58:16+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/\"},\"wordCount\":1525,\"commentCount\":0,\"image\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/image2-4.jpg\",\"keywords\":[\"auto eda libraries python\",\"best python eda library\",\"eda libraries in python\",\"What are the Python libraries for automated EDA?\",\"What is the alternative to pandas profiling?\",\"What libraries in Python are used for data analytics?\",\"Which Python library is commonly used for performing EDA *?\"],\"articleSection\":[\"Python\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/\",\"url\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/\",\"name\":\"Explore data effortlessly with Python Libraries for (Partial) EDA\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/image2-4.jpg\",\"datePublished\":\"2023-12-11T06:09:38+00:00\",\"dateModified\":\"2024-07-30T11:58:16+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/#\\\/schema\\\/person\\\/8d771a2f91d8bfc0fa9518f8d4eee397\"},\"description\":\"Discover the top Python libraries for Exploratory Data Analysis (EDA), including Pandas, Matplotlib, Seaborn, Plotly, and Dask.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/image2-4.jpg\",\"contentUrl\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/image2-4.jpg\",\"width\":1200,\"height\":628,\"caption\":\"Side shot of a code editor using react js and its hooks\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/powerful-python-libraries-to-automate-partial-eda\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Python\",\"item\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/category\\\/python\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/#website\",\"url\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/\",\"name\":\"Pickl.AI\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/#\\\/schema\\\/person\\\/8d771a2f91d8bfc0fa9518f8d4eee397\",\"name\":\"Aashi Verma\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2024\\\/08\\\/avatar_user_29_1723028535-96x96.jpg3fe02b5764d08ea068a95dc3fc5a3097\",\"url\":\"https:\\\/\\\/pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2024\\\/08\\\/avatar_user_29_1723028535-96x96.jpg\",\"contentUrl\":\"https:\\\/\\\/pickl.ai\\\/blog\\\/wp-content\\\/uploads\\\/2024\\\/08\\\/avatar_user_29_1723028535-96x96.jpg\",\"caption\":\"Aashi Verma\"},\"description\":\"Aashi Verma has dedicated herself to covering the forefront of enterprise and cloud technologies. As an Passionate researcher, learner, and writer, Aashi Verma interests extend beyond technology to include a deep appreciation for the outdoors, music, literature, and a commitment to environmental and social sustainability.\",\"url\":\"https:\\\/\\\/www.pickl.ai\\\/blog\\\/author\\\/aashiverma\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Explore data effortlessly with Python Libraries for (Partial) EDA","description":"Discover the top Python libraries for Exploratory Data Analysis (EDA), including Pandas, Matplotlib, Seaborn, Plotly, and Dask.","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:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/","og_locale":"en_US","og_type":"article","og_title":"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration","og_description":"Discover the top Python libraries for Exploratory Data Analysis (EDA), including Pandas, Matplotlib, Seaborn, Plotly, and Dask.","og_url":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/","og_site_name":"Pickl.AI","article_published_time":"2023-12-11T06:09:38+00:00","article_modified_time":"2024-07-30T11:58:16+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg","type":"image\/jpeg"}],"author":"Aashi Verma, Tarun Chaturvedi","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Aashi Verma","Est. reading time":"7 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#article","isPartOf":{"@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/"},"author":{"name":"Aashi Verma","@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/8d771a2f91d8bfc0fa9518f8d4eee397"},"headline":"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration","datePublished":"2023-12-11T06:09:38+00:00","dateModified":"2024-07-30T11:58:16+00:00","mainEntityOfPage":{"@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/"},"wordCount":1525,"commentCount":0,"image":{"@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#primaryimage"},"thumbnailUrl":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg","keywords":["auto eda libraries python","best python eda library","eda libraries in python","What are the Python libraries for automated EDA?","What is the alternative to pandas profiling?","What libraries in Python are used for data analytics?","Which Python library is commonly used for performing EDA *?"],"articleSection":["Python"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/","url":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/","name":"Explore data effortlessly with Python Libraries for (Partial) EDA","isPartOf":{"@id":"https:\/\/www.pickl.ai\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#primaryimage"},"image":{"@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#primaryimage"},"thumbnailUrl":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg","datePublished":"2023-12-11T06:09:38+00:00","dateModified":"2024-07-30T11:58:16+00:00","author":{"@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/8d771a2f91d8bfc0fa9518f8d4eee397"},"description":"Discover the top Python libraries for Exploratory Data Analysis (EDA), including Pandas, Matplotlib, Seaborn, Plotly, and Dask.","breadcrumb":{"@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#primaryimage","url":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg","contentUrl":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg","width":1200,"height":628,"caption":"Side shot of a code editor using react js and its hooks"},{"@type":"BreadcrumbList","@id":"https:\/\/www.pickl.ai\/blog\/powerful-python-libraries-to-automate-partial-eda\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.pickl.ai\/blog\/"},{"@type":"ListItem","position":2,"name":"Python","item":"https:\/\/www.pickl.ai\/blog\/category\/python\/"},{"@type":"ListItem","position":3,"name":"Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration"}]},{"@type":"WebSite","@id":"https:\/\/www.pickl.ai\/blog\/#website","url":"https:\/\/www.pickl.ai\/blog\/","name":"Pickl.AI","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.pickl.ai\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/8d771a2f91d8bfc0fa9518f8d4eee397","name":"Aashi Verma","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/08\/avatar_user_29_1723028535-96x96.jpg3fe02b5764d08ea068a95dc3fc5a3097","url":"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/08\/avatar_user_29_1723028535-96x96.jpg","contentUrl":"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/08\/avatar_user_29_1723028535-96x96.jpg","caption":"Aashi Verma"},"description":"Aashi Verma has dedicated herself to covering the forefront of enterprise and cloud technologies. As an Passionate researcher, learner, and writer, Aashi Verma interests extend beyond technology to include a deep appreciation for the outdoors, music, literature, and a commitment to environmental and social sustainability.","url":"https:\/\/www.pickl.ai\/blog\/author\/aashiverma\/"}]}},"jetpack_featured_media_url":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2023\/12\/image2-4.jpg","authors":[{"term_id":2219,"user_id":29,"is_guest":0,"slug":"aashiverma","display_name":"Aashi Verma","avatar_url":"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/08\/avatar_user_29_1723028535-96x96.jpg","first_name":"Aashi","user_url":"","last_name":"Verma","description":"Aashi Verma has dedicated herself to covering the forefront of enterprise and cloud technologies. As an Passionate researcher, learner, and writer, Aashi Verma interests extend beyond technology to include a deep appreciation for the outdoors, music, literature, and a commitment to environmental and social sustainability."},{"term_id":2180,"user_id":14,"is_guest":0,"slug":"tarunchaturvedi","display_name":"Tarun Chaturvedi","avatar_url":"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2023\/04\/avatar_user_14_1681111392-96x96.png","first_name":"Tarun","user_url":"","last_name":"Chaturvedi","description":"I am a data enthusiast and aspiring leader in the analytics field, with a background in engineering and experience in Data Science. Passionate about using data to solve complex problems, I am dedicated to honing my skills and knowledge in this field to positively impact society.  I am working as a Data Science intern with Pickl.ai, where I have explored the enormous potential of machine learning and artificial intelligence to provide solutions for businesses &amp; learning."}],"_links":{"self":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts\/5491","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/users\/29"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/comments?post=5491"}],"version-history":[{"count":22,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts\/5491\/revisions"}],"predecessor-version":[{"id":12759,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts\/5491\/revisions\/12759"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/media\/12756"}],"wp:attachment":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/media?parent=5491"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/categories?post=5491"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/tags?post=5491"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/ppma_author?post=5491"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}