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  1. www.geeksforgeeks.org › top-python-libraries-forTop 8 Python Libraries for Data Visualization - GeeksforGeeks

    Mar 8, 2024 · Top Python Libraries for Data Visualization. These libraries are so popular because they allow analysts and statisticians to create visual data models easily according to their specifications by conveniently providing an interface, and data visualization tools all in one place!

  2. www.geeksforgeeks.org › data-visualization-with-pythonData Visualization with Python - GeeksforGeeks

    • Database Used
    • Matplotlib
    • Seaborn
    • Bokeh
    • Plotly
    • Conclusion
    • GeneratedCaptionsTabForHeroSec

    Tips Database

    Tips database is the record of the tip given by the customers in a restaurant for two and a half months in the early 1990s. It contains 6 columns such as total_bill, tip, sex, smoker, day, time, size. You can download the tips database from here. Example: Output:

    See full list on geeksforgeeks.org

    Matplotlib is an easy-to-use, low-level data visualization library that is built on NumPy arrays. It consists of various plots like scatter plot, line plot, histogram, etc. Matplotlib provides a lot of flexibility. To install this type the below command in the terminal. After installing Matplotlib, let’s see the most commonly used plots using this ...

    See full list on geeksforgeeks.org

    Seaborn is a high-level interface built on top of the Matplotlib. It provides beautiful design styles and color palettes to make more attractive graphs. To install seaborn type the below command in the terminal. Seaborn is built on the top of Matplotlib, therefore it can be used with the Matplotlib as well. Using both Matplotlib and Seaborn togethe...

    See full list on geeksforgeeks.org

    Let’s move on to the third library of our list. Bokeh is mainly famous for its interactive charts visualization. Bokeh renders its plots using HTML and JavaScript that uses modern web browsers for presenting elegant, concise construction of novel graphics with high-level interactivity. To install this type the below command in the terminal.

    See full list on geeksforgeeks.org

    This is the last library of our list and you might be wondering why plotly. Here’s why – 1. Plotly has hover tool capabilities that allow us to detect any outliers or anomalies in numerous data points. 2. It allows more customization. 3. It makes the graph visually more attractive. To install it type the below command in the terminal.

    See full list on geeksforgeeks.org

    In this tutorial, we have plotted the tips dataset with the help of the four different plotting modules of Python namely Matplotlib, Seaborn, Bokeh, and Plotly. Each module showed the plot in its own unique way and each one has its own set of features like Matplotlib provides more flexibility but at the cost of writing more code whereas Seaborn bei...

    See full list on geeksforgeeks.org

    Learn how to visualize data using Python with four libraries: Matplotlib, Seaborn, Bokeh and Plotly. See examples of scatter plots, line charts, bar charts and histograms using the tips database.

    See full list on geeksforgeeks.org

  3. learnpython.com › blog › python-libraries-dataThe Top 5 Python Libraries for Data Visualization

    • Matplotlib. Matplotlib is the most widely used visualization library. It was born in 2003 as an open-source replacement of MATLAB, a scientific graphing package.
    • seaborn. seaborn is a visualization library that makes Matplotlib plots practical. It abstracts away Matplotlib’s complexity and offers an intuitive syntax and presentable results right out of the box.
    • Bokeh. Bokeh is a visualization library influenced by the grammar of graphics paradigm developed for web-based visualizations of big datasets. It provides a structured way to create plots and support server-side rendering of interactive visualizations in web applications.
    • Altair. Altair is a visualization library that provides a unique declarative syntax for interactive plot creation. It relies on the Vega-Lite grammar specification, allowing you to compose charts from graphical units and combine them in a modular way.

  4. matplotlib.orgMatplotlib — Visualization with Python

    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Create publication quality plots . Make interactive figures that can zoom, pan, update. Customize visual style and layout . Export to many file formats .

  5. seaborn.pydata.orgseaborn: statistical data visualization — seaborn 0.13.2 ...

    Seaborn provides a high-level interface for drawing attractive and informative statistical graphics. Learn how to install, use, and customize seaborn with tutorials, examples, and API reference.

  6. mode.com › blog › python-data-visualization-libraries12 Python Data Visualization Libraries to Explore for ... - Mode

    May 17, 2022 · Oct. '22 update: Python 3.9 and new libraries have been added to the standard notebook environment. Scroll through the Python Package Index and you'll find libraries for practically every data visualization need—from GazeParser for eye movement research to pastalog for realtime visualizations of neural network training.

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  8. www.datacamp.com › tutorial › seaborn-python-tutorialPython Seaborn Tutorial For Beginners: Start Visualizing Data

    Seaborn is a powerful and flexible data visualization library in Python that offers an easy-to-use interface for creating informative and aesthetically pleasing statistical graphics. It provides a range of tools for visualizing data, including advanced statistical analysis, and makes it easy to create complex multi-plot visualizations. Image Source

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