If you prefer to learn about the fundamentals of the library first, you can read about the structure of figures, how to create and update figures, how to display figures, how to theme figures with templates, how to export figures to various formats and about Plotly Express, the high-level API for doing all of the above.You jump right in to examples of how to make basic charts, statistical charts, scientific charts, financial charts, maps, and 3-dimensional charts.Once you've installed, you can use our documentation in three main ways: This Getting Started guide explains how to install plotly and related optional pages. exporting notebooks to PDF with high-quality vector images). QtConsole, Spyder, P圜harm) and static document publishing (e.g. Thanks to deep integration with our Kaleido image export utility, plotly also provides great support for non-web contexts including desktop editors (e.g. The plotly Python library is sometimes referred to as "plotly.py" to differentiate it from the JavaScript library. Select the package and click on it to begin the installation.The plotly Python library is an interactive, open-source plotting library that supports over 40 unique chart types covering a wide range of statistical, financial, geographic, scientific, and 3-dimensional use-cases.īuilt on top of the Plotly JavaScript library ( plotly.js), plotly enables Python users to create beautiful interactive web-based visualizations that can be displayed in Jupyter notebooks, saved to standalone HTML files, or served as part of pure Python-built web applications using Dash.In the Anaconda Prompt or terminal, enter:.Launch Anaconda Navigator via the Start Menu or click on the Anaconda Navigator Desktop app.If you prefer to take a GUI approach, you can use Anaconda Navigator to install packages by doing the following: To install a package with Conda, open an Anaconda Prompt or terminal (depending on the operating system) and enter: conda install Installing Python Packages with Anaconda Navigator While you could use the GUI-based Navigator, it’s often quicker and easier to use the Conda command-line tool that is included as part of your Anaconda distribution. The Conda package manager is the most commonly used way to install and manage packages in a conda environment. The most common method of ensuring that both Anaconda and Conda are up-to-date is to open an Anaconda Prompt or terminal (depending on the operating system) and enter: conda update conda -allĬonda update anaconda Installing Python Packages with Conda Package Installation on Anaconda – Requirementsīefore any Python packages should be installed, ensure that the latest versions of Conda and Anaconda are present. Pip will work in any environment where Python is installed, including Anaconda and Conda environments, but it cannot install Conda Python packages.To avoid dependency conflicts, pip uses tools such as virtualenv and venv to create isolated environments. Pip installs all package dependencies, regardless of whether they conflict with other packages already installed.Conda will work with any version of Python, however it is limited to Anaconda and Conda environments.If there is conflict, Conda will let the user know that the installation cannot be completed. Conda analyzes the package for compatible dependencies and how to install them without conflict.Note that Conda and Pip handle dependencies differently: Navigator is the desktop graphical user interface (GUI) for managing packages, and Conda is the command line equivalent. ![]() ![]() If you work with Anaconda Python, you’re probably already familiar with the fact that Conda and Anaconda Navigator are package managers that can be used to add packages to your Anaconda/Conda environments.
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