How to install graph in python

Как установить модуль graph в python?

 @ urban_will   Чтобы установить модуль graph в Python, вам нужно сначала убедиться, что у вас установлен пакетный менеджер pip . В большинстве случаев pip уже установлен вместе с Python. Чтобы убедиться, что pip установлен, можно выполнить следующую команду в командной строке (терминале) или командной оболочке:

Если pip установлен, вы увидите его версию. Если же pip не установлен, вам нужно будет установить его сначала.

После того как у вас установлен pip , вы можете установить модуль graph с помощью следующей команды:

Эта ко***** установит модуль graph и все необходимые зависимости. После успешной установки вы сможете импортировать модуль graph в своем коде, используя следующую конструкцию:

Для установки модуля graph в Python необходимо выполнить следующие шаги:

1. Убедитесь, что у вас установлен менеджер пакетов pip. Для этого можно запустить команду pip —version в командной строке. Если pip не установлен, его можно установить, следуя инструкциям на официальном сайте pip (https://pip.pypa.io/en/stable/installation/).
2. Откройте командную строку (или терминал в Linux/MacOS) и выполните команду pip install graph.
3. Дождитесь завершения установки модуля. После установки вы можете использовать модуль graph в своих программах на Python.

Обратите внимание, что в Python есть несколько модулей, которые называются graph , поэтому в зависимости от того, какой модуль вам нужен, вы можете использовать другую команду установки. Например, если вам нужен модуль graph-tool , вы можете установить его с помощью команды pip install graph-tool .

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How to Install Matplotlib in Python?

Matplotlib is an open-source python library that can be installed using python packages like pip and conda on different operating systems like Windows, Linux, and macOS.

• It displays numeric data in the form of plots, graphs, and charts in Python.
• It provides a wide variety of functionality for plotting.
• It is a very useful library that helps to plot different figures on the graph, like line plot, bar graphs, contour plot, histograms, scatter plots, etc.

Prerequisites

• It is mandatory to install python from www.python.org before installing matplotlib.
• During the installation of matplotlib, some files are automatically installed. The following list is mainly for reference:
  • Python (>= 3.7)
  • NumPy (>= 1.17)
  • setup tools
  • cycler (>= 0.10.0)
  • dateutil (>= 2.7)
  • kiwisolver (>= 1.0.1)
  • Pillow (>= 6.2)
  • pyparsing (>=2.2.1)
  • fontTools (>=4.22.0)

  Installing Matplotlib

  Let’s discuss installation of matplotlib on different operating systems, below.

  Installing Matplotlib on MacOS

  1. Check if pip3 and python3 are installed correctly by running the following command:

  

  Installing Matplotlib in Windows

  Steps for installing Matplotlib on Windows:

  1. Download python from www.python.org according to your operating system and install it.
  2. Next, install Matplotlib using the following PIP command in the command prompt terminal:

  

  The installation will start automatically, and Matplotlib will be successfully installed with its latest version.

  

  You must have noticed that some files are automatically installed with matplotlib, like python-dateutil, packaging, pyparsing, numpy, kiwisolver, etc. These files are the mandatory dependencies of the matplotlib module.

  Matplotlib Installation On Ubuntu

  Python is pre-installed on Ubuntu computers. Pip, on the other hand, is not installed. There are two ways to install pip:

  1. Install the complete package by downloading python from python.org, then use the apt install command for installing on the ubuntu system.
  2. Another way is to directly install pip first on Ubuntu and then install matplotlib by performing the following steps:

  

  for installing matplotlib in python3, use

  

  For installing matplotlib in python2. Matplotlib is successfully installed on Ubuntu using the above commands.

  Installing From the Source

  First, we must install the dependencies (as discussed in the ‘prerequisites’ section). A C compiler is required for this.

  To run the tests, you will need to install some additional dependencies:

  Advanced Usage

  Installing Matplotlib Using Conda

  Conda is an open-source environment and package system.

  • It offers prebuilt packages and can install and update.
  • We do not need to install the system and python packages separately since everything is already included in the .yml (a text file that contains a list of dependencies, etc., in a single file). Anaconda must be commanded below in cmd /conda prompt/ terminal:

  Above command install matplotlib from anaconda main channel. Matplotlib can also be installed from the anaconda community channel.

  

  Matplotlib Installation Using PIP

  Comparing Python2 and Python3

  For Python2 Users:

  Python2 users must use pip for the installation of matplotlib.

  For macOS, windows, and ubuntu users:

  For Python3 Users:

  Python3 users must use pip3 for the installation of matplotlib.

  For macOS, windows, and ubuntu users:

  How to Install Matplotlib Python venv?

  How to Install Matplotlib Python venv in MacOS?

  How to Install Matplotlib Python venv in Windows

  

  

  1. Retrieve the latest version of matplotlib from the git source, and install matplotlib in editable mode.

  How to Install Matplotlib Python venv in Ubuntu?

  1. Retrieve the latest version of matplotlib from the git source, and install matplotlib in editable mode.

  Verify Matplotlib Installation

  Verifying Installation of Matplotlib on MacOS

  Verifying the installation of matplotlib on macOS can be done using the command:

  1. We set up the python environment by typing python3 in the terminal.
  2. Successful import of matplotlib verifies that matplotlib is installed on the system. The command for importing matplotlib is import matplotlib . Set of commands to verify installation

  

  Verifying Installation of Matplotlib on Windows

  Verifying matplotlib installation can be done in two different ways.

  

  In the command prompt.

  1. Another verification method is setting up a python environment, importing matplotlib, and then checking its version.

  

  Verifying Installation of Matplotlib on Ubuntu

  Verifying the Installation of matplotlib on Ubuntu can be done using the command:

  1. We set the python environment by typing python3 in the terminal.
  2. Successful import of matplotlib verifies that matplotlib is installed on the system. The command for importing matplotlib is import matplotlib .
  3. Checking the version of the matplotlib using the command matplotlib.__version__

  Set of commands to verify installation

  

  What Happens If Matplotlib is not Installed Correctly?

  The Python «ModuleNotFoundError: No module named ‘matplotlib'» occurs when we forget to install the matplotlib module before importing it or installing it in an incorrect environment. Check if pip is installed by simply writing pip in the python console. If you do not have pip, get a python script call g e t − p i p . p y get-pip.py g e t − p i p . p y from the internet and save it to your local system.

  Run the g e t − p i p . p y get-pip.py g e t − p i p . p y script to install pip by writing the following code in cmd (command prompt) to install pip:

  Now in cmd, type the following code to install matplotlib with its dependencies:

  Conclusion

  • Python and compilers are prerequisites for installing matplotlib.
  • Matplotlib can be installed using conda and pip python packages. Pip contains python libraries. On the other hand, conda has python libraries, c libraries, and executables like c compilers, etc.
  • Matplotlib can be installed from the GitHub repository of matplotlib.
  • Matplotlib installation verification can be done in two ways.
    • Importing matplotlib
    • Checking matplotlib version

    Learn More:

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    Getting Started with Plotly in Python

    Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

    Overview¶

    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.

    Built 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. The plotly Python library is sometimes referred to as «plotly.py» to differentiate it from the JavaScript library.

    Thanks to deep integration with our Kaleido image export utility, plotly also provides great support for non-web contexts including desktop editors (e.g. QtConsole, Spyder, PyCharm) and static document publishing (e.g. exporting notebooks to PDF with high-quality vector images).

    This Getting Started guide explains how to install plotly and related optional pages. Once you’ve installed, you can use our documentation in three main ways:

    1. You jump right in to examples of how to make basic charts, statistical charts, scientific charts, financial charts, maps, and 3-dimensional charts.
    2. 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.
    3. You can check out our exhaustive reference guides: the Python API reference or the Figure Reference

    For information on using Python to build web applications containing plotly figures, see the Dash User Guide.

    We also encourage you to join the Plotly Community Forum if you want help with anything related to plotly .

    Installation¶

    plotly may be installed using pip :

    This package contains everything you need to write figures to standalone HTML files.

    Note: No internet connection, account, or payment is required to use plotly.py. Prior to version 4, this library could operate in either an «online» or «offline» mode. The documentation tended to emphasize the online mode, where graphs get published to the Chart Studio web service. In version 4, all «online» functionality was removed from the plotly package and is now available as the separate, optional, chart-studio package (See below). plotly.py version 4 is «offline» only, and does not include any functionality for uploading figures or data to cloud services.

    import plotly.express as px fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2]) fig.write_html('first_figure.html', auto_open=True) 

    Plotly charts in Dash¶

    Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash , click «Download» to get the code and run python app.py .

    Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.

    Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.

    JupyterLab Support¶

    For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip :

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