Purpose of matplotlib inline

Question

Could someone explain to me what exactly is the use of  matplotlib inline

User · Answer

Provided you are running Jupyter Notebook  the  matplotlib inline command will make your plot outputs appear in the notebook  also can be stored

User · Answer

Provided you are running IPython  the  matplotlib inline will make your plot outputs appear and be stored within the notebook    According to documentation     To set this up  before any plotting or import of matplotlib is   performed you must execute the  matplotlib magic command  This   performs the necessary behind-the-scenes setup for IPython to work   correctly hand in hand with matplotlib  it does not  however    actually execute any Python import commands  that is  no names are   added to the namespace       A particularly interesting backend  provided by IPython  is the   inline backend  This is available only for the Jupyter Notebook and   the Jupyter QtConsole  It can be invoked as follows    matplotlib inline       With this backend  the output of plotting commands is displayed inline   within frontends like the Jupyter notebook  directly below the code   cell that produced it  The resulting plots will then also be stored in   the notebook document

User · Answer

matplotlib is a magic function in IPython  I ll quote the relevant documentation here for you to read for convenience      IPython has a set of predefined    magic functions    that you can call with a command line style syntax  There are two kinds of magics  line-oriented and cell-oriented  Line magics are prefixed with the   character and work much like OS command-line calls  they get as an argument the rest of the line  where arguments are passed without parentheses or quotes  Lines magics can return results and can be used in the right hand side of an assignment  Cell magics are prefixed with a double     and they are functions that get as an argument not only the rest of the line  but also the lines below it in a separate argument     matplotlib inline sets the backend of matplotlib to the  inline  backend      With this backend  the output of plotting commands is displayed inline within frontends like the Jupyter notebook  directly below the code cell that produced it  The resulting plots will then also be stored in the notebook document    When using the  inline  backend  your matplotlib graphs will be included in your notebook  next to the code  It may be worth also reading How to make IPython notebook matplotlib plot inline for reference on how to use it in your code   If you want interactivity as well  you can use the nbagg backend with  matplotlib notebook  in IPython 3 x    as described here

User · Answer

To explain it clear    If you don t like it like this     add  matplotlib inline    and there you have it in your jupyter notebook

User · Answer

If you want to add plots to your Jupyter notebook  then  matplotlib inline is a standard solution  And there are other magic commands will use matplotlib interactively within Jupyter    matplotlib  any plt plot command will now cause a figure window to open  and further commands can be run to update the plot  Some changes will not draw automatically  to force an update  use plt draw     matplotlib notebook  will lead to interactive plots embedded within the notebook  you can zoom and resize the figure   matplotlib inline  only draw static images in the notebook

User · Answer

It is not mandatory to write that  It worked fine for me without   matplotlib  magic function  I am using Sypder compiler  one that comes with in Anaconda

User · Answer

Starting with IPython 5 0 and matplotlib 2 0 you can avoid the use of   IPython   s specific magic and use   matplotlib pyplot ion   matplotlib pyplot ioff   which have the   advantages of working outside of IPython as well    ipython docs

User · Answer

It just means that any graph which we are creating as a part of our code will appear in the same notebook and not in separate window which would happen if we have not used this magic statement

User · Answer

If you don t know what backend is   you can read this   https   matplotlib org tutorials introductory usage html backends     Some people use matplotlib interactively from the python shell and   have plotting windows pop up when they type commands  Some people run   Jupyter notebooks and draw inline plots for quick data analysis    Others embed matplotlib into graphical user interfaces like wxpython   or pygtk to build rich applications  Some people use matplotlib in   batch scripts to generate postscript images from numerical   simulations  and still others run web application servers to   dynamically serve up graphs  To support all of these use cases    matplotlib can target different outputs  and each of these   capabilities is called a backend  the  frontend  is the user facing   code  i e   the plotting code  whereas the  backend  does all the hard   work behind-the-scenes to make the figure    So when you type  matplotlib inline   it activates the inline backend  As discussed in the previous posts        With this backend  the output of plotting commands is displayed inline   within frontends like the Jupyter notebook  directly below the code   cell that produced it  The resulting plots will then also be stored in   the notebook document

User · Answer

TL DR   matplotlib inline - Displays output inline    IPython kernel has the ability to display plots by executing code  The IPython kernel is designed to work seamlessly with the matplotlib plotting library to provide this functionality       matplotlib is a magic command which performs the necessary behind-the-scenes setup for IPython to work correctly hand-in-hand with matplotlib    it does not execute any Python import commands  that is  no names are added to the namespace    Display output in separate window   matplotlib   Display output inline   available only for the Jupyter Notebook and the Jupyter QtConsole    matplotlib inline   Display with interactive backends   valid values  GTK3Agg    GTK3Cairo    MacOSX    nbAgg    Qt4Agg    Qt4Cairo    Qt5Agg    Qt5Cairo    TkAgg    TkCairo    WebAgg    WX    WXAgg    WXCairo    agg    cairo    pdf    pgf    ps    svg    template     matplotlib gtk   Example - GTK3Agg - An Agg rendering to a GTK 3 x canvas  requires PyGObject and pycairo or cairocffi    More details about matplotlib interactive backends  here       Starting with IPython 5 0 and matplotlib 2 0 you can avoid the use of    IPython   s specific magic and use matplotlib pyplot ion   matplotlib pyplot ioff      which have the advantages of working outside of IPython as well    Refer  IPython Rich Output - Interactive Plotting

[python] Purpose of "%matplotlib inline"

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