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Introduction to Jupyter Notebook

Build a Conda Environment

Our default base is where we have installed Anaconda.

  • Go to the directory you wish to create your environment using Terminal.
    • cd <YourPath>
    • conda create --prefix ./env <tools You need>
    • conda install <your tool>

As an Example :

$ cd /d G:\GitRepositories\NewEnvironment
$ conda create --prefix ./env pandas matplotlib numpy scikit-Learn
$ conda activate
$ conda install jupyter

How To Open Jupyter Notebook

  • Firstly you should build a Conda Environment
  • Open Terminal
  • cd to the directory that contains the built environment.
cd /d <path>
Ex : cd /d G:\GitRepository\Machine-Learning\

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  • Activate Anaconda Environment simply by typing : $ conda activate [environmentName]
    • If you don't specifically name the [environmentName] name , it will automatically open the base environment. =======
  • Acitvate Anaconda Environment simply by typing : $ conda activate [environmentName]
    • If you don't specifictly name the [environmentName] name , it will automatically open the base environment.
    • You can see the existing environments by simply typing conda info --env

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  • Open Jupyter Notebook : $ jupyter notebook

As an Example :

$ cd /d G:\GitRepository\Machine-Learning/
$ conda activate RegEnv
$ jupyter notebook

Summary

$ cd /d G:\GitRepositories\NewEnvironment
$ conda create --prefix ./env pandas matplotlib numpy scikit-Learn
$ conda activate
$ conda install jupyter
$ jupyter notebook

Jupyter Guide

Switch to Markdown
  • Press Esc
  • Press m on the keyboard
Switch to Code
  • Press Esc
  • Press y on the keyboard
Delete a Line
  • Press Esc
  • Press x on the keyboard
Run a Line
  • Shift + Enter
Guide of each function
  • Go to the paranthesis () of the function
  • push shift + tab to see the function's documentation
Auto Complete
  • Only Tab ... push multiple times to show the options.

License

This repository is released under Apache 2.0 License. To put it in a nutshell, This means that you can use the source codes in any opensource projects or contributions. Attribution is not mandatory but appreciated.

To remove all barriers in the way of science.