Download and install Anaconda. If it’s too big, you can choose Miniconda instead. Suppose that the Anaconda is installed (by default) in:


Add below directories into System Environment Variables:


If you don’t wanna use Anaconda and install it by yourself, add this:


(You can find C:\...\Roaming by typing %appdata% in the Windows Explorer’s navigation bar)

Using Windows’ command prompt (cmd) or PowerShell as a command line environment. For me, I prefer cmder (use this setting file).

Jupyer Notebook

Anaconda contains JN in it, no need to install it again. cd to the folder you wanna work on and run

python -m notebook

If you meet the error ImportError: DLL load failed, try:

active base # active environment "base" in anaconda
jupyter notebook


Updated later!

Linux (Ubuntu)

Python is already installed on Ubuntu. You would like to install Anaconda, download and install it.

Add Anaconda to the $path:

  1. Open ~/.profile.
  2. Paste export PATH=/home/<user>/anaconda3/bin:$PATH (this is the default directory when you install anaconda)
  3. Excute: source ~/.profile in order to immediately reflect changes to your current terminal instance
  4. Check with which python, if it returns /home/<user>/anaconda3/bin/python then it works (python -v returns anaconda also).
  5. If you wanna go back to the system default, open the .bashrc file and comment out settings of anaconda with #. That’s it!

On Ubuntu, I use Guake Terminal to replace the system terminal.

Install new packages

Install packages with pip

Install pip (It’s actually installed with Anaconda). If you wanna upgrade it to the latest version:

python -m pip install --user --upgrade pip # install for current user only
python -m pip install --upgrade pip # need to run cmder as administrator

First, activate <env> and then using easy_install -U pip. You can check the version of pip by pip -V.

Install a package with pip:

pip install <package> # administrator <-- SHOULDN'T!!!
pip install --user <package> # current user only

Check the version & info of a package:

pip show <package>

If install packages with pip, they are installed in which environment of conda? Where pip is executed from.

which python
which pip

conda info --envs
# or
# conda env list

# conda environments:
base                  *  C:\ProgramData\Anaconda3
fastai                   C:\Users\thi\.conda\envs\fastai

Install packages with conda

activate <env> # you need to activate an environment first
conda install <package> # install for <env> only


acctivate <env> # choose an env first
conda update <package> # ud package in that env

List all installed packages (in <env>),

conda list

Update packages listed in an env file to current env,

conda env update -n <env> -f /path/to/<file>.yml

pip vs conda?


  • pip installs python packages in any environment.
  • conda installs any package in conda environments.

Which one to be used?[ref]

  • If you installed Python using Anaconda or Miniconda, then use conda to install Python packages. If conda tells you the package you want doesn’t exist, then use pip (or try conda-forge, which has more packages available than the default conda channel).
  • If you installed Python any other way (from source, using pyenv, virtualenv, etc.), then use pip to install Python packages

Install Jupyter Notebook

By using pip,

# first, always upgrade pip!
pip install --upgrade pip
pip install --upgrade ipython jupyter

By using conda,

conda install ipython jupyter


Install conda without Anaconda

You can even install conda using pip (without installing Anaconda / Minianaconda):

pip install conda

Update conda

conda update -n base -c defaults conda

If there is an error TypeError: LoadLibrary() argument 1 must be str, not None at the end of the log, try to activate the environment base before running above line.

activate base # on Windows
source activate base # on MacOS


Check an official doc here or this useful post.

Create a new environment with python version 3.7:

conda create -n <env-name> python=3.7 anaconda

# The same python version with current shell's Python interpreter
conda create -n <env-name> python 

# with addtional packages (python will be automatically installed)
conda create -n <env-name> <package1> <package2>
# with version
conda create -n <env-name> <package1>=1.16 <package2>

# in different directory
conda create --prefix /path/to/<env-name>

# create from file <file>.yml
conda env create -n <env> -f /path/to/<file>.yml

# Clone from another env
conda create --name <cloned-env> --clone <env>

Most of below commands are assumed to be run in an environment named env which is already activated. If you don’t activate any environment before, use an alternative instead. For example,

conda update pandas             # <env> activated
conda update -n <env> pandas    # <env> isn't activated
conda update -p /path/to/<env>  # <env> isn't in the default directory of conda

conda env export -f <file>.yml                       # <env> activated & current folder
conda env export -n <env> -f /path/to/<file>.yml      # <env> isn't activated & different folder
conda update -p /path/to/<env> -f /path/to/<file>.yml # <env> isn't in the default directory of conda & different folder

Deactivate an env:

conda deactivate # Linux
deactivate # Windows
source deactivate # MacOS

Remove an env,

conda remove -n <env> --all

Show the list of current envs:

conda info --envs
# or
conda env list

Export to an env file,

conda env export -f <file>.yml

Create from file,

conda env create -n <env> -f /path/to/<file>.yml

Update packages listed in an env file to current env,

conda env update -n <env> -f /path/to/<file>.yml --prune

Clone from another env,

conda create --name <cloned-env> --clone <env>

Kernel 2 & 3 for Jupyter Notebook

Check if nb_conda_kernels is installed by conda list. If not, install it by:

conda install nb_conda_kernels

If you are using Python 2 and you wanna separate Python 3,

conda create -n py37 python=3.7 ipykernel # "py37" is a custom name

If you are using Python 3 and you wanna separate Python 2,

conda create -n py27 python=2.7 ipykernel # "py37" is a custom name

Restart the Jupyter Notebook, the list of kernels is available under New.

Conda Revisions

Check revisions,

conda list --revisions

Go back to revision 1,

conda install --revision 1

Notice an error?

Everything on this site is published on Github. Just summit a suggested change or email me directly (don't forget to include the URL containing the bug), I will fix it.