- Installation #
- Other tips #
- Check the info #
- Multiline commands #
- Hotkeys / Shortcuts #
- Jupyter notebook on remote server #
- Install new python package inside Jupyter Notebook #
- Display dataframes side-by-side #
- Get previous outputs #
- Display 2 figures side-by-side markdown cell #
- Magic Functions #
- Extensions #
Installation #
Jupyter notebook #
# BY PIP
pip install --upgrade pip
pip install --upgrade ipython jupyter
# BY CONDA
conda install ipython jupyter
Or read more in this note.
If you meet error OSError: [Errno 99] Cannot assign requested address
, try
jupyter notebook --ip=127.0.0.1 --port=8080
# or
jupyter notebook --ip=127.0.0.1 --port=8080 --allow-root
Setting up a password #
# create a juputer notebook config file
# it can be used for other settings
# https://jupyter-notebook.readthedocs.io/en/stable/public_server.html#prerequisite-a-notebook-configuration-file
jupyter notebook --generate-config
# create a new password
# note: sha1 cannot be reverted!!
jupyter notebook password
Inside notebook:
from notebook.auth import passwd
passwd()
With docker
# create a sha1 password
# download file create_sha1.py from https://github.com/dinhanhthi/scripts
# run ./create_sha1.py
# docker-compose.yml
environment:
- PASSWD='sha1:d03968479249:319e92302e68d601392918f011d6c9334493023f'
# Dockerfile
CMD /bin/bash -c 'jupyter lab --no-browser --allow-root --ip=0.0.0.0 --NotebookApp.password="$PASSWD" "[email protected]"'
R with jupyter notebook #
Read more here.
# install jupyter
sudo apt-get install libzmq3-dev libcurl4-openssl-dev libssl-dev jupyter-core jupyter-client
# install R on linux
sudo apt install r-base
# R kernel for Jupyter Notebook
R # enter R environnement
# install R kernel
install.packages(c('repr', 'IRdisplay', 'IRkernel'), type = 'source')
# or
install.packages(c('repr', 'IRkernel'), type = 'source')
# make jupyter see r kernel
IRkernel::installspec() # current user
IRkernel::installspec(user = FALSE) # global
# embedded R
# use by cell magic %%R
pip install rpy2
# in a notebook
%load_ext rpy2.ipython
# then use
%%R
# R's codes
Other tips #
- Running 2 tasks in the same cell TAKE LONGER TIME than running each on different cells.
- Download a folder in jupyter notebook:
Inside notebook, use:
%%bash
tar -czf archive.tar.gz foldernameOr using nbzip (only working on current server).
Check the info #
# function's info
?<func-name>
# function's shortcode
??<func-name>
# get the list of current variables
whos
Check where command executed from (in your $path
)?
!type python
python is /Users/thi/anaconda/envs/python3.6/bin/python
Multiline commands #
# Using '\'
df.columns = df.columns.str.replace('.', ' ')\
.str.replace('\s+', ' ')\
.str.strip().str.upper()
You CANNOT put # comments
at the end of each line break!
Hotkeys / Shortcuts #
There are 2 modes: command mode (pres ESC to activate) and edit mode (Enter to activate). Below are the most useful ones (for me).
You can edit / add more shortcuts in Help > Edit Keyboard Shortcuts.
For both modes,
- Shift + Enter run the current cell, select below.
- Ctrl + Enter run selected cells.
- Alt + Enter run the current cell, insert below.
- Ctrl + S save and checkpoint.
Command modes,
- Enter take you into edit mode.
- H show all shortcuts.
- Up / Down select cell above / below.
- Shift + Up / Down extend selected cells above / below.
- A / B insert cell above / below.
- X cut selected cells.
- C copy selected cells.
- V / Shift + V paste cells below / above.
- D, D (press the key twice) delete selected cells.
- Z undo cell deletion.
- S Save and Checkpoint.
- Y change the cell type to Code.
- M change the cell type to Markdown.
Edit mode,
- Esc take you into command mode.
- Tab code completion or indent.
- Ctrl + ] indent.
- Ctrl + [ dedent.
- Ctrl + A select all.
- Ctrl + Z undo.
- Ctrl + Shift + Z or Ctrl + Y redo.
Jupyter notebook on remote server #
Open jupyter notebook in local browser but the backend-server is on remote.
If jupyter server is already running on remote at
http://192.168.0.155:9889
,ssh -N -L localhost:9888:192.168.0.155:9899 <username-remote>@<remote-host> -p <port>
# if there is no port, remove `-p <port>`Open browser:
http://localhost:9888
(type password if needed).If jupyter server is not running on remote yet,
# connect to remote
ssh <username-remote>@<remote-host> -p <port>
# if there is no port, remove `-p <port>`On remote,
# run juputer with custom port
jupyter notebook --no-browser --port=9899
# if there is error `OSError: [Errno 99] Cannot assign requested address`
jupyter notebook --ip=0.0.0.0 --no-browser --port=9899
# if there is error `Running as root is not recommended`
jupyter notebook --ip=0.0.0.0 --no-browser --port=9899 --alow-rootIt's running and there are somethings like that,
http://127.0.0.1:9889/?token=717d9d276f0537a9...831793df6319ad389accd
Open another terminal window and type,
ssh -N -L localhost:9888:localhost:9889 <username-remote>@<remote-host> -p <port>
# if there is no port, remove `-p <port>`
# there is nothing but it's runningOpen browser:
http://localhost:9888/?token=717d9d276f0537a9...831793df6319ad389accd
You can choose any port number you wanna instead of 9888
and 9889
(they can be the same), note that, you need to use a port number GREATER THAN 8000
!
Install new python package inside Jupyter Notebook #
Using conda
[ref],
# Install a conda package in the current Jupyter kernel
import sys
!conda install --yes --prefix {sys.prefix} numpy
# DON'T DO THIS
!conda install --yes numpy
Using pip
,
# Install a pip package in the current Jupyter kernel
import sys
!{sys.executable} -m pip install numpy
# DON'T DO THIS
!pip install numpy
Check version and update/upgrade,
!pip show pandas
Display dataframes side-by-side #
from IPython.display import display_html
def display_side_by_side(*args):
html_str=''
for df in args:
html_str+=df.to_html()
display_html(html_str.replace('table','table style="display:inline; margin-right: 5px;"'),raw=True)
display_side_by_side(df1,df2,df1)
Get previous outputs #
_ # previous output
__ # second-to-last output
___ # third-to-last output
Display 2 figures side-by-side markdown cell #
Put below codes in the markdown cell of Jupyter Notebook.
<tr>
<td> <img src="Nordic_trails.jpg" alt="Drawing" style="width: 250px;"/> </td>
<td> <img src="Nordic_trails.jpg" alt="Drawing" style="width: 250px;"/> </td>
</tr>
Magic Functions #
- Check the full list (in examples) here or their docs here.
- You can define your custom magic functions here.
Auto update the new updated modules (put at the beginning of the notebook)
%load_ext autoreload
%autoreload 2 # Reload all modules every time before executing
%autoreload 0 # disable autoreloader
Check more settings of %autoreload
here.
Show the plots inside the notebook:
%matplotlib inline
Get the commands from 1 to 4:
%history -n 1-4 # get commands 1 to 4
Extensions #
Table of contents #
- Install npm and nodejs.
- Install this extension.
- Enable in jupyter lab view.
- Refresh the page.
# errors
# UnicodeDecodeError: 'ascii' codec can't decode byte 0xf0 in position 23: ordinal not in range(128)
npm config set unicode false
Debugger #
- Install
xeus-python
,jupyterlab
pip install xeus-python
pip install jupyterlab
- Install this extension.
- Refresh the page, you have to choose kernel xpython (instead of Python 3) to use the debugger.