Python for Data Science

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For a standard Python tutorial go to Python


  • Udemy - Python for Data Science and Machine Learning Bootcamp


Anaconda is a free and open source distribution of the Python and R programming languages for data science and machine learning related applications (large-scale data processing, predictive analytics, scientific computing), that aims to simplify package management and deployment. Package versions are managed by the package management system conda.

En otras palabras, Anaconda puede ser visto como un paquete (a distribution) que incluye no solo Python (or R) but many libraries that are used in Data Science, as well as its own virtual environment system. It's an "all-in-one" install that is extremely popular in data science and Machine Learning.Creating sample array for the following examples:


Installation from the official Anaconda Web site:

Anaconda comes with a few IDE

  • Jupyter Lab
  • Jupyter Notebook
  • Spyder
  • Qtconsole
  • and others

Anaconda Navigator

Anaconda Navigator is a GUI that helps you to easily start important applications and manage the packages in your local Anaconda installation

You can open the Anaconda Navigator from the Terminal:



Jupyter comes with Anaconda.

  • It is a development environment (IDE) where we can write codes; but it also allows us to display images, and write down markdown notes.
  • It is the most popular IDE in data science for exploring and analyzing data.
  • Other famoues IDE for Python are Sublime Text and PyCharm.
  • There is Jupyter Lab and Jupyter Notebook

Remote connection


(base) adelo@vmi346715:~/.jupyter$ openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout mykey.key -out mycert.pem
Generating a RSA private key
writing new private key to 'mykey.key'
You are about to be asked to enter information that will be incorporated
into your certificate request.
What you are about to enter is what is called a Distinguished Name or a DN.
There are quite a few fields but you can leave some blank
For some fields there will be a default value,
If you enter '.', the field will be left blank.
Country Name (2 letter code) [AU]:IE	
State or Province Name (full name) [Some-State]:Dublin
Locality Name (eg, city) []:Dublin
Organization Name (eg, company) [Internet Widgits Pty Ltd]:.
Organizational Unit Name (eg, section) []:.
Common Name (e.g. server FQDN or YOUR name) []:sinfronteras    
Email Address []

Share Jupyter Notebook online

  • GitHub:

  • 'Nbviewer

Customize Jupyter


Ver el tema que muestran en esta página:

jt   -t oceans16     -cellw 98%   -lineh 120   -fs 14   -nfs 14   -dfs 14   -ofs 14

jt   -t monokai      -cellw 98%   -lineh 120   -fs 14   -nfs 14   -dfs 14   -ofs 14   -f fira   -nf ptsans   -N   -kl   -cursw 2   -cursc r   -T


This post mention so nice extension and configuration that can be done:

Unofficial Jupyter Notebook Extensions

This is very important. There are very nice extensions in this package:


I had some issues to install it. La format indicada por defecto:

pip install jupyter_contrib_nbextensions
jupyter contrib nbextension install --user

A través de la forma anterior no pude instalar el paquete de forma correcta. La instalación no retornó errorres, y la extensión se mostraba en Jupyter-notebook pero no podía activar "enable" las extensiones.

Al parecer es un problema con la ubicación de la instalación. Yo estaba usando conda pero conda está presentando problemas. La instalación de los paquestes demora muchísimo y luego el paquete parece no estar disponible.

En el siguiente post encontré una solución para instalar nbextension usando pip:

pip install --upgrade jupyter_contrib_nbextensions
jupyter contrib nbextension install  --sys-prefix  --symlink

«--symlink» creo que lo usé pero no estoy completamente seguro. También realicé el --upgrade pero creo que la diferencia la hicieron las opciones --sys-prefix --symlink

Si no se muestra la Nbextensions tab (), try to reinstall the

pip install jupyter_nbextensions_configurator


conda install -c conda-forge jupyter_nbextensions_configurator

CustomJS and CustonCSS files

This is a good post:

Keyboard Shortcut Customization:

/** Mis configuraciones */ 

// This is to enable syntax highlighting for SQL code: 
require(['notebook/js/codecell'], function(codecell) {
  codecell.CodeCell.options_default.highlight_modes['magic_text/x-mssql'] = {'reg':[/^%%sql/]} ;'kernel_ready.Kernel', function(){
      if (cell.cell_type == 'code'){ cell.auto_highlight(); } }) ;

// My plain theme
// This is a good post where I took some ideas to write the following fuction:
function plainTheme() {
    var input_promp_fields = document.getElementsByClassName("prompt_container");
    var text_render_fields = document.getElementsByClassName("text_cell_render");

    if (input_promp_fields[0].style.visibility == "collapse"){
        action = "visible";
        input_marginLeft = "0px";
        border_top  = "3px";
        prompt_width = "74px";
        padding_top = "0px";
        output_margin = "40px";
        action = "collapse";
        input_marginLeft = "74px";
        border_top  = '0px';
        prompt_width = "74px";
        padding_top = "40px";
        output_margin = "40px";

    // Si queremos usar !important debemos hacerlo de esta forma utilizando JQuery:
    var text_cell_fields = document.getElementsByClassName("text_cell");
            'cssText': `width: 40px !important; max-width: ${prompt_width} !important; min-width: ${prompt_width} !important;`

            'visibility', `${action}`
            'padding-left', `${input_marginLeft}`
            'margin-left', `${output_margin}`
            'cssText': `border-top-width: ${border_top} !important; border-bottom-width: ${border_top} !important;`
            'cssText': `padding-top:${padding_top} !important; border-top-width: ${border_top} !important; border-bottom-width: ${border_top} !important;`

            'cssText': `margin-left: -10px;`

Jupyter.keyboard_manager.command_shortcuts.add_shortcut('Alt-Ctrl-Q', {
    help : '...',
    help_index : 'zz',
    handler : function (event) {
    return false;

Jupyter.keyboard_manager.edit_shortcuts.add_shortcut('Alt-Ctrl-Q', {
    help : '...',
    help_index : 'zz',
    handler : function (event) {
    return false;

// This could be very usefull. It allows to add text automatically into a cell
Jupyter.keyboard_manager.edit_shortcuts.add_shortcut('Ctrl-Shift-J', {
    help : '...',
    help_index : 'zz',
    handler : function (event) { = 'blue'
        var target = Jupyter.notebook.get_selected_cell()
        var cursor = target.code_mirror.getCursor()
        var before = target.get_pre_cursor()
        var after = target.get_post_cursor()
        target.set_text(before + 'from IPython.core.display import display, HTML; \n\taverrrdisplay(HTML("<style>.container { width:98% !important;}</style>"))' + after) += 20 // where to put your cursor
        return false;

// To get the real value of a css field:
// window.getComputedStyle(document.body).backgroundColor
// window.getComputedStyle(document.getElementsByClassName("input_area")[0]).backgroundColor

/*  Mis configuraciones  */

.container { width:98% !important; }
/* document.getElementById("notebook-container").style.minWidth = "50%"; */
/* document.getElementById("notebook-container").style.maxWidth = "50%"; */

#notebook-container {
 width:98% !important;

.CodeMirror-gutters {
 background-color: transparent !important;
 background: transparent !important;

.CodeMirror-linenumber {
 margin-left: -20px !important;

.output_subarea {
 margin-left: 40px !important;

#toc .fa-fw {
 color: blue !important;

#toc .highlight_on_scroll {
 margin-left: -4px !important;

#toc {
 padding-left: 10px !important;

/*  I have also changed the color
/*  #a6e22e   by   #388bfd 
 *  in the entire custom.css

/* I have also chenged some of the properties of the toc directly above in the code: 

#toc-wrapper {
 z-index: 90;
 position: fixed !important;
 display: flex;
 flex-direction: column;
 overflow: hidden;
 padding: 10px;
 padding-top: 40px !important;
 border-style: solid;
 border-width: thin;
 border-right-width: medium !important;
 background-color: #1e1e1e !important;
#toc-wrapper.ui-draggable.ui-resizable.sidebar-wrapper {
 border-color: rgba(93,92,82,.25) !important;
#toc a,
#navigate_menu a,
.toc {
 color: #f8f8f0 !important;
 font-size: 16pt !important;
#toc li > span:hover {
 background-color: rgba(93,92,82,.25) !important;
#toc a:hover,
#navigate_menu a:hover,
.toc {
 color: #DAA520 !important;
 font-size: 16pt !important;
#toc-wrapper .toc-item-num {
 color: #388bfd !important;
 font-size: 16pt !important;

Configurations from the Juniper notebook

from IPython.core.display import display, HTML; 

display(HTML("<style>.container { width:98% !important;}</style>"<))

display(HTML('<style>.prompt.input_prompt{display:none !important;}</style>'))
display(HTML('<style>.prompt.input_prompt{visibility: visible !important;</style>'))
display(HTML('<style>.prompt.input_prompt{margin-left8kmclustering.ipynb 50px}</style>'))
display(HTML('<style>.prompt.input_prompt{visibility: visible !important; width: 0px !important; min-width: 0px !important}</style>'))  

display(HTML('<style>.input_area{margin-left: -50px;}</style>'))
display(HTML('<style>.input{margin-left: -20px;}</style>'))

display(HTML('<style>.output_area{margin-left: 55px}</style>'))

# display(HTML('<style>.cell{margin-bottom: -5px !important; margin-top: -5px !important;}</style>'))
# display(HTML('<style>.code_cell{margin-bottom: -5px !important; margin-top: -5px !important;}</style>'))

# display(HTML('<style>.output_wrapper{margin-bottom: 0px !important; margin-top: 0px !important;}</style>'))

Online Jupyter

There are many sites that provides solutions to run your Jupyter Notebook in the cloud:

I have tried:
Parece bueno, pero tiene opciones que no son gratis
Parece bueno pero no encontré la forma adicionar una TOC

Es el que estoy utilizando ahora

Some remarks

Executing Terminal Commands in Jupyter Notebooks

If we are in the Notebook, and we want to run a shell command rather than a notebook command we use the ! or %

Try, for example:


It's the same as if you opened up a terminal and typed it without the !

Creating Presentations in Jupyter Notebook with RevealJS

Some of the most popular Python Data Science Libraries

  • NumPy
  • SciPy
  • Pandas
  • Seaborn
  • SciKit'Learn
  • MatplotLib
  • Plotly
  • PySpartk

NumPy and Pandas

Data Visualization with Python

Natural Language Processing

Dash - Plotly