Difference between revisions of "Python for Data Science"

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<br />
 
<br />
==Binance API==
 
To get the API Key and Secret Key es muy simple. Basta con ir a '''Binance > User Icon > IPI Management''' and create an API
 
 
 
Cada Wallat tiene su API. Por ejemplo en '''Binance > Derivatives > USD-Futures => Information > API Access''' se encuentra la informacin oficial sobre las API:<br />
 
https://binance-docs.github.io/apidocs/futures/en/#change-log
 
* Spot/Margin/Saving/Mining
 
* USD-Futures
 
* Coin-M Futures
 
* Vanilla Options
 
 
 
<br />
 
===USD-Futures API===
 
https://binance-docs.github.io/apidocs/futures/en/#change-log
 
 
In the above links se encuentra el link to the official '''SDK for Binance Futures''' (Python, Java):
 
<blockquote>
 
What’s the difference between an SDK and an API?
 
There isn't a simple answer to how an SDK and an API differ, because SDKs commonly contain an API.
 
When a developer uses an SDK to create systems and develop applications, those applications need to communicate with other applications. An SDK includes an API to make that communication possible.
 
</blockquote>
 
 
 
<br />
 
====Binance Testnet environments====
 
https://testnet.binancefuture.com/en/futures/BTCUSDT
 
 
https://dev.binance.vision/t/binance-testnet-environments/99
 
 
 
<br />
 
====Python 3 SDK for Binance Futures====
 
: https://github.com/Binance-docs/Binance_Futures_python
 
:* In the example folder there are many examples
 
 
<blockquote>
 
<syntaxhighlight lang="bash">
 
git  clone  https://github.com/Binance-docs/Binance_Futures_python.git
 
cd  Binance_Futures_python
 
python3  setup.py  install
 
</syntaxhighlight>
 
</blockquote>
 
 
 
<br />
 
 
====Otros ejemplos====
 
Aquí hay un par de python script for Binance Future... creo que son sin usar la Python 3 SDK: https://github.com/binance-exchange/binance-signature-examples/tree/master/python
 
 
 
<br />
 
 
 
==Using SQL in Jupyter==
 
==Using SQL in Jupyter==
 
Connecting to a database in Jupyter
 
Connecting to a database in Jupyter
Line 568: Line 515:
 
   
 
   
 
  sudo apt-get install python3-mysqldb
 
  sudo apt-get install python3-mysqldb
 
 
  
  
 
Luego adding SQL syntax highlighting to Jupyter as describe above in the corrrespoinding source.
 
Luego adding SQL syntax highlighting to Jupyter as describe above in the corrrespoinding source.
 
 
<br />
 
 
==Keep a python script running on a remote server==
 
 
 
<br />
 
===Screen===
 
How can I keep a python script on a remote server running after closing out of SSH:
 
https://stackoverflow.com/questions/55462226/how-can-i-keep-a-python-script-on-a-remote-server-running-after-closing-out-of-s
 
 
 
How to use Linux Screen: https://linuxize.com/post/how-to-use-linux-screen/
 
 
 
Kill a screen session:
 
* https://askubuntu.com/questions/356006/kill-a-screen-session
 
* https://stackoverflow.com/questions/14806051/kill-attached-screen-in-linux
 
 
screen -X -S SCREENID kill
 
 
 
Kill all sessions: https://unix.stackexchange.com/questions/94527/how-do-i-kill-all-screens
 
killall screen
 
 
 
Reattaching to an existing screen session using the screen name instead of the id: https://askubuntu.com/questions/302662/reattaching-to-an-existing-screen-session
 
  
  
 
<br />
 
<br />

Latest revision as of 14:47, 11 September 2024


For a standard Python tutorial go to Python



Courses

  • Udemy - Python for Data Science and Machine Learning Bootcamp
https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/



Anaconda

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. https://en.wikipedia.org/wiki/Anaconda_(Python_distribution)

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

Installation from the official Anaconda Web site: https://docs.anaconda.com/anaconda/install/



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:

anaconda-navigator



Jupyter

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

https://jupyter-notebook.readthedocs.io/en/stable/public_server.html


A**1


(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 []:adeloaleman@gmail.com



Share Jupyter Notebook online

  • GitHub:
https://docs.github.com/en/github/managing-files-in-a-repository/working-with-jupyter-notebook-files-on-github
Example: https://github.com/adeloaleman/AmazonLaptopsDashboard/blob/master/DataAnalysis/data_analysis2.ipynb


  • 'Nbviewer
https://nbviewer.jupyter.org/
Example: https://nbviewer.jupyter.org/github/bokeh/bokeh-notebooks/blob/main/tutorial/06%20-%20Linking%20and%20Interactions.ipynb



Customize Jupyter


Themes

https://github.com/dunovank/jupyter-themes

Ver el tema que muestran en esta página: https://gist.github.com/pierrejoubert73/902cc94d79424356a8d20be2b382e1ab


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


https://www.kaggle.com/getting-started/97540

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



Extensions

This post mention so nice extension and configuration that can be done: https://towardsdatascience.com/bringing-the-best-out-of-jupyter-notebooks-for-data-science-f0871519ca29


Unofficial Jupyter Notebook Extensions

https://jupyter-contrib-nbextensions.readthedocs.io/en/latest/index.html

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


Installation

https://jupyter-contrib-nbextensions.readthedocs.io/en/latest/install.html

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: https://github.com/ipython-contrib/jupyter_contrib_nbextensions/issues/1127

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 https://github.com/Jupyter-contrib/jupyter_nbextensions_configurator

pip install jupyter_nbextensions_configurator

or

conda install -c conda-forge jupyter_nbextensions_configurator



CustomJS and CustonCSS files

This is a good post: https://forums.fast.ai/t/jupyter-notebook-enhancements-tips-and-tricks/17064

Keyboard Shortcut Customization: https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Custom%20Keyboard%20Shortcuts.html



custom.js
/** Mis configuraciones */ 

// This is to enable syntax highlighting for SQL code: 
// https://stackoverflow.com/questions/43641362/adding-syntax-highlighting-to-jupyter-notebook-cell-magic
require(['notebook/js/codecell'], function(codecell) {
  codecell.CodeCell.options_default.highlight_modes['magic_text/x-mssql'] = {'reg':[/^%%sql/]} ;
  Jupyter.notebook.events.one('kernel_ready.Kernel', function(){
  Jupyter.notebook.get_cells().map(function(cell){
      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: https://forums.fast.ai/t/jupyter-notebook-enhancements-tips-and-tricks/17064
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";
    }else{
        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:
    // https://makitweb.com/how-to-add-important-to-css-property-with-jquery/
    var text_cell_fields = document.getElementsByClassName("text_cell");
    $(text_cell_fields).ready(function(){
        $('.input_prompt').css({
            'cssText': `width: 40px !important; max-width: ${prompt_width} !important; min-width: ${prompt_width} !important;`
        });
    });

    $(document).ready(function(){
        $(".prompt_container").css(
            'visibility', `${action}`
        );
        
        $(".input").css(
            'padding-left', `${input_marginLeft}`
        );
        
        $(".output_subarea").css(
            'margin-left', `${output_margin}`
        );
                    
        $('.cell').css({
            'cssText': `border-top-width: ${border_top} !important; border-bottom-width: ${border_top} !important;`
        });
        
        $(".collapsible_headings_ellipsis").css({
            'cssText': `padding-top:${padding_top} !important; border-top-width: ${border_top} !important; border-bottom-width: ${border_top} !important;`
        });

        $(".text_cell_render").css({
            'cssText': `margin-left: -10px;`
        });
    });            
}

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

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


// This could be very usefull. It allows to add text automatically into a cell
// https://forums.fast.ai/t/jupyter-notebook-enhancements-tips-and-tricks/17064/27
Jupyter.keyboard_manager.edit_shortcuts.add_shortcut('Ctrl-Shift-J', {
    help : '...',
    help_index : 'zz',
    handler : function (event) {
        document.body.style.background = '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)
        cursor.ch += 20 // where to put your cursor
        target.code_mirror.setCursor(cursor)
        return false;
    }}
);


// To get the real value of a css field: https://stackoverflow.com/questions/26074476/document-body-style-backgroundcolor-doesnt-work-with-external-css-style-sheet
// window.getComputedStyle(document.body).backgroundColor
// window.getComputedStyle(document.getElementsByClassName("input_area")[0]).backgroundColor



custom.css
/*  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: https://www.dataschool.io/cloud-services-for-jupyter-notebook/

I have tried:

https://cocalc.com/projects/595bf475-61a7-47fa-af69-ba804c3f23f9/files/?session=default
Parece bueno, pero tiene opciones que no son gratis


https://www.kaggle.com/adeloaleman/kernel1917a91630/edit
Parece bueno pero no encontré la forma adicionar una TOC


Es el que estoy utilizando ahora



Some remarks


Executing Terminal Commands in Jupyter Notebooks

https://support.anaconda.com/hc/en-us/articles/360023858254-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:

%ls 
!pwd

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


Scrapy


Using SQL in Jupyter

Connecting to a database in Jupyter


https://pypi.org/project/ipython-sql/

https://stackoverflow.com/questions/454854/no-module-named-mysqldb

https://stackoverflow.com/questions/5178292/pip-install-mysql-python-fails-with-environmenterror-mysql-config-not-found

https://docs.kyso.io/guides/sql-interface-within-jupyterlab

https://www.datacamp.com/community/tutorials/sql-interface-within-jupyterlab

https://stackoverflow.com/questions/43641362/adding-syntax-highlighting-to-jupyter-notebook-cell-magic

https://www.sqlshack.com/learn-jupyter-notebooks-for-sql-server/


Verificar las fuentes above. Creo que lo único que tuve que hacer la última vez que lo instalé fue basado en las 3 primeras sources:

pip install ipython-sql

sudo apt install default-libmysqlclient-dev

pip install mysqlclient

sudo apt-get install python3-mysqldb


Luego adding SQL syntax highlighting to Jupyter as describe above in the corrrespoinding source.