The treebeard will guard your notebook

Episode #186: The treebeard will guard your notebook

Published Thu, Jun 18, 2020, recorded Wed, Jun 10, 2020.

Sponsored by us! Support our work through:

• Our courses at Talk Python Training
• Brian’s pytest book

Michael #1: sidetable - Create Simple Summary Tables in Pandas

• by Chris Moffitt
• Makes it easy to build a frequency table and simple summary of missing values in a DataFrame.
• Example without and with 
• A useful tool when starting data exploration on a new data set
• At its core, sidetable is a super-charged version of pandas value_counts with a little bit of crosstab mixed in.
• With sidetable is imported, you have a new accessor on all your DataFrames - stb that you can use to build summary tables.

Brian #2: tabulate

• suggested by Tom McDermott
• Pretty-print tabular data in Python, a library and a command-line utility.

    from tabulate import tabulate

    table = [["Sun",696000,1989100000],
             ["Earth",6371,5973.6],
             ["Moon",1737,73.5],
             ["Mars",3390,641.85]]
    headers=["Planet","R (km)", "mass (x 10^29 kg)"]
    table_str = tabulate(table, headers=headers)
    print(table_str)
    Planet      R (km)    mass (x 10^29 kg)
    --------  --------  -------------------
    Sun         696000           1.9891e+09
    Earth         6371        5973.6
    Moon          1737          73.5
    Mars          3390         641.85

• lots of table formats, including
• simple (Markdown extended)
• github (github flavored markdown)
• pipe
• jira
• mediawiki
• html
• plain (just spaces)
• different column alignment options
• number formatting

#python #courses at talk python training #treebeard

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The treebeard will guard your notebook

Episode #186: The treebeard will guard your notebook

Published Thu, Jun 18, 2020, recorded Wed, Jun 10, 2020.

Sponsored by us! Support our work through:

• Our courses at Talk Python Training
• Brian’s pytest book

Michael #1: sidetable - Create Simple Summary Tables in Pandas

• by Chris Moffitt
• Makes it easy to build a frequency table and simple summary of missing values in a DataFrame.
• Example without and with 
• A useful tool when starting data exploration on a new data set
• At its core, sidetable is a super-charged version of pandas value_counts with a little bit of crosstab mixed in.
• With sidetable is imported, you have a new accessor on all your DataFrames - stb that you can use to build summary tables.

Brian #2: tabulate

• suggested by Tom McDermott
• Pretty-print tabular data in Python, a library and a command-line utility.

    from tabulate import tabulate

    table = [["Sun",696000,1989100000],
             ["Earth",6371,5973.6],
             ["Moon",1737,73.5],
             ["Mars",3390,641.85]]
    headers=["Planet","R (km)", "mass (x 10^29 kg)"]
    table_str = tabulate(table, headers=headers)
    print(table_str)
    Planet      R (km)    mass (x 10^29 kg)
    --------  --------  -------------------
    Sun         696000           1.9891e+09
    Earth         6371        5973.6
    Moon          1737          73.5
    Mars          3390         641.85

• lots of table formats, including
• simple (Markdown extended)
• github (github flavored markdown)
• pipe
• jira
• mediawiki
• html
• plain (just spaces)
• different column alignment options
• number formatting

#python #courses at talk python training #treebeard

Rodrigo Senra - Jupyter Notebooks

Nosso convidado de hoje é diretor técnico na Work & Co, PhD em Ciências da Computação, já contribuiu com inúmeros projetos open source em Python, ajudou a fundar a Associação Python Brasil e já foi premiado com o Prêmio Dorneles Tremea por contribuições para a comunidade Python Brasil.

#alexandre oliva #anaconda #apache zeppelin #associação python brasil #azure notebooks #beakerx #binder #c++ #closure #colaboratory #donald knuth #fernando pérez #fortran #graphql #guido van rossum #ipython #java #javascript #json #jupyter kenels #jupyter notebooks #jupyterhub #jupyterlab #latex #lisp #literate programming #lua #matlab #perl #cinerdia #prêmio dorneles tremea #python #r #rodrigo senra #scala #spark notebook #tcl #typescript #zope

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15 Tips and Tricks for Jupyter Notebook that will ease your Coding Experience

Jupyter Notebook is a browser bases REPL (read eval print loop) built on IPython and other open-source libraries, it allows us to run interactive python code on the browser.

It not only runs python code but also has many interesting plugins and magic commands which enhances the python coding experience greatly.

1. Calculate the time of execution of a cell:

One can calculate the time of execution of a jupyter notebook cell using magic command at the beginning of the cell. It calculates the wall time that can be referred to as the total time required to execute that cell.

#artificial-intelligence #tips-and-tricks #machine-learning #data-science #jupyter-notebook

Why $XRP is about to hit ALL TIME HIGHS and MORE! Ripple will WIN

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