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Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk through a few of the highlights and show how to use the new scatter and line plot functions for quickly creating very useful visualizations of data.
Interactive IPython Notebook to demonstrate OWASP ZAP's API and Scripting Functions - OWASP ZAP 2.8.0
Get started with the toolbox of SIMATIC Artificial Intelligence Launcher.
Python package for generating and adding alt text to matplotlib figures
Execute several jupyter cells simultaneously with beautiful output. Do not waste time waiting
Repository containing portfolio of data science and machine learning projects. Presented in the form of iPython Notebooks
Portfolio of Data science projects built using ipython notebooks and R language.
A collection of my Jupyter notebooks on various topics
A collection of example Jupyter (iPython) Notebooks showing prototype code in Python notebook format. We do not recommend this approach to Python development.
Self Learning Projects and Hackathons solutions.
Nuestro equipo se enfrenta al reto de analizar los datos registrados en USA durante la crisis pandémica por COVID-19 🦠 ☠️
iPython notebooks for a IBM Data Science course in Coursera...
Spring ‘19 Honda Parking Project
A Repository containing all my Machine Learning Projects.
Lets you interact with MarkLogic directly from your Jupyter notebooks
Multiplayer dice game with various score multipliers
Dice rolling game with infinite number of rolls until the rolled number is not the number of sides