This repository contains tutorials for python basics, pandas, and scikit-learn.

• About me
• Python basics
• Python 2 vs Python 3
• Jupyter notebook
• Python tutorial
• Pandas
  • Intro tutorials on pandas basics
  • Data munging with pandas
• Scikit-learn
• Your first data analysis case

Slides can be found here

Slides can be found here

• Great Jupyter notebook covering the main differences between Python 2 and 3, cloned from Sebastian Raschka's github
• To keep code compatible with both Python 2 and Python 3: Cheat Sheet

• Experiment further with the Jupyter Notebook with this Notebook
• Many more Jupyter features in this blog post

• Time to get your hands dirty. Read and test for yourself: The SciPy Lectures -- The Python Language
• Python interactive exercises
• Join the codewars competitions

• Tutorial: Data structures
• Tutorial: Working with dataframes
• Tutorial: Using pandas on the MovieLens dataset

• Exercises

• Introduction to machine learning with scikit-learn slides
• Doing machine learning with scikit-learn slides
• General concepts on machine learning
• Tutorial: Introduction to scikit-learn

A great source of data problems nowadays is the Kaggle platform. We'll be starting today with a simple but representative dataset: Titanic: Machine Learning from Disaster.

• Guide for orientation to approach the problem

IMPORTANT: you will find plenty of materials to analyze this data, however you'll learn the most if you give the problem some thought and try out several things before resorting to ready-made answers.

Derivative content credits its original creators and it's distributed under the license provided by them. Original content developed by Lucía Santamaría is distributed under the MIT license.