Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)

Learn Data Analysis with Python in this comprehensive tutorial for beginners, with exercises included! NOTE: Check description for updated Notebook links. Data Analysis has been around for a long time, but up until a few years ago, it was practiced using closed, expensive and limited tools like Excel or Tableau. Python, SQL and other open libraries have changed Data Analysis forever. In this tutorial you'll learn the whole process of Data Analysis: reading data from multiple sources (CSVs, SQL, Excel, etc), processing them using NumPy and Pandas, visualize them using Matplotlib and Seaborn and clean and process it to create reports. Additionally, we've included a thorough Jupyter Notebook tutorial, and a quick Python reference to refresh your programming skills. 💻 Course created by Santiago Basulto from DataWars 🔗 Check out all Data Science courses from DataWars: https://datawars.io/ref=fcc ⚠️ Note: Instead of loading the notebooks on notebooks.ai, you should use Google Colab instead. Here are instructions on loading a notebook directly from GitHub into Google Colab: https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb#scrollTo=K-NVg7RjyeTk ❤️ Try interactive Python courses we love, right in your browser: https://scrimba.com/freeCodeCamp-Python (Made possible by a grant from our friends at Scrimba)  ⭐️ Course Contents ⭐️ ⌨️ Part 1: Introduction What is Data Analysis, why Python?, what other options are there? what's the cycle of a Data Analysis project? What's the difference between Data Analysis and Data Science? 🔗 Slides for this section: https://docs.google.com/presentation/d/1XXhVx2a7z2GrG5qddIyLFk4T_5s5mmdqSptDGBD9hWk/edit?usp=sharing ⌨️ Part 2: Real Life Example of a Python/Pandas Data Analysis project (00:11:11) A demonstration of a real life data analysis project using Python, Pandas, SQL and Seaborn. Don't worry, we'll dig deeper in the following sections 🔗 Notebooks: https://github.com/rmo