Getting my feet wet w/ Python 3
Quick tips and one-liners on how I was able to play around with Python
Terminal reskin via Hyper (aesthetic)
Package manager via Homebrew (think pandas, python)
Downloading your Jupyter Notebook
Jupyter is an open-source interactive development environment that allows developers to write interactive code chunks to easily analyze and visualize their data. You don’t need to write all the code and run it as a Python file. Instead, you write small code chunks that individually read data, display data, or visualize a single plot, and then run them instantly. It comprises of different interactive components called cells where you can write code or markdown and load data to make the code more explainable and shareable.
While Jupyter is the interface that helps you write interactive code, Python is the computational engine underneath. In particular for data analysis, the feature-rich library Pandas provides functions for reading, analyzing, manipulating, exploring, and cleaning datasets. It mainly aims to handle “relational” or “labeled” data with the help of its two data structures: DataFrames and Series. With Pandas, you can load and store data in CSV, Excel, JSON, or MySQL easily.
Now ready to connect to play around!
Option 1) Leverage packages to create a digital clock (great read)
Option 2) Explore some dummy data (great read)
Leverage existing syntax to explore the data…
Visualize w/in the notebook…
Happy exploring!
-Lucas
