Data wrangling is a must-have skill for every data analyst. Use this handy cheat sheet to reshape, group, and blend data in Python for your next project.
NumPy is a powerful Python library to work with arrays in Python. There are a TON of features in NumPy but this cheat sheet has the basics to get you started.
Pandas is built on NumPy and makes it easy to work with data with Python. This cheat sheet provides a quick start on the basics of this powerful library.
Seaborn is a great data visualization library (probably my favorite right now) and is built on top of matplotlib. This cheat sheet will get you started quickly! ⚡
To do any #DataAnalytics work in #Python, you've gotta have data. This cheat sheet gives examples how to import data from 9 common use cases (csv, #Excel, #SQL, etc.)
Bokeh makes it simple to create common charts and graphs in Python but also can handle custom or specialized use cases. Use this cheat sheet to get up and running in no time.
This cheat sheet is great for Data Analysts that want to use Python. Topics include importing and exporting, data cleansing, filtering, sorting, grouping and more.
The step-by-step process to creating an awesome portfolio website in 60 minutes or less: ⤵️
Many beginner data analysts waste a lot of time trying to get their portfolios online:
• Using amateur-looking platforms like Google Sites
• Using clunky sites like Kaggle and GitHub
• Procrastinating because it’s too hard
But, your online data analytics portfolio sends a signal: "I can solve problems with data."
And recruiters and hiring managers know what they need:
• Professionals that can work with data
• Analysts that know how to think
• Sample work to show skills