Try Pandas Tutorial - Use Python for Data Science, Spreadsheets, CSV & Excel

Video Description

Pandas is a great tool for doing analysis on spreadsheets. It's easy to say that but let's actually learn why by doing something real. We're going to be analyzing NBA data to help understand why Pandas should be a tool in your data science toolkit. Launch your project with: https://deepnote.com/launch?url=https://github.com/codingforentrepreneurs/Try-Pandas But more importantly, doing something practical will help you better understand the need for a tool like Pandas. To help us work with Pandas in a practical way, we've teamed up with Deepnote. Deepnote is a service that makes it easy to run interactive notebooks (also known as Juptyer Notebooks). These notebooks allow us to run Python & Pandas in a highly visual and highly interactive manner. What's better, notebooks, especially on Deepnote, allow non-technical team members to participate in a code-heavy document (as we'll see how). Resources: - Code: https://github.com/codingforentrepreneurs/Try-Pandas - Deepnote Sign up (includes bonus resources): https://deepnote.com/referral?token=cfe - Setup Jupyter Notebooks on Mac, Windows or Linux: https://www.youtube.com/watch?v=9tPS-7TWjq0 00:00:00 Welcome to Try Pandas 00:01:13 Overview & Requirements 00:02:12 Setup Project on Deepnote 00:06:05 Creating your First DataFrame 00:11:06 Importing & Exporting in Pandas 00:20:17 Rename Columns in Pandas 00:28:04 Clean Rows 00:45:13 Basic Analysis 00:52:32 Group Data & Plots 01:04:20 Clean & Analyze Real Data Part 1 01:12:03 Clean & Analyze Real Data Part 2 01:18:06 Merge DataFrames Part 1 01:25:02 Merge DataFrames Part 2 01:37:11 Experimenting with a REST API 01:58:52 Flatten Dictionary Columns in DataFrames 02:22:09 Stats DataFrame Convenience Method 02:30:17 Final Player Analysis 02:45:49 The Appendix 02:47:17 Thank you for watching try pandas