Python NumPy For Your Grandma Now available in written format on Practice Probs!
Wanna learn NumPy? I did. And I consolidated everything I learned into a 43 videos spanning roughly three hours of content, including 25 lecture videos (~1.7 hrs) and 18 challenge videos (~1.3 hrs).
Course Curriculum Introduction
1.1 Introduction Basic Array Stuff
2.1 NumPy Array Motivation
2.2 NumPy Array Basics
2.3 Creating NumPy Arrays
2.4 Indexing 1-D Arrays
In this tutorial, we’ll cover everything you need to set up and use Google BigQuery. If you know R and/or Python, there’s some bonus content for you, but no programming is necessary to follow this guide.
Specifically, we’ll cover
Setting up a Google Cloud Project Setting up a BigQuery dataset and table Transferring data from Google Cloud Storage to BigQuery Transferring data from AWS S3 to BigQuery Querying your data Gotchas, Tips, and Best Practices BigQuery for R and Python users Before we get into the details…
Adobe Analytics' clickstream data is the raw hit data that adobe tracks on your website. Used properly, it’s a powerful source of data as it tells you exactly what someone did when they visited your site - what they clicked on, what their IP address is, the exact time of every hit, etc. A consequence of the granularity of the data is that this dataset is big, especially if your site gets a lot of traffic.
Connecting AWS S3 to Python is easy thanks to the boto3 package. In this tutorial, we’ll see how to
Set up credentials to connect Python to S3 Authenticate with boto3 Read and write data from/to S3 1. Set Up Credentials To Connect Python To S3 If you haven’t done so already, you’ll need to create an AWS account. Sign in to the management console. Search for and pull up the S3 homepage.
GormAnalysis
