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Visualizing Data with Python Libraries and Amazon SageMaker
Imagine you are the data engineer, and you have been assigned to produce visualization charts and answer the following business questions using the dataset provided. Your data contains both categorical and numerical data. In this hands-on lab, you will create charts using Seaborn and matplotlib Python libraries.
Lab Info
Table of Contents
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Challenge
Launch SageMaker Notebook
Log in to the AWS console and navigate to AWS SageMaker AI, and configure the Kernel you'll be using. Then, load the Jupyter Notebook that has been provided with this hands-on lab.
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Challenge
Load libraries and prepare the data
Import the required libraries and load the .csv file.
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Challenge
Perform univariate analysis
Use matplotlib functions to add chart titles and labels to x and y axes. Also use the Seaborn library to create a visualization.
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Challenge
Perform bivariate analysis
Modify the Seaborn library to present ranges and illustrate this visually, and also present a relationship between data.
Real skill practice before real-world application
Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.
Learn by doing
Engage hands-on with the tools and technologies you’re learning. You pick the skill, we provide the credentials and environment.
Follow your guide
All labs have detailed instructions and objectives, guiding you through the learning process and ensuring you understand every step.
Turn time into mastery
On average, you retain 75% more of your learning if you take time to practice. Hands-on labs set you up for success to make those skills stick.