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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. 1. Distribution of all employee ages. 2. Distribution of employee ages in each department. 3. Compare the salary ranges of employees by department. 4. Relationship between employee age and salary. 5. Distribution of employee salary across all departments. 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. Load the Jupyter Notebook that has been provided with this hands-on lab.
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Challenge
Load Libraries and Prepare the Data
- Use the Pandas library and load
Employee.csv
. - Display the top few rows and ensure the data is read successfully.
- Use the Pandas library and load
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Challenge
Perform Univariate Analysis
- Use matplotlib functions to add chart title and labels to x and y axes.
- Use the Seaborn Library and create a visualization showing the distribution of employee age in each department.
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Challenge
Perform Bivariate Analysis
- Modify the Seaborn library to present the salary range of employees by department, show the descriptive statistics visually, and present the relationship between age and salary.
About the author
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