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Can You Visualize Data Distributions by Using Python in JupyterLab?

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Part of Jupyter Data Visualization Topic: Data Science

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What you'll do

In this lab, you will You need to analyze and visualize data distributions by using Python™ in the JupyterLab development environment.

  1. Import the Python NumPy, Matplotlib, and pandas libraries
  2. Load data stored in a comma-separated values (CSV) file into a pandas DataFrame
  3. Create and compare a bar chart and a histogram
  4. Add custom colors, labels, a legend, and a trend line to a histogram
  5. Create a boxplot
  6. Change the orientation of a boxplot

Note: Once you begin the lab, you will not be able to pause, save, or exit and then return to your lab. Please ensure that you have set aside enough time to complete the lab before you start.

  • ⏱ About 45 minutes