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DataCamp

Introduction to Data Visualization with Matplotlib

via DataCamp

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Overview

Learn how to create, customize, and share data visualizations using Matplotlib.

Visualizing data in plots and figures exposes the underlying patterns in the data and provides insights. Good visualizations also help you communicate your data to others, and are useful to data analysts and other consumers of the data. In this course, you will learn how to use Matplotlib, a powerful Python data visualization library. Matplotlib provides the building blocks to create rich visualizations of many different kinds of datasets. You will learn how to create visualizations for different kinds of data and how to customize, automate, and share these visualizations.

Syllabus

Introduction to Matplotlib
-This chapter introduces the Matplotlib visualization library and demonstrates how to use it with data.

Plotting time-series
-Time series data is data that is recorded. Visualizing this type of data helps clarify trends and illuminates relationships between data.

Quantitative comparisons and statistical visualizations
-Visualizations can be used to compare data in a quantitative manner. This chapter explains several methods for quantitative visualizations.

Sharing visualizations with others
-This chapter shows you how to share your visualizations with others: how to save your figures as files, how to adjust their look and feel, and how to automate their creation based on input data.

Taught by

Ariel Rokem

Reviews

4.5 rating at DataCamp based on 94 ratings

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