By the end of this project we will learn how to analyze time series data. We are going to talk about different visualization techniques for time series datasets and we are going to compare them in terms of the tasks that we can solve using each of them. Tasks such as outlier detection, Key moments detection and overall trend analysis. During this project, we will learn how and when to use Line charts, Bar charts, and Boxplot. We will also learn some techniques about color mapping and we will understand how it can help us for a better analysis and understanding of our data.
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What you'll learn
Learn to analyze Time series data using different tasks
Learn to analyze boxplots, linecharts and barcharts
Learn to work with plotly python module
Skills you'll practice
Details to know
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About this Guided Project
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In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction to the project
Data Preprocessing
Analyzing Global temperature from 1995 to 2019
Comparing yearly average temperature of different regions over time
Analyzing Monthly average temperature in Canada
Recommended experience
Good Knowledge of Python Programming language and Plotly module. Experienced with Jupyter notebook. Familiarity with basics of data visualization.
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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