After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
รายละเอียดคอร์ส
In this course, you will strengthen your knowledge of time series topics through interactive exercises and interesting datasets. You’ll explore a variety of datasets about Boston, including data on flights, weather, economic trends, and local sports teams.
ข้อกำหนดเบื้องต้น
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โครงสร้างคอร์ส
1
Flight Data
You've been hired to understand the travel needs of tourists visiting the Boston area. As your first assignment on the job, you'll practice the skills you've learned for time series data manipulation in R by exploring data on flights arriving at Boston's Logan International Airport (BOS) using xts & zoo.
- Review xts fundamentals50 XP
- Identify the time series50 XP
- Flight data100 XP
- Pick out the xts object50 XP
- Encoding your flight data100 XP
- Manipulating and visualizing your data50 XP
- Exploring your flight data100 XP
- Visualize flight data100 XP
- Calculate time series trends100 XP
- Saving and exporting xts objects50 XP
- Assessing flight trends50 XP
- Saving time - I100 XP
- Saving time - II100 XP
2
Weather Data
In this chapter, you'll expand your time series data library to include weather data in the Boston area. Before you can conduct any analysis, you'll need to do some data manipulation, including merging multiple xts objects and isolating certain periods of the data. It's a great opportunity for more practice!
3
Economic Data
Now it's time to go further afield. In addition to flight delays, your client is interested in how Boston's tourism industry is affected by economic trends. You'll need to manipulate some time series data on economic indicators, including GDP per capita and unemployment in the United States in general and Massachusetts (MA) in particular.
4
Sports Data
Having exhausted other options, your client now believes Boston's tourism industry must be related to the success of local sports teams. In your final task on this project, your supervisor has asked you to assemble some time series data on Boston's sports teams over the past few years.
R
Case Study: Analyzing City Time Series Data in R
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