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사례 연구: R로 도시 시계열 데이터 분석
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업데이트됨 2026. 1.
RProbability & Statistics4시간12 동영상50 연습 문제3,950 XP14,090성취 증명서
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Manipulating Time Series Data in R1
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.
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.
사례 연구: R로 도시 시계열 데이터 분석
강의 완료
19백만 명 이상의 학습자와 함께 사례 연구: R로 도시 시계열 데이터 분석을(를) 시작하세요!
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Google에서 계속 진행더 많은 옵션 보기또는
DataCamp for Mobile을 통해 데이터 분석 능력을 향상시키세요.
모바일 강좌와 매일 5분 코딩 챌린지를 통해 이동 중에도 학습 효과를 높이세요.