Tackling exercises from the Hyndman book.

Solving exercises Chapter 3 Hyndman and Athanasopoulos (Forecasting: Principles and Practice)

Exploring exercises 2.1, 2.2, 2.3, 2.4, 2.5 and 2.8 from the Hyndman online Forecasting book.

In this exercise, results from a depression survey are compared with NYC public health data. Statistical analysis is demonstrated along with different examples of data transformation.

Assignment about reviewing a recommender system, having chosen Netflix. References included.

Sentiment Analysis, using different lexicons in R. First part of the file comes from Text Mining with R, Chapter 1 & 2. Ref: Silge, J., & Robinson, D. (2017). Chapter 1 & 2. In Text Mining with R: A Tidy Approach. O’Reilly Media.

This work explores how to handle 3 different formats in R: HTML, JSON, and XML. To make the example easier they all contain the same information, which allows us to see how the loaded structure will look different for each format initially.

A project that uses 3 different datasets provided by classmates to practice tidying and analyzing them.

Brief exercise to tidy and visualize data starting from a wide structure in a CSV file

Exercise to practice the creation of an organized CSV file, with some minimal data transformation. The file includes information about a chess tournament and the players' ratings.

Solutions for week 3 exercises

This is a brief overview of the data from the latest polls regarding presidential elections in the US. For the complete article and source of the data please see <https://projects.fivethirtyeight.com/polls/>.