Using Python for Research

Exercises for homework (Week 1). In this homework, we will use objects, functions, and randomness to find the length of documents, approximate pi, and smooth out random noise.

Exercises for Homework (Week 2). Tic-tac-toe (or noughts and crosses) is a simple strategy game in which two players take turns placing a mark on a 3x3 board, attempting to make a row, column, or diagonal of three with their mark. In this homework, we will use the tools we've covered in the past two weeks to create a tic-tac-toe simulator and evaluate basic winning strategies.

A cipher is a secret code for a language. In this case study, we will explore a cipher that is reported by contemporary Greek historians to have been used by Julius Caesar to send secret messages to generals during times of war.

In this case study, we will find and plot the distribution of word frequencies for each translation of Hamlet. Perhaps the distribution of word frequencies of Hamlet depends on the translation - let's find out!

In this case study, we will analyze a dataset consisting of an assortment of wines classified into "high quality" and "low quality", and will use k-Nearest Neighbors to predict whether or not other information about the wine helps us correctly guess whether a new wine will be of high quality.

In this case study, we have prepared step-by-step instructions for you on how to prepare plots in Bokeh, a library designed for simple and interactive plotting. We will demonstrate Bokeh by continuing the analysis of Scotch whiskies.

In this case study, we will continue taking a look at patterns of flight for each of the three birds in our dataset.

Homophily is a network characteristic. Homophily occurs when nodes that share an edge share a characteristic more often than nodes that do not share an edge. In this case study, we will investigate homophily of several characteristics of individuals connected in social networks in rural India.

The [movie dataset on which this case study is based](https://www.kaggle.com/tmdb/tmdb-movie-metadata) is a database of 5000 movies catalogued by [The Movie Database (TMDb)](https://www.themoviedb.org/?language=en). The information available about each movie is its budget, revenue, rating, actors and actresses, etc. In this case study, we will use this dataset to determine whether any information about a movie can predict the total revenue of a movie. We will also attempt to predict whether a movie's revenue will exceed its budget. In Part 1, we will inspect, clean, and transform the data.

The [movie dataset on which this case study is based](https://www.kaggle.com/tmdb/tmdb-movie-metadata) is a database of 5000 movies catalogued by [The Movie Database (TMDb)](https://www.themoviedb.org/?language=en). The information available about each movie is its budget, revenue, rating, actors and actresses, etc. In this case study, we will use this dataset to determine whether any information about a movie can predict the total revenue of a movie. We will also attempt to predict whether a movie's revenue will exceed its budget. In Part 2, we will use the dataset prepared in Part 1 for an applied analysis.