Introduction to python

You are required to extract data from relevant dataset(s), namely the transaction.txt, frauddescription.txt, and descriptions.txt.

Three datasets are provided. The first dataset(description.txt) contains the description of genuine transactions. The second dataset(fraudulent-transaction.txt) contains the description of fraudulent transactions. The last dataset(transaction.txt) contains the actual transactions (10,000). The transaction dataset contains the description of the transactions, the amount of the transactions and the locations of the transactions. The locations are not real location to avoid tracing any transaction to anyone. The locations are just Euclidean coordinates in x, and y points. The following are the attributes of the transaction dataset, also see Figure 1.

Figure 1: sample data from the transaction.txt

* The user id

* The transaction id

* The description of the transaction

* The amount of the transaction

* The x coordinate of each transaction

* The y coordinate of each transaction

* A Boolean label that represents whether the transaction is fraudulent or not.

1. Design and develop 4 python modules namely: dataset_module, distance_module, statistics_module and test_module.

2. Implement a dataset_module with a function that retrieves the above attributes/features and returns a dictionary. You must use python file objects. Please do not use any other libraries for this task.