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  3. Unit Testing for Data Science in Python

Exercise

Testing float return values

The get_data_as_numpy_array() function (which was called mystery_function() in one of the previous exercises) takes two arguments: the path to a clean data file and the number of data columns in the file . An example file has been printed out in the IPython console. It contains three rows.

The function converts the data into a 3x2 NumPy array with dtype=float64. The expected return value has been stored in a variable called expected. Print it out to see it.

The housing areas are in the first column and the housing prices are in the second column. This array will be the features that will be fed to the linear regression model for learning.

The return value contains floats. Therefore you have to be especially careful when writing unit tests for this function.

Instructions

100 XP
  • Complete the assert statement to check if get_data_as_numpy_array() returns expected, when called on example_clean_data_file.txt with num_columns set to 2.