[DDFG] Add BadInputError for dtype handling

[Alexander Bogdan]

In the first case, an UnboundLocalError occurs because data is not assigned based on the current if/else criteria. Add an else clause and raise BadInputError accompanied by a more informative error handling message.

impyute/impyute/dataset/base.py

Lines 34 to 37 in 2c25368

 if dtype == "int": 
     data = np.random.randint(bound[0], bound[1], size=shape).astype(float) 
 elif dtype == "float": 
     data = np.random.uniform(bound[0], bound[1], size=shape) 

In the second case, no matter what value you pass through dtype, no error occurs. This is because, in this instance, data is assigned immediately. Follow the same logic as above.

impyute/impyute/dataset/base.py

Lines 66 to 70 in 2c25368

 data = np.random.normal(mean, sigma, size=shape) 
 if dtype == "int": 
     data = np.round(data) 
 elif dtype == "float": 
     pass 

Be sure to follow the 4 steps outlined in contributing.md

The below labels are for DDFG (Data Days for Good) participant reference:
Priority: Low
Difficulty: Low