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VladNitu

main.py Rares proiect

Jan 9th, 2023
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Python 1.82 KB | None | 0 0
  1. import pandas as pd
  2. from src import processing
  3. def main():
  4.     """This method should be called when the program is run from the command line.
  5.    The aim of the method is to run the complete, automated workflow you developed
  6.    to solve the assignment.
  7.  
  8.    This function will be called by the automated test suite, so make sure that
  9.    the function signature is not changed, and that it does not require any
  10.    user input.
  11.  
  12.    If your workflow requires mongoDB (or any other) credentials, please commit them to
  13.    this repository.
  14.    Remember that if the workflow pushed new data to a mongo database without checking
  15.    if the data is already present, the database will contain copies of the data and
  16.    skew the results.
  17.  
  18.    After having implemented the method, please delete this docstring and replace
  19.    it with a description of what your main method does.
  20.  
  21.    Hereafter, we provide a **volountarily suboptimal** example of how to structure
  22.    your code. You are free to use this structure, and encouraged to improve it.
  23.  
  24.    Example:
  25.        def main():
  26.            # acquire the necessary data
  27.            data = acquire()
  28.  
  29.            # store the data in MongoDB Atlas or Oracle APEX
  30.            store(data)
  31.  
  32.            # format, project and clean the data
  33.            proprocessed_data = preprocess(data)
  34.  
  35.            # perform exploratory data analysis
  36.            statistics = explore(proprocessed_data)
  37.  
  38.            # show your findings
  39.            visualise(statistics)
  40.  
  41.            # create a model and train it, visualise the results
  42.            model = fit(proprocessed_data)
  43.            visualise(model)
  44.    """
  45.     raise NotImplementedError()
  46.  
  47.  
  48. if __name__ == "__main__":
  49.     d = {'col1': [1, 2], 'col2': [3, 4]}
  50.     df = pd.DataFrame(data=d)
  51.     processing.get_number_of_null(df)
  52.  
  53.  
  54.  
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