utils.py
def make_error_df(actual, predicted):
    '''
    returns a dataframe with prediction errors (diff-error and relative-errors)
    from input numpy arrays of actual and predicted values.
    :param actual: numpy array
    :param predicted: numpy array
    :return:
    '''
    dict = {'actual': actual, 'predicted': predicted}
    error_df = pd.DataFrame(data=dict)
    error_df['error'] = error_df['actual'] - error_df['predicted']
    error_df['error_relative_to_predicted'] = error_df['error'] / error_df['predicted']
    error_df['error_relative_to_actual'] = error_df['error'] / error_df['actual']
    return error_df

    returns a dataframe with prediction errors (diff-error and relative-errors)
    from input numpy arrays of actual and predicted values.
    :param actual: numpy array
    :param predicted: numpy array
    :return:
    
returns a dataframe with prediction errors (diff-error and relative-errors)
from input numpy arrays of actual and predicted values.
returns a dataframe with prediction errors ( diff - error and relative - errors ) from input numpy arrays of actual and predicted values .
def make_error_df(actual, predicted):
    dict = {'actual': actual, 'predicted': predicted}
    error_df = pd.DataFrame(data=dict)
    error_df['error'] = error_df['actual'] - error_df['predicted']
    error_df['error_relative_to_predicted'] = error_df['error'] / error_df['predicted']
    error_df['error_relative_to_actual'] = error_df['error'] / error_df['actual']
    return error_df
def make_error_df ( actual , predicted ) : dict = { 'actual' : actual , 'predicted' : predicted } error_df = pd . DataFrame ( data = dict ) error_df [ 'error' ] = error_df [ 'actual' ] - error_df [ 'predicted' ] error_df [ 'error_relative_to_predicted' ] = error_df [ 'error' ] / error_df [ 'predicted' ] error_df [ 'error_relative_to_actual' ] = error_df [ 'error' ] / error_df [ 'actual' ] return error_df
returns a dataframe with prediction errors (diff-error and relative-errors)
from input numpy arrays of actual and predicted values.
returns a dataframe with prediction errors ( diff - error and relative - errors ) from input numpy arrays of actual and predicted values .
'''
    returns a dataframe with prediction errors (diff-error and relative-errors)
    from input numpy arrays of actual and predicted values.
    :param actual: numpy array
    :param predicted: numpy array
    :return:
    '''
None
actual
None
predicted
None