''' Saves cleaned data in a new Excel sheet '''
with pd.ExcelWriter('cleaned.xlsx') as writer:
DP.get_df().to_excel(writer, sheet_name='Clean Data')
print('Preprocessed data excel spreadsheet created: cleaned.xlsx!')
# Currency Conversion
if args.currency:
''' Currency conversion to USD, but if second argument is added to the constructor below, it converts to any other currency'''
CC = CurrencyConverter(DP.get_df())
''' Converts all columns of type float64 to the specified currency above '''
CC.convert_all('float64')
''' Save converted data in a new Excel sheet '''
with pd.ExcelWriter('converted.xlsx') as writer:
DP.get_df().to_excel(writer,
sheet_name='Converted Currency To {}'.format(
CC.get_currency()))
print('Currency conversion excel spreadsheet created: converted.xlsx!')
# Outlier Detection
if args.outliers:
DO = OutlierDetector(DP.get_df())
''' Computes Tukey outlier upper/lower inner/outer ranges '''
DO.compute_ranges([
'Material Cost', 'Blending Cost', 'Production Cost',
'Transportation Cost', 'Duty Cost', 'Total Cost'
])
'''
Adds a style to the dataframe which has the outlier cells coloured in 4 different colours,
depending on the range the outlier falls in
'''
outliers_df = DP.get_df().style.apply(DO.highlight_outlier_cells,
