original_docstring: 
          Creates 2 Graphs showcasing the Net Present Value distribution across simulations
          
docstring: Creates 2 Graphs showcasing the Net Present Value distribution across simulations
docstring_tokens: Creates 2 Graphs showcasing the Net Present Value distribution across simulations
code: def create_graphs(self):
          '''
          Creates 2 Graphs showcasing the Net Present Value distribution across simulations
          '''
          font = {'size'   : 12}
          matplotlib.rc('font', **font)
          if self.npvs is None:
              setattr(self, 'npvs', self.calculate_npv())
          
          npv_dist = sns.displot(self.npvs, x='NPV',)
          ticks = npv_dist.axes[0][0].get_xticks()
          xlabels = ['R$' + '{:,.0f}'.format(x) for x in ticks]
          npv_dist.set_xticklabels(xlabels, rotation=45)
          npv_dist.set_axis_labels(x_var='Net Present Value/Hectare')
          
          npv_cumult_dist = sns.displot(self.npvs, x='NPV', kind='ecdf',
                                complementary=True, height=6, 
                                aspect=1.1618)
          xticks1 = npv_cumult_dist.axes[0][0].get_xticks()
          xlabels1 = ['R$' + '{:,.0f}'.format(x) for x in xticks1]
          ylabels1 = npv_cumult_dist.axes[0][0].get_yticks()
          ylabels1 = [f'{int(ylabel*100)}%' for ylabel in ylabels1]
          
          npv_cumult_dist.set_xticklabels(xlabels1, rotation=45)
          npv_cumult_dist.set_yticklabels(ylabels1, rotation=45)
          npv_cumult_dist.set_axis_labels(x_var='Net Present Value/Agricultural Land Hectare', 
                                          y_var='Probability of at least this NPV')
          return npv_dist, npv_cumult_dist
code_tokens: def create_graphs ( self ) : font = { 'size' : 12 } matplotlib . rc ( 'font' , ** font ) if self . npvs is None : setattr ( self , 'npvs' , self . calculate_npv ( ) ) npv_dist = sns . displot ( self . npvs , x = 'NPV' , ) ticks = npv_dist . axes [ 0 ] [ 0 ] . get_xticks ( ) xlabels = [ 'R$' + '{:,.0f}' . format ( x ) for x in ticks ] npv_dist . set_xticklabels ( xlabels , rotation = 45 ) npv_dist . set_axis_labels ( x_var = 'Net Present Value/Hectare' ) npv_cumult_dist = sns . displot ( self . npvs , x = 'NPV' , kind = 'ecdf' , complementary = True , height = 6 , aspect = 1.1618 ) xticks1 = npv_cumult_dist . axes [ 0 ] [ 0 ] . get_xticks ( ) xlabels1 = [ 'R$' + '{:,.0f}' . format ( x ) for x in xticks1 ] ylabels1 = npv_cumult_dist . axes [ 0 ] [ 0 ] . get_yticks ( ) ylabels1 = [ f'{int(ylabel*100)}%' for ylabel in ylabels1 ] npv_cumult_dist . set_xticklabels ( xlabels1 , rotation = 45 ) npv_cumult_dist . set_yticklabels ( ylabels1 , rotation = 45 ) npv_cumult_dist . set_axis_labels ( x_var = 'Net Present Value/Agricultural Land Hectare' , y_var = 'Probability of at least this NPV' ) return npv_dist , npv_cumult_dist
short_docstring: Creates 2 Graphs showcasing the Net Present Value distribution across simulations
short_docstring_tokens: Creates 2 Graphs showcasing the Net Present Value distribution across simulations
comment: '''
          Creates 2 Graphs showcasing the Net Present Value distribution across simulations
          '''