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Quick Start

Install AmortaPy

Currently only available via Github install.

pip install git+https://github.com/b3mery/AmortaPy.git

Generating a Amortization Table DataFrame:

• Amortization DataFrame

  import AmortaPy as ap
  
  input_interest_rate = 0.0394
  input_loan = 515000
  input_years = 30
  repayment_freq = 12 # monthly
  
  period_int_rate = input_interest_rate/repayment_freq
  periods = input_years*repayment_freq
  
  df = ap.generate_amortization_table(period_int_rate, input_loan, periods)

• Amortization DataFrame with additional payments per peirod

  df = ap.generate_amortization_table(period_int_rate, input_loan, periods, additional_payment_per_period=50)

Generatating an Amortization Object

• Create an amortization schedule

  import AmortaPy as ap
  
  input_interest_rate = 0.0394
  input_loan = 515000
  input_years = 30
  input_repayment_method = 'weekly'
  
  loan = ap.generate_amortization_schedule(input_interest_rate, input_loan, input_years, input_repayment_method)

• Get a quick summary

  loan # if in Jupyter Notebook
  print(loan) # if in Python file/cmd

• Tap into the amortization table dataframe

  loan.amortization_schedule.head()

• Use the Setter Methods to recalculate the schedule. Setters default to inplace updates. Meaning the instance will be updated. If you want to reterive a copy set inplace=False

  # Update the years of the Amortization object and preview the table head again
  loan.set_years(20).amortization_schedule.head()
  
  # Update some attribute and have a new object returned
  loan2 = loan.set_nominal_annual_interest_rate(0.045, inplace=False)

• AmortaPy Classes support dot notation. This means you can chain commands

  loan2.set_nominal_annual_interest_rate(0.028).set_repayment_frequency_periods('monthly')

• Like how the inplace argument of False returns a copy of the object you can also explicitly create a copy.

  loan3 = loan.copy()

Graph Visualization

To visualize the Amortization Schedule in a graph you will need to manually install plotly-express

pip install plotly-express

• Once installed you can simply tap into the figure properties.

  loan.period_balances_chart.show()

  

  loan.period_repayments_chart.show()

  

• You can also create a stacked graph manually using the plot_stacked_bar_chart API which is was created to be reusable with the Amortization class.

• More custom graphs should be created using plotly or plotly-express directly