timeseries_example_1.py

# Copyright (c) 2023 - 2024 Open Risk (https://www.openriskmanagement.com)
#
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# of this software and associated documentation files (the "Software"), to deal
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# SOFTWARE.

# Script used in Step 4 of the Open Risk Academy Course
# https://www.openriskacademy.com/mod/page/view.php?id=754

"""
['loan_identifier', 'portfolio_snapshot_id',
       'high_loan_to_value_refinance_option_indicator', 'zero_balance_code',
       'zero_balance_effective_date', 'upb_at_the_time_of_removal',
       'total_principal_current', 'last_paid_installment_date',
       'months_to_amortization', 'mortgage_insurance_cancellation_indicator',
       'scheduled_principal_current', 'unscheduled_principal_current',
       'zero_balance_code_change_date', 'loan_holdback_indicator',
       'loan_holdback_effective_date', 'next_interest_rate_adjustment_date',
       'next_payment_change_date', 'servicer_name', 'current_interest_rate',
       'current_actual_upb', 'loan_age', 'remaining_months_to_legal_maturity',
       'remaining_months_to_maturity', 'maturity_date',
       'servicing_activity_indicator'
"""

import matplotlib.pyplot as plt
import pandas as pd

if __name__ == '__main__':
    # load the loan state (variable fields)
    input_file = "DB_TABLES/loan_state.csv"
    input_table = pd.read_csv(input_file, header=0, sep='|')

    rem_mat = input_table['remaining_months_to_maturity'].squeeze()
    rem_mat.plot()
    print(type(rem_mat))
    # plt.show()
    plt.savefig("loan_maturity_all.png")