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Text Description Output Functionality #7

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Text Description Output Functionality #7

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597042b
Removed old input_mapper file
sgerson2 Aug 14, 2024
65e481b
Added text description output functionality
sgerson2 Aug 14, 2024
6d11ce6
Fixed standard output variables
sgerson2 Aug 14, 2024
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10 changes: 7 additions & 3 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@ python3 taxsim_emulator.py taxsim_input.raw
8. age1 (age of first dependent)
9. age2 (age of second dependent)
10. age3 (age of third dependent)
11. idtl (determines the level of output. 0 = standard, 2 = full, 5 = full with text descriptions)

### Income: ###
1. pwages (wage of primary taxpayer)
Expand All @@ -38,6 +39,9 @@ python3 taxsim_emulator.py taxsim_input.raw
6. intrec (taxable interest received)
7. stcg (short-term capital gains)
8. ltcg (long-term capital gains)
9. pui (primary taxpayer unemployment compensation received)
10. sui (spouse unemployment compensation received)
11. proptax (real estate taxes paid)
9. otherprop (other property incomes)
10. nonprop (other non-property incomes)
11. pensions (taxable pensions and IRA distributions)
12. pui (primary taxpayer unemployment compensation received)
13. sui (spouse unemployment compensation received)
14. proptax (real estate taxes paid)
13 changes: 10 additions & 3 deletions TaxsimInputReader.py
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Expand Up @@ -86,13 +86,20 @@ def add_variables(self, situation, row, year):
"intrec": "taxable_interest_income",
"stcg": "short_term_capital_gains",
"ltcg": "long_term_capital_gains",
"nonprop": "alimony_income",
"otherprop": "partnership_s_corp_income",
"pensions": "pension_income",
"pui": "unemployment_compensation",
"sui": "unemployment_compensation",
"proptax": "real_estate_taxes"
"proptax": "real_estate_taxes",
"scorp": "s_corp_self_employment_income",
"pbusinc": "qualified_business_income",
"sbusinc": "qualified_business_income"
}

primary_variables = ["pwages","psemp","dividends","intrec","stcg","ltcg","pui","proptax"]
spouse_variables = ["swages","ssemp","sui"]
primary_variables = ["pwages","psemp","dividends","intrec","stcg","ltcg","pui","proptax","pbusinc","nonprop","otherprop",
"scorp","pensions"]
spouse_variables = ["swages","ssemp","sui","sbusinc"]

primary_taxpayer = "you"
spouse_taxpayer = "your partner"
Expand Down
181 changes: 181 additions & 0 deletions TextDescriptionWriter.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,181 @@
import pandas as pd

from TaxsimInputReader import InputReader


class TextDescriptionWriter:
def __init__(self, input_data, InputReader):
self.input_data = input_data
self.reader = InputReader
self.output = self.format_data()
self.write_to_file()

# return the full name of the state corresponding to the state number
def get_state_name(self, state_number):
state_mapping = {
1: "Alabama", 2: "Alaska", 3: "Arizona", 4: "Arkansas", 5: "California", 6: "Colorado", 7: "Connecticut",
8: "Delaware", 9: "District of Columbia", 10: "Florida", 11: "Georgia", 12: "Hawaii", 13: "Idaho",
14: "Illinois", 15: "Indiana", 16: "Iowa", 17: "Kansas", 18: "Kentucky", 19: "Louisiana", 20: "Maine",
21: "Maryland", 22: "Massachusetts", 23: "Michigan", 24: "Minnesota", 25: "Mississippi", 26: "Missouri",
27: "Montana", 28: "Nebraska", 29: "Nevada", 30: "New Hampshire", 31: "New Jersey", 32: "New Mexico",
33: "New York", 34: "North Carolina", 35: "North Dakota", 36: "Ohio", 37: "Oklahoma", 38: "Oregon",
39: "Pennsylvania", 40: "Rhode Island", 41: "South Carolina", 42: "South Dakota", 43: "Tennessee",
44: "Texas", 45: "Utah", 46: "Vermont", 47: "Virginia", 48: "Washington", 49: "West Virginia",
50: "Wisconsin", 51: "Wyoming"
}
return state_mapping.get(state_number)

# return filing status. Taxsim leaves 6 and 5 as blank ()
def get_filing_status(self, mstat):
filing_status_map = {
1: "Single",
2: "Joint",
6: "",
8: "Single",
5: ""
}
return filing_status_map.get(mstat, f"Unknown filing status: {mstat}")

# convert the input data and the output data to dictionaries and get the values corresponding to the left column. Returns 0 if none
def format_data(self):
output_df = self.input_data.iloc[0].to_dict()
input_df = self.reader.df.iloc[0].to_dict()

state_number = input_df['state']

state_name = self.get_state_name(state_number)

mstat = input_df['mstat']
marital_status = self.get_filing_status(mstat)


placeholder = "placeholder"


formatted_output = f"""
Input Data:
1. Record ID: {input_df.get('taxsimid', 0):>5.0f}.
2. Tax Year: {input_df.get('year', 0):>4.2f}
3. State Code: {state_number:>2.0f}.{state_name:<20}
4. Marital Status: {input_df.get('mstat', 0):>7.2f} {marital_status:<10}
5-6. Age (Txpyr/Spouse): {input_df.get('page', 0):>7.2f}{input_df.get('sage', 0):>11.2f}
7. Dependent Exemptions: {placeholder}
8-10. #deps for CCC/CTC/EIC: {input_df.get('depx', 0):>7.2f}
11-12. Wages (Txpyr/Spouse): {input_df.get('pwages', 0):>10.2f}{input_df.get('swages', 0):>11.2f}
11a12a Self-employment income: {input_df.get('psemp', 0):>10.2f}{input_df.get('ssemp', 0):>11.2f}
13. Dividend Income: {input_df.get('dividends', 0):>7.2f}
14. Interest Received: {input_df.get('intrec', 0):>7.2f}
15. Short Term Gains: {input_df.get('stcg', 0):>7.2f}
16. Long Term Gains: {input_df.get('ltcg', 0):>7.2f}
17. Other Property: {input_df.get('otherprop', 0):>7.2f}
18. Other Non-Property: {input_df.get('nonprop', 0):>7.2f}
19. Taxable Pensions: {input_df.get('pensions', 0):>7.2f}
20. Gross Social Security: {input_df.get('gssi', 0):>7.2f}
21-22. Tot/Txpy/Spouse UI: {placeholder}
23. Non-taxable Transfers: {input_df.get('transfers', 0):>7.2f}
24. Rent Paid: {input_df.get('rentpaid', 0):>7.2f}
25. Property Taxes Paid: {input_df.get('proptax', 0):>7.2f}
26. Other Itemized Deds: {input_df.get('otheritem', 0):>7.2f}
27. Child Care Expenses: {input_df.get('childcare', 0):>7.2f}
28. Mortgage Interest: {input_df.get('mortgage', 0):>7.2f}
29. S-Corp profits: {input_df.get('scorp', 0):>7.2f}
29 31. Txpy/Spouse QBI w/o PO: {input_df.get('pbusinc', 0):>7.2f}{input_df.get('sbusinc', 0):>11.2f}
30 32. Txpy/Spouse SSTB w PO: {input_df.get('pprofinc', 0):>7.2f}{input_df.get('sprofinc', 0):>11.2f}

Basic Output:
1. Record ID: {input_df['taxsimid']:>3.0f}.
2. Year: {output_df['year']:>8}
3. State (SOI code): {state_number:>10.0f}{state_name:>15}
4. Federal IIT Liability: {output_df['fiitax']:>8}
5. State IIT Liability: {output_df['siitax']:>8}
6. SS Payroll Tax Liability: {output_df['fica']:>8}
Marginal Rates wrt Weighted Average Earnings
7. Federal Marginal Rate: {output_df['frate']:>8}
8. State Marginal Rate: {output_df['srate']:>8}
9. Weighed Payroll Tax Rate: {output_df['tfica']:>8}

Federal Tax Calculation: Base
10. Federal AGI {output_df['v10']:>9}
11. UI in AGI 1979+ {output_df['v11']:>9}
12. Social Security in AGI 84 {output_df['v12']:>9}
13. Zero Bracket Amount {output_df['v13']:>9}
14. Personal Exemptions {output_df['v14']:>9}
15. Exemption Phaseout 1991+ {output_df['v15']:>9}
16. Deduction Phaseout 1991+ {output_df['v16']:>9}
17. Deductions allowed {output_df['v17']:>9}
QBI deduction {placeholder:>9}
18. Federal Taxable Income {output_df['v18']:>9}
19. Federal Regular Tax {output_df['v19']:>9}
20. Exemption Surtax 1988-96 {output_df['v20']:>9}
21. General Tax Credit 1975-8 {output_df['v21']:>9}
22. Child Tax Credit*17/22 98 {output_df['v22']:>9}
23. Refundable Part {output_df['v23']:>9}
24. Child Care Credit 1076+ {output_df['v24']:>9}
25. Earned Income Credit 1975 {output_df['v25']:>9}
26. Alternative Min Income: {output_df['v26']:>9}
27. AMT {output_df['v27']:>9}
28. Income Tax Before Credits {output_df['v28']:>9}
Total Credits {placeholder:>9}
29. FICA {output_df['v29']:>9}
Taxpayer share of FICA {placeholder:>9}

State Tax Calculation:
30. Household Income {output_df['v30']:>9}
31. Imputed Rent {output_df['v31']:>9}
32. AGI {output_df['v32']:>9}
33. Exemptions {output_df['v33']:>9}
34. Standard Deduction {output_df['v34']:>9}
35. Itemized Deductions {output_df['v35']:>9}
36. Taxable Income {output_df['v36']:>9}
Tax before credits {placeholder:>9}
37. Property Tax Credit {output_df['v37']:>9}
38. Child Care Credit {output_df['v38']:>9}
39. EIC {output_df['v39']:>9}
Energy|Fuel Credit {placeholder:>9}
Child Tax Credit {placeholder:>9}
40. Total Credits {output_df['v40']:>9}
41. Bracket Rate {output_df['v41']:>9}
State Tax after Credits {placeholder:>9}

42. QBI Deduction {placeholder:>9}

Decomposition of Federal Marginal Rate
(taxpayer earned income)

Regular Income Tax
Bracket rate from X,Y or Z {placeholder:>9}
Deduction Phaseout: {placeholder:>9}
Exemption Phaseout: {placeholder:>9}
Social Security Phasein: {placeholder:>9}
Child Tax Credit: {placeholder:>9}
Child Care Credit: {placeholder:>9}
Refundable Part of CTC: {placeholder:>9}
Earned Income Credit: {placeholder:>9}
Surtax on 15% bracket: {placeholder:>9}
Exemption Surtax: {placeholder:>9}
Unemployment Insurance: {placeholder:>9}
Max Tax on Earned Income: {placeholder:>9}
Elderly Credit: {placeholder:>9}
Dependent Care Credit: {placeholder:>9}
Percentage Std Deduction: {placeholder:>9}
Medicare tax on Unearned Income:{output_df['v43']:>9}
Cares Recovery Rebates: {output_df['v45']:>9}

Alternative Minimum Income Tax
AMT Bracket Rate {placeholder:>9}
AMT Phaseout {placeholder:>9}

Only Regular Tax Relevant
Total Marginal Rate: {placeholder:>9}
FICA w Medicare (t,s): {placeholder:>9}{placeholder:>12}
"""

return formatted_output

# create a new file called text_description_output.txt with the f string
def write_to_file(self, file_path = "text_description_output.txt"):
formatted_output = self.format_data()
with open(file_path, 'w') as file:
file.write(formatted_output)


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