[Python-Financial]NPV, SPP,DPP and IRR to assess the feasibility of project implementation

import pandas as pd
import datetime as dt
from scipy.optimize import fsolve

investment = 1000000
start_date = dt.datetime(2020, 1, 1)
end_date = dt.datetime(2024, 12, 31)
project_life = round((end_date - start_date).days / 365, 0)
tax_rate = 0.25
discount_rate = 0.15
scrap_value = 100000

cash_flow = {
    'Date': [
        dt.datetime(2020, 12, 31),
        dt.datetime(2021, 12, 31),
        dt.datetime(2022, 12, 31),
        dt.datetime(2023, 12, 31),
        dt.datetime(2024, 12, 31)
    ],
    'Cash Inflow': [1000000, 1000000, 1100000, 1100000, 1100000],
    'Cash Outflow': [660000, 670000, 680000, 690000, 700000]
}

df = pd.DataFrame(cash_flow)

# Calculate number of periods, 
#depreciation, profit before tax, 
#income tax, net profit, net cash flow, 
# discount factor and discounted cash flow

df['Period'] = round((df['Date'] - start_date).dt.days / 365, 2)
df['Depreciation'] = (investment - scrap_value) / project_life * (df['Period'] - df['Period'].shift(1).fillna(0))
df['Pre-tax Profit'] = df['Cash Inflow'] - df['Cash Outflow'] - df['Depreciation']
df['Income Tax'] = df['Pre-tax Profit'] * tax_rate
df['Net Profit'] = df['Pre-tax Profit'] - df['Income Tax']
df['Net Cash Flow'] = df['Net Profit'] + df['Depreciation']
df['Discount Factor'] = (1 + discount_rate) ** df['Period']
df['Discounted Cash Flow'] = df['Net Cash Flow'] / df['Discount Factor']

# Calculate NPV
NPV = df['Discounted Cash Flow'].sum() - investment

# Calculate SPP
df2 = df[['Net Cash Flow', 'Discounted Cash Flow']].cumsum()
df2 = pd.concat([df['Period'], df2 - investment], axis=1)
i = df2[(df2['Net Cash Flow'] * df2['Net Cash Flow'].shift(1)) < 0].index[0]
SPP = df2.iloc[i-1, 0] + abs(df2.iloc[i-1, 1]) / (abs(df2.iloc[i-1, 1]) + df2.iloc[i, 1])

# Calculate DPP
j = df2[(df2['Discounted Cash Flow'] * df2['Discounted Cash Flow'].shift(1)) < 0].index[0]
DPP = df2.iloc[j-1, 0] + abs(df2.iloc[j-1, 2]) / (abs(df2.iloc[j-1, 2]) + df2.iloc[j, 2])

# Calculate IRR
def f(x):
    y = 0
    for i, row in df[['Period', 'Net Cash Flow']].iterrows():
        y = y + row['Net Cash Flow'] / (1 + x[0]) ** row['Period']
    y = -investment + y
    return y

irr = fsolve(f, [0])[0]

# Output results
print("NPV:", NPV)
print("SPP:", SPP)
print("DPP:", DPP)
print("IRR:", irr)