commission = 2%,
growth = 10%,
start_price = 100,
current_transaction = 1000
I wanted to create columns (transaction, revenue)
My question is how to create a dataframe with above information for 3 years.
| Element | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| Transaction | 1100 | 1210 | 1331 |
| Revenue | 2200 | 2420 | 2662 |
formula for transaction (transaction X growth) e.g(1000 X 10%)
formula for revenue (transaction X commission X price) e.g(1100X 2% X 100)
the year 2 column is outcome of year 1 ..so on.
This is a classic exponential growth series. You can leverage numpy broadcasting to compute them:
# Convert all percentages into decimals
commission = 0.02
growth = 0.1
start_price = 100
current_transaction = 1000
# We are going to rely on numpy broadcasting to help us do computations on
# arrays
year = np.arange(1,4)
factor = (1 + growth) ** year
# And make the dataframe
df = pd.DataFrame({
"Transaction": current_transaction * factor,
"Revenue": current_transaction * factor * commission * start_price
}, index=year).T.add_prefix("Year ")
