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Q: 4 import pandas as pd def compute _ profit _ per _ dollar _ sold ( df ) : # Calculate profit per dollar
Q:
import pandas as pd
def computeprofitperdollarsolddf:
# Calculate profit per dollar sold
dfprofitperdollarsold' dfProfit dfSales
# Return the dataframe with the new column
return df
# Example of usage:
# Assuming df is your pandas dataframe with columns "Profit" and "Sales"
newdf computeprofitperdollarsolddf
Question:
Objective: Filter data over relevant columns To understand how profit has evolved over time, create a function computetimeaverage. This function receives as input a pandas dataframe and list of integers representing years, eg and computes the mean profitperdollarsold for each year in the list. Repeat the same process to compute the mean Discount for each year. Return the result as tuple with two lists: the first with the mean profitperdollarsold per year, the second with the mean Discount per year Round the values to two decimal places. Note: the lists must be aligned so that meanprofitperdollarsold and meandiscount have the average for the year in listyears Hint: There are different ways to compute this. A possible one requires you to filter the data in the dataframe for each year. You can use other methods also covered in Programming Inception. Example of usage: meanprofitperdollarsold, meanvaluesdiscount computetimeaveragenewdf newdf the pandas dataframe from question ; meanprofitperdollarsold is a list with floats with the average profitperdollarsold for each year; meandiscount is a list with floats with the average discount for each year in the listyears;
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