Compute relative difference by industry
Computing the relative difference between a company's ratio and its industry average is an excellent way to see if a company is at par with its peers. In this exercise, you'll practice computing the relative difference of the equity multiplier ratio of various FMCG companies from their industry average.
A pandas
DataFrame balance_sheet
has been loaded for you. pandas
has been loaded for you under the alias pd
. You can call balance_sheet.columns
in the console to assess which columns you can use for the exercise.
This exercise is part of the course
Analyzing Financial Statements in Python
Exercise instructions
- Subset the entries in
balance_sheet
to get onlyfmcg
companies in the column"comp_type"
ofbalance_sheet
. - Add a column in
fcmg
where you compute the equity multiplier ratio. - Add a column to
fmcg
where you compute the average yearly equity multiplier ratio. - Add a column to
fmcg
where you compute the relative difference of the company's equity multiplier ratio with its industry average.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Subset the fmcg companies
fmcg = balance_sheet.____[____]
# Compute equity multiplier ratio
fmcg["equity_multiplier_ratio"] = ____
# Compute average equity multiplier ratio by year
fmcg["average_equity_multiplier_ratio"] = fmcg.____(____)[____].____(____)
# Compute the relative difference
fmcg["relative_difference"] = ____
print(fmcg[["Year", "company", "relative_difference"]])