Computing multiple ratios with the user-defined function
Let's have a look at the function you saw in the last two exercises.
def compute_ratio(df, numerator, denominator, ratio_name,
addition_in_numerator = True,
addition_in_denominator = True):
ratio_numerator = np.where(addition_in_numerator,
df[numerator].sum(axis=1),
df[numerator[0]] - df[numerator[1:]].sum(
axis=1))
ratio_denominator = np.where(addition_in_denominator,
df[denominator].sum(axis=1),
df[denominator[0]] - df[denominator[1:]].sum(axis=1))
df[ratio_name] = ratio_numerator/ratio_denominator
return df
Recall that in the previous exercise, we used the function to compute ratios. Still, it was not more efficient nor did it involve less coding to compute the ratios using this function. In this exercise, you'll see how the function can be used to compute many ratios in a loop. This will make computing multiple ratios more efficient and involve less coding.
Este ejercicio forma parte del curso
Analyzing Financial Statements in Python
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# Print the columns
print(merged_dat.____)