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  3. Analyzing Financial Statements in Python
  • 1

    The Balance Sheet

    Gratuito

    In this chapter, you will learn how to read and interpret a balance sheet and compute and use financial ratios to evaluate a company's performance using information from the balance sheet. Additionally, you'll gain hands-on experience using the powerful pandas data manipulation package to analyze a company's financial ratios and compare them to its peers in the industry.

  • 2

    The Income Statement

    In this chapter, you'll learn how to read and interpret an income statement, calculate key financial ratios, and even create your own functions in Python to automate repetitive tasks. You'll also gain experience using seaborn, a powerful data visualization library, to produce figures to help you understand a company's financial performance.

  • 3

    The Cash Flow Statement

    In this chapter, you’ll analyze the cash flow statement and use its information to compute and interpret financial ratios. Using Seaborn to create informative plots that compare financial ratios across different companies, you'll build on your existing knowledge of Python and data visualization. By the end of this chapter, you'll have the skills to extract insights from cash flow statements using Python and handle messy, real-world data sets with missing data.

  • 4

    Profitability metrics

    In this chapter, you'll learn about the different financial ratios that measure a company's profitability, how to compute them, and how to compare them across other companies. You'll build upon your knowledge of the Seaborn library to create visualizations that help you analyze profitability ratios and identify trends.

Initializing

Exercicio

Updating user-defined function to do subtraction

The function you worked on in the previous exercise cannot do subtraction. Have a look at this function:

def compute_ratio(df, numerator, denominator, ratio_name, 
                  addition_in_numerator = True,
                  addition_in_denominator = True):
  numerator_of_ratio = np.where(addition_in_numerator,
                             df[numerator].sum(axis=1), 
                             df[numerator[0]] - df[numerator[1:]].sum(
                               axis=1))
  denominator_of_ratio = np.where(addition_in_denominator, 
                               df[denominator].sum(axis=1), 
                               df[denominator[0]] - df[denominator[1:]].sum(axis=1))
  df[ratio_name] = numerator_of_ratio/denominator_of_ratio
  return df

This function can deal with addition and subtraction in numerators and denominators of financial ratios. Notice that the function uses np.where. This is a function from the package NumPy. np.where checks if the first argument is True; if so, it returns the second argument, else it returns the third. For example, in the above, we have: 

np.where(addition_in_numerator,
                             df[numerator].sum(axis=1), 
                             df[numerator[0]] - df[numerator[1:]].sum(
                               axis=1))

If addition_in_numerator is true, np.where will return df[numerator].sum(axis=1), else it will return df[numerator[0]] - df[numerator[1:]].sum(axis=1).

In this exercise, the balance_sheet DataFrame, along with pandas and NumPy aspd and np, respectively, have been loaded for you. Use these to determine which of the following statements is correct.

Instruções

50 XP

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