Well done!

1. Well done!

Congratulations! You have made it to the end of this course.

2. Summary

In this course, you learned how to read and analyze financial ratios from the balance sheet, income statement, and cash flow statement, the main financial statements, using modern tools in Python like pandas and Seaborn. You also learned about profitability metrics and how to analyze profitability visually using Seaborn.

3. Summary

In Chapter 1, you learned about the ratios that can be computed using information from the balance sheet, and how to compute the relative difference between ratios. In Chapter 2, you learned about the financial ratios from the income statement and balance sheet. You also learned how to reduce repetitive work by using user-defined functions and visualize ratios for within company analysis.

4. Summary

In Chapter 3, you learned about financial ratios from the three main financial statements. You also covered how to load JSON data into Python, impute missing values in the data, merge DataFrames and visualize ratios for a between company analysis.

5. Summary

Finally, Chapter 4 was all about profitability. You learned about profitability metrics, what drives the differences in ratios between different industries and you also learned many methods of visualization to analyze a company's profitability.

6. Recommended courses for the future

Now that you know about financial statements, you can build upon this knowledge! Courses on data science will help you gain cool skills like predicting the profitability of companies and even their share prices! Courses on PowerBI, a very powerful visualization tool, will build upon your newly gained visualization skills and further improve them. Unlike plots with Seaborn, where the image is static, images with PowerBI can also be made interactive, which is invaluable in business presentations!

7. Let's practice!

No more practice now. ;) :P

This exercise is part of the course

Analyzing Financial Statements in Python

IntermediateSkill Level

4.6+

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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.

Exercise 1: Introduction to the balance sheet Exercise 2: Match balance sheet items to their class Exercise 3: Relation of assets, liabilities, and shareholders' equity Exercise 4: Practice using the main equation of accounting Exercise 5: Financial ratios from the balance sheet Exercise 6: Match the ratio to its family Exercise 7: Compute the current ratio Exercise 8: Leverage ratios Exercise 9: Computing financial ratios using pandas Exercise 10: Compute current and debt-to-equity ratios Exercise 11: Compute relative difference by industry Exercise 12: Compute ratios by industry

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.

Exercise 1: Introduction to the income statement Exercise 2: Compute net income Exercise 3: Computing ratios from the income statement Exercise 4: Ratios from the income statement and balance sheet Exercise 5: Updating the user-defined function Exercise 6: Updating user-defined function to do subtraction Exercise 7: Computing ratios with user-defined function Exercise 8: Computing multiple ratios with the user-defined function Exercise 9: Visualizing ratios for within-company analysis Exercise 10: Plotting ratios Exercise 11: Plotting ratios in one figure

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.

Exercise 1: Cash flow statement Exercise 2: Assign cash flow entries to the correct part Exercise 3: Compute net cash flow Exercise 4: Financial ratios from the cash flow statement Exercise 5: Merging financial statements Exercise 6: Compute cash flow statement ratios Exercise 7: Imputing and filling in missing values using averages Exercise 8: Imputing missing values with percentiles Exercise 9: Merging financial statements and filling missing values Exercise 10: Visualizing financial ratios for comparison Exercise 11: Plotting cash flow ratios

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.

Exercise 1: A glimpse into the financial ratios of some industries Exercise 2: Using margins in pivot tables and making a bar plot Exercise 3: Preparing data for a facet grid plot Exercise 4: Making a facet grid plot Exercise 5: User-defined function to make plots Exercise 6: Profitability metrics Exercise 7: Relationship between operating margin and debt-to-equity for real estate companies Exercise 8: Practice with sns.regplot()Exercise 9: Updating the user-defined function for plotting Exercise 10: More on analyzing profitability Exercise 11: Practice making heat maps Exercise 12: Broad analysis Exercise 13: Well done!

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