Gegevens voorbereiden voor een facet grid-plot

In deze oefening ga je de gegevens voorbereiden om deze plot te maken: This plot shows the gross margin of tech companies, FMCG companies, the average tech company, and the average FMCG companies over many years. In de volgende oefening maak je de plot zelf. Met deze plot kun je goed zien:

De brutomarge van techbedrijven is meer verspreid dan die van FMCG-bedrijven
Per jaar hoe winstgevend een bedrijf is vergeleken met het gemiddelde bedrijf in zijn sector.

pandas is geladen met de alias pd en seaborn is geladen met de alias sns. Er is een pandas DataFrame dataset voor je geladen waarin de kolom gross_margin al is berekend.

Deze oefening maakt deel uit van de cursus

Financiële overzichten analyseren in Python

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Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Subset tech and fmcg companies
subset_dat = dataset.loc[____]

Code bewerken en uitvoeren

Deze oefening maakt deel uit van de cursus

Financiële overzichten analyseren in Python

SkillTag.level.intermediateSkillTag.label

4.7+

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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: Een kijkje in de financiële kengetallen van enkele sectoren Exercise 2: Marges gebruiken in draaitabellen en een staafdiagram maken Exercise 3: Gegevens voorbereiden voor een facet grid-plot

Huidige oefening

Exercise 4: Een facetgrid-plot maken Exercise 5: Zelfgedefinieerde functie om plots te maken Exercise 6: Winstgevendheidsstatistieken Exercise 7: Relatie tussen operationele marge en debt-to-equity voor vastgoedbedrijven Exercise 8: Oefenen met sns.regplot()Exercise 9: De door de gebruiker gedefinieerde plotfunctie bijwerken Exercise 10: Meer over het analyseren van winstgevendheid Exercise 11: Oefen met het maken van heatmaps Exercise 12: Brede analyse Exercise 13: Goed gedaan!