Calcule o lucro líquido

Uma das utilidades da demonstração do resultado (income statement) é determinar quanto de lucro (também chamado de lucro líquido) a empresa está gerando. Neste exercício, você vai calcular o lucro líquido de uma empresa.

Neste exercício, total_revenue, depreciation e cost_of_goods_sold já foram carregados para você. Você vai calcular a renda antes dos impostos usando esses itens. Depois, assumindo uma alíquota de imposto de 5%, você calculará o lucro líquido, ou seja, a renda após os impostos.

Este exercicio faz parte do curso

Análise de Demonstrativos Financeiros em Python

Instruções do exercicio

Calcule a renda antes dos impostos.
Assumindo uma alíquota de 5%, calcule o lucro líquido.

exercicio interativo prático

Tente este exercicio completando este código de exemplo.

depreciation = 260
total_revenue = 3640
cost_of_goods_sold = 460

# Compute income before taxes
income_before_taxes = ____

# Compute income after taxes
net_income = ____

print(net_income)

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Este exercicio faz parte do curso

Análise de Demonstrativos Financeiros em Python

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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: Introdução à demonstração do resultado Exercise 2: Calcule o lucro líquido

Exercicio Atual

Exercise 3: Calculando índices a partir da demonstração de resultados Exercise 4: Rácios do demonstrativo de resultados e do balanço patrimonial Exercise 5: Atualizando a função definida pelo usuário Exercise 6: Atualizando a função definida pelo usuário para fazer subtração Exercise 7: Calculando índices com função definida pelo usuário Exercise 8: Calculando múltiplos índices com a função definida pelo usuário Exercise 9: Visualizando índices para análise dentro da empresa Exercise 10: Plotando índices Exercise 11: Plotando índices em uma única figura

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!