Usando margens em tabelas dinâmicas e criando um gráfico de barras

Você acabou de aprender a funcionalidade margins de pivot_table().

Definir margins = True ao usar pivot_table() retorna o aggfunc do value como um todo, ou seja, é o aggfunc do value sem condicioná-lo ao seu index.

Neste exercício, você vai praticar o que aprendeu. Você vai criar um gráfico preparando os dados com pivot_table() e também usando a funcionalidade margins.

Um DataFrame do pandas chamado dataset já foi carregado para você. pandas e Seaborn foram carregados com os aliases pd e sns, respectivamente.

Este exercicio faz parte do curso

Análise de Demonstrativos Financeiros em Python

exercicio interativo prático

Tente este exercicio completando este código de exemplo.

# Print the columns of the dataset
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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: 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: Um vislumbre dos índices financeiros de alguns setores Exercise 2: Usando margens em tabelas dinâmicas e criando um gráfico de barras

Exercicio Atual

Exercise 3: Preparando dados para um gráfico com facet grid Exercise 4: Criando um facet grid plot Exercise 5: Função definida pelo usuário para criar gráficos Exercise 6: Métricas de lucratividade Exercise 7: Relação entre margem operacional e dívida sobre patrimônio para empresas imobiliárias Exercise 8: Pratique com sns.regplot()Exercise 9: Atualizando a função definida pelo usuário para plotagem Exercise 10: Mais sobre a análise de lucratividade Exercise 11: Pratique criar mapas de calor Exercise 12: Análise ampla Exercise 13: Muito bem!