Isı haritası oluşturma pratiği

Isı haritaları, çeşitli finansal oranlar arasındaki korelasyonları görselleştirmenin harika bir yoludur. Kârlılık oranlarıyla güçlü korelasyon gösteren oranları görmek ve buna göre hangi şirketlere yatırım yapacağımıza karar vermemize yardımcı olması için kullanılabilirler.

Bu egzersizde isı haritaları oluşturmayı pratik yapacaksın. Bazı oranları önceden hesaplanmış bir pandas DataFrame'i olan merged_dat senin için yüklendi. pandas ve Seaborn sırasıyla pd ve sns kısaltmalarıyla yüklendi.

Bu egzersiz

Python ile Finansal Tabloları Analiz Etme

kursunun bir parçasıdır

Kursu Görüntüle

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Make the correlation matrix
corr_mat = merged_dat[["Gross Margin", "Operating Margin", "Debt-to-equity",
                             "Equity Multiplier", "Current Ratio"]]____

Kodu Düzenle ve Çalıştır

Bu egzersiz

Python ile Finansal Tabloları Analiz Etme

kursunun bir parçasıdır

IntermediárioNível de habilidade

4.7+

Kursa Ücretsiz Başlayın

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: Bazı sektörlerin finansal oranlarına kısa bir bakış Exercise 2: Pivot tablolarında margins kullanma ve çubuk grafik çizme Exercise 3: Facet grid grafiği için veriyi hazırlama Exercise 4: Facet grid grafiği oluşturma Exercise 5: Grafikler için kullanıcı tanımlı fonksiyon Exercise 6: Karlılık metrikleri Exercise 7: Gayrimenkul şirketleri için faaliyet kâr marjı ile borç/özsermaye oranı arasındaki ilişki Exercise 8: sns.regplot() ile pratik Exercise 9: Grafik çizimi için kullanıcı tanımlı fonksiyonu güncelleme Exercise 10: Kârlılığı analiz etmeye devam Exercise 11: Isı haritası oluşturma pratiği

Geçerli Egzersiz

Exercise 12: Geniş kapsamlı analiz Exercise 13: Aferin!