Berlatih membuat heat map

Heat map adalah cara yang sangat baik untuk memvisualisasikan korelasi antar berbagai rasio keuangan. Ini dapat digunakan untuk melihat rasio mana yang berkorelasi kuat dengan rasio profitabilitas dan dengan demikian membantu kita memutuskan perusahaan mana yang akan diinvestasikan.

Dalam latihan ini, Anda akan berlatih membuat heat map. Sebuah DataFrame pandas merged_dat telah dimuat untuk Anda dengan beberapa rasio yang sudah dihitung. pandas dan Seaborn telah dimuat dengan alias pd dan sns.

Latihan ini adalah bagian dari kursus

Menganalisis Laporan Keuangan dengan Python

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

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

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Menganalisis Laporan Keuangan dengan Python

SkillTag.level.intermediateSkillTag.label

4.7+

Mulai Kursus Gratis

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: Sekilas rasio keuangan di beberapa industri Exercise 2: Menggunakan margins dalam pivot table dan membuat bar plot Exercise 3: Menyiapkan data untuk plot facet grid Exercise 4: Membuat facet grid plot Exercise 5: Fungsi buatan pengguna untuk membuat plot Exercise 6: Metrik profitabilitas Exercise 7: Hubungan antara margin operasi dan debt-to-equity untuk perusahaan real estat Exercise 8: Berlatih dengan sns.regplot()Exercise 9: Memperbarui fungsi buatan pengguna untuk membuat plot Exercise 10: Lebih lanjut tentang menganalisis profitabilitas Exercise 11: Berlatih membuat heat map

Latihan Saat Ini

Exercise 12: Analisis menyeluruh Exercise 13: Bagus sekali!