Analyzing Financial Statements in Python
Analyze company financials using Python and pandas
This practical course teaches how to analyze company financial statements using Python and pandas, focusing on balance sheets, income statements, and cash flow statements. You’ll learn to compute essential financial ratios, handle missing real-world data, and present results with clear data visualizations.
Through hands-on exercises and user-defined functions, it emphasizes reproducible workflows for merging statements, benchmarking companies by industry, and automating repetitive computations with pandas and seaborn. The course is best suited to learners with basic Python and pandas experience who want applied financial-analysis skills.
At a Glance
Analyzing Financial Statements in Python is a practical course taught by Rohan Chatterjee with support from collaborators that teaches applied financial analysis using Python tools.
It covers reading and interpreting balance sheets, income statements, and cash flow statements, computing key ratios with pandas, handling missing data, and presenting results with data visualization.
| Level | Intermediate |
| Rating | 4.7 out of 5 |
| Duration | 4+ hours |
| Languages | English |
| Certificate | Statement of Accomplishment |
| Access | Access for as long as your subscription is active |
| Course includes |
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| Price | Subscription-based, monthly or annual plans |
What This Course Teaches
This course frames outcomes as concrete, measurable competencies students can use to analyze company financials and produce reproducible, data-driven conclusions in Python.
Learners will leave able to compute and interpret financial ratios with pandas, handle missing real-world data, write reusable analysis functions, and visualize comparisons across companies and industries.
How the Course Is Structured
The course is organized as a short sequence of focused chapters that move from statement-level reading to cross-statement integration and industry comparison.
Overall it comprises 4 modules and runs about 4 hours in total, presented as bite-sized videos accompanied by interactive exercises and assessments.
Curriculum overview
01The Balance Sheet▾
Introduces how to read and interpret balance sheets and compute leverage and liquidity ratios using pandas for peer comparison.
- Introduction to the balance sheet
- Match balance sheet items to their class
- Relation of assets, liabilities, and shareholders’ equity
- Practice using the main equation of accounting
- Financial ratios from the balance sheet
- Match the ratio to its family
- Compute the current ratio
- Leverage ratios
- Computing financial ratios using pandas
- Compute current and debt-to-equity ratios
- Compute relative difference by industry
- Compute ratios by industry
02The Income Statement▾
Covers income-statement structure, calculation of net income and margin-based ratios, and automating those computations with user-defined functions.
- Introduction to the income statement
- Compute net income
- Computing ratios from the income statement
- Ratios from the income statement and balance sheet
- Updating the user-defined function
- Updating user-defined function to do subtraction
- Computing ratios with user-defined function
- Computing multiple ratios with the user-defined function
- Visualizing ratios for within-company analysis
- Plotting ratios
- Plotting ratios in one figure
03The Cash Flow Statement▾
Teaches cash-flow statement structure, computation of cash-flow metrics, and techniques for merging statements and handling missing values for analysis.
- Cash flow statement
- Assign cash flow entries to the correct part
- Compute net cash flow
- Financial ratios from the cash flow statement
- Merging financial statements
- Compute cash flow statement ratios
- Imputing and filling in missing values using averages
- Imputing missing values with percentiles
- Merging financial statements and filling missing values
- Visualizing financial ratios for comparison
- Plotting cash flow ratios
04Profitability metrics▾
Focuses on profitability ratios, advanced visualization techniques with seaborn, and comparative analyses across industries.
- A glimpse into the financial ratios of some industries
- Using margins in pivot tables and making a bar plot
- Preparing data for a facet grid plot
- Making a facet grid plot
- User-defined function to make plots
- Profitability metrics
- Relationship between operating margin and debt-to-equity for real estate companies
- Practice with sns.regplot()
- Updating the user-defined function for plotting
- More on analyzing profitability
- Practice making heat maps
- Broad analysis
- Well done!
Audience & Requirements
Analyzing Financial Statements in Python is aimed at data analysts, business-intelligence and finance professionals, and students or upskillers seeking to apply Python to company financial statements and cross-company comparisons. The course expects prior familiarity with Python and pandas, and it lists completion of Data Manipulation with pandas as a prerequisite.
- Data analysts and BI professionals who need financial-statement analysis in Python.
- Finance professionals (financial analysts, accountants) upskilling on programmatic analysis.
- Students and researchers learning practical, code-based financial analysis.
- Professionals preparing to benchmark companies and industries with reproducible analytics.
- Completion of Data Manipulation with pandas (explicit prerequisite).
- Basic to intermediate Python proficiency, including writing simple functions.
- Working familiarity with pandas DataFrame operations.
- Access to a Python environment (DataCamp workspace or a local Jupyter/Anaconda setup) for exercises.
Final Verdict
This is a focused, practical course that is well suited to analysts, finance professionals, and students who already have Python and pandas experience and want a compact, application-oriented path to analyzing company financials.
If you meet the stated prerequisites and you use or plan to use the host platform regularly, this course represents good value for building reproducible, code-first financial analysis skills.
Because the course is delivered through a subscription-based platform and issues a formal Statement of Accomplishment, it is especially attractive to learners who will take additional courses under the same subscription; single-course buyers should weigh the subscription model against their broader learning plans.
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