Should Your First FMP Project Be A Spreadsheet, Notebook, Script, Or Dashboard?

Your first Financial Modeling Prep (FMP) project should match the question you are trying to answer, not the most advanced format available.

A spreadsheet may be the fastest way to organize a watchlist. A notebook may be better for testing an idea. A script may help when the same data needs to refresh on a schedule. A dashboard or app prototype may make sense when other people need to use the output.

FMP can support each of these formats because its APIs provide structured access to market data, financial statements, company information, calendars, and other datasets that can power research workflows, dashboards, models, and applications.

Key Takeaways

• The right first format depends on your goal, comfort level, and expected output.
• Spreadsheets are best for quick analysis and familiar financial models, while notebooks are better for exploration and testing.
• Scripts, dashboards, and app prototypes make more sense when repeatability, sharing, or user interaction becomes important.
• Start with the simplest format that can produce a useful result, then move to a more structured workflow only when the project requires it.

Start With The Output, Not The Tool

Before choosing a format, define what you want your first project to produce.

Do you want a table of stock prices? A simple valuation model? A chart of historical returns? A list of upcoming earnings dates? A small internal dashboard? A product screen for a fintech prototype?

The answer matters because each format has a different strength.

• A spreadsheet is strong when the output is a model or table.
• A notebook is strong when the output is an analysis.
• A script is strong when the output needs to run again.
• A dashboard is strong when the output needs to be monitored.
• An app prototype is strong when the output needs to feel like a product.

Your first project does not need to solve everything. It should prove that you can request the right data, shape it into a useful output, and understand how the format fits your workflow.

Format Comparison At A Glance

Format	Best-Fit User	Best-Fit Use Case	First Output Example	Main Benefit	Main Limitation
Spreadsheet	Analysts, students, finance teams	Watchlists, models, tables, quick comparisons	A stock comparison table with price, market cap, and sector	Familiar and fast	Can become hard to maintain as logic grows
Notebook	Students, analysts, data analysts, developers	Testing, research, charts, data exploration	A chart comparing historical returns for several tickers	Flexible for analysis	Less ideal for non-technical users
Script	Developer, analysts with coding experience	Repeatable pulls, saved files, scheduled updates	A daily CSV or database update for selected tickers	Repeatable and clean	Requires more setup discipline
Dashboard	Finance teams, product teams, startup builders	Shared monitoring, KPIs, market views	A screen showing prices, earnings dates, and financial metrics	Easy to share and review	Requires design and refresh planning
App Prototype	Developer, fintech builders, startup teams	Testing a product idea or user workflow	A simple company lookup screen	Useful for product validation	More complex than needed for basic research

Spreadsheet

A spreadsheet is often the best first format when your goal is to inspect, compare, or model financial data in a familiar environment.

It fits analysts, students, finance teams, and business users who already think in rows, columns, formulas, and tables. If your first question is “Can I pull this data into a model?” or “Can I compare these companies quickly?” a spreadsheet is usually a practical place to begin.

A simple first output could be a watchlist with ticker, company name, sector, market cap, price, and basic financial statement fields. The Company Profile API can provide company-level information such as stock price, market capitalization, industry, and other profile details. Financial statement data can then support basic revenue, profitability, or margin comparisons.

The main benefit is speed. Spreadsheets make it easy to see the data, adjust assumptions, and share a familiar file with other users.

The main limitation is maintainability. As the workbook grows, logic can become scattered across many tabs, formulas, and manual adjustments. If the same workflow needs to run every day or support many tickers, a spreadsheet may eventually need a more repeatable structure.

For a deeper spreadsheet-specific workflow, the next step is The Best Way to Stream Live Stock Data into Excel Without Macros. For Google Sheets users, Best Google Sheets Software for Stock Analysis is the better follow-up resource.

Notebook

A notebook is a strong first format when your goal is to explore data, test logic, and explain your analysis step by step.

It fits students, data analysts, developers, and finance users who are comfortable working with code but still want a flexible research environment. A notebook works well when you do not yet know the exact final output and need room to experiment.

A simple first output could be a return chart for several companies, a revenue trend analysis, or a basic comparison of financial metrics across a small peer group. Historical Market Data APIs can support daily or intraday price analysis, charts, return calculations, and historical lookbacks. Income statement data can support revenue, expense, and profitability trend analysis.

The main benefit is flexibility. You can pull data, clean it, chart it, write notes, and revise your approach in one place.

The main limitation is handoff. A notebook can be clear to the person who built it, but less accessible to someone who only wants the final answer. If the output needs to be used by a broader team, a dashboard, spreadsheet, or saved report may be more practical.

If you need help setting up the coding environment first, How to create your own Python environment is the more specific next step.

Script

A script is the right first format when repeatability matters more than exploration.

It fits developers, technical analysts, data teams, and startup builders who want a process that can be run again with the same inputs and outputs. A script makes sense when you already know what data you need and want to save it, refresh it, or pass it into another workflow.

A simple first output could be a daily file that saves prices for a list of tickers, a scheduled pull of financial statements, or a clean dataset that feeds another model. FMP's API documentation notes that API requests use an API key, and that financial data can be accessed through structured endpoints.

The main benefit is consistency. A script can turn a one-time test into a repeatable process with fewer manual steps.

The main limitation is that scripts require more structure. You need to think about inputs, outputs, errors, saved files, and refresh timing. That does not mean the first script needs to be complex, but it should be organized enough that you can run it again without rebuilding the work.

A script is often the natural second step after a notebook. Use the notebook to explore the logic, then move the stable parts into a script once the workflow is clear.

Dashboard

A dashboard is a good first format when the output needs to be reviewed visually by more than one person.

It fits finance teams, product teams, startup builders, and analysts who need a shared view of changing data. A dashboard makes sense when the project is less about one calculation and more about monitoring a set of metrics over time.

A simple first output could be a market overview screen, a company snapshot page, an earnings calendar view, or a small watchlist dashboard with prices, financial metrics, and upcoming events. Historical Market Data APIs can support charts and price history, while Market Calendar APIs can support earnings, IPO, dividend, and stock split tracking.

The main benefit is usability. A dashboard turns API data into something that stakeholders can scan quickly.

The main limitation is scope creep. Once a dashboard exists, users may ask for filters, alerts, exports, permissions, and more datasets. For a first project, keep the dashboard narrow. One page, one use case, and a few reliable fields are enough.

A dashboard is not the best starting point if you are still deciding which data fields matter. In that case, begin with a spreadsheet or notebook, then build the dashboard after the core view is clear.

App Prototype

An app prototype is the best first format when you are testing a user experience, not just analyzing data.

It fits developers, fintech builders, startup teams, and product teams that want to validate how financial data might appear inside a product. An app prototype makes sense when the main question is “Would a user understand and use this?” rather than “Can I analyze this dataset?”

A simple first output could be a company lookup screen, a stock detail page, a watchlist feature, or a basic card that shows profile data, historical price movement, and selected financial metrics. The Company Profile API can support company identity and key profile fields, while historical and financial statement endpoints can provide the data behind charts and company fundamentals.

The main benefit is product validation. You can test whether the data, layout, and user flow make sense before investing in a larger build.

The main limitation is complexity. Even a simple prototype introduces interface decisions, loading states, user actions, and data presentation choices. If the goal is only to understand the data, an app prototype is usually too much for a first step.

Start with an app prototype only when the product experience is part of the question.

A Simple Decision Framework

Use these questions to choose your first format.

• If you mainly want to calculate, compare, or review data manually, start with a spreadsheet.
• If you mainly want to explore patterns, test assumptions, or build charts while thinking through the analysis, start with a notebook.
• If you already know the process and want to run it repeatedly, start with a script.
• If other people need to monitor the result visually, start with a dashboard.
• If you are testing a product idea or user workflow, start with an app prototype.

You can also choose based on the first dataset you want to use.

• Company Profile data is a good starting point for company lookup pages, watchlists, and comparison tables.
• Historical Market Data is useful for charts, return analysis, and market monitoring.
• Financial Statements are useful for models, profitability analysis, and peer comparisons.
• Market Calendar data is useful for earnings views, event tracking, and planning workflows.

What A Good First Output Looks Like

A good first output should be small, useful, and easy to check.

For example, instead of trying to build a complete investment platform, start with a five-stock watchlist. Instead of building a full valuation system, start with one company's revenue, net income, and market cap. Instead of building a complex dashboard, start with one page that shows price history and the next earnings date.

The first output should answer one practical question. It should also make the next step obvious.

If the output is useful but too manual, move toward a script. If it is useful but hard to explain, move toward a dashboard. If it is useful but needs a product experience, move toward an app prototype. If it is not useful yet, stay in the simpler format and refine the idea.

Where No-Code Fits

Some users do not want to start with code, and that is reasonable.

If your goal is to connect FMP data into an existing workflow without writing code, a no-code or low-code path may be the right starting point. This is separate from choosing between spreadsheet, notebook, script, dashboard, or app prototype because no-code tools can sometimes support several of those formats.

For a workflow-specific guide, Five Key Steps to Integrate FMP APIs Without Writing a Single Line of Code is the more relevant next read.

The key is not whether the workflow uses code. The key is whether the format supports the output you need.

Start Simple, Then Upgrade The Format

Your first FMP project should not be judged by how advanced it looks. It should be judged by whether it helps you move from a successful data request to a useful result.

Start in the simplest format that supports your goal.

Use a spreadsheet when you need a table or model. Use a notebook when you need to explore. Use a script when the process needs to repeat. Use a dashboard when the result needs to be shared visually. Use an app prototype when the user experience is part of the test.

You can always move to a more structured format later. The best first project is the one that gets you to a clear, usable output without adding complexity before you need it.

FAQ

What Is The Best First FMP Project Format For Beginners?

For most beginners, a spreadsheet is the easiest place to start. It lets you review data in a familiar format, compare companies, and build a simple watchlist without adding too much setup.

A good first output could be a table with ticker, company name, sector, market capitalization, price, and a few financial fields. Once the workflow becomes too manual or too large, you can move the stable parts into a notebook, script, or dashboard.

When Should I Start With A Notebook Instead Of A Spreadsheet?

Start with a notebook when your first project requires exploration, charts, or step-by-step analysis. A notebook works well when you want to test assumptions, compare historical performance, calculate returns, or document your logic while working.

It is usually a better fit than a spreadsheet when the analysis may change several times before you settle on the final output.

When Does A Script Make More Sense Than A Notebook?

A script makes more sense when the workflow is already clear and needs to run repeatedly. For example, if you need to pull the same data every day, save a clean file, or update a dataset for another tool, a script is more reliable than repeating notebook cells manually.

A notebook is better for discovery. A script is better for repeatability.

Should My First FMP Project Be A Dashboard?

A dashboard is a good first project only if the result needs to be shared or monitored visually. For example, a finance team may want a watchlist dashboard, an earnings calendar view, or a company snapshot screen.

If you are still deciding which data fields matter, start with a spreadsheet or notebook first. Build the dashboard after the core output is clear.

When Should I Build An App Prototype With FMP Data?

Build an app prototype when you are testing a product experience, not just analyzing data. This fits fintech builders, startup teams, and developers who want to see how FMP data might appear inside a user-facing workflow.

A simple prototype could be a company lookup page, stock detail screen, or watchlist feature. If the goal is only to understand the data, an app prototype is usually more complex than necessary.

Which FMP Datasets Are Good For A First Project?

Company Profile data is useful for company lookup pages, watchlists, and comparison tables. Historical Market Data is useful for charts, return analysis, and market monitoring. Financial Statements are useful for company analysis, profitability review, and financial models. Market Calendar data is useful for earnings views, event tracking, and planning workflows.

The best dataset depends on the first output you want to create. Start with one dataset, build one useful result, and add related data only when it improves the workflow.