S&P 500 Financial Health Dashboard

Build an interactive S&P 500 dashboard in Tableau with sector and valuation analysis.

Introduction

30 Second Summary

When you see interactive financial dashboards in analyst reports or on LinkedIn, they look like something only a seasoned data team could build. The truth is, you can create one yourself with free tools and publicly available market data.

In this project, you will build an interactive S&P 500 Financial Health Dashboard using Tableau and real financial data from all 500 companies. You will publish it to a live URL that anyone can access and interact with.

What You'll Build

When a recruiter clicks your Tableau Public link, they see a polished multi-view dashboard where they can filter by sector, hover over any company to see its financials, and watch all views update when they click a single sector bar.

By the end of this project, you'll have:

A sector breakdown chart that ranks all industries by market capitalization, so you can instantly see which sectors dominate the S&P 500 index.
A valuation scatter plot powered by a custom 52-Week Position calculated field you designed, letting you visually spot overvalued and undervalued companies across the entire index.
A live, interactive Tableau Public dashboard URL where clicking any sector bar instantly filters all views. You can paste this link directly into your resume or LinkedIn.
Secret Mission: A custom "Value Score" metric and a Top 10 Undervalued Companies highlight table with conditional formatting.

Are there any prerequisites?

None. This guide walks you through installing Tableau and downloading the dataset from scratch. All you need is a Windows PC and an internet connection.

Before We Start

You are about to build a financial analysis dashboard using real S&P 500 data. Before any hands-on work begins, take a moment to commit to what you are building and why it matters for your career goals.

Download Tableau and Your Dataset

Every dashboard starts with two ingredients: a visualization tool and raw data. In this step, you will get both set up so the rest of the project is pure building.

You will install Tableau Desktop Public Edition (completely free, no credit card required) and download a CSV file containing financial data for all S&P 500 companies.

In this step, get ready to:

Install Tableau Desktop Public Edition on your Windows PC.
Download the S&P 500 financial dataset as a CSV file.

Download and install Tableau Desktop Public Edition

Tableau Desktop Public Edition is the free version of the industry-standard data visualization tool used by analysts worldwide. It lets you build interactive charts and publish them to a free public URL.

Open your browser and go to the Tableau Public download page.
Click DOWNLOAD THE APP.
Fill out the registration form with your name and email address.
Click DOWNLOAD THE APP on the form to start the download.

A .exe installer file will download to your Downloads folder.

Open the downloaded .exe file to launch the installer.
On the Welcome screen, confirm the product listed is Tableau Desktop Public Edition.
Accept the licensing agreement and click Install.

The installation takes a few minutes. When it finishes, Tableau opens automatically.

When the registration dialog appears on first launch, select the option to use Tableau for free.
Sign in with the email you used during the download, or create a Tableau Public profile if prompted.

After registration, you land on the Tableau Start page.

Why do I need to register?

Registration creates your free Tableau Public profile. This is where your dashboard will be published later so anyone can view it via a shareable URL.

Installer not running or download stuck?

Make sure you are logged in as an Administrator on your Windows PC. The installer requires admin permissions.

If the download does not start, try a different browser or temporarily disable any ad blockers on the Tableau page.

help me troubleshoot my Tableau Desktop Public Edition installation on Windows

Download the S&P 500 financial dataset

This dataset contains financial metrics for all S&P 500 companies, sourced from Yahoo Finance. It includes stock prices, market cap, valuation ratios, and 52-week trading ranges.

Go to the S&P 500 Companies with Financial Information page on DataHub.io.
Find the constituents-financials section on the page.
Click the Download button next to it to download the CSV file.
Save the file somewhere easy to find, such as your Desktop or Documents folder.

What is in this dataset?

The constituents-financials.csv file is about 95 KB and contains one row per company. Each row includes columns like Symbol, Name, Sector, Price, Market Cap, Price/Earnings, Price/Book, 52 Week Low, and 52 Week High.

Some companies have missing values for certain financial fields. This is normal and you will learn how to handle it later in the project.

Can't find the download button?

You can also download the file directly using this stable URL: constituents-financials.csv. Right-click the link and select Save link as to save it to your computer.

help me download the S&P 500 dataset from DataHub.io

Verify your setup

Before you move on, confirm both pieces are in place.

Switch to Tableau Desktop Public Edition (it should still be open from the installation).
Look at the left side of the Start page under the Connect panel.
Confirm you can see Text file listed under To a File. This is the option you will use to load your CSV in the next step.
Open your Desktop or Documents folder and confirm the constituents-financials.csv file is there.

What should I see?

Tableau's Start page shows a Connect panel on the left with options grouped under headings like To a File and To a Server. You will use the Text file option to connect to your CSV data.

Your tools and data are ready. Next up, you will connect the CSV to Tableau and build your first sector overview chart.

Connect Your Data and Build a Sector Overview

Your tools are installed and your data is ready. Before diving into company-level comparisons, you need to orient yourself in the dataset.

Which sectors dominate the S&P 500 by market capitalization? In this step, you will connect your CSV file to Tableau and build a sector breakdown bar chart that answers that question in seconds.

In this step, get ready to:

Connect the CSV to Tableau as a data source.
Build a horizontal bar chart ranking sectors by market cap.
Format the chart for professional clarity.

Connect the CSV to Tableau

Tableau needs a data source before you can build any visualizations. You will point it at the CSV you downloaded in the previous step.

In Tableau, click Text file under the Connect panel on the left side of the Start page.
Navigate to where you saved constituents-financials.csv and select it.
Click Open.

Tableau displays a data preview showing the contents of your file.

Confirm you see columns including Symbol, Name, Sector, Price, and Market Cap in the preview table.

Don't see the right columns?

Make sure you selected the file named constituents-financials.csv and not a different CSV. The dataset from DataHub.io includes multiple files.

If columns appear but the data looks garbled, Tableau may have guessed the wrong delimiter. Click the separator dropdown above the preview and confirm it is set to comma.

Click the Sheet 1 tab at the bottom of the screen to move to the worksheet view.

You now see a blank worksheet with a Data pane on the left listing all the fields from your CSV.

Build the sector bar chart

The worksheet view is where you build visualizations by dragging fields onto shelves and the Marks card. You will place Sector on one axis and Market Cap on the other to see how total market capitalization breaks down.

In the Data pane on the left, find Sector and drag it onto the Rows shelf at the top.
Find Market Cap in the Data pane and drag it onto the Columns shelf.

Tableau automatically sums Market Cap for each sector and draws horizontal bars. You should see 11 bars of varying lengths.

Click the Sort Descending button in the toolbar to rank sectors from largest to smallest.
Drag Sector from the Data pane onto the Color mark on the Marks card (the panel below the shelves).

Each sector bar is now a distinct color, and a color legend appears on the right side of the view.

What is the Marks card?

The Marks card is where you control visual properties of your chart. Dragging a field to Color assigns each unique value a distinct color. Dragging to Size scales marks by a measure. Dragging to Detail adds granularity without changing appearance.

You will use all three of these properties in later steps to build richer visualizations.

Rename the sheet tab by double-clicking Sheet 1 at the bottom of the screen and typing Sector Overview.
Press Enter to confirm the name.

Format the chart for clarity

The raw Market Cap values display as long numbers (e.g. 83294183424). Formatting them as billions makes the chart instantly readable.

Right-click the Market Cap axis (the numbers along the top of the chart).
Select Format.
In the Format pane that opens on the left, click the Numbers dropdown.
Choose Currency (Custom).
Set Display Units to Billions.

The axis now shows clean values like $1B, $2B, $4B instead of raw integers.

Double-click the chart title area at the very top of the worksheet (it may say "Sheet 1" or be blank).
Type S&P 500 Market Cap by Sector in the title editor.
Click OK to apply the title.

Before you look at the final result, which sector do you expect to see at the top of the chart?

You should now see a horizontal bar chart with 11 colored bars representing GICS sectors, ranked from largest (likely Information Technology) to smallest. Market cap values display in billions along the top axis.

What are GICS sectors?

GICS (Global Industry Classification Standard) is the system used to categorize S&P 500 companies into 11 sectors like Information Technology, Health Care, and Financials. Every company in the index belongs to exactly one sector.

Chart looks different than expected?

If you see vertical bars instead of horizontal, check that Sector is on the Rows shelf and Market Cap is on the Columns shelf. Swapping them flips the chart orientation.

If your bars are not sorted, click the Sort Descending button in the toolbar again.

Still stuck? Ask for help here.

Your first visualization is complete. Next, you will build a scatter plot that zooms in from sector totals to individual company valuations.

Build a Valuation Scatter Plot

Your sector overview tells a high-level story about which industries dominate the S&P 500. Now it is time to zoom in and compare individual companies against each other.

A scatter plot comparing valuation ratios like P/E and Price/Book can reveal which companies might be overvalued or undervalued relative to their peers. But real-world financial data is messy. You are about to see firsthand why data cleaning is a critical analyst skill.

In this step, get ready to:

Create a new worksheet for your scatter plot.
Build a scatter plot comparing company valuations by P/E and Price/Book.
Observe how null values and outliers distort the visualization.

Create a new worksheet

Each visualization in Tableau lives on its own worksheet. You need a fresh one for the scatter plot so it stays separate from your sector bar chart.

Click the New Worksheet icon (the tab with a plus sign) at the bottom of the screen.
Double-click the new tab label at the bottom (it will say something like "Sheet 2").
Type Valuation Scatter and press Enter to rename it.

You should now see a blank worksheet with "Valuation Scatter" as the tab name at the bottom.

Build the scatter plot

A scatter plot needs two continuous measures on the axes, one for each dimension of comparison. You will use Price/Earnings on the horizontal axis and Price/Book on the vertical axis.

In the Data pane on the left, find Price/Earnings under Measures.
Drag Price/Earnings to the Columns shelf at the top of the workspace.
Drag Price/Book to the Rows shelf.

You should see a single dot on the canvas. Tableau is aggregating all companies into one data point. You need to tell Tableau to show each company individually.

Drag Name to the Detail mark on the Marks card (the card in the middle-left area of the workspace).

Now you should see many dots appear, one for each company in the dataset.

Drag Market Cap to the Size mark on the Marks card. Larger companies now get bigger dots.
Drag Sector to the Color mark on the Marks card. Each sector now has a distinct color.

What does each encoding mean?

You have mapped four data dimensions onto a single chart. The x-axis shows Price/Earnings (how much investors pay per dollar of earnings). The y-axis shows Price/Book (price relative to the company's book value).

Dot size represents Market Cap, so you can quickly spot the largest companies. Color represents Sector, letting you see whether certain industries cluster together in valuation space.

Only seeing one dot or no dots at all?

If you still see a single dot, make sure you dragged Name to the Detail mark specifically, not to Rows or Columns. Placing a dimension on Detail disaggregates the data without splitting the view into separate panes.

If you see dots but no color or size variation, confirm that Market Cap is on Size and Sector is on Color in the Marks card.

help me fix my scatter plot in Tableau

Observe the data quality problem

Your scatter plot is technically complete. Before you assess how useful it is, take a moment to predict what you expect to see.

Look at the overall shape of your scatter plot. Do you think the dots are spread out evenly across the chart, making it easy to compare companies? Or does something look off?

Here is what you are actually seeing: most of the dots are crammed into the bottom-left corner of the chart. A few extreme outliers stretch the axes far to the right or top, compressing everyone else into an unreadable cluster.

Why is this happening?

Some companies in the dataset have extremely high P/E ratios (200+), and some have null values where Yahoo Finance did not report a number. These extremes force Tableau to stretch the axes to accommodate them, which squashes the majority of companies into a tiny corner.

The chart is technically correct. Every data point is accurately plotted. But it is practically useless for comparison purposes. This is the real-world data quality challenge every analyst faces.

This is intentional. The unreadable scatter plot is exactly what happens when you visualize raw financial data without cleaning it first.

You have built a scatter plot that is accurate but useless. In the next step, you will clean the data by filtering out nulls and extreme outliers, then add a custom calculated field that turns this mess into a genuinely insightful visualization.

Clean the Data and Add a Calculated Field

Your scatter plot exists, but it is not useful yet. Most companies are crammed into a tiny corner while a few extreme outliers stretch the axes beyond recognition.

This is the real-world data quality challenge every analyst faces. Raw financial data contains null values and extreme numbers that distort the view. In this step, you will clean the data by filtering out noise and then create a custom calculated field that reveals where each stock sits in its 52-week price range.

In this step, get ready to:

Filter out null values and extreme outliers from the scatter plot.
Create a custom calculated field called 52-Week Position.
Customize tooltips to show a financial summary on hover.

Filter out nulls and outliers on Price/Earnings

The scatter plot's axes are stretched because some companies report extremely high P/E ratios (200+) or have missing values that Tableau cannot plot meaningfully. Filtering these out makes the chart readable.

Switch to your Valuation Scatter worksheet tab at the bottom of Tableau.
Right-click Price/Earnings on the Columns shelf.
Select Filter from the context menu.
In the Filter dialog that opens, check Exclude next to Null values to remove companies with missing P/E data.
Set the range to a minimum of 0 and a maximum of 100. This removes negative P/E values and extreme outliers while keeping the meaningful majority of companies.
Click OK.

Your scatter plot immediately updates. The horizontal axis now stops around 100 instead of stretching into the hundreds.

Why filter to 0-100 for P/E?

A Price/Earnings ratio above 100 usually means a company has very small earnings relative to its stock price. These extreme values compress everyone else into a tiny cluster. Removing them does not delete data from your source. It only hides them from this particular view so you can see the meaningful distribution clearly.

Filter out nulls and outliers on Price/Book

Right-click Price/Book on the Rows shelf.
Select Filter.
In the Filter dialog, exclude Null values.
Set the range to a minimum of 0 and a maximum of 30.
Click OK.

Your scatter plot should now show a readable spread of companies across both axes. The dots are no longer crammed into one corner.

Still seeing dots crammed in a corner?

Confirm both filters are applied. Check the Filters shelf on the left side of the worksheet. You should see both Price/Earnings and Price/Book listed there.
Double-check your range values. Right-click each field on the Filters shelf and select Edit Filter to review the settings.
Make sure you excluded Null values for both fields, not just set the range.

Help me fix my scatter plot filters.

Create a calculated field for 52-Week Position

Filtering cleaned the view. Now you will add analytical value by creating a custom metric. The 52-Week Position shows where each stock's current price sits between its yearly low (0%) and yearly high (100%). A stock near 1.0 is trading close to its 52-week high. A stock near 0 is trading close to its 52-week low.

Click Analysis in the top menu bar.
Select Create Calculated Field.
In the Calculation Editor that opens, name the field 52-Week Position.
Enter this formula in the formula area:

([Price] - [52 Week Low]) / ([52 Week High] - [52 Week Low])

Click OK.

What does this formula calculate?

The formula takes the current price, subtracts the 52-week low, and divides by the total range (high minus low). The result is a number between 0 and 1.

A value of 0.8 means the stock is trading at 80% of its 52-week range. This is your own custom financial metric. Recruiters notice when candidates design their own analytical measures rather than just displaying raw data.

The new calculated field appears in the Data pane with an equals sign (=) next to it, indicating it is a calculated field.

From the Data pane, drag 52-Week Position to the Color mark on the Marks card. This replaces the Sector coloring you had before.

Your scatter plot updates to show a color gradient. Stocks near their 52-week high appear as one color and stocks near their 52-week low appear as another.

Seeing an error in the Calculation Editor?

Check that the field names in your formula match the exact column names from your CSV. They must be [Price], [52 Week Low], and [52 Week High] with those exact spaces and capitalization.
Make sure the square brackets surround each field name. Tableau requires brackets around field names that contain spaces.
If the formula bar shows a red underline, hover over it to see the specific error message Tableau reports.

Help me fix my calculated field formula.

Add detailed tooltips for each company

Tooltips are the pop-up details that appear when you hover over a mark. Right now the default tooltip shows raw field names. You will customize it to display a clean financial summary for each company.

Click Tooltip on the Marks card to open the Edit Tooltip dialog box.
Clear the existing text in the tooltip editor.
Use the Insert menu at the top of the dialog to add fields one at a time. Insert: Name, Sector, Price, Price/Earnings, Price/Book, and 52-Week Position.
Add labels before each inserted field so the tooltip reads clearly (for example, type Company: before the Name field, Sector: before the Sector field, and so on).
Click OK to save your tooltip.

Before you test, what do you think you will see when you hover over a dot? Think about what data the tooltip should now display.

Hover over any dot in the scatter plot.

You should see a complete financial summary for that company: the company name, its sector, current price, P/E ratio, Price/Book value, and the 52-Week Position you just created.

Why customize the tooltip?

The default tooltip just dumps raw field names. A well-labeled tooltip turns your chart into an interactive research tool. Anyone exploring your dashboard can hover over any company and immediately understand its financial position without needing a separate data table.

Your scatter plot has gone from an unreadable mess to a genuine analytical tool. You cleaned the noise, added a custom metric that demonstrates original thinking, and made the whole thing explorable through tooltips. Next up, you will combine this chart with your sector overview into a single interactive dashboard and publish it live.

Assemble the Dashboard and Publish

You have two worksheets that tell different stories: one shows which sectors dominate the S&P 500, the other reveals individual company valuations. Right now they live on separate tabs, disconnected from each other.

Combining them into a single interactive dashboard with filter actions transforms separate views into a cohesive analytical tool. Publishing to Tableau Public gives you the live URL that goes directly on your resume.

In this step, get ready to:

Combine both worksheets into a single dashboard layout.
Add a filter action so clicking a sector filters the scatter plot.
Publish to Tableau Public to get a live shareable URL.

Create the dashboard layout

A Tableau dashboard is a canvas that holds multiple worksheets in a single view. You will place the sector bar chart on top and the valuation scatter plot below it.

Click the New Dashboard icon (the tab with a plus sign) at the bottom of the Tableau window.
In the Dashboard pane on the left, find the Size section and set it to Automatic so it adapts to any screen size.
In the Sheets section of the left pane, drag Sector Overview onto the top half of the dashboard canvas.
Drag Valuation Scatter onto the bottom half of the canvas.
Adjust the divider between the two views by dragging it up or down until both charts are clearly visible.

You should now see both your sector bar chart and your scatter plot on a single screen, stacked vertically.

Only seeing one chart?

Make sure you dragged the second sheet below the first, not on top of it. If a sheet replaced the other, press Ctrl+Z to undo, then drag again to the empty lower half of the canvas.

If the Sheets section is empty, confirm you renamed your worksheets to Sector Overview and Valuation Scatter in previous steps.

help me fix my dashboard layout

Add filter actions for interactivity

Filter actions let one chart control what another chart shows. You will connect the sector bar chart to the scatter plot so clicking a sector bar filters the scatter to show only companies in that sector.

Click Dashboard in the top menu bar.
Select Actions from the dropdown menu.
In the Actions dialog box, click Add Action and choose Filter.
In the Name field at the top, type Filter by Sector.
Under Source Sheets, check only Sector Overview (this is the chart that triggers the filter).
Under Target Sheets, check only Valuation Scatter (this is the chart that gets filtered).
Set Run action on to Select (the action fires when a user clicks a mark).
Click OK to close the Edit Filter Action dialog, then click OK again to close the Actions dialog.

What does this filter action do?

When someone clicks the Information Technology bar in the sector chart, the scatter plot instantly updates to show only IT companies. Clicking an empty area of the bar chart resets the filter and shows all companies again.

This is how professional dashboards guide analysis without requiring viewers to manually use filter controls.

Before you test, think about this: what do you expect to see when you click one of the sector bars in the top chart?

Click any sector bar in the Sector Overview chart on your dashboard.
Look at the scatter plot below. It now shows only companies from the sector you clicked.
Click an empty area of the bar chart to reset. All companies reappear in the scatter plot.

Clicking a bar does nothing?

Make sure you set Run action on to Select (not Hover or Menu). Reopen Dashboard > Actions and double-click your filter action to check.

Confirm that the Source is set to Sector Overview only and the Target is set to Valuation Scatter only. If both sheets are checked as Source, the action may behave unexpectedly.

help me troubleshoot my filter action

Publish to Tableau Public

Publishing uploads your dashboard to Tableau Public's free hosting. Anyone with the URL can view and interact with your work.

Click Server in the top menu bar.
Hover over Tableau Public, then click Save to Tableau Public.
Sign in with your Tableau Public account credentials. If you do not have an account yet, click the link to create a new one for free and follow the prompts.
When prompted for a workbook name, type S&P 500 Financial Health Dashboard and click Save.

What happens during publishing?

Tableau creates a data extract from your CSV and uploads it alongside your workbook. This process may take a minute or two depending on your internet speed.

When it finishes, your browser automatically opens to show your live dashboard on the Tableau Public website.

Your dashboard is public

Workbooks published to Tableau Public are freely accessible to anyone on the internet. Do not publish dashboards containing sensitive or private data.

For this project, the S&P 500 dataset is already public information, so publishing is safe.

What do you expect to see once publishing completes?

Your browser opens to a live Tableau Public page showing your interactive dashboard. The URL in your browser address bar is your shareable portfolio link.

Confirm that clicking a sector bar in the top chart still filters the scatter plot below, just like it did locally.
Copy the URL from your browser address bar. It looks something like public.tableau.com/views/....
Save this URL somewhere safe. This is the link you paste into your resume or LinkedIn profile.

Getting an error when publishing?

If Tableau asks you to switch from a live connection to an extract, allow it. Tableau Public does not support live data connections, so an extract is required.

If sign-in fails, make sure you are using your Tableau Public account (not a Tableau Server or Tableau Cloud account). You can create a free Tableau Public profile at public.tableau.com.

help me publish to Tableau Public

Your dashboard is live and shareable. Anyone with that URL can now explore your financial analysis, filter by sector, and hover over companies for details. Next up, tackle the Secret Mission to add a custom Value Score and a Top 10 Undervalued Companies table to your dashboard.

Secret mission

Build a Top 10 Undervalued Companies Table

Recruiters want to see you can go beyond visualization into original analysis. In this secret mission, you'll design a custom "Value Score" metric, rank companies by it, and add a conditionally formatted highlight table to your dashboard.

Clean Up Your Resources

This project runs entirely on free tools and free hosting. There are no ongoing costs, subscriptions, or paid resources to worry about. Decide whether to keep your resources as they are, or delete them entirely.

Resources you used:

Tableau Desktop Public Edition (installed on your Windows PC).
Published workbook on Tableau Public (free cloud hosting, no expiration).
Tableau Public account (free, no charges).
Local files: constituents-financials.csv and any saved .twbx workbook file on your computer.

Keep everything running

No action needed. Choose this if you want your dashboard to stay live and shareable.

Your dashboard remains accessible at its Tableau Public URL indefinitely at no cost.
Tableau Desktop Public Edition stays installed and ready for future projects.
You can re-open your local workbook file at any time, make changes, and re-publish to update the live version.

Pause - I'll come back to this later

Close Tableau Desktop to free up system memory. Your published dashboard stays live on Tableau Public with no action needed.

Close Tableau Desktop Public Edition.
Your published dashboard on Tableau Public will remain accessible at its URL. There is nothing to pause or shut down on the cloud side.
When you return, re-open Tableau Desktop and open your local .twbx file to continue editing.

Delete - I don't want to use this again

Remove all project resources and start fresh. Follow each step below for a complete cleanup.

Delete your published workbook from Tableau Public: sign in at public.tableau.com, go to your profile page, hover over your viz, click the More Actions icon, then select Delete This Viz.
Delete your local files: find and delete the constituents-financials.csv file and any saved .twbx workbook files from the folder where you saved them.
Uninstall Tableau Desktop Public Edition: open Control Panel, go to Programs, then Programs and Features. Right-click Tableau Public in the list and select Uninstall/Change. In the Modify Setup menu, select Uninstall.
Optionally delete leftover files: navigate to C:\Program Files\Tableau and delete the Tableau folder for the version you uninstalled.
Optionally delete your Tableau Public account: sign in to Tableau Public, click your profile icon and select Settings. Scroll to the Delete Tableau Public Profile section and select Delete My Tableau Public Profile. Enter your email address and select Delete.

Nice Work!

You just built and published a live, interactive financial dashboard that analyzes all 500 companies in the S&P 500. That Tableau Public URL is a portfolio piece you can paste straight into your resume or LinkedIn today.

You've learned how to:

Connect raw financial data, clean messy values (nulls and outliers), and transform a CSV into a multi-view interactive dashboard.
Design a custom calculated field (52-Week Position) that demonstrates original analytical thinking beyond displaying existing data.
Build interactive filter actions that connect multiple views into a cohesive dashboard and publish a live shareable URL to Tableau Public.
Secret Mission: Designed a custom Value Score metric combining multiple financial ratios and built a Top 10 Undervalued Companies highlight table with conditional formatting.

Ready to quiz yourself?