📺 Friends TV Series – Audience & Cultural Impact Analysis

This project explores the audience of the TV series Friends across its 10 seasons, combining quantitative metrics (viewership and ratings) with qualitative aspects (directors, writers, and iconic quotes). The goal is to analyze which factors influenced the audience and how certain elements became part of the cultural legacy of the show.

🔗 Interactive visualizations on Tableau Public

• Friends TV Series – Audience & Cultural Impact
• Tableau Portfolio with Advanced Features – Ana Nobre Santos
• Power BI with Advanced Features – Ana Nobre Santos

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🎯 Project Objectives

• Analyze the evolution of viewership per season and episode.
• Assess whether episode direction had a direct impact on audience levels.
• Investigate whether iconic quotes influenced peaks in viewership.
• Demonstrate the connection between viewership data and the cultural impact of Friends.

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🖥️ How to Open the Project

Tableau Public

1. Download Tableau Public Desktop (free).
2. Open the .twbx packaged workbooks inside the Tableau/ folder.
3. Or access directly via the Tableau Public links above.

Power BI (Mac users with VirtualBox)

1. Install VirtualBox and set up a Windows VM.
2. Inside Windows, install Power BI Desktop (free from Microsoft Store).
3. Clone or download this GitHub repository inside the Windows environment.
4. Open the file with Power BI Desktop:

   Power-BI/Friends - Power BI.pbix
   

📌 Note: Power BI Desktop only runs on Windows. If you are on macOS or Linux, you will need to use a Windows VM (e.g., VirtualBox, Parallels) to open the .pbix file.

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📊 Tableau Visualizations

1. Big Numbers

• 236 episodes across 10 seasons.
• 32M peak audience in the U.S.
• 52.9M viewers for the final episode.
• Average IMDb rating: 8.5/10.
• Cultural longevity: iconic quotes like “How you doin’?” and “Oh my God!” remain part of popular culture decades after airing.

2. Audience by Season (Total & Average Views)

   • Consolidated viewership per season.
   • Insight: the show averaged 22M–26M viewers per season, peaking in Season 2.

   🏆 Top 5 Episodes by Audience:
   1 “The One After the Superbowl, Part 1” (S2E12) → 52.9M
   2 “The One After the Superbowl, Part 2” (S2E13) → 52.9M
   3 “The Last One, Part 1” (S10E17) → 52.5M
   4 “The Last One, Part 2” (S10E18) → 52.5M
   5 “The One Where Rachel Has a Baby, Part 2” (S8E24) → 34.9M

3. Directors vs Audience

   • Stacked area chart comparing directors’ contributions.
   • Insight: no strong correlation between directors and audience; trends aligned with the narrative arc.

4. Quotes, Views & Cultural Impact

   • Cross-analysis of quotes (“How you doin’?”, “Oh my God!”) vs ratings.
   • Insight: quotes did not spike viewership but became part of the cultural memory.

📷 Tableau Dashboard Previews

1. The One With the Context

2. The One Where Peak to Finale

3. The One With the Highest Ratings

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📊 Power BI Visualizations

1. Audience Overview by Season & Year

• KPIs: total episodes (236), seasons (10), IMDb rating (8.46), total audience (~6B views).
• Viewership trends by season and across time (year/quarter/month/day).

2. Audience by Episode & Season

• Viewership evolution across episodes within each season.
• Highlights spikes for milestone episodes such as the Super Bowl special and the finale.

3. Directors & Top Episodes

• Number of episodes directed by each director.
• Correlation between directors, votes, and average viewers.
• Highlight of the Top 5 episodes by votes using a Treemap visualization.

4. Quotes by Character

• Distribution of quotes by character.
• Breakdown of iconic phrases (“Oh my God!”, “How you doin’?”, “We were on a break!”).
• Dynamic Season filter for interactivity.

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⚡ Advanced Features Implemented

🔹 Tableau

• Navigation Buttons → interactive storytelling across dashboards.
• Calculated Fields (with rationale):

// Season & Episode 
// Creates a compact, readable key (e.g., "S2E13") to uniquely identify each episode
// across the entire series. Useful for labeling charts, building tooltips, joining tables,
// and enabling quick filtering/search by episode code.

Code: "S" + STR(INT([Season])) + "E" + STR(INT([Episode Number]))

// Standardize character names
// Source data had inconsistent casing (e.g., "rachel", "RACHEL", "Rachel").
// PROPER() normalizes to "Rachel", ensuring clean grouping, accurate aggregations,
// correct sorting, and a polished look in legends/labels.

Code: PROPER([Author])

// Detect iconic quote
// Flags whether a quote contains Joey’s catchphrase regardless of capitalization.
// LOWER() standardizes text to lower case; CONTAINS() finds the substring.
// This boolean can drive filters, highlight actions, counts by episode/character,
// and comparisons against viewership peaks.

Code: CONTAINS(LOWER([Quote]), "how you doin")```tableau
// Season & Episode 
// Creates a compact, readable key (e.g., "S2E13") to uniquely identify each episode
// across the entire series. Useful for labeling charts, building tooltips, joining tables,
// and enabling quick filtering/search by episode code.

Code: "S" + STR(INT([Season])) + "E" + STR(INT([Episode Number]))

// Standardize character names
// Source data had inconsistent casing (e.g., "rachel", "RACHEL", "Rachel").
// PROPER() normalizes to "Rachel", ensuring clean grouping, accurate aggregations,
// correct sorting, and a polished look in legends/labels.

Code: PROPER([Author])

// Detect iconic quote
// Flags whether a quote contains Joey’s catchphrase regardless of capitalization.
// LOWER() standardizes text to lower case; CONTAINS() finds the substring.
// This boolean can drive filters, highlight actions, counts by episode/character,
// and comparisons against viewership peaks.

Code: CONTAINS(LOWER([Quote]), "how you doin")

🔹 Power BI

• Buttons with Bookmarks — Add interactivity and a clean UX by letting users toggle between chart states (e.g., different visuals, views, or filters) within the same page. This avoids clutter, keeps context, and supports storytelling (e.g., “Overview” vs “Deep Dive”).

  • How it works (high-level):
    1. Arrange the visuals for View A (e.g., line chart) and View B (e.g., bar chart).
    2. Create a bookmark for each state (View A, View B) capturing data/visibility.
    3. Insert buttons and assign Action → Bookmark (View A / View B).
    4. (Optional) Use Selection Pane to show/hide visuals per bookmark and Sync slicers to carry the same filters across views.

• Custom DAX Column — Detects an iconic phrase in the quotes table regardless of capitalization, so you can segment, filter, or highlight episodes/characters that use it. This enables counts, comparisons (e.g., against viewership peaks), and dynamic labels.

-- Returns a readable label
-- Returns a Boolean (preferred for modeling/filters), more efficient for measures and visuals that need TRUE/FALSE logic.
-- Useful for filters, visuals, and storytelling (“Contains OMG” vs “Does not contain”).
Column_OMG =
IF (
    CONTAINSSTRING ( LOWER ( 'friends_quotes'[quote] ), "oh my god" ),
    "Contains OMG",
    "Does not contain"
)

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🎬 Data Storytelling

This project goes beyond data visualization. By combining interactivity (buttons, filters, parameters) with cultural context (quotes, characters, directors), the dashboards create a storytelling experience that explains not just what happened with Friends viewership, but also why it mattered in popular culture.

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📂 Repository Structure

Portfolio-Tableau-Power-Bi-Friends-Audience-Impact │ ├── 📄 README.md
│ ├── 📂 data/
│ ├── friends_episodes_v3.csv │ ├── friends_info.csv │ └── friends_quotes.csv │ ├── 📂 Power-BI/
│ ├── Dashboard-1-Power-BI-(Episode-and-Season).png │ ├── Dashboard-1-Power-BI-(Season-and-Year).png │ ├── Dashboard-2-Power-BI.png │ ├── Dashboard-3-Power-BI.png │ └── Friends - Power BI.pbix │ ├── 📂 Tableau/
│ ├── (1) The One With the Context.png │ ├── (2) The One Where Peak to Finale.png │ └── (3) The One With the Highest RatingsScreenshot.png │ └── .gitignore

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📌 Key Insights

Audience consistency Over ten seasons, Friends kept an unusually steady audience. Most seasons averaged between 22 and 26 million viewers, with a high point around 31 million in Season 2. That gap of about 5 million viewers is striking. To put it in context, it matches the audience size of many U.S. primetime shows (Hollywood Reporter, 2025). It’s also similar to the population of entire states like Wisconsin or Colorado (U.S. Census Bureau, 2024a; 2024b) or even a country such as Norway (~5.6 million) (Statistics Norway, 2025).

Why peaks happened The biggest spikes were not about the directors. They came from special contexts. “The One After the Superbowl” (S2E12–13), which aired right after the Super Bowl, pulled in around 52.9M viewers. The finale, “The Last One” (S10E17–18), reached about 52.5M because it was the end of the story.

Direction wasn’t determinant Directors like Kevin S. Bright and Michael Lembeck were behind many well-known episodes. But ratings didn’t really move with their names. The ups and downs followed the storylines and the timing—big cultural moments, not who was calling the shots behind the camera.

Engagement beyond TV It’s important to highlight that we’re not talking here about traditional TV audience, but rather about fan engagement on IMDb. Each episode can be rated by users, and the number of votes reflects how many people actively left a score—regardless of whether it was high or low.

When looking at the chart, we see that the series starts very strong, with just over ~100k votes in Season 1, and then gradually declines to ~65k. This points to a reduction in online engagement over time, even though the fan base remained wide. Analytically, these “votes” can be read as a proxy for how much interest fans kept showing in the series year after year.

Iconic quotes Catchphrases didn’t drive immediate ratings. Their impact came later, as part of the show’s long-term memory. A good example is Joey’s “How you doin’?”. Many people think he said it dozens of times, when in reality it appears only ~22 times across all 236 episodes. What makes it unforgettable isn’t the absolute number, but the weight of each moment:

🔹 Joey uses it in very marked comic situations, so the context makes each repetition stronger. 🔹 Those ~22 occurrences were rewatched millions of times in DVDs and streaming, amplifying the memory. 🔹 The phrase was reinforced outside the show—merchandising, interviews, memes—until it became pop culture itself.

Hollywood Reporter (2025) ‘TV Ratings: All 112 Shows That Averaged 5 Million or More Viewers in 2024–25’. Available at: https://www.hollywoodreporter.com/tv/tv-news/2024-25-tv-season-100-biggest-shows-ratings-1236257863/ (Accessed 17 September 2025).

U.S. Census Bureau (2024a) QuickFacts: Wisconsin. Available at: https://www.census.gov/quickfacts/WI (Accessed 17 September 2025).

U.S. Census Bureau (2024b) QuickFacts: Colorado. Available at: https://www.census.gov/quickfacts/CO (Accessed 17 September 2025).

Statistics Norway (2025) Population. Available at: https://www.ssb.no/en (Accessed 17 September 2025).

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👩‍💻 Author

Ana Nobre Santos

• LinkedIn
• Tableau Public
• GitHub

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📂 This project is part of my Data Analytics portfolio, showcasing the blend of data visualization, interactivity, and storytelling applied to one of the most popular TV series of all time. Explore my Tableau Public and GitHub for more projects featuring advanced Tableau and Power BI techniques.