Update README.md

README.md

@@ -4,7 +4,133 @@ task_categories:
 - tabular-classification
 language:
 - en
-pretty_name: Google Play Store Apps (2010-2021)
+pretty_name: Google Play Store Apps 2020 - Cleaned
 size_categories:
-- 1M<n<10M
----
+- 1K<n<10K
+---
+
+# 📱 Google Play Store 2020 — What Made an App Go Viral?
+
+> **A data-driven EDA of 9,436 apps released in 2020, exploring the patterns behind viral success on the Play Store.**
+
+---
+
+## 🎬 Video Walkthrough
+
+<!-- Replace the src with your actual video link after uploading -->
+<video src="YOUR_VIDEO_URL_HERE" controls="controls" style="max-width: 720px;"></video>
+
+*Can't see the video? [Click here to watch](YOUR_VIDEO_URL_HERE)*
+
+---
+
+## 🔬 Research Question
+
+> **"What made an app released in 2020 go viral?"**
+
+Defined as reaching **1M+ installs by June 2021** — within 6–18 months of launch.
+
+2020 was chosen deliberately: the COVID-19 pandemic drove unprecedented mobile app adoption, and since the data was collected in June 2021, apps from 2020 had a consistent 6–18 month measurement window.
+
+---
+
+## 📊 Key Visualizations
+
+### 1. The Winner-Takes-All Market
+86% of apps never exceed 10K installs. Viral apps (<1%) are a thin but real right tail.
+
+![Installs Distribution](viz_01_installs_distribution.png)
+
+---
+
+### 2. Does Quality = Success? (Surprising Answer: No)
+Rating and Installs show a weak **negative** linear correlation (r = −0.31).
+Viral apps attract polarising reviews — millions of users means more critics.
+
+![Rating vs Installs](viz_06_rating_vs_installs.png)
+
+---
+
+### 3. Monetization Strategy Matters
+Ad-based and Hybrid (ads + IAP) apps reach significantly higher install counts.
+The price barrier for Premium apps dramatically limits reach.
+
+![Monetization vs Installs](viz_04_monetization_violin.png)
+
+---
+
+### 4. The Gap Between Tiers is Enormous
+Each tier is roughly **1,000x** the previous — a textbook power-law gap.
+
+| Tier | Median Installs | n apps |
+|------|----------------|--------|
+| Low | ~100 | 8,135 |
+| Medium | ~10,000 | 1,227 |
+| Viral | ~1,000,000 | 74 |
+
+![Success Tiers](viz_08_success_tiers.png)
+
+---
+
+## 🔑 Key Findings
+
+1. **The market is winner-takes-all.** 86% of apps sit in the Low tier. Viral apps represent less than 1% of 2020 launches.
+2. **Monetization is the strongest predictor.** Ad-based and Hybrid models (ads + IAP) significantly outperform Pure Free and Premium.
+3. **Higher ratings do NOT predict more installs** (r = −0.31). Quality alone is not the driver — distribution and visibility are.
+4. **Having a rating at all is a strong proxy for traction.** Rated apps contain virtually all Medium and Viral tier apps.
+5. **Fresher apps win.** Regular updates correlate negatively with days_since_update (r = −0.25).
+6. **The Rating–Installs relationship is category-specific.** A global r = −0.31 masks very different dynamics per category.
+
+---
+
+## 🗂️ Dataset
+
+| Property | Value |
+|----------|-------|
+| **Source** | [Kaggle — gauthamp10/google-playstore-apps](https://www.kaggle.com/datasets/gauthamp10/google-playstore-apps) |
+| **Original size** | 2.31M rows × 24 columns |
+| **Subset** | Apps released in 2020 only |
+| **Sample size** | 9,436 rows (Cochran's formula + stratified by Category) |
+| **Scraped** | June 2021 |
+
+### Features in this dataset
+
+| Feature | Type | Description |
+|---------|------|-------------|
+| `App Name` | string | Name of the app |
+| `Category` | categorical | App category (48 unique) |
+| `Rating` | float | Average user rating (NaN if unrated) |
+| `Rating Count` | int | Number of user ratings |
+| `Installs_clean` | int | Parsed install count |
+| `log_installs` | float | log(1 + Installs) — for modeling |
+| `Size_MB` | float | App size in MB (winsorized at 65.8MB) |
+| `Min_Android_ver` | float | Minimum Android version required |
+| `Released` | datetime | Launch date (all in 2020) |
+| `Last Updated` | datetime | Last update date |
+| `Free` | bool | Whether app is free |
+| `Ad Supported` | bool | Whether app shows ads |
+| `In App Purchases` | bool | Whether app has IAP |
+| `Editors Choice` | bool | Whether app is Editor's Choice |
+| `has_rating` | bool | Whether app has crossed rating threshold |
+| `app_age_days` | int | Days from release to scrape date |
+| `days_since_update` | int | Days from last update to scrape date |
+| `engagement_ratio` | float | Rating Count / Installs |
+| `log_engagement` | float | log(1 + engagement_ratio) |
+| `developer_app_count` | int | Total apps by same developer in 2020 |
+| `monetization_model` | categorical | Pure Free / Ad-based / Freemium / Hybrid / Premium |
+| `success_tier` | categorical | **Target variable** — Low / Medium / Viral |
+
+---
+
+## 📓 Notebook
+
+The full analysis notebook is available here:
+👉 [Open The Notebook in Google Colab](https://colab.research.google.com/drive/1YxqN2Urjli1ToxtYO9LtUztXxb5SeEcb?usp=sharing)
+---
+
+## 👤 Author
+
+**Yonathan Levy**
+Econ & Entrepreneurship with Data Science Specialization
+Reichman Uni
+Class of 2028