Interactive Data Analysis Dashboard

💡 What Is This?

Hey there! Got some data you wanna check out without writing a ton of code?
Perfect. This little app is your data playground — upload your file, clean it up, make some sick charts, and explore insights fast.

It’s all about getting quick answers from your data without firing up a heavy Jupyter notebook.
Super easy, super fast. Let’s dive in! 🚀

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🧠 What This App Can Do

1. 📂 Upload Your Files

• Supports CSV and Excel files.
• Automatically detects delimiters (commas, semicolons, etc.).
• Choose between multiple Excel sheets if needed.

2. 🧹 Clean Up Your Data

• Nuke Missing Stuff:
  Delete rows with missing data or auto-fill them using smart techniques (mean for numbers, most frequent for text).
• Ditch Useless Columns:
  Remove irrelevant columns (like random ID fields) to keep your analysis tidy and focused.

3. 📈 Get the Lowdown on Your Data

• Before & After: Compare original vs cleaned data side-by-side.
• Quick Stats: Instantly see:
  • Number of rows & columns
  • Data types (numeric, text, etc.)
  • Basic stats: mean, max, min, std. deviation, etc.
• Spot the Gaps: Identify columns with missing values and their counts.

4. 🎨 Make Awesome Charts!

Bring your data to life with interactive visuals:

• Histograms: Understand data distribution.
• Box Plots: Spot outliers and ranges.
• Scatter Plots: Explore relationships between variables (with optional color-coding!).
• Bar Charts: Compare metrics across categories.
• Heatmaps: Reveal correlations and relationships at a glance.

5. 📝 Grab a Report

Download a .txt summary of your cleaned dataset — includes:

• Statistical summaries
• Data types
• Missing value counts
  Perfect for note-taking or sharing with your team.

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⚙️ How to Get It Running

✅ Requirements

• Python 3.8+ installed on your system.
• (Optional but recommended) Use a virtual environment to keep dependencies isolated.

🪄 Installation & Startup

1. Get the Code
   Download or clone this repository and locate the app.py file.

2. Install Dependencies

   Open your terminal or command prompt and run:

   pip install streamlit pandas matplotlib seaborn openpyxl
   

3. Run the App

   Navigate to the project folder and execute:

   streamlit run app.py