EZ-Analyst: Automated EDA and Data Analysis App

EZ-Analyst is a Streamlit-based application that streamlines the process of exploratory data analysis (EDA) and automates data analysis tasks. With its user-friendly interface and powerful features, EZ-Analyst makes it easy for data analysts and enthusiasts to gain insights from their datasets quickly. The tool also leverages Open-AI to improve data analysis and generate code and reports easily.

Features

1. Data Exploration

• 📋 Dataset Preview: Get a quick overview of your dataset by displaying a specified number of rows.
• 📊 Dataset Overview: View the number of rows, columns, and duplicates in your dataset.
• 🕳️ Missing Values: Identify and summarize missing values in each column.
• 📈 Data Statistics and Visualization:
  • 🔢 Summary statistics for numerical columns
  • 📊 Statistics and value counts for categorical columns
• 📋 Data Types: Explore the data types of each column and filter columns by data type.
• 📊 Individual Feature Distribution: Analyze the distribution of individual numerical features using histogram, box plot, or KDE plot.
• 📈 Scatter Plot: Visualize the relationship between two numerical features.
• 📊 Categorical Variable Analysis: Analyze categorical variables using bar charts or pie charts.
• 🔍 Feature Exploration: Explore relationships between multiple numerical features using scatter plot matrix, pair plot, and correlation heatmap.
• 📊 Categorical and Numerical Variable Analysis: Analyze the relationship between a categorical and numerical variable using box plots.

2. Data Preprocessing

• 🗑️ Remove Unwanted Columns: Easily remove unwanted columns from your dataset.
• 🕳️ Handle Missing Data: Choose from various methods to handle missing data, such as removing rows or filling with mean, median, or mode.
• 📊 Encode Categorical Data: Apply one-hot encoding or label encoding to categorical columns.
• 📈 Feature Scaling: Scale numerical features using standardization or normalization techniques.
• 📊 Identify and Handle Outliers: Detect outliers in numerical columns and choose to remove them or replace them with the median value.
• 📥 Download Preprocessed Data: Download the preprocessed dataset as a CSV file.

3. Auto Analysis (BETA)

• 📊 CSV Analysis: Get recommendations and analysis based on your CSV file, including suggested visualizations, statistical tests, and insights.
• 🤖 Perform Auto Analysis: Generate auto analysis code and summary based on your dataset using OpenAI's language model.
  • Generate auto analysis code that performs a complete analysis, including importing required libraries, creating plots, and providing explanations.
  • Generate a detailed summary and analysis of the auto-generated code, explaining the generated graphs and providing insights as a full story analysis.
  • Download the auto analysis code and summary as PDF reports.

Usage

1. Clone the repository:

   git clone https://github.com/itsOwen/EZ-Analyst.git
   

2. Set your OpenAI API key in the auto_analysis.py file:

   openai.api_key = "YOUR_API_KEY"

3. Run the Streamlit app:

   streamlit run main.py
   

4. Access the app in your web browser at http://localhost:8501.

5. Upload your CSV file or use the default "amazon_reviews.csv" dataset.

6. Explore the various features of the app, including data exploration, data preprocessing, and auto analysis.

Dependencies

• Streamlit
• Pandas
• Matplotlib
• Seaborn
• Scikit-learn
• OpenAI
• FPDF

Contributing

Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.

Contact

For any questions or inquiries, please contact Owen Singh.

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