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.
- 📋 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.
- 🗑️ 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.
- 📊 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.
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Clone the repository:
git clone https://github.com/itsOwen/EZ-Analyst.git
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Set your OpenAI API key in the
auto_analysis.py
file:openai.api_key = "YOUR_API_KEY"
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Run the Streamlit app:
streamlit run main.py
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Access the app in your web browser at
http://localhost:8501
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Upload your CSV file or use the default "amazon_reviews.csv" dataset.
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Explore the various features of the app, including data exploration, data preprocessing, and auto analysis.
- Streamlit
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn
- OpenAI
- FPDF
Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.
This project is licensed under the MIT License.
For any questions or inquiries, please contact Owen Singh.
Feel free to customize the README file based on your specific project details and add any additional sections or information as needed.