Load-Transform-Analyze (LTA) Streamlit App

Overview

The Load-Transform-Analyze App is a Streamlit-based data analysis tool designed for easy dataset handling. It allows users to load, clean, and visualize data interactively.

Try It Here

lta-py.streamlit.app

Features

Load Data

🔸Upload CSV or Excel files.
🔸Load sample datasets.
🔸Preview loaded data, including the first rows and the shape of the DataFrame.
🔸Edit column data types using a data editor.

Transform Data

🔸Handle missing values using various methods such:

• Dropping rows
• Forward fill
• Backward fill
• Mean imputation
• Median imputation
• Mode imputation

🔸Download the transformed data as a CSV file.

Analyze Data

🔸Generate summary statistics for numeric columns.
🔸Create interactive charts, including:

• Line chart
• Bar chart
• Box plot
• Scatter chart

🔸Customizable X and Y axes with optional color grouping.
🔸Display a correlation heatmap for numeric columns.
🔸Show histograms for the distribution of numeric columns.

📊 Sample Data

This app includes publicly available datasets from Kaggle as sample datasets:

• ph_school_enrollment.csv
• ph_shs_table_strand.csv
• screentime_analysis_jan_2025.csv

Try It Here

lta-py.streamlit.app

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To install dependencies:

pip install -r requirements.txt

To run the app:

streamlit run main.py

Contributing

Contributions are wellcome! Feel free to fork the repository, make changes and submit a pull request.