eda-ts 1.1.0

An exploratory data analysys (EDA) tool for time series data

📘 Urecsys EDA Tool

Welcome to the Urecsys Exploratory Data Analysis (EDA) tools. This toolkit provides various features for analyzing and visualizing your datasets.

Overview

EDA is a crucial step in the data analysis process that helps you:

• Summarize main characteristics of datasets
• Detect anomalies
• Uncover patterns
• Visualize data relationships

Getting Started

1. Set up a virtual environment:

python -m venv .venv
source .venv/bin/activate  

Tip: You can also create a virtual environment in VS Code by pressing Ctrl+Shift+P (⌘ + Shift + P on macOS), typing Python: Create Environment, and following the prompts.

2. Install dependencies using Poetry:

poetry install

3. Launch the EDA tool:

streamlit run 0_📘_EDA.py

Tip: You can type streamlit run 0 and press Tab for auto-completion

4. Once launched, navigate to 🏠Overview in the sidebar

5. Upload your pickle file to begin analysis

Development

Adding New EDA Features

New EDA tools should be added under the eda/pages directory following this naming convention:

<number>_<emoji>_<title>.py

Example: 1_📊_overview.py

This naming pattern ensures proper ordering and visual organization in the Streamlit sidebar.

To create a new EDA page, you can start by copying the 101_📝_Template.py file. This template provides a basic structure for your new page.

Replace <number>, <emoji>, and <title> with appropriate values for your new page. This will help maintain consistency and organization within the project.