tseapy: Time Series Explorative Analysis Python

tseapy is an innovative open-source Python application designed for comprehensive and intuitive analysis of time series data. Leveraging the power of Python, it offers a user-friendly web interface that enables users to interact with their data dynamically, facilitating various time series analysis tasks. Whether you're a data scientist, researcher, or enthusiast, tseapy makes it easier to explore and understand time series data.

Getting Started

Follow these instructions to set up tseapy on your local machine for development and testing purposes.

Prerequisites

Before you begin, ensure you have the following installed:

Python 3.6 or higher
pip

Installation

Clone the Repository:

git clone https://github.com/mrkshdt/tseapy.git

Navigate to the Project Directory:
```
cd tseapy
```
Create a Virtual Environment:
```
python3 -m venv tseapy-venv
```
Activate the Virtual Environment:
- On Windows:
```
tseapy-venv\Scripts\activate
```
- On Unix or MacOS:
```
source tseapy-venv/bin/activate
```
Install Required Packages:
```
pip install -r requirements.txt
```

Usage

To launch tseapy:

Start the application:
```
python app.py
```
Open your web browser and navigate to: http://localhost:5000.

Project Structure

app.py: The entry point of the application.
tseapy/: The heart of the application, containing core functionalities such as data processing (tseapy/data/), task management (tseapy/tasks/), and web view (tseapy/view/).
templates/: Houses HTML templates for the web interface.
static/: Contains static files like CSS for styling.
tests/: Includes unit tests to ensure the reliability and efficiency of the application.

Embark on your time series analysis journey with tseapy – your go-to tool for insightful and interactive data exploration!

mrkshdt / tseapy