https://github.com/adityaraute/therminer-assignment
Development Assignment for Therminer
https://github.com/adityaraute/therminer-assignment
flask
Last synced: 2 months ago
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Development Assignment for Therminer
- Host: GitHub
- URL: https://github.com/adityaraute/therminer-assignment
- Owner: adityaraute
- Created: 2024-11-07T18:30:24.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-11-13T07:58:48.000Z (over 1 year ago)
- Last Synced: 2025-12-26T17:39:13.703Z (6 months ago)
- Topics: flask
- Language: Python
- Homepage:
- Size: 69.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
### Therminer Assignment
This repository contains the code developed for the Flask assignment received as part of the Therminer evaluation process.
*Following the closure of the process, this repository will be turned private.*
### Aim
To create a Python - Flask web app with a data analytics page.
### Changelog
###### v0.4.0
Features
- Legend repositioned to bottom-left
- Parametric traces added to main visualisation
Scope for Improvement
- Prediction Model Accuracy
- Responsive Legend for mobile
Screenshot
###### v0.3.0
Features
- Display Count of observations and Standard Deviation values of the generated dataset
- Make the entire UI responsive enough for mobile usage
- Fix the `requirements.txt` file
Scope for Improvement
- Prediction Model Accuracy
- Metrics on graph
Mobile Screenshot
###### v0.2.0
Features
- Display Median and Mean values of the generated dataset
- Value Forecast for the next 6 hours for the graph (Beta)
- Confidence interval for the forecast graph
- Plotly visualisation displaying forecast values and confidence interval values
- Form fields flushed after Back button
Scope for improvement
- Accuracy of the forecasting model for both linear and random graphs is poor
- Webpage could be made more responsive for mobile devices
Screenshot
###### v0.1.0
Features
- Flask repository creation
- Form for Linear and Random curve data inputs
- Dataset generation based on form inputs
- Plotly Express visualisation based on generated dataet
- Display Minimum and Maximum value of the generated dataset
- Header and footer with necessary styling elements
Scope for improvement
- Format the parameter section better
- Implement a forecasting module
- Improve UX
Screenshot
