Automobile Data Analysis App - Streamlit

Data Analysis
It is the process of systematically applying statistical and/or logical techniques such as cleaning, transforming, and modeling data to discover useful information for business decision-making.

Dataset used

Technologies used
Language

  • Python- for programming and writing logic.
  • CSS - for adding some UI/UX.

Python libraries
api, beautifulsoup4, matplotlib, numpy, pandas, pickle_mixin, plotly, requests, scikit_learn.

Algorithms
Machine Learning Algorithms such as Linear Regression and SVM Regression.

APIs
NewsAPI.

Framework for deployment
Streamlit.

Hosted on
Streamlit share.

Deployment
After all the code is written, it is deployed on Streamlit framework, with a few changes to the code for errorfree deployment.

Hosting
After all the code is ready and the app is all deployed, it is hosted on streamlit share.

Deployed Link:

Functionality & features :

1. Visual Representation :
You can visually represent the different features of cars such as engine size, length, width, horsepower, etc in the form of various charts and graphs such as bar, line, area, scatter, pie, donut chart. The charts and graphs are interactive; you can choose or select one or more features, and also the type of graphs.

2. Dependency & Analysis :
You can check out the dependency and variation of one feature of an automobile with other features such as engine size, length, width, horsepower, etc , in the form of line and area graph. The charts and graphs are interactive; you can choose or select one or more features, and also the type of graphs.

3. Price Prediction :
You can predict the price of a car by inputting several parameters such as width, horsepower, engine size etc. You can also choose the prediction model to predict the price - Linear Regression or SVM Regression.

4. Resolve Queries :
You can resolve various queries related to automobiles such as-

  • find the cars with specific value of features , for example find the car names whose engine size is greater than 200, etc.
  • find the highest/lowest values of the features, for example find the highest value of length or width of car, and the car names which possess these values,etc.
  • find and view grouping and segmentation of two features ie to show best combinations of two specific features which are availabel.

5. Automobile News :
News extracted using the NewsAPI can be shown here.You can search a keyword related to automobiles and get access to news related to it.

Application of Data Analysis in Automobile Industry

In automobile industry, analyzed data is used to improve the customer experience, where data grouping and segmentation can lead to more effective marketing and improved customer engagement , more targeted one‑to‑one offers and can help the automobile industry to correctly manage the features and price of cars. -The analyzed data can be used for changing the auto business, support mechanization, and boost automation.

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