This repository contains a collection of data analysis projects implemented in Python. Each project uses Python libraries and techniques to extract insights and make data-driven decisions.
Labs List
Lab 1 Introduction
Description:
- Acquire data in various ways
- Obtain insights from data with Pandas library
Libraries/Frameworks used: Pandas, NumPy
Key techniques employed:
- Data Acquisition
- Basic Insight into the Dataset
Lab 2 Data Wrangling
Objectives:-
- Handle missing values
- Correct data format
- Standardize and normalize data
Table of Contents:-
- Identify and handle missing values
- Identify missing values
- Deal with missing values
- Correct data format
- Data standardization
- Data normalization (centering/scaling)
- Binning
- Indicator variable
Lab 3 Exploratory Data Analysis
Objectives:- Explore features or characteristics to predict the price of the car
Table of Contents:-
- Import Data from Module
- Analyzing Individual Feature Patterns Using Visualization
- Descriptive Statistical Analysis
- Basics of Grouping
- Correlation and Causation
- ANOVA
Lab 4 Model Development
Objectives:- After completing this lab you will be able to:
Table of Contents:-
- Develop Prediction Models
How to Use Clone the repository:- git clone https://github.com/Yash22222/data-analysis-with-python.git
Install the required dependencies:
''' pip install -r requirements.txt '''
Navigate to the desired project folder: cd project-folder-name
Run the project: python main.py
