/Online-Shopping-Sentiment-Analysis---Flipkart

This project, conducted in collaboration with Global Core Tech, focuses on analyzing sentiment in Flipkart reviews. Using Python and essential data science libraries like Pandas, Matplotlib, NLTK, and Seaborn, we aim to extract valuable insights into customer sentiments from the reviews.

Primary LanguageJupyter NotebookMIT LicenseMIT

Global Core Tech Internship - Data Science with Python

Welcome to the Global Core Tech Internship on Data Science with Python! This four-week program, from October 26th to November 24th, equips you with essential skills in data science using Python, focusing on libraries such as NumPy, Pandas, Matplotlib, and exploratory data analysis (EDA).

Table of Contents

  • Prerequisites
  • Python 3.7 Installation
  • Setting up the Environment
  • Getting Started
  • Verifying Python Installation
  • Installing Libraries
  • Exploratory Data Analysis (EDA)
  • Projects

Prerequisites

Python 3.7 Installation

  1. Download Python 3.7 from python.org.
  2. Run the Windows x86-64 executable installer.
  3. During installation, ensure to:
    • Add Python 3.7 to your system PATH.
    • Select "Install launcher for all users" and "Add Python 3.7 to PATH."
  4. Complete the installation process and verify Python 3.7 installation by running: 
    python --version

Setting up the Environment

  1. Open a command prompt and execute: 
    set PATH=%PATH%;C:\Program Files\Python3
  2. Edit system variables, adding C:\Program Files\Python3 to the PATH variable.
  3. Verify the Python version: 
    python --version

Getting Started

Verifying Python Installation

Ensure Python 3.7 is installed:

python --version

Installing Libraries

Install required libraries using pip:

pip install numpy pandas matplotlib seaborn plotly

After installation, close the command prompt.

Verifying Library Installation

Verify libraries by running commands in Python IDLE for Python 3.7.0:

import pip
import numpy
import pandas
import matplotlib
import seaborn
import plotly

Exploratory Data Analysis (EDA)

Explore and analyze data using installed libraries. During this internship, work on data science projects in Jupyter Notebook using Python 3.7.0. One project is the Online Shopping Sentiment Analysis Project: Flipkart.

Online Shopping Sentiment Analysis Project: Flipkart

Project Description: Analyze sentiment in online shopping reviews on Flipkart. Classify reviews into positive, negative, or neutral sentiments, providing valuable insights for consumers and businesses.

Project Goals:

  1. Collect and preprocess data from Flipkart reviews.
  2. Perform text analysis and sentiment classification.
  3. Create visualizations to present findings effectively.
  4. Draw conclusions and make recommendations based on sentiment analysis results.

This project allows you to apply knowledge gained during the internship to a real-world data science scenario, showcasing your abilities as a data scientist.