Problem Statement
Suppose there is a pharmaceutical startup that was recently acquired by one of the world's largest MNC. for the acqurision process,startup is required to tabulate all drugs that they have sold and account for each drug's effectiveness.
Healthcare providers and patients alike can benefit from understanding consumer reviews of drugs to make informed decisions. However, with the vast amount of data available, it's challenging to sift through reviews manually. The goal of this project is to use data science techniques to analyze consumer reviews and provide insights into drug effectiveness based on consumer sentiment.
Objectives:-
1.Data Collection: Gather consumer review data from a reliable source.
2.Data Cleaning and Preparation: Preprocess the data to ensure it is suitable for analysis.
3.Exploratory Data Analysis (EDA): Explore the data to understand distributions, trends, and correlations
4.Sentiment Analysis: Apply natural language processing techniques to extract sentiment from consumer reviews.
5.Drug Effectiveness Analysis: Analyze the relationship between drug ratings, reviews, and reported effectiveness.
6.Visualization: Create visualizations to present insights clearly and intuitively
7.Recommendations: Provide recommendations for healthcare providers based on the analysis.
Dataset-
The dataset used in this project is sourced from consumer drug reviews. It includes information such as the drug name, condition treated, consumer review, rating, and useful count
Technologies Used:-
Python
Pandas, NumPy, Matplotlib, Seaborn
Natural Language Toolkit (NLTK), TextBlob
Textual Analysis
Jupyter Notebook