# Clinical-Trials-Analysis

This repository contains my first assignment for the Exploratory Data Analysis (EDA) class at Atomcamp, guided by Ma'am Maimoona Khilji. The assignment focuses on analyzing clinical trials data, with an emphasis on data cleaning, processing, and exploratory analysis using Python and pandas.

## Assignment Context

- **Institution**: Atomcamp

- **Instructor**: Ma'am Maimoona Khilji

- **Course**: Exploratory Data Analysis (EDA)

- **Assignment**: Analyze clinical trials data to extract insights and trends, particularly for trials starting after January 1, 2020.

## Contents

- Data cleaning scripts to handle missing values and format inconsistencies.

- Exploratory analysis scripts to understand trial enrollments and outcomes.

- Visualizations to represent the data and insights effectively.

## Objectives

- To provide a comprehensive view of the clinical trials landscape in recent years.

- To identify trends and patterns that could inform future research directions.

- To contribute to the open-source community by sharing methodologies for analyzing clinical trials data.

## How to Use

- Clone the repository to your local machine.

- Ensure you have pandas installed in your Python environment.

- Run the scripts to generate insights on your own clinical trials dataset.

Feel free to fork, star, or contribute to this repository if you find it helpful for your research or work!