Data Analysis Programs

Web Scraping: Extract data (such as images, user reviews, or product descriptions) from web pages using Python libraries or tools like Beautiful Soup.

Exploratory Data Analysis (EDA): Dive into a dataset to summarize its main characteristics. Explore variables, distributions, correlations, and outliers.

Data Visualization: Create compelling visualizations using libraries like Matplotlib, Seaborn, or Plotly. Visualize trends, patterns, and insights from your data.

Sentiment Analysis: Analyze text data (e.g., social media posts, reviews) to determine sentiment (positive, negative, neutral). Use Natural Language Processing (NLP) techniques.

Cleaning Data: Practice data cleaning skills by handling missing values, duplicates, and outliers in a dataset.