Welcome to my Data Analysis repository! 📊📈
- Pandas and Numpy: Dive into the power of Pandas and Numpy as I explore data structures, perform data aggregation, and more.
- Data Cleaning: Learn how to handle missing values, eliminate duplicates and ensure data consistency for a clean and reliable dataset.
- Data Visualization: Experience the beauty of data visualization with matplotlib and seaborn, bringing data to life with insightful charts and graphs.
- Reading Data with Python: Discover how to effortlessly read data from various sources, including Excel, CSV, HTML tables and relation databases.
- Explore the world of interactive web applications for data analysis. Using Streamlit, I've developed various applications that allow users to visualize and analyze data in an intuitive and interactive manner. From stock price analysis to DNA sequence counting, each Streamlit app serves a unique purpose in exploring and understanding data.
Data Analysis: A process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making. (Definition by Wikipedia)
All this content in this repository was provided by FreeCodeCamp.