DATA ANALYSIS WITH PYTHON

Data analysis with Python involves using Python’s powerful libraries and tools to collect, clean, explore, visualize, and interpret data to support decision-making. It relies heavily on libraries such as Pandas for data manipulation, NumPy for numerical computations, Matplotlib/Plotly for visualization, and Scikit-learn for machine learning. The process typically includes importing datasets, handling missing values, filtering and transforming data, performing statistical analysis, generating charts, and building predictive models. Python’s simplicity, efficiency, and extensive ecosystem make it one of the most popular languages for data analysis across fields like business, research, finance, and engineering.