Python plays a crucial role in both data visualization and analysis. Here’s a brief overview:

1. Data Analysis:
   • Python, with libraries like Pandas, allows you to manipulate, clean, and explore data efficiently.
   • You can load data from various sources (CSV files, databases, APIs) and perform tasks like filtering, aggregation, and transformation.
   • NumPy provides essential tools for numerical computing, including arrays and mathematical functions.
2. Data Visualization:
   • Python’s Matplotlib library enables you to create various plots (line charts, bar charts, histograms) for visualizing data.
   • Seaborn builds on Matplotlib, offering higher-level interfaces for statistical visualizations.
   • With Python, you can generate insightful graphs, charts, and dashboards to communicate findings effectively.

Remember that Python’s versatility and rich ecosystem make it a powerful choice for data professionals!