Correlation b/w data analytics and Python ?

Python Libraries Used for Data Analytics!

1?? Pandas: This library is essential for data manipulation and exploration. It provides efficient data structures and functions to work with structured data

.2?? NumPy: Widely used for numerical computing, NumPy facilitates operations on large arrays and matrices, offering essential mathematical functions.

3?? Matplotlib & Seaborn: These libraries are fundamental for data visualization. They allow users to create various types of plots and graphs to represent data visually.

4?? Scikit-learn: Ideal for machine learning tasks, Scikit-learn offers a range of algorithms and tools for data modeling, classification, regression, and clustering.

5?? TensorFlow & PyTorch: These frameworks are essential for deep learning applications. They provide tools for building and training neural networks, enabling advanced machine learning tasks.

6?? Statsmodels: This library is invaluable for statistical modeling and analysis. It offers a wide range of statistical tests and models for hypothesis testing and regression analysis.

7?? Dask: Useful for parallel computing and handling large datasets, Dask enables users to work with data that exceeds the memory capacity of their systems.

8?? Bokeh & Plotly: These libraries are crucial for creating interactive visualizations and dashboards, and enhancing data exploration and presentation. #data #analytics #python