Python
📊 Data Analysts:
A Data Analyst is a professional who 📊 collects, processes, and 📈 analyzes data to provide insights and support decision-making.
🐍 Python/R: Programming languages used for data analysis, statistical modeling, and visualization.
Python is a versatile and widely-used programming language that has gained significant popularity in the data science and analysis communities. It offers a rich ecosystem of libraries and tools for data manipulation, analysis, and visualization.
NumPy: A fundamental package for scientific computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a wide range of mathematical functions to operate on these arrays.
Pandas: A powerful library for data manipulation and analysis. It introduces data structures like DataFrame, which makes handling and analyzing structured data more intuitive.
Matplotlib: A widely-used 2D plotting library that produces high-quality figures and plots. It provides a flexible range of visualization options for various types of data.
Seaborn: Built on top of Matplotlib, Seaborn is another visualization library that provides a higher-level interface for creating attractive and informative statistical graphics.
Scipy: Built on top of NumPy, Scipy is used for scientific and technical computing. It provides functions for optimization, integration, interpolation, and more.
Scikit-learn: A machine learning library that provides simple and efficient tools for data mining and data analysis. It includes various algorithms for classification, regression, clustering, and more.
Statsmodels: A library focused on statistical modeling. It provides classes and functions for estimating and interpreting a wide range of statistical models.
🔗 Learn more:
Official Python Website: The official website for the Python programming language, where you can find documentation, tutorials, and resources: python.org
NumPy: The official website for the NumPy library, which provides support for large, multi-dimensional arrays and matrices: numpy.org
Pandas: The official website for the Pandas library, used for data manipulation and analysis: pandas.pydata.org
Matplotlib: The official website for the Matplotlib library, used for creating 2D plots and visualizations: matplotlib.org
Seaborn: The official website for the Seaborn library, which provides high-level interface for statistical data visualization: seaborn.pydata.org
Scipy: The official website for the SciPy library, used for scientific and technical computing: scipy.org
Scikit-learn: The official website for the Scikit-learn library, used for machine learning: scikit-learn.org
.png)
Comments
Post a Comment