Tools \ Pandas
Pandas is a powerful, flexible, and easy-to-use library for data manipulation and analysis, providing high-performance tools for working with structured (tabular) and time-series data.
Source codeMaturity : Maintained | Categories : Python Stack, Processing Chains (pipelines) | License : | Producer : Pandas Developers
Overview
Pandas is one of the most popular and powerful open-source libraries in Python for data manipulation and analysis. It provides easy-to-use structures such as DataFrames and Series for organizing and analyzing tabular data. With its extensive functionality, Pandas simplifies working with large datasets, reshaping, merging, filtering, and performing various operations with ease.
Key Features:
- DataFrames and Series: Flexible data structures for handling both labeled and relational data.
- Data Manipulation: Powerful data wrangling tools for filtering, transforming, merging, and reshaping data.
- Time Series Support: Efficient tools for handling and analyzing time-series data, including resampling and rolling window operations.
- File I/O: Read and write data from various formats, including CSV, Excel, SQL databases, and more.
- Integration: Works seamlessly with other libraries in the Python data stack like NumPy, SciPy, and Matplotlib.
For more details and example , refer to the Pandas documentation.
Installation
Pandas can be installed using pip or conda:
Using pip:
pip install pandas