Basic data structures in pandas # Pandas provides two types of classes for handling data: Series: a one-dimensional labeled array holding data of any type such as integers, strings, Python objects etc. DataFrame: a two-dimensional data structure that holds data like a two-dimension array or a table with rows and columns. Object creation # See the Intro to data structures section. Creating a Series by passing a list of values, letting pandas create a default RangeIndex. To install pandas , please reference the installation page from the pandas documentation. Tutorials You can learn more about pandas in the tutorials, and more about JupyterLab in the JupyterLab documentation. Books The book we recommend to learn pandas is Python for Data Analysis, by Wes McKinney, creator of pandas . Videos Cheat sheet pandas ... Pandas (stands for Python Data Analysis) is an open-source software library designed for data manipulation and analysis. Revolves around two primary Data structures: Series (1D) and DataFrame (2D) Built on top of NumPy, efficiently manages large datasets, offering tools for data cleaning, transformation, and analysis. Tools for working with time series data, including date range generation and frequency conversion. For example, we can convert date or time columns into pandas’ datetime type ... pandas is a Python library for data structures and analysis. Learn how to get started, use the API, and contribute to the project with the documentation guides.
