Pandas library in python: Pandas is a Python

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. 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 ... 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. User Guide # The User Guide covers all of pandas by topic area. Each of the subsections introduces a topic (such as “working with missing data”), and discusses how pandas approaches the problem, with many examples throughout. Users brand-new to pandas should start with 10 minutes to pandas . For a high level summary of the pandas fundamentals, see Intro to data structures and Essential basic functionality. Further information on any specific method can be obtained in the API reference ...