Pandas is an open source, data analysis library for the Python programming language. It was created in 2008 by Wes McKinney and is now maintained by a community of developers from multiple organizations. Pandas provides flexible and powerful data manipulation capabilities, allowing users to efficiently extract, store, and process data from different sources in order to answer complex questions.
Pandas offers a range of features that are designed to make it easier to work with data. These features include data structures and operations for manipulating numerical tables and time series as well as tools for reading and writing data between in-memory data structures and different file types. It also offers a variety of built-in and customisable visualisation tools for exploring and presenting data.
Pandas is widely used in a range of industries, including finance, marketing, analytics, and data science. Companies such as Google, Facebook, and IBM all use Pandas in their data pipelines. Other notable users of Pandas include the Boston Consulting Group, Microsoft, The New York Times, and many more.
The majority of Pandas users are data analysists or data scientists who use Pandas to manipulate, clean, and analyse structured datasets. It is also used for workload automation, ETL (Extract, Transform, Load), and general data analysis tasks.
Pandas is an extremely powerful and popular data analysis library that offers a wide range of features to make managing and analysing data easier. This makes it a powerful asset in the data science community.
