What is Pandas?
Pandas is a powerful open-source Python library designed for working with data sets. It offers easy-to-use data structures and data analysis tools for tasks like cleaning, analyzing, exploring, and manipulating data.The name “Pandas” is derived from both “Panel Data” (a term used in econometrics) and “Python Data Analysis.” The library was created by Wes McKinney in 2008.
Why Use Pandas?
Pandas is essential for handling large and complex data. It allows data scientists and analysts to:
- Analyze and visualize trends
- Clean and structure messy datasets
- Draw meaningful insights from data
In the field of data science, where making sense of vast data is crucial, Pandas is an indispensable tool.
What Can Pandas Do?
Pandas provides quick answers to key questions in your dataset, such as:
- Is there a correlation between multiple columns?
- What is the average, maximum, or minimum value?
- Which data points are missing or incorrect?
It can also clean data by removing irrelevant rows or handling null (empty) values ensuring the data is consistent and useful.
What is Data Science?
Data Science is a field of computer science focused on storing, processing, and analyzing data to extract valuable information and insights.
Where is the Pandas Codebase?
Pandas is open-source and its source code is available on GitHub:
GitHub is a collaborative platform where developers can contribute to projects and maintain a shared codebase.
