Summary: in this tutorial, you’ll understand what Pandas is, what it can do and why you should start learning pandas today.
Pandas is a Python library designed for data manipulation and analysis. Pandas strength lies in its ability to deal with large amounts of tabular and sequential data in a convenient and efficient manner.
1) Data manipulation
Pandas can take in data from various formats, including CSV, JSON, HTML, XLS, XLSX, SQL, Parquet,etc and process them efficiently, thanks to NumPy – the scientific computing library that powers most of its functionality.
2) Data analysis
DataFrame – the two-dimensional data structure of Pandas allows it to perform various data cleaning and data wrangling operations.
By leveraging sophisticated indexing techniques, pandas is able to easily carry out many complex data operations such as reshaping, slicing, aggregations, and subset selection.
- Pandas is free and open source.
- Pandas has a big community revolving around it. Most of the common questions have been answered somewhere, by someone, you just have to find it.
- Pandas API is robust, allows for quick yet efficient data manipulation without having to dig deep into the mechanics of the library.
- DataFrame concepts are easy to understand and practical.
- Pandas has been battle-tested since 2008.
- Pandas is efficient. It has been built in such a way that it can handle large datasets easily.
- Pandas supports a large number of file formats, such as CSV, TSV, JSON, Excel, etc.
- Pandas is well integrated with the existing data science community.
History of Pandas
The first version of Pandas was released back in 2008 by Wes McKinney, a MIT grad with heavy quantitative finance experience. He was tired of doing simple tasks like reading CSV at his job and wanted to find something better. After unsuccessful attempts with Excel and R, he fell in love with Python – a beautiful, easy to learn programming language. He then realized the Python world at the time lacks the tools to deal with data manipulation tasks. After some time, Pandas was born.
With the release of other popular Python libraries which focuses on data visuallization like Matplotlib, followed by machine learning libraries such as Scikit-Learn and robust Python IDE like Jupyter Notebooks, pandas eventually became the go-to tool when it comes to data manipulation and analysis.
Pandas online resources
- Pandas homepage (pandas.pydata.org)
- Pandas documentation (web version) (pydata.org)
- Pandas documentation (PDF)
- Kaggle’s interactive Learn Pandas Tutorials
- Pandas is a free and open source data manipulation and data analysis library for Python.
- Pandas is now the essential tool for data scientists and business analysts.