What is Pandas, how to install and use

Jupyter Notebook Examples

Project on GitHub with example Jupyter Notebooks for each of the sections in this guide.

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Effective Pandas 2: Opinionated Patterns for Data Manipulation by Matt Harrison

I recommend this book if you want to learn Pandas in much more detail and see what else Pandas has to offer that is out of scope of this quick start guide.

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What is Pandas?

Pandas is a powerful, open-source Python library for data manipulation and analysis. It provides flexible, high-performance data structures like:

• Series: A one-dimensional labeled array (like a list with labels).
• DataFrame: A two-dimensional table of data with rows and columns (like an Excel sheet or SQL table).

Pandas makes it easy to load, clean, analyse, and visualise data, and it’s widely used in data science, machine learning, and financial analysis.

Key Features

• Fast and efficient handling of tabular and time-series data.
• Tools for filtering, grouping, and aggregating data.
• Handling missing data and data type conversions.
• Reading/writing data from CSV, Excel, SQL, JSON, and more.
• Integration with NumPy, Matplotlib, and scikit-learn.

Installation

After installation, the Pandas module can be included by:

By convention, it’s always imported as pd.