Pandas makes it easy to quickly load, manipulate, align, merge, and even visualize data tables directly in Python.

Pandas and the DataFrame Pandas is a BSD-licensed open source library that provides high-performance, easy-to-use data structures and data analysis tools for Python.

Still using Excel for your data analysis? Learn how to leverage Python so you can work with larger datasets and automate repetitive tasks.

Introduction to Python for Data Analysis Recall that R is a statistical programming language—a language designed to do things like t -tests, regression, and so on. The core of R was developed during ...

If you do not have either installed, guidance will be given in Chapter 2, Up and Running with pandas, regarding installing pandas on installing both on Windows, OSX, and Ubuntu systems. For those not ...

DataPrep.EDA is the fastest and the easiest EDA (Exploratory Data Analysis) tool in Python. It allows you to understand a Pandas/Dask DataFrame with a few lines of code in seconds. You can create a ...

You don't need to be a data scientist to use Pandas for some basic analysis. Traditionally, people who program in Python use the data types that come with the language, such as integers, strings, ...

Data manipulation and transformation Let’s understand how Python, especially using the Pandas library, can replicate and surpass Excel’s capabilities. With Excel, you can enter data in cells ...

Stefanie Molin's new book, “Hands-On Data Analysis with Pandas" is about using the powerful pandas library to get started with machine learning in Python.