Foundations of Data Analysis with Pandas and Python

Packt starts with the working environment before introducing Python and pandas Series. Setup, basic programming and initial data operations share a roughly ten-hour syllabus. It is a starting point for learners who need the programming foundation as well as the analysis library.

What you will learn

• Run Python code in a Jupyter environment.
• Use basic functions and data structures in a notebook.
• Import, inspect and transform a pandas Series.

Who this suits

New data-analysis learners who want an introduction to Python and pandas together.

Before you enroll

The provider describes this as beginner and allows learners without programming experience. Continue with a DataFrame-focused course after the initial Series exercises.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Tool subscriptions, model API usage and cloud services may cost extra.

Put it into practice

Load a public single-column dataset, check its missing values and compare its original and sorted forms. Explain which operation changes the observations and which changes their order.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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