Advanced Data Analysis and Visualization with Pandas

Packt focuses this course on tasks that surround an established pandas analysis: time handling, file exchange, plotting and configuration. The roughly five-hour outline is narrower than a general analytics program, making it useful when those workflow details are the immediate gap.

What you will learn

• Work with timestamps, date indexes and time offsets.
• Exchange DataFrames through CSV and Excel formats.
• Customize plots and pandas display behavior.

Who this suits

Python and pandas users with intermediate experience who want to refine their analysis workflow.

Before you enroll

The provider marks this advanced and expects existing pandas skills. Some file operations require additional packages; inspect installation instructions before starting.

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

Create a dated report from a public time series and export it to Excel. Re-import the file and check that dates, missing values and numerical precision were preserved.

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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