Data Tidying and Importing with R

This Duke course addresses the preparation work that comes before a chart or model. It moves through tidy table structure, recoding and importing, then introduces web collection and programming. Its roughly thirteen-hour scope suits someone ready to make inconsistent data usable.

What you will learn

• Reshape observations between long and wide table formats.
• Recode values and inspect the types of imported columns.
• Join datasets and collect structured information from a web source.

Who this suits

R learners who want practice preparing real datasets for analysis.

Before you enroll

The provider classifies this as beginner but leaves prerequisites unspecified. Basic familiarity with RStudio and tabular data will make the preparation exercises easier to follow.

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

Combine two public CSV files with inconsistent identifiers. Record type changes, unmatched rows and the effect of your chosen join on the final row count.

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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