Reshaping

Lesson in the Python for Data Analysis Roadmap · Stage 7: Reading Local Files

Last updated 14 September 2026

What is Reshaping?

Reshaping transforms the structure of a DataFrame without changing its data. pivot() and pivot_table() convert long-format data to wide format. melt() does the reverse, converting wide to long. stack() and unstack() move index levels to columns or vice versa. Reshaping is often needed to prepare data for specific visualizations or models.

Study this in the interactive course See the whole Python for Data Analysis roadmap

Free resources to learn Reshaping

Official docsReshaping and pivot tables
ArticleReshaping a Pandas Dataframe: Long-to-Wide and Vice Versa
VideoPandas - Reshape Dataframe

Reshaping: common questions

Can I learn Reshaping in Hindi?

This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Reshaping in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.

Is this Reshaping tutorial for beginners?

It is lesson 58 of 112 in the free Python for Data Analysis roadmap, in stage 7, Reading Local Files. If you are new to Python for Data Analysis, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.