Massaging Data Using Pandas
When we talk about managing data, it is quite inevitable to see data presented in tables. With column header, and sometimes with names for rows, it makes understanding data easier. In fact, it often happens that we see data of different types staying together. For example, we have quantity as numbers and name as strings in a table of ingredients for a recipe. In Python, we have the pandas library to help us handle tabular data.
After finishing this tutorial, you will learn:
- What the pandas library provides
- What is a DataFrame and a Series in pandas
- How to manipulate DataFrame and Series beyond the trivial array operations
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