How to Update Rows and Columns in Pandas and Modify Data Within DataFrames

In this video, we'll be going over the different ways you can update rows and columns in a Pandas DataFrame. We'll start with the basics of updating individual cells and then move on to more advanced techniques like updating multiple cells at once and using conditional statements.
First, we'll go over how to update a single cell in a DataFrame. To do this, we'll use the at method, which allows us to access a cell by its index and column label. We'll also show you how to update a single cell using the iat method, which allows us to access a cell by its integer index.
Next, we'll cover how to update multiple cells at once. We'll show you how to use the loc method to update rows and columns using boolean indexing and how to use the iloc method to update cells by their integer index.
After that, we'll demonstrate how to update rows and columns using conditional statements. We'll use the where method to update cells that meet certain conditions and the mask method to update cells that do not meet certain conditions.
Finally, we'll show you how to update a column by reassigning the values of a DataFrame and how to rename columns by using the rename method.
By the end of this video, you'll have a solid understanding of the different ways you can update rows and columns in a Pandas DataFrame and be able to modify data within DataFrames with confidence.
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pandas, dataframe, update, rows, columns, modify, data, python, tutorial, programming, coding, data analysis, data manipulation, at, iat, loc, iloc, where, mask, rename, data science, coding tutorial
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[@dorixon5410]

this was really useful for a project im working on at university! your explanation was extremely helpful and clear, thank you so much!

[@Softlinks]

Thank you for the kind words! I'm happy to hear the explanation was clear and helpful for your project.