Month: December 2020

This article is part of a series of practical guides for using the Python data processing library pandas. To see view all the available parts, click here.

For many users starting out with pandas, a common and frustrating warning that pops up sooner or later is the following:

SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.

Try using .loc[row_indexer,col_indexer] = value instead

To the uninitiated, it can be hard to know what it means or if it even matters. In this guide, we’ll walk through what the warning means, why you are seeing it, and what you can do to avoid it.

This article is part of a series of practical guides for using the Python data processing library pandas. To see view all the available parts, click here.

In other sections in this series, we’ve looked at how we can use booleans (a value that is either True or False) in pandas. Specifically, we’ve looked at how a list or array of booleans can be used to filter a DataFrame. In those examples we generated lists of booleans using simple comparisons like “are the values in the fixed acidity column > 12?” However, simple comparisons like this are only one of many ways we can create booleans. In this guide we are going to look at a range of methods that allow us to do more complex comparisons, while also making our code more concise and easier to understand.

This article is part of a series of practical guides for using the Python data processing library pandas. To see view all the available parts, click here.

One of the most common ways you will interact with a pandas DataFrame is by selecting different combinations of columns and rows. This can be done using the numerical positions of columns and rows in the DataFrame, column names and row indices, or by filtering the rows by applying some criteria to the data in the DataFrame. All of these options (and combinations of them) are available, so let’s dig in!