4. Sort by Multiple Columns

In this article, we’ll be using the flights dataset, which records the monthly passenger...

Apparently, the sorted data isn’t something that we expect — the months are not in the desired order. To make this happen, we can take advantage of the sort_method taking a key parameter, to which we can pass a custom function for sorting, just like Python’s built-in

It’s important to remember that your datasets can always contain NANs. Unless you’ve examined your data quality and know that there are no NANs, you should pay attention to that. When we sort values, these NANs are placed behind all the other valid values, by default. If we want to change this de...

The above sorting using the key parameter can be confusing to some people. Is there a cleaner way? Pandas is arguably the most versatile library for data processing, and you can expect that there is something neat to solve this relatively common problem — converting these lexicograph...

In the previous sorting, you may notice that the index goes with each sorted row, which puzzles me sometimes, when I want the sorted DataFrame has an ordered index. In this case, you can either reset the index after sorting, or simply take advantage of the ignore_index parameter, as ...

In the previous sorting, one thing you may have notices is that the sort_values method will create a new DataFrame object, as shown below.

To avoid creating a new DataFrame, you can request the sorting to be done inplace by setting the inplace paramet...