Sorting Rows in Python
pandas Sort: Your Guide to Sorting Data in Python
Learning pandas sort methods is a great way to start with or practice doing basic data analysis using Python. Most commonly, data analysis is done with spreadsheets, SQL, or pandas. One of the great things about using pandas is that it can handle a large amount of data and offers highly performant data manipulation capabilities.
In this tutorial, you’ll learn how to use .sort_values()
and .sort_index()
, which will enable you to sort data efficiently in a DataFrame.
By the end of this tutorial, you’ll know how to:
- Sort a pandas DataFrame by the values of one or more columns
- Use the
ascending
parameter to change the sort order - Sort a DataFrame by its
index
using.sort_index()
- Organize missing data while sorting values
- Sort a DataFrame in place using
inplace
set toTrue
To follow along with this tutorial, you’ll need a basic understanding of pandas DataFrames and some familiarity with reading in data from files.
Getting Started With Pandas Sort Methods
As a quick reminder, a DataFrame is a two-dimensional labeled data structure with columns of potentially different types. It’s similar to a spreadsheet or SQL table, but with more powerful indexing capabilities.
Here are the main steps we’ll cover in this tutorial:
- Preparing the Dataset
- Getting Familiar With
.sort_values()
- Getting Familiar With
.sort_index()
Preparing the Dataset
In this tutorial, we’ll be using a sample dataset to demonstrate the various sorting methods. The dataset contains information about students, including their names, ages, and grades.
The output will be:
This is our starting DataFrame. It includes four columns: Name, Age, and Grade. We’ll use this dataset for all the examples in this tutorial.
Getting Familiar With .sort_values()
The .sort_values()
method is used to sort a DataFrame by the values of one or more columns. By default, the sort is performed in ascending order.
Let’s start by sorting the DataFrame by the Age column in ascending order:
The output will be:
As you can see, the DataFrame is now sorted based on the values in the Age column. The rows are rearranged in ascending order of Age.
To sort the DataFrame in descending order, you can set the ascending
parameter to False
:
The output will be:
Now the DataFrame is sorted in descending order based on the values in the Age column.
Getting Familiar With .sort_index()
The .sort_index()
method is used to sort a DataFrame by its index. By default, the sort is performed in ascending order.
Let’s sort the DataFrame by the index in ascending order:
The output will be the same as the original DataFrame:
To sort the DataFrame by the index in descending order, you can set the ascending
parameter to False
:
The output will be:
Now the DataFrame is sorted by the index in descending order.
Conclusion
In this tutorial, you learned how to use .sort_values()
and .sort_index()
to sort data in a pandas DataFrame. You now have the knowledge and tools to sort your data efficiently and organize it in a way that suits your needs. Sorting data is an essential step in the data analysis process, and pandas provides powerful methods to make this process easy and intuitive. Keep practicing with different datasets to enhance your understanding and proficiency in sorting data with pandas.