How to Sort a DataFrame by Values in a Column

In this short how-to article, we will learn how to sort the rows of a DataFrame by the value in a column in Pandas and PySpark.

Pandas

The sort_values function can be used for this task. We just need to give it the column name.

df.sort_values(by="Age")

By default, the index of the rows prior to sorting are kept, which is not an ideal situation. We can change this behavior by using the ignore_index parameter.

df.sort_values(by="Age", ignore_index=True)

By default, the values are sorted in ascending order and this can be changed using the ascending parameter.

df.sort_values(by="Age", ignore_index=True, ascending=False)

PySpark

The orderBy function can be used for this task. The syntax is similar to that of the sort_values function of Pandas.

df.orderBy("number")

The orderBy also sorts rows in ascending order. We can use the ascending parameter to sort in descending order.

df.orderBy("number", ascending=False)

This question is also being asked as:

• How to sort Pandas DataFrame by column?

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