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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.
The sort_values function can be used for this task. We just need to give it the column name.
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.
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)
The orderBy function can be used for this task. The syntax is similar to that of the sort_values function of Pandas.
The orderBy also sorts rows in ascending order. We can use the ascending parameter to sort in descending order.