How to Iterate over Dataframe Groups in Python-Pandas?
In this article, we’ll see how we can iterate over the groups in which a dataframe is divided. So, let’s see different ways to do this task.
First, Let’s create a dataframe:
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Method 1: Using Dataframe.groupby().
This function is used to split the data into groups based on some criteria.
Example: we’ll simply iterate over all the groups created.
In above example, we have grouped on the basis of column “X”. As there are two different values under column “X”, so our dataframe will be divided into 2 groups. Then our for loop will run 2 times as the number groups are 2. “name” represents the group name and “group” represents the actual grouped dataframe.
Method 2: Using Dataframe.groupby() and Groupby_object.groups.keys() together.
Groupby_object.groups.keys() method will return the keys of the groups.
Example: we’ll iterate over the keys.
In above example, we’ll use the function groups.get_group() to get all the groups. First we’ll get all the keys of the group and then iterate through that and then calling get_group() method for each key. get_group() method will return group corresponding to the key.