In this article, we’ll see how we can display all the values of each group in which a dataframe is divided. The dataframe is first divided into groups using the DataFrame.groupby() method. Then we modify it such that each group contains the values in a list.
First, Let’s create a Dataframe:
Python3
# import pandas libraryimport pandas as pd # create a dataframedf = pd.DataFrame({'a': ['A', 'A', 'B', 'B', 'B', 'C', 'C', 'D'], 'b': [1, 2, 5, 3, 5, 4, 8, 6]})# show the dataframe df |
Output:
Method 1: Using DataFrame.groupby() and Series.apply() together.
Example: We’ll create lists of all values of each group and store it in new column called “listvalues”.
Python3
# import pandas libraryimport pandas as pd # create a dataframedf = pd.DataFrame({'a': ['A', 'A', 'B', 'B', 'B', 'C', 'C', 'D'], 'b': [1, 2, 5, 3, 5, 4, 8, 6]}) # convert values of each group# into a listgroups = df.groupby('a')['b'].apply(list) print(groups) # groups store in a new # column called listvaluesdf1 = groups.reset_index(name = 'listvalues')# show the dataframedf1 |
Output:
Method 2: Using DataFrame.groupby() and Series.agg().
Example: We use the lambda function inside the Series.agg() to convert the all values of a group to a list.
Python3
# import pandas libraryimport pandas as pd # create a dataframedf = pd.DataFrame( {'a': ['A', 'A', 'B', 'B', 'B', 'C', 'C', 'D'], 'b': [1, 2, 5, 3, 5, 4, 8, 6]} )# convert values of each group# into a listgroups = df.groupby('a').agg(lambda x: list(x)) print(groups) |
Output:
