How to List values for each Pandas group? Last Updated : 20 Aug, 2020 Summarize Comments Improve Suggest changes Share Like Article Like Report 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 library import pandas as pd # create a dataframe df = 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 library import pandas as pd # create a dataframe df = 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 list groups = df.groupby('a')['b'].apply(list) print(groups) # groups store in a new # column called listvalues df1 = groups.reset_index(name = 'listvalues') # show the dataframe df1 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 library import pandas as pd # create a dataframe df = 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 list groups = df.groupby('a').agg(lambda x: list(x)) print(groups) Output: Comment More infoAdvertise with us Next Article How to Select Column Values to Display in Pandas Groupby P parasmadan15 Follow Improve Article Tags : Python Python-pandas Python pandas-groupby Practice Tags : python Similar Reads How to count unique values in a Pandas Groupby object? Here, we can count the unique values in Pandas groupby object using different methods. This article depicts how the count of unique values of some attribute in a data frame can be retrieved using Pandas. Method 1: Count unique values using nunique() The Pandas dataframe.nunique() function returns a 2 min read Pandas GroupBy - Count last value A groupby operation involves grouping large amounts of data and computing operations on these groups. It is generally involved in some combination of splitting the object, applying a function, and combining the results. In this article let us see how to get the count of the last value in the group u 5 min read How to Plot Value Counts in Pandas In this article, we'll learn how to plot value counts using provide, which can help us quickly understand the frequency distribution of values in a dataset.Table of ContentConcepts Related to Plotting Value CountsSteps to Plot Value Counts in Pandas1. Install Required Libraries2. Import Required Lib 3 min read How to Select Column Values to Display in Pandas Groupby Pandas is a powerful Python library used extensively in data analysis and manipulation. One of its most versatile and widely used functions is groupby, which allows users to group data based on specific criteria and perform various operations on these groups. This article will delve into the details 5 min read How to Get Cell Value from Pandas DataFrame? In this article, we will explore various methods to retrieve cell values from a Pandas DataFrame in Python. Pandas provides several functions to access specific cell values, either by label or by position.Get value from a cell of Dataframe using loc() functionThe .loc[] function in Pandas allows you 3 min read Pandas - Groupby value counts on the DataFrame Prerequisites: Pandas Pandas can be employed to count the frequency of each value in the data frame separately. Let's see how to Groupby values count on the pandas dataframe. To count Groupby values in the pandas dataframe we are going to use groupby() size() and unstack() method. Functions Used:gro 3 min read Like