How to count unique values in a Pandas Groupby object?

How to List values for each Pandas group?

Last Updated : 20 Aug, 2020

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:

Dataframe

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:

Group into list

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:

Group into list

How to count unique values in a Pandas Groupby object?

P

parasmadan15

Improve

Article Tags :

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

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

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

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

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

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

How to do groupby on a multiindex in Pandas?

In this article, we will be showing how to use the groupby on a Multiindex Dataframe in Pandas. In Data science when we are performing exploratory data analysis, we often use groupby to group the data of one column based on the other column. So, we are able to analyze how the data of one column is g

How to reset index after Groupby pandas?

In pandas, groupby() is used to group data based on specific criteria, allowing for operations like aggregation, transformation and filtering. However, after applying groupby(), the resulting DataFrame often has a MultiIndex or a non-sequential index, which can make data handling more complex. Reset

How to Count Observations by Group in Pandas?

In real data science projects, youâ€™ll be dealing with large amounts of data and trying things over and over, so for efficiency, we use the Groupby concept. Groupby concept is really important because its ability to aggregate data efficiently, both in performance and the amount code is magnificent. G

How to Calculate Quantiles by Group in Pandas?

In this article, how to calculate quantiles by group in Pandas using Python. There are many methods to calculate the quantile, but pandas provide groupby.quantile() function to find it in a simple few lines of code. This is the Method to use when the desired quantile falls between two points. Syntax