Trusted answers to developer questions
Trusted Answers to Developer Questions

Related Tags

python
communitycreator

What is grouping in Koalas?

Sarvech Qadir

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

Koalas is an important package to use when dealing with Data Science and big data in Python. Koalas implements the pandas DataFrame API on top of Apache Spark, making life easier for data scientists who are constantly interacting with big data.

pandas itself is widely used in the field of Data Science. The only difference between pandas and Spark is that pandas is a single node DataFrame implementation, whereas Spark is the standard for big data processing.

The Koalas package ensures that a user can immediately start working with Spark as long as they have experience working in pandas. Additionally, it provides a single codebase that works with both Spark and pandas.

Groupby in Koalas

A groupby operation involves some combination of splitting the object, applying a function, and combining the results. We can use this to group large amounts of data and perform operations on these groups.

groupby in Koalas is similar to groupby in pandas. groupby splits a DataFrame based on one feature to return a groupby object. Next, A function is applied on the groupby object, which groups large sets of data.

Click here for a detailed list of all the functions.

It is one of the most widely used techniques to group large amounts of data.

Code

Let’s work through a coding example:

groupby_koalas_df = ks.DataFrame({'Species': ['Reptiles', 'Reptiles',
                              'Mammals', 'Mammals'],
                   'Length': [2.5, 3.2, 1.5 , 1.75]},
                  columns=['Species', 'Length'])
# grouping the length by Species and applying the totalsum function.
>> groupby_koalas_df.groupby('Species').sum()

          Length
Species         
Mammals     3.25
Reptiles    5.70

# grouping the length by Species and applying the mean function.
>> groupby_koalas_df.groupby('Species').mean()

          Length
Species         
Mammals    1.625
Reptiles   2.850

RELATED TAGS

python
communitycreator

CONTRIBUTOR

Sarvech Qadir
Copyright ©2022 Educative, Inc. All rights reserved

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

Keep Exploring