Connect with us
Apply Now

Tech + Startups

What Is Better Than Pandas DataFrame?


DataFrame is a data structure that is two-dimensional and aligned in a tabular manner in columns and rows. It is somewhat similar to a spreadsheet. It is ideal for data analysts and data miners to work in a modern way as it is flexible enough to store and work on data in a unique way. This allows you to store many datasets in a DataFrame. When it comes to Panda DataFrame, there are infinite options to declare, store, add, edit, delete, etc. If you are using Panda DataFrame and want to look for an alternative, or are a beginner planning to create a DataFrame, but other than using Pandas. Both of you must be looking for a better substitute than Pandas.

Beginners and learners often find themselves in sheer confusion when it comes to finding what is better than Pandas Dataframe.  It happens to everyone, including me. I found myself in utter confusion as to whether use the pandas dataframe or use any other alternative. After thorough research, I learned what can be used. Beginners should need to have enough information to decide which one to choose to create a dataframe; pandas or PySpark.

What is Panda?

It is an amazing Python library that is most frequently used for working with structured tabular data ideal for analysis. This open-source library is widely used for machine learning, data analysis, data science projects, etc. in order to create a dataframe, Pandas has the ability to load the data by reading JSON, CSV, SQL, and other formats.

Pandas dataframe consists of rows and columns. Distributed processing is not supported by Pandas. Thus, resources need to be increased when you want to support growing data. In that case, you require additional horsepower to tackle increasing data.

Dataframe in Panda is not lazy but mutable with each column having statistical functions applied by default. Pandas is imported using Pandas as pd to be passed with import.

If you don’t want to use Pandas Dataframe, then the best option is to use PySpark.

What is PySpark?

PySpark has the capability to run operations on multiple machines, whereas Pandas run on a single machine. When you want to work on machine learning applications for dealing with large datasets is the motive, then PySpark is just the right and better alternative to using. It is 100 times faster than Pandas. It is a Spark library to execute Python applications, which is also written in Python. To run applications parallelly, it uses Apache Spark. To do that, you can simply run apps on the distributed cluster on single or multiple nodes.

With PySpark, you can efficiently and effectively process data in a distributed manner as it has a distributed processing engine. Moreover, it is a popular in-memory, and general-purpose library that makes creating and working on dataframes easier. SpySpark features built-in optimization for using DataFrames. It is fault-tolerant, immutable, and offers lazy evaluation.

How to decide between PySpark and Pandas

Now that the concept of both is cleared. Let’s check out when you need to prefer PySpark over Pandas

  • If you have large data that seems to be growing and you want to boost the processing time.
  • You need fault-tolerant
  • Stream data and real-time processing
  • If you need to have capabilities of machine learning
  • Compatibility with ANSI SQL
  • Choose different languages as sparks also support Scala, R, and Java along with Python.


I have discussed the difference between Pandas DataFrame and PySpark DataFrame. Both are good for DataFrames. I leave the decision to you to decide which one is better for you and your project’s needs. I answered what is better than Pandas DataFrame, so if you want to use another one, then PySpark is the better option.

Continue Reading

Copyright © 2022 Disrupt ™ Magazine is a Minority Owned Privately Held Company - Disrupt ™ was founder by Puerto Rican serial entrepreneur and philanthropist Tony Delgado who is on a mission to transform Latin America using the power of education and entrepreneurship.

Disrupt ™ Magazine
151 Calle San Francisco
Suite 200
San Juan, Puerto Rico, 00901

Opinions expressed by Disrupt Contributors are their own. Disrupt Magazine invites voices from many diverse walks of life to share their perspectives on our contributor platform. We are big believers in freedom of speech and while we do enforce our community guidelines, we do not actively censor stories on our platform because we want to give our contributors the freedom to express their opinions. Articles are not commissioned by our editorial team, and opinions expressed by our community contributors do not reflect the opinions of Disrupt or its employees.
We are committed to fighting the spread of misinformation online so if you feel an article on our platform goes against our community guidelines or contains false information, we do encourage you to report it. We need your help to fight the spread of misinformation. For more information please visit our Contributor Guidelines available here.

Disrupt ™ is the voice of latino entrepreneurs around the world. We are part of a movement to increase diversity in the technology industry and we are focused on using entrepreneurship to grow new economies in underserved communities both here in Puerto Rico and throughout Latin America. We enable millennials to become what they want to become in life by learning new skills and leveraging the power of the digital economy. We are living proof that all you need to succeed in this new economy is a landing page and a dream. Disrupt tells the stories of the world top entrepreneurs, developers, creators, and digital marketers and help empower them to teach others the skills they used to grow their careers, chase their passions and create financial freedom for themselves, their families, and their lives, all while living out their true purpose. We recognize the fact that most young people are opting to skip college in exchange for entrepreneurship and real-life experience. Disrupt Magazine was designed to give the world a taste of that.