Software Alternatives, Accelerators & Startups

Pandas VS Rows

Compare Pandas VS Rows and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Rows logo Rows

The spreadsheet where teams work faster
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Rows Landing page
    Landing page //
    2023-02-23

Slick design. Built-in integrations. Revolutionary sharing. Rows reinvented spreadsheets so teams do more, crazy fast.

Rows

Website
rows.com
$ Details
-
Release Date
2016 January
Startup details
Country
Germany
State
Berlin
City
Berlin
Founder(s)
Humberto Ayres Pereira
Employees
10 - 19

Pandas features and specs

  • Data Wrangling
    Pandas offers robust tools for manipulating, cleaning, and transforming data, making it easier to prepare data for analysis.
  • Flexible Data Structures
    Pandas provides two primary data structures: Series and DataFrame, which are flexible and offer powerful capabilities for handling various types of datasets.
  • Integration with Other Libraries
    Pandas integrates seamlessly with other Python libraries such as NumPy, Matplotlib, and SciPy, facilitating comprehensive data analysis workflows.
  • Performance with Data Size
    For data sizes that fit into memory, Pandas performs excellently with operations and computations being highly optimized.
  • Rich Feature Set
    Pandas provides a wide array of functionalities, including but not limited to group-by operations, merging and joining data sets, time-series functionality, and input/output tools.
  • Community and Documentation
    Pandas has a strong community and extensive documentation, offering a wealth of tutorials, examples, and support for new and experienced users alike.

Possible disadvantages of Pandas

  • Memory Consumption
    Pandas can become memory inefficient with very large datasets because it relies heavily on in-memory operations.
  • Single-threaded
    Many Pandas operations are single-threaded, which can lead to performance bottlenecks when handling very large datasets.
  • Steep Learning Curve
    For users who are new to data analysis or Pandas, there can be a steep learning curve due to its extensive capabilities and complex syntax at times.
  • Less Suitable for Real-time Analytics
    Pandas is not designed for real-time analytics and is better suited for batch processing due to its in-memory operations and single-threaded nature.
  • Error Handling
    Error messages in Pandas can sometimes be cryptic and hard to interpret, making debugging a challenge for users.

Rows features and specs

  • User-Friendly Interface
    Rows provides an intuitive and easy-to-use spreadsheet interface that is accessible for users of all skill levels, from beginners to advanced.
  • Integration Capabilities
    Supports a variety of integrations with other software services and APIs, allowing for seamless data import and export.
  • Real-Time Collaboration
    Allows multiple users to work on the same spreadsheet simultaneously, enhancing team productivity and ensuring everyone has the latest information.
  • Customization and Automation
    Offers powerful automation features and the ability to write custom scripts, which can save time and reduce manual errors.
  • Template Library
    Provides a rich library of pre-designed templates that can help users quickly get started on common business tasks.

Possible disadvantages of Rows

  • Learning Curve
    While user-friendly, more advanced features and scripting capabilities may require a significant learning curve for new users.
  • Limited Offline Functionality
    Primarily a cloud-based tool, which means it relies heavily on internet connection and offers limited offline functionality.
  • Pricing
    The cost of premium features or larger scale deployments can be high, which may not be affordable for small businesses or individual users.
  • Dependency on Integrations
    Heavily reliant on third-party integrations, which means any issues or changes in connected services can impact Rows' functionality.
  • Security Concerns
    As with any cloud-based service, there may be concerns about data security and privacy, especially for sensitive or confidential information.

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Rows videos

Welcome to Rows

More videos:

  • Review - The Truth about Barbell Rows (AVOID MISTAKES!)
  • Review - 9/21/21 bentover rows review

Category Popularity

0-100% (relative to Pandas and Rows)
Data Science And Machine Learning
Spreadsheets
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Productivity
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Pandas and Rows

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Rows Reviews

The best no-code tools for sales teams
You can bring your data to life. With Rows, you can jazz up your spreadsheets with slick charts, images, audio and even interactive features such as buttons and checkboxes. What’s more, you can share your spreadsheets with colleagues and clients in the form of interactive dashboards and websites.
Source: www.nocode.tech

Social recommendations and mentions

Based on our record, Pandas should be more popular than Rows. It has been mentiond 219 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Pandas mentions (219)

  • Top Programming Languages for AI Development in 2025
    Libraries for data science and deep learning that are always changing. - Source: dev.to / 7 days ago
  • How to import sample data into a Python notebook on watsonx.ai and other questions…
    # Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 23 days ago
  • How I Hacked Uber’s Hidden API to Download 4379 Rides
    As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 27 days ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • Sample Super Store Analysis Using Python & Pandas
    This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 8 months ago
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Rows mentions (24)

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What are some alternatives?

When comparing Pandas and Rows, you can also consider the following products

NumPy - NumPy is the fundamental package for scientific computing with Python

Airtable - Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

NocoDB - The Open Source Airtable alternative

OpenCV - OpenCV is the world's biggest computer vision library

Baserow - Open source no-code database and Airtable alternative. Create your own online database without technical experience. Performant with high volumes of data, can be self hosted and supports plugins