Software Alternatives, Accelerators & Startups

Python VS Google Sheets

Compare Python VS Google Sheets 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.

Python logo Python

Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.

Google Sheets logo Google Sheets

Synchronizing, online-based word processor, part of Google Drive.
  • Python Landing page
    Landing page //
    2021-10-17

  • Google Sheets Landing page
    Landing page //
    2022-01-17

Python features and specs

  • Easy to Learn
    Python syntax is clear and readable, which makes it an excellent choice for beginners and allows for quick learning and prototyping.
  • Versatile
    Python can be used for web development, data analytics, artificial intelligence, machine learning, automation, and more, making it a highly versatile programming language.
  • Large Standard Library
    Python comes with a comprehensive standard library that includes modules and packages for various tasks, reducing the need to write code from scratch.
  • Strong Community Support
    Python has a large and active community, which means a wealth of third-party packages, tutorials, and documentation is available for assistance.
  • Cross-Platform Compatibility
    Python is compatible with major operating systems like Windows, macOS, and Linux, allowing for easy development and deployment across different platforms.
  • Good for Rapid Development
    The high-level nature of Python allows for quick development cycles and fast iteration, which is ideal for startups and prototyping.

Possible disadvantages of Python

  • Performance Limitations
    Python is generally slower than compiled languages like C or Java because it is an interpreted language, which can be a drawback for performance-critical applications.
  • Global Interpreter Lock (GIL)
    The GIL in CPython, the most used Python interpreter, prevents multiple native threads from executing Python bytecodes at once, limiting multi-threading capabilities.
  • Memory Consumption
    Python can be more memory-intensive compared to some other languages, which might be a concern for applications with tight memory constraints.
  • Mobile Development
    Python is not a primary choice for mobile app development, where languages like Java, Swift, or Kotlin are more commonly used.
  • Runtime Errors
    Being a dynamically typed language, Python code can sometimes lead to runtime errors that would be caught at compile-time in statically typed languages.
  • Dependency Management
    Managing dependencies in Python projects can sometimes be complex and cumbersome, especially when dealing with conflicting versions of libraries.

Google Sheets features and specs

  • Accessibility
    Google Sheets is cloud-based, allowing users to access their documents from anywhere with an internet connection, on any device.
  • Collaboration
    Multiple users can work on the same spreadsheet simultaneously, with real-time updates and the ability to see each other's changes.
  • Integrations
    Easily integrates with other Google Workspace apps like Google Drive, Docs, and Forms, as well as third-party services.
  • Cost
    Basic features are available for free, with additional advanced features accessible through affordable Google Workspace subscriptions.
  • Functionality
    Offers a wide range of built-in functions and formulas, supporting complex calculations and data analysis.
  • Version History
    Keeps a detailed version history of every change made, allowing users to revert to previous versions as needed.

Possible disadvantages of Google Sheets

  • Feature Limitations
    Lacks some advanced features found in more robust spreadsheet applications like Microsoft Excel, such as certain data visualization and pivot table capabilities.
  • Data Limitations
    Less efficient at handling very large datasets, which can slow down user experience and affect performance.
  • Internet Dependence
    Requires a stable internet connection for optimal use, though offline capabilities are available but limited.
  • Privacy Concerns
    Storing sensitive data on cloud-based services can raise privacy and security concerns for some users.
  • Customization
    Limited customization options compared to some other spreadsheet software, particularly in terms of advanced scripting and macro functions.

Python videos

Creator of Python Programming Language, Guido van Rossum | Oxford Union

Google Sheets videos

Excel Online vs. Google Sheets

More videos:

  • Tutorial - Google Sheets Quickstart - Easy Tutorial 2018
  • Review - Airtable vs. Google Sheets

Category Popularity

0-100% (relative to Python and Google Sheets)
Programming Language
100 100%
0% 0
Spreadsheets
0 0%
100% 100
OOP
100 100%
0% 0
Office Suites
0 0%
100% 100

User comments

Share your experience with using Python and Google Sheets. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Python and Google Sheets

Python Reviews

Pine Script Alternatives: A Comprehensive Guide to Trading Indicator Languages
Technical analysis in trading has come a long way, with various programming languages emerging to support traders in developing custom indicators. While Pine Script has been a popular choice for many, alternatives like Indie, ThinkScript, NinjaScript, MetaQuotes Language (MQL), and even general-purpose languages like Python and C++ are gaining traction. Letโ€™s explore these...
Source: medium.com
Top 5 Most Liked and Hated Programming Languages of 2022
No wonder Python is one of the easiest programming languages to work upon. This general-purpose programming language finds immense usage in the field of web development, machine learning applications, as well as cutting-edge technology in the software industry. The fact that Python is used by major tech giants such as Amazon, Facebook, Google, etc. is good enough proof as to...
Top 10 Rust Alternatives
This programming langue is typed statically and operates on a complied system. It works based on several computing languages Python, Ada, and Modula.
15 data science tools to consider using in 2021
Python is the most widely used programming language for data science and machine learning and one of the most popular languages overall. The Python open source project's website describes it as "an interpreted, object-oriented, high-level programming language with dynamic semantics," as well as built-in data structures and dynamic typing and binding capabilities. The site...
The 10 Best Programming Languages to Learn Today
Python's variety of applications make it a powerful and versatile language for different use cases. Python-based web development frameworks like Django and Flask are gaining popularity fast. It's also equipped with quality machine learning and data analysis tools like Scikit-learn and Pandas.
Source: ict.gov.ge

Google Sheets Reviews

HIGHLIGHTING DUPLICATES: GOOGLE SHEETS VS FLOOKUP
Highlighting your data is a very good way to get an overview of what your data looks like before performing destructive operations like removing duplicates or using that data for any other purpose. Unfortunately, at the time of writing this article, Google Sheets does not provide a predefined way of highlighting duplicates. However, with custom formulas and conditional...

Social recommendations and mentions

Based on our record, Python seems to be more popular. It has been mentiond 299 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.

Python mentions (299)

  • How to Build a Dependency Map of a Legacy Codebase Using AI Tools
    137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / 2 months ago
  • How to Prepare a Legacy Codebase for AI-Assisted Refactoring
    For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / 2 months ago
  • Async Web Scraping in Python: asyncio + aiohttp + httpx (Complete 2026 Guide)
    Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ€” no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 4 months ago
  • Don't Be Afraid of Git: A Beginner's Guide to Saving and Sharing
    **_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โ€œSave this dataโ€ - โ€œGet this dataโ€ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
  • Asyncio: Interview Questions and Practice Problems
    Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago
View more

Google Sheets mentions (0)

We have not tracked any mentions of Google Sheets yet. Tracking of Google Sheets recommendations started around Mar 2021.

What are some alternatives?

When comparing Python and Google Sheets, you can also consider the following products

JavaScript - Lightweight, interpreted, object-oriented language with first-class functions

Microsoft Office Excel - Microsoft Office Excel is a commercial spreadsheet application.

Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible

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

C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation

Apple Numbers - Numbers lets you build beautiful spreadsheets on a Mac, iPad, or iPhone โ€” or on a PC using iWork for iCloud. And itโ€™s compatible with Apple Pencil.