Software Alternatives, Accelerators & Startups

Plausible.io VS Pandas

Compare Plausible.io VS Pandas and see what are their differences

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Plausible.io logo Plausible.io

Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure 🇪🇺

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
  • Plausible.io Landing page
    Landing page //
    2020-07-07

Plausible Analytics is not designed to be a clone of Google Analytics. It is meant as a simple-to-use replacement and a privacy-friendly alternative that can help many site owners.

  • It's quick, simple to use and understand with all the metrics displayed on one page. Doesn't track hundreds of metrics like Google Analytics does

  • Lightweight script of less than 1 KB so sites load fast. The script is 45 times smaller script than the Google Analytics one

  • Doesn't use cookies so there's no need to worry about cookie banners

  • Doesn't track personal data so it's compliant with GDPR out of the box and you don't need to worry about asking for data consent

  • It's open source with the code available on GitHub so you can even self host exactly the same product free as in beer

  • Unlike Google Analytics, the cloud product is not free as in beer because the business model is subscriptions rather than selling the data of your visitors. Plausible Analytics is bootstrapped without any external funding so the subscription fees help cover the costs and time spent on development.

  • Pandas Landing page
    Landing page //
    2023-05-12

Plausible.io

$ Details
paid Free Trial $9.0 / Monthly (10,000 pageviews)
Platforms
Web Browser Google Chrome Firefox Safari Wordpress
Release Date
2019 April

Plausible.io features and specs

  • Privacy-focused
    Plausible does not collect personal data about your visitors and is fully compliant with GDPR, CCPA, and PECR.
  • Simple to Use
    The user interface is intuitive and easy to navigate, making it accessible for users without technical expertise.
  • Lightweight
    Plausible's script is under 1 KB in size, making it fast to load and reducing the impact on site speed.
  • Open-Source
    The platform is open-source, which allows for community contributions and transparency in how data is handled.
  • Real-Time Data
    Plausible provides real-time analytics, which can be useful for monitoring live events and activities on your site.
  • Affordable Pricing
    Offers competitive pricing models that can be more budget-friendly for small to medium-sized businesses compared to other analytics platforms.

Possible disadvantages of Plausible.io

  • Limited Features
    Lacks some advanced features found in more comprehensive analytics tools like Google Analytics, such as multi-channel funnels and detailed demographic information.
  • No Free Tier
    Plausible does not offer a free tier, which could be an obstacle for very small websites or individual users on a tight budget.
  • Basic Reporting
    The reporting may be too basic for larger enterprises that require more granular and customizable analytics.
  • No App Integration
    Currently, Plausible does not offer integrations with mobile app analytics, limiting its use to web applications.
  • Smaller User Base
    As a relatively new and smaller player in the market, it may not have the extensive user community or third-party support seen with more established platforms.

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.

Plausible.io videos

Cardano Blackboard Series #5: What is plausible deniability?

More videos:

  • Review - How Plausible is the Balkanized America from Crimson Skies? (A Map Analysis)
  • Review - Movie Review - How Plausible is The Martian?

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

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

Category Popularity

0-100% (relative to Plausible.io and Pandas)
Analytics
100 100%
0% 0
Data Science And Machine Learning
Web Analytics
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

Share your experience with using Plausible.io and Pandas. For example, how are they different and which one is better?
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Reviews

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

Plausible.io Reviews

  1. Happy Paying User :)

    I've been using plausible since Sep 2019 and never had any doubts about it. It provides me with everything I need related to visitor stats while keeping privacy in first place.

    It doesn't slow down my website loading speed (it's amazing, it's less than 1KB in size!), is not blocked by adblockers since it's not really a tracker tracker, and owners are super cool and they actually respond to every inquiry you could possibly have.

    If you're looking for de-googling your stuff, you can start with Plausible :)

    🏁 Competitors: Google Analytics, Matomo, Woopra
    👍 Pros:    Loading speed|Clean ui|Privacy concisous|Custom domain|Affordable prices|Easy integration|Super simple
  2. Makis
    · Senior Software Engineer ·
    Plausibly simple analytics!

    I tried several analytics tools prior to Plausible, namely Google Analytics and later on Matomo. I found both to be fairly complicated for my usage which is a personal blog. Complicated in the way I had to install and use them. Plausible's simple to set up approach combined with a very clean and inviting user interface was a breath of fresh air. It's simple and clean enough that it actually makes me want to check and analyse my traffic which is a feeling I never thought I'd have having tried alternatives.

  3. Cesar Reyes
    · CEO at Reyes.Pro ·
    Excellent alternative to google analytics

    It offers clear information about what I really need, without distractions, without advertising and does not slow my site.

    🏁 Competitors: Google Analytics

Top 5 Plausible Analytics Alternatives in 2024
Looking for an excellent Plausible Analytics alternative? Read on as in this blog we will be exploring the best Plausible alternatives in 2024.
Source: www.putler.com
Top 9 Plausible Analytics alternatives in 2024
Plausible is an analytics platform focused on delivering clear insights into website traffic. By offering essential metrics like page views and referral sources, Plausible aids businesses in making informed decisions to optimize their online presence.
Source: usermaven.com
Top 5 Self-Hosted, Open Source Alternatives to Google Analytics
Use Case Example: An educational blog opts for Plausible to track user engagement metrics without impacting site performance or user privacy.
Source: zeabur.com
Top 5 open source alternatives to Google Analytics
Plausible is a newer kid on the open source analytics tools block. It’s lean, it’s fast, and only collects a small amount of information — that includes numbers of unique visitors and the top pages they visited, the number of page views, the bounce rate, and referrers. Plausible is simple and very focused.
Source: opensource.com
Privacy-oriented alternatives to Google Analytics
I learned about Plausible just recently, but they deserve to be on top of this list for me. Their platform is completely Open Source on GitHub under the MIT license. I personally also like that it’s written in Elixir.

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

Social recommendations and mentions

Pandas might be a bit more popular than Plausible.io. We know about 219 links to it since March 2021 and only 200 links to Plausible.io. 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.

Plausible.io mentions (200)

  • 10 of the Best Web Analytics Tools for React Websites
    Plausible is a privacy-focused website analytics tool that provides simple, actionable insights into website traffic and visitor behavior. It prioritizes data privacy by offering transparent analytics without cookies, tracking scripts, or personal data collection. - Source: dev.to / 2 months ago
  • Top 10 European Open-Source Projects to Watch in 2025
    Perfect for companies running under tight EU privacy regulations. Find more: Plausible analytics. - Source: dev.to / 2 months ago
  • Meet Marko Saric, Co-founder of Privacy-friendly Plausible Analytics
    In this interview, Marko Saric shared his thoughts on privacy and running a bootstrapped SaaS business. Plausible integration is already available in Open SaaS as a privacy-friendly alternative to Google Analytics. We hope this interview helps you understand the value of such a product, and the nature of running an open source business. - Source: dev.to / 3 months ago
  • 5 Side Project Ideas for Developers to Monetize as Micro-SaaS in 2025
    Plausible Analytics (https://plausible.io/) is a lightweight, privacy-focused analytics tool that’s designed to be simple and easy to use. Unlike Google Analytics, Plausible gives you just the metrics you need—without the bloat. - Source: dev.to / 3 months ago
  • Umami is a simple, fast, privacy-focused alternative to Google Analytics
    It is not entirely clear who wrote these descriptions. Maybe it was not the vendor. At least their website https://plausible.io/ has a much better wording. > No need for cookie banners or GDPR consent. - Source: Hacker News / 3 months ago
View more

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 / 26 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 / about 1 month 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 / about 2 months 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 / 4 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 / 9 months ago
View more

What are some alternatives?

When comparing Plausible.io and Pandas, you can also consider the following products

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

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

Fathom Analytics - Simple, trustworthy website analytics (finally)

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

Matomo - Matomo is an open-source web analytics platform

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