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Pandas VS OpenX

Compare Pandas VS OpenX and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Pandas logo Pandas

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

OpenX logo OpenX

Ad technology platform available as a hosted service or as an open source download.
  • Pandas Landing page
    Landing page //
    2023-05-12
  • OpenX Landing page
    Landing page //
    2023-02-07

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.

OpenX features and specs

  • Comprehensive Ad Exchange
    OpenX offers a powerful and extensive ad exchange platform that enables publishers and advertisers to connect, optimize ad placements, and maximize revenue.
  • Real-time Bidding
    OpenX's real-time bidding (RTB) technology allows advertisers to bid on ad placements in real-time, ensuring the most relevant ads are shown to the right audience at the right time.
  • Cross-Platform Support
    OpenX supports a variety of platforms (desktop, mobile, video) and ad formats, providing flexibility and reach for advertisers and publishers alike.
  • Advanced Targeting
    With advanced audience segmentation and targeting capabilities, OpenX enables advertisers to deliver more personalized and effective ad campaigns.
  • Transparency and Reporting
    OpenX provides detailed reporting and data transparency, allowing users to analyze performance metrics and make informed decisions.
  • High Quality Standards
    OpenX places a strong emphasis on maintaining high-quality ad inventory and follows stringent ad quality guidelines to ensure a safe and effective advertising ecosystem.

Possible disadvantages of OpenX

  • Complex Setup
    The setup and integration process for OpenX can be complex and may require technical expertise, which could be a barrier for smaller publishers or less tech-savvy users.
  • Costs
    While OpenX offers powerful features, the costs associated with using their platform can be relatively high, which may not be suitable for all budgets.
  • Competition
    The ad exchange market is highly competitive, and OpenX faces strong competition from other major players, which might affect pricing and service offerings.
  • Learning Curve
    Due to its advanced features and capabilities, new users may experience a steep learning curve when first starting with OpenX.
  • Support Limitations
    Some users report that customer support can be slow or insufficient, particularly for smaller clients who might not receive the same level of attention as larger accounts.

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

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

OpenX videos

+ Add

OpenX CEO's Advice for Addressing the 'Asymmetry' in Digital Ads

More videos:

  • Review - OpenX CEO I We Want to Create a Fair and Open Marketplace for Businesses
  • Review - Getting New Domains and App URLs Approved for the OpenX Ad Exchange

Category Popularity

0-100% (relative to Pandas and OpenX)

Pandas

OpenX

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Ad Networks
0 0%
Ad Networks
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Advertising
0 0%
Advertising
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 OpenX

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

OpenX Reviews

A Beginner’s Guide to Ad Servers (Plus: 8 Ad Servers Reviewed)
OpenX is aimed at the larger publisher that serves a high number of ads per month. They seem to be secretive about pricing, but we did manage to find a few quotes others have received from the OpenX sales team.
Source: www.adpushup.com
Best Ad Serving Platforms For 2018: Third Party Technology Companies (Free Options Included In List)
With the Broad Street platform you can expect ease of use (little additional learning curve for previous GAM or OpenX users), automated reporting to make delivering reports to clients effortless, sponsored content analytics, newsletter advertising management via your dashboard, and even a white labeling option.
Source: www.monetizemore.com

Social recommendations and mentions

Based on our record, Pandas seems to be more popular. 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 / 20 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 1 month 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 / 9 months ago
View more

OpenX mentions (0)

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

What are some alternatives?

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

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

Google Ad Manager - Grow revenue wherever your users are with an integrated ad management platform that surfaces insights for smarter business decisions.

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

AerServ - AerServ offers monetization solution for mobile publishers.

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

Kevel - Kevel's APIs make it easy for engineers and PMs to quickly launch a fully-customized, white-labeled, server-side ad server.

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