Software Alternatives, Accelerators & Startups

Google Ad Manager VS Pandas

Compare Google Ad Manager VS Pandas 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.

Google Ad Manager logo Google Ad Manager

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

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
  • Google Ad Manager Landing page
    Landing page //
    2022-10-02
  • Pandas Landing page
    Landing page //
    2023-05-12

Google Ad Manager features and specs

  • Comprehensive Ad Management
    Google Ad Manager integrates various facets of ad placement, trafficking, and reporting into a single platform, making it easier for publishers to manage their advertisements across multiple channels.
  • Advanced Targeting Capabilities
    It offers advanced targeting options based on factors like demographics, interests, and behaviors, allowing for personalized ad experiences and increased relevance for the audience.
  • Robust Reporting Tools
    Google Ad Manager provides detailed reporting and analytics, helping users measure performance, track revenue, and optimize their ad strategies in real-time.
  • Scalability
    Suitable for organizations of any size, from small businesses to large enterprises, making it a versatile solution that can grow with your business needs.
  • Integration with Google Ecosystem
    Seamlessly integrates with other Google products like Google Analytics and Google Marketing Platform, creating a cohesive digital marketing ecosystem.

Possible disadvantages of Google Ad Manager

  • Complexity
    The platform can be overwhelming for beginners due to its comprehensive features and interface, requiring time and effort to fully understand and utilize.
  • Cost
    While it offers a free tier, advanced features and higher usage levels can lead to significant costs, which might not be suitable for small businesses with limited budgets.
  • Learning Curve
    Even experienced marketers may face a steep learning curve when initially using the platform, which may require additional training or support.
  • Data Privacy Concerns
    Given its extensive data collection and targeting capabilities, there may be concerns regarding data privacy and compliance with global regulations like GDPR and CCPA.
  • Dependence on Google Ecosystem
    Heavy reliance on the Google ecosystem could be a drawback for those looking to diversify their digital marketing tools or who have concerns about vendor lock-in.

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.

Google Ad Manager videos

Google Ad Manager reporting integration

More videos:

  • Review - Troubleshoot bad ads - Review and Manage Ads in Google Ad Manager- Google Ad Manager course 2020
  • Review - Opportunities And Experiments In Google Ad Manager

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 Google Ad Manager and Pandas)
Ad Networks
100 100%
0% 0
Data Science And Machine Learning
Advertising
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

Share your experience with using Google Ad Manager and Pandas. 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 Google Ad Manager and Pandas

Google Ad Manager Reviews

We have no reviews of Google Ad Manager yet.
Be the first one to post

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

Based on our record, Pandas seems to be a lot more popular than Google Ad Manager. While we know about 219 links to Pandas, we've tracked only 4 mentions of Google Ad Manager. 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.

Google Ad Manager mentions (4)

  • What is Prebid.js & how to debug it using Requestly!
    Prebid.js is an open-source header bidding wrapper that enables publishers to conduct auctions for their ad inventory across multiple demand sources. It integrates seamlessly with ad servers like Google Ad Manager, allowing publishers to increase competition and, consequently, ad revenue. - Source: dev.to / 9 months ago
  • (need tool) How to better sell ad spaces to my direct ad customers?
    I read somewhere that Google Ad Manager can solve my Problems. Is that true? Can someone send me a link of their documentation where they show this feature? Because I don't understand really Google Ad Manager, I saw their website https://admanager.google.com/home/ but it feels like AdSense, just for businesses who have more ad space with different interest groups and so on with better ad network Management or... Source: over 3 years ago
  • 15 Million page views but rejected from GAM
    Thanks for that info! Yes, I filled out a form at https://admanager.google.com/home/ and that's when this Google person reached out to us. Source: about 4 years ago
  • 15 Million page views but rejected from GAM
    You sure you just signed up at https://admanager.google.com/home/ ? Just register an Adsense account, then a free GAM account and you should be good to go. Source: about 4 years ago

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

What are some alternatives?

When comparing Google Ad Manager and Pandas, you can also consider the following products

OpenX - Ad technology platform available as a hosted service or as an open source download.

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

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

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