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Shadow VS Pandas

Compare Shadow VS Pandas and see what are their differences

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Shadow logo Shadow

Transform any device into a supercharged gaming machine.

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
  • Shadow Landing page
    Landing page //
    2023-10-04
  • Pandas Landing page
    Landing page //
    2023-05-12

Shadow

Website
shadow.tech
$ Details
-
Release Date
2015 January
Startup details
Country
France
State
Ile-de-France
City
Paris
Founder(s)
Asher Kagan
Employees
100 - 249
Edit details

Pandas

Website
pandas.pydata.org
$ Details
Release Date
-
Edit details

Shadow features and specs

  • High-Performance
    Shadow provides a high-performance virtual computer with dedicated resources, ensuring smooth operation for demanding applications and games.
  • Accessibility
    Users can access their Shadow PC from various devices including Windows, macOS, Android, and iOS, making it versatile and highly accessible.
  • Cost-Effective
    For users who require high-end hardware but cannot afford the upfront cost, Shadow's subscription model provides access to powerful technology for a manageable monthly fee.
  • Security and Updates
    The service includes regular updates and security measures, so users don’t need to worry about maintaining their hardware or software.
  • Storage
    Shadow offers substantial cloud storage, which can be a significant advantage for users needing large amounts of space for their projects and files.

Possible disadvantages of Shadow

  • Internet Dependency
    Shadow requires a stable and fast internet connection to function properly. Poor connectivity can result in lag and reduced performance.
  • Bandwidth Usage
    Streaming a virtual computer can consume a lot of data, which may be an issue for users with limited bandwidth or data caps.
  • Subscription Cost
    Although cost-effective for some, the subscription fee can become expensive over time compared to owning your own hardware outright.
  • Latency
    Despite high performance, users may still experience latency issues, especially in high-speed applications like competitive gaming.
  • Limited Offline Use
    The reliance on cloud means that there is no offline mode, so users can’t access their virtual machine without an internet connection.

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.

Analysis of Pandas

Overall verdict

  • Pandas is highly recommended for tasks involving data manipulation and analysis, especially for those working with tabular data. Its efficiency and ease of use make it a staple in the data science toolkit.

Why this product is good

  • Pandas is widely considered a good library for data manipulation and analysis due to its powerful data structures, like DataFrames and Series, which make it easy to work with structured data. It provides a wide array of functions for data cleaning, transformation, and aggregation, which are essential tasks in data analysis. Furthermore, Pandas seamlessly integrates with other libraries in the Python ecosystem, making it a versatile tool for data scientists and analysts. Its extensive documentation and strong community support also contribute to its reputation as a reliable tool for data analysis tasks.

Recommended for

    Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.

Shadow videos

+ Add

Shadow - Movie Review

More videos:

  • Review - Shadow Cloud Gaming Review
  • Review - Shadow - Movie Review

Pandas videos

+ Add

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 Shadow and Pandas)

Shadow

Pandas

Games
100 100%
Games
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Game Streaming
100 100%
Game Streaming
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Shadow 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 Shadow and Pandas

Shadow Reviews

11 Best Parsec Alternatives & Similar Apps
Still, it can consume your battery. All in all, Shadow is a worth-trying app for those who love games and want to always connect with their games regardless of the location.
Source: www.regendus.com
7 Best Cloud Gaming Services for 2020 (No. 3 is My Favorite)
Although games are a popular use of Shadow, and work well on it, Shadow’s core service is more than just games. While that’s a pro for some, it may be extra weight for people who want to keep things simple.
Source: hostingpill.com
Stream games with these Google Stadia alternatives
The Shadow cloud gaming model is about to be updated, and it will make it quite the formidable foe. For the basic monthly investment of £13, you gain access to a timeshare comprised of an Intel Xeon CPU, an Nvidia GTX 1080 equivalent graphics card, 12GB of DDR4, a 256GB SSD, and an internet connection that’ll make you weep in awe. It’s 1Gbps, so you absolutely don’t need to...
Source: www.pcgamesn.com
15 game streaming services you can try before Google Stadia arrives
You might not have heard of Shadow, but it’s a real cloud game streaming service based in the United States. Like other similar platforms, Shadow works by giving you a virtualized computer with the means to play 3D games. Currently, Shadow is operational in 38 out of the 50 states, with more on the way.
Source: www.theverge.com
The Best Cloud Gaming Services for Streaming Video Games
Shadow: Cloud gaming at a fixed price. Shadow functions as a subscription service, with a price of $35 a month no matter how much time you spend playing. For those of you that play way more than you should, this service may be for you. It’s also similar to Parsec in that it’s essentially a computer in the cloud, so you can run any app you want in it.
Source: www.howtogeek.com

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

Shadow might be a bit more popular than Pandas. We know about 320 links to it since March 2021 and only 219 links to Pandas. 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.

Shadow mentions (320)

  • 🚀 Get a 5€ Discount on Your ShadowPC Subscription with Code: 80EDA79
    Upgrade your gaming experience with ShadowPC! Use my referral code "80EDA79" at checkout to snag a cool 5€ off your first subscription. Game on! 🚀. Source: over 1 year ago
  • PCVR on Mac?
    I had Shadow. There quite affordable when I registered and the hardware was top line. I was using it as my gaming PC for a long time (mainly for PCVR). I live in Spain and these days there wasn't dedicated servers here so I connected through Paris nodes (and that increased a bit the latency) but I play HL Alyx and a lot of games that way with good graphics (in that moment Shadow has a GTX1080 GPU) and great... Source: almost 2 years ago
  • Journeyperson save on a potato? Or stuck to one large nation/several small ones?
    Https://shadow.tech/ It’s a cloud PC. I used to use it until I got my current laptop. Not cheap but very good. Source: about 2 years ago
  • Apple's game porting toolkit is fantastic. Cyperbunk 2077 at Ultra on an M1 MBP
    > But then Apple doesn't ship devices with actually powerful GPUs, so it can never compete with the gaming PCs which are far less expensive and far more powerfull graphics-wise. It is still expensive to have to use Windows just so you can game. Or put all the effort into dual booting Linux. Most people just use a Macbook and then get an Xbox/Ps5/Switch/Quest2. For games I can't use on those you can get Shadow PC... - Source: Hacker News / about 2 years ago
  • Stream pirated Games
    There is shadow.tech, which just gives you a full Windows Desktop with a little persistent disk. This should in theory work the way you want to. Source: about 2 years ago
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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 / about 1 month 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 2 months 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 / 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 / 10 months ago
View more

What are some alternatives?

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

Parsec - Streams games locally or over the internet

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

Geforce Now - Underpowered PC can now pack the punch of high-performance GeForce GTX GPUs with GeForce NOW.

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

Stadia - A new gaming platform from Google

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

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