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Panoply VS NumPy

Compare Panoply VS NumPy and see what are their differences

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

Panoply logo Panoply

Panoply is a smart cloud data warehouse

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Panoply Landing page
    Landing page //
    2023-09-27

Panoply is a smart data warehouse that automates all three key aspects of the data analytics stack: data collection & transformation (ETL), database storage management, and query performance optimization. Panoply empowers anyone working with data analytics to quickly gain actionable insights on their own - without the need of IT and Engineering.

  • NumPy Landing page
    Landing page //
    2023-05-13

Panoply videos

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Panoply demo: Get faster data analytics in minutes!

NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Panoply and NumPy)

Panoply

NumPy

Data Management
100 100%
Data Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Integration
100 100%
Data Integration
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Panoply and NumPy

Panoply Reviews

Top 14 ETL Tools for 2023
Panoply is an automated, self-service cloud data warehouse that aims to simplify the data integration process. Any data connector with a standard ODBC/JDBC connection, Postgres connection, or AWS Redshift connection is compatible with Panoply. In addition, users can connect Panoply with other ETL tools, such as Stitch and Fivetran, to further augment their data integration...
Source: www.integrate.io
Top 5 BigQuery Alternatives: A Challenge of Complexity
Although Panoply was developed for data analysts, you don't have to be one to use it. Anyone with a good understanding of SQL can get a data pipeline up and running within a matter of minutes. This frees up your time to focus on analysis, whether you’re running queries directly in Panoply or in your favorite BI tool.
Source: blog.panoply.io
Top ETL Tools For 2021...And The Case For Saying "No" To ETL
Under the hood, Panoply uses a flexible ELT approach (rather than traditional ETL), which makes data ingestion much faster and more dynamic, since you don’t have to wait for transformation to complete before loading your data. And since Panoply builds managed cloud data warehouses for every user, you won’t need to set up a separate destination to store all the data you pull...
Source: blog.panoply.io
Top 7 ETL Tools for 2021
Panoply is an automated, self-service cloud data warehouse that aims to simplify the data integration process. Any data connector with a standard ODBC/JDBC connection, Postgres connection, or AWS Redshift connection is compatible with Panoply. In addition, users can connect Panoply with other ETL tools such as Stitch and Fivetran to further augment their data integration...
Source: www.xplenty.com

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Panoply. While we know about 107 links to NumPy, we've tracked only 3 mentions of Panoply. 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.

Panoply mentions (3)

NumPy mentions (107)

  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 2 months ago
  • JSON in data science projects: tips & tricks
    Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 3 months ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
  • A Comprehensive Guide to NumPy Arrays
    Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 7 months ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
View more

What are some alternatives?

When comparing Panoply and NumPy, you can also consider the following products

QuickBI - Export data from over 300 sources to a data warehouse and analyze it with a reporting tool of your choice. Quick and easy setup.

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

Supermetrics - Supermetrics condenses all the major vectors of data relevant to a user's marketing campaigns and helps them make sense of it all.

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

Airbyte - Replicate data in minutes with prebuilt & custom connectors

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

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