Software Alternatives, Accelerators & Startups
Register | Login

Geckoboard VS NumPy

Compare Geckoboard VS NumPy and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Geckoboard logo Geckoboard

Get to know Geckoboard: Instant access to your most important metrics displayed on a real-time dashboard.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Geckoboard Landing page
    Landing page //
    2023-10-15

  www.geckoboard.comSoftware by Geckoboard

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

Geckoboard features and specs

  • User-Friendly Interface
    Geckoboard has a clean and intuitive interface, making it easy for users to set up and navigate dashboards without the need for in-depth technical skills.
  • Real-Time Data
    Geckoboard offers real-time data visualization, allowing users to monitor key metrics and make data-driven decisions swiftly.
  • Integration Capabilities
    Geckoboard supports a wide range of integrations with popular data sources such as Google Analytics, Salesforce, and Zendesk, making it versatile for different business needs.
  • Customizable Dashboards
    Users can customize dashboards extensively to focus on the KPIs that matter most to their organization, providing a tailored data visualization experience.
  • Easy Sharing
    Dashboards can be easily shared with team members or external stakeholders through secure links, making collaboration straightforward.

Possible disadvantages of Geckoboard

  • Cost
    Geckoboard can be relatively expensive, particularly for small businesses or startups with limited budgets.
  • Limited Advanced Analytics
    While it excels in data visualization, Geckoboard lacks advanced analytics features, such as complex data manipulation or predictive analytics, that some businesses may require.
  • Integration Limitations
    Although Geckoboard supports many integrations, users might find that not all data sources are covered, requiring additional data handling.
  • Dependency on External Data Integrity
    The accuracy of the dashboards heavily depends on the quality and accuracy of the external data sources integrated with Geckoboard.
  • Learning Curve
    Although the interface is user-friendly, there is still a learning curve for users unfamiliar with data dashboards and those who need to customize more advanced features.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Geckoboard videos

+ Add

Spreadsheet dashboards with Geckoboard - how to get key metrics seen

More videos:

  • Review - Geckoboard Data Dashboard: Product Spotlight

NumPy videos

+ Add

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 Geckoboard and NumPy)

Geckoboard

NumPy

Data Dashboard
84 84%
Data Dashboard
16% 16
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Business Intelligence
100 100%
Business Intelligence
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Geckoboard and NumPy. 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 Geckoboard and NumPy

Geckoboard Reviews

11 Metabase Alternatives
Geckoboard is a great service that is used to build featured dashboards with the help of eighty different integrations that is a very useful method to connect your data with this application. By using this platform, you will be able to create real-time dashboards with easy-to-use and simple steps that are available for even first-time users. This application is trusted by...
Source: www.justalternativeto.com
Top 10 Visual Analytics Provider For 2021
A UK-based firm, Geckoboard specialises in what it calls TV dashboarding. The company creates dashboards that are more customisable to TV or bigger screens and can help companies define goals and monitor performances through KPIs that can change real-time. The platform connects to more than 60 data sources across horizontals like finance, marketing project management, social...
Source: analyticsindiamag.com
27 dashboards you can easily display on your office screen with Airtame 2
Sometimes, one dashboard just isn’t enough. That’s why Geckoboards lets you display several different dashboards on the same screen. You can even add your own logo for a customized look and feel that matches your brand.
Source: airtame.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 more popular. It has been mentiond 119 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.

Geckoboard mentions (0)

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

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

What are some alternatives?

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

Databox - Databox is an easy-to-use analytics platform that helps growing businesses centralize their data, and use it to make better decisions and improve performance.

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

Google Data Studio - Data Studio turns your data into informative reports and dashboards that are easy to read, easy to share, and fully custom. Sign up for free.

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

Klipfolio - Klipfolio is an online dashboard platform for building powerful real-time business dashboards for your team or your clients.

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

Loading...