Software Alternatives, Accelerators & Startups

Float VS NumPy

Compare Float VS NumPy 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.

Float logo Float

The leading resource management software for agencies, studios, and firms. With a simple, drag and drop interface and powerful editing tools, Float saves you time and keeps projects on track.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Float Landing page
    Landing page //
    2023-02-11

Float is the world's leading resource management software for agencies, studios, and firms. Since 2012, Float has been helping the world’s best teams including RGA, VICE, Deloitte, and Buzzfeed schedule and deliver over 5.5million tasks, in more than 150 countries.

With an easy to use, intuitive interface, drag and drop features, and powerful editing tools, Float makes planning your projects and scheduling your team's time visual and simple. Search your schedule for practically anything and track your team's utilization with powerful reporting tools. Forecast your budget spend and plan ahead based on your team's real capacity and resources.

Integrate your schedule with Slack, Google Calendar and 1,000+ of your apps via Zapier. Access and update your Float schedule from anywhere with apps for iOS and Android.

By providing a single view of your real resource capacity and a shared calendar of who's working on what, Float makes team scheduling across multiple projects faster, easier and more efficient.

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

Float

Website
float.com
$ Details
$5.0 / Monthly ($5/person scheduled/month)
Platforms
Browser iOS Android
Release Date
2012 February

Float features and specs

  • User-Friendly Interface
    Float offers an intuitive and easy-to-navigate interface, making it accessible for users of all skill levels.
  • Collaboration Tools
    Float provides robust collaboration features, including real-time updates and team communication capabilities, which enhance team coordination.
  • Resource Management
    The platform excels at resource management, allowing for efficient allocation and tracking of team members and project resources.
  • Integrations
    Float integrates with popular tools like Slack, Trello, and Asana, streamlining workflows and improving productivity.
  • Mobile Accessibility
    With mobile accessibility, users can manage schedules and resources on-the-go, adding flexibility to their project management.

Possible disadvantages of Float

  • Cost
    Float may be considered expensive for small businesses or startups due to its subscription pricing model.
  • Limited Customization
    Users may find limitations in terms of customization options for specific needs or preferences.
  • Learning Curve
    Despite its user-friendly design, there may still be a learning curve for users who are new to project management tools.
  • Performance Issues
    Some users report occasional performance issues, such as slow loading times or lag, particularly with larger projects.
  • Reporting Features
    While adequate for basic needs, the reporting and analytics features may not be as advanced as some competitors.

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.

Float videos

Sonic NEW Lemonberry Slush Float Review 🍋🍓

More videos:

  • Review - Swimways Baby Float Review | Dude Dad
  • Review - Glorious G Float Review.. Should You Upgrade To Ceramic Mouse Feet?

NumPy videos

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 Float and NumPy)
Resource Scheduling
100 100%
0% 0
Data Science And Machine Learning
Employee Scheduling
100 100%
0% 0
Data Science Tools
0 0%
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 Float and NumPy

Float Reviews

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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.
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 Float. While we know about 119 links to NumPy, we've tracked only 2 mentions of Float. 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.

Float mentions (2)

  • 2022 Accounting/time billing ideas for SW dev consulting? On my second, not really happy
    You wouldn't want something like NetSuite just for time entry. Try float.com, one of my clients uses this and it seems to be work and is simple. Source: about 3 years ago
  • Project/Team Management software/platform assistance needed
    Schedule more than one task to a team member per day i.e. Hours per task per day - float.com and avasa.com allows this. Source: over 3 years ago

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 Float and NumPy, you can also consider the following products

ResourceGuru - The fast, simple way to schedule people, equipment, and other resources online.

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

When I Work - When I Work is an employee scheduling and communication app using the web, mobile apps, text messaging, social media, and email.

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

Ganttic - Ganttic is a flexible resource management platform for scheduling teams, equipment, vehicles and multiple projects simultaneously. Save time, eliminate double bookings, and increase efficiency.

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