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Excel Dashboard School VS NumPy

Compare Excel Dashboard School VS NumPy and see what are their differences

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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
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Excel Dashboard School logo Excel Dashboard School

Free Excel add-ins and tools on Excel Dashboard School. Boost your work productivity and save your time! No trials, 100% power!

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Excel Dashboard School Landing page
    Landing page //
    2023-09-24

Text Tools and Smart Utilities! Text processing and string manipulations in Excel are not an easy tasks but we’ll help you to simplify string related functions using our add-in.

Feature list:

  • Convert text to uppercase, apply Excel lowercase to your data or convert your text values to proper / title case
  • Delete first or last character from a selected string
  • Delete x characters starting at the nth position
  • Remove spaces, non-printable characters, all line breaks, initial apostrophes
  • Insert text before first, after last character
  • Insert text starting at nth position and much more….
  • Calendar. Quick dates entry to save your time.
  • Drop-down list creator: Create drop-down list in selected cells in seconds
  • Spreadsheet Tools – Effective management for Ranges
  • Data Collector: Consolidate Multiple Worksheets into one Workbook
  • Split Ranges: Split one data table into several different sheets based on the values of the specified column or other criteria.
  • Compare Ranges: Compare two columns or ranges and the output or highlighting of coincidences / differences between them.
  • Clean Ranges: Delete text, formats, notes, hyperlinks, conditional formatting, etc. in selected cells.
  • Screenshot Manager: Create screenshot of selected range and export it into various formats.
  • WorkSheet Manager
  • Perform vary operations (adding, sorting, protecting, etc.) on sheets in current workbook.
  • NumPy Landing page
    Landing page //
    2023-05-13

Excel Dashboard School features and specs

  • Comprehensive Learning Resources
    Excel Dashboard School provides a wide range of learning materials, including tutorials, templates, and examples, catering to different skill levels.
  • High-Quality Templates
    The site offers professionally designed templates that are ready to use, saving users time and ensuring a polished appearance.
  • Step-by-Step Tutorials
    Detailed, easy-to-follow tutorials help users build dashboards from scratch, making it easier for beginners to learn.
  • Regular Updates
    The platform frequently updates its content, ensuring users have access to the latest techniques and best practices in dashboard creation.
  • Community Support
    Excel Dashboard School has a community of users where members can share tips, ask questions, and offer support to each other.

Possible disadvantages of Excel Dashboard School

  • Cost
    Some of the resources and templates are behind a paywall, which may not be affordable for all users.
  • Complexity
    Even with tutorials, some users might find advanced dashboard features and functions quite complex and challenging to implement.
  • Limited Free Content
    Although there is free content available, it may be insufficient for users who need comprehensive or specific solutions without purchasing premium resources.
  • User Interface
    The website's interface and navigation could be more intuitive, potentially making it difficult for users to find specific resources or tutorials.
  • Excel Dependency
    Resources and tutorials are primarily focused on Microsoft Excel, limiting applicability for users who prefer or require alternative data analysis tools.

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.

Analysis of Excel Dashboard School

Overall verdict

  • Excel Dashboard School is generally a good resource for learning how to create dashboards in Excel.

Why this product is good

  • It provides a variety of tutorials, templates, and step-by-step guides which are beneficial for both beginners and advanced users looking to enhance their skills in Excel dashboard creation. The resources are practical and focused on real-world scenarios, making it easier for learners to apply their knowledge effectively.

Recommended for

  • Business professionals who need to create detailed reports and dashboards regularly.
  • Data analysts who want to improve their report presentation using Excel.
  • Students seeking to improve their Excel skills for career advancement.
  • Anyone interested in learning how to communicate data insights more effectively through visual representations.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Excel Dashboard School videos

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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 Excel Dashboard School and NumPy)

Excel Dashboard School

NumPy

Data Dashboard
63 63%
Data Dashboard
37% 37
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Technical Computing
100 100%
Technical Computing
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 Excel Dashboard School and NumPy

Excel Dashboard School 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.
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.

Excel Dashboard School mentions (0)

We have not tracked any mentions of Excel Dashboard School yet. Tracking of Excel Dashboard School 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 / 9 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 / 10 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 / 10 months ago
View more

What are some alternatives?

When comparing Excel Dashboard School and NumPy, you can also consider the following products

Kutools for Excel - A handy Microsoft Excel add-ins collection to free you from time-consuming operations.

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

KPI Dashboard in Excel - Professional Management KPI Dashboard. Includes trend charts, past year/target comparisons, monthly & cumulative analysis in performance dashboard.

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

ASAP Utilities - ASAP Utilities is a powerful Excel add-in that fills the gaps in Excel.

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

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