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NumPy VS Google Analytics

Compare NumPy VS Google Analytics and see what are their differences

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LiveSession helps you analyze users’ behavior, improve UX, find JS bugs, and increase conversion rates using session replays, and event-based product analytics. featured
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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Google Analytics logo Google Analytics

Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Google Analytics Landing page
    Landing page //
    2023-08-26

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.

Google Analytics features and specs

  • Comprehensive Data Collection
    Google Analytics offers extensive data collection capabilities, allowing you to track various metrics and derive insights on user behavior, traffic sources, and more.
  • Integration with Other Google Services
    It easily integrates with other Google services like Google Ads, Google Search Console, and Google Tag Manager, providing a cohesive ecosystem.
  • Free Tier Available
    A robust free tier is available that meets the needs of many small- to medium-sized businesses, making it accessible without financial investment.
  • Customizable Reports and Dashboards
    Users can create customized reports and dashboards to focus on the specific metrics and KPIs important to their business.
  • Advanced Segmentation
    The platform allows for advanced segmentation of user data, enabling detailed analysis of different user groups and behaviors.
  • Real-Time Data
    Google Analytics provides real-time reports, facilitating immediate analysis and quicker decision-making.
  • E-commerce Tracking
    Special features for e-commerce websites allow you to track transactions, revenue, and other e-commerce-related metrics effectively.

Possible disadvantages of Google Analytics

  • Complex Interface
    The interface can be overwhelming and difficult to navigate for beginners, requiring a steep learning curve.
  • Data Sampling
    For large datasets, Google Analytics may use data sampling, which can compromise the accuracy and precision of your reports.
  • Privacy Concerns
    There are ongoing privacy concerns about data sharing and user tracking, which have led to legal scrutiny in some regions.
  • Limited Free Tier
    While the free tier is powerful, it has limitations on data collection and features, which may require upgrading to the paid tier for larger businesses.
  • Dependence on Third-Party Cookies
    Google Analytics heavily relies on third-party cookies, which are increasingly being restricted by browsers and privacy regulations.
  • Lag in Data Processing
    There can be a delay in data processing and updates, which may hinder timely decision-making.
  • Limited Customer Support
    Customer support for the free tier is limited, often requiring users to rely on community forums and online resources for assistance.

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

Google Analytics videos

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Google Analytics Review

More videos:

  • Review - Google Analytics, Ultimate Beginner’s Guide
  • Review - Google Analytics Review

Category Popularity

0-100% (relative to NumPy and Google Analytics)

NumPy

Google Analytics

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Analytics
0 0%
Analytics
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Web Analytics
0 0%
Web Analytics
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 NumPy and Google Analytics

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

Google Analytics Reviews

10 Best Mixpanel Alternatives for Product Analytics in 2024
Google Analytics is a popular digital insights platform that allows website owners to monitor multiple aspects of their user analytics, online performance, and more. Use the paid or free plan to optimize your website with user behavior insights to get higher conversion rates.
Source: clickup.com
Best Mixpanel Alternatives for SaaS
GA 360 (now GA4) provides higher data limits, BigQuery integration, service level agreements, custom variables, and a dedicated support team. The cost of Google Analytics 360 starts from $12,500 per month and $150,000 per year. Google suggests that the cost of Google Analytics 4 360 starts at a retail price of USD $50,000/year, which entitles customers to 25 million events...
Source: userpilot.com
Top 5 Plausible Analytics Alternatives in 2024
It allows you to bring in data from 17+ sources including multiple shopping carts, payment gateways, Google Analytics, and email marketing platforms.
Source: www.putler.com
Top 9 Plausible Analytics alternatives in 2024
Google Analytics, a prominent player, offers extensive functionalities, making it suitable for businesses needing comprehensive data analysis. Its versatility spans from tracking website traffic, user demographics, and behavior to providing insights on conversion rates and traffic sources.
Source: usermaven.com
Top 5 Self-Hosted, Open Source Alternatives to Google Analytics
Choosing the right open source, self-hosted alternative to Google Analytics depends on your specific needs, whether it's for enhanced privacy, detailed data insights, or ease of use. Each of these tools offers unique strengths, empowering website owners with the flexibility and control needed in today's digital landscape.
Source: zeabur.com

Social recommendations and mentions

Based on our record, NumPy should be more popular than Google Analytics. 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.

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

Google Analytics mentions (36)

  • Navigating the Digital Landscape: The Role of Website Analytics in Measuring Performance
    Let’s discuss Google Analytics in particular and other tools in general, which are available online to measure the website performance. Source: almost 2 years ago
  • 10 BEST FREE SEO REPORTING TOOLS
    Google Analytics: A free tool from Google that provides in-depth website analytics and performance metrics, including traffic sources, user behavior, and conversions. Source: almost 2 years ago
  • Affiliate Marketing Automation: How to Save Time and Improve Your Results?
    Automating your affiliate marketing has a clear advantage: scalability. As your affiliate network grows, manual management becomes difficult. Automation makes it easier to handle a larger volume of affiliates, communicate with them, and monitor their performance. This means that your affiliate program can grow without sacrificing efficiency. You can also use automation tools to track and report affiliate... Source: almost 2 years ago
  • Which tool do you use the most for SEO?
    Google Analytics: It provides in-depth insights into website traffic, user behavior, conversions, and other important metrics. Source: almost 2 years ago
  • The dos and don'ts of website redesigns and migrations
    Implement a robust website analytics tool, such as Google Analytics, to track key metrics and gather insights about user behavior. Set up goals and conversion tracking to measure the impact of your website redesign or migration on your business objectives. Source: almost 2 years ago
View more

What are some alternatives?

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

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

Matomo - Matomo is an open-source web analytics platform

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

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

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

Adobe Analytics - Adobe Analytics is an industry-leading solution that empowers you to understand your customers as people and steer your business with customer intelligence.

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