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Data Miner VS statsmodels

Compare Data Miner VS statsmodels and see what are their differences

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incident management, error monitoring, alerting, on-call, devops, developer tools, webhooks, mobile 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. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Data Miner logo Data Miner

Data Miner is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.

statsmodels logo statsmodels

Statsmodels: statistical modeling and econometrics in Python - statsmodels/statsmodels
  • Data Miner Landing page
    Landing page //
    2021-10-14
  • statsmodels Landing page
    Landing page //
    2023-08-18

Data Miner features and specs

  • User-Friendly Interface
    Data Miner offers a clean and intuitive user interface that allows users to easily navigate and set up web scraping tasks without requiring extensive technical knowledge.
  • Browser Extension
    Being available as a browser extension for both Chrome and Edge makes it easy to install and use directly within the browser, without needing separate software installations.
  • Pre-built Recipes
    Data Miner provides a library of pre-built recipes for common web scraping tasks, enabling users to quickly deploy scrapers without starting from scratch.
  • Custom Recipes
    Users have the option to create custom recipes, offering flexibility and the ability to tailor scraping tasks to specific needs.
  • Cloud Storage
    Offers cloud storage options that allow users to save and manage their scraped data directly on the platform for easy access and organization.
  • Export Options
    Supports multiple export formats like CSV, XLS, and Google Sheets, making it easy for users to integrate scraped data with other tools and workflows.
  • Scheduling
    Allows users to schedule scraping tasks, automating the data collection process at specified intervals.

Possible disadvantages of Data Miner

  • Limited Free Tier
    The free version of Data Miner is limited in terms of the number of rows and pages that can be scraped, which may not be sufficient for more extensive data collection needs.
  • Learning Curve
    While the interface is user-friendly, there can still be a learning curve for users unfamiliar with web scraping concepts and the tool itself.
  • Browser Dependence
    As Data Miner is a browser extension, its functionality is limited to the browser environment, which might not be ideal for more complex or large-scale web scraping tasks.
  • Potential Website Restrictions
    Some websites actively prevent scraping activities, which could limit the effectiveness of Data Miner on certain web pages.
  • Subscription Cost
    Advanced features and higher usage requirements necessitate a subscription plan, which may be costly for individual users or small businesses.
  • Reliance on Internet Stability
    As an online tool, its performance can be hindered by poor internet connectivity, potentially disrupting the scraping process.

statsmodels features and specs

No features have been listed yet.

Analysis of Data Miner

Overall verdict

  • Data Miner is generally considered a good tool for individuals and businesses that need to quickly and easily extract large amounts of data from websites without the need for advanced technical skills. It is appreciated for its ease of use and effectiveness in various scenarios.

Why this product is good

  • Data Miner (dataminer.io) is a web scraping tool that allows users to extract data from websites into various formats such as CSV or Excel. It is known for its user-friendly interface and does not require any programming skills, making it accessible to many users. Additionally, it offers a number of ready-made scraping recipes and the ability to create custom ones, adding flexibility to its use.

Recommended for

  • Researchers
  • Marketers
  • Data Analysts
  • Business Professionals
  • Anyone needing to automate data extraction from websites

Analysis of statsmodels

Overall verdict

  • statsmodels is a robust, well-established open-source Python library for statistical modeling, offering rigorous implementations of a wide range of statistical methods with strong documentation and academic credibility.

Why this product is good

  • Comprehensive coverage of statistical models including linear regression, generalized linear models, time series analysis (ARIMA, VAR), and mixed effects models
  • Provides detailed statistical output such as p-values, confidence intervals, and diagnostic tests, which is often lacking in machine-learning-focused libraries
  • Well-integrated with the broader scientific Python ecosystem including NumPy, SciPy, and pandas
  • Open-source with an active community, thorough documentation, and extensive examples
  • Emphasizes statistical rigor and inference rather than just prediction, making results interpretable and defensible

Recommended for

  • Statisticians and data scientists who need detailed statistical inference and hypothesis testing
  • Researchers and academics performing econometric or time series analysis
  • Analysts who require interpretable model outputs like coefficients, p-values, and confidence intervals
  • Python users who want R-like statistical modeling capabilities
  • Educational settings teaching applied statistics and econometrics

Data Miner videos

+ Add

Data Miner 4.0

statsmodels videos

+ Add

Linear Regressions with StatsModels

More videos:

  • Review - Code review - Z Test using statsmodels
  • Review - Code Review: Analyse Training VAR statsmodels with a real world dataset

Category Popularity

0-100% (relative to Data Miner and statsmodels)

Data Miner

statsmodels

Web Scraping
100 100%
Web Scraping
0% 0
Application Builder
0 0%
Application Builder
100% 100
Data Extraction
100 100%
Data Extraction
0% 0
Development Tools
0 0%
Development Tools
100% 100

User comments

Share your experience with using Data Miner and statsmodels. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Data Miner should be more popular than statsmodels. It has been mentiond 7 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.

Data Miner mentions (7)

  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Data Miner - A browser extension (Google Chrome, MS Edge) for data extraction from web pages CSV or Excel. The free plan gives you 500 pages/month. - Source: dev.to / over 2 years ago
  • What's something you'd like to see implemented on AO3?
    The web app at https://dataminer.io/. If you open it on your Saved for Later page, it should show you a public "recipe" that I made to scrape the data. Possibly others as well. Source: over 3 years ago
  • free-for.dev
    Data Miner - A browser extension (Google Chrome, MS Edge) for data extraction from web pages CSV or Excel. The free plan gives you 500 pages/month. - Source: dev.to / almost 4 years ago
  • Need help exporting references from CENTRAL
    Ungh, annoying. There are lots of free scraping tools you could play with like https://dataminer.io but I have no idea how practical that approach will be for you. Source: almost 4 years ago
  • Are cover letters super important in getting internships and jobs?
    Go on your states licensure website, look up the directory of licensed professionals and use a data mining tool (https://dataminer.io/) to scrape the website of all the emails or everyone who's licensed. Source: about 4 years ago
View more

statsmodels mentions (4)

  • [P] statsmodels.tsa.holtwinters.ExponentialSmoothing results in NaN forecasts and parameters when fitting on entire dataset using known parameters from training model.
    I reckon you're more likely to get a good response on their Github page than here. Unless a dev happens to see this post. Source: over 3 years ago
  • How do you usually build your models?
    Since you are using python, pandas, scikit-learn, scipy, and statsmodels are what you are looking for. Source: almost 4 years ago
  • Can we solve serverless cold starts?
    In case you're really worried about cold start latency and your application load shows high variance in the number of concurrent requests, you might want to get a bit fancier. You could use time-series forecasting to anticipate how many containers should be warmed at each point in time. StatsModels is an open-source project that offers the most common algorithms for working with time-series. Here's a good... - Source: dev.to / about 5 years ago
  • Advice required to choose appropriate software for an assignment
    Can't you get a student discount for Stata? R would definitely be able to handle everything. For Python, have a look through the statsmodel package https://github.com/statsmodels/statsmodels. Source: over 5 years ago

What are some alternatives?

When comparing Data Miner and statsmodels, you can also consider the following products

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

Ionic - Ionic is a cross-platform mobile development stack for building performant apps on all platforms with open web technologies.

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

Material UI - A CSS Framework and a Set of React Components that Implement Google's Material Design

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

Flutter - Build beautiful native apps in record time ๐Ÿš€

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