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import.io VS statsmodels

Compare import.io VS statsmodels and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

import.io logo 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.

statsmodels logo statsmodels

Statsmodels: statistical modeling and econometrics in Python - statsmodels/statsmodels
  • import.io Landing page
    Landing page //
    2023-06-12
  • statsmodels Landing page
    Landing page //
    2023-08-18

import.io features and specs

  • Ease of Use
    Import.io offers a user-friendly interface that allows users to easily extract data without needing to write code, making it accessible for non-technical users.
  • Data Integration
    The platform provides robust integration options with various analytics and data storage tools, enabling seamless data workflows.
  • Scalability
    Import.io can handle large volumes of data efficiently, making it suitable for both small and large-scale data extraction projects.
  • Speed
    The tool is designed to extract data quickly, minimizing the time required to obtain and process large datasets.
  • Data Transformation
    Offers features for data transformation and cleaning, allowing users to manipulate the data to fit their needs before export.

Possible disadvantages of import.io

  • Cost
    Import.io can be expensive, especially for businesses or users requiring extensive data extraction and processing capabilities.
  • Learning Curve for Advanced Features
    While basic features are easy to use, mastering the more advanced functionalities can require a significant amount of time and effort.
  • Limited Customization
    There are constraints on customization, which could be limiting for users with complex or highly specific data extraction needs.
  • Occasional Stability Issues
    Users have reported occasional performance and stability issues, which can cause interruptions during data extraction processes.
  • Dependency on Web Structure
    The tool is highly dependent on the structure of the target websites. Any changes in the website's layout can disrupt data extraction processes and require reconfiguration.

statsmodels features and specs

No features have been listed yet.

import.io videos

+ Add

mobile review extraction using import.io

More videos:

  • Review - Import.io Infinite Scroll Website Data Extraction

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 import.io and statsmodels)

import.io

statsmodels

Web Scraping
100 100%
Web Scraping
0% 0
Development Tools
0 0%
Development Tools
100% 100
Data Extraction
100 100%
Data Extraction
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100

User comments

Share your experience with using import.io 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, statsmodels should be more popular than import.io. It has been mentiond 4 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.

import.io mentions (2)

  • Woke up in hella good mood - I guess weekend - how are y’all
    Sort of, import.io is a portion. This could also automate tasks on your local computer as well. Source: over 4 years ago
  • Offering help for Free: If anyone's trying to get a custom internal tool built, I can Help
    This should be possible. But I think you can do this faster with import.io and google sheets. DM me, we'll figure it out. Source: over 4 years ago

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: almost 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: about 3 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 4 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 4 years ago

What are some alternatives?

When comparing import.io and statsmodels, you can also consider the following products

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 🚀

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

python wiki - Component Libraries

ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.

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

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