Software Alternatives & Reviews

Sightengine VS Pandas

Compare Sightengine VS Pandas and see what are their differences

Sightengine logo Sightengine

Effortless moderation of user-submitted photos. Instantly detect nudity and adult content with our easy-to-use API, for a fraction of the cost of human moderation

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
  • Sightengine Landing page
    Landing page //
    2023-10-20
  • Pandas Landing page
    Landing page //
    2023-05-12

Sightengine videos

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Pandas videos

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Category Popularity

0-100% (relative to Sightengine and Pandas)
Image Processing
100 100%
0% 0
Data Science And Machine Learning
Image Analysis
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 Sightengine and Pandas

Sightengine Reviews

  1. Very happy with their content moderation

    We were looking for a scalable way to moderate all our images and text messages. Very happy with the Sightengine integration: very flexible in terms of how and what you filter, works great for us! We started with "standard" moderation and then created our own workflow with all our rules (community rules & guidelines). They do automated moderation only from what I understand.

    👍 Pros:    Easy integration|High performance|Many built-in features
    👎 Cons:    Lack support by phone|Saas

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Social recommendations and mentions

Based on our record, Pandas seems to be a lot more popular than Sightengine. While we know about 198 links to Pandas, we've tracked only 2 mentions of Sightengine. 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.

Sightengine mentions (2)

Pandas mentions (198)

  • AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
    Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 11 days ago
  • Pandas reset_index(): How To Reset Indexes in Pandas
    In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 5 days ago
  • Deploying a Serverless Dash App with AWS SAM and Lambda
    Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
  • Stuff I Learned during Hanukkah of Data 2023
    Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
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What are some alternatives?

When comparing Sightengine and Pandas, you can also consider the following products

PicPurify - Real-time image moderation API which accurately detects inappropriate images containing specific elements like porn, nudity, violence, drugs, weapons... Our goal is to identify those images in user generated content and remove them automatically.

NumPy - NumPy is the fundamental package for scientific computing with Python

Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.

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

Amazon Rekognition - Add Amazon's advanced image analysis to your applications.

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