Distill is a web monitoring tool. It can monitor RSS feeds, a webpage or a part of webpage. Alerts in the form of pop-up, audio or emails can be received.
Featured highlights:
• Content selection from any webpage including iframes. • Supported actions: • Push notifications on phone • Pop-up • Audio • Email • SMS • Webhook • Easy to use inbox style Watchlist with label, trash etc. • Conditions for smart actions. • History of previous changes for each monitor. • Powerful expressions to select source content. Supports XPath expression, CSS rule or JavaScript expression to select content. • View highlighted changes.
Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
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One of the best tools I have used to keep track of changes on my competitors website. I love the chrome extension and its ease of use.
Based on our record, Pandas seems to be a lot more popular than Distill Web Monitor. While we know about 219 links to Pandas, we've tracked only 2 mentions of Distill Web Monitor. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 1 month ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 10 months ago
I haven't used any in recent years so I'm not up to speed with the pros/cons of each, but PageProbe, SiteDelta Watch, and Distill Web Monitor are a few to try. Source: about 3 years ago
I’ve had pretty good luck with the distill web monitor https://distill.io/apps/web-monitor. Source: about 4 years ago
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