DontPayFull is a multinational coupon business headquartered in Romania with a strong service presence in the United States, United Kingdom, Canada, and Australia. It provides free coupons and discount offers to consumers doing their shopping online.
Founders: The DontPayFull project was founded by Andrei Vasilescu and Adrian Cristea in 2012.
Employees: There are 27 full-time employees that work here and over 100 external collaborators that discover coupons and deals.
Clients: A few of the brands DontPayFull works with include Amazon, NewEgg, Macy's, Target, and Walmart.
Tools created: Amazon Discount Finder allows consumers to find coupons and discount offers directly from the Amazon website.
The affiliate networks that DontPayFull collaborates with for coupons and deals monetization are: CJ Affiliate, Rakuten Advertising, Awin, ShareASale, TradeDoubler AB, Skimlinks, VigLink, WebGains, Pepperjam, Impact Tech Inc., AvantLink, Performance Horizon Group Limited.
DontPayFull is a Corporate Member of the Performance Marketing Association since August 2016.
Media appearances: DontPayFull has appeared in publications such as MoneyPantry, DollarSprout, Well Kept Wallet, Yahoo! Finance, GoBanking Rates, and Reader's Digest.
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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I've used DontPayFull as well as TopCashBack a lot to save on the new year's sales. A lot of the deals work well.
I was able to find a coupon for the store I was shopping at and was able to save a significant amount of money on my purchase. I will definitely be using this website in the future and would recommend it to anyone looking for a way to save money on their online shopping.
Based on our record, Pandas seems to be more popular. It has been mentiond 219 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 2 months 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 / 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
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