Our platform plugin and integrations enable stores to print labels, automate international paperwork, display real-time courier rates, and offer their customers dynamic tax and duties at checkout.
Easyship makes shipping globally so simple, that anyone can get started in a couple clicks. Online sellers can leverage over 250+ shipping solutions and 50+ couriers, while saving up to 70% on shipping rates. Growing businesses can also join their network of more than 20+ 3PL partners worldwide, giving them the opportunity to provide faster delivery to overseas customers.
Based on our record, Plotly seems to be a lot more popular than Easyship. While we know about 30 links to Plotly, we've tracked only 1 mention of Easyship. 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.
When I do go back to selling on eBay, I plan to remove GSP and instead offer direct shipping to the buyer using FedEx International Priority. I have a duties calculator provided by easyship.com that gives reasonably close duties estimates. I do not want to use USPS since I paid for their fastest service (Express Int'l) only to have the item sit in chicago for an entire month before it moved again to to buyer's... Source: over 3 years ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 22 days ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 7 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: about 1 year ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago
I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: over 1 year ago
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