Mailmodo
Loops.so
MailerLite
MailChimp
Moda
Customer.io
Stripo
Selzy
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
At Mailmodo, we are building the future of marketing and transactional emails. With Mailmodo, businesses will be able to add web-like interactivity like forms, survey, calendar, likes, comments, etc. right inside emails to their users. This will help them to engage their users better and achieve a higher conversion rate from their emails.
Mailmodo MatplotlibBased on our record, Matplotlib seems to be a lot more popular than Mailmodo. While we know about 114 links to Matplotlib, we've tracked only 2 mentions of Mailmodo. 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.
Yeah, the ability to do this is ~3 years old, so there are few no-code tools, and it's expensive to do in house. None of the no-code tools that do exist are verticalized around eCommerce. Check out mailmodo.com for an example of a horizontally positioned company in the space. Source: over 3 years ago
Mailmodo helps marketers create app-like experiences in email by adding forms, shopping cart, calendar, NPS and more widgets within the email without any coding. Our interactive emails reduce the number of steps for users, thereby increasing email conversions by ~3x for brands like Razorpay, Cleartax, etc. You can use it to collect feedback from your users, book meetings with prospects, recover abandon carts,... Source: over 4 years ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 7 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
Loops.so - We bought a billboard in Times Square and we're letting you advertise your startup on it!It's free.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
MailerLite - Affordable Email Marketing Software. Get all features (Segmentation, Automation, A/B testing) for up to 1,000 subscribers & send unlimited emails for free!
NumPy - NumPy is the fundamental package for scientific computing with Python
MailChimp - MailChimp is the best way to design, send, and share email newsletters.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.