Based on our record, Plotly should be more popular than Blazer. It has been mentiond 29 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.
I try to avoid these tools wherever possible, given the choice I'd always go for tools like Blazer. https://github.com/ankane/blazer No such luck in my current role, Looker and PowerBI are both in use by different bits of the org and nobody has the ability to delve into the underlying figures. - Source: Hacker News / 2 months ago
As u/jaxn said you could use Blazer for this kind of thing. I would also look into materialized views or custom tables and a scheduled job that calculates the metrics they care about. That will take you a long way. Eventually you can use something like Metabase but I would put that off for as long as possible as it's really expensive and pretty involved. Source: 10 months ago
And it's Open Source: https://github.com/evidence-dev/evidence if you are into the Ruby on Rails world. It's super solid, and it's been an indispensable tool integrated to all my projects. - Source: Hacker News / about 1 year ago
I use Ahoy too, but I don't have very good visibility into the data. I should spend more time building queries and creating charts. I should probably set up blazer as well: https://github.com/ankane/blazer. - Source: Hacker News / almost 2 years ago
The Blazer gem provides a nice way to analyze the results easily. It is simple to install and allows SQL queries to run against tables. The query here shows that the candidate implementation is significantly faster than the original. - Source: dev.to / almost 2 years ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 5 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: 12 months 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: almost 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: about 1 year ago
Plotly Dash is a great framework for developing interactive data dashboards using Python, R, and Javascript. It works alongside Plotly to bring your beautiful visualizations to the masses. - Source: dev.to / over 1 year ago
Metabase - Metabase is the easy, open source way for everyone in your company to ask questions and learn from...
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Chart.js - Easy, object oriented client side graphs for designers and developers.
Chartbrew - Create interactive dashboards and reports from your databases, APIs, and 3rd party services. Supporting MySQL, Postgres, MongoDB, Firestore, Customer.io, and more. Chartbrew is 100% open source and can be self-hosted for free.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application