Plotly
D3.js
Chart.js
Highcharts
Google Charts
RAWGraphs
Tableau
Microsoft Power BI
PostHog
Mixpanel
June
Amplitude
Segment
ObsidianLaunch.co
Plausible.io
Countly
For developers just starting out, PostHog is a free way to understand how your product is being used, without having to send any data to 3rd parties.
For enterprise customers, one data security becomes a key concern, or B2C businesses where using a SaaS solution is unaffordable, it's typical to see teams hosting an event capture platform, a data lake, and sophisticated analytics tools. The end result is that data scientists are needed and most developers don't have easy access to product intel. PostHog solves that gap - it lets everyone understand how your product is being used, without having to send data to 3rd parties, even once you have scaled to millions of visitors.
It has a JS snippet that can autocapture events, and pre-built libraries to push backend data to. Build up full user histories, visualize product trends, funnels, and run experiments with new features.
Plotly PostHogBased on our record, PostHog should be more popular than Plotly. It has been mentiond 46 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.
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 / 6 days ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 6 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: about 1 year ago
It would be a shame not to mention PostHog as the telemetry provider we are using, since it turned out to be extremely useful. Because it is hard to find people who will talk with you about your product, gathering statistics gave us a much greater insight into our users. - Source: dev.to / 2 months ago
PostHog - Full Product Analytics suite free for up to 1m tracked events per month. - Source: dev.to / 5 months ago
Don't insert the logs/events/analytics into your Application DB. Usually, you send those to specialist datastores (OLAP etc) that process such high volume of data. You can use something like clickhouse [0] for example or use 3rd party SAAS solutions like posthog [1] etc that are built on top of clickhouse [0] https://clickhouse.com [1] https://posthog.com. - Source: Hacker News / 8 months ago
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable. Now... Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application... - Source: Hacker News / 9 months ago
PostHog | Remote (US/Europe timezones) | Full stack engineer, technical ex-founder, tech lead | https://posthog.com or email us careers@posthog.com [0] https://posthog.com/handbook/. - Source: Hacker News / 12 months ago
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.
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
Chart.js - Easy, object oriented client side graphs for designers and developers.
June - Instant analytics reports, built on top of Segment
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
Amplitude - Mobile analytics: come with questions, leave with answers