Plotly VS PostHog
Compare Plotly VS PostHog and see what are their differences
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featured
Plotly
D3.js
RAWGraphs
Tableau
Highcharts
Google Charts
Bokeh
Chart.js
PostHog
Mixpanel
Amplitude
Plausible.io
Google Analytics
Hotjar
Heap
LaunchDarkly
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 PostHogPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
PostHog is particularly well-suited for product teams, developers, and startups that require deep insights into user interactions and need the flexibility of a self-hosted solution. It is also a good fit for organizations that prioritize data privacy and want to maintain full control over their data.
Based on our record, PostHog should be more popular than Plotly. It has been mentiond 71 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.
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year 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 / about 2 years ago
This is the same model that PostHog, Supabase, and dozens of other developer tools use. Open core, with a managed offering on top. - Source: dev.to / 3 months ago
Offchain: Website traffic, in-app behaviour, marketing channels, growth campaigns (Google Analytics or PostHog). - Source: dev.to / 2 months ago
--- Title: "Validate Your Startup Idea in One Weekend: Next.js + PostHog + Stripe Test Mode" Published: true Description: "A step-by-step workshop for wiring up a landing page with analytics, a waitlist, and Stripe test-mode checkout to measure real willingness-to-pay before writing product code." Tags: typescript, api, architecture, cloud Canonical_url:... - Source: dev.to / 3 months ago
Topic PostHog (Web Vitals) Apogee Watcher Primary job Product analytics OS; Web Vitals are real-user metrics from the browser Synthetic PageSpeed monitoring + CrUX in results Instrumentation Requires posthog-js on the site No script on monitored sites Metrics FCP, LCP, INP, CLS from real sessions ($web\_vitals) when capture runs Lighthouse lab + CrUX (where available) via PSI Cookieless analytics With... - Source: dev.to / 3 months ago
PostHog provides an open-source analytics approach, giving teams flexibility to customize dashboards, session recordings, and heatmaps. - Source: dev.to / 4 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.
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
Amplitude - Chart Your Path to Growth with Digital Analytics
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.
Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure ๐ช๐บ