Watershed
Greenly
Climatebase π
Neutral
Electricity Map
GreenFrame
Carbon Visualiser
Senseible.earth
Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
Plotly 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.
Based on our record, Plotly should be more popular than Watershed. It has been mentiond 34 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.
We use DuckDB extensively where I work (https://watershed.com), the primary way we're using it is to query Parquet formatted files stored in GCS, and we have some machinery to make that doable on demand for reporting and analysis "online" queries. - Source: Hacker News / over 3 years ago
Watershed (https://watershed.com), platform for enterprises to reduce carbon emissions. - Source: Hacker News / over 4 years ago
Here's why I'm asking β Watershed, a new carbon accounting tool that recently raised $60m, was spun out of Stripe. Patch.io, an API-first offsets marketplace, has strong ties to Plaid. And Bend, a CO2e emissions data API that I'm working on, grew out of Abacus, an expense management app. Source: over 4 years ago
Your best bet with your current skillset (assuming you're more SWE-oriented) would be to join forward-looking startups and companies in the climate space. There's plenty of startups that are in need of engineers, and it would surprise you that a lot of them are relatively well-funded (e.g. https://watershedclimate.com/, funded by Stripe founders and Kleiner Perkins). Alternatively, you can probably join as a SWE... Source: over 4 years ago
There are software companies working on this already, checkout https://watershedclimate.com/. Source: over 4 years ago
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 / 6 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 / almost 2 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 / about 2 years ago
Greenly - Front page of the Green Revolution.
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.
Climatebase π - Discover climate tech jobs, organizations, & events π
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
Neutral - Offset your carbon emissions, right from your shopping cart
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.
