Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
Hoodmaps
Mapme
Mapiful
Avoid Tourist
YouMap
Snap
Craft & Oak
500 Earth
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.
Hoodmaps is recommended for travelers, city newcomers, urban planners, and anyone interested in understanding the cultural nuances of urban neighborhoods through the eyes of the community.
Based on our record, Plotly should be more popular than Hoodmaps. 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.
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
That's hood maps: https://hoodmaps.com/new-york-city-neighborhood-map. Source: over 3 years ago
There is a whole crowdsourced site for this called https://hoodmaps.com. It's pretty good. Source: about 4 years ago
Hoodmaps.com is good for this kind of question. Note the areas in CDMX marked "danger", "don't ever go here, EVER" "Say goodbye to your iPhone", "why are you here run for your life"... Avoid those areas. Source: about 4 years ago
Hoodmaps.com is great if you want to know the area you will be moving into. Source: over 4 years ago
Ever seen hoodmaps? You should contribute! It looks like Charlottesville doesn't have a presence on here yet. Source: over 4 years 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.
Mapme - Build smart and beautiful maps within minutes with no coding
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
Mapiful - Create & order custom printed maps of your favorite places
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.
Avoid Tourist - A crowdsourced map of touristy places to avoid 🗺️