Based on our record, Pandas seems to be a lot more popular than Bokeh. While we know about 197 links to Pandas, we've tracked only 5 mentions of Bokeh. 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.
Visualization: https://docs.bokeh.org/en/latest/. Source: almost 2 years ago
Now that we can get task timing information in a consistent manner, let’s do some plotting. For this, I’m going to use Bokeh which generates nice interactive plots. - Source: dev.to / about 2 years ago
Bokeh The Bokeh library is native to Python and is mainly used to create interactive, web-ready plots, which can be easily output as HTML documents, JSON objects, or interactive web applications. Like ggplot, its concepts are also based on the Grammar of Graphics. It has the added advantage of managing real-time data and streaming. This library can be used for creating common charts such as histograms, bar plots,... - Source: dev.to / over 2 years ago
It's not in the least bit "underrated" and it's documentation is extensive. Source: almost 3 years ago
Hi guys! I am currently working on a project to enrich my Master thesis with some interactive plots. I have been using the Bokeh library to make a standalone application, which I was then planning to deploy in Heroku. You can find the code in this repository. But I will also add it at the bottom of the post. Source: about 3 years ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / about 22 hours ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / about 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 4 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential. - Source: dev.to / 5 months ago
Plotly - Low-Code Data Apps
NumPy - NumPy is the fundamental package for scientific computing with Python
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.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
OpenCV - OpenCV is the world's biggest computer vision library