Plotly Reviews

nbviewer.org Reviews

Plotly mentions (30)

• Essential Deep Learning Checklist: Best Practices Unveiled

  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

• Python equivalent to power bi/power query?

  For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 6 months ago

• Junior Developer asked to make Saaas in first month.

  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

• PSA: You don't need fancy stuff to do good work.

  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

• Wait, but I thought they were the same thing?

  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

nbviewer.org mentions (13)

• Jupyter kernel for Logtalk

  Example notebooks are included in the repo and can be previewed using nbviewer:. Source: over 1 year ago

• Is there a CodePen/OverLeaf equivalent for sharing and viewing Jupyter Notebooks/Labs

  Nbviewer (https://nbviewer.org/): very easy to use for smaller jupyter notebook that does not require heavy rendering. Source: over 1 year ago

• Collaborative Jupyter Whiteboards

  Nbconvert renders everything exactly as it looks in your notebook app into a read-only HTML version and is what GitHub uses for notebooks. Interactive plots from Bokeh, Holoviews, etc can still work if you trust the JS, and since editing notebooks while showing them during a meeting usually doesn't go well, read-only is probably good enough (eager to hear feedback on this point though). The nice thing is that... Source: over 1 year ago

• First data science project (visualization): What should I improve on?

  Just as a heads up, I used plotly to generate a lot of the charts, so you'll need to view it from an nbviewer like nbviewer.org. Source: about 2 years ago

• Can someone please review my data visualisation notebook?

  I used a lot of plotly not knowing that Github wouldn't show it, so you'll need notebook viewer like nbviewer.org to see some of the charts. Source: about 2 years ago