InteractivePlots

Tutorial and introductory scripts for using HoloViews (Bokeh backend) to generate interactive plots

COW Tutoral/Getting Started:

Use tutorial files in the 'COW Tutorial' Folder

• Install Conda environment from InteractivePlots.yml file:

  conda env create —f InteractivePlots.yml

• Open in a code in a notebook (requires ipython installation for VS Code or jupyter for Jupyter Lab/Notebook)

Note: Import section of python script will require 1-2 minutes to run for first use

Supported HoloViews Functions (and Current Uses)

HoloViews Reference Gallery

• hv.Scatter (bokeh backend) HoloViews Scatter
  • 2D Models
  • Chemical Space
  • Heatmap, Bubble Plots, and Heatmap Bubble Plots
• hv.Slope (bokeh backend) HoloViews Slope
  • Linear Modeling
• hv.Area (bokeh backend, plotly dependency) Holoviews Area
  • Confidence Interval
• hv.Bars (bokeh backend) Holoviews Bars
  • Data Distribution
  • Training / Validation Splits

Possible Errors

• Hover data displays as '???'
  • JavaScript backend does not accomodate for any special characters in column names. If these are present, the column names must be changed.
• Some Bokeh color palettes cannot be found

  • If hv.extensions includes both 'bokeh' and 'matplotlib' and palette name is used by both programs (example: 'Accent'), it cannot be used. Restart notebook and remove 'matplotlib' from hv.extensions.

  • Alternatively, you can import dataframe from Bokeh directly (most cases)

    color = hv.Cycle('Category20b').values

• Matplotlib/Yellowbrick fonts not found

  import matplotlib.font_manager
  fonts = matplotlib.font_manager.findSystemFonts(fontpaths=None, fontext='ttf')
  font_names = [matplotlib.font_manager.get_font(f).family_name for f in fonts]
  import matplotlib.pyplot as plt
  plt.rcParams["font.family"] = "DejaVu Sans"  # or another font available on your system
  

• VS Code not showing plot (not seen in Jupyter Notebooks)
  • Restart VS Code