Common plotting pitfalls that get worse with large data¶
When working with large datasets, visualizations are often the only way available to understand the properties of that dataset -- there are simply too many data points to examine each one! Thus it is very important to be aware of some common plotting problems that are minor inconveniences with small datasets but very serious problems with larger ones.
- Underutilized range
- Nonuniform colormapping
You can skip to the end if you just want to see an illustration of these problems.
conda install holoviews colorcet matplotlib scikit-image
We'll first load the plotting libraries and set up some defaults:
import numpy as np np.random.seed(42) import holoviews as hv from holoviews.operation.datashader import datashade from holoviews import opts, dim hv.extension('matplotlib') from colorcet import fire datashade.cmap=fire[50:]