It is just that visualizations are not a solved thing yet.
* What kind of plot do I want? Bar chart? Scatter plot? Boxplot? Pick the geom based on this.
* What column goes on each axis? Do I need to transform the axis? For e.g., is log scale better?
* Do I split data by some other column? Use different colors/fill, shapes, or facets.
* Do I need any annotations to point out interesting parts of the plot?
GGPlot and Plotnine are joy to work with once you grok the ideas of tidy data and grammar of graphics. Since the API is consistent, experimentation can be quick:
* That scatter plot looks to busy? Change the geom to a boxplot.
* Want to see if an attribute has any predictive power? Assign it to any unused aesthetic.
Seaborn can provide some higher-level functions compared to plotnine/ggplot like pair-plot. But as you said, you need to lookup seaborn's documentation all the time to work with it.