My biggest problem with ggplot is that it&#x27;s slow, unbearably slow. It also enforces all data to be realized into a single dataframe, which is true only for small (as is: fits in memory) datasets.<p>Very often, to produce specialized plots, I have to send data to the canvas in chunks by performing pre-processing myself. ggplot really doesn&#x27;t work in this scenario. Combined with the general slowness, it forces me to use alternatives quite frequently.<p>It&#x27;s a bummer, really, because I&#x27;d like my plots to have a consistent visual style, and doing that across different plotting packages is an issue.<p>I very often resort to gnuplot when it comes to huge datasets and&#x2F;or incremental plotting. The same is true also in python (matplotlib is also very slow, independently of the backend). But at least, if you use seaborn (<a href="https:&#x2F;&#x2F;github.com&#x2F;mwaskom&#x2F;seaborn" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;mwaskom&#x2F;seaborn</a>), you can easily intermix the easiness of plotting through a DataFrame or just supply data arrays.<p>ggplot is really awesome for what it does, but 1) the syntax doesn&#x27;t really please me (feels just plainly forced onto the wrong context 2) doesn&#x27;t scale, which forces me to use alternatives too frequently 3) trying to customize the plot style beyond a few minor tweaks is pure hell.