I have a custom function that creates a scatterplot:
def scatterplot(df): enrich,number=separate_types(df) fig=plt.figure(1) axes=plt.gca() plt.xlabel("P") plt.ylabel("E") for i in range(len(enrich)): if enrich["Treatment"][i]=="C": color="tab:blue" else: color="tab:orange" plt.errorbar(x=number["mean"][i],y=enrich["mean"][i],yerr=enrich["stdev"][i],xerr=number["stdev"][i],color=color,marker=".",label=enrich["Treatment"][i]) handles, labels = plt.gca().get_legend_handles_labels() by_label = dict(zip(labels, handles)) plt.legend(by_label.values(), by_label.keys()) return(fig)
The idea is to get a scatterplot that has x errors and y errors on it, as well as a color scheme based on a different column.
I’ve noticed that if I were to do use d1 (of 5 points total) like this:
And then another d2 (of 5 points total) like this:
I’d get 1 plot with 10 points. I want 2 plots with 5 points (each belonging to d1 and d2). How do I modify the function to accomodate this?
The documentation highlights why this behavior happens.
fig=plt.figure(1) you create a new figure if there is no other figure with the same identifier. In your case, this means the
1. In your case, the figure with the identifier with the
1 is always restored and no new figure is created.
From the documentation:
num: int or str or Figure, optional A unique identifier for the figure. If a figure with that identifier already exists, this figure is made active and returned. An integer refers to the Figure.number attribute, a string refers to the figure label.