Have you tried the ci argument? According to the documentation: ci : float or None, optional Size of confidence intervals to draw around estimated values. If None, no bootstrapping will be performed, and error bars will not be drawn. sns.barplot(x=df[‘Time’], y=df[‘Volume_Count’], ax=ax7, ci=None)
Outlier display You should be able to pass any arguments to seaborn.boxplot that you can pass to plt.boxplot (see documentation), so you could adjust the display of the outliers by setting flierprops. Here are some examples of what you can do with your outliers. If you don’t want to display them, you could do seaborn.boxplot(x=”centrality”, … Read more
In current versions of matplotlib you can do: boxplot([1,2,3,4,5,10], showfliers=False) or boxplot([1,2,3,4,5,10], sym=”) In older versions, only the second approach will work. The docs for boxplot do mention this, btw as, “Enter an empty string (‘’) if you don’t want to show fliers.”, though, at least for myself, “outliers” is the more familiar word.
You can get what handles/labels should exist in the legend before you actually draw the legend itself. You then draw the legend only with the specific ones you want. import matplotlib.pyplot as plt import seaborn as sns import pandas as pd tips = sns.load_dataset(“tips”) sns.stripplot(x=”day”, y=”total_bill”, hue=”smoker”, data=tips, jitter=True, palette=”Set2″, dodge=True, linewidth=1, edgecolor=”gray”) # Get … Read more