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To fill the area under the curve, put x and y with ste="pre", using fill_between() method. Plot (x, y1) and (x, y2) lines using plot() method with drawstyle="steps" method. To display the figure, use show() method.
distplot() The seaborn. distplot() function accepts the data variable as an argument and returns the plot with the density distribution. Example 1: import numpy as np import seaborn as sn import matplotlib.
I have two variables
x = [1.883830, 7.692308,8.791209, 9.262166]
y = [5.337520, 4.866562, 2.825746, 6.122449]
And I want to fit a Gaussian distribution using the seaborn wrapped for matplotlib. It seems like the sns.distplot function is the best way to do this, but I can't figure out how to fill in the area under the curve. Help?
fig, ax = plt.subplots(1)
sns.distplot(x,kde_kws={"shade":True}, kde=False, fit=stats.gamma, hist=None, color="red", label="2016", fit_kws={'color':'red'});
sns.distplot(y,kde_kws={"shade":True}, kde=False, fit=stats.gamma, hist=None, color="blue", label="2017", fit_kws={'color':'blue'})
I think the "shade" argument could be part of the fit_kws argument but I haven't gotten this to work.
Another option would be to use ax.fill()?
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