calculate p-values from cdf and show them in a graph
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I have plotted the cdf of my dataset. I would like to know find out some p-values (probabilities), I could do it looking at the graph, however, I would like to know if there is a way to do it with a python code and show it in the graph. I have the following code x = np.sort(df['Consumption KW']) y = np.arange(1,len(x)+1)/len(x) plt.plot(x,y,marker='.',linestyle='none', label='Consumption KW') And I get something like this: However, I would like to calculate the value of KW (x-axis) with a probability of 93% (I other words when the CDF(0.93)). The following graph shows what I want but with another data set: Does anybody know how to calculate p-values and show them on a graph as aforementioned? It would be of great help! Thanks
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