Hi there,
I have a small dataset with just 80 datapoints and I am trying to plot a histogram with a normal distrubution curve on top of it. When I run the following code in Jupyter notebook, I got a nice distribution of the values. (first photo)
However, when I run the same code in Power BI using the Python visual, I get a totally different histogram. I checked populating a table with the data I am using for the histogram which seems correct, so the data in Power BI is correct but for some reason the visual doesnt depict the same data.Does anyone know why this is happening?
Also, if I dont filter out the one negative value in the dataset, the histogram seems to be pretty close to the actual result but as soon as I filter the one record with the negative value, the histogram changes completely in values.
Code:
import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt
import pandas as pd
plt.hist(dataset.UCS_PoissonsRatio, bins = 33, density = False, edgecolor = "#FFFFFF")
mu, std = norm.fit(dataset.UCS_PoissonsRatio)
xmin, xmax = plt.xlim()
x = np.linspace(xmin, xmax, 100)
p = norm.pdf(x, mu, std)
plt.plot(x, p, 'k', linewidth=2) plt.xlabel("Poisson Ratio")
plt.ylabel("Frequency")
plt.show()
