matplotlib hist function argmument density not working

Question

plt.hist's density argument does not work.

I tried to use the density argument in the plt.hist function to normalize stock returns in my plot, but it didn't work.

The following code worked fine for me and give me the probability density function which I desired.

import matplotlib
import numpy as np
import matplotlib.pyplot as plt

np.random.seed(19680801)

# example data
mu = 100  # mean of distribution
sigma = 15  # standard deviation of distribution
x = mu + sigma * np.random.randn(437)

num_bins = 50

plt.hist(x, num_bins, density=1)

plt.show()

But when I tried it with stock data, it simply didn't work. The result gave the unnormalized data. I didn't find any abnormal data in my data array.

import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
plt.hist(returns, 50,density = True)
plt.show()
# "returns" is a np array consisting of 360 days of stock returns

Answer 1

This is a known issue in Matplotlib.

As stated in Bug Report: The density flag in pyplot.hist() does not work correctly

When density = False, the histogram plot would have counts on the Y-axis. But when density = True, the Y-axis does not mean anything useful. I think a better implementation would plot the PDF as the histogram when density = True.

The developers view this as a feature not a bug since it maintains compatibility with numpy. They have closed several the bug reports about it already with since it is working as intended. Creating even more confusion the example on the matplotlib site appears to show this feature working with the y-axis being assigned a meaningful value.

What you want to do with matplotlib is reasonable but matplotlib will not let you do it that way.

Answer 2

It is not a bug. Area of the bars equal to 1. Numbers only seem strange because your bin sizes are small