https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.hist.html
https://matplotlib.org/stable/gallery/statistics/hist.html
Compute and draw the histogram of x. The return value is typically a tuple (n, bins, patches).
# matplotlib.pyplot.hist(x, bins=None, range=None, density=False, weights=None, # cumulative=False, bottom=None, histtype='bar', align='mid', # orientation='vertical', rwidth=None, log=False, color=None, label=None, # stacked=False, *, data=None, **kwargs) # # x : input values, an array or a sequence of arrays # bins : int or sequence or str (default: 10) # range : tuple or None; the lower and upper range of the bins # density : bool; if True then the area under the histogram will sum to 1 # histtype : {'bar', 'barstacked', 'step', 'stepfilled'} # align : {'left', 'mid', 'right'} # orientation : {'vertical', 'horizontal'} # label : a string for the legend
# histogram1.py import numpy as np import matplotlib.pyplot as plt x = np.random.uniform(0.0, 10.0, 100) #plt.hist(x, bins=10) plt.hist(x, bins=10, density=True) # `density=False` (default) would make counts plt.ylabel('Probability') plt.xlabel('Data') plt.title('Histogram') plt.grid(True) plt.show()