In This Article, You Will Learn About Numpy Uniform Distribution.
Numpy Uniform Distribution – Before moving ahead, let’s know a bit of Python Numpy Poisson Distribution
Describe the possible chances to occur every task equal times.
E.g., Probabilities of generating random numbers at equal times.
It includes three parameters:
a - Lower Bound. Default value is 0.0. b - Upper Bound. Default value is 1.0. size - The shape of the returned array.
Example – Create a 3×2 uniform distribution sample.
from numpy import random
x = random.uniform(size=(3, 2))
print(x)
Output - [[0.27732781 0.06429024] [0.08773632 0.58586866] [0.38442203 0.65052188]]
As shown above, it returned an array of shape 3×2 containing random decimal numbers.
Note: You will learn in detail later about Uniform Distribution Tutorial.
Visualization of Uniform Distribution
Example – Visualizing the Uniform Distribution graph without histogram.
from numpy import random
import matplotlib.pyplot as plt
import seaborn as kl
kl.distplot(random.uniform(size=1000), hist=False)
plt.show()
As a result, it Visualized the Uniform Distribution graph.
Example – Visualizing the Uniform Distribution graph with histogram.
from numpy import random
import matplotlib.pyplot as plt
import seaborn as kl
kl.distplot(random.uniform(size=1000))
plt.show()
As shown above, it Visualized the Uniform Distribution graph.
If you find anything incorrect in the above-discussed topic and have any further questions, please comment below.
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