triangular()
is an inbuilt method of the random
module. It is used to return a random floating point number within a range with a bias towards one extreme.
Syntax : random.triangular(low, high, mode)
Parameters :
low : the lower limit of the random number
high : the upper limit of the random number
mode : additional bias; low < mode < highif the parameters are (10, 100, 20) then due to the bias, most of the random numbers generated will be closer to 10 as opposed to 100.
Returns : a random floating number
Example 1:
# import the random module import random # determining the values of the parameters low = 10 high = 100 mode = 20 # using the triangular() method print (random.triangular(low, high, mode)) |
Output :
22.614510550239572
Example 2: If we generate the number multiple times we can probably identify the bias.
# import the random module import random # determining the values of the parameters low = 10 high = 100 mode = 20 # running the triangular method with the # same parameters multiple times for i in range ( 10 ): print (random.triangular(low, high, mode)) |
Output :
58.645768016894735 46.690692250503226 33.57590419190895 52.331804090351305 33.09451214875767 12.03845752596168 32.816080679206294 20.4739124559502 82.49208123077557 63.511062284733015
Example 3: We can visualize the triangular pattern by plotting a graph.
# import the required libraries import random import matplotlib.pyplot as plt # store the random numbers in a list nums = [] low = 10 high = 100 mode = 20 for i in range ( 10000 ): temp = random.triangular(low, high, mode) nums.append(temp) # plotting a graph plt.hist(nums, bins = 200 ) plt.show() |
Output :
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.