<reponame>kavya2812/class-109
import plotly.figure_factory as ff
import plotly.graph_objects as go
import statistics
import random
#Creating a list of sum of 2 dice, rolled 1000 times
dice_result = []
for i in range(0, 1000):
    dice1 = random.randint(1, 6)
    dice2 = random.randint(1, 6)
    dice_result.append(dice1 + dice2)
#Calculating the mean and the standard deviation
mean = sum(dice_result) / len(dice_result)
std_deviation = statistics.stdev(dice_result)
median = statistics.median(dice_result)
mode = statistics.mode(dice_result)
fig = ff.create_distplot([dice_result], ["Result"], show_hist=False)
fig.show()
print("Mean of this data is {}".format(mean))
print("Median of this data is {}".format(median))
print("Mode of this data is {}".format(mode))
print("Standard deviation of this data is {}".format(std_deviation))

print("Mean of this data is {}".format(mean))
import plotly.figure_factory as ff
import plotly.graph_objects as go
import statistics
import random
#Creating a list of sum of 2 dice, rolled 1000 times
dice_result = []
for i in range(0, 1000):
    dice1 = random.randint(1, 6)
    dice2 = random.randint(1, 6)
    dice_result.append(dice1 + dice2)
#Calculating the mean and the standard deviation
mean = sum(dice_result) / len(dice_result)
std_deviation = statistics.stdev(dice_result)
median = statistics.median(dice_result)
mode = statistics.mode(dice_result)
fig = ff.create_distplot([dice_result], ["Result"], show_hist=False)
fig.show()
print("Mean of this data is {}".format(mean))
print("Median of this data is {}".format(median))
print("Mode of this data is {}".format(mode))
print("Standard deviation of this data is {}".format(std_deviation))

print("Mean of this data is {}".format(mean))
#Creating a list of sum of 2 dice, rolled 1000 times #Calculating the mean and the standard deviation