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## Import Numpy and check version import numpy as np print ( f Numpy version is { np . _ _ version _ _
## Import Numpy and check version
import numpy as np
printfNumpy version is npversion
Numpy version is
Random numbers are frequently used in Data Science.
Generating random numbers or rather pseudorandom numbers is an important function.
Numpy provides a random number module called numpy.random.
Create a random number generator called myrng using the defaultrng method in nprandom. Use the default seed.
:
# Write your code below.
Now use myrng to generate a X numpy array of random values.
Print out this array
:
# Write your code below.
:
Use the Numpy array created above to create a second Numpy array of random numbers that is between and
This question requires you to figure out the mapping that will convert a set of random numbers that are distributed as found in the previous question to have the range from to
The form of the distributon does not change.
:
# Show your code below.
nprandom can also generate random integers. Generate a X array of random integers between and
:
# Your code here.
nprandom can also generate various common distributions. Generate a X array of numbers from a normal distribution with mean and standard deviation
:
# Your code here
Call the X matrix of normal random variables generated in the last step gm
Use Numpy methods to create two other numpy arrays, rowsum and colsum:
rowsum should be the length array of the sum of the rows of gm
colsum should be the length array of the sum of the columns of gm
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