Select 50 items from list at random
Question:
I have a function which reads a list of items from a file. How can I select only 50 items from the list randomly to write to another file?
def randomizer(input, output='random.txt'):
query = open(input).read().split()
out_file = open(output, 'w')
random.shuffle(query)
for item in query:
out_file.write(item + 'n')
For example, if the total randomization file was
random_total = ['9', '2', '3', '1', '5', '6', '8', '7', '0', '4']
and I would want a random set of 3, the result could be
random = ['9', '2', '3']
How can I select 50 from the list that I randomized?
Even better, how could I select 50 at random from the original list?
Answers:
If the list is in random order, you can just take the first 50.
Otherwise, use
import random
random.sample(the_list, 50)
random.sample
help text:
sample(self, population, k) method of random.Random instance
Chooses k unique random elements from a population sequence.
Returns a new list containing elements from the population while
leaving the original population unchanged. The resulting list is
in selection order so that all sub-slices will also be valid random
samples. This allows raffle winners (the sample) to be partitioned
into grand prize and second place winners (the subslices).
Members of the population need not be hashable or unique. If the
population contains repeats, then each occurrence is a possible
selection in the sample.
To choose a sample in a range of integers, use xrange as an argument.
This is especially fast and space efficient for sampling from a
large population: sample(xrange(10000000), 60)
I think random.choice()
is a better option.
import numpy as np
mylist = [13,23,14,52,6,23]
np.random.choice(mylist, 3, replace=False)
the function returns an array of 3 randomly chosen values from the list
One easy way to select random items is to shuffle then slice.
import random
a = [1,2,3,4,5,6,7,8,9]
random.shuffle(a)
print a[:4] # prints 4 random variables
Say your list has 100 elements and you want to pick 50 of them in a random way. Here are the steps to follow:
- Import the libraries
- Create the seed for random number generator, I have put it at 2
- Prepare a list of numbers from which to pick up in a random way
- Make the random choices from the numbers list
Code:
from random import seed
from random import choice
seed(2)
numbers = [i for i in range(100)]
print(numbers)
for _ in range(50):
selection = choice(numbers)
print(selection)
-
we have 3 samples (‘orange’,’mango’,’apple’). Created series, should contain 7 elements & randomly selected from list.
random.choice
import random
import numpy as np
fruits = ['orange','mango','apple']
np.random.choice(fruits, 7, replace=True)
Output
array(['orange', 'mango', 'apple', 'orange', 'orange', 'mango', 'apple'],
dtype='<U6')
-
Random selection from list (less than 3 values)
random.sample
import random
random.sample(fruits, 3)
I have a function which reads a list of items from a file. How can I select only 50 items from the list randomly to write to another file?
def randomizer(input, output='random.txt'):
query = open(input).read().split()
out_file = open(output, 'w')
random.shuffle(query)
for item in query:
out_file.write(item + 'n')
For example, if the total randomization file was
random_total = ['9', '2', '3', '1', '5', '6', '8', '7', '0', '4']
and I would want a random set of 3, the result could be
random = ['9', '2', '3']
How can I select 50 from the list that I randomized?
Even better, how could I select 50 at random from the original list?
If the list is in random order, you can just take the first 50.
Otherwise, use
import random
random.sample(the_list, 50)
random.sample
help text:
sample(self, population, k) method of random.Random instance
Chooses k unique random elements from a population sequence.
Returns a new list containing elements from the population while
leaving the original population unchanged. The resulting list is
in selection order so that all sub-slices will also be valid random
samples. This allows raffle winners (the sample) to be partitioned
into grand prize and second place winners (the subslices).
Members of the population need not be hashable or unique. If the
population contains repeats, then each occurrence is a possible
selection in the sample.
To choose a sample in a range of integers, use xrange as an argument.
This is especially fast and space efficient for sampling from a
large population: sample(xrange(10000000), 60)
I think random.choice()
is a better option.
import numpy as np
mylist = [13,23,14,52,6,23]
np.random.choice(mylist, 3, replace=False)
the function returns an array of 3 randomly chosen values from the list
One easy way to select random items is to shuffle then slice.
import random
a = [1,2,3,4,5,6,7,8,9]
random.shuffle(a)
print a[:4] # prints 4 random variables
Say your list has 100 elements and you want to pick 50 of them in a random way. Here are the steps to follow:
- Import the libraries
- Create the seed for random number generator, I have put it at 2
- Prepare a list of numbers from which to pick up in a random way
- Make the random choices from the numbers list
Code:
from random import seed
from random import choice
seed(2)
numbers = [i for i in range(100)]
print(numbers)
for _ in range(50):
selection = choice(numbers)
print(selection)
-
we have 3 samples (‘orange’,’mango’,’apple’). Created series, should contain 7 elements & randomly selected from list.
random.choice
import random import numpy as np fruits = ['orange','mango','apple'] np.random.choice(fruits, 7, replace=True)
Output
array(['orange', 'mango', 'apple', 'orange', 'orange', 'mango', 'apple'], dtype='<U6')
-
Random selection from list (less than 3 values)
random.sample
import random random.sample(fruits, 3)