CODEWITHSUNDEEP
python-3.xpandasnumpyrandom
KubiK888
KubiK888

Reputation: 4723

How to specify a random seed while using Python's numpy random choice?

I have a list of four strings. Then in a Pandas dataframe I want to create a variable randomly selecting a value from this list and assign into each row. I am using numpy's random choice, but reading their documentation, there is no seed option. How can I specify the random seed to the random assignment so every time the random assignment will be the same?

service_code_options = ['899.59O', '12.42R', '13.59P', '204.68L']
df['SERVICE_CODE'] = [np.random.choice(service_code_options ) for i in df.index]

Upvotes: 15

Views: 21177

Answers (3)

medium-dimensional
medium-dimensional

Reputation: 2253

According to the notes of numpy.random.seed in numpy v1.2.4:

Best practice is to use a dedicated Generator instance rather than the random variate generation methods exposed directly in the random module.

Such a Generator is constructed using np.random.default_rng.

Thus, instead of np.random.seed, the current best practice is to use a np.random.default_rng with a seed to construct a Generator, which can be further used for reproducible results.

Combining jezrael's answer and the current best practice, we have:

import pandas as pd 
import numpy as np 

rng = np.random.default_rng(seed=121)

df = pd.DataFrame({'a':range(10)})

service_code_options = ['899.59O', '12.42R', '13.59P', '204.68L']
df['SERVICE_CODE'] = rng.choice(service_code_options, size=len(df))

print(df)

   a SERVICE_CODE
0  0       12.42R
1  1       13.59P
2  2       12.42R
3  3       12.42R
4  4      899.59O
5  5      204.68L
6  6      204.68L
7  7       13.59P
8  8       12.42R
9  9       13.59P

Upvotes: 6

jezrael
jezrael

Reputation: 862681

You need define it before by numpy.random.seed, also list comprehension is not necessary, because is possible use numpy.random.choice with parameter size:

np.random.seed(123)

df = pd.DataFrame({'a':range(10)})

service_code_options = ['899.59O', '12.42R', '13.59P', '204.68L']
df['SERVICE_CODE'] = np.random.choice(service_code_options, size=len(df))
print (df)
   a SERVICE_CODE
0  0       13.59P
1  1       12.42R
2  2       13.59P
3  3       13.59P
4  4      899.59O
5  5       13.59P
6  6       13.59P
7  7       12.42R
8  8      204.68L
9  9       13.59P

Upvotes: 12

piRSquared
piRSquared

Reputation: 294278

Documentation numpy.random.seed

np.random.seed(this_is_my_seed)

That could be an integer or a list of integers

np.random.seed(300)

Or

np.random.seed([3, 1415])

Example

np.random.seed([3, 1415])

service_code_options = ['899.59O', '12.42R', '13.59P', '204.68L']
np.random.choice(service_code_options, 3)

array(['899.59O', '204.68L', '13.59P'], dtype='<U7')

Notice that I passed a 3 to the choice function to specify the size of the array.

numpy.random.choice

Upvotes: 3

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