CODEWITHSUNDEEP
pythonpandasdataframerandom
Zephyr
Zephyr

Reputation: 1352

Random value for each row in pandas data Frame

Hi I have the following data frames:

import numpy as np
import pandas as pd
df = pd.DataFrame()
df['T1'] = ['A','B','C','D','E']
df['T2'] = ['G','H','I','J','K']
df['Match'] = df['T1'] +' Vs '+ df['T2']
Nsims = 5
df1 = pd.DataFrame((pd.np.tile(df,(Nsims,1))))

I created two new columns T1_point and T2_point by summing of five random numbers. when I do as follow: it gave me the same number for all rows. 

Ninit = 5
df1['T1_point'] = np.sum(np.random.uniform(size=Ninit))
df1['T2_point'] = np.sum(np.random.uniform(size=Ninit))

What I wanted to do is that I would like to get different values for each row by using random number.

How could I do that?

Thanks

Zep.

Upvotes: 3

Views: 14538

Answers (2)

Mark Andersen
Mark Andersen

Reputation: 1028

The list comprehension answer is not optimal.

A simpler and more efficient answer is to use the size parameter available in numpy which creates a matching array:

import numpy as np
df1['RAND'] = np.random.randint(1,10000000, size=len(df1))

Upvotes: 2

ajsp
ajsp

Reputation: 2670

What you are basically asking is for a random number in each row. Just create a list of random numbers then and append them to your dataframe?

import random

df1['RAND'] = [ random.randint(1,10000000)  for k in df1.index]

print df1

    0  1     RAND
0   A  G  6850189
1   B  H  3692984
2   C  I  8062507
3   D  J  6156287
4   E  K  7037728
5   A  G  7641046
6   B  H  1884503
7   C  I  7887030
8   D  J  4089507
9   E  K  4253742
10  A  G  8947290
11  B  H  8634259
12  C  I  7172269
13  D  J  4906697
14  E  K  7040624
15  A  G  4702362
16  B  H  5267067
17  C  I  3282320
18  D  J  6185152
19  E  K  9335186
20  A  G  3448703
21  B  H  6039862
22  C  I  9884632
23  D  J  4846228
24  E  K  5510052

Upvotes: 10

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