[FIXED] How to combine/union two separate numpy Gaussian sets?

Issue

I want to combine two separate random Gaussian data sets, one with its own mean and std and the other with an outlier mean and std. My code that I have is this:

import random
import numpy as np
import numpy.random as ra
from numpy.random import seed 

#This makes the random numbers generated not change when rerunning the code
np.random.seed(0)

#Creating two Gaussian sets, one with mean 0 and std 1, the second is outlier with mean 3 and std 1
#Each set contains 1,000 trials, first set contains 99 points while outlier set contains 1 point for each trial (for 1% outlier)

data = np.random.normal(loc=0, scale=1, size=(1000, 99))
dataoutlier = np.random.normal(loc=3, scale=1, size=(1000, 1))

Now how can I combine this so the outlier numbers are with the first set for each trial? I thought using np.union1d would work, but that combines all the trials into one giant array. Any help would be very appreciated!

Solution

In order to combine two numpy arrays by column you might use the append method.

np.append(data, dataoutlier, axis=1)

Answered By - Grzegorz

Answer Checked By - Gilberto Lyons (PHPFixing Admin)