How I can get the vectors for words that were not present in word2vec vocabulary?

Question

I have check the previous post link but it doesn't seems to work for my case:-

I have pre trained word2vec model:

import gensim    
model = Word2Vec.load('w2v_model')

Now I have a pandas dataframe with keywords:

keyword
corruption
people
budget
cambodia
.......
......

All I want to add the vectors for each keyword in its corresponding columns but when I use model['cambodia'] it throw me error as KeyError: "word 'cambodia' not in vocabulary"

so I have update the keyword as:

model.train(['cambodia'])

But this won't work out for me, when I use model['cambodia']

it still giving an error as KeyError: "word 'cambodia' not in vocabulary". How to update new words into word2vec vocabulary so i can get its vectors? Expected output will be:-

keyword    V1         V2          V3         V4            V5         V6   
corruption 0.07397  0.290874    -0.170812   0.085428    -0.148551   0.38846 
people      ..............................................................
budget      ...........................................................

Answer 1

You can initial the first vector as [0,0,...0]. And the word that not in vocabulary can set to 0.

keyword    V1         V2          V3         V4            V5         V6  
0          0          0           0           0           0           0
1       0.07397  0.290874    -0.170812   0.085428    -0.148551   0.38846 
2      ..............................................................
3      ...........................................................

You can use two dicts to solve the problem.

word2id['corruption']=1 
vec['corruption']=[0.07397 0.290874 -0.170812 0.085428 -0.148551 0.38846]
 ...
word2id['cambodia']=0 
vec['cambodia']=[0 0 0 0 0 0]