How to update an existing column of a dataframe based on values in another column?

In python, I’m dealing with a sales data of about 21,000 houses. Each house (row) has columns ‘sqft_living’ (int64), and ‘grade’ (int64) among others.
I want to increase the ‘grade’ of every house by 2 if its sqft_living > 400, or by 1 otherwise.
How do I do this?

>Solution :

df = pd.DataFrame()
df['sqft_living'] = [x for x in range(396, 405)]
df['grade'] = [x for x in range(9)]
df

So we have:

sqft_living     grade
0   396     0
1   397     1
2   398     2
3   399     3
4   400     4
5   401     5
6   402     6
7   403     7
8   404     8

We apply the condition:

df['grade'] = df.apply( lambda row: row.grade + 1 if row.sqft_living < 400 else row.grade + 2 , axis=1)
df

New dataframe:

sqft_living     grade
0   396     1
1   397     2
2   398     3
3   399     4
4   400     6
5   401     7
6   402     8
7   403     9
8   404     10