Reputation: 171
I have a dataframe as below. I am trying to check if there is 0 or 1 in the vector column, if yes, add 10 to the vector and divide by adding 2 to the vector otherwise keep the same vector.
df = pd.DataFrame({'user': ['user 1', 'user 2', 'user 3'],
'vector': [[0.01, 0.07, 0.0, 0.14, 0.0, 0.55, 0.11],
[0.12, 0.27, 0.1, 0.14, 0.1, 0.09, 0.19],
[0.58, 0.07, 0.02, 0.14, 0.04, 0.06, 1]]})
df
Output:
user vector
0 user 1 [0.01, 0.07, 0.0, 0.14, 0.0, 0.55, 0.11]
1 user 2 [0.12, 0.27, 0.1, 0.14, 0.1, 0.09, 0.19]
2 user 3 [0.58, 0.07, 0.02, 0.14, 0.04, 0.06, 1]
I used the following code:
df['vector']=df.apply(lambda x: x['vector']+10/(x['vector']+2) if x['vector']==0|1 else x['vector'], axis=1)
But the Output:
user vector
0 user 1 [0.01, 0.07, 0.0, 0.14, 0.0, 0.55, 0.11]
1 user 2 [0.12, 0.27, 0.1, 0.14, 0.1, 0.09, 0.19]
2 user 3 [0.58, 0.07, 0.02, 0.14, 0.04, 0.06, 1]
The expected output:
Upvotes: 2
Views: 120
Reputation: 260300
Use a list comprehension (faster than apply
):
df['vector'] = [[x+10/(x+2) if x in [0,1] else x for x in v] for v in df['vector']]
Output:
user vector
0 user 1 [0.01, 0.07, 5.0, 0.14, 5.0, 0.55, 0.11]
1 user 2 [0.12, 0.27, 0.1, 0.14, 0.1, 0.09, 0.19]
2 user 3 [0.58, 0.07, 0.02, 0.14, 0.04, 0.06, 4.333333333333334]
Upvotes: 4