I have a dataframe like this:
lis = [['a','b','c'],
['17','10','6'],
['5','30','x'],
['78','50','2'],
['4','58','x']]
df = pd.DataFrame(lis[1:],columns=lis[0])
How can I write a function that says, if 'x' is in column [c], then overwrite that value with the corresponding one in column [b]. The result would be this:
[['a','b','c'],
['17','10','6'],
['5','30','30'],
['78','50','2'],
['4','58','58']]
By using .loc and np.where
import numpy as np
df.c=np.where(df.c=='x',df.b,df.c)
df
Out[569]:
a b c
0 17 10 6
1 5 30 30
2 78 50 2
3 4 58 58
This should do the trick
import numpy as np
df.c = np.where(df.c == 'x',df.b, df.c)
I am not into pandas but if you want to change the lis you could do it like so:
>>> [x if x[2] != "x" else [x[0], x[1], x[1]] for x in lis]
[['a','b','c'],
['17','10','6'],
['5','30','30'],
['78','50','2'],
['4','58','58']]
