Mutiplying dataframe by -1 loses data

I have an issue and I have no idea what is causing it.. I have a very very simply dataframe which looks like the following;

            A   B
01/01/2022 -34 -102.34
02/01/2022 -4  -89.23
03/01/2022 -78 -43.2
.
.
.
31/12/2022 -32 -34.21

I simply need to convert this dataframe to positive numbers.
When I do this with a simple;

df = df * -1

A column multiples but the B column loses its’ data to the following;

            A   B
01/01/2022 34 
02/01/2022 4  
03/01/2022 78 
.
.
.
31/12/2022 32 

I assume this is something to do with interger vs float64 but just can’t crack it.

Any help much appreciated!

>Solution :

You likely have strings in your data, multiplying a string by an integer less than 1 converts to empty string:

df = pd.DataFrame({'A': [0,1,2], 'B': [0,'1',2]})
df*-1

output:

   A   B
0  0   0
1 -1    
2 -2  -2

Workaround: convert to_numeric:

df.apply(pd.to_numeric, errors='coerce')*-1

# or
# df.astype(float)*-1

output:

   A  B
0  0  0
1 -1 -1
2 -2 -2