Pandas Set on copy warning when using .loc - pandas

Question

I'm trying to change the values in a column of a dataframe based on a condition.
In [1]:df.head()
Out[2]: gen cont
timestamp
2012-07-01 00:00:00 0.293 0
2012-07-01 00:30:00 0.315 0
2012-07-01 01:00:00 0.0 0
2012-07-01 01:30:00 0.005 0
2012-07-01 02:00:00 0.231 0
I want to set the 'gen' column to NaN whenever the sum of the 2 columns is below a threshold of 0.01, so what I want is this:
In [1]:df.head()
Out[2]: gen cont
timestamp
2012-07-01 00:00:00 0.293 0
2012-07-01 00:30:00 0.315 0
2012-07-01 01:00:00 NaN 0
2012-07-01 01:30:00 NaN 0
2012-07-01 02:00:00 0.231 0
I have used this:
df.loc[df.gen + df.con <0.01 ,'gen'] = np.nan
It gives me the result I want but with the warning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
I am confused because I am using .loc and I think I'm using it in the way suggested.

Answer 1

For me your solution works nice.
Alternative solution with mask, it by default add NaN if condition True:
df['gen'] = df['gen'].mask(df['gen'] + df['cont'] < 0.01)
print (df)
timestamp gen cont
0 2012-07-01 00:00:00 0.293 0
1 2012-07-01 00:30:00 0.315 0
2 2012-07-01 01:00:00 NaN 0
3 2012-07-01 01:30:00 NaN 0
4 2012-07-01 02:00:00 0.231 0
EDIT:
You need copy.
If you modify values in df later you will find that the modifications do not propagate back to the original data (df_in), and that Pandas does warning.
df = df_in.loc[sDate:eDate].copy()