Conditionally Set Entire Row to NaN/None in Pandas

Question

I have a DataFrame indexed by date. I would like to be able to Null out all rows where the index is greater than some value (like today) but keep them in the DataFrame. What's the best way to do this? For instance this

10/20/16  15, 20
10/25/16  13, 12
10/30/16  16, 15

#--> 10/30/16 should go to NaN, NaN

Answer 1

Solution with DataFrame.mask, for mask is necessary same index as df:

#convert index to datetime
df.index = pd.to_datetime(df.index)

mask = pd.Series(df.index > pd.datetime.today(), index=df.index)
print (mask)
Date
2016-10-20    False
2016-10-25    False
2016-10-30     True
dtype: bool

df = df.mask(mask)
print (df)
               a     b
Date                  
2016-10-20  15.0  20.0
2016-10-25  13.0  12.0
2016-10-30   NaN   NaN

Answer 2

df.loc[df.index > pd.datetime.today()] = np.nan
df