Replace NaT in a dataframe with a previous variable

Question

how can I replace NaT from a dataframe with a date/variable that was created (setup) before?

I got the following dataframe:

     Date            Name         CF
0        NaT         Peter       -10
0 2017-12-14         Peter       -20
1        NaT         Tomas       -5.5
1 2017-12-15         Peter       -25
2        NaT         Tomas       -3
2 2017-12-14         Tomas       -5
3        NaT         Walker      -4.6
3 2017-12-15         Tomas        88
4 2017-12-15         Tomas       -30
5 2017-12-15         Walker       15

I would like to replace NaT with a variable that was setup at the beginning of my Project: anEnd variable like this:

format_date = "%d-%m-%Y"
end = datetime.date(2017, 12, 15)

I tried two approaches: First, I used np.where from Pandas, but it does not recognize the NaT. Second, I tried this

test = table_final2.Date.astype(object).where(table_final2.Date.notnull(), end)

but this results in a mix of formats for the column Date

         Date              Name      CF
0           2017-12-15     Peter    -10
0  2017-12-14 00:00:00     Peter    -20
1           2017-12-15     Tomas    -5.5
1  2017-12-15 00:00:00     Peter    -25
2           2017-12-15     Tomas    -3
2  2017-12-14 00:00:00     Tomas    -5
3           2017-12-15     Walker   -4.6
3  2017-12-15 00:00:00     Tomas     88
4  2017-12-15 00:00:00     Tomas    -30
5  2017-12-15 00:00:00     Walker    15

So, how can I replace NaT accurately? Thanks in advance!

PD: when test.dtypes shows Date as an object.

Answer 1

IIUC you can use Series.fillna() method:

In [138]: end = pd.to_datetime('2017-12-15')

In [139]: df['Date'] = df['Date'].fillna(end)

In [140]: df
Out[140]:
        Date    Name    CF
0 2017-12-15   Peter -10.0
0 2017-12-14   Peter -20.0
1 2017-12-15   Tomas  -5.5
1 2017-12-15   Peter -25.0
2 2017-12-15   Tomas  -3.0
2 2017-12-14   Tomas  -5.0
3 2017-12-15  Walker  -4.6
3 2017-12-15   Tomas  88.0
4 2017-12-15   Tomas -30.0
5 2017-12-15  Walker  15.0