Conditional replacement of objects in a pandas dataframe

Question

I have 2 dataframes df_1 and df_2. Both have an index datetimecodewhich is a pd.datetime64 object, and a temp column. I want to iterate through df_1 and replace all the NaN temperature values with the corresponding temp from 'df_2'.

Something like this:

for index, row in df_1.iterows():
      row['temp'] = df_2[index]['temp'] if row['temp'] ==np.nan

but this is invalid sytax

Answer 1

Is this what you're looking for:

df_1 = pd.DataFrame({'temp': [1,2,3,np.nan,5,np.nan,7]})
   temp
0   1.0
1   2.0
2   3.0
3   NaN
4   5.0
5   NaN
6   7.0

df_2 = pd.DataFrame({'temp': [8,9,10,11,12,13,14]})
   temp
0     8
1     9
2    10
3    11
4    12
5    13
6    14

df_1.temp.fillna(df_2['temp'], inplace=True)

   temp
0   1.0
1   2.0
2   3.0
3  11.0
4   5.0
5  13.0
6   7.0

   temp
0     8
1     9
2    10
3    11
4    12
5    13
6    14

Answer 2

IIUC

df_1.fillna(df_2, inplace=True)

or

df_1.loc[df_1.temp.isnull(), 'temp'] = df_2.temp

---

demonstration

tidx = pd.date_range('2016-03-31', periods=5)
df_1 = pd.DataFrame(dict(temp=[1, np.nan, 3, np.nan, 5]), tidx)
df_2 = pd.DataFrame(dict(temp=np.arange(11, 16)), tidx)

df_1.fillna(df_2)

df_1.loc[df_1.temp.isnull(), 'temp'] = df_2.temp

df_1