Avoid memory error and reduce the processing time
#### Code Sample, a copy-pastable example if possible

```python

temp_list = [i for i in range(1, 1441)]

df_daypart = pd.DataFrame(columns=temp_list)

 for index, row in df_1.iterrows():
    for element in temp_list:
        if element == row['begin_day_part']:
            for item in range(row['begin_day_part'], row['end_day_part']+1):
                df_daypart.loc[index, item] = 60
            print "Time required " + str(datetime.now() - temp_time)
            break


```
#### Problem description
So, I have a DataFrame(df_1) with shape as (3785649, 5) somewhat like below

Household | Individual | Channel | begin_day_part | end_day_part
-- | -- | -- | -- | --
123 | 1 | ABC | 657 | 687
456 | 1 | DEF | 705 | 706
789 | 1 | ABC | 706 | 761
1122 | 1 | DEF | 761 | 762
1455 | 1 | ABC | 762 | 769
1788 | 1 | DEF | 769 | 770
2121 | 1 | ABC | 770 | 794
2454 | 1 | DEF | 795 | 797
2787 | 1 | ABC | 797 | 798
3120 | 1 | DEF | 798 | 799
3453 | 1 | ABC | 799 | 800
3786 | 1 | DEF | 800 | 815
4119 | 1 | ABC | 825 | 826
4452 | 1 | DEF | 826 | 892
4785 | 1 | ABC | 892 | 893
5118 | 1 | DEF | 893 | 894
5451 | 1 | ABC | 894 | 927
5784 | 1 | DEF | 927 | 928
6117 | 1 | ABC | 928 | 933

I want to add some fixed value in a rows of dataframe (df_daypart) where loop starts from df_1['begin_day_part] upto df_1['end_day_part].

Since, it's big data the looping takes 30 minutes and sometime I face 'Memory Error' too.
Therefore, I'm looking for a way by which I can eliminate 'memory Error' completely and if possible reduce processing time to 10 minutes.

Right solution is always welcome. 

Thanks in advance!