I have a csv file on with millions of rows. I used to create a dictionary out the csv file like this

```
 with open('us_db.csv', 'rb') as f:
    data = csv.reader(f)
    for row in data:
       Create Dictionary based on a column

```

Now to filter the rows based on some conditions I use pandas Dataframe as it is super fast in these operations. I load the csv as pandas Dataframe do some filtering. Then I want to continue doing the above. I thought of using pandas **df.iterrows()** or **df.itertuples()** but it is really slow. 

Is there a way to convert the pandas dataframe to csv.reader() directly so that I can continue to use the above code. If I use `csv_rows = to_csv()`, it gives a long string. Ofcourse, I can write out a csv and then read from it again. But I want to know if there is a way to skip the extra read and write to a file.