I read a csv file containing 150,000 lines into a pandas dataframe. This dataframe has a field, `Date`, with the dates in `yyyy-mm-dd` format. I want to extract the month, day and year from it and copy into the dataframes' columns, `Month`, `Day` and `Year` respectively. For a few hundred records the below two methods work ok, but for 150,000 records both take a ridiculously long time to execute. Is there a faster way to do this for 100,000+ records?

First method: 

```
df = pandas.read_csv(filename)
for i in xrange(len(df)): 
   df.loc[i,'Day'] = int(df.loc[i,'Date'].split('-')[2])

```

Second method: 

```
df = pandas.read_csv(filename)
for i in xrange(len(df)):
   df.loc[i,'Day'] = datetime.strptime(df.loc[i,'Date'], '%Y-%m-%d').day

```

Thank you.