I am working on a script that uses the Twitter API to pull recent statuses from a list of users. I am able to retrieve the data using the API however upon converting it to a DataFrame, I get columns that are storing dictionaries. I want to spread the indexes of those dictionaries to additional columns. Ultimately, I am trying to save all that information to a CSV.

Here is the code:

```
import twython
import time
import pandas as pd
import numpy as np

app_key = ''
app_secret = ''
oauth_token = ''
oauth_token_secret = ''

twitter = twython.Twython(app_key, app_secret, oauth_token, oauth_token_secret)

screen_names = ['@', '@'] #enter screen names of interest

tweets = []

for screen_name in screen_names:
    tweets.extend(twitter.get_user_timeline(screen_name=screen_name, count=200))
    time.sleep(5)

df = pd.DataFrame(tweets)

```

which returns a DataFrame (400,25). `df[[2,3,5]]` returns the following:

```
     created_at                       entities                                         favorite_count
0    Thu Jun 19 13:14:39 +0000 2014  {u'symbols': [], u'user_mentions': [], u'hasht...       0
1    Thu Jun 19 11:53:51 +0000 2014  {u'symbols': [], u'user_mentions': [{u'id': 18...       0
2    Thu Jun 19 11:53:25 +0000 2014  {u'symbols': [], u'user_mentions': [], u'hasht...       3
3    Thu Jun 19 11:49:34 +0000 2014  {u'symbols': [], u'user_mentions': [], u'hasht...       0
4    Thu Jun 19 11:01:31 +0000 2014  {u'symbols': [], u'user_mentions': [{u'id': 18...       0

```

**How do I split up the `entities` column across additional columns?** For example, I'd like `symbols`, `user_mentions`, `hastags`, etc. to become additional columns in `df`. 

Any help is greatly appreciated.