Question: I am trying to remove the duplicate strings in a list of strings under a column in a Pandas DataFrame. 

For example; the list value of:

```
[btc, btc, btc]

```

Should be;

```
[btc]

```

I have tried multiple methods however, none seems to be working as I am unable access the string values in the list. Any help is much appreciated.

DataFrame:

```
          dollar_sign  followers_count  \
0                   [btc]            35946
1                   [btc]            35946
2                   [btc]            35946
3                   [nav]            35946
4         [btc, btc, btc]            35946

```

Access the list of strings under a column

```
for row in df_twitter['dollar_sign']:
    print row

```

Output:

```
[btc]
[btc]
[btc]
[nav]
[btc, btc, btc]

```

Answer: 
From the information revealed, I believe OP's df is actually not full of list of strings but strings that look like a list.

From the OP's print result, we see

```
[btc]
[btc]
[nav]
[btc, btc,btc]

```

However, if it is of lists of strings, it should yield

```
['btc']
['btc']
['btc']
['nav']
['btc', 'btc', 'btc']

```

Solution: 

```
df = pd.DataFrame({
        'dollar_sign':['[btc]','[btc]','[btc]','[nav]','[btc, btc, btc]'],
        'followers_count':[35946,35946,35946,35946,35946]}
     )

df.dollar_sign.str[1:-1].str.split(",\s").map(set)

0    {btc}
1    {btc}
2    {btc}
3    {nav}
4    {btc}
Name: dollar_sign, dtype: object

```

* `.str[1:-1]` removes `[` and `]`.
* `str.split(",\s")` splits with ", ", a comma and a space. (Assuming the strings use ", " as the delimiter, otherwise, you may need `"\s*,\s*"` or something even more sophisticated.)
* `map(set)` turns each list into a set.
You can using `list` with `map` , and `set` can get the unique value 

```
df['dollar_sign']=list(map(set,df['dollar_sign']))
df
Out[1068]: 
  dollar_sign  followers_count
0       {btc}            35946
1       {btc}            35946
2       {btc}            35946
3       {nav}            35946
4       {btc}            35946

```

This is how I create the df 

```
df=pd.DataFrame({'dollar_sign':[['btc'],['btc'],['btc'],['nav'],['btc','btc','btc']],'followers_count':[35946,35946
,35946
,35946
,35946
]})

```