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: 
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
]})

```
Simpler, and will turn the Series back into lists so you can stack, unstack, etc:

```
df['column_name'] = df['column_name'].apply(set).apply(list)

```