```
df_clean['message'] = df_clean['message'].apply(lambda x: gensim.parsing.preprocessing.remove_stopwords(x))

```

I tried this on a dataframe's column 'message' but I get the error: 

```
TypeError: decoding to str: need a bytes-like object, list found

```
['https://Stackoverflow.com/questions/62387623', 'https://Stackoverflow.com', 'https://Stackoverflow.com/users/10608841/']
Apparently, the `df_clean["message"]` column contains a list of words, not a string, hence the error saying that `need a bytes-like object, list found`. 

To fix this issue, you need to convert it to string again using `join()` method like so:

```
df_clean['message'] = df_clean['message'].apply(lambda x: gensim.parsing.preprocessing.remove_stopwords(" ".join(x)))

```

Notice that the `df_clean["message"]` will contain string objects after applying the previous code.
What the error is saying is that *remove\_stopwords* needs **string** type object and you are passing a **list**, So before removing *stop words* check that all the values in column are of string type. [See the Docs](https://radimrehurek.com/gensim/parsing/preprocessing.html#gensim.parsing.preprocessing.remove_stopwords)