'>' not supported between instances of 'str' and 'int'

First make sure that all value of survey_df_clean['text'] is the same, if you want to convert as numeric, do this :

survey_df_clean['text'] = pd.to_numeric(survey_df_clean['text'])

Then do this

survey_df_clean.loc[survey_df_clean['text']>30].shape

survey_df_clean['text'] might have NAN or str values in it some where. to find out :

survey_df_clean['text'].isnull().sum()

if they are,first take care of them then apply

print (survey_df_clean[survey_df_clean['text']>30].shape)

I had the same error message when trying to use that conditional. What intrigued me was that the same command had run correctly on another notebook.

The difference was in how I read the csv file. This was the troublesome one:

df=pd.read_csv('data.csv')

And when I put the decimal argument it worked:

df=pd.read_csv('data.csv', decimal=',')

Obviously, it'll depend on how your data is organized. ;)

This is because values in 'text' column are of type str and you are comparing str with int. You can do a quick check for getting type of 'text' column.

print(type(survey_df_clean['text'][:1][0]))

For comparing you can do as following

survey_df_clean[survey_df_clean['text'].astype(int)>30]