CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
user7565295
user7565295

Reputation:

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

I encountered the error

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

while trying to print the below lines in Pandas dataframe

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

Should I try to convert them to int and how would that work in this statement?

Upvotes: 6

Views: 73503

Answers (5)

Paulo U
Paulo U

Reputation: 11

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. ;)

Upvotes: 1

Arjun Singh
Arjun Singh

Reputation: 1

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]

Upvotes: 0

Fariliana Eri
Fariliana Eri

Reputation: 301

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

Upvotes: 6

Athar Noraiz
Athar Noraiz

Reputation: 491

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)

Upvotes: 1

zimmerrol
zimmerrol

Reputation: 4951

This message suggests, that you try to compare a string object (str) with an integer (int). The expression

survey_df_clean['text']

will probably return a string. Therefore, you cannot directly compare it with the number 30. If you want to compare the length of the entry, you can use the pandas.Series.str.len() operation as you can see here.

If this field should actuallty contain an integer, you can use this method (pandas.to_numeric) to cast it from str to int.

Upvotes: 3

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