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def sentiment_analyzer_scores(sentence):
    for sentence in df['clean_text']:
        score =analyser.polarity_scores(sentence)

        print({<40{}".format(sentence,str(score)))

print(sentiment_analyzer_scores(df['clean_text'])

This is the code I want to put the output into a dataframe what do I do?

2
  • 1
    use return - but you woulnd need first put all values in list and then return list. OR concatenate all strings in one string. Commented Jan 24, 2020 at 6:14
  • 1
    do you want to put in the same DataFrame in new column? Maybe you should use .apply() Commented Jan 24, 2020 at 6:19

2 Answers 2

1

In general you can create a new column in this way:

import pandas as pd
df = pd.DataFrame({'col':['hello', 'bye']})
df['len'] = df['col'].apply(len)
print(df)

Output:

     col  len
0  hello    5
1    bye    3

In your case I think that something like this should work:

df['new_column'] = df['clean_text'].apply(analyser.polarity_scores)

where polarity_scoresis the function that you want to apply

Or something like this:

df['new_column'] = df['clean_text'].apply(lambda x:"{}<40{}".format(x, str(analyser.polarity_scores(x))))
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Comments

0

To get data from function you would have to keep all strings on list - without print() and use return to return it

def sentiment_analyzer_scores(data):
    results = []
    for sentence in data:
        score = analyser.polarity_scores(sentence)
        text = "{<40{}".format(sentence, str(score))
        results.append(text)

    return results

df['results'] = sentiment_analyzer_scores(df['clean_text'])

or in new DataFrame

results = sentiment_analyzer_scores(df['clean_text'])
new_df = pd.DataFrame(results)

But maybe you should use .apply() instread of for-loop

More or less

def sentiment_analyzer_scores(sentence):
    score = analyser.polarity_scores(sentence)
    returm "{<40{}".format(sentence, str(score))

df['results'] = df['clean_text'].apply(sentiment_analyzer_scores)

or in new DataFrame

results = df['clean_text'].apply(sentiment_analyzer_scores)
new_df = pd.DataFrame(results)

Comments

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