DataFrame write information to specific column and row in a loop-CodePudding

I am quite new to Pandas and would like to find out how I can read and then write to a DataFrame row by from in a loop.

Input information

Index lemmatized_text MulNB
1     item inexpens   NaN
2     overall exper   NaN
3     screen n't co   NaN
4     screen not co   NaN
5     've view nume   NaN

Create the pandas DataFrame

df10 = pd.DataFrame(data, columns = ['MulNB', 'lemmatized_text'])

Attempted code to loop through the information:

for i in range(1,len(df10)):
    test=df10['lemmatized_text'].loc[i]
    df10['MulNB'].loc[i]=model.predict(vec.transform(test))
    i =1

Currently it iterates until line 10 and then it stops and shows the following:

Thank you for any assistance on this.

CodePudding user response：

Instead of the loop, you could use apply:

df10['MulNB'] = df10['lemmatized_text'].apply(lambda test: model.predict(vec.transform([test])))

but then again, it may be more efficient to use a list comprehension.

df10['MulNB'] = [model.predict(vec.transform([test])) for test in df10['lemmatized_text']]

I don't know how your model is set up but if it's a text mining model, I think it should be vectorized:

df10['MulNB'] = model.predict(vec.transform(df10['lemmatized_text']))

CodePudding user response：

To update/iterate over rows in Panadas Dataframe I would recommend you to checkout iterrows() provided by Pandas.

for i, row in df10.iterrows():
    test = df10.loc[i,'lemmatized_text']
    df10.loc[i,'MulNB'] = model.predict(vec.transform(test))

Other Alternative is to use List Comprehension.