How can I convert results from a for loop print statement to pandas dataframe?

Question

I have built a model to see it's predictions on unseen data and this is the ending chunk. I would like to convert the results from the print function into a dataframe. How can I achieve this?

text_features = tfidf.transform(texts)
predictions = model.predict(text_features)
for text, predicted in zip(texts, predictions):
    print('"{}"'.format(text))
    print("  - Predicted as: '{}'".format(id_to_category[predicted]))
    print("")

This is the output

"Accessibility by phone !!!"
  - Predicted as: 'Communication'

"very nice"
  - Predicted as: 'Irrelevant - other'

"NO"
  - Predicted as: 'Irrelevant - other'

"nothing"
  - Predicted as: 'Irrelevant - other'

"RAS"
  - Predicted as: 'Irrelevant - other'

"pbm at the share level"
  - Predicted as: 'Irrelevant - other'

"no, not that I know"
  - Predicted as: 'Irrelevant - other'

I would like to convert this output into a dataframe.

An example would be

Text                                Predicted as

Accessability by phone              Communication

No                                  Irrelevant other

Answer 1

Try this,You can use append method in pandas .

text_features = tfidf.transform(texts)
predictions = model.predict(text_features)
df = pd.DataFrame(columns=["Text","Predicted as"])
for text, predicted in zip(texts, predictions):
    df = df.append({"Text":text,"Predicted as":id_to_category[predicted]})

Answer 2

df = pd.DataFrame(columns=['Text', 'PredictedAs'])
text_features = tfidf.transform(texts)
predictions = model.predict(text_features)

for ind, (text, predicted) in enumerate(zip(texts, predictions)):
    print('"{}"'.format(text))
    print("  - Predicted as: '{}'".format(id_to_category[predicted]))
    print("")
    df.loc[ind, 'Text'] = text
    df.loc[ind, 'PredictedAs'] = id_to_category[predicted]

Answer 3

import pandas as pd
texts = [
    "Accessibility by phone !!!",
    "very nice",
    "NO"
]
predictions = [0, 1, 1]
id_to_category = {0: "Communication", 1: "Irrelevant - other"}
predictions_as_text = [id_to_category[i] for i in predictions]
df = pd.DataFrame({"text": texts, "prediction": predictions_as_text})

I mocked some of the data, all you need is the first line and the last 2.