How in Pandas Dataframe and Python can extract the specific text string after a given word?

Question

I would like to extract the text inside the range "text: ....." from this dataframe and create another column with that value.

This is my Pandas Dataframe

issues_df['new_column'] = issues_df['fields.description.content'].apply(lambda x: x['text'])

However, it returns the following error:

issues_df['new_column'] = issues_df['fields.description.content'].apply(lambda x: x['text'])
TypeError: Object 'float' is not writable.

Any suggestions?

Thanks in advance.

Please [do not upload images of code/data/errors when asking a question](http://meta.stackoverflow.com/q/285551) and provide a [minimal reproducible example](https://stackoverflow.com/help/minimal-reproducible-example), including a small example input data and the corresponding expected result. — Pierre D, Aug 09 '22 at 15:05
the column values are list not object try to change `x["text"]` to `x[0]["content"][0]["text"]` — Mouad Slimane, Aug 09 '22 at 15:08
perhaps this helps https://stackoverflow.com/questions/51660357/extract-substring-between-two-characters-in-pandas/51660658#51660658 — Yuca, Aug 09 '22 at 15:12

score 2 · Accepted Answer · answered Aug 09 '22 at 15:13

2

Problem is NaN in column, you can try .str accessor

issues_df['new_column'] = issues_df['fields.description.content'].str[0].str['content'].str[0].str['text']

answered Aug 09 '22 at 15:13

Ynjxsjmh

score 0 · Answer 2 · answered Aug 09 '22 at 15:16

0

That could be a good task for the rather efficient json_normalize:

df['new_column'] = pd.json_normalize(
    df['fields.description.content'], 'content'
)['text']

answered Aug 09 '22 at 15:16

Pierre D

2 Answers2