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I don't think read.bib works remotely so you could download the file first.

You can use FunctionTransformer in scikit learn for this and just choose to which columns you want to apply the transformation. As a second step, you can just add these transformed columns to your original dataframe.

On a dummy example, it would look like this:

Note: the following will not work correctly if any field contains a comma character (,).

Try this bash script (named process for the terminal session that follows):

Below for BigQuery Standard SQL

Update: I found that what I was missing was that I didn't check where the code run.
So be sure to do so and eventually move the input files (if you have any) in the directory where python is executing, otherwise the script can't find them and elaborate them.

You can use

The question lacks minimum details & code required for help. However I am trying to give you a code that would pickup person names & email addresses from one table in a document containing the code. the table should have 3 columns, 1st col contain Name of the person, 2nd col should contain Email address with 3rd column blank for remarks from code. See image

On running the code you would be prompted to select the word files that would be replaced by the email address. On trial use only copy files and may try only a handful of files at a time (if file sizes are large). It is assumed that files will contain Name and word “E-mail:” (if "E-mail:" word is not in the file try to modify the code as commented)

Code:

The former is a dictionary, the latter are keyword arguments to a function. I don't see how they compare.

It's like asking why you have to use / for floating point division but // for integer division. You're asking Python to do two different things, so you need two different syntax.

Note that you can call foo(bar=baz) also as foo(**{bar: baz}), which supplies a dictionary as a set of keyword arguments to foo.

Note also that : already has meaning within a function signature -- it's a function annotation.

You can iterate over each row, checking if the row starts with that id.

Complete Code:

It's not working because entries in file still have the trailing newline at the end of each one. You will need to trim, which you can do with ease: