Identify value across multiple columns in a dataframe that contain string from a list in python

Question

I have a dataframe with multiple columns containing phrases. What I would like to do is

1. identify the column (per row observation) that contains a string that exists within a pre-made list of words.
2. With this information, create a new variable in this dataframe that contains the value in the column that matched with the list. (In this example, "lst" is my list of words)

For example: Starting Dataframe:

And I would like to end up with this:

New_var is the new variable, and it selected the response in col1 of observation 1 because the "apple" in apple sauce matched with the "apple" in the list. Big oranges would appear for Observation 2 because it matched with "oranges" from the list.

I have tried doing this with list comprehension from this link: List Comprehension, but remain unsuccessful. I wish to do this in python. Any suggestions? I am relatively new to this programming language.

Thank you very much. If I have posted inappropriately or the answer exists somewhere I have not found it, I appreciate any guidance in the right direction.

Answer 1

Let's take the list of words and data frame as you have mentioned

lst = ['a','m','n','o','p']

df = pd.DataFrame({'Observation': [1], 'col1': ['ab'], 'col2': ['dc'], 'col3': ['ef'], 'col4': ['yz']})
df
   Observation  col1    col2    col3    col4
  0    1         ab      dc      ef      yz

Check whether values of data frame match with values in the list

df['New_var'] = [x for x in df.values[0] if any(b for b in lst if b in str(x))]
df
   Observation  col1    col2    col3    col4    New_var
  0        1     ab      dc      ef      yz       ab