Python Dataframe: Fill in Row as 1 or 0 Based on If Column Name is Contained in String Row of Another Column in Dataframe

Question

Let's say hypothetically I have a dataframe with one column called "Col_Strings". This column has 30k rows. I am only showing the first three rows in my table

Next I am going to add a bunch of additional columns to my dataframe.

I want to use logic that says: If my column name is contained in the row of "Col_Strings" then I want the value to say 1 ... otherwise 0.

Below is a sample table (first row is the column names):

Col_Strings       2C    GAD D2  6F  ABCDE
2C 1B D2 6F ABC    1    0   1   1   0
Act Dog House GAD  0    1   0   0   0
D2 6F Ant          0    0   1   1   0

Based on someone's else help I can do the following by creating a dataframe from scratch. But my question is how do I employ the above python logic when I already have a dataframe and need to reference the "Col_Strings" to determine 1 or 0?

Answer 1

map a function on the database column Col_Strings , checking if the word is contained in each element. Assign the results to the column

df['Act'] = df['Col_Strings'].map(lambda x: int('Act' in x.split())

If you have a list of words to create columns for, then execute the above logic in a loop:

for word in ['Act', 'Now', 'Buy', 'MORE']:
    df[word] = df['Col_Strings'].map(lambda x: int(word in x.split())