Checking if a pandas dataframe column(that has lists as values) has one element of another list

Question

I have following dataframe called "files_to_export":

|Assignee                                                             |otherColumns...|
["Samsung", "Apple", "Apple Inc."]
["Honda Tech", "Honda Motors", "General Motors", "Huawei"]

I have another list called "Companies" that contains the companies I'm interested at having in my data, the list structure is the following:

 Companies=['Ford','General motors','Mazda',..........]

So i want to have the rows in my data that contain at least one company in my company list( by contain i mean the regex sense of containing, in other words if there is a row with "Ford global tech." then i want it included in my data because it has the word Ford.

I wrote the following code but i don't capture any data:

output = file_to_export[file_to_export['Assignee'].str.contains('|'.join(companies), case=False, na=False).count(True) > 0]

The actual result is an empty dataframe with no rows in the output dataframe

The expected result is to have a dataframe with rows of different companies in the out dataframe

Any suggestions? Thanks for your help and i wish that i was clear in my question!

Answer 1

Setup of data

files_to_export = pd.DataFrame({'Assignee':[['Samsung','Apple','Apple Inc.'],['Honda Tech','Honda Motors','General Motors']],
                                'other_col':[1,2]})

companies = ['Ford','General motors','Mazda']

# Filter df
# The pattern is a case of or where matching any of the individuals strings will work
pattern = '|'.join(companies) # 'Ford|General motors|Mazda'
# convert the column of lists to a column of comma separated strings
# then check for string containment
files_to_export[files_to_export.Assignee.apply(lambda x: ','.join(x)).str
                .contains(pattern,
                          case=False)]