Getting AttributeError: 'list' object has no attribute 'split' when using list comprehension

Question

I am trying to extract countries from the Locations column in a dataframe , each cell could have more than one Locations split by '|'. Currently I am doing this,

conditions = [
          (len(org_df['Locations'].str.lower().str.split('|')) == 1),
          (len(org_df['Locations'].str.lower().str.split('|')) > 1)]

values = [
          list(org_df['Locations'].str.lower().str.split(','))[-1],
          [x.split(',')[-1] for x in list(org_df['Locations'].str.lower().str.split('|'))]
]

org_df['Country'] = np.select(conditions,values)

This gives me AttributeError: 'list' object has no attribute 'split'

, if I do the same thing with a particular cell in the dataframe like this,

bruh = [x.split(',')[-1] for x in list(org_df.loc[97,'Locations'].split('|'))]
print(bruh)

I get the desired output, [' India', ' India']

I am not able to understand how to resolve this, any help would be appreciated.

Update

I was trying to make a list of a list to store the values of one or more countries. And as @meh pointed out I did land up with more rows than my dataframe. For now I have done this

for x in org_df['Locations'].str.lower().str.split('|'):
            loc_list = []
            for y in x :
              word = y.split(',')[-1].lower()
              if(word.strip() in loc_list):
                continue
              else:
                loc_list.append(word.strip())
            loc_str= ','.join(loc_list)

            country_list.append(loc_str)

Is there any way that I can use list comprehension to improve my code ?

Update Two Here is the output @Onur requested.

[{'Acronym': nan,
  'Age': '35 Years to 64 Years \xa0 (Adult)',
  'Completion Date': nan,
  'Conditions': 'Breast Cancer|Cervical Cancer',
  'Country': 'india',
  'Enrollment': 151538.0,
  'First Posted': 'March 10, 2008',
  'Funded Bys': 'Other|NIH',
  'Gender': 'Female',
  'Interventions': 'Other: active surveillance|Other: educational intervention|Procedure: examination|Procedure: long-term screening',
  'Last Update Posted': 'August 26, 2013',
  'Locations': 'Tata Memorial Hospital, Mumbai, India',
  'NCT Number': 'NCT00632047',
  'Other IDs': 'CDR0000586791|TATA-1900215717A1',
  'Outcome Measures': 'Effectiveness of well planned health education programs and low-cost screening methods (e.g., clinical breast exam and visual inspection of the cervix) in reducing the incidence of and mortality due to breast and cervical cancer',
  'Phases': 'Phase 2',
  'Primary Completion Date': 'December 2015',
  'Rank': 1,
  'Results First Posted': nan,
  'Sponsor/Collaborators': 'Tata Memorial Hospital|National Cancer Institute (NCI)',
  'Start Date': 'May 1998',
  'Status': 'Unknown status',
  'Study Designs': 'Allocation: Randomized|Primary Purpose: Screening',
  'Study Documents': nan,
  'Study Results': 'No Results Available',
  'Study Type': 'Interventional',
  'Title': 'Early Detection of Breast Cancer and Cervical Cancer in Women in India',
  'URL': 'https://ClinicalTrials.gov/show/NCT00632047'}]

Answer 1

You have to recalcuate the offsets for the new resolution. Simply calculate a scale factor by which you can multiply the offsets and redraw the canvas. Pseudocode:

offset = (76.2, 75.2)
scale = 450/300 // 1.5
newOffset = offset * scale //(114.3, 112,5)