Extracting countries from string - python-3.x

Question

I am trying to go through a column of data frame in python 3. What I need to do is take from each row the country that it is mentioned and the number of times that country is mentioned.
i.e. if I have this row:
['[Aydemir, Deniz', ' Gunduz, Gokhan', ' Asik, Nejla] Bartin Univ, Fac Forestry, Dept Forest Ind Engn, TR-74100 Bartin, Turkey', ' [Wang, Alice] Lulea Univ Technol, Wood Technol, Skelleftea, Sweden']
it needs to output a list: ['Turkey', 'Sweden']
and if I have this row:
['[Fang, Qun', ' Cui, Hui-Wang] Zhejiang A&F Univ, Sch Engn, Linan 311300, Peoples R China', ' [Du, Guan-Ben] Southwest Forestry Univ, Kunming 650224, Yunnan, Peoples R China']
the output should be: ['China', 'China'].
I have written this code but it is not working as I want to:
from geotext import GeoText
sentence = df.iloc[0,0]
places = GeoText(sentence)
print(places.countries)
It prints only the country once and in some cases when it is USA it doesn't recognize the abbreviation. Can you help me figure out what to do?
l = [['[Aydemir, Deniz\', \' Gunduz, Gokhan\', \' Asik, Nejla] Bartin Univ, Fac Forestry, Dept Forest Ind Engn, TR-74100 Bartin, Turkey\', \' [Wang, Alice] Lulea Univ Technol, Wood Technol, Skelleftea, Sweden',1990],
['[Fang, Qun\', \' Cui, Hui-Wang] Zhejiang A&F Univ, Sch Engn, Linan 311300, Peoples R China\', \' [Du, Guan-Ben] Southwest Forestry Univ, Kunming 650224, Yunnan, Peoples R China',2005],
['[Blumentritt, Melanie\', \' Gardner, Douglas J.\', \' Shaler, Stephen M.] Univ Maine, Sch Resources, Orono, ME USA\', \' [Cole, Barbara J. W.] Univ Maine, Dept Chem, Orono, ME 04469 USA',2012]]
dataf = pd.DataFrame(l, columns = ['Authors', 'Year'])
I tried to do this code but I have the same problem, it doesn't give all the counties only one per row:
def find_country(n):
for c in pycountry.countries:
if str(c.name).lower() in n.lower():
return c.name
country1 = (dataf['Authors']
.replace(r"\bUSA\b", "United States", regex=True)
.apply(lambda x: find_country(x)))

Answer 1

USA does not seem to be detected correctly by geotext - it's worth trying to raise an issue with that package. As a workaround here, I replace USA with United States, which is correctly detected.
df = (dataf['Authors']
.replace(r"\bUSA\b", "United States", regex=True)
.apply(lambda x: geotext.GeoText(x).countries)
)
I'm not sure what you were doing before, but this will get the list of countries for each of the rows in Author, including duplicates.
0 [Turkey, Sweden]
1 [China, China]
2 [United States, United States]
Name: Authors, dtype: object
As mentioned in the comment, if you want to have an actual list of lists, just add tolist() to the end.
df.tolist()
[['Turkey', 'Sweden'], ['China', 'China'], ['United States', 'United States']]