I would need to manage a data frame by adding more columns. 
My sample of data headers is

```
`Date` `Sentence` 
28 Jan      who.c   
30 Jan      house.a
02 Feb      eurolet.it

```

I would need to add another column, `Tp`, that for each link assigns a value: 

* if a sentence ends with `a` then assign `apartment`; if it ends with `b` then assign `bungalow` and so on as shown in `original`;
* if a sentence ends with `UK` then assign `United Kingdom`; if it ends with `IT` then assign `Italy`, and so on. Values are from `country`. 
I would expect something like this: 

Date Sentence Tp
28 Jan who.c church
30 Jan house.a apartment
02 Feb eurolet.it. Italy

I wrote the following: 

```
conditions = [df['Sentence'].str.endswith(original), df['Sentence'].str.endswith(country)]
choices = [original, country]
# df['Tp'] = df.apply(lambda row: urlparse(row['Sentence']).netloc, axis = 1)
df['Tp'] = np.select(conditions, choices, default ='Unknown')
print(df)

```

where 

```
original= [('a', 'apartment'), ('b', 'bungalow'), ('c', 'church')]

```

and 

```
country = [('UK', 'United Kingdom'), ('IT', 'Italy'), ('DE', 'Germany'), ('H', 'Holland'), ..., ('F', 'France'), ('S', 'Spain')]

```

`country` contains more than 50 elements.

Could you tell me how to fix it? The column should be added in the data frame, then to a csv file. 

Thanks

Update: 

```
                      Sentences  \
    0                                      
    1                       who.c  
    2                  citta.me.it   
    3                    office.of
    4                   eurolet.eu   
    ..                               ...   
    995                    uilpa.ie   
    996                      fog.de

Original and country are from

list_country=np.array(country).tolist()
list_country_name=np.array(country_name).tolist()
flat_name_country = [item for sublist in list_country for item in sublist]
flat_country_name = [item for sublist in list_country_name for item in sublist] 

zip_domains=list(zip(flat_name_country, flat_country_name))

```