将多个值分配给一个变量

Question

I am trying to get phone numbers based on users choice

#the dict that contains the data I need
x={"contact": 
{
    "facility_message": "testing testing testing", 
    "facilitydigits":101,
    "name": "", 
    "urn": "tel:+1234567891011", 
    "uuid": "60409852-a2089-43d5-bd4c-4b89a6191793",
    "selection_anc_pnc":"C"
    }
}

#extracting data from the dict
facility_number=str(x['contact']['facilitydigits'])
group=(x['contact']['selection_anc_pnc']).upper()
facility_message=(x['contact']['facility_message'])

#checking user selection 
if group =='A':
    group="MIMBA"
elif group =='B':
    group='MAMA'    
elif group=='C':
    group='MAMA' and "MIMBA"

My df looks like so

phone       group   County  PNC/ANC Facility Name   Optedout    Facility Code
25470000040 MIMBA   Orange  PNC     Centre            FALSE      101
25470000030 MAMA    Orange  PNC     Centre            FALSE      101
25470000010 MIMBA   Orange  PNC     Centre            FALSE      101
25470000020 MAMA    Orange  PNC     Centre            FALSE      101
25470000050 MAMA    Orange  PNC     Main Centre       FALSE      112

extracting phone numbers from my df

phone_numbers =merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Opted out'] == optout)]['phone']
print(phone_numbers)

what is currently happening because of the if statement

[25470000010,25470000040]

desired output

[25470000040,25470000030,25470000010,25470000020]

Answer 1

You are incorrectly assigning the group value using group = 'MAMA' and "MIMBA" which after execution assigns the value "MIMBA" to group which is the last truty value, instead what you want to do is to assign a list of values that group can take using group = ['MAMA', "MIMBA"] . Then, you can use Series.isin method to filter the group in dataframe which belong to groups present in group variable.

Use:

if group =='A':
    group=["MIMBA"]
elif group =='B':
    group=['MAMA']    
elif group=='C':
    group=['MAMA', "MIMBA"]

m = (
    merged_df['Facility Code'].astype(str).eq(facility_number) 
    & merged_df['group'].isin(group) 
    & merged_df['Optedout'].eq(optout)
)

phone_numbers = merged_df.loc[m, "phone"]
print(phone_numbers.values)

This prints:

[25470000040 25470000030 25470000010 25470000020] # assuming variable optout is False