I am trying to get a list of phone numbers
here is the code
response='108'
group="MAMA"
optout='False'
phone_numbers = merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Optedout'] == optout)]['phone'].values
print(phone_numbers)
My dataframe looks like so
phone group County PNC/ANC Facility Name Optedout Facility Code
25470000000 MAMA Orange PNC Main Centre FALSE 112
25470000000 MAMA Orange PNC Main Centre FALSE 112
25470000010 MAMA Orange PNC Centre FALSE 108
25470000020 MAMA Orange PNC Centre FALSE 108
25470000000 MAMA Orange PNC Main Centre FALSE 112
This is the error I get
AttributeError: 'Series' object has no attribute 'value'
desired output
[25470000010,25470000020]
I can't seem to figure out what I am doing wrong. kindly help me fix this
2 Answers
You need to remove .values:
phone_numbers = merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Optedout'] == optout)]['phone']
@Serge Ballesta's comment is the most likely cause.
There are typos in the code that you have shared. Check whether you called value instead of values.
The following code works as expected:
import pandas as pd
data = {'phone': [25470000000, 25470000000, 25470000010, 25470000020, 25470000000], 'group': ['MAMA', 'MAMA', 'MAMA', 'MAMA', 'MAMA'], 'County': ['Orange', 'Orange', 'Orange', 'Orange', 'Orange'], 'PNC/ANC': ['PNC', 'PNC', 'PNC', 'PNC', 'PNC'], 'Facility Name': ['Main Centre', 'Main Centre', 'Centre', 'Centre', 'Main Centre'], 'Optedout': ['FALSE', 'FALSE', 'FALSE', 'FALSE', 'FALSE'], 'Facility Code': [112, 112, 108, 108, 112]}
merged_df = pd.DataFrame.from_dict(data)
facility_number = 108
group = 'MAMA'
optout = 'FALSE'
phone_numbers = merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Optedout'] == optout)]['phone'].values
print(phone_numbers)
Output:
[25470000010 25470000020]
By removing .values, the output is a dataframe:
2 25470000010
3 25470000020
Name: phone, dtype: int64
