I need to match contacts in a database by how they were contacted by a unique ID number. I've created a very small mock dataframe below to help with a suggestion:
data = [
["email", "[email protected]", 1],
["phone", "555-555-1111", 1],
["slack", "secondpersonslack", 2],
["phone", "111-111-1111", 3],
]
data2 = [
[1, "[email protected]", "555-555-1111", "slack1"],
[2, "[email protected]", "555-555-2222", "secondpersonslack"],
[3, "[email protected]", "111-111-1111", "tomasslack"],
]
stackdata = pd.DataFrame(
data, columns=["contact method", "from:", "column that I dont know how to make"]
)
stackdata2 = pd.DataFrame(data2, columns=["id", "email", "phone", "slack"])
In my real dataset, what I want to fill out is the column 'column that I dont know how to make'.
So, take first contact method in stackdata in row one, which was an email address. This email lines up with ID 1 in stack2, so it would populate the column in the stackdata1 with "1".
I was thinking of some of kind of for loop like:
for i in stackdata['column that I dont know how to make']:
if i matches one of the columns in any row, then populate column with id of that row
Thanks for any help and let me know if i can make this question easier to answer!
Try this:
for i in range(len(stackdata)):
stackdata['contact_id'][i] = str(stackdata2[(stackdata2['email'] == stackdata['from:'][i]) | (stackdata2['phone'] == stackdata['from:'][i]) | (stackdata2['slack'] == stackdata['from:'][i])]['id'].values).strip('[]')
'contact_id' is the column 'column that I dont know how to make'