AttributeError: ‘Series’ object has no attribute ‘split’ error in sending emails

Let’s try str.split and str.join:

import pandas as pd

df = pd.DataFrame({'SENDFROM': {0: '[email protected]', 1: '[email protected]'},
                   'Test': {0: '[email protected];[email protected];[email protected]',
                            1: '[email protected];[email protected];[email protected]'}})

# Use str.split and str.join and astype
df['Test'] = df['Test'].str.split(';').str.join(',')

print(df.to_string())

Output:

       SENDFROM                                        Test
0  [email protected]  [email protected],[email protected],[email protected]
1    [email protected]       [email protected],[email protected],[email protected]

The email_to object is apparently a Series, not a string, so it does not have a split() method. The Series is already a sequence-like object, so you don’t need to split it anyway. Do a type(email_to) to confirm this.

You can’t use split to a Series Object.
From what I understood you want to do something like this:

import pandas as pd

test  = pd.Series(['[email protected];[email protected];[email protected]'])

print(test)

>> 0    [email protected];[email protected];[email protected]
>> dtype: object

# You can see that the only and first row of Series s is a string of all 
# emails you want to split by ';'. Here you can do:

# Apply split to string in first row of Series: returns a list
print(test[0].split(';'))

>> ['[email protected]', '[email protected]', '[email protected]']

# I believe you can solve your problem with this list of emails. 
# However you should code a loop to iterate for the remaing rows of initial Series. 
# ----------------------------------------------------------------------------------
# Furthermore, you can explode your pandas Series. 
# This will return you a DataFrame (ser), from which you can extract the info you want.

t = pd.concat([pd.Series(test[0], test[0].split(';'))              
                    for _, row in test.iteritems()]).reset_index()

# Remove weird column
t.drop(labels=[0], axis=1, inplace=True)

# Convert DataFrame back to Series
t = t.squeeze()

# The info you probably want:
print(t)

>> 0       [email protected]
>> 1      [email protected]
>> 2    [email protected]
>> Name: index, dtype: object

Shout out to: Split (explode) pandas dataframe string entry to separate rows

You can use pandas.Series.replace() to replace ; with ,

df['Test'] = df['Test'].replace(';', ',')