How to Fix AttributeError: ‘Series’ object has no attribute ‘split’

AttributeError: ‘Series’ object has no attribute ‘split’ error typically occurs when you use the split() method directly on a Pandas Series object.

Reproduce the error

Visual representation of 'Series' object has no attribute 'split' error

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

print(srs)

result = srs.split(',')

print(result)

Output

AttributeError: 'Series' object has no attribute 'split'

How to fix the error

Here are six ways to fix the error.

Solution 1: Using str.split() instead of split() method

To fix the AttributeError, use the str.split() method, available for Series objects, instead of using the split() method directly on Series object.

Visual representation of str.split() method

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

result = srs.str.split(',')

print(result)

Output

dtype: object
0  [John]
1  [Wick]
2  [Harry]
3  [Potter]
dtype: object

Solution 2: Using astype()

Another effective solution is to convert the Series object to a string using the astype() function and then use the string method split().

Visual representation of using astype()

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

# Convert the Series object to a string
s_string = srs.astype(str).str.cat(sep=',')

# Use the split() method on the string
result_string_split = s_string.split(',')

print(result_string_split)

Output

['John', 'Wick', 'Harry', 'Potter']

Solution 3: Converting series object to a string before using the split()

Visual representation of Converting series object to a string before using the split()

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

# Convert the Series object to a string
s = srs.str.cat(sep='|')

# Use the split() method on the string
result = s.split('|')

print(result)

Output

['John', 'Wick', 'Harry', 'Potter']

Solution 4: Converting the series object to a list before using the split()

Visual representation of Converting the series object to a list before using the split()

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

# Convert the Series object to a list
s_list = srs.tolist()

# Use the split() method on each element of the list
result_list_split = [item.split(',') for item in s_list]

print(result_list_split)

Output

[['John'], ['Wick'], ['Harry'], ['Potter']]

Solution 5: Using the apply() method with a lambda function

Visual representation of Using the apply() method with a lambda function

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

result = srs.apply(lambda x: x.split(','))

print(result)

Output

0  [John]
1  [Wick]
2  [Harry]
3  [Potter]
dtype: object

Solution 6: Using explode()

Visual representation of Using explode() method

import pandas as pd

# Create a sample pandas Series object
srs = pd.Series(['John', "Wick", "Harry", "Potter"])

# Use the str.split() method followed by explode()
result = srs.str.split(',').explode()

# Reset the index
result = result.reset_index(drop=True)

print(result)

Output

0  John
1  Wick
2  Harry
3  Potter
dtype: object

That’s it.

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