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Tutorials Pandas String Operations

String Operations

4 min read Quiz at the end
Use the .str accessor for vectorised string operations: clean, extract, split, and match patterns.

String Operations

import pandas as pd
df = pd.DataFrame({'name': ['alice smith', 'BOB JONES', ' carol ']})

# All pandas string methods via .str accessor
df['name'].str.lower()
df['name'].str.upper()
df['name'].str.title()
df['name'].str.strip()
df['name'].str.len()

df['name'].str.contains('ali', case=False)
df['name'].str.startswith('alice')
df['name'].str.endswith('es')
df['name'].str.replace('alice', 'ALICE')
df['name'].str.split(' ')
df['name'].str.split(' ', expand=True)  # to columns

# Extract with regex
df['email'].str.extract(r'([a-z]+)@(.+)', expand=True)
df['name'].str.findall(r'[A-Z][a-z]+')

# Count and get part
df['name'].str.count('o')
df['name'].str.get(0)    # first character