Pandas: Contains Using Case Insensitive Search

John D K -

To perform case-insensitive string matching in Pandas, you can use the .str accessor along with regular expressions and the case=False parameter

(1) parameter case of str.contains

df1['col'].str.contains("MaX", na=False, case=False)

(2) Margin only on columns

df.query("City.str.lower() == 'new york'")

(3) Margin only on columns

df[df['col'].str.strip().str.match('MaX'.strip(), case=False)]

1. Check if a string contains a word (case-insensitive)

import pandas as pd

df = pd.DataFrame({
    'name': ['maximum', 'Maxxy', 'MAXa', 'Mini', 'MInimum', 'MaX']
})

# Filter rows where 'name' contains 'bob', ignoring case
filtered = df[df['name'].str.contains('max', case=False)]
print(filtered)

Output:

      name
0  maximum
1    Maxxy
2     MAXa
5      MaX

2. Exact match ignoring case

For exact matches (not substrings), normalize strings using .str.lower() or .str.upper():

df[df['name'].str.lower() == 'max']

Result:

  name
5  MaX

3. Case-insensitive query

We can perform case-insensitive search with Pandas query like:

df.query("name.str.lower() == 'max'")

Result:

  name
5  MaX

Notes:

  • case=False works only with .str.contains() and .str.match() using regex.
  • For non-regex comparisons, normalize both sides with .str.lower() or .str.upper().

Summary

To make your string filters case-insensitive in Pandas:

  • Use .str.contains(..., case=False) for substring matching.
  • Use .str.lower() or .str.upper() for exact value comparisons.

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