regex

• Syntax
• Usage
  • Use re
  • Use Pandas
• Example
  • Example 1

s—
id: “regex”
aliases:
- “Usage”
- “Syntax”
tags:
- “regex”
- “python”

Syntax

regex101
regexr

Usage

Use re

re.sub(pattern,repl,str)
re.search(pattern, str)
re.findall(pattern,str)

Use Pandas

df['column_name'].str.contains('pattern')
df['column_name'].str.findall('pattern')
df['column_name'].str.replace('pattern', 'replacement')

Example

Example 1

Extracting room numbers from a ‘Description’ column in a DataFrame using regular expressions:

1. Import the re module:

   import re
   ````
   
   2.  Define a function to extract the room number from a description:
   
   ```python
   def extract_room_number(description):
       match = re.search(r'(\d+\.\d+|\d+)(?=\s+of which are bedrooms)', description)
       if match:
           return float(match.group(1))
       else:
           return None

2. Use the apply() method to apply the function to the ‘Description’ column and create a new ‘RoomNumber’ column:

df['RoomNumber'] = df['Description'].apply(extract_room_number)

This will extract the room number from the ‘Description’ column and store it in the new ‘RoomNumber’ column.